Author: "Medlyn BE" / Topic: ecology - Searchworks@Jio Institute Digital Library Search Results

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1. A constraint on historic growth in global photosynthesis due to rising CO2

Author: Keenan, TF, Luo, X, Stocker, BD, De Kauwe, MG, Medlyn, BE, Prentice, IC, Smith, NG, Terrer, C, Wang, H, Zhang, Y, and Zhou, S
Subjects: Plant Biology, Biological Sciences, Ecology, Climate Action, Atmospheric Sciences, Physical Geography and Environmental Geoscience, Environmental Science and Management
Abstract: Theory predicts that rising CO2 increases global photosynthesis, a process known as CO2 fertilization, and that this is responsible for much of the current terrestrial carbon sink. The estimated magnitude of the historic CO2 fertilization, however, differs by an order of magnitude between long-term proxies, remote sensing-based estimates and terrestrial biosphere models. Here we constrain the likely historic effect of CO2 on global photosynthesis by combining terrestrial biosphere models, ecological optimality theory, remote sensing approaches and an emergent constraint based on global carbon budget estimates. Our analysis suggests that CO2 fertilization increased global annual terrestrial photosynthesis by 13.5 ± 3.5% or 15.9 ± 2.9 PgC (mean ± s.d.) between 1981 and 2020. Our results help resolve conflicting estimates of the historic sensitivity of global terrestrial photosynthesis to CO2 and highlight the large impact anthropogenic emissions have had on ecosystems worldwide.
Published: 2023

2. Environmental correlates of the forest carbon distribution in the Central Himalayas

Author: Shiva Khanal, Rachael H. Nolan, Belinda E. Medlyn, and Matthias M. Boer
Subjects: aboveground carbon, disturbance, environmental drivers, forest, Himalaya, soil organic carbon, Ecology, QH540-549.5
Abstract: Abstract Understanding the biophysical limitations on forest carbon across diverse ecological regions is crucial for accurately assessing and managing forest carbon stocks. This study investigates the role of climate and disturbance on the spatial variation of two key forest carbon pools: aboveground carbon (AGC) and soil organic carbon (SOC). Using plot‐level carbon pool estimates from Nepal's national forest inventory and structural equation modelling, we explore the relationship of forest carbon stocks to broad‐scale climatic water and energy availability and fine‐scale terrain and disturbance. The forest AGC and SOC models explained 25% and 59% of the observed spatial variation in forest AGC and SOC, respectively. Among the evaluated variables, disturbance exhibited the strongest negative correlation with AGC, while the availability of climatic energy demonstrated the strongest negative correlation with SOC. Disturbances such as selective logging and firewood collection result in immediate forest carbon loss, while soil carbon changes take longer to respond. The lower decomposition rates in the high‐elevation region, due to lower temperatures, preserve organic matter and contribute to the high SOC stocks observed there. These results highlight the critical role of climate and disturbance regimes in shaping landscape patterns of forest carbon stocks. Understanding the underlying drivers of these patterns is crucial for forest carbon management and conservation across diverse ecological zones including the Central Himalayas.
Published: 2024
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3. A reporting format for leaf-level gas exchange data and metadata

Author: Ely, Kim S, Rogers, Alistair, Agarwal, Deborah A, Ainsworth, Elizabeth A, Albert, Loren P, Ali, Ashehad, Anderson, Jeremiah, Aspinwall, Michael J, Bellasio, Chandra, Bernacchi, Carl, Bonnage, Steve, Buckley, Thomas N, Bunce, James, Burnett, Angela C, Busch, Florian A, Cavanagh, Amanda, Cernusak, Lucas A, Crystal-Ornelas, Robert, Damerow, Joan, Davidson, Kenneth J, De Kauwe, Martin G, Dietze, Michael C, Domingues, Tomas F, Dusenge, Mirindi Eric, Ellsworth, David S, Evans, John R, Gauthier, Paul PG, Gimenez, Bruno O, Gordon, Elizabeth P, Gough, Christopher M, Halbritter, Aud H, Hanson, David T, Heskel, Mary, Hogan, J Aaron, Hupp, Jason R, Jardine, Kolby, Kattge, Jens, Keenan, Trevor, Kromdijk, Johannes, Kumarathunge, Dushan P, Lamour, Julien, Leakey, Andrew DB, LeBauer, David S, Li, Qianyu, Lundgren, Marjorie R, McDowell, Nate, Meacham-Hensold, Katherine, Medlyn, Belinda E, Moore, David JP, Negrón-Juárez, Robinson, Niinemets, Ülo, Osborne, Colin P, Pivovaroff, Alexandria L, Poorter, Hendrik, Reed, Sasha C, Ryu, Youngryel, Sanz-Saez, Alvaro, Schmiege, Stephanie C, Serbin, Shawn P, Sharkey, Thomas D, Slot, Martijn, Smith, Nicholas G, Sonawane, Balasaheb V, South, Paul F, Souza, Daisy C, Stinziano, Joseph Ronald, Stuart-Haëntjens, Ellen, Taylor, Samuel H, Tejera, Mauricio D, Uddling, Johan, Vandvik, Vigdis, Varadharajan, Charuleka, Walker, Anthony P, Walker, Berkley J, Warren, Jeffrey M, Way, Danielle A, Wolfe, Brett T, Wu, Jin, Wullschleger, Stan D, Xu, Chonggang, Yan, Zhengbing, and Yang, Dedi
Subjects: Biological Sciences, Ecology, Data Science, Photosynthesis, Carbon dioxide, Irradiance, Data reporting format, Metadata, Data standard, Information and Computing Sciences, Biological sciences, Information and computing sciences
Abstract: Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system.
Published: 2021

4. A reporting format for leaf-level gas exchange data and metadata

Author: Ely, KS, Rogers, A, Agarwal, DA, Ainsworth, EA, Albert, LP, Ali, A, Anderson, J, Aspinwall, MJ, Bellasio, C, Bernacchi, C, Bonnage, S, Buckley, TN, Bunce, J, Burnett, AC, Busch, FA, Cavanagh, A, Cernusak, LA, Crystal-Ornelas, R, Damerow, J, Davidson, KJ, De Kauwe, MG, Dietze, MC, Domingues, TF, Dusenge, ME, Ellsworth, DS, Evans, JR, Gauthier, PPG, Gimenez, BO, Gordon, EP, Gough, CM, Halbritter, AH, Hanson, DT, Heskel, M, Hogan, JA, Hupp, JR, Jardine, K, Kattge, J, Keenan, T, Kromdijk, J, Kumarathunge, DP, Lamour, J, Leakey, ADB, LeBauer, DS, Li, Q, Lundgren, MR, McDowell, N, Meacham-Hensold, K, Medlyn, BE, Moore, DJP, Negrón-Juárez, R, Niinemets, Ü, Osborne, CP, Pivovaroff, AL, Poorter, H, Reed, SC, Ryu, Y, Sanz-Saez, A, Schmiege, SC, Serbin, SP, Sharkey, TD, Slot, M, Smith, NG, Sonawane, BV, South, PF, Souza, DC, Stinziano, JR, Stuart-Haëntjens, E, Taylor, SH, Tejera, MD, Uddling, J, Vandvik, V, Varadharajan, C, Walker, AP, Walker, BJ, Warren, JM, Way, DA, Wolfe, BT, Wu, J, Wullschleger, SD, Xu, C, Yan, Z, and Yang, D
Subjects: Photosynthesis, Carbon dioxide, Irradiance, Data reporting format, Metadata, Data standard, Ecology, Biological Sciences, Information and Computing Sciences
Abstract: Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system.
Published: 2021

5. Observed and modelled historical trends in the water‐use efficiency of plants and ecosystems

Author: Lavergne, Aliénor, Graven, Heather, De Kauwe, Martin G, Keenan, Trevor F, Medlyn, Belinda E, and Prentice, Iain Colin
Subjects: Plant Biology, Biological Sciences, Ecology, Clean Water and Sanitation, Carbon Dioxide, Ecosystem, Photosynthesis, Plant Leaves, Plants, Water, carbon isotopic discrimination, eddy-covariance flux, spatial scales, stomatal conductance, trends in water-use efficiency, vegetation modelling, Environmental Sciences, Biological sciences, Earth sciences, Environmental sciences
Abstract: Plant water-use efficiency (WUE, the carbon gained through photosynthesis per unit of water lost through transpiration) is a tracer of the plant physiological controls on the exchange of water and carbon dioxide between terrestrial ecosystems and the atmosphere. At the leaf level, rising CO2 concentrations tend to increase carbon uptake (in the absence of other limitations) and to reduce stomatal conductance, both effects leading to an increase in leaf WUE. At the ecosystem level, indirect effects (e.g. increased leaf area index, soil water savings) may amplify or dampen the direct effect of CO2 . Thus, the extent to which changes in leaf WUE translate to changes at the ecosystem scale remains unclear. The differences in the magnitude of increase in leaf versus ecosystem WUE as reported by several studies are much larger than would be expected with current understanding of tree physiology and scaling, indicating unresolved issues. Moreover, current vegetation models produce inconsistent and often unrealistic magnitudes and patterns of variability in leaf and ecosystem WUE, calling for a better assessment of the underlying approaches. Here, we review the causes of variations in observed and modelled historical trends in WUE over the continuum of scales from leaf to ecosystem, including methodological issues, with the aim of elucidating the reasons for discrepancies observed within and across spatial scales. We emphasize that even though physiological responses to changing environmental drivers should be interpreted differently depending on the observational scale, there are large uncertainties in each data set which are often underestimated. Assumptions made by the vegetation models about the main processes influencing WUE strongly impact the modelled historical trends. We provide recommendations for improving long-term observation-based estimates of WUE that will better inform the representation of WUE in vegetation models.
Published: 2019

6. Decadal biomass increment in early secondary succession woody ecosystems is increased by CO2 enrichment

Author: Walker, Anthony P, De Kauwe, Martin G, Medlyn, Belinda E, Zaehle, Sönke, Iversen, Colleen M, Asao, Shinichi, Guenet, Bertrand, Harper, Anna, Hickler, Thomas, Hungate, Bruce A, Jain, Atul K, Luo, Yiqi, Lu, Xingjie, Lu, Meng, Luus, Kristina, Megonigal, J Patrick, Oren, Ram, Ryan, Edmund, Shu, Shijie, Talhelm, Alan, Wang, Ying-Ping, Warren, Jeffrey M, Werner, Christian, Xia, Jianyang, Yang, Bai, Zak, Donald R, and Norby, Richard J
Subjects: Plant Biology, Biological Sciences, Ecology, Biomass, Carbon Dioxide, Climate, Ecosystem, Photosynthesis, Trees, Wood
Abstract: Increasing atmospheric CO2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO2-enrichment experiments in woody ecosystems that measured total NPP and biomass. CO2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m-2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO2 response of NPP (0.16 ± 0.03 kg C m-2 y-1) and the CO2-independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). An ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO2-independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO2 responses.
Published: 2019

7. Thirty-eight years of CO2 fertilization has outpaced growing aridity to drive greening of Australian woody ecosystems

Author: S. W. Rifai, M. G. De Kauwe, A. M. Ukkola, L. A. Cernusak, P. Meir, B. E. Medlyn, and A. J. Pitman
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Climate change is projected to increase the imbalance between the supply (precipitation) and atmospheric demand for water (i.e., increased potential evapotranspiration), stressing plants in water-limited environments. Plants may be able to offset increasing aridity because rising CO2 increases water use efficiency. CO2 fertilization has also been cited as one of the drivers of the widespread “greening” phenomenon. However, attributing the size of this CO2 fertilization effect is complicated, due in part to a lack of long-term vegetation monitoring and interannual- to decadal-scale climate variability. In this study we asked the question of how much CO2 has contributed towards greening. We focused our analysis on a broad aridity gradient spanning eastern Australia's woody ecosystems. Next we analyzed 38 years of satellite remote sensing estimates of vegetation greenness (normalized difference vegetation index, NDVI) to examine the role of CO2 in ameliorating climate change impacts. Multiple statistical techniques were applied to separate the CO2-attributable effects on greening from the changes in water supply and atmospheric aridity. Widespread vegetation greening occurred despite a warming climate, increases in vapor pressure deficit, and repeated record-breaking droughts and heat waves. Between 1982–2019 we found that NDVI increased (median 11.3 %) across 90.5 % of the woody regions. After masking disturbance effects (e.g., fire), we statistically estimated an 11.7 % increase in NDVI attributable to CO2, broadly consistent with a hypothesized theoretical expectation of an 8.6 % increase in water use efficiency due to rising CO2. In contrast to reports of a weakening CO2 fertilization effect, we found no consistent temporal change in the CO2 effect. We conclude rising CO2 has mitigated the effects of increasing aridity, repeated record-breaking droughts, and record-breaking heat waves in eastern Australia. However, we were unable to determine whether trees or grasses were the primary beneficiary of the CO2-induced change in water use efficiency, which has implications for projecting future ecosystem resilience. A more complete understanding of how CO2-induced changes in water use efficiency affect trees and non-tree vegetation is needed.
Published: 2022
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8. Global‐scale environmental control of plant photosynthetic capacity

Author: Ali, Ashehad A, Xu, Chonggang, Rogers, Alistair, McDowell, Nathan G, Medlyn, Belinda E, Fisher, Rosie A, Wullschleger, Stan D, Reich, Peter B, Vrugt, Jasper A, Bauerle, William L, Santiago, Louis S, and Wilson, Cathy J
Subjects: Plant Biology, Biological Sciences, Ecology, Conservation of Natural Resources, Environmental Monitoring, Models, Biological, Nitrogen, Photosynthesis, Plant Leaves, Plants, Uncertainty, climate change, climate variables, Earth System Models, leaf nitrogen content, photosynthetic capacity, plant traits, Environmental Sciences, Agricultural and Veterinary Sciences, Agricultural, veterinary and food sciences, Biological sciences, Environmental sciences
Abstract: Photosynthetic capacity, determined by light harvesting and carboxylation reactions, is a key plant trait that determines the rate of photosynthesis; however, in Earth System Models (ESMs) at a reference temperature, it is either a fixed value for a given plant functional type or derived from a linear function of leaf nitrogen content. In this study, we conducted a comprehensive analysis that considered correlations of environmental factors with photosynthetic capacity as determined by maximum carboxylation (V(cm)) rate scaled to 25 degrees C (i.e., V(c),25; μmol CO2 x m(-2)x s(-1)) and maximum electron transport rate (J(max)) scaled to 25 degrees C (i.e., J25; μmol electron x m(-2) x s(-1)) at the global scale. Our results showed that the percentage of variation in observed V(c),25 and J25 explained jointly by the environmental factors (i.e., day length, radiation, temperature, and humidity) were 2-2.5 times and 6-9 times of that explained by area-based leaf nitrogen content, respectively. Environmental factors influenced photosynthetic capacity mainly through photosynthetic nitrogen use efficiency, rather than through leaf nitrogen content. The combination of leaf nitrogen content and environmental factors was able to explain -56% and -66% of the variation in V(c),25 and J25 at the global scale, respectively. Our analyses suggest that model projections of plant photosynthetic capacity and hence land-atmosphere exchange under changing climatic conditions could be substantially improved if environmental factors are incorporated into algorithms used to parameterize photosynthetic capacity in ESMs.
Published: 2015

9. Low sensitivity of gross primary production to elevated CO2 in a mature eucalypt woodland

Author: J. Yang, B. E. Medlyn, M. G. De Kauwe, R. A. Duursma, M. Jiang, D. Kumarathunge, K. Y. Crous, T. E. Gimeno, A. Wujeska-Klause, and D. S. Ellsworth
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: The response of mature forest ecosystems to a rising atmospheric carbon dioxide concentration (Ca) is a major uncertainty in projecting the future trajectory of the Earth's climate. Although leaf-level net photosynthesis is typically stimulated by exposure to elevated Ca (eCa), it is unclear how this stimulation translates into carbon cycle responses at the ecosystem scale. Here we estimate a key component of the carbon cycle, the gross primary productivity (GPP), of a mature native eucalypt forest exposed to free-air CO2 enrichment (the EucFACE experiment). In this experiment, light-saturated leaf photosynthesis increased by 19 % in response to a 38 % increase in Ca. We used the process-based forest canopy model, MAESPA, to upscale these leaf-level measurements of photosynthesis with canopy structure to estimate the GPP and its response to eCa. We assessed the direct impact of eCa, as well as the indirect effect of photosynthetic acclimation to eCa and variability among treatment plots using different model scenarios. At the canopy scale, MAESPA estimated a GPP of 1574 g C m−2 yr−1 under ambient conditions across 4 years and a direct increase in the GPP of +11 % in response to eCa. The smaller canopy-scale response simulated by the model, as compared with the leaf-level response, could be attributed to the prevalence of RuBP regeneration limitation of leaf photosynthesis within the canopy. Photosynthetic acclimation reduced this estimated response to 10 %. After taking the baseline variability in the leaf area index across plots in account, we estimated a field GPP response to eCa of 6 % with a 95 % confidence interval (−2 %, 14 %). These findings highlight that the GPP response of mature forests to eCa is likely to be considerably lower than the response of light-saturated leaf photosynthesis. Our results provide an important context for interpreting the eCa responses of other components of the ecosystem carbon cycle.
Published: 2020
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10. Examining the evidence for decoupling between photosynthesis and transpiration during heat extremes

Author: M. G. De Kauwe, B. E. Medlyn, A. J. Pitman, J. E. Drake, A. Ukkola, A. Griebel, E. Pendall, S. Prober, and M. Roderick
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Recent experimental evidence suggests that during heat extremes, wooded ecosystems may decouple photosynthesis and transpiration, reducing photosynthesis to near zero but increasing transpiration into the boundary layer. This feedback may act to dampen, rather than amplify, heat extremes in wooded ecosystems. We examined eddy covariance databases (OzFlux and FLUXNET2015) to identify whether there was field-based evidence to support these experimental findings. We focused on two types of heat extremes: (i) the 3 days leading up to a temperature extreme, defined as including a daily maximum temperature >37 ∘C (similar to the widely used TXx metric), and (ii) heatwaves, defined as 3 or more consecutive days above 35 ∘C. When focusing on (i), we found some evidence of reduced photosynthesis and sustained or increased latent heat fluxes at seven Australian evergreen wooded flux sites. However, when considering the role of vapour pressure deficit and focusing on (ii), we were unable to conclusively disentangle the decoupling between photosynthesis and latent heat flux from the effect of increasing the vapour pressure deficit. Outside of Australia, the Tier-1 FLUXNET2015 database provided limited scope to tackle this issue as it does not sample sufficient high temperature events with which to probe the physiological response of trees to extreme heat. Thus, further work is required to determine whether this photosynthetic decoupling occurs widely, ideally by matching experimental species with those found at eddy covariance tower sites. Such measurements would allow this decoupling mechanism to be probed experimentally and at the ecosystem scale. Transpiration during heatwaves remains a key issue to resolve, as no land surface model includes a decoupling mechanism, and any potential dampening of the land–atmosphere amplification is thus not included in climate model projections.
Published: 2019
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11. A unifying conceptual model for the environmental responses of isoprene emissions from plants

Author: Morfopoulos, Catherine, Prentice, Iain C, Keenan, Trevor F, Friedlingstein, Pierre, Medlyn, Belinda E, Peñuelas, Josep, and Possell, Malcolm
Subjects: Plant Biology, Biological Sciences, Butadienes, Carbon Dioxide, Electrons, Environment, Hemiterpenes, Light, Models, Biological, NADP, Pentanes, Photosynthesis, Plants, Temperature, Isoprene, modelling, electron transport, photosynthesis, temperature, carbon dioxide, isoprene emission, volatile organic compounds, Ecology, Forestry Sciences, Plant Biology & Botany, Plant biology
Abstract: Background and aimsIsoprene is the most important volatile organic compound emitted by land plants in terms of abundance and environmental effects. Controls on isoprene emission rates include light, temperature, water supply and CO2 concentration. A need to quantify these controls has long been recognized. There are already models that give realistic results, but they are complex, highly empirical and require separate responses to different drivers. This study sets out to find a simpler, unifying principle.MethodsA simple model is presented based on the idea of balancing demands for reducing power (derived from photosynthetic electron transport) in primary metabolism versus the secondary pathway that leads to the synthesis of isoprene. This model's ability to account for key features in a variety of experimental data sets is assessed.Key resultsThe model simultaneously predicts the fundamental responses observed in short-term experiments, namely: (1) the decoupling between carbon assimilation and isoprene emission; (2) a continued increase in isoprene emission with photosynthetically active radiation (PAR) at high PAR, after carbon assimilation has saturated; (3) a maximum of isoprene emission at low internal CO2 concentration (ci) and an asymptotic decline thereafter with increasing ci; (4) maintenance of high isoprene emissions when carbon assimilation is restricted by drought; and (5) a temperature optimum higher than that of photosynthesis, but lower than that of isoprene synthase activity.ConclusionsA simple model was used to test the hypothesis that reducing power available to the synthesis pathway for isoprene varies according to the extent to which the needs of carbon assimilation are satisfied. Despite its simplicity the model explains much in terms of the observed response of isoprene to external drivers as well as the observed decoupling between carbon assimilation and isoprene emission. The concept has the potential to improve global-scale modelling of vegetation isoprene emission.
Published: 2013

12. Inferring the effects of sink strength on plant carbon balance processes from experimental measurements

Author: K. Mahmud, B. E. Medlyn, R. A. Duursma, C. Campany, and M. G. De Kauwe
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: The lack of correlation between photosynthesis and plant growth under sink-limited conditions is a long-standing puzzle in plant ecophysiology that currently severely compromises our models of vegetation responses to global change. To address this puzzle, we applied data assimilation to an experiment in which the sink strength of Eucalyptus tereticornis seedlings was manipulated by restricting root volume. Our goals were to infer which processes were affected by sink limitation and to attribute the overall reduction in growth observed in the experiment to the effects on various carbon (C) component processes. Our analysis was able to infer that, in addition to a reduction in photosynthetic rates, sink limitation reduced the rate of utilization of nonstructural carbohydrate (NSC), enhanced respiratory losses, modified C allocation and increased foliage turnover. Each of these effects was found to have a significant impact on final plant biomass accumulation. We also found that inclusion of an NSC storage pool was necessary to capture seedling growth over time, particularly for sink-limited seedlings. Our approach of applying data assimilation to infer C balance processes in a manipulative experiment enabled us to extract new information on the timing, magnitude and direction of the internal C fluxes from an existing dataset. We suggest that this approach could, if used more widely, be an invaluable tool to develop appropriate representations of sink-limited growth in terrestrial biosphere models.
Published: 2018
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13. Large but decreasing effect of ozone on the European carbon sink

Author: R. J. Oliver, L. M. Mercado, S. Sitch, D. Simpson, B. E. Medlyn, Y.-S. Lin, and G. A. Folberth
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: The capacity of the terrestrial biosphere to sequester carbon and mitigate climate change is governed by the ability of vegetation to remove emissions of CO2 through photosynthesis. Tropospheric O3, a globally abundant and potent greenhouse gas, is, however, known to damage plants, causing reductions in primary productivity. Despite emission control policies across Europe, background concentrations of tropospheric O3 have risen significantly over the last decades due to hemispheric-scale increases in O3 and its precursors. Therefore, plants are exposed to increasing background concentrations, at levels currently causing chronic damage. Studying the impact of O3 on European vegetation at the regional scale is important for gaining greater understanding of the impact of O3 on the land carbon sink at large spatial scales. In this work we take a regional approach and update the JULES land surface model using new measurements specifically for European vegetation. Given the importance of stomatal conductance in determining the flux of O3 into plants, we implement an alternative stomatal closure parameterisation and account for diurnal variations in O3 concentration in our simulations. We conduct our analysis specifically for the European region to quantify the impact of the interactive effects of tropospheric O3 and CO2 on gross primary productivity (GPP) and land carbon storage across Europe. A factorial set of model experiments showed that tropospheric O3 can suppress terrestrial carbon uptake across Europe over the period 1901 to 2050. By 2050, simulated GPP was reduced by 4 to 9 % due to plant O3 damage and land carbon storage was reduced by 3 to 7 %. The combined physiological effects of elevated future CO2 (acting to reduce stomatal opening) and reductions in O3 concentrations resulted in reduced O3 damage in the future. This alleviation of O3 damage by CO2-induced stomatal closure was around 1 to 2 % for both land carbon and GPP, depending on plant sensitivity to O3. Reduced land carbon storage resulted from diminished soil carbon stocks consistent with the reduction in GPP. Regional variations are identified with larger impacts shown for temperate Europe (GPP reduced by 10 to 20 %) compared to boreal regions (GPP reduced by 2 to 8 %). These results highlight that O3 damage needs to be considered when predicting GPP and land carbon, and that the effects of O3 on plant physiology need to be considered in regional land carbon cycle assessments.
Published: 2018
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14. Upside-down fluxes Down Under: CO2 net sink in winter and net source in summer in a temperate evergreen broadleaf forest

Author: A. A. Renchon, A. Griebel, D. Metzen, C. A. Williams, B. Medlyn, R. A. Duursma, C. V. M. Barton, C. Maier, M. M. Boer, P. Isaac, D. Tissue, V. Resco de Dios, and E. Pendall
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Predicting the seasonal dynamics of ecosystem carbon fluxes is challenging in broadleaved evergreen forests because of their moderate climates and subtle changes in canopy phenology. We assessed the climatic and biotic drivers of the seasonality of net ecosystem–atmosphere CO2 exchange (NEE) of a eucalyptus-dominated forest near Sydney, Australia, using the eddy covariance method. The climate is characterised by a mean annual precipitation of 800 mm and a mean annual temperature of 18 °C, hot summers and mild winters, with highly variable precipitation. In the 4-year study, the ecosystem was a sink each year (−225 g C m−2 yr−1 on average, with a standard deviation of 108 g C m−2 yr−1); inter-annual variations were not related to meteorological conditions. Daily net C uptake was always detected during the cooler, drier winter months (June through August), while net C loss occurred during the warmer, wetter summer months (December through February). Gross primary productivity (GPP) seasonality was low, despite longer days with higher light intensity in summer, because vapour pressure deficit (D) and air temperature (Ta) restricted surface conductance during summer while winter temperatures were still high enough to support photosynthesis. Maximum GPP during ideal environmental conditions was significantly correlated with remotely sensed enhanced vegetation index (EVI; r2 = 0.46) and with canopy leaf area index (LAI; r2 = 0.29), which increased rapidly after mid-summer rainfall events. Ecosystem respiration (ER) was highest during summer in wet soils and lowest during winter months. ER had larger seasonal amplitude compared to GPP, and therefore drove the seasonal variation of NEE. Because summer carbon uptake may become increasingly limited by atmospheric demand and high temperature, and because ecosystem respiration could be enhanced by rising temperatures, our results suggest the potential for large-scale seasonal shifts in NEE in sclerophyll vegetation under climate change.
Published: 2018
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15. Ideas and perspectives: how coupled is the vegetation to the boundary layer?

