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As Open Science practices become more commonplace, there is a need for the next generation of scientists to be well versed in these aspects of scientific research. Yet, many training opportunities for early career researchers (ECRs) could better emphasize or integrate Open Science elements. Field courses provide opportunities for ECRs to apply theoretical knowledge, practice new methodological approaches, and gain an appreciation for the challenges of real‐life research, and could provide an excellent platform for integrating training in Open Science practices. Our recent experience, as primarily ECRs engaged in a field course interrupted by COVID‐19, led us to reflect on the potential to enhance learning outcomes in field courses by integrating Open Science practices and online learning components. Specifically, we highlight the opportunity for field courses to align teaching activities with the recent developments and trends in how we conduct research, including training in: publishing registered reports, collecting data using standardized methods, adopting high‐quality data documentation, managing data through reproducible workflows, and sharing and publishing data through appropriate channels. We also discuss how field courses can use online tools to optimize time in the field, develop open access resources, and cultivate collaborations. By integrating these elements, we suggest that the next generation of field courses will offer excellent arenas for participants to adopt Open Science practices., Open Science methodology is becoming an increasingly important goal of scientific research. Yet, our higher education system does not necessarily reflect these developments, even though such methods are beneficial for the advancement of early career researchers. Here we highlight how field courses can be a valuable resource for early career researchers and our learning of best practice in Open Science methodology, and how online workflows can support this process.

A fundamental assumption in trait-based ecology is that relationships between traits and environmental conditions are globally consistent. We use field-quantified microclimate and soil data to explore if trait–environment relationships are generalizable across plant communities and spatial scales. We collected data from 6,720 plots and 217 species across four distinct tundra regions from both hemispheres. We combined these data with over 76,000 database trait records to relate local plant community trait composition to broad gradients of key environmental drivers: soil moisture, soil temperature, soil pH and potential solar radiation. Results revealed strong, consistent trait–environment relationships across Arctic and Antarctic regions. This indicates that the detected relationships are transferable between tundra plant communities also when fine-scale environmental heterogeneity is accounted for, and that variation in local conditions heavily influences both structural and leaf economic traits. Our results strengthen the biological and mechanistic basis for climate change impact predictions of vulnerable high-latitude ecosystems. acceptedVersion

A prominent signal of the Anthropocene is the extinction and population reduction of the megabiota—the largest animals and plants on the planet. However, we lack a predictive framework for the sensitivity of megabiota during times of rapid global change and how they impact the functioning of ecosystems and the biosphere. Here, we extend metabolic scaling theory and use global simulation models to demonstrate that (i) megabiota are more prone to extinction due to human land use, hunting, and climate change; (ii) loss of megabiota has a negative impact on ecosystem metabolism and functioning; and (iii) their reduction has and will continue to significantly decrease biosphere functioning. Global simulations show that continued loss of large animals alone could lead to a 44%, 18% and 92% reduction in terrestrial heterotrophic biomass, metabolism, and fertility respectively. Our findings suggest that policies that emphasize the promotion of large trees and animals will have disproportionate impact on biodiversity, ecosystem processes, and climate mitigation., Human-driven losses of megafauna and megaflora may have disproportionate ecological consequences. Here, the authors combine metabolic scaling theory and global simulation models to show that past and continued reduction of megabiota have and will continue to decrease ecosystem and biosphere functioning.

Datos disponibles en https://github.com/fmsabatini/sPlotOpen_Code, EU H2020 project BACI, Grant No. 640176 (...), Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E.A., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jiménez-Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Alvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., de Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El-Sheikh, M.A.E.-R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán-de-Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J.-A., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Peñuelas, J., Pérez-Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas-Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J.-C., Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez-Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., von Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H.-F., Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H.

Predictions from species distribution models (SDMs) are commonly used in support of environmental decision-making to explore potential impacts of climate change on biodiversity. However, because future climates are likely to differ from current climates, there has been ongoing interest in understanding the ability of SDMs to predict species responses under novel conditions (i.e., model transferability). Here, we explore the spatial and environmental limits to extrapolation in SDMs using forest inventory data from 11 model algorithms for 108 tree species across the western United States. Algorithms performed well in predicting occurrence for plots that occurred in the same geographic region in which they were fitted. However, a substantial portion of models performed worse than random when predicting for geographic regions in which algorithms were not fitted. Our results suggest that for transfers in geographic space, no specific algorithm was better than another as there were no significant differences in predictive performance across algorithms. There were significant differences in predictive performance for algorithms transferred in environmental space with GAM performing best. However, the predictive performance of GAM declined steeply with increasing extrapolation in environmental space relative to other algorithms. The results of this study suggest that SDMs may be limited in their ability to predict species ranges beyond the environmental data used for model fitting. When predicting climate-driven range shifts, extrapolation may also not reflect important biotic and abiotic drivers of species ranges, and thus further misrepresent the realized shift in range. Future studies investigating transferability of process based SDMs or relationships between geodiversity and biodiversity may hold promise.