Author: M. G. De Kauwe, B. E. Medlyn, J. Knauer, and C. A. Williams
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Understanding the sensitivity of transpiration to stomatal conductance is critical to simulating the water cycle. This sensitivity is a function of the degree of coupling between the vegetation and the atmosphere and is commonly expressed by the decoupling factor. The degree of coupling assumed by models varies considerably and has previously been shown to be a major cause of model disagreement when simulating changes in transpiration in response to elevated CO2. The degree of coupling also offers us insight into how different vegetation types control transpiration fluxes, which is fundamental to our understanding of land–atmosphere interactions. To explore this issue, we combined an extensive literature summary from 41 studies with estimates of the decoupling coefficient estimated from FLUXNET data. We found some notable departures from the values previously reported in single-site studies. There was large variability in estimated decoupling coefficients (range 0.05–0.51) for evergreen needleleaf forests. This is a result that was broadly supported by our literature review but contrasts with the early literature which suggests that evergreen needleleaf forests are generally well coupled. Estimates from FLUXNET indicated that evergreen broadleaved forests were the most tightly coupled, differing from our literature review and instead suggesting that it was evergreen needleleaf forests. We also found that the assumption that grasses would be strongly decoupled (due to vegetation stature) was only true for high precipitation sites. These results were robust to assumptions about aerodynamic conductance and, to a lesser extent, energy balance closure. Thus, these data form a benchmarking metric against which to test model assumptions about coupling. Our results identify a clear need to improve the quantification of the processes involved in scaling from the leaf to the whole ecosystem. Progress could be made with targeted measurement campaigns at flux sites and greater site characteristic information across the FLUXNET network.
Published: 2017
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16. Transient dynamics of terrestrial carbon storage: mathematical foundation and its applications

Author: Y. Luo, Z. Shi, X. Lu, J. Xia, J. Liang, J. Jiang, Y. Wang, M. J. Smith, L. Jiang, A. Ahlström, B. Chen, O. Hararuk, A. Hastings, F. Hoffman, B. Medlyn, S. Niu, M. Rasmussen, K. Todd-Brown, and Y.-P. Wang
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Terrestrial ecosystems have absorbed roughly 30 % of anthropogenic CO2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Overall, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.
Published: 2017
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17. Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

Author: Jason Beringer, Caitlin E. Moore, Jamie Cleverly, David I. Campbell, Helen Cleugh, Martin G. De Kauwe, Miko U. F. Kirschbaum, Anne Griebel, Sam Grover, Alfredo Huete, Lindsay B. Hutley, Johannes Laubach, Tom Van Niel, Stefan K. Arndt, Alison C. Bennett, Lucas A. Cernusak, Derek Eamus, Cacilia M. Ewenz, Jordan P. Goodrich, Mingkai Jiang, Nina Hinko‐Najera, Peter Isaac, Sanaa Hobeichi, Jürgen Knauer, Georgia R. Koerber, Michael Liddell, Xuanlong Ma, Craig Macfarlane, Ian D. McHugh, Belinda E. Medlyn, Wayne S. Meyer, Alexander J. Norton, Jyoteshna Owens, Andy Pitman, Elise Pendall, Suzanne M. Prober, Ram L. Ray, Natalia Restrepo‐Coupe, Sami W. Rifai, David Rowlings, Louis Schipper, Richard P. Silberstein, Lina Teckentrup, Sally E. Thompson, Anna M. Ukkola, Aaron Wall, Ying‐Ping Wang, Tim J. Wardlaw, and William Woodgate
Subjects: Global and Planetary Change, Ecology, Climate Change, Australia, Environmental Chemistry, Carbon Dioxide, Ecosystem, Carbon Cycle, General Environmental Science
Abstract: In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.
Published: 2022

18. Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

Author: M. G. De Kauwe, S.-X. Zhou, B. E. Medlyn, A. J. Pitman, Y.-P. Wang, R. A. Duursma, and I. C. Prentice
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSM and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.
Published: 2015
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19. Patterns of post‐drought recovery are strongly influenced by drought duration, frequency, post‐drought wetness, and bioclimatic setting

Author: Christopher R. Schwalm, Tong Jiao, Martin G. De Kauwe, Belinda E. Medlyn, and Christopher B. Williams
Subjects: Canopy, Global and Planetary Change, Ecology, Climate Change, Biome, Australia, Vegetation, Arid, Droughts, Plant Leaves, Water balance, Agronomy, Productivity (ecology), Photosynthetically active radiation, Drought recovery, Environmental Chemistry, Environmental science, Ecosystem, General Environmental Science
Abstract: Understanding vegetation recovery after drought is critical for projecting vegetation dynamics in future climates. From 1997 to 2009, Australia experienced a long-lasting drought known as the Millennium Drought (MD), which led to widespread reductions in vegetation productivity. However, vegetation recovery post-drought and its determinants remain unclear. This study leverages remote sensing products from different sources-fraction of absorbed photosynthetically active radiation (FPAR), based on optical data, and canopy density, derived from microwave data-and random forest algorithms to assess drought recovery over Australian natural vegetation during a 20-year period centered on the MD. Post-drought recovery was prevalent across the continent, with 6 out of 10 drought events seeing full recovery within about 6 months. Canopy density was slower to recover than leaf area seen in FPAR. The probability of full recovery was most strongly controlled by drought return interval, post-drought hydrological condition, and drought length. Full recovery was seldom observed when drought events occurred at intervals of 3 months or less, and moderately dry (standardized water balance anomaly [SWBA] within [-1, -0.76]) post-drought conditions resulted in less complete recovery than wet (SWBA > 0.3) post-drought conditions. Press droughts, which are long term but not extreme, delayed recovery more than pulse droughts (short term but extreme) and led to a higher frequency of persistent decline. Following press droughts, the frequency of persistent decline differed little among biome types but peaked in semi-arid regions across aridity levels. Forests and savanna required the longest recovery times for press drought, while grasslands were the slowest to recover for pulse drought. This study provides quantitative thresholds that could be used to improve the modeling of ecosystem dynamics post-drought.
Published: 2021

20. Oscillatory behavior of two nonlinear microbial models of soil carbon decomposition

Author: Y. P. Wang, B. C. Chen, W. R. Wieder, M. Leite, B. E. Medlyn, M. Rasmussen, M. J. Smith, F. B. Agusto, F. Hoffman, and Y. Q. Luo
Subjects: Ecology, QH540-549.5, Life, QH501-531, Geology, QE1-996.5
Abstract: A number of nonlinear models have recently been proposed for simulating soil carbon decomposition. Their predictions of soil carbon responses to fresh litter input and warming differ significantly from conventional linear models. Using both stability analysis and numerical simulations, we showed that two of those nonlinear models (a two-pool model and a three-pool model) exhibit damped oscillatory responses to small perturbations. Stability analysis showed the frequency of oscillation is proportional to √(ϵ−1−1) Ks/Vs in the two-pool model, and to √(ϵ−1−1) Kl/Vl in the three-pool model, where ϵ is microbial growth efficiency, Ks and Kl are the half saturation constants of soil and litter carbon, respectively, and /Vs and /Vl are the maximal rates of carbon decomposition per unit of microbial biomass for soil and litter carbon, respectively. For both models, the oscillation has a period of between 5 and 15 years depending on other parameter values, and has smaller amplitude at soil temperatures between 0 and 15 °C. In addition, the equilibrium pool sizes of litter or soil carbon are insensitive to carbon inputs in the nonlinear model, but are proportional to carbon input in the conventional linear model. Under warming, the microbial biomass and litter carbon pools simulated by the nonlinear models can increase or decrease, depending whether ϵ varies with temperature. In contrast, the conventional linear models always simulate a decrease in both microbial and litter carbon pools with warming. Based on the evidence available, we concluded that the oscillatory behavior and insensitivity of soil carbon to carbon input are notable features in these nonlinear models that are somewhat unrealistic. We recommend that a better model for capturing the soil carbon dynamics over decadal to centennial timescales would combine the sensitivity of the conventional models to carbon influx with the flexible response to warming of the nonlinear model.
Published: 2014
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21. Increasing aridity will not offset CO2fertilization in fast‐growing eucalypts with access to deep soil water

Author: Daniel Nadal-Sala, Belinda E. Medlyn, David T. Tissue, Craig V. M. Barton, David S. Ellsworth, Mark G. Tjoelker, Nadine K. Ruehr, Santi Sabaté, and Carles Gracia
Subjects: 0106 biological sciences, Limiting factor, Global and Planetary Change, Irrigation, Eucalyptus saligna, 010504 meteorology & atmospheric sciences, Ecology, biology, Vapour Pressure Deficit, Primary production, biology.organism_classification, 010603 evolutionary biology, 01 natural sciences, Nutrient, Agronomy, Soil water, Environmental Chemistry, Environmental science, Soil horizon, 0105 earth and related environmental sciences, General Environmental Science
Abstract: Rising atmospheric [CO2 ] (Ca ) generally enhances tree growth if nutrients are not limiting. However, reduced water availability and elevated evaporative demand may offset such fertilization. Trees with access to deep soil water may be able to mitigate such stresses and respond more positively to Ca . Here, we sought to evaluate how increased vapor pressure deficit and reduced precipitation are likely to modify the impact of elevated Ca (eCa ) on tree productivity in an Australian Eucalyptus saligna Sm. plantation with access to deep soil water. We parameterized a forest growth simulation model (GOTILWA+) using data from two field experiments on E. saligna: a 2-year whole-tree chamber experiment with factorial Ca (ambient =380, elevated =620 μmol mol-1 ) and watering treatments, and a 10-year stand-scale irrigation experiment. Model evaluation showed that GOTILWA+ can capture the responses of canopy C uptake to (1) rising vapor pressure deficit (D) under both Ca treatments; (2) alterations in tree water uptake from shallow and deep soil layers during soil dry-down; and (3) the impact of irrigation on tree growth. Simulations suggest that increasing Ca up to 700 μmol mol-1 alone would result in a 33% increase in annual gross primary production (GPP) and a 62% increase in biomass over 10 years. However, a combined 48% increase in D and a 20% reduction in precipitation would halve these values. Our simulations identify high D conditions as a key limiting factor for GPP. They also suggest that rising Ca will compensate for increasing aridity limitations in E. saligna trees with access to deep soil water under non-nutrient limiting conditions, thereby reducing the negative impacts of global warming upon this eucalypt species. Simulation models not accounting for water sources available to deep-rooting trees are likely to overestimate aridity impacts on forest productivity and C stocks.
Published: 2021

22. Identifying areas at risk of drought‐induced tree mortality across South‐Eastern Australia

Author: Mengyuan Mu, Michael L. Roderick, Patrick Meir, Anna M. Ukkola, Andrew J. Pitman, Sami W. Rifai, Brendan Choat, Martin G. De Kauwe, Chris J. Blackman, Lucas A. Cernusak, Manon Sabot, Peter R. Briggs, David T. Tissue, Ximeng Li, and Belinda E. Medlyn
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, Climate Change, media_common.quotation_subject, Drought tolerance, Eddy covariance, Vulnerability, Climate change, 010603 evolutionary biology, 01 natural sciences, Trees, Hydraulic conductivity, Environmental Chemistry, 0105 earth and related environmental sciences, General Environmental Science, media_common, Global and Planetary Change, Ecology, Australia, Water, Biosphere, Vegetation, 15. Life on land, Droughts, Plant Leaves, 13. Climate action, Environmental science, Psychological resilience, Physical geography
Abstract: South-East Australia has recently been subjected to two of the worst droughts in the historical record (Millennium Drought, 2000-2009 and Big Dry, 2017-2019). Unfortunately, a lack of forest monitoring has made it difficult to determine whether widespread tree mortality has resulted from these droughts. Anecdotal observations suggest the Big Dry may have led to more significant tree mortality than the Millennium drought. Critically, to be able to robustly project future expected climate change effects on Australian vegetation, we need to assess the vulnerability of Australian trees to drought. Here we implemented a model of plant hydraulics into the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. We parameterized the drought response behaviour of five broad vegetation types, based on a common garden dry-down experiment with species originating across a rainfall gradient (188-1,125 mm/year) across South-East Australia. The new hydraulics model significantly improved (similar to 35%-45% reduction in root mean square error) CABLE's previous predictions of latent heat fluxes during periods of water stress at two eddy covariance sites in Australia. Landscape-scale predictions of the greatest percentage loss of hydraulic conductivity (PLC) of about 40%-60%, were broadly consistent with satellite estimates of regions of the greatest change in both droughts. In neither drought did CABLE predict that trees would have reached critical PLC in widespread areas (i.e. it projected a low mortality risk), although the model highlighted critical levels near the desert regions of South-East Australia where few trees live. Overall, our experimentally constrained model results imply significant resilience to drought conferred by hydraulic function, but also highlight critical data and scientific gaps. Our approach presents a promising avenue to integrate experimental data and make regional-scale predictions of potential drought-induced hydraulic failure.
Published: 2020

23. Low phosphorus supply constrains plant responses to elevated CO 2 : A meta‐analysis

Author: Mingkai Jiang, Haiyang Zhang, Peter B. Reich, David S. Ellsworth, Belinda E. Medlyn, Katrin Fleischer, Jinyan Yang, Kristine Y. Crous, Martin G. De Kauwe, Silvia Caldararu, Sönke Zaehle, and David T. Tissue
Subjects: 0106 biological sciences, Plant growth, 010504 meteorology & atmospheric sciences, chemistry.chemical_element, Biology, Photosynthesis, 010603 evolutionary biology, 01 natural sciences, chemistry.chemical_compound, Animal science, Nutrient, soil phosphorus, Environmental Chemistry, mycorrhizae, 0105 earth and related environmental sciences, General Environmental Science, nutrient concentration, 2. Zero hunger, plant morphology, Global and Planetary Change, Biomass (ecology), biomass, Ecology, Phosphorus, carbon dioxide, food and beverages, 15. Life on land, leaf gas exchange, meta-analysis, plant nutrient uptake, chemistry, Plant morphology, Carbon dioxide, Woody plant
Abstract: Phosphorus (P) is an essential macro-nutrient required for plant metabolism and growth. Low P availability could potentially limit plant responses to elevated carbon dioxide (eCO2), but consensus has yet to be reached on the extent of this limitation. Here, based on data from experiments that manipulated both CO2 and P for young individuals of woody and non-woody species, we present a meta-analysis of P limitation impacts on plant growth, physiological, and morphological response to eCO2. We show that low P availability attenuated plant photosynthetic response to eCO2 by approximately one-quarter, leading to a reduced, but still positive photosynthetic response to eCO2 compared to those under high P availability. Furthermore, low P limited plant aboveground, belowground, and total biomass responses to eCO2, by 14.7%, 14.3%, and 12.4%, respectively, equivalent to an approximate halving of the eCO2 responses observed under high P availability. In comparison, low P availability did not significantly alter the eCO2-induced changes in plant tissue nutrient concentration, suggesting tissue nutrient flexibility is an important mechanism allowing biomass response to eCO2 under low P availability. Low P significantly reduced the eCO2-induced increase in leaf area by 14.3%, mirroring the aboveground biomass response, but low P did not affect the eCO2-induced increase in root length. Woody plants exhibited stronger attenuation effect of low P on aboveground biomass response to eCO2 than non-woody plants, while plants with different mycorrhizal associations showed similar responses to low P and eCO2 interaction. This meta-analysis highlights crucial data gaps in capturing plant responses to eCO2 and low P availability. Field-based experiments with longer-term exposure of both CO2 and P manipulations are critically needed to provide ecosystem-scale understanding. Taken together, our results provide a quantitative baseline to constrain model-based hypotheses of plant responses to eCO2 under P limitation, thereby improving projections of future global change impacts.
Published: 2020

24. The temperature optima for tree seedling photosynthesis and growth depend on water inputs

Author: Belinda E. Medlyn, Angelica Vårhammar, Dushan Kumarathunge, Sebastian Pfautsch, Rosana López, Mark G. Tjoelker, and John E. Drake
Subjects: 0106 biological sciences, Global and Planetary Change, Biomass (ecology), 010504 meteorology & atmospheric sciences, Ecology, biology, Specific leaf area, Global warming, Plant physiology, Photosynthesis, biology.organism_classification, 010603 evolutionary biology, 01 natural sciences, Indirect effect, Agronomy, Seedling, Respiration, Environmental Chemistry, Environmental science, 0105 earth and related environmental sciences, General Environmental Science
Abstract: Understanding how tree growth is affected by rising temperature is a key to predicting the fate of forests in future warmer climates. Increasing temperature has direct effects on plant physiology, but there are also indirect effects of increased water limitation because evaporative demand increases with temperature in many systems. In this study, we experimentally resolved the direct and indirect effects of temperature on the response of growth and photosynthesis of the widely distributed species Eucalyptus tereticornis. We grew E. tereticornis in an array of six growth temperatures from 18 to 35.5°C, spanning the climatic distribution of the species, with two watering treatments: (a) water inputs increasing with temperature to match plant demand at all temperatures (Wincr ), isolating the direct effect of temperature; and (b) water inputs constant for all temperatures, matching demand for coolest grown plants (Wconst ), such that water limitation increased with growth temperature. We found that constant water inputs resulted in a reduction of temperature optima for both photosynthesis and growth by ~3°C compared to increasing water inputs. Water limitation particularly reduced the total amount of leaf area displayed at Topt and intermediate growth temperatures. The reduction in photosynthesis could be attributed to lower leaf water potential and consequent stomatal closure. The reduction in growth was a result of decreased photosynthesis, reduced total leaf area display and a reduction in specific leaf area. Water availability had no effect on the response of stem and root respiration to warming, but we observed lower leaf respiration rates under constant water inputs compared to increasing water inputs at higher growth temperatures. Overall, this study demonstrates that the indirect effect of increasing water limitation strongly modifies the potential response of tree growth to rising global temperatures.
Published: 2020

25. Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

Author: Beringer, J, Moore, CE, Cleverly, J, Campbell, DI, Cleugh, H, De Kauwe, MG, Kirschbaum, MUF, Griebel, A, Grover, S, Huete, A, Hutley, LB, Laubach, J, Van Niel, T, Arndt, SK, Bennett, AC, Cernusak, LA, Eamus, D, Ewenz, CM, Goodrich, JP, Jiang, M, Hinko-Najera, N, Isaac, P, Hobeichi, S, Knauer, J, Koerber, GR, Liddell, M, Ma, X, Macfarlane, C, McHugh, ID, Medlyn, BE, Meyer, WS, Norton, AJ, Owens, J, Pitman, A, Pendall, E, Prober, SM, Ray, RL, Restrepo-Coupe, N, Rifai, SW, Rowlings, D, Schipper, L, Silberstein, RP, Teckentrup, L, Thompson, SE, Ukkola, AM, Wall, A, Wang, Y-P, Wardlaw, TJ, and Woodgate, W
Subjects: Ecology, 05 Environmental Sciences, 06 Biological Sciences
Abstract: In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those 'next users' of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.
Published: 2022

26. TRY plant trait database – enhanced coverage and open access

Author: Kattge, J., Bonisch, G., Diaz, S., Lavorel, S., Prentice, I. C., Leadley, P., Tautenhahn, S., Werner, G. D. A., Aakala, T., Abedi, M., Acosta, A. T. R., Adamidis, G. C., Adamson, K., Aiba, M., Albert, C. H., Alcantara, J. M., Alcazar, C C., Aleixo, I., Ali, H., Amiaud, B., Ammer, C., Amoroso, M. M., Anand, M., Anderson, C., Anten, N., Antos, J., Apgaua, D. M. G., Ashman, T. L., Asmara, D. H., Asner, G. P., Aspinwall, M., Atkin, O., Aubin, I., Baastrup-Spohr, L., Bahalkeh, K., Bahn, M., Baker, T., Baker, W. J., Bakker, J. P., Baldocchi, D., Baltzer, J., Banerjee, A., Baranger, A., Barlow, J., Barneche, D. R., Baruch, Z., Bastianelli, D., Battles, J., Bauerle, W., Bauters, M., Bazzato, E., Beckmann, M., Beeckman, H., Beierkuhnlein, C., Bekker, R., Belfry, G., Belluau, M., Beloiu, M., Benavides, R., Benomar, L., Berdugo-Lattke, M. L., Berenguer, E., Bergamin, R., Bergmann, J., Bergmann Carlucci, M., Berner, L., Bernhardt Romermann, M., Bigler, C., Bjorkman, A. D., Blackman, C., Blanco, C., Blonder, B., Blumenthal, D., Bocanegra Gonzalez, K. T., Boeckx, P., Bohlman, S., Bohning Gaese, K., Boisvert Marsh, L., Bond, W., Bond-Lamberty, B., Boom, A., Boonman, C. C. F., Bordin, K., Boughton, E. H., Boukili, V., Bowman, D. M. J. S., Bravo, S., Brende, l M. R., Broadley, M. R., Brown, K. A., Bruelheide, H., Brumnich, F., Bruun, H. H., Bruy, D., Buchanan, S. W., Bucher, S. F., Buchmann, N., Buitenwerf, R., Bunker, D. E., Burge, r J., Burrascano, S., Burslem, D. F. R. P., Butterfield, B. J., Byun, C., Marques, M., Scalon, M. C., Caccianiga, M., Cadotte, M., Cailleret, M., Camac, J., Camarero, J. J., Campany, C., Campetella, G., Campos, J. A., Cano Arboleda, L., Canullo, R., Carbognani, M., Carvalho, F., Casanoves, F., Castagneyrol, B., Catford, J. A., Cavender Bares, J., Cerabolini, B. E. L., Cervellini, M., Chacon Madrigal, E., Chapin, K., Chapin, F. S., Chelli, S., Chen, S. C., Chen, A., Cherubini, P., Chianucci, F., Choat, B., Chung, K. S., Chytry, M., Ciccarelli, D., Coll, L., Collins, C. G., Conti, L., Coomes, D., Cornelissen, J. H. C., Cornwell, W. K., Corona, P., Coyea, M., Craine, J., Craven, D., Cromsigt, J. P. G. M., Csecserits, A., Cufar, K., Cuntz, M., da Silva, A. C., Dahlin, K. M., Dainese, M., Dalke, I., Dalle Fratte, M., Dang Le, A. T., Danihelka, J., Dannoura, M., Dawson, S., de Beer, A. J., De Frutos, A., De Long, J. R., Dechant, B., Delagrange, S., Delpierre, N., Derroire, G., Dias, A. S., Diaz Toribio, M. H., Dimitrakopoulos, P. G., Dobrowolski, M., Doktor, D., Drevojan, P., Dong, N., Dransfield, J., Dressler, S., Duarte, L., Ducouret, E., Dullinger, S., Durka, W., Duursma, R., Dymova, O., E- Vojtko, A., Eckstein, R. L., Ejtehadi, H., Elser, J., Emilio, T., Engemann, K., Erfanian, M. B., Erfmeier, A., Esquivel Muelbert, A., Esser, G., Estiarte, M., Domingues, T. F., Fagan, W. F., Fagundez, J., Falster, D. S., Fan, Y., Fang, J., Farris, E., Fazlioglu, F., Feng, Y., Fernandez, Mendez, Ferrara, C., Ferreira, J., Fidelis, A., Finegan, B., Firn, J., Flowers, T. J., Flynn, D. F. B., Fontana, V., Forey, E., Forgiarini, C., Francois, L., Frangipani, M., Frank, D., Frenette Dussault, C., Freschet, G. T., Fry, E. L., Fyllas, N. M., Mazzochini, G. G., Gachet, S., Gallagher, R., Ganade, G., Ganga, F., Garcia Palacios, P., Gargaglione, V., Garnier, E., Garrido, J. L., de Gasper, A. L., Gea Izquierdo, G., Gibson, D., Gillison, A. N., Giroldo, A., Glasenhardt, M. C., Gleason, S., Gliesch, M., Goldberg, E., Goldel, B., Gonzalez Akre, E., Gonzalez Andujar, J. L., Gonzalez Melo, A., Gonzalez Robles, A., Graae, B. J., Granda, E., Graves, S., Green, W. A., Gregor, T., Gross, N., Guerin, G. R., Gunther, A., Gutierrez, A. G., Haddock, L., Haines, A., Hall, J., Hambuckers, A., Han, W., Harrison, S. P., Hattingh, W., Hawes, J. E., He, T., He, P., Heberling, J. M., Helm, A., Hempel, S., Hentschel, J., Herault, B., Heres, A. M., Herz, K., Heuertz, M., Hickler, T., Hietz, P., Higuchi, P., Hipp, A. L., Hirons, A., Hock, M., Hogan, J. A., Holl, K., Honnay, O., Hornstein, D., Hou, E., Hough Snee, N., Hovstad, K. A., Ichie, T., Igic, B., Illa, E., Isaac, M., Ishihara, M., Ivanov, L., Ivanova, L., Iversen, C. M., Izquierdo, J., Jackson, R. B., Jackson, B., Jactel, H., Jagodzinsk, A. M., Jandt, U., Jansen, S., Jenkins, T., Jentsch, A., Jespersen, J. R. P., Jiang, G. F., Johansen, J. L., Johnson, D., Jokela, E. J., Joly, C. A., Jordan, G. J., Joseph, G. S., Junaedi, D., Junker, R. R., Justes, E., Kabzems, R., Kane, J., Kaplan, Z., Kattenborn, T., Kavelenova, L., Kearsley, E., Kempel, A., Kenzo, T., Kerkhoff, A., Khalil, M. I., Kinlock, N. L., Kissling, W. D., Kitajima, K., Kitzberger, T., Kjoller, R., Klein, T., Kleyer, M., Klimesova, J., Klipel, J., Kloeppel, B., Klotz, S., Knops, J. M. H., Kohyama, T., Koike, F., Kollmann, J., Komac, B., Komatsu, K., Konig, C., Kraft, N. J. B., Kramer, K., Kreft, H., Kuhn, I., Kumarathune, D., Kuppler, J., Kurokawa, H., Kurosawa, Y., Kuyah, S., Laclau, J. P., Lafleur, B., Lallai, E., Lamb, E., Lamprecht, A., Larkin, D. J., Laughlin, D., Le Bagousse Pinguet, Y., le Maire, G., le Roux, P. C., le Roux, E., Lee, T., Lens, F., Lewis, S. L., Lhotsky, B., Li, Y., Li, X., Lichstein, J. W., Liebergesell, M., Lim, J. Y., Lin, Y. S., Linares, Y. C., Liu, C., Liu, D., Liu, U., Livingstone, S., Llusia, J., Lohbeck, M., Lopez Garcia, A., Lopez Gonzalez, G., Lososov, a Z., Louault, F., Lukacs, B. A., Lukes, P., Luo, Y., Lussu, M., Ma, S., Maciel Rabelo Pereira, C., Mack, M., Maire, V., Makela, A., Makinen, H., Malhado, A. C. M., Mallik, A., Manning, P., Manzoni, S., Marchetti, Z., Marchino, L., Marcilio Silva, V., Marcon, E., Marignani, M., Markesteijn, L., Martin, A., Martinez Garza, C., Martinez Vilalta, J., Maskova, T., Mason, K., Mason, N., Massad, T. J., Masse, J., Mayrose, I., Mccarthy, J., Mccormack, M. L., Mcculloh, K., Mcfadden, I., Mcgill, B. J., Mcpartland, M. Y., Medeiros, J., Medlyn, B., Meerts, P., Mehrabi, Z., Meir, P., Melo, F., P. L., Mencuccini, M., Meredieu, C., Messier, J., Meszaros, I., Metsaranta, J., Michaletz, S. T., Michelaki, C., Migalina, S., Milla, R., Miller, J., E. D., Minden, V., Ming, R., Mokany, K., Moles, A. T., Molnar, A., Molofsky, J., Molz, M., Montgomery, R. A., Monty, A., Moravcova, L., Moreno Martinez, A., Moretti, M., Mori, A. S., Mori, S., Morris, D., Morrison, J., Mucina, L., Mueller, S., Muir, C. D., Muller, S. C., Munoz, F., Myers Smith, I. H., Myster, R. W., Nagano, M., Naidu, S., Narayanan, A., Natesan, B., Negoita, L., Nelson, A. S., Neuschulz, E. L., Ni, J., Niedrist, G., Nieto, J., Niinemets, U., Nolan, R., Nottebrock, H., Nouvellon, Y., Novakovskiy, A., Nystuen, K. O., O'Grady, A., O'Hara, K., O'Reilly Nugent, A., Oakley, S., Oberhuber, W., Ohtsuka, T., Oliveira, R., Ollerer, K., Olson, M. E., Onipchenko, V., Onoda, Y., Onstein, R. E., Ordonez, J. C., Osada, N., Ostonen, I., Ottaviani, G., Otto, S., Overbeck, G. E., Ozinga, W. A., Pahl, A. T., Paine, C. E. T., Pakeman, R. J., Papageorgiou, A. C., Parfionova, E., Partel, M., Patacca, M., Paula, S., Paule, J., Pauli, H., Pausas, J., Peco, B., Penuelas, J., Perea, A., Peri, P. L., Petisco Souza, A. C., Petraglia, A., Petritan, A. M., Phillips, O. L., Pierce, S., Pillar, V. D., Pisek, J., Pomogaybin, A., Poorter, H., Portsmuth, A., Poschlod, P., Potvin, C., Pounds, D., Powell, A., Power, S. A., Prinzing, A., Puglielli, G., Pysek, P., Raevel, V., Rammig, A., Ransijn, J., Ray, C. A., Reich, P. B., Reichstein, M., Reid, D. E. B., Rejou Mechain, M., de Dios, V. R., Ribeiro, S., Richardson, S., Riibak, K., Rillig, M. C., Riviera, F., Robert, E. M. R., Roberts, S., Robroek, B., Roddy, A., Rodrigues, A. V., Rogers, A., Rollinson, E., Rolo, V., Romermann, C., Ronzhina, D., Roscher, C., Rosell, J. A., Rosenfield, M. F., Rossi, C., Roy, D. B., Royer Tardif, S., Ruger, N., Ruiz Peinado, R., Rumpf, S. B., Rusch, G. M., Ryo, M., Sack, L., Saldana, A., Salgado Negret, B., Salguero Gomez, R., Santa Regina, I., Santacruz Garcia, A. C., Santos, J., Sardans, J., Schamp, B., Scherer Lorenzen, M., Schleuning, M., Schmid, B., Schmidt, M., Schmitt, S., Schneider, J. V., Schowanek, S. D., Schrader, J., Schrodt, F., Schuldt, B., Schurr, F., Selaya Garvizu, G., Semchenko, M., Seymour, C., Sfair, J. C., Sharpe, J. M., Sheppard, C. S., Sheremetiev, S., Shiodera, S., Shipley, B., Shovon, T. A., Siebenkas, A., Sierra, C., Silva, V., Silva, M., Sitzia, T., Sjoman, H., Slot, M., Smith, N. G., Sodhi, D., Soltis, P., Soltis, D., Somers, B., Sonnier, G., Sorensen, M. V., Sosinski, E. E., Soudzilovskaia, N. A., Souza, A. F., Spasojevic, M., Sperandii, M. G., Stan, A. B., Stegen, J., Steinbauer, K., Stephan, J. G., Sterck, F., Stojanovic, D. B., Strydom, T., Suarez, M. L., Svenning, J. C., Svitkova, I., Svitok, M., Svoboda, M., Swaine, E., Swenson, N., Tabarelli, M., Takagi, K., Tappeiner, U., Tarifa, R., Tauugourdeau, S., Tavsanoglu, C., te Beest, M., Tedersoo, L., Thiffault, N., Thom, D., Thomas, E., Thompson, K., Thornton, P. E., Thuiller, W., Tichy, L., Tissue, D., Tjoelker, M. G., Tng, D. Y. P., Tobias, J., Torok, P., Tarin, T., Torres Ruiz, J. M., Tothmeresz, B., Treurnicht, M., Trivellone, V., Trolliet, F., Trotsiuk, V., Tsakalos, J. L., Tsiripidis, I., Tysklind, N., Umehara, T., Usoltsev, V., Vadeboncoeur, M., Vaezi, J., Valladares, F., Vamosi, J., van Bodegom, P. M., van Breugel, M., Van Cleemput, E., van de Weg, M., van der Merwe, S., van der Plas, F., van der Sande, M. T., van Kleunen, M., Van Meerbeek, K., Vanderwel, M., Vanselow, K. A., Varhammar, A., Varone, L., Vasquez Valderrama, M. Y., Vassilev, K., Vellend, M., Veneklaas, E. J., Verbeeck, H., Verheyen, K., Vibrans, A., Vieira, I., Villacis, J., Violle, C., Vivek, P., Wagner, K., Waldram, M., Waldron, A., Walker, A . P., Waller, M., Walther, G., Wang, H., Wang, F., Wang, W., Watkins, H., Watkins, J., Weber, U., Weedon, J. T., Wei, L., Weigelt, P., Weiher, E., Wells, A. W., Wellstein, C., Wenk, E., Westoby, M., Westwood, A., White, P. J., Whitten, M., Williams, M., Winkler, D. E., Winter, K., Womack, C., Wright, I. J., Wright, S. J., Wright, J., Pinho, B. X., Ximenes, F., Yamada, T., Yamaji, K., Yanai, R., Yankov, N., Yguel, B., Zanini, K. J., Zanne, A. E., Zeleny, D., Zhao, Y. P., Zheng, J., Zieminska, K., Zirbel, C. R., Zizka, G., Zo Bi, I. C., Zotz, G., Wirth, C., Systèmes d'élevage méditerranéens et tropicaux (UMR SELMET), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Laboratoire de Physique et Physiologie Intégratives de l’Arbre en environnement Fluctuant - Clermont Auvergne (PIAF), Université Clermont Auvergne (UCA)-Institut National de la Recherche Agronomique (INRA), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Institut de Recherche pour le Développement (IRD [France-Sud])-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Biodiversité, Gènes & Communautés (BioGeCo), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB), SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ecologie des forêts de Guyane (UMR ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Unité Expérimentale Forêt Pierroton (UEFP), Institut National de la Recherche Agronomique (INRA), Max Planck Institute for Biogeochemistry Max Planck SocietyFoundation CELLEX German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig International Programme of Biodiversity Science (DIVERSITAS) International Geosphere-Biosphere Programme (IGBP) French Foundation for Biodiversity Research (FRB) GIS 'Climat, Environnement et Societe' France AXA Research Fund NERC Natural Environment Research Council Future Earth, Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, German Centre for Integrative Biodiversity Research (iDiv), Instituto Multidisciplinario de Biología Vegetal [Córdoba] (IMBIV), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Facultad de Ciencias Exactas, Físicas y Naturales [Córdoba], Universidad Nacional de Córdoba [Argentina]-Universidad Nacional de Córdoba [Argentina], Laboratoire d'Ecologie Alpine (LECA ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Imperial College London, Ecologie Systématique et Evolution (ESE), AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Department of Zoology [Oxford], University of Oxford, Balliol College, Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Tarbiat Modares University [Tehran], Università degli Studi Roma Tre = Roma Tre University (ROMA TRE), Department of Environment [Aegean], University of the Aegean, Institute of Ecology and Evolution [Bern, Switzerland], University of Bern, University of Tartu, Tohoku University [Sendai], Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS), Universidad de Jaén (UJA), Instituto Alexander Von Humboldt, Bogota, Colombia, National Institute of Amazonian Research (INPA), Manaus, Brazil, Botany Department, Faculty of Science, Suez Canal University, Ismailia, Egypt, Laboratoire Agronomie et Environnement - Antenne Colmar (LAE-Colmar ), Laboratoire Agronomie et Environnement (LAE), Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Forest Sciences, University of Göttingen, Göttingen, Germany, Centre for Biodiversity and Sustainable Land-use [University of Göttingen] (CBL), Georg-August-University = Georg-August-Universität Göttingen, Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural (IRNAD), Universidad Nacional de Río Negro, El Bolsón, Argentina, Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET), School of Environmental Sciences, University of Guelph, Pacific Northwest National Laboratory, Richland, WA, USA, University of Massachusetts [Amherst] (UMass Amherst), University of Massachusetts System (UMASS), Centre for Crop Systems Analysis, Wageningen University and Research [Wageningen] (WUR), University of Victoria [Canada] (UVIC), College of Science & Engineering, James Cook University, Smithfield, Qld, Australia, University of Pittsburgh, Pittsburgh, PA, USA, Centre for Forest Research, Institute for Integrative Systems Biology, Université Laval, Quebec, QC, Canada, Arizona State University, Tempe, AZ, USA, University of North Florida [Jacksonville] (UNF), Australian National University (ANU), Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, Sault Ste. Marie, ON, Canada, Department of Biology [Copenhagen], Faculty of Science [Copenhagen], University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH), Department of Ecology [Innsbruck], Leopold Franzens Universität Innsbruck - University of Innsbruck, University of Leeds, Royal Botanic Gardens Kew, Richmond, UK, Conservation Ecology, Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Groningen, The Netherlands, Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Biology Department, Wilfrid Laurier University, Waterloo, ON, Canada, Department of Forest Resources, University of Minnesota, St. Paul, MN, USA, AgroParisTech, Lancaster Environment Centre, Lancaster University, University of Exeter, University of Adelaide, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Département Environnements et Sociétés (Cirad-ES), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), University of California [Berkeley] (UC Berkeley), University of California (UC), Department of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO, USA, Universiteit Gent = Ghent University (UGENT), Università degli Studi di Cagliari = University of Cagliari (UniCa), Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Royal Museum for Central Africa, Tervuren, Belgium, Bayreuth Center of Ecology and Environmental Research (BayCEER), Groningen Institute of Archaeology (GIA), University of Groningen, Groningen, The Netherlands, Department of Biological Sciences, University of Tennessee, Knoxville, TN, USA, Rocky Mountain Biological Laboratory, Crested Butte, CO, USA, Département des Science, Université du Québec À Montréal, Montreal, QC, Canada, Department of Biogeography, University of Bayreuth, Bayreuth, Germany, Museo Nacional de Ciencias Naturales [Madrid] (MNCN), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Université Laval, Quebec, QC, Canada, Instituto de Ciencias Naturales, Universidad Nacional de Colombia, Bogota, Colombia, Fundación Natura, Bogota, Colombia, Environmental Change Institute, Laboratório de Estudos em Vegetação Campestre (LEVCamp), Programa de Pós-Graduação em Botânica, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil, Freie Universität Berlin, Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany, Laboratório de Ecologia Funcional de Comunidades (LABEF), Departamento de Botânica, Universidade Federal do Paraná, Curitiba, Brazil, School of Informatics, Computing, and Cyber Systems (SICCS), Northern Arizona University [Flagstaff], Institute of Ecology and Evolution, Friedrich Schiller University Jena, Jena, Germany, ETH Zurich, Universitatstrasse 16, 8092 Zurich, Switzerland, University of Gothenburg (GU), Laboratoire de Physique et Physiologie Intégratives de l’Arbre en environnement Fluctuant (PIAF), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Universidade Federal do Rio Grande do Sul [Porto Alegre] (UFRGS), School of Life Sciences, Arizona State University, Tempe, AZ, USA, USDA-ARS Rangeland Resources & Systems Research Unit, Fort Collins, CO, USA, Grupo de Investigación en Biodiversidad y Dinámica de Ecosistémas Tropicales - Universidad del Tolima, Ibagué, Colombia, Laboratory of Applied Physical Chemistry - ISOFYS (Gent, Belgium), School of Forest Resources and Conservation [Gainesville] (UF|IFAS|FFGS), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), Senckenberg Biodiversity and Climate Research Centre, Frankfurt am Main, Germany, Department of Biological Sciences, Goethe Universität Frankfurt, Frankfurt am Main, Germany, Department of Biological Sciences, University of Cape Town, Cape Town, South Africa, SAEON Fynbos Node, Claremont, South Africa, Pacific Northwest National Laboratory, College Park, MD, USA, University of Leicester, Department of Environmental Science, Institute for Water and Wetland Research, Radboud University, Nijmegen, The Netherlands, Laboratório de Ecologia Vegetal (LEVEG), Programa de Pós-Graduação em Ecologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil, Archbold Biological Station’s Buck Island Ranch, FL, Lake Placid, USA, Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA, University of Tasmania [Hobart, Australia] (UTAS), Facultad de Ciencias Forestales, Universidad Nacional de Santiago del Estero, Santiago del Estero, Argentina, Universität Hohenheim, School of Geography, University of Nottingham, Nottingham, UK, Department of Geography and Geology, Kingston University, Kingston upon Thames, UK, Martin-Luther-Universität Halle Wittenberg (MLU), Facultad de Ingeniería y Ciencias Hídricas, Universidad Nacional del Litoral (FICH-UNL), Santa Fe, Argentina, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Recherche pour le Développement (IRD [Nouvelle-Calédonie]), University of Toronto at Scarborough, Friedrich-Schiller-Universität = Friedrich Schiller University Jena [Jena, Germany], Section for Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Aarhus, Denmark, Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Bioscience, Aarhus University, Aarhus, Denmark, New Jersey Institute of Technology [Newark] (NJIT), University of Rostock, Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA), School of Biological Sciences, University of Aberdeen, Aberdeen, UK, Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA, School of Civil and Environmental Engineering, Yonsei University, Seoul, Korea, Departamento de Botânica, SCB, UFPR – Federal University of Parana, Curitiba, Brazil, Centro Politécnico, Universidade Federal do Paraná, Curitiba, Brazil, Università degli Studi di Milano = University of Milan (UNIMI), Risques, Ecosystèmes, Vulnérabilité, Environnement, Résilience (RECOVER), Aix Marseille Université (AMU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Centre of Excellence for Bioscurity Risk Analysis, The University of Melbourne, Melbourne, Vic., Australia, Centro de Investigaciones Biológicas (CSIC), Colgate University, Hamilton, NY, USA, School of Biosciences and Veterinary Medicine, Plant Diversity and Ecosystems Management Unit, University of Camerino, Camerino, Italy, University of the Basque Country/Euskal Herriko Unibertsitatea (UPV/EHU), Departamento de Geociencias y Medio Ambiente, Universidad Nacional de Colombia, Medellin, Colombia, Università degli studi di Parma = University of Parma (UNIPR), Centro Agronómico Tropical de Investigación y Enseñanza - Tropical Agricultural Research and Higher Education Center (CATIE), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Geography, King’s College London, London, UK, University of Minnesota [Twin Cities] (UMN), University of Minnesota System, Universitá degli Studi dell’Insubria = University of Insubria [Varese] (Uninsubria), Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Universidad de Costa Rica (UCR), University of Arizona, Institute of Arctic Biology, University of Alaska [Fairbanks] (UAF), Royal Botanic Gardens [Kew], Department of Biology [Fort Collins], Colorado State University [Fort Collins] (CSU), WSL Swiss Federal Research Institute, Birmensdorf, Switzerland, Faculty of Forestry, University of British Columbia, Vancouver, BC, Canada, CREA – Research Centre for Forestry and Wood, Arezzo, Italy, Western Sydney University, ungwon University, Goesan, Chungbuk, Korea, Department of Botany and Zoology [Brno] (SCI / MUNI), Faculty of Science [Brno] (SCI / MUNI), Masaryk University [Brno] (MUNI)-Masaryk University [Brno] (MUNI), University of Pisa - Università di Pisa, Department of Agriculture and Forest Engineering (EAGROF), University of Lleida, Lleida, Spain, Joint Research Unit CTFC – AGROTECNIO, Solsona, Spain, University of California Riverside, Riverside, CA, USA, Faculty of Environmental Sciences, University of Life Sciences Prague, Institute of Botany of the Czech Academy of Sciences (IB / CAS), Czech Academy of Sciences [Prague] (CAS), University of Cambridge [UK] (CAM), Systems Ecology, Department of Ecological Science, Vrije Universiteit, Amsterdam, The Netherlands, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, NSW, Australia, Faculté de foresterie, de géographie et de géomatique, Université Laval, Quebec, QC, Canada, Jonah Ventures, Boulder, CO, USA, Centro de Modelación y Monitoreo de Ecosistemas, Universidad Mayor, Santiago, Chile, Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences (SLU), Centre for African Conservation Ecology, Department of Zoology, Nelson Mandela University, Port Elizabeth, South Africa, MTA Centre for Ecological Research [Tihany], Hungarian Academy of Sciences (MTA), University of Ljubljana, Santa Catarina State University, Lages, SC, Brazil, Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, USA, Eurac Research, Institute for Alpine Environment, Bozen-Bolzano, Italy, Institute of Biology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences, Syktyvkar, Komi Republic, Russia, University of Science – Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam, Graduate School of Agriculture, Kyoto University, Kyoto, Japan, Graduate School of Global Environmental Studies, Kyoto University, Kyoto, Japan, Swedish Species Information Centre, University of Pretoria [South Africa], Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany, Department of Terrestrial Ecology, Netherlands Institute of Ecology, Wageningen, The Netherlands, Department Computational Landscape Ecology [UFZ Leipsig], Department Computational Hydrosystems, UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany, Seoul National University [Seoul] (SNU), Institute of Temperate Forest Sciences (ISFORT), Ripon, QC, Canada, UQO, Department of Natural Sciences, Ripon, QC, Canada, Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Goethe-Universität Frankfurt am Main, University of Florida [Gainesville] (UF), The University of Western Australia (UWA), School of Biological Sciences, The University of Western Australia, Department of Biological Sciences, Macquarie University, Department of Botany and Molecular Evolution, Senckenberg Research Institute and Natural History Museum, Universität Wien, Karlstad University [Sweden], Ferdowsi University of Mashhad (FUM), Flathead Lake Biological Station, University of Montana, School of Sustainability, Arizona State University, Programa Nacional de Pós-Doutorado (PNPD), Programa de Pós Graduação em Ecologia, Institute of Biology, University of Campinas UNICAMP, Institute for Ecosystem Research/Geobotany, Kiel University, School of Geography, Earth and Environmental Sciences [Birmingham], University of Birmingham [Birmingham], Justus-Liebig-Universität Gießen = Justus Liebig University (JLU), Global Ecology Unit CREAF-CEAB-CSIC, Universitat Autònoma de Barcelona (UAB), FFCLRP-USP, Department of Biology [USA], University of Maryland [College Park], University of Maryland System-University of Maryland System, University of A Coruña (UDC), School of Physics [UNSW Sydney] (UNSW), University of New South Wales [Sydney] (UNSW), Icahn School of Medicine at Mount Sinai [New York] (MSSM), University of Peking, Peking University [Beijing], Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), Ordu University - Ordu Üniversitesi, Lanzhou University, Universidad del Tolima, Research Centre for Forestry and Wood, Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics (CREA), Brazilian Agricultural Research Corporation (Embrapa), Universidade de São Paulo = University of São Paulo (USP), Centro Agronomico Tropical de Investigacion y Ensenanza (CATIE), Queensland University of Technology [Brisbane] (QUT), University of Sussex, Harvard University, Institute for Alpine Environment, European Academy of Bozen-Bolzano (EURAC), Étude et compréhension de la biodiversité (ECODIV), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Laboratoire de Physique Atmosphérique et Planétaire (LPAP), Université de Liège, Université de Sherbrooke (UdeS), Station d'écologie théorique et expérimentale (SETE), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, University of Manchester [Manchester], Universidade Estadual de Campinas = University of Campinas (UNICAMP), Macquarie University, Universidade Federal do Rio Grande do Norte [Natal] (UFRN), Universidad Rey Juan Carlos [Madrid] (URJC), Universidad Nacional de la Patagonia Austral (UNPA), Universidade Regional de Blumenau (FURB), INIA-CIFOR, Southern Illinois University [Carbondale] (SIU), Center for Biodiversity Management, Instituto Federal de Educação Ciência e Tecnologia do Cearà, The Morton Arboretum, United States Department of Agriculture (USDA), Swiss Federal Institute of Technology, Aarhus University [Aarhus], Smithsonian Conservation Biology Institute, Centre Supérieur de la Recherche Scientifique (CSIC), Centre Supérieur de la Recherche Scientifique, Universidad del Rosario [Bogota], Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU), Université Paris Sud (Paris 11), Senckenberg