AIM: The geographic range and ecological niche of species are widely used concepts in ecology, evolution and conservation and many modelling approaches have been developed to quantify each. Niche and distribution modelling methods require a litany of design choices; differences among subdisciplines have created communication barriers that increase isolation of scientific advances. As a result, understanding and reproducing the work of others is difficult, if not impossible. It is often challenging to evaluate whether a model has been built appropriately for its intended application or subsequent reuse. Here, we propose a standardized model metadata framework that enables researchers to understand and evaluate modelling decisions while making models fully citable and reproducible. Such reproducibility is critical for both scientific and policy reports, while international standardization enables better comparison between different scenarios and research groups. INNOVATION: Range modelling metadata (RMMS) address three challenges: they (a) are designed for convenience to encourage use, (b) accommodate a wide variety of applications, and (c) are extensible to allow the research community to steer them as needed. RMMS are based on a metadata dictionary that specifies a hierarchical structure to catalogue different aspects of the range modelling process. The dictionary balances a constrained, minimalist vocabulary to improve standardization with flexibility for users to modify and extend. To facilitate use, we have developed an R package, rangeModelMetaData, to build templates, automatically fill values from common modelling objects, check for inconsistencies with standards, and suggest values. MAIN CONCLUSIONS: Range Modelling Metadata tools foster cross‐disciplinary advances in biogeography, conservation and allied disciplines by improving evaluation, model sharing, model searching, comparisons and reproducibility among studies. Our initially proposed standards here are designed to be modified and extended to evolve with research trends and needs.

Trait-based ecology claims to offer a mechanistic approach for explaining the drivers that structure biological diversity and predicting the responses of species, trophic interactions and ecosystems to environmental change. However, support for this claim is lacking across broad taxonomic groups. A framework for defining ecosystem processes in terms of the functional traits of their constituent taxa across large spatial scales is needed. Here, we provide a comprehensive assessment of the linkages between climate, plant traits and soil microbial traits at many sites spanning a broad latitudinal temperature gradient from tropical to subalpine forests. Our results show that temperature drives coordinated shifts in most plant and soil bacterial traits but these relationships are not observed for most fungal traits. Shifts in plant traits are mechanistically associated with soil bacterial functional traits related to carbon (C), nitrogen (N) and phosphorus (P) cycling, indicating that microbial processes are tightly linked to variation in plant traits that influence rates of ecosystem decomposition and nutrient cycling. Our results are consistent with hypotheses that diversity gradients reflect shifts in phenotypic optima signifying local temperature adaptation mediated by soil nutrient availability and metabolism. They underscore the importance of temperature in structuring the functional diversity of plants and soil microbes in forest ecosystems and how this is coupled to biogeochemical processes via functional traits.

Aims Plant height is a key functional trait related to aboveground biomass, leaf photosynthesis and plant fitness. However, large-scale geographical patterns in community-average plant height (CAPH) of woody species and drivers of these patterns across different life forms remain hotly debated. Moreover, whether CAPH could be used as a predictor of ecosystem primary productivity is unknown. Methods We compiled mature height and distributions of 11 422 woody species in eastern Eurasia, and estimated geographic patterns in CAPH for different taxonomic groups and life forms. Then we evaluated the effects of environmental (including current climate and historical climate change since the Last Glacial Maximum (LGM)) and evolutionary factors on CAPH. Lastly, we compared the predictive power of CAPH on primary productivity with that of LiDAR-derived canopy-height data from a global survey. Important Findings Geographic patterns of CAPH and their drivers differed among taxonomic groups and life forms. The strongest predictor for CAPH of all woody species combined, angiosperms, all dicots and deciduous dicots was actual evapotranspiration, while temperature was the strongest predictor for CAPH of monocots and tree, shrub and evergreen dicots, and water availability for gymnosperms. Historical climate change since the LGM had only weak effects on CAPH. No phylogenetic signal was detected in family-wise average height, which was also unrelated to the tested environmental factors. Finally, we found a strong correlation between CAPH and ecosystem primary productivity. Primary productivity showed a weaker relationship with CAPH of the tallest species within a grid cell and no relationship with LiDAR-derived canopy height reported in the global survey. Our findings suggest that current climate rather than historical climate change and evolutionary history determine the geographical patterns in CAPH. However, the relative effects of climatic factors representing environmental energy and water availability on spatial variations of CAPH vary among plant life forms. Moreover, our results also suggest that CAPH can be used as a good predictor of ecosystem primary productivity.

Latitudinal and elevational richness gradients have received much attention from ecologists but there is little consensus on underlying causes. One possible proximate cause is increased levels of species turnover, or β diversity, in the tropics compared to temperate regions. Here, we leverage a large botanical dataset to map taxonomic and phylogenetic β diversity, as mean turnover between neighboring 100 × 100 km cells, across the Americas and determine key climatic drivers. We find taxonomic and tip-weighted phylogenetic β diversity is higher in the tropics, but that basal-weighted phylogenetic β diversity