Research Institutes and Natural History Museums, Universidad de Chile = University of Chile [Santiago] (UCHILE), Joint Global Change Research Institute, Pacific Northwest National Laboratory (PNNL)-University of Maryland [College Park], Smithsonian Tropical Research Institute, University of Liege, Université de Liège - Gembloux, Institut Pasteur de Shanghai, Académie des Sciences de Chine - Chinese Academy of Sciences (IPS-CAS), Réseau International des Instituts Pasteur (RIIP), University of Bristol [Bristol], University of the Witwatersrand [Johannesburg] (WITS), Norwegian University of Life Sciences (NMBU), Murdoch University, Carnegie Museum of Natural History [Pittsburgh], Transilvania University of Brasov, Martin-Luther-University Halle-Wittenberg, Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Goethe-Universität Frankfurt am Main-Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association-Leibniz Association, Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche] (BOKU), Santa Catarina State University (UDESC), University Centre Myerscough, Kiel University, Florida International University [Miami] (FIU), Division of Plant Ststematic and Ecology, Biology department, Université Catholique de Louvain = Catholic University of Louvain (UCL), University of Applied Sciences of Weihenstephan, Four Peaks Environmental Science and Data Solutions, Norsk institutt for bioøkonomi=Norwegian Institute of Bioeconomy Research (NIBIO), Kochi University of Technology (KUT), University of Illinois [Chicago] (UIC), University of Illinois System, Universitat de Barcelona (UB), Kyoto University, Tyumen State University, Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, Universitat Politècnica de Catalunya [Barcelona] (UPC), Stanford University, University of Edinburgh, Polish Academy of Sciences (PAN), Philips Research Europe - Hamburg, Sector Medical Imaging Systems, Philips Research, Institute for Systematic Botany and Ecology, Universität Ulm - Ulm University [Ulm, Allemagne], Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Universität Bayreuth, University of Copenhagen = Københavns Universitet (UCPH), Guangxi Normal University, University College of London [London] (UCL), Hobart - Tasmania 7001, University of Venda [South Africa] (UNIVEN), University of Melbourne, Philipps Universität Marburg = Philipps University of Marburg, Agrosystèmes Cultivés et Herbagers (ARCHE), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse (ENSAT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT), Natural Resource Operations and Rural Development, Humboldt State University (HSU), Charles University [Prague] (CU), Karlsruhe Institute of Technology (KIT), Samara National Research University, Institute of Plant Sciences, Forestry and Forest Products Research Institute (FFPRI), Kenyon College, University of Garmian, State University of New York (SUNY), Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam [Amsterdam] (UvA), Universidad Nacional del Comahue [Neuquén] (UNCOMA), IT University of Copenhagen (ITU), Agricultural Research Organization, Landscape Ecology Group, University of Oldenburg, Western Carolina University, Xi'an Jiaotong-Liverpool University [Suzhou], Hokkaido University [Sapporo, Japan], Yokohama National University, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Institut d Estudis Andorrans, Smithsonian Environmental Research Center (SERC), Humboldt University Of Berlin, University of California [Los Angeles] (UCLA), Department of Biodiversity, Macroecology and Biogeography, Yamagata University, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Université du Québec en Abitibi-Témiscamingue (UQAT), University of Saskatchewan [Saskatoon] (U of S), University of Natural Resources and Life Sciences, Institute of Mountain Risk Engineering - Vienna, Austria, University of Wyoming (UW), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Nelson Mandela University [Port Elizabeth], University of Wisconsin - Eau Claire, Naturalis Biodiversity Center [Leiden], Département de biologie [Sherbrooke] (UdeS), Faculté des sciences [Sherbrooke] (UdeS), Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS), Yangzhou University, Leipzig University, University Pablo de Olavide, Shanghai Jiao Tong University [Shanghai], Royal Botanical Gardens, Masaryk University [Brno] (MUNI), Department of Physiology, University of Debrecen Egyetem [Debrecen]-Research Centre for Molecular Medicine-Medical and Health Science Centre, Global Change Research Centre (CzechGlobe), Université du Québec à Trois-Rivières (UQTR), Natural Resources Institute Finland (LUKE), Universidade Federal de Alagoas = Federal University of Alagoas (UFAL), Lakehead University, Stockholm University, Universidad Nacional del Litoral [Santa Fe] (UNL), Universidade Federal do Paraná (UFPR), Bangor University, Universidad Autonoma del Estado de Morelos (UAEM), Manaaki Whenua – Landcare Research [Lincoln], Gorongosa National Park, Université de Montréal (UdeM), Tel Aviv University (TAU), University of Queensland [Brisbane], University of Wisconsin-Madison, University of Maine, Holden Arboretum, Hawkesbury Institute for he Environment, Laboratoire d'Ecologie Végétale et Biogéochimie, Université libre de Bruxelles (ULB), University of British Columbia (UBC), Research School of Biology, Universidade Federal de Pernambuco [Recife] (UFPE), School of Geosciences [Edinburgh], Ecology and Evolutionary Biology [Tucson] (EEB), University of Debrecen, Northern Forestry Centre, Canadian Forest Service - CFS (CANADA), University of Illinois at Urbana-Champaign [Urbana], Data61 [Canberra] (CSIRO), Australian National University (ANU)-Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), University of Debrecen Egyetem [Debrecen], University of Vermont [Burlington], Fundação Zoobotânica do Rio Grande do Sul, University of Montana, Institut de RadioAstronomie Millimétrique (IRAM), Centre National de la Recherche Scientifique (CNRS), University of Freiburg [Freiburg], University of Hawaii, Institut Français de Pondichéry (IFP), Ministère de l'Europe et des Affaires étrangères (MEAE)-Centre National de la Recherche Scientifique (CNRS), Oklahoma State University [Stillwater] (OSU), Osaka City University, Charles Darwin Research Station (CDRS), Charles Darwin Foundation, Los Alamos National Laboratory (LANL), Zhejiang Normal University, European Academy of Bolzano, Universidad Distrital Francisco Jose de Caldas [Bogota], University of Bayreuth, Institute of Biology of Komi Scientific Centre of the Ural Branch of the Russian Academy of Sciences, Russian Academy of Sciences [Moscow] (RAS), CSIRO Land and Water, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), University of Canberra, CEH, Department of Systems and Science, Graduate School of Informatics, Kyoto University-Kyoto University, Departamento de Telemática, Faculdade de Engenharia Elétrica e de Computação (DT/FEEC), Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), Moscow State University, Vrije Universiteit Amsterdam [Amsterdam] (VU), Meijo University, Institute of Ecology and Earth Sciences [Tartu], Astronomical Institute of the Czech Academy of Sciences (ASU / CAS), University of Nijmegen, University of New England (UNE), The James Hutton Institute, Democritus University of Thrace (DUTH), Institute of Ecology and Earth Sciences, University of Tartu, Spanish National Research Council (CSIC), Senckenberg Research Institute and Natural History Museum, University of Vienna [Vienna], Center for Desertification Research (CIDE), Universitat de València (UV), Universidad Autónoma de Madrid (UAM), Université de Jaén, National Institute for Research and Development in Forestry, Department of Plant Production (University of Milan), Tartu Observatory, Botanical Garden of the Samara University, Forschungszentrum Jülich GmbH, Tallinn University, Universität Regensburg (REGENSBURG), Universität Regensburg, School of Social Sciences [Cardiff], Cardiff University, Estonian University of Life Sciences (EMU), Sch Life Sci Weihenstephan, Arizona State University [Tempe] (ASU), Department of Forest Resources, University of Minnesota System-University of Minnesota System, Research Institute for Networks and Communications Engineering (RINCE), Dublin City University [Dublin] (DCU)-Science Foundation Ireland-Enterprise Ireland-Higher Education Authority-School of Electronic Engineering, Southwest University of Science and Technology [Mianyang] (SWUST), Universidade Federal do Acre (UFAC), Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Centre méditérannéen de médecine moléculaire (C3M), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Mississippi State University [Mississippi], University of Southampton, Yale University [New Haven], Brookhaven National Laboratory [Upton, NY] (BNL), UT-Battelle, LLC-Stony Brook University [SUNY] (SBU), State University of New York (SUNY)-State University of New York (SUNY)-U.S. Department of Energy [Washington] (DOE), East Stroudsburg University, INDEHESA, Forestry School, Universidad de Extremadura - University of Extremadura (UEX), Institute of Physical Geography [Frankfurt am Main], Universität Zürich [Zürich] = University of Zurich (UZH), Lake Ecosystems Group [Lancaster, U.K.] (Centre for Ecology & Hydrology), Lancaster Environment Centre [Lancaster, U.K.], University of Valladolid, Norwegian Institute for Nature Research (NINA), Universidad Nacional de Colombia [Bogotà] (UNAL), Instituto de Recursos Naturales y Agrobiología de Salamanca (IRNASA), Universidade de Coimbra [Coimbra], Algoma University, Senckenberg biodiversität und klima forschungszentrum (BIK-F), Forschungsinstitut Senckenberg (SGN), University of Nottingham, UK (UON), University of Würzburg = Universität Würzburg, Agence Française de Sécurité Sanitaire des Aliments (AFSSA), Herencia, Kirstenbosch Research Centre, South African National Biodiversity Institute, Federal University of Pernambuco [Recife], Sharplex Services, University of Hohenheim, Komarov Botanical Institute RAS, Center for Sustainability Science, Hokkaido, Département de Biologie, University of Regina (UR), Technische Universität Ilmenau (TU ), Universidade de Lisboa = University of Lisbon (ULISBOA), Universidade Federal de Lavras = Federal University of Lavras (UFLA), Università degli Studi di Padova = University of Padua (Unipd), Gothenburg Global Biodiversity Centre, Department of Biology [Gainesville] (UF|Biology), Texas Tech University [Lubbock] (TTU), Florida Museum of Natural History [Gainesville], KU Leuven, Embrapa Recursos Genéticos e Biotecnologia [Brasília], Universiteit Leiden, University of California [Riverside] (UC Riverside), Pacific Northwest National Laboratory (PNNL), University of Natural Resources and Applied Life Sciences, Vienna, (BOKU) and Competence Centre Wood K plus, University of Novi Sad, Instituto Nacional de Investigaciones en Biodiversidad y Medioambiente [Bariloche] (INIBIOMA-CONICET), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Universidad Nacional del Comahue [Neuquén] (UNCOMA), Slovak Academy of Sciences (SAS), Technical University in Zvolen (TUZVO), Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague (CZU), University of Aberdeen, University of Maryland System, Universität Innsbruck [Innsbruck], Estacion Experimental de Zonas Aridas, Hacettepe University = Hacettepe Üniversitesi, Centre for Forest Research (CFR), Université du Québec à Montréal = University of Québec in Montréal (UQAM), Bioversity International [Montpellier], Bioversity International [Rome], Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Department of Animal and Plant Sciences [Sheffield], University of Sheffield [Sheffield], The School for Field Studies, Quantum Optics and Laser Science, Blackett Laboratory, Blackett Laboratory, Imperial College London-Imperial College London, University of Delaware [Newark], Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Biodiversity and Ecosystem Services Research Group, Stellenbosch University, Czech University of Life Science, Aristotle University of Thessaloniki, Osaka Natural History Center, Ural State Forest Engineering University, University of New Hampshire (UNH), University of Calgary, Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Hawkesbury Institute for the Environment [Richmond] (HIE), Computational & Applied Vegetation Ecology (CAVElab), Dept Forest & Water Management, Lab Forestry, Museu Paraense Emílio Goeldi, Federal University of Para - Universidade Federal do Pará - UFPA [Belém, Brazil] (UFPA), State Key Laboratory of Natural and Biomimetic Drugs, Fudan University [Shanghai], Department of Ecological Science [Amsterdam], Vrije Universiteit Brussel (VUB), Laboratoire de Biologie des Ligneux et des Grandes Cultures (LBLGC), Université d'Orléans (UO)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Biology, Free University of Bozen-Bolzano, Dpt Biological Sciences, Macquarie University, Duke University [Durham], IFP Energies nouvelles (IFPEN), Department of Primary Industries, Graduate School of Integrated Arts and Sciences, Hiroshima University, Université de Tsukuba = University of Tsukuba, SUNY College of Environmental Science and Forestry (SUNY-ESF), Biological Sciences Department (BIOLOGICAL SCIENCES DEPARTMENT), Nanjing University (NJU), National Taiwan University [Taiwan] (NTU), Zhejiang University, Beijing Forestry University, Institut National Polytechnique Félix Houphouët-Boigny, Universität Leipzig, Max Planck Fellow Program for Christian Wirth, the International Programme of Biodiversity Science (DIVERSITAS), the International Geosphere‐Biosphere Programme (IGBP), Future Earth, the French Foundation for Biodiversity Research (FRB), and GIS ‘Climat, Environnement et Société’ France, JENS KATTGE, MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY, GERMANY, ELLEN L. FRY, UNIVERSITY OF LIÈGE, BELGIUM, NIKOLAOS M. FYLLAS, UNIVERSITY OF THE AEGEAN, GREECE, GERHARD BÖNISCH, MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY, GERMANY, SUSANNE TAUTENHAHN, MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY, JENA, GERMANY, GIJSBERT D. A. WERNER, UNIVERSITY OF OXFORD, OXFORD, UK, TUOMAS AAKALA, UNIVERSITY OF HELSINKI, FINLAND, MEHDI ABEDI, TARBIAT MODARES UNIVERSITY, IRAN, ALICIA T. R. ACOSTA, UNIVERSITY OF ROMA TRE, ITALY, GEORGE C. ADAMIDIS, UNIVERSITY OF BERN, SWITZERLAND, KAIRI ADAMSON, UNIVERSITY OF TARTU, ESTONIA, MASAHIRO AIBA, TOHOKU UNIVERSITY, JAPAN., CÉCILE H. ALBERT, AIX MARSEILLE UNIV, UNIV AVIGNON, FRANCE., JULIO M. ALCÁNTARA, UNIVERSIDAD DE JAÉN, SPAIN, CAROLINA ALCÁZAR C, Instituto Alexander Von Humboldt, Colombia., HAMADA ALI, SUEZ CANAL UNIVERSITY, EGYPT, BERNARD AMIAUD, UNIVERSITÉ DE LORRAINE, FRANCE., CHRISTIAN AMMER, UNIVERSITY OF GÖTTINGEN, GERMANY, MARIANO M. AMOROSO, UNIVERSIDAD NACIONAL DE RÍO NEGRO, ARGENTINA, MADHUR ANAND, UNIVERSITY OF GUELPH, CANADA., MARIJN BAUTERS, GHENT UNIVERSITY, BELGIUM., ERIKA BAZZATO, UNIVERSITY OF CAGLIARI, ITALY., MICHAEL BECKMANN, Helmholtz Centre for Environmental Research, Germany., HANS BEECKMAN, ROYAL MUSEUM FOR CENTRAL AFRICA, BELGIUM., CARL BEIERKUHNLEIN, UNIVERSITY OF BAYREUTH, GERMANY., RENEE BEKKER, UNIVERSITY OF GRONINGEN, THE NETHERLANDS., JOANA BERGMANN, FREIE UNIVERSITÄT BERLIN, GERMANY., MARCOS BERGMANN CARLUCCI, UFPC, LOGAN BERNER, NORTHERN ARIZONA UNIVERSITY, USA., MARKUS BERNHARDT-RÖMERMANN, FRIEDRICH SCHILLER UNIVERSITY JENA, GERMANY., CHRISTOF BIGLER, ETH ZURICH, SWITZERLAND., FEDERICO BRUMNICH, UNIVERSIDAD NACIONAL DEL LITORAL (FICH-UNL), ARGENTINA, HANS HENRIK BRUUN, UNIVERSITY OF COPENHAGEN, DENMARK, DAVID BRUY, UNIVERSITÉ DE MONTPELLIER, FRANCE, SERRA W. BUCHANAN, UNIVERSITY OF TORONTO SCARBOROUGH, CANADA, ROBERT BUITENWERF, AARHUS UNIVERSITY, DENMARK, DANIEL E. BUNKER, NEW JERSEY INSTITUTE OF TECHNOLOGY, USA, JANA BÜRGER, UNIVERSITY OF ROSTOCK, GERMANY, SABINA BURRASCANO, SAPIENZA UNIVERSITY OF ROME, ITALY, DAVID F. R. P. BURSLEM, UNIVERSITY OF ABERDEEN, UK, BRADLEY J. BUTTERFIELD, NORTHERN ARIZONA UNIVERSITY, USA, CHAEHO BYUN, YONSEI UNIVERSITY, KOREA, MARINA C. SCALON, UFP, MARCO CACCIANIGA, UNIVERSITÀ DEGLI STUDI DI MILANO, ITALY, MARC CADOTTE, UNIVERSITY OF TORONTO SCARBOROUGH, CANADA, MAXIME CAILLERET, AIX?MARSEILLE UNIVERSITY, FRANCE, JAMES CAMAC, THE UNIVERSITY OF MELBOURNE, AUSTRALIA, JESÚS JULIO CAMARERO, INSTITUTO PIRENAICO DE ECOLOGÍA (IPE?CSIC), SPAIN, COURTNEY CAMPANY, COLGATE UNIVERSITY, USA, GIANDIEGO CAMPETELLA, UNIVERSITY OF CAMERINO, ITALY, JUAN ANTONIO CAMPOS, UNIVERSITY OF THE BASQUE COUNTRY UPV/EHU, SPAIN, LAURA CANO-ARBOLEDA, UNIVERSIDAD NACIONAL DE COLOMBIA, COLOMBIA, ROBERTO CANULLO, UNIVERSITY OF CAMERINO, ITALY, MICHELE CARBOGNANI, UNIVERSITY OF PARMA, ITALY, FABIO CARVALHO, LANCASTER UNIVERSITY, UK, BASTIEN CASTAGNEYROL, UNIV. BORDEAUX, FRANCE, JANE A. CATFORD, KING'S COLLEGE LONDON, UK, JEANNINE CAVENDER-BARES, UNIVERSITY OF MINNESOTA, USA, BRUNO E. L. CERABOLINI, UNIVERSITY OF INSUBRIA, ITALY, MARCO CERVELLINI, UNIVERSITY OF BOLOGNA, ITALY, EDUARDO CHACÓN-MADRIGAL, UNIVERSIDAD DE COSTA RICA, COSTA RICA, KENNETH CHAPIN, THE UNIVERSITY OF ARIZONA, USA, SAMANTHA DAWSON, SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES, AREND JACOBUS DE BEER, UNIVERSITY OF PRETORIA, SOUTH AFRICA, ANGEL DE FRUTOS, HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH, GERMANY, LEANDRO DUARTE, UFRGS, EMILIE DUCOURET, UMR ECOFOG (AGROPARISTECH, CNRS, INRA, UNIVERSITÉ DES ANTILLES, UNIVERSITÉ DE LA GUYANE), FRANCE, STEFAN DULLINGER, UNIVERSITY OF VIENNA, AUSTRIA, DAN F. B. FLYNN, ARNOLD ARBORETUM OF HARVARD UNIVERSITY, USA, VERONIKA FONTANA, INSTITUTE FOR ALPINE ENVIRONMENT, ITALY, KYONG-SOOK CHUNG, JUNGWON UNIVERSITY, KOREA, MILAN CHYTRÝ, MASARYK UNIVERSITY, CZECH REPUBLIC, DANIELA CICCARELLI, UNIVERSITY OF PISA, ITALY, LLUÍS COLL, UNIVERSITY OF LLEIDA, SPAIN, COURTNEY G. COLLINS, UNIVERSITY OF CALIFORNIA RIVERSIDE, USA, LUISA CONTI, UNIVERSITY OF LIFE SCIENCES PRAGUE, CZECH REPUBLIC, DAVID COOMES, UNIVERSITY OF CAMBRIDGE, UK, JOHANNES H. C. CORNELISSEN, VRIJE UNIVERSITEIT, THE NETHERLANDS, WILLIAM K. CORNWELL, EARTH AND ENVIRONMENTAL SCIENCES, AUSTRALIA, PIERMARIA CORONA, CREA – RESEARCH CENTRE FOR FORESTRY AND WOOD, ITALY, MARIE COYEA, UNIVERSITÉ LAVAL, CANADA, JOSEPH CRAINE, JONAH VENTURES, USA, DYLAN CRAVEN, UNIVERSIDAD MAYOR, CHILE, JORIS P. G. M. CROMSIGT, SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES, SWEDEN, ANIKÓ CSECSERITS, MTA CENTRE FOR ECOLOGICAL RESEARCH, HUNGARY, KATARINA CUFAR, UNIVERSITY OF LJUBLJANA, SLOVENIA, MATTHIAS CUNTZ, UNIVERSITÉ DE LORRAINE, FRANCE, ANA CAROLINA DA SILVA, SANTA CATARINA STATE UNIVERSITY, BRAZIL, KYLA M. DAHLIN, MICHIGAN STATE UNIVERSITY, USA, MATTEO DAINESE, INSTITUTE FOR ALPINE ENVIRONMENT, ITALY, IGOR DALKE, INSTITUTE OF BIOLOGY OF KOMI SCIENCE CENTRE OF THE URAL BRANCH OF THE RUSSIAN ACADEMY OF SCIENCES, RUSSIA, MICHELE DALLE FRATTE, UNIVERSITY OF INSUBRIA, ITALY, ANH TUAN DANG-LE, UNIVERSITY HO CHI MINH CITY, VIETNAM, JIRÍ DANIHELKA, MASARYK UNIVERSITY, CZECH REPUBLIC, MASAKO DANNOURA, KYOTO UNIVERSITY, JAPAN, JONATHAN R. DE LONG, NETHERLANDS INSTITUTE OF ECOLOGY, THE NETHERLANDS, BENJAMIN DECHANT, SEOUL NATIONAL UNIVERSITY, REPUBLIC OF KOREA, SYLVAIN DELAGRANGE, INSTITUTE OF TEMPERATE FOREST SCIENCES (ISFORT), CANADA, NICOLAS DELPIERRE, UNIVERSITY OF PARIS?SUD, FRANCE, GÉRALDINE DERROIRE, UNIVERSITÉ DES ANTILLES, FRANCE, ARILDO S. DIAS, UNIVERSITÄT FRANKFURT, GERMANY, MILTON HUGO DIAZ-TORIBIO, UNIVERSITY OF FLORIDA, USA, PANAYIOTIS G. DIMITRAKOPOULOS, UNIVERSITY OF THE AEGEAN, GREECE, MARK DOBROWOLSKI, THE UNIVERSITY OF WESTERN AUSTRALIA, AUSTRALIA, DANIEL DOKTOR, HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH – UFZ, GERMANY, PAVEL DREVOJAN, MASARYK UNIVERSITY, CZECH REPUBLIC, NING DONG, MACQUARIE UNIVERSITY, AUSTRALIA, JOHN DRANSFIELD, ROYAL BOTANIC GARDENS KEW, UK, STEFAN DRESSLER, DEPARTMENT OF BOTANY AND MOLECULAR EVOLUTION, GERMANY, WALTER DURKA, GERMAN CENTER FOR INTEGRATIVE BIODIVERSITY RESEARCH (IDIV) HALLE?JENA?LEIPZIG, GERMANY, REMKO DUURSMA, WESTERN SYDNEY UNIVERSITY, AUSTRALIA, OLGA DYMOVA, KOMI REPUBLIC, RUSSIA, E-VOJTKÓ, A., UNIVERSITY OF SOUTH BOHEMIA, CZECH REPUBLIC, ROLF LUTZ ECKSTEIN, KARLSTAD UNIVERSITY, SWEDEN, HAMID EJTEHADI, FERDOWSI UNIVERSITY OF MASHHAD, IRAN, JAMES ELSER, UNIVERSITY OF MONTANA, USA, THAISE EMILIO, UNIVERSITY OF CAMPINAS UNICAMP, BRAZIL, KRISTINE ENGEMANN, AARHUS UNIVERSITY, DENMARK, MOHAMMAD BAGHER ERFANIAN, FERDOWSI UNIVERSITY OF MASHHAD, IRAN, ALEXANDRA ERFMEIER, KIEL UNIVERSITY, KIEL, GERMANY, ADRIANE ESQUIVEL-MUELBERT, EARTH AND ENVIRONMENTAL SCIENCES, AUSTRALIA, GERD ESSER, JUSTUS LIEBIG UNIVERSITY, GERMANY, MARC ESTIARTE, SPANISH NATIONAL RESEARCH COUNCIL – CSIC, SPAIN, TOMAS F. DOMINGUES, DEPARTMENT OF BIOLOGY – FFCLRP/USP, BRAZIL, WILLIAM F. FAGAN, UNIVERSITY OF MARYLAND, USA, JAIME FAGÚNDEZ, UNIVERSITY OF A CORUÑA, SPAIN, DANIEL S. FALSTER, EVOLUTION & ECOLOGY RESEARCH CENTRE, AUSTRALIA, YING FAN, RUTGERS UNIVERSITY, USA, JINGYUN FANG, PEKING UNIVERSITY, CHINA, EMMANUELE FARRIS, UNIVERSITY OF SASSARI, ITALY, FATIH FAZLIOGLU, ORDU UNIVERSITY, TURKEY, YANHAO FENG, LANZHOU UNIVERSITY, CHINA, FERNANDO FERNANDEZ-MENDEZ, UNIVERSIDAD DEL TOLIMA, COLOMBIA, CARLOTTA FERRARA, CREA – RESEARCH CENTRE FOR FORESTRY AND WOOD, ITALY, JOICE NUNES FERREIRA, CPATU, ALESSANDRA FIDELIS, (UNESP), RIO CLARO, BRAZIL, BRYAN FINEGAN, CATIE-CENTRO AGRONÓMICO TROPICAL DE INVESTIGACIÓN Y ENSEÑANZA, COSTA RICA, JENNIFER FIRN, QUEENSLAND UNIVERSITY OF TECHNOLOGY (QUT), AUSTRALIA, TIMOTHY J. FLOWERS, UNIVERSITY OF SUSSEX, UK, ESTELLE FOREY, UNIVERSITÉ DE ROUEN, FRANCE, CRISTIANE FORGIARINI, UFRGS, BRAZIL., LOUIS FRANÇOIS, UNIVERSITY OF LIÈGE, BELGIUM., MARCELO FRANGIPANI, UFRGS, BRAZIL, DOROTHEA FRANK, MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY, GERMANY, CEDRIC FRENETTE-DUSSAULT, GÉOPOLE DE L'UNIVERSITÉ DE SHERBROOKE, CANADA, GRÉGOIRE T. FRESCHET, PAUL SABATIER UNIVERSITY TOULOUSE, FRANCE, PAUL LEADLEY, UNIVERSITY OF PARIS-SUD, UNIVERSITÉ PARIS-SACLAY, ORSAY, FRANCE, IZABELA ALEIXO, NATIONAL INSTITUTE OF AMAZONIAN RESEARCH (INPA), BRAZIL, SANDRA DÍAZ, UNIVERSIDAD NACIONAL DE CÓRDOBA, ARGENTINA, SANDRA LAVOREL, UNIV. SAVOIE MONT BLANC, LECA, GRENOBLE, FRANCE, IAIN COLIN PRENTICE, IMPERIAL COLLEGE, UK., CAROLYN ANDERSON, UNIVERSITY OF MASSACHUSETTS AMHERST, USA, NIELS ANTEN, WAGENINGEN UNIVERSITY, THE NETHERLANDS, JOSEPH ANTOS, UNIVERSITY OF VICTORIA, CANADA, DEBORAH MATTOS GUIMARÃES APGAUA, JAMES COOK UNIVERSITY, AUSTRALIA, TIA-LYNN ASHMAN, UNIVERSITY OF PITTSBURGH, USA, DEGI HARJA ASMARA, UNIVERSITÉ LAVAL, CANADA, GREGORY P. ASNER, ARIZONA STATE UNIVERSITY, USA., MICHAEL ASPINWALL, UNIVERSITY OF NORTH FLORIDA, USA., OWEN ATKIN, AUSTRALIAN NATIONAL UNIVERSITY, AUSTRALIA., ISABELLE AUBIN, NATURAL RESOURCES CANADA, LARS BAASTRUP-SPOHR, UNIVERSITY OF COPENHAGEN, DENMARK., KHADIJEH BAHALKEH, TARBIAT MODARES UNIVERSITY, IRAN., MICHAEL BAHN, UNIVERSITY OF INNSBRUCK, AUSTRIA., TIMOTHY BAKER, UNIVERSITY OF LEEDS, LEEDS, UK., WILLIAM J. BAKER, ROYAL BOTANIC GARDENS KEW, UK., JAN P. BAKKER, UNIVERSITY OF GRONINGEN, THE NETHERLANDS., DENNIS BALDOCCHI, UNIVERSITY OF CALIFORNIA BERKELEY, USA., JENNIFER BALTZER, WILFRID LAURIER UNIVERSITY, CANADA, ARINDAM BANERJEE, UNIVERSITY OF MINNESOTA, USA., ANNE BARANGER, AGROPARISTECH, FRANCE., JOS BARLOW, LANCASTER UNIVERSITY, UK., DIEGO R. BARNECHE, UNIVERSITY OF EXETER, UK., ZDRAVKO BARUCH, THE UNIVERSITY OF ADELAIDE, AUSTRALIA., DENIS BASTIANELLI, UNIV MONTPELLIER, FRANCE., JOHN BATTLES, UNIVERSITY OF CALIFORNIA AT BERKELEY, USA, WILLIAM BAUERLE, COLORADO STATE UNIVERSITY, USA, SOLVEIG FRANZISKA BUCHER, FRIEDRICH?SCHILLER?UNIVERSITÄT JENA, GERMANY, GAVIN BELFRY, UNIVERSITY OF TENNESSEE, USA., MICHAEL BELLUAU, UNIVERSITÉ DU QUÉBEC À MONTRÉAL, CANADA., MIRELA BELOIU, UNIVERSITY OF BAYREUTH, GERMANY., RAQUEL BENAVIDES, MUSEO NACIONAL DE CIENCIAS NATURALES-CSIC, SPAIN., LAHCEN BENOMAR, UNIVERSITÉ LAVAL, CANADA., MARY LEE BERDUGO-LATTKE, UNIVERSIDAD NACIONAL DE COLOMBIA, COLOMBIA., ERIKA BERENGUER, UNIVERSITY OF OXFORD, UK., RODRIGO BERGAMIN, UFRS, NINA BUCHMANN, ETH ZURICH, ZURICH, SWITZERLAND, ANNE D. BJORKMAN, UNIVERSITY OF GOTHENBURG, SWEDEN., CHRIS BLACKMAN, UNIVERSITÉ CLERMONT-AUVERGNE, FRANCE., CAROLINA BLANCO, UFRGS, BENJAMIN BLONDER, ARIZONA STATE UNIVERSITY, USA., DANA BLUMENTHAL, USDA-ARS RANGELAND RESOURCES & SYSTEMS RESEARCH UNIT, USA., KELLY T. BOCANEGRA-GONZÁLEZ, UNIVERSIDAD DEL TOLIMA, COLOMBIA., PASCAL BOECKX, GHENT UNIVERSITY, BELGIUM., STEPHANIE BOHLMAN, UNIVERSITY OF FLORIDA, USA., KATRIN BÖHNING-GAESE, UNIVERSITÄT FRANKFURT, GERMANY., LAURA BOISVERT-MARSH, UNIVERSITÄT FRANKFURT, GERMANY., WILLIAM BOND, UNIVERSITY OF CAPE TOWN, SOUTH AFRICA., BEN BOND-LAMBERTY, COLLEGE PARK, USA., ARNOUD BOOM, UNIVERSITY OF LEICESTER, UK., COLINE C. F. BOONMAN, RADBOUD UNIVERSITY, THE NETHERLANDS., KAUANE BORDIN, UFRGS, ELIZABETH H. BOUGHTON, ARCHBOLD BIOLOGICAL STATION'S BUCK ISLAND RANCH, USA., VANESSA BOUKILI, UNIVERSITY OF CONNECTICUT, USA, DAVID M. J. S. BOWMAN, UNIVERSITY OF TASMANIA, AUSTRALIA., SANDRA BRAVO, UNIVERSIDAD NACIONAL DE SANTIAGO DEL ESTERO, MARCO RICHARD BRENDEL, UNIVERSITY OF HOHENHEIM, MARTIN R. BROADLEY, UNIVERSITY OF NOTTINGHAM, UK, KERRY A. BROWN, KINGSTON UNIVERSITY, UK., HELGE BRUELHEIDE, MARTIN LUTHER UNIVERSITY HALLE?WITTENBERG, GERMANY, FERNANDO CASANOVES, CATIE-CENTRO AGRONÓMICO TROPICAL DE INVESTIGACIÓN Y ENSEÑANZA, COSTA RICA, F. STUART CHAPIN, UNIVERSITY OF ALASKA FAIRBANKS, USA, STEFANO CHELLI, UNIVERSITY OF CAMERINO, ITALY, SI?CHONG CHEN, ROYAL BOTANIC GARDENS, UK, ANPING CHEN, COLORADO STATE UNIVERSITY, USA, PAOLO CHERUBINI, UNIVERSITY OF BRITISH COLUMBIA, CANADA, FRANCESCO CHIANUCCI, CREA – RESEARCH CENTRE FOR FORESTRY AND WOOD, ITALY, BRENDAN CHOAT, WESTERN SYDNEY UNIVERSITY, AUSTRALIA, GUILHERME G. MAZZOCHINI, UNIVERSITY OF CAMPINAS, CAMPINAS, BRAZIL, SOPHIE GACHET, UNIV AVIGNON, FRANCE, RACHAEL GALLAGHER, MACQUARIE UNIVERSITY, AUSTRALIA, GISLENE GANADE, UFRN, BRAZIL., MARY-CLAIRE GLASENHARDT, THE MORTON ARBORETUM, USA, ALAIN HAMBUCKERS, UNIVERSITY OF LIÈGE, BELGIUM, MASAE ISHIHARA, KYOTO UNIVERSITY, JAPAN, LEONID IVANOV, TYUMEN STATE UNIVERSITY, RUSSIA, LARISSA IVANOVA, TYUMEN STATE UNIVERSITY, RUSSIA., COLLEEN M. IVERSEN, OAK RIDGE NATIONAL LABORATORY, USA, JORDI IZQUIERDO, Universitat Politècnica de Catalunya, Spain, ROBERT B. JACKSON, STANFORD UNIVERSITY, USA, FRANCESCA GANGA, UNIVERSITY OF CAGLIARI, ITALY, PABLO GARCÍA-PALACIOS, UNIVERSIDAD REY JUAN CARLOS, SPAIN, VERÓNICA GARGAGLIONE, UNIVERSIDAD NACIONAL DE LA PATAGONIA AUSTRAL, ARGENTINA, ERIC GARNIER, UNIV. MONTPELLIER, FRANCE, JOSE LUIS GARRIDO, ESTACIÓN EXPERIMENTAL DEL ZAIDÍN, SPAIN, ANDRÉ LUÍS DE GASPER, UNIVERSIDADE REGIONAL DE BLUMENAU, BRAZIL, GUILLERMO GEAIZQUIERDO, INIA?CIFOR, SPAIN, DAVID GIBSON, SOUTHERN ILLINOIS UNIVERSITY CARBONDALE, USA, ANDREW N. GILLISON, CENTER FOR BIODIVERSITY MANAGEMENT, AUSTRALIA, AELTON GIROLDO, INSTITUTO FEDERAL DE EDUCAÇÃO CIÊNCIA E TECNOLOGIA DO CEARÁ, BRAZIL, SEAN GLEASON, WATER MANAGEMENT AND SYSTEMS RESEARCH UNIT, USA, MARIANA GLIESCH, INSTITUTE OF INTEGRATIVE BIOLOGY, SWITZERLAND, EMMA GOLDBERG, UNIVERSITY OF MINNESOTA, USA, BASTIAN GÖLDEL, AARHUS UNIVERSITY, DENMARK, ERIKA GONZALEZ-AKRE, NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY NTNU, NORWAY, JOSE L. GONZALEZ-ANDUJAR, CSIC-INSTITUTE FOR SUSTAINABLE AGRICULTURE (IAS), SPAIN, ANDRÉS GONZÁLEZ-MELO, UNIVERSIDAD DEL ROSARIO, COLOMBIA, ANA GONZÁLEZ-ROBLES, UNIVERSIDAD DE JAÉN, SPAIN, BENTE JESSEN GRAAE, NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY NTNU, NORWAY, ELENA GRANDA, UNIVERSITY OF ALCALÁ, SPAIN, SARAH GRAVES, UNIVERSITY OF FLORIDA, USA, WALTON A. GREEN, HARVARD UNIVERSITY, USA, THOMAS GREGOR, SENCKENBERG RESEARCH INSTITUTE AND NATURAL HISTORY MUSEUM, GERMANY, NICOLAS GROSS, UNIVERSIDAD REY JUAN CARLOS, SPAIN, GREG R. GUERIN, THE UNIVERSITY OF ADELAIDE, AUSTRALIA, ANGELA GÜNTHER, MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY, GERMANY, ALVARO G. GUTIÉRREZ, UNIVERSIDAD DE CHILE, CHILE, LILLIE HADDOCK, COLLEGE PARK, USA, ANNA HAINES, THE UNIVERSITY OF MANCHESTER, UK, JEFFERSON HALL, SMITHSONIAN TROPICAL RESEARCH INSTITUTE, REPUBLIC OF PANAMA, WENXUAN HAN, CHINA AGRICULTURAL UNIVERSITY, CHINA, SANDY P. HARRISON, UNIVERSITY OF READING, UK, WESLEY HATTINGH, UNIVERSITY OF THE WITWATERSRAND, SOUTH AFRICA, JOSEPH E. HAWES, ANGLIA RUSKIN UNIVERSITY, UK, TIANHUA HE, CURTIN UNIVERSITY, AUSTRALIA, PENGCHENG HE, CHINESE ACADEMY OF SCIENCES, CHINA, JACOB MASON HEBERLING, CARNEGIE MUSEUM OF NATURAL HISTORY, USA, AVELIINA HELM, UNIVERSITY OF TARTU, ESTONIA, STEFAN HEMPEL, FREIE UNIVERSITÄT BERLIN, GERMANY, JÖRN HENTSCHEL, FRIEDRICH-SCHILLER-UNIVERSITÄT JENA, GERMANY, BRUNO HÉRAULT, UNIVERSITÉ DE MONTPELLIER, FRANCE, ANA-MARIA HERE, TRANSILVANIA UNIVERSITY OF BRASOV, ROMANIA, KATHARINA HERZ, MARTIN LUTHER UNIVERSITY HALLE?WITTENBERG, GERMANY, MYRIAM HEUERTZ, UNIV. BORDEAUX, FRANCE, THOMAS HICKLER, GOETHE UNIVERSITY, GERMANY, PETER HIETZ, UNIVERSITY OF NATURAL RESOURCES AND LIFE SCIENCES, AUSTRIA, PEDRO HIGUCHI, SANTA CATARINA STATE UNIVERSITY, BRAZIL, ANDREW L. HIPP, THE MORTON ARBORETUM, USA, ANDREW HIRONS, UNIVERSITY CENTRE MYERSCOUGH, UK, MARIA HOCK, INSTITUTE FOR ECOSYSTEM RESEARCH/GEOBOTANY, GERMANY, JAMES AARON HOGAN, FLORIDA INTERNATIONAL UNIVERSITY, USA, KAREN HOLL, UNIVERSITY OF CALIFORNIA, USA, OLIVIER HONNAY, PLANT CONSERVATION AND POPULATION BIOLOGY, BELGIUM, KNUT ANDERS HOVSTAD, DEPARTMENT OF LANDSCAPE AND BIODIVERSITY, NORWAY, TOMOAKI ICHIE, KOCHI UNIVERSITY, JAPAN, BORIS IGIC, UNIVERSITY OF ILLINOIS AT CHICAGO, USA, ESTELA ILLA, UNIVERSITAT DE BARCELONA, SPAIN, MARNEY ISAAC, UNIVERSITY OF TORONTO, CANADA, BENJAMIN JACKSON, UNIVERSITY OF EDINBURGH, SCOTLAND, HERVÉ JACTEL, UNIV. BORDEAUX, FRANCE, ANDRZEJ M. JAGODZINSKI, UNIVERSITY OF LIFE SCIENCES, POLAND, UTE JANDT, MARTIN LUTHER UNIVERSITY HALLE-WITTENBERG, GERMANY, STEVEN JANSEN, ULM UNIVERSITY, GERMANY, THOMAS, University of Oxford [Oxford], University of Helsinki, Tarbiat Modaras University, Roma Tre University, Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), Centre for Biodiversity and Sustainable Land-use, University of Göttingen, Göttingen, Germany, Department of Biology, University of North Florida, Jacksonville, FL, USA, University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), Department of Range Management, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Iran, University of Innsbruck, School of Geography, University of Leeds, Leeds, UK, Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn, UK., School of Biological Sciences, The University of Adelaide, Adelaide, SA, Australia, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of California at Berkeley, Berkeley, CA, USA, Department of Green Chemistry and Technology, Ghent University, Gent, Belgium, Department of Environment, Ghent University, Gent, Belgium, Department of Life and Environmental Sciences, Botany Division, University of Cagliari, Cagliari, Italy, Museo Nacional de Ciencias Naturales-CSIC, Madrid, Spain, Environmental Change Institute, University of Oxford, Oxford, UK, Institut für Biologie, Freie Universität Berlin, Berlin, Germany, Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil, Universiteit Gent = Ghent University [Belgium] (UGENT), School of Geography, Geology and Environment, University of Leicester, Leicester, UK, Institute of Landscape and Plant Ecology, University of Hohenheim, Stuttgart, Germany, Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Halle, Germany, German Center for Integrative Biodiversity Research (iDiv) Halle-Jena- Leipzig, Leipzig, Germany, University of Toronto [Scarborough, Canada], Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany, Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], Dipartimento di Bioscienze, Università degli Studi di Milano, Milano, Italy, Department of Plant Biology and Ecology, University of the Basque Country UPV/ EHU, Bilbao, Spain, Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy, Department of Biotechnology and Life Sciences, University of Insubria, Varese, Italy, BIGEA, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum – University of Bologna, Bologna, Italy, Escuela de Biología, Universidad de Costa Rica, San José, Costa Rica, The University of Arizona, Tucson, AZ, USA, University of Alaska [Anchorage], Royal Botanic Gardens, Kew, Department of Biology, University of Pisa, Pisa, Italy, Department of Plant Sciences, University of Cambridge, Cambridge, UK, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia, Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-AgroParisTech, Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa, Department of Landscape Architecture and Rural Systems Engineering, Seoul National University, Seoul, Republic of Korea, Department of Botany and Biodiversity Research, University of Vienna, Department of Environmental and Life Sciences – Biology, Karlstad University, Quantitative Plant Ecology and Biodiversity Research Laboratory, Department of Biology, Faculty of Science, Ferdowsi University of Mashhad, Justus Liebig University, Justus-Liebig-Universität Gießen (JLU), University of Sassari, Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria (CREA), Universidade de São Paulo (USP), Harvard University [Cambridge], Federal University of Rio Grande do Sul, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), University of Campinas [Campinas] (UNICAMP), University of Cagliari, Universidad de Chile, University of Natural Resources and Life Sciences (BOKU), University of California, Norwegian Institute of Bioeconomy Research (NIBIO), Kyoto University [Kyoto], Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), University of Copenhagen = Københavns Universitet (KU), University of Venda, Philipps University of Marburg, Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, State University of New York, Stonybrook, IT University of Copenhagen, Smithsonian Environmental Research Center, Humboldt University of Berlin, Georg-August-University [Göttingen], Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Nelson Mandela Metropolitan University [Port Elizabeth, South Africa], Netherlands Centre for Biodiversity Naturalis, University of Leipzig [Leipzig, Allemagne], Unité d'Agronomie, University of Debrecen-Research Centre for Molecular Medicine-Medical and Health Science Centre, Global Change Research Institute, University of California [Berkeley], Natural resources institute Finland, Universita degli Studi di Cagliari [Cagliari], Tel Aviv University [Tel Aviv], Oklahoma State University [Stillwater], Kyoto University [Kyoto]-Kyoto University [Kyoto], Universidade Estadual de Campinas (UNICAMP), Universidad Nacional Autónoma de México (UNAM), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Universidad Autonoma de Madrid (UAM), University of Parma = Università degli studi di Parma [Parme, Italie], University of Milan, Forschungszentrum Juelich, Université Nice Sophia Antipolis (... - 2019) (UNS), U.S. Department of Energy [Washington] (DOE)-UT-Battelle, LLC-Stony Brook University [SUNY] (SBU), State University of New York (SUNY)-State University of New York (SUNY), University of Extremadura, University of Göttingen - Georg-August-Universität Göttingen, Universidade de Lisboa (ULISBOA), Federal University of Lavras, Universita degli Studi di Padova, Leiden University, University of California [Riverside] (UCR), Ferdowsi University of Mashhad, Museo Nacional de Ciencias Naturales (MNCN), Departments of Botany and Zoology, Federal University of Para - Universidade Federal do Para [Belem - Brésil], Institut National de la Recherche Agronomique (INRA)-Université d'Orléans (UO), Institut national polytechnique Félix Houphouët-Boigny, Universität Leipzig [Leipzig], Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA), Consejo Nacional de Investigaciones Científicas y Técnicas, Instituto Multidisciplinario de Biología Vegetal (IMBIV), and Factulad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina, Laboratoire d'Ecologie Alpine (LECA), Centre National de la Recherche Scientifique (CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Joseph Fourier - Grenoble 1 (UJF)-Université Grenoble Alpes (UGA), Imperial College London, London SW7 2AZ, UK., Department of Zoology, University of Oxford, Oxford, UK, Balliol College, University of Oxford, Oxford, UK, University of Roma Tre, Rome, Italy, Biodiversity Conservation Laboratory, Department of Environment, University of the Aegean, Mytilene, Greece, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland, Tartu Observatory, University of Tartu, Tartumaa, Estonia, Graduate School of Life Sciences, Tohoku University, Sendai, Japan, Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UMR237-Aix Marseille Université (AMU)-Avignon Université (AU), Universidad de Jaén, Jaén, Spain, UMR Nancy-Université- INRA Agronomie et Environnement Nancy-Colmar, Nancy Université, Conicet-Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina, Environmental Sciences, Guelph, University of Massachusetts Amherst, Amherst, MA, USA, Wageningen University and Research Center (WUR), University of Victoria, Victoria, BC, Canada, Department of Ecology, University of Innsbruck, Innsbruck, Austria, Department of Biological Sciences-Lancaster University, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Helmholtz Centre for Environmental Research (UFZ), School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA, Université Clermont Auvergne (UCA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Universiteit Gent [Ghent], School of Forest Resources and Conservation, University of Florida, Gainesville, FL, USA, University of Tasmania, Hobart, Tas., Australia, AMAP, IRD, Herbier de Nouvelle-Calédonie, Nouméa, New Caledonia, Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Friedrich-Schiller-Universität Jena, Jena, Germany, Università degli Studi di Roma 'La Sapienza' [Rome], wiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland, Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Tropical Agricultural Centre for Research and Higher Education (CATIE), Tropical Agricultural Centre for Research and Higher Education, Univ. Bordeaux, INRAE, BIOGECO, Cestas, France, Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN, USA, Royal Botanic Gardens, Kew, West Sussex, UK, Department of Biology, Colorado State University, Fort Collins, CO, USA, Hawkesbury Institute for the Environment, Western Sydney University, Sydney, NSW, Australia, Department of Botany and Zoology, Masaryk University, Brno, Czech Republic, Faculty of Environmental Sciences, University of Life Sciences Prague, Praha-Suchdol, Czech Republic, Institute of Botany, Czech Academy of Sciences, Třeboň, Czech Republic, Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden, MTA Centre for Ecological Research, Tihany, Hungary, Swedish Species Information Centre, Swedish University of Agricultural Sciences, Uppsala, Sweden, Université des Antilles (UA)-Centre National de la Recherche Scientifique (CNRS)-Université de Guyane (UG)-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), University of Florida [Gainesville], UFZ - Helmholtz Centre for Environmental Research, School of Geography, Earth and Environmental Sciences – University of Birmingham, Universitat Autònoma de Barcelona [Barcelona] (UAB), University of Ordu, Council for Agricultural Research and Economics (CREA), Université de Sherbrooke [Sherbrooke], Université Paul-Valéry - Montpellier 3 (UM3)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), United States Department of Agriculture - USDA (USA), Smithsonian Institution, Carnegie Museum of Natural History, Friedrich-Schiller-Universität Jena, Biodiversité, Gènes et Communautés, Goethe-Universität Frankfurt am Main-Senckenberg Gesellschaft für Naturforschung, University of Natural Resources and Applied Life Sciences (BOKU), Florida International University (FIU), Université Catholique de Louvain (UCL), Stanford University [Stanford], Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Centre National de la Recherche Scientifique (CNRS), University of Tasmania (UTAS), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Toulouse-Institut National Polytechnique (Toulouse) (Toulouse INP), Charles University [Prague], Ghent University [Belgium] (UGENT), Helmholtz Zentrum für Umweltforschung (UFZ), Hokkaido University, Technical University of Munich (TUM), Wageningen University and Research Centre [Wageningen] (WUR), Georg-August-Universität Göttingen, Western Sydney University (UWS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Département de Biologie, Université de Sherbrooke, Sherbrooke, QC, Canada, Université de Sherbrooke, Masaryk University, Czech Academy of Sciences [Prague] (ASCR), Natural Resources Institute Finland, Landcare Research [Lincoln], Université de Montréal [Montréal], Université Libre de Bruxelles [Bruxelles] (ULB), Centre National de la Recherche Scientifique (CNRS)-Ministère de l'Europe et des Affaires étrangères (MEAE), French Institute of Pondicherry (IFP), Normal Zhejiang University, Estonian University of Life Sciences, Institute of Biology Bucharest, Romanian Academy, VU University Amsterdam, Astronomical Institute of the Czech Academy of Sciences, Technische Universität München [München] (TUM), University of Parma, Cardiff School of Social Sciences, University of Cardiff, University of Minnesota [Twin Cities], Manaaki Whenua Landcare Research, Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Brookhaven National Laboratory [Upton] (BNL), Stony Brook University [SUNY] (SBU), University of Zürich [Zürich] (UZH), Algoma University [Canada], University of Goettingen, University of Wuerzburg, University of Würzburg, AFSSA, Sherbrooke University, University of Lisbon, Department of Biology (University of Florida), Florida Museum of Natural History, Technical University in Zvolen, University of Zvolen, Fac Forestry & Wood Sci, Université du Québec à Montréal (UQAM), Bioversity International, Consultative Group on International Agricultural Research [CGIAR], Université Clermont Auvergne (UCA), Vrije Universiteit [Brussels] (VUB), University of Tsukuba, Kattge, Jen, Bönisch, Gerhard, Díaz, Sandra, Lavorel, Sandra, Prentice, Iain Colin, Leadley, Paul, Tautenhahn, Susanne, Werner, Gijsbert D A, Aakala, Tuoma, Abedi, Mehdi, Acosta, Alicia Teresa Rosario, Adamidis, George C, Adamson, Kairi, Aiba, Masahiro, Albert, Cécile H, Alcántara, Julio M, Alcázar C, Carolina, Aleixo, Izabela, Ali, Hamada, Amiaud, Bernard, Ammer, Christian, Amoroso, Mariano M, Anand, Madhur, Anderson, Carolyn, Anten, Niel, Antos, Joseph, Apgaua, Deborah Mattos Guimarãe, Ashman, Tia-Lynn, Asmara, Degi Harja, Asner, Gregory P, Aspinwall, Michael, Atkin, Owen, Aubin, Isabelle, Baastrup-Spohr, Lar, Bahalkeh, Khadijeh, Bahn, Michael, Baker, Timothy, Baker, William J, Bakker, Jan P, Baldocchi, Denni, Baltzer, Jennifer, Banerjee, Arindam, Baranger, Anne, Barlow, Jo, Barneche, Diego R, Baruch, Zdravko, Bastianelli, Deni, Battles, John, Bauerle, William, Bauters, Marijn, Bazzato, Erika, Beckmann, Michael, Beeckman, Han, Beierkuhnlein, Carl, Bekker, Renee, Belfry, Gavin, Belluau, Michael, Beloiu, Mirela, Benavides, Raquel, Benomar, Lahcen, Berdugo-Lattke, Mary Lee, Berenguer, Erika, Bergamin, Rodrigo, Bergmann, Joana, Bergmann Carlucci, Marco, Berner, Logan, Bernhardt-Römermann, Marku, Bigler, Christof, Bjorkman, Anne D, Blackman, Chri, Blanco, Carolina, Blonder, Benjamin, Blumenthal, Dana, Bocanegra-González, Kelly T, Boeckx, Pascal, Bohlman, Stephanie, Böhning-Gaese, Katrin, Boisvert-Marsh, Laura, Bond, William, Bond-Lamberty, Ben, Boom, Arnoud, Boonman, Coline C F, Bordin, Kauane, Boughton, Elizabeth H, Boukili, Vanessa, Bowman, David M J S, Bravo, Sandra, Brendel, Marco Richard, Broadley, Martin R, Brown, Kerry A, Bruelheide, Helge, Brumnich, Federico, Bruun, Hans Henrik, Bruy, David, Buchanan, Serra W, Bucher, Solveig Franziska, Buchmann, Nina, Buitenwerf, Robert, Bunker, Daniel E, Bürger, Jana, Burrascano, Sabina, Burslem, David F R P, Butterfield, Bradley J, Byun, Chaeho, Marques, Marcia, Scalon, Marina C, Caccianiga, Marco, Cadotte, Marc, Cailleret, Maxime, Camac, Jame, Camarero, Jesús Julio, Campany, Courtney, Campetella, Giandiego, Campos, Juan Antonio, Cano-Arboleda, Laura, Canullo, Roberto, Carbognani, Michele, Carvalho, Fabio, Casanoves, Fernando, Castagneyrol, Bastien, Catford, Jane A, Cavender-Bares, Jeannine, Cerabolini, Bruno E L, Cervellini, Marco, Chacón-Madrigal, Eduardo, Chapin, Kenneth, Chapin, F Stuart, Chelli, Stefano, Chen, Si-Chong, Chen, Anping, Cherubini, Paolo, Chianucci, Francesco, Choat, Brendan, Chung, Kyong-Sook, Chytrý, Milan, Ciccarelli, Daniela, Coll, Lluí, Collins, Courtney G, Conti, Luisa, Coomes, David, Cornelissen, Johannes H C, Cornwell, William K, Corona, Piermaria, Coyea, Marie, Craine, Joseph, Craven, Dylan, Cromsigt, Joris P G M, Csecserits, Anikó, Cufar, Katarina, Cuntz, Matthia, da Silva, Ana Carolina, Dahlin, Kyla M, Dainese, Matteo, Dalke, Igor, Dalle Fratte, Michele, Dang-Le, Anh Tuan, Danihelka, Jirí, Dannoura, Masako, Dawson, Samantha, de Beer, Arend Jacobu, De Frutos, Angel, De Long, Jonathan R, Dechant, Benjamin, Delagrange, Sylvain, Delpierre, Nicola, Derroire, Géraldine, Dias, Arildo S, Diaz-Toribio, Milton Hugo, Dimitrakopoulos, Panayiotis G, Dobrowolski, Mark, Doktor, Daniel, Dřevojan, Pavel, Dong, Ning, Dransfield, John, Dressler, Stefan, Duarte, Leandro, Ducouret, Emilie, Dullinger, Stefan, Durka, Walter, Duursma, Remko, Dymova, Olga, E-Vojtkó, Anna, Eckstein, Rolf Lutz, Ejtehadi, Hamid, Elser, Jame, Emilio, Thaise, Engemann, Kristine, Erfanian, Mohammad Bagher, Erfmeier, Alexandra, Esquivel-Muelbert, Adriane, Esser, Gerd, Estiarte, Marc, Domingues, Tomas F, Fagan, William F, Fagúndez, Jaime, Falster, Daniel S, Fan, Ying, Fang, Jingyun, Farris, Emmanuele, Fazlioglu, Fatih, Feng, Yanhao, Fernandez-Mendez, Fernando, Ferrara, Carlotta, Ferreira, Joice, Fidelis, Alessandra, Finegan, Bryan, Firn, Jennifer, Flowers, Timothy J, Flynn, Dan F B, Fontana, Veronika, Forey, Estelle, Forgiarini, Cristiane, François, Loui, Frangipani, Marcelo, Frank, Dorothea, Frenette-Dussault, Cedric, Freschet, Grégoire T, Fry, Ellen L, Fyllas, Nikolaos M, Mazzochini, Guilherme G, Gachet, Sophie, Gallagher, Rachael, Ganade, Gislene, Ganga, Francesca, García-Palacios, Pablo, Gargaglione, Verónica, Garnier, Eric, Garrido, Jose Lui, de Gasper, André Luí, Gea-Izquierdo, Guillermo, Gibson, David, Gillison, Andrew N, Giroldo, Aelton, Glasenhardt, Mary-Claire, Gleason, Sean, Gliesch, Mariana, Goldberg, Emma, Göldel, Bastian, Gonzalez-Akre, Erika, Gonzalez-Andujar, Jose L, González-Melo, André, González-Robles, Ana, Graae, Bente Jessen, Granda, Elena, Graves, Sarah, Green, Walton A, Gregor, Thoma, Gross, Nicola, Guerin, Greg R, Günther, Angela, Gutiérrez, Alvaro G, Haddock, Lillie, Haines, Anna, Hall, Jefferson, Hambuckers, Alain, Han, Wenxuan, Harrison, Sandy P, Hattingh, Wesley, Hawes, Joseph E, He, Tianhua, He, Pengcheng, Heberling, Jacob Mason, Helm, Aveliina, Hempel, Stefan, Hentschel, Jörn, Hérault, Bruno, Hereş, Ana-Maria, Herz, Katharina, Heuertz, Myriam, Hickler, Thoma, Hietz, Peter, Higuchi, Pedro, Hipp, Andrew L, Hirons, Andrew, Hock, Maria, Hogan, James Aaron, Holl, Karen, Honnay, Olivier, Hornstein, Daniel, Hou, Enqing, Hough-Snee, Nate, Hovstad, Knut Ander, Ichie, Tomoaki, Igić, Bori, Illa, Estela, Isaac, Marney, Ishihara, Masae, Ivanov, Leonid, Ivanova, Larissa, Iversen, Colleen M, Izquierdo, Jordi, Jackson, Robert B, Jackson, Benjamin, Jactel, Hervé, Jagodzinski, Andrzej M, Jandt, Ute, Jansen, Steven, Jenkins, Thoma, Jentsch, Anke, Jespersen, Jens Rasmus Plantener, Jiang, Guo-Feng, Johansen, Jesper Liengaard, Johnson, David, Jokela, Eric J, Joly, Carlos Alfredo, Jordan, Gregory J, Joseph, Grant Stuart, Junaedi, Decky, Junker, Robert R, Justes, Eric, Kabzems, Richard, Kane, Jeffrey, Kaplan, Zdenek, Kattenborn, Teja, Kavelenova, Lyudmila, Kearsley, Elizabeth, Kempel, Anne, Kenzo, Tanaka, Kerkhoff, Andrew, Khalil, Mohammed I, Kinlock, Nicole L, Kissling, Wilm Daniel, Kitajima, Kaoru, Kitzberger, Thoma, Kjøller, Rasmu, Klein, Tamir, Kleyer, Michael, Klimešová, Jitka, Klipel, Joice, Kloeppel, Brian, Klotz, Stefan, Knops, Johannes M H, Kohyama, Takashi, Koike, Fumito, Kollmann, Johanne, Komac, Benjamin, Komatsu, Kimberly, König, Christian, Kraft, Nathan J B, Kramer, Koen, Kreft, Holger, Kühn, Ingolf, Kumarathunge, Dushan, Kuppler, Jona, Kurokawa, Hiroko, Kurosawa, Yoko, Kuyah, Shem, Laclau, Jean-Paul, Lafleur, Benoit, Lallai, Erik, Lamb, Eric, Lamprecht, Andrea, Larkin, Daniel J, Laughlin, Daniel, Le Bagousse-Pinguet, Yoann, le Maire, Guerric, le Roux, Peter C, le Roux, Elizabeth, Lee, Tali, Lens, Frederic, Lewis, Simon L, Lhotsky, Barbara, Li, Yuanzhi, Li, Xine, Lichstein, Jeremy W, Liebergesell, Mario, Lim, Jun Ying, Lin, Yan-Shih, Linares, Juan Carlo, Liu, Chunjiang, Liu, Daijun, Liu, Udayangani, Livingstone, Stuart, Llusià, Joan, Lohbeck, Madelon, López-García, Álvaro, Lopez-Gonzalez, Gabriela, Lososová, Zdeňka, Louault, Frédérique, Lukács, Balázs A, Lukeš, Petr, Luo, Yunjian, Lussu, Michele, Ma, Siyan, Maciel Rabelo Pereira, Camilla, Mack, Michelle, Maire, Vincent, Mäkelä, Annikki, Mäkinen, Harri, Malhado, Ana Claudia Mende, Mallik, Azim, Manning, Peter, Manzoni, Stefano, Marchetti, Zuleica, Marchino, Luca, Marcilio-Silva, Viniciu, Marcon, Eric, Marignani, Michela, Markesteijn, Lar, Martin, Adam, Martínez-Garza, Cristina, Martínez-Vilalta, Jordi, Mašková, Tereza, Mason, Kelly, Mason, Norman, Massad, Tara Joy, Masse, Jacynthe, Mayrose, Itay, Mccarthy, Jame, Mccormack, M Luke, Mcculloh, Katherine, Mcfadden, Ian R, Mcgill, Brian J, Mcpartland, Mara Y, Medeiros, Juliana S, Medlyn, Belinda, Meerts, Pierre, Mehrabi, Zia, Meir, Patrick, Melo, Felipe P L, Mencuccini, Maurizio, Meredieu, Céline, Messier, Julie, Mészáros, Ilona, Metsaranta, Juha, Michaletz, Sean T, Michelaki, Chrysanthi, Migalina, Svetlana, Milla, Ruben, Miller, Jesse E D, Minden, Vanessa, Ming, Ray, Mokany, Karel, Moles, Angela T, Molnár, Attila, Molofsky, Jane, Molz, Martin, Montgomery, Rebecca A, Monty, Arnaud, Moravcová, Lenka, Moreno-Martínez, Alvaro, Moretti, Marco, Mori, Akira S, Mori, Shigeta, Morris, Dave, Morrison, Jane, Mucina, Ladislav, Mueller, Sandra, Muir, Christopher D, Müller, Sandra Cristina, Munoz, Françoi, Myers-Smith, Isla H, Myster, Randall W, Nagano, Masahiro, Naidu, Shawna, Narayanan, Ayyappan, Natesan, Balachandran, Negoita, Luka, Nelson, Andrew S, Neuschulz, Eike Lena, Ni, Jian, Niedrist, Georg, Nieto, Jhon, Niinemets, Ülo, Nolan, Rachael, Nottebrock, Henning, Nouvellon, Yann, Novakovskiy, Alexander, Nystuen, Kristin Odden, O'Grady, Anthony, O'Hara, Kevin, O'Reilly-Nugent, Andrew, Oakley, Simon, Oberhuber, Walter, Ohtsuka, Toshiyuki, Oliveira, 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Kebun Raya Cibodas, Philipps-University Marburg, University Salzburg, CIRAD, Humboldt State University, The Czech Academy of Sciences, Charles University, Karlsruhe Institute of Technology, Forestry and Forest Products Research Institute, State University of New York at Stony Brook, University of Amsterdam, CONICET, Universidad Nacional del Comahue, Weizmann Institute of Science, Helmholtz Centre for Environmental Research-UFZ, Xi'an Jiaotong Liverpool University, Technical University of Munich, Wageningen University & Research, Land Life Company, Coconut Research Institute of Sri Lanka, UMR Eco&Sols, University of Montpellier, Université du Québec en Abitibi-Témiscamingue, University of Saskatchewan, University of Natural Resources and Life Sciences Vienna, University of Wyoming, University of Wisconsin Eau Claire, Naturalis Biodiversity Center, University College London, Sun Yat-sen University, University of Leipzig, Shanghai Jiao Tong University, National Forestry and Grassland Administration, Universitat Autònoma de Barcelona, Wageningen University and Research, World Agroforestry (ICRAF), University of Jaén, DRI, Global Change Research Institute AS CR, Université du Québec à Trois-Rivières, Federal University of Alagoas, Bolin Centre for Climate Research, Universidad Autónoma del Estado de Morelos, Manaaki Whenua - 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S. Geological Survey, Duke University, NSW Department of Primary Industries, SUNY-College of Environmental Science and Forestry, Sorbonne-Université, Laboratório de Ecologia Vegetal (LEVEG), George Washington University, National Taiwan University, Institut National Polytechnique Félix Houphouët-Boigny (INP-HB), University Oldenburg, and Biyoloji
Subjects: [SDE] Environmental Sciences, LIFE-HISTORY, Geography & travel, WOOD DENSITY, plant trait, Biodiversity & Conservation, 05 Environmental Sciences, Growth, 580 Plants (Botany), COMMUNITY COMPOSITION, ROOT TRAITS, Biologiska vetenskaper, Ecological modeling, data coverage, data integration, data representativeness, functional diversity, plant traits, TRY plant trait database, Biodiversity, Ecology, Plants, Access to Information, Ecosystem, data representativene, ddc:910, General Environmental Science, Global and Planetary Change, GLOBAL PATTERNS, food and beverages, LEAF PHOTOSYNTHETIC TRAITS, Biological Sciences, CAVElab, Data processing, ddc:580, [SDE]Environmental Sciences, Biodiversity Conservation, Life Sciences & Biomedicine, INCLINATION ANGLE DISTRIBUTION, Environmental Sciences & Ecology, Ecology and Environment, Database, LITTER DECOMPOSITION, ddc:570, Datenintegration, Environmental Chemistry, DDC 004 / Data processing & computer science, Intraspecific competition, Data integration (Computer science), Science & Technology, Biology and Life Sciences, Plant, 06 Biological Sciences, Environmental factor, Nutrient Network, Biology and Microbiology, FUNCTIONAL TRAITS, DDC 580 / Botanical sciences, Earth and Environmental Sciences, ddc:004, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Environmental Sciences, RELATIVE GROWTH-RATE
Abstract: Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives., publishedVersion
Published: 2020

27. On which timescale(s) do optimal adjustments to vegetation function confer resilience? A case study in South-Eastern Australia

Author: Belinda E. Medlyn, Silvia Caldararu, Martin G. De Kauwe, Andrew J. Pitman, David S. Ellsworth, Manon Sabot, and Sönke Zaehle
Subjects: Geography, Ecology, media_common.quotation_subject, medicine, medicine.symptom, Vegetation (pathology), Function (engineering), Resilience (network), South eastern, media_common
Abstract: Droughts have been implicated as the driver behind recent vegetation die-off across a variety of hydroclimates and are projected to drive greater mortality under future climate change. Predicting ecosystem resilience to future drought requires a predictive capacity, which is currently lacking in state-of-the-art land surface models (LSMs) that rely on simplified empirical relationships to represent the impacts of water stress on vegetation. Novel approaches that optimise stomatal conductance with respect to plant photosynthetic and hydraulic functions have been shown to reduce the biases of LSM gas exchange predictions during drought. These approaches also offer a pathway to further develop mechanistic optimality theory, e.g. pertaining to leaf drought deciduousness. But on what timescale(s) does vegetation function adjust to maximise resource investment? We explore the following timescales of optimality within a simple LSM: (i) instantaneous (regulating canopy gas exchange); (ii) monthly (regulating the investment of nitrogen in photosynthetic capacity); and (iii) seasonal to annual (water stress legacies on plant hydraulics). We use observations from a temperate woodland in South-Eastern Australia to test which optimisation timescales and processes are best supported and whether competing timescales can operate together, both under well-watered conditions and during a severe multi-year drought, and from the leaf-scale to the ecosystem-scale. The insights gained help us characterize how adjoined allocation processes, like leaf biomass adjustment, relate to leaf carbon uptake and plant water status through time (e.g. leaves can be shed to mitigate drought stress or built from structural storage pools when water is not limiting), therefore conferring additional resilience.
Published: 2021

28. A reporting format for leaf-level gas exchange data and metadata

Author: Chonggang Xu, Robert Crystal-Ornelas, Johan Uddling, Lucas A. Cernusak, Dushan Kumarathunge, Ellen Stuart-Haëntjens, John R. Evans, Sasha C. Reed, Belinda E. Medlyn, Shawn P. Serbin, Dedi Yang, Bruno O. Gimenez, Stephanie C. Schmiege, Danielle A. Way, Paul F. South, Qianyu Li, David Shaner LeBauer, Berkley J. Walker, Hendrik Poorter, Zhengbing Yan, Mauricio Tejera, J. Aaron Hogan, Stan D. Wullschleger, Aud H. Halbritter, Elizabeth P. Gordon, Loren P. Albert, Jin Wu, Nate G. McDowell, Martin G. De Kauwe, Kenneth J Davidson, Steve Bonnage, Thomas D. Sharkey, Jason R. Hupp, Nicholas G. Smith, Ashehad A. Ali, Tomas F. Domingues, Samuel H. Taylor, Julien Lamour, Mary A. Heskel, Deb Agarwal, Brett T. Wolfe, Álvaro Sanz-Sáez, Anthony P. Walker, Martijn Slot, Joseph R. Stinziano, Marjorie R. Lundgren, Alexandria L. Pivovaroff, Kolby J. Jardine, David T. Hanson, Thomas N. Buckley, Daisy C. Souza, Ülo Niinemets, J. Damerow, Chandra Bellasio, Amanda P. Cavanagh, Robinson I. Negrón-Juárez, Michael Dietze, Florian A. Busch, Jens Kattge, Andrew D. B. Leakey, David S. Ellsworth, Mirindi Eric Dusenge, James A. Bunce, Colin P. Osborne, Balasaheb V. Sonawane, Elizabeth A. Ainsworth, Alistair Rogers, Katherine Meacham-Hensold, Jeffrey M. Warren, Angela C. Burnett, Youngryel Ryu, Christopher M. Gough, Carl J. Bernacchi, Charuleka Varadharajan, David J. P. Moore, Vigdis Vandvik, Trevor F. Keenan, Michael J. Aspinwall, Johannes Kromdijk, Jeremiah Anderson, Kim S. Ely, Paul P. G. Gauthier, Burnett, Angela [0000-0002-2678-9842], Kromdijk, Johannes [0000-0003-4423-4100], and Apollo - University of Cambridge Repository
Subjects: 0106 biological sciences, Computer science, Information repository, Reuse, 010603 evolutionary biology, 01 natural sciences, Data type, Documentation, Information and Computing Sciences, Irradiance, Data reporting, Photosynthesis, Ecology, Evolution, Behavior and Systematics, Metadata, Ecology, 010604 marine biology & hydrobiology, Applied Mathematics, Ecological Modeling, Data reporting format, 15. Life on land, Biological Sciences, Data science, Discoverability, Computer Science Applications, Data Standard, Data standard, Computational Theory and Mathematics, Carbon dioxide, 13. Climate action, Modeling and Simulation, ddc:333.7
Abstract: Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system. publishedVersion
Published: 2021

29. Corrigendum to: Conversion of canopy intercepted radiation to photosynthate: a review of modelling approaches for regional scales

Author: Damian Barrett, Joe Landsberg, Robert Clement, P.J. Sands, and Belinda E. Medlyn
Subjects: Canopy, Scale (ratio), Ecology, Process (engineering), Eddy covariance, System identification, Plant Science, Vegetation, Biology, Atmospheric sciences, Agronomy and Crop Science, Scaling, Productivity
Abstract: A fundamental component of most models of terrestrial carbon balance is an estimate of plant canopy photosynthetic uptake driven by radiation interception by the canopy. In this article, we review approaches used to model the conversion of radiation into photosynthate. As this process is well understood at the leaf-scale, the modelling problem is essentially one of up-scaling, to canopy, regional or global scale. Our review therefore focuses on issues of scaling, including model identification, parameterisation and validation at large scales. Four different approaches are commonly taken to modelling photosynthate production at large scales: the maximum productivity, resource-use efficiency, big-leaf, and sun-shade models. Models representing each of these approaches are discussed and model predictions compared with estimates of gross primary productivity derived from eddy covariance data measured above a Sitka spruce forest. The sun-shade model was found to perform best at all time scales considered. However, other models had significant advantages including simplicity of implementation and the ability to combine the model with remotely-sensed information on vegetation radiation interception. We conclude that all four approaches can be successfully used to model photosynthetic uptake and that the best approach in a given situation will depend on model objectives and data availability.
Published: 2020

30. Linking Forest Flammability and Plant Vulnerability to Drought

Author: Belinda E. Medlyn, Matthias M. Boer, Ross A. Bradstock, Víctor Resco de Dios, Ximeng Li, Brendan Choat, Rachael H. Nolan, Chris J. Blackman, Western Sydney University, Laboratoire de Physique et Physiologie Intégratives de l’Arbre en environnement Fluctuant (PIAF), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Southwest University of Science and Technology [Mianyang] (SWUST), Hawkesbury Institute for the Environment [Richmond] (HIE), Technical University of Denmark [Lyngby] (DTU), New South Wales Government's Department of Planning, Industry and Environment via the NSW Bushfire Risk Management Research Hub Spanish Government / RYC-2012-10970 and AGL2015-69151-RAustralian Research CouncilNew South Wales Department of Planning, Industry and Environment /LP140100232Australian Research Council / FT130101115, and Danmarks Tekniske Universitet = Technical University of Denmark (DTU)
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], flammability, Fuel moisture content, drought, Wildfire, 010603 evolutionary biology, 01 natural sciences, leaf water potential, wildfire, Ecosystem services, Flammability, fuel moisture, Fuel moisture, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Ecosystem, Plant traits, Water content, 0105 earth and related environmental sciences, Fire regime, Drought, Ecology, Forestry, lcsh:QK900-989, 15. Life on land, Leaf water potential, 13. Climate action, plant traits, Soil water, lcsh:Plant ecology, Environmental science
Abstract: Globally, fire regimes are being altered by changing climatic conditions. New fire regimes have the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Despite the co-occurrence of forest fires with drought, current approaches to modelling flammability largely overlook the large body of research into plant vulnerability to drought. Here, we outline the mechanisms through which plant responses to drought may affect forest flammability, specifically fuel moisture and the ratio of dead to live fuels. We present a framework for modelling live fuel moisture content (moisture content of foliage and twigs) from soil water content and plant traits, including rooting patterns and leaf traits such as the turgor loss point, osmotic potential, elasticity and leaf mass per area. We also present evidence that physiological drought stress may contribute to previously observed fuel moisture thresholds in south-eastern Australia. Of particular relevance is leaf cavitation and subsequent shedding, which transforms live fuels into dead fuels, which are drier, and thus easier to ignite. We suggest that capitalising on drought research to inform wildfire research presents a major opportunity to develop new insights into wildfires, and new predictive models of seasonal fuel dynamics. We thank the New South Wales Government’s Department of Planning, Industry and Environment for providing funds to support this research via the NSW Bushfire Risk Management Research Hub; the Spanish Government (RYC-2012-10970, AGL2015-69151-R); an Australian Research Council Linkage grant with the New South Wales Department of Planning, Industry and Environment (LP140100232); and an Australian Research Council Future Fellowship (FT130101115).
Published: 2020

31. Drought Impacts on Australian Vegetation During the Millennium Drought Measured With Multisource Spaceborne Remote Sensing

Author: John Rogan, Belinda E. Medlyn, Martin G. De Kauwe, Christopher B. Williams, and Tong Jiao
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Ecology, 0211 other engineering and technologies, Paleontology, Soil Science, Forestry, 02 engineering and technology, Aquatic Science, 01 natural sciences, Carbon cycle, Remote sensing (archaeology), medicine, Environmental science, Ecosystem, medicine.symptom, Vegetation (pathology), 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Water Science and Technology, Remote sensing
Published: 2020

32. Tree hydraulic traits are coordinated and strongly linked to climate-of-origin across a rainfall gradient

Author: Chris J. Blackman, Brendan Choat, Remko A. Duursma, Belinda E. Medlyn, Ximeng Li, David T. Tissue, and Paul D. Rymer
Subjects: 0106 biological sciences, Ecophysiology, Physiology, Ecology, Range (biology), Drought tolerance, Xylem, Plant Science, Vegetation, Biology, 010603 evolutionary biology, 01 natural sciences, Arid, Trait, Adaptation, 010606 plant biology & botany
Abstract: Plant hydraulic traits capture the impacts of drought stress on plant function, yet vegetation models lack sufficient information regarding trait coordination and variation with climate-of-origin across species. Here, we investigated key hydraulic and carbon economy traits of 12 woody species in Australia from a broad climatic gradient, with the aim of identifying the coordination among these traits and the role of climate in shaping cross-species trait variation. The influence of environmental variation was minimized by a common garden approach, allowing us to factor out the influence of environment on phenotypic variation across species. We found that hydraulic traits (leaf turgor loss point, stomatal sensitivity to drought [Pgs ], xylem vulnerability to cavitation [Px ], and branch capacitance [Cbranch ]) were highly coordinated across species and strongly related to rainfall and aridity in the species native distributional range. In addition, trade-offs between drought tolerance and plant growth rate were observed across species. Collectively, these results provide critical insight into the coordination among hydraulic traits in modulating drought adaptation and will significantly advance our ability to predict drought vulnerability in these dominant trees species.
Published: 2018

33. Biome‐specific climatic space defined by temperature and precipitation predictability

Author: Mingkai Jiang, Benjamin S. Felzer, Uffe N. Nielsen, Belinda E. Medlyn, and Marie‐Josée Fortin
Subjects: 0106 biological sciences, Global and Planetary Change, 010504 meteorology & atmospheric sciences, Ecology, Biome, Biodiversity, Climate change, 15. Life on land, Seasonality, medicine.disease, 010603 evolutionary biology, 01 natural sciences, 13. Climate action, medicine, Environmental science, Precipitation, Predictability, Mean radiant temperature, Ecology, Evolution, Behavior and Systematics, Macroecology, 0105 earth and related environmental sciences
Abstract: Aim Global biomes are often classified by mean annual temperature and precipitation, but there is significant overlap between biomes, making it difficult to interpret the role of climate in the distribution of biomes globally. Climate predictability (including long-term reliability of both seasonality and inter-annual variability) varies considerably between biomes and regulates biodiversity distribution, adaptation and evolution, but its global pattern has rarely been investigated. The aim of this study was to characterize climatic space quantitatively for major biomes of the world using temperature and precipitation predictability, and to interpret its biological implications under future climate change. Location Global. Time Period 1901–2012. Methods We calculated global gridded temperature and precipitation predictability based on an information theory approach, and compared climatic spaces defined by these measures within and across biomes. Results We show that temperature predictability has a clear latitudinal gradient, whereas precipitation predictability is geographically variable. We further show that temperature and precipitation predictability form distinct climatic spaces for major biomes across the globe, and importantly, temperature and precipitation predictability can robustly distinguish biomes that are overlapping in mean annual climate statistics. Main conclusions Climatic space created by temperature and precipitation predictability supplements the traditional biome-specific climatic spaces created by annual mean temperature and total precipitation. Quantifying measures of climate predictability helps us to understand adaptation strategies adopted by local organisms within and across biomes. Our results show that quantifying climate predictability is a simple and effective way to delineate more robustly biome climate space and its influences on macroecology and evolutionary biology, which in turn could underpin conservation efforts under future climate change, especially when prevailing climates are comparable in terms of magnitude.
Published: 2017

34. Gross primary production responses to warming, elevated <scp>CO</scp> 2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland

Author: Edmund Ryan, Christian Werner, William J. Parton, Jianyang Xia, Sönke Zaehle, Xingjie Lu, Drew M. P. Peltier, Elise Pendall, Bertrand Guenet, Kiona Ogle, K. A. Luus, Martin G. De Kauwe, Belinda E. Medlyn, Shijie Shu, Anna B. Harper, David G. Williams, Shinichi Asao, Anthony P. Walker, Colorado State University [Fort Collins] (CSU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
Subjects: 0106 biological sciences, warming, 010504 meteorology & atmospheric sciences, Vapour Pressure Deficit, Climate change, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, Grassland, Carbon cycle, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, carbon cycle, Environmental Chemistry, Ecosystem, elevated CO, 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, Hydrology, elevated CO2, Global and Planetary Change, geography, geography.geographical_feature_category, Ecology, AMAX, grasslands, Primary production, Biosphere, 15. Life on land, gross primary production, Bayesian modeling, 13. Climate action, Environmental science, [SDV.EE.BIO]Life Sciences [q-bio]/Ecology, environment/Bioclimatology, multi-factor global change experiment, Bayesian modelling, multifactor global change experiment
Abstract: Determining whether the terrestrial biosphere will be a source or sink of carbon (C) under a future climate of elevated CO2 (eCO2) and warming requires accurate quantification of gross primary production (GPP), the largest flux of C in the global C cycle. We evaluated 6 years (2007–2012) of flux-derived GPP data from the Prairie Heating and CO2 Enrichment (PHACE) experiment, situated in a grassland in Wyoming, USA. The GPP data were used to calibrate a light response model whose basic formulation has been successfully used in a variety of ecosystems. The model was extended by modeling maximum photosynthetic rate (Amax) and light-use efficiency (Q) as functions of soil water, air temperature, vapor pressure deficit, vegetation greenness, and nitrogen at current and antecedent (past) timescales. The model fits the observed GPP well (R2 = 0.79), which was confirmed by other model performance checks that compared different variants of the model (e.g. with and without antecedent effects). Stimulation of cumulative 6-year GPP by warming (29%, P = 0.02) and eCO2 (26%, P = 0.07) was primarily driven by enhanced C uptake during spring (129%, P = 0.001) and fall (124%, P = 0.001), respectively, which was consistent across years. Antecedent air temperature (Tairant) and vapor pressure deficit (VPDant) effects on Amax (over the past 3–4 days and 1–3 days, respectively) were the most significant predictors of temporal variability in GPP among most treatments. The importance of VPDant suggests that atmospheric drought is important for predicting GPP under current and future climate; we highlight the need for experimental studies to identify the mechanisms underlying such antecedent effects. Finally, posterior estimates of cumulative GPP under control and eCO2 treatments were tested as a benchmark against 12 terrestrial biosphere models (TBMs). The narrow uncertainties of these data-driven GPP estimates suggest that they could be useful semi-independent data streams for validating TBMs.
Published: 2017

35. Water‐use efficiency in a semi‐arid woodland with high rainfall variability

Author: Tarin Terrazas T, Nolan RH, Medlyn BE, Cleverly J, and Eamus D
Subjects: Soil, Ecology, 05 Environmental Sciences, 06 Biological Sciences, Australia, Water, Photosynthesis, Forests, Ecosystem
Abstract: As the ratio of carbon uptake to water use by vegetation, water-use efficiency (WUE) is a key ecosystem property linking global carbon and water cycles. It can be estimated in several ways, but it is currently unclear how different measures of WUE relate, and how well they each capture variation in WUE with soil moisture availability. We evaluated WUE in an Acacia-dominated woodland ecosystem of central Australia at various spatial and temporal scales using stable carbon isotope analysis, leaf gas exchange and eddy covariance (EC) fluxes. Semi-arid Australia has a highly variable rainfall pattern, making it an ideal system to study how WUE varies with water availability. We normalized our measures of WUE across a range of vapour pressure deficits using g1 , which is a parameter derived from an optimal stomatal conductance model and which is inversely related to WUE. Continuous measures of whole-ecosystem g1 obtained from EC data were elevated in the 3 days following rain, indicating a strong effect of soil evaporation. Once these values were removed, a close relationship of g1 with soil moisture content was observed. Leaf-scale values of g1 derived from gas exchange were in close agreement with ecosystem-scale values. In contrast, values of g1 obtained from stable isotopes did not vary with soil moisture availability, potentially indicating remobilization of stored carbon during dry periods. Our comprehensive comparison of alternative measures of WUE shows the importance of stomatal control of fluxes in this highly variable rainfall climate and demonstrates the ability of these different measures to quantify this effect. Our study provides the empirical evidence required to better predict the dynamic carbon-water relations in semi-arid Australian ecosystems.
Published: 2019

36. Water-use efficiency in a semi-arid woodland with high rainfall variability

Author: Tonantzin Tarin, James Cleverly, Derek Eamus, Belinda E. Medlyn, and Rachael H. Nolan
Subjects: 0106 biological sciences, Global and Planetary Change, Stomatal conductance, 010504 meteorology & atmospheric sciences, Ecology, Eddy covariance, Australia, Water, Forests, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, Arid, Soil, Environmental Chemistry, Environmental science, Ecosystem, Water cycle, Water-use efficiency, Photosynthesis, Water content, Water use, 0105 earth and related environmental sciences, General Environmental Science
Abstract: As the ratio of carbon uptake to water use by vegetation, water-use efficiency (WUE) is a key ecosystem property linking global carbon and water cycles. It can be estimated in several ways, but it is currently unclear how different measures of WUE relate, and how well they each capture variation in WUE with soil moisture availability. We evaluated WUE in an Acacia-dominated woodland ecosystem of central Australia at various spatial and temporal scales using stable carbon isotope analysis, leaf gas exchange and eddy covariance (EC) fluxes. Semi-arid Australia has a highly variable rainfall pattern, making it an ideal system to study how WUE varies with water availability. We normalized our measures of WUE across a range of vapour pressure deficits using g1 , which is a parameter derived from an optimal stomatal conductance model and which is inversely related to WUE. Continuous measures of whole-ecosystem g1 obtained from EC data were elevated in the 3 days following rain, indicating a strong effect of soil evaporation. Once these values were removed, a close relationship of g1 with soil moisture content was observed. Leaf-scale values of g1 derived from gas exchange were in close agreement with ecosystem-scale values. In contrast, values of g1 obtained from stable isotopes did not vary with soil moisture availability, potentially indicating remobilization of stored carbon during dry periods. Our comprehensive comparison of alternative measures of WUE shows the importance of stomatal control of fluxes in this highly variable rainfall climate and demonstrates the ability of these different measures to quantify this effect. Our study provides the empirical evidence required to better predict the dynamic carbon-water relations in semi-arid Australian ecosystems.
Published: 2019

37. Using plant, microbe and soil fauna traits to improve the predictive power of biogeochemical models

Author: John E. Drake, Benjamin G. Jackson, Nil Alvarez, Sara Hortal, David W. Johnson, Richard D. Bardgett, Elizabeth M. Baggs, Jocelyn M. Lavallee, Shun Hasegawa, Mingkai Jiang, Brajesh K. Singh, Ellen L. Fry, Pete Smith, Jennifer M. Rhymes, Yolima Carrillo, Mathilde Chomel, Belinda E. Medlyn, Jonathan R. De Long, Lucía Álvarez Garrido, Ian C. Anderson, Laura Castañeda-Gómez, Marta Dondini, Terrestrial Ecology (TE), Producció Animal, and Aigües Marines i Continentals
Subjects: 0106 biological sciences, Biogeochemical cycle, intra- and interspecific variation, Soil biology, Biodiversity, Climate change, 010603 evolutionary biology, 01 natural sciences, above-belowground interactions, carbon and nitrogen cycling, mycorrhizae, Biological sciences, Ecology, Evolution, Behavior and Systematics, biodiversity, effect and response traits, 2. Zero hunger, Ecology, 010604 marine biology & hydrobiology, Ecological Modeling, Plant microbe, 15. Life on land, climate change, Work (electrical), 13. Climate action, international, Predictive power, Environmental science, community weighted means
Abstract: Process‐based models describing biogeochemical cycling are crucial tools to understanding long‐term nutrient dynamics, especially in the context of perturbations, such as climate and land‐use change. Such models must effectively synthesize ecological processes and properties. For example, in terrestrial ecosystems, plants are the primary source of bioavailable carbon, but turnover rates of essential nutrients are contingent on interactions between plants and soil biota. Yet, biogeochemical models have traditionally considered plant and soil communities in broad terms. The next generation of models must consider how shifts in their diversity and composition affect ecosystem processes. One promising approach to synthesize plant and soil biodiversity and their interactions into models is to consider their diversity from a functional trait perspective. Plant traits, which include heritable chemical, physical, morphological and phenological characteristics, are increasingly being used to predict ecosystem processes at a range of scales, and to interpret biodiversity–ecosystem functional relationships. There is also emerging evidence that the traits of soil microbial and faunal communities can be correlated with ecosystem functions such as decomposition, nutrient cycling, and greenhouse gas production. Here, we draw on recent advances in measuring and using traits of different biota to predict ecosystem processes, and provide a new perspective as to how biotic traits can be integrated into biogeochemical models. We first describe an explicit trait‐based model framework that operates at small scales and uses direct measurements of ecosystem properties; second, an integrated approach that operates at medium scales and includes interactions between biogeochemical cycling and soil food webs; and third, an implicit trait‐based model framework that associates soil microbial and faunal functional groups with plant functional groups, and operates at the Earth‐system level. In each of these models, we identify opportunities for inclusion of traits from all three groups to reduce model uncertainty and improve understanding of biogeochemical cycles. These model frameworks will generate improved predictive capacity of how changes in biodiversity regulate biogeochemical cycles in terrestrial ecosystems. Further, they will assist in developing a new generation of process‐based models that include plant, microbial, and faunal traits and facilitate dialogue between empirical researchers and modellers. info:eu-repo/semantics/acceptedVersion
Published: 2019

38. On the minimum leaf conductance: its role in models of plant water use, and ecological and environmental controls

Author: Nicolas Martin-StPaul, Chris J. Blackman, Rosana López, Belinda E. Medlyn, Remko A. Duursma, Hervé Cochard, Hawkesbury Institute for the Environment, Western Sydney University, Laboratoire de Physique et Physiologie Intégratives de l’Arbre en environnement Fluctuant (PIAF), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Ecologie des Forêts Méditerranéennes (URFM), Institut National de la Recherche Agronomique (INRA), and Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de la Recherche Agronomique (INRA)
Subjects: 0106 biological sciences, 0301 basic medicine, Stomatal conductance, Physiology, conductivité foliaire, Acclimatization, Drought tolerance, drought tolerance, Ecological and Environmental Phenomena, plant water relations, Plant Science, Photosynthesis, Models, Biological, 01 natural sciences, écosystème, 03 medical and health sciences, Ecosystem model, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Ecosystem, conductance stomatique, cuticular conductance, 2. Zero hunger, Vegetal Biology, relation plante eau, ecosystem modeling, Ecology, fungi, Water, Conductance, tolérance à la sécheresse, food and beverages, stomatal conductance mode, 15. Life on land, Plant Leaves, 030104 developmental biology, Plant Stomata, Soil water, Environmental science, Water use, Biologie végétale, 010606 plant biology & botany
Abstract: Contents Summary 693 I. Introduction 693 II. Comparison of various definitions and measurement techniques of minimum conductance 694 III. Cuticular conductance 695 IV. Contribution of stomata 696 V. Environmental and ecological variation in minimum conductance 696 VI. Use of minimum conductance in models 698 VII. Conclusions 703 Acknowledgements 703 References 703 SUMMARY: When the rate of photosynthesis is greatly diminished, such as during severe drought, extreme temperature or low light, it seems advantageous for plants to close stomata and completely halt water loss. However, water loss continues through the cuticle and incompletely closed stomata, together constituting the leaf minimum conductance (gmin ). In this review, we critically evaluate the sources of variation in gmin , quantitatively compare various methods for its estimation, and illustrate the role of gmin in models of leaf gas exchange. A literature compilation of gmin as measured by the weight loss of detached leaves is presented, which shows much variation in this trait, which is not clearly related to species groups, climate of origin or leaf type. Much evidence points to the idea that gmin is highly responsive to the growing conditions of the plant, including soil water availability, temperature and air humidity - as we further demonstrate with two case studies. We pay special attention to the role of the minimum conductance in the Ball-Berry model of stomatal conductance, and caution against the usual regression-based method for its estimation. The synthesis presented here provides guidelines for the use of gmin in ecosystem models, and points to clear research gaps for this drought tolerance trait.
Published: 2019

39. Effects of mesophyll conductance on vegetation responses to elevated CO 2 concentrations in a land surface model

Author: Markus Reichstein, Jürgen Knauer, John R. Evans, Belinda E. Medlyn, Christiane Werner, Sönke Zaehle, Martin G. De Kauwe, and Nur H. A. Bahar
Subjects: 0106 biological sciences, Global and Planetary Change, 010504 meteorology & atmospheric sciences, Ecology, Representative Concentration Pathways, Vegetation, 15. Life on land, Evergreen, Atmospheric sciences, Photosynthesis, 010603 evolutionary biology, 01 natural sciences, Latitude, 13. Climate action, Temperate climate, Environmental Chemistry, Environmental science, Ecosystem, 0105 earth and related environmental sciences, General Environmental Science, Transpiration
Abstract: Mesophyll conductance (g m) is known to affect plant photosynthesis. However, g m is rarely explicitly considered in land surface models (LSMs), with the consequence that its role in ecosystem and large‐scale carbon and water fluxes is poorly understood. In particular, the different magnitudes of g m across plant functional types (PFTs) are expected to cause spatially divergent vegetation responses to elevated CO2 concentrations. Here, an extensive literature compilation of g m across major vegetation types is used to parameterize an empirical model of g m in the LSM JSBACH and to adjust photosynthetic parameters based on simulated A n − C i curves. We demonstrate that an explicit representation of g m changes the response of photosynthesis to environmental factors, which cannot be entirely compensated by adjusting photosynthetic parameters. These altered responses lead to changes in the photosynthetic sensitivity to atmospheric CO2 concentrations which depend both on the magnitude of g m and the climatic conditions, particularly temperature. We then conducted simulations under ambient and elevated (ambient + 200 μmol/mol) CO2 concentrations for contrasting ecosystems and for historical and anticipated future climate conditions (representative concentration pathways; RCPs) globally. The g m‐explicit simulations using the RCP8.5 scenario resulted in significantly higher increases in gross primary productivity (GPP) in high latitudes (+10% to + 25%), intermediate increases in temperate regions (+5% to + 15%), and slightly lower to moderately higher responses in tropical regions (−2% to +5%), which summed up to moderate GPP increases globally. Similar patterns were found for transpiration, but with a lower magnitude. Our results suggest that the effect of an explicit representation of g m is most important for simulated carbon and water fluxes in the boreal zone, where a cold climate coincides with evergreen vegetation.
Published: 2019
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40. Bridging Drought Experiment and Modeling: Representing the Differential Sensitivities of Leaf Gas Exchange to Drought

Author: Belinda E. Medlyn, Shuangxi Zhou, I. Colin Prentice, AXA Research Fund, and Commission of the European Communities
Subjects: 0106 biological sciences, V-cmax, TREE MORTALITY, 010504 meteorology & atmospheric sciences, land surface model, Climate change, mesophyll conductance, Plant Science, Review, lcsh:Plant culture, Deserts and xeric shrublands, Photosynthesis, 01 natural sciences, Acclimatization, TERM WATER-STRESS, QUERCUS-ILEX, NONSTOMATAL LIMITATIONS, Vcmax, Jmax, DECREASED RUBISCO ACTIVITY, Ecosystem, lcsh:SB1-1110, 0105 earth and related environmental sciences, Science & Technology, CLIMATE-CHANGE, photosynthesis, Ecology, Global warming, Plant Sciences, J(max), OPTIMAL STOMATAL CONDUCTANCE, HYDRAULIC TRAITS, 15. Life on land, Plant functional type, Photosynthetic capacity, 6. Clean water, 13. Climate action, J max, drought acclimation, Environmental science, stomatal and non-stomatal limitation, flux measurement, V cmax, Life Sciences & Biomedicine, PHOTOSYNTHETIC CAPACITY, 010606 plant biology & botany
Abstract: Global climate change is expected to increase drought duration and intensity in certain regions while increasing rainfall in others. The quantitative consequences of increased drought for ecosystems are not easy to predict. Process-based models must be informed by experiments to determine the resilience of plants and ecosystems from different climates. Here, we demonstrate what and how experimentally derived quantitative information can improve the representation of stomatal and non-stomatal photosynthetic responses to drought in large-scale vegetation models. In particular, we review literature on the answers to four key questions: (1) Which photosynthetic processes are affected under short-term drought? (2) How do the stomatal and non-stomatal responses to short-term drought vary among species originating from different hydro-climates? (3) Do plants acclimate to prolonged water stress, and do mesic and xeric species differ in their degree of acclimation? (4) Does inclusion of experimentally based plant functional type specific stomatal and non-stomatal response functions to drought help Land Surface Models to reproduce key features of ecosystem responses to drought? We highlighted the need for evaluating model representations of the fundamental eco-physiological processes under drought. Taking differential drought sensitivity of different vegetation into account is necessary for Land Surface Models to accurately model drought responses, or the drought impacts on vegetation in drier environments may be over-estimated.
Published: 2019

41. Global-scale environmental control of plant photosynthetic capacity

Author: Jasper A. Vrugt, Chonggang Xu, Rosie A. Fisher, Peter B. Reich, Louis S. Santiago, Cathy J. Wilson, Ashehad A. Ali, Alistair Rogers, Nate G. McDowell, Stan D. Wullschleger, William L. Bauerle, and Belinda E. Medlyn
Subjects: Conservation of Natural Resources, Ecology, Nitrogen, Uncertainty, Humidity, chemistry.chemical_element, Plants, Plant functional type, Photosynthesis, Models, Biological, Photosynthetic capacity, Plant Leaves, Carboxylation, chemistry, Agronomy, Environmental science, Chemical composition, Plant nutrition, Environmental Monitoring
Abstract: Photosynthetic capacity, determined by light harvesting and carboxylation reactions, is a key plant trait that determines the rate of photosynthesis; however, in Earth System Models (ESMs) at a reference temperature, it is either a fixed value for a given plant functional type or derived from a linear function of leaf nitrogen content. In this study, we conducted a comprehensive analysis that considered correlations of environmental factors with photosynthetic capacity as determined by maximum carboxylation (V(cm)) rate scaled to 25 degrees C (i.e., V(c),25; μmol CO2 x m(-2)x s(-1)) and maximum electron transport rate (J(max)) scaled to 25 degrees C (i.e., J25; μmol electron x m(-2) x s(-1)) at the global scale. Our results showed that the percentage of variation in observed V(c),25 and J25 explained jointly by the environmental factors (i.e., day length, radiation, temperature, and humidity) were 2-2.5 times and 6-9 times of that explained by area-based leaf nitrogen content, respectively. Environmental factors influenced photosynthetic capacity mainly through photosynthetic nitrogen use efficiency, rather than through leaf nitrogen content. The combination of leaf nitrogen content and environmental factors was able to explain -56% and -66% of the variation in V(c),25 and J25 at the global scale, respectively. Our analyses suggest that model projections of plant photosynthetic capacity and hence land-atmosphere exchange under changing climatic conditions could be substantially improved if environmental factors are incorporated into algorithms used to parameterize photosynthetic capacity in ESMs.
Published: 2015

42. Do land surface models need to include differential plant species responses to drought? Examining model predictions across a mesic-xeric gradient in Europe

Author: Belinda E. Medlyn, Ying-Ping Wang, Andrew J. Pitman, Iain Colin Prentice, Remko A. Duursma, M. G. De Kauwe, and Shuangxi Zhou
Subjects: Stomatal conductance, TREE MORTALITY, ECOSYSTEM PRODUCTIVITY, STOMATAL CONDUCTANCE, 04 Earth Sciences, 05 Environmental Sciences, lcsh:Life, Climate change, Environmental Sciences & Ecology, Atmospheric sciences, Deserts and xeric shrublands, ANISOHYDRIC BEHAVIORS, ROOT-WATER-UPTAKE, lcsh:QH540-549.5, USE EFFICIENCY, Meteorology & Atmospheric Sciences, Geosciences, Multidisciplinary, Ecology, Evolution, Behavior and Systematics, TERRESTRIAL BIOSPHERE, Earth-Surface Processes, Hydrology, Science & Technology, CLIMATE-CHANGE, Ecology, lcsh:QE1-996.5, Biosphere, Geology, Vegetation, 15. Life on land, 06 Biological Sciences, lcsh:Geology, lcsh:QH501-531, Water potential, 13. Climate action, Physical Sciences, Soil horizon, Environmental science, Climate model, lcsh:Ecology, ATMOSPHERE CONTINUUM, Life Sciences & Biomedicine, GAS-EXCHANGE
Abstract: Future climate change has the potential to increase drought in many regions of the globe, making it essential that land surface models (LSMs) used in coupled climate models realistically capture the drought responses of vegetation. Recent data syntheses show that drought sensitivity varies considerably among plants from different climate zones, but state-of-the-art LSMs currently assume the same drought sensitivity for all vegetation. We tested whether variable drought sensitivities are needed to explain the observed large-scale patterns of drought impact on the carbon, water and energy fluxes. We implemented data-driven drought sensitivities in the Community Atmosphere Biosphere Land Exchange (CABLE) LSM and evaluated alternative sensitivities across a latitudinal gradient in Europe during the 2003 heatwave. The model predicted an overly abrupt onset of drought unless average soil water potential was calculated with dynamic weighting across soil layers. We found that high drought sensitivity at the most mesic sites, and low drought sensitivity at the most xeric sites, was necessary to accurately model responses during drought. Our results indicate that LSMs will over-estimate drought impacts in drier climates unless different sensitivity of vegetation to drought is taken into account.
Published: 2018

43. Observed and modelled historical trends in the water-use efficiency of plants and ecosystems

Author: Aliénor Lavergne, Heather Graven, Trevor F. Keenan, Martin G. De Kauwe, Belinda E. Medlyn, Iain Colin Prentice, and AXA Research Fund
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, trends in water-use efficiency, EDDY COVARIANCE, Biodiversity & Conservation, 05 Environmental Sciences, Atmospheric sciences, 01 natural sciences, ATMOSPHERIC CO2 CONCENTRATIONS, Photosynthesis, General Environmental Science, Transpiration, Global and Planetary Change, Ecology, spatial scales, Biological Sciences, Plants, carbon isotopic discrimination, Biodiversity Conservation, Terrestrial ecosystem, Life Sciences & Biomedicine, Stomatal conductance, MESOPHYLL CONDUCTANCE, STOMATAL CONDUCTANCE, Eddy covariance, Environmental Sciences & Ecology, RISING CO2, CARBON-ISOTOPE DISCRIMINATION, 010603 evolutionary biology, Environmental Chemistry, Ecosystem, FIELD EXPERIMENTS, Water-use efficiency, Leaf area index, eddy-covariance flux, vegetation modelling, 0105 earth and related environmental sciences, Science & Technology, TREE-RING, Water, 06 Biological Sciences, Carbon Dioxide, GAS-EXCHANGE MEASUREMENTS, Plant Leaves, stomatal conductance, Soil water, Environmental science, ELEVATED CO2, Environmental Sciences
Abstract: Plant water-use efficiency (WUE, the carbon gained through photosynthesis per unit of water lost through transpiration) is a tracer of the plant physiological controls on the exchange of water and carbon dioxide between terrestrial ecosystems and the atmosphere. At the leaf level, rising CO2 concentrations tend to increase carbon uptake (in the absence of other limitations) and to reduce stomatal conductance, both effects leading to an increase in leaf WUE. At the ecosystem level, indirect effects (e.g. increased leaf area index, soil water savings) may amplify or dampen the direct effect of CO2 . Thus, the extent to which changes in leaf WUE translate to changes at the ecosystem scale remains unclear. The differences in the magnitude of increase in leaf versus ecosystem WUE as reported by several studies are much larger than would be expected with current understanding of tree physiology and scaling, indicating unresolved issues. Moreover, current vegetation models produce inconsistent and often unrealistic magnitudes and patterns of variability in leaf and ecosystem WUE, calling for a better assessment of the underlying approaches. Here, we review the causes of variations in observed and modelled historical trends in WUE over the continuum of scales from leaf to ecosystem, including methodological issues, with the aim of elucidating the reasons for discrepancies observed within and across spatial scales. We emphasize that even though physiological responses to changing environmental drivers should be interpreted differently depending on the observational scale, there are large uncertainties in each data set which are often underestimated. Assumptions made by the vegetation models about the main processes influencing WUE strongly impact the modelled historical trends. We provide recommendations for improving long-term observation-based estimates of WUE that will better inform the representation of WUE in vegetation models.
Published: 2018

44. Towards a more physiological representation of vegetation phosphorus processes in land surface models

Author: Silvia Caldararu, Belinda E. Medlyn, Mingkai Jiang, Sönke Zaehle, and David S. Ellsworth
Subjects: 0106 biological sciences, 0301 basic medicine, Physiology, chemistry.chemical_element, Plant Science, Photosynthesis, 01 natural sciences, Models, Biological, 03 medical and health sciences, Nutrient, Ecosystem model, Ecosystem, Biomass, Plant Physiological Phenomena, 2. Zero hunger, Biomass (ecology), Ecology, Phosphorus, Vegetation, 15. Life on land, Carbon, 030104 developmental biology, Productivity (ecology), chemistry, 13. Climate action, Environmental science, 010606 plant biology & botany
Abstract: Contents Summary 1223 I. Introduction 1223 II. Photosynthesis and respiration 1224 III. Biomass growth 1224 IV. Carbon allocation 1225 V. Plant internal P redistribution 1226 VI. Plant P uptake 1227 VII. Conclusion 1227 Acknowledgements 1228 References 1228 SUMMARY: Our ability to understand the effect of nutrient limitation on ecosystem productivity is key to the prediction of future terrestrial carbon storage. Significant progress has been made to include phosphorus (P) cycle processes in land surface models (LSMs), but these efforts are focused on the soil component of the P cycle. Incorporating the soil component is important to estimate plant-available P, but does not necessarily address the vegetation response to P limitation or plant-soil interactions. A more detailed representation of plant P processes is needed to link nutrient availability and ecosystem productivity. We review physiological and biochemical evidence for vegetation responses to P availability, and recommend ways to move towards a more physiological representation of vegetation P processes in LSMs.
Published: 2018

45. Trees tolerate an extreme heatwave via sustained transpirational cooling and increased leaf thermal tolerance

Author: Peter B. Reich, John E. Drake, Dushan Kumarathunge, Angelica Vårhammar, Chris J. Blackman, Rosana López, Owen K. Atkin, Kristine Y. Crous, Brendan Choat, Belinda E. Medlyn, Remko A. Duursma, Sebastian Pfautsch, Martin G. De Kauwe, Adrienne B. Nicotra, Craig V. M. Barton, Michael J. Aspinwall, David T. Tissue, Mingkai Jiang, Mark G. Tjoelker, Andrea Leigh, Hawkesbury Institute for the Environment, Western Sydney University, SUNY College of Environmental Science and Forestry (SUNY-ESF), State University of New York (SUNY), Department of Forest Resources, University of Minnesota [Twin Cities] (UMN), University of Minnesota System-University of Minnesota System, School of Life Sciences, University of Technology Sydney (UTS), Laboratoire de Physique et Physiologie Intégratives de l’Arbre en environnement Fluctuant (PIAF), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de la Recherche Agronomique (INRA), University of North Florida [Jacksonville] (UNF), University of New South Wales [Sydney] (UNSW), Australian National University (ANU), Australian Research Council Discovery DP140103415, and New South Wales Climate Action Grant NSW T07/CAG/016
Subjects: 0106 biological sciences, Canopy, Irrigation, Hot Temperature, 010504 meteorology & atmospheric sciences, warming, Climate Change, [SDV]Life Sciences [q-bio], Climate change, Forests, Photosynthesis, Atmospheric sciences, 01 natural sciences, thermal tolerance, Trees, heatwave, Environmental Chemistry, 0105 earth and related environmental sciences, General Environmental Science, Transpiration, Eucalyptus parramattensis, Global and Planetary Change, Eucalyptus, photosynthesis, Ecology, Global warming, temperature, Plant Transpiration, Vegetation, 15. Life on land, Plant Leaves, climate change, 13. Climate action, latent cooling, [SDE]Environmental Sciences, Environmental science, Climate model, 010606 plant biology & botany
Abstract: International audience; Heatwaves are likely to increase in frequency and intensity with climate change, which may impair tree function and forest C uptake. However, we have little information regarding the impact of extreme heatwaves on the physiological performance of large trees in the field. Here, we grew Eucalyptus parramattensis trees for 1 year with experimental warming (+ 3 degrees C) in a field setting, until they were greater than 6 m tall. We withheld irrigation for 1 month to dry the surface soils and then implemented an extreme heatwave treatment of 4 consecutive days with air temperatures exceeding 43 degrees C, while monitoring whole-canopy exchange of CO2 and H2O, leaf temperatures, leaf thermal tolerance, and leaf and branch hydraulic status. The heatwave reduced midday canopy photosynthesis to near zero but transpiration persisted, maintaining canopy cooling. A standard photosynthetic model was unable to capture the observed decoupling between photosynthesis and transpiration at high temperatures, suggesting that climate models may underestimate a moderating feedback of vegetation on heatwave intensity. The heatwave also triggered a rapid increase in leaf thermal tolerance, such that leaf temperatures observed during the heatwave were maintained within the thermal limits of leaf function. All responses were equivalent for trees with a prior history of ambient and warmed (+ 3 degrees C) temperatures, indicating that climate warming conferred no added tolerance of heatwaves expected in the future. This coordinated physiological response utilizing latent cooling and adjustment of thermal thresholds has implications for tree tolerance of future climate extremes as well as model predictions of future heatwave intensity at landscape and global scales.
Published: 2018

46. Elevated carbon dioxide is predicted to promote coexistence among competing species in a trait‐based model

Author: Peter B. Reich, Kristine Y. Crous, Belinda E. Medlyn, Ashehad A. Ali, and Thomas G. Aubier
Subjects: 0106 biological sciences, media_common.quotation_subject, Biology, 010603 evolutionary biology, 01 natural sciences, Competition (biology), chemistry.chemical_compound, species traits, Ecosystem, Nitrogen cycle, Ecology, Evolution, Behavior and Systematics, Original Research, Nature and Landscape Conservation, media_common, 2. Zero hunger, plant competition, species diversity, Ecology, Species diversity, Plant community, 15. Life on land, Plant ecology, chemistry, Carbon dioxide, Species evenness, Elevated CO2, 010606 plant biology & botany
Abstract: Differential species responses to atmospheric CO 2 concentration (Ca) could lead to quantitative changes in competition among species and community composition, with flow‐on effects for ecosystem function. However, there has been little theoretical analysis of how elevated Ca (eC a) will affect plant competition, or how composition of plant communities might change. Such theoretical analysis is needed for developing testable hypotheses to frame experimental research. Here, we investigated theoretically how plant competition might change under eC a by implementing two alternative competition theories, resource use theory and resource capture theory, in a plant carbon and nitrogen cycling model. The model makes several novel predictions for the impact of eC a on plant community composition. Using resource use theory, the model predicts that eC a is unlikely to change species dominance in competition, but is likely to increase coexistence among species. Using resource capture theory, the model predicts that eC a may increase community evenness. Collectively, both theories suggest that eC a will favor coexistence and hence that species diversity should increase with eC a. Our theoretical analysis leads to a novel hypothesis for the impact of eC a on plant community composition. This hypothesis has potential to help guide the design and interpretation of eC a experiments.
Published: 2015

47. Predicting long‐term carbon sequestration in response to CO 2 enrichment: How and why do current ecosystem models differ?

Author: Belinda E. Medlyn, Anthony P. Walker, David Wårlind, Shinichi Asao, Thomas Hickler, Soenke Zaehle, William J. Parton, Martin G. De Kauwe, Ying-Ping Wang, Richard J. Norby, and Daniel M. Ricciuto
Subjects: 0106 biological sciences, Atmospheric Science, Global and Planetary Change, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Ecology, chemistry.chemical_element, 15. Life on land, Carbon sequestration, Atmospheric sciences, 01 natural sciences, Nitrogen, Sink (geography), chemistry, Process dynamics, 13. Climate action, Turnover, Co2 concentration, Environmental Chemistry, Environmental science, Ecosystem, 010606 plant biology & botany, 0105 earth and related environmental sciences, General Environmental Science
Abstract: Large uncertainty exists in model projections of the land carbon (C) sink response to increasing atmospheric CO2. Free-Air CO2 Enrichment (FACE) experiments lasting a decade or more have investigated ecosystem responses to a step change in atmospheric CO2 concentration. To interpret FACE results in the context of gradual increases in atmospheric CO2 over decades to centuries, we used a suite of seven models to simulate the Duke and Oak Ridge FACE experiments extended for 300 years of CO2 enrichment. We also determine key modeling assumptions that drive divergent projections of terrestrial C uptake and evaluate whether these assumptions can be constrained by experimental evidence. All models simulated increased terrestrial C pools resulting from CO2 enrichment, though there was substantial variability in quasi-equilibrium C sequestration and rates of change. In two of two models that assume that plant nitrogen (N) uptake is solely a function of soil N supply, the net primary production response to elevated CO2 became progressively N limited. In four of five models that assume that N uptake is a function of both soil N supply and plant N demand, elevated CO2 led to reduced ecosystem N losses and thus progressively relaxed nitrogen limitation. Many allocation assumptions resulted in increased wood allocation relative to leaves and roots which reduced the vegetation turnover rate and increased C sequestration. In addition, self-thinning assumptions had a substantial impact on C sequestration in two models. Accurate representation of N process dynamics (in particular N uptake), allocation, and forest self-thinning is key to minimizing uncertainty in projections of future C sequestration in response to elevated atmospheric CO2. (Less)
Published: 2015

48. Photosynthetic temperature responses of tree species in Rwanda: evidence of pronounced negative effects of high temperature in montane rainforest climax species

Author: Donat Nsabimana, Göran Wallin, Belinda E. Medlyn, Thomas B. Hasper, Johan Uddling, Angelica Vårhammar, Mirindi Eric Dusenge, and Christopher M. McLean
Subjects: Rainforest, Physiology, Ribulose-Bisphosphate Carboxylase, Introduced species, Plant Science, Photosynthesis, Global Warming, Models, Biological, Trees, Electron Transport, chemistry.chemical_compound, Climax species, Botany, Temperate climate, Tropical Climate, biology, Ecology, Global warming, RuBisCO, Rwanda, Temperature, Carbon Dioxide, Plant Leaves, chemistry, Carbon dioxide, biology.protein
Abstract: The sensitivity of photosynthetic metabolism to temperature has been identified as a key uncertainty for projecting the magnitude of the terrestrial feedback on future climate change. While temperature responses of photosynthetic capacities have been comparatively well investigated in temperate species, the responses of tropical tree species remain unexplored. We compared the responses of seedlings of native cold-adapted tropical montane rainforest tree species with those of exotic warm-adapted plantation species, all growing in an intermediate temperature common garden in Rwanda. Leaf gas exchange responses to carbon dioxide (CO2 ) at different temperatures (20-40°C) were used to assess the temperature responses of biochemical photosynthetic capacities. Analyses revealed a lower optimum temperature for photosynthetic electron transport rates than for Rubisco carboxylation rates, along with lower electron transport optima in the native cold-adapted than in the exotic warm-adapted species. The photosynthetic optimum temperatures were generally exceeded by daytime peak leaf temperatures, in particular in the native montane rainforest climax species. This study thus provides evidence of pronounced negative effects of high temperature in tropical trees and indicates high susceptibility of montane rainforest climax species to future global warming.
Published: 2015

49. Volatile isoprenoid emissions from plastid to planet

Author: M. P. Barkley, Sandy P. Harrison, Belinda E. Medlyn, Ülo Niinemets, Francesco Loreto, K. G. Srikanta Dani, Catherine Morfopoulos, Brian J. Atwell, Josep Peñuelas, Michelle R. Leishman, Almut Arneth, I. Colin Prentice, Ian J. Wright, Malcolm Possell, Harrison, Sp, Morfopoulos, C, Dani, Kg, Prentice, Ic, Arneth, A, Atwell, Bj, Barkley, Mp, Leishman, Mr, Loreto, F, Medlyn, Be, Niinemets, U, Possell, M, Penuelas, J, and Wright, Ij
Subjects: Chloroplasts, Physiology, Plant Science, 010501 environmental sciences, Atmospheric sciences, Models, Biological, 01 natural sciences, Atmosphere, 03 medical and health sciences, chemistry.chemical_compound, Planet, Photosynthesis, Plastid, Air quality index, Ecosystem, Isoprene, 030304 developmental biology, 0105 earth and related environmental sciences, 0303 health sciences, Terpenes, Ecology, Temperature, Primary production, Carbon Dioxide, Plants, Adaptation, Physiological, Droughts, Plant Leaves, chemistry, 13. Climate action, Greenhouse gas, Atmospheric chemistry, Environmental science, Seasons, Volatilization
Abstract: Summary Approximately 1–2% of net primary production by land plants is re-emitted to the atmosphere as isoprene and monoterpenes. These emissions play major roles in atmospheric chemistry and air pollution–climate interactions. Phenomenological models have been developed to predict their emission rates, but limited understanding of the function and regulation of these emissions has led to large uncertainties in model projections of air quality and greenhouse gas concentrations. We synthesize recent advances in diverse fields, from cell physiology to atmospheric remote sensing, and use this information to propose a simple conceptual model of volatile isoprenoid emission based on regulation of metabolism in the chloroplast. This may provide a robust foundation for scaling up emissions from the cellular to the global scale.
Published: 2012

50. Challenging terrestrial biosphere models with data from the long‐term multifactor Prairie Heating and CO 2 Enrichment experiment

Author: K. A. Luus, Anthony P. Walker, Sönke Zaehle, Elise Pendall, Xingjie Lu, Ying-Ping Wang, Thomas Hickler, Yiqi Luo, Bertrand Guenet, Christian Werner, Tamara J. Zelikova, Jack A. Morgan, Edmund Ryan, Martin G. De Kauwe, Richard J. Norby, William J. Parton, Shinichi Asao, Yolima Carrillo, Shijie Shu, Anna B. Harper, Feike A. Dijkstra, Belinda E. Medlyn, Jianyang Xia, Atul K. Jain, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, Growing season, Atmospheric sciences, phenology, 01 natural sciences, Grassland, models, allocation, FACE, Environmental Chemistry, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Nitrogen cycle, Water content, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, Hydrology, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Global and Planetary Change, geography, geography.geographical_feature_category, Ecology, Phenology, carbon dioxide, temperature, Biosphere, Primary production, Global change, 15. Life on land, 13. Climate action, PHACE, Environmental science, grassland, soil moisture, 010606 plant biology & botany
Abstract: Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31–390 g C m−2 yr−1). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO2-induced water savings to extend the growing season length. Observed interactive (CO2 × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.
Published: 2017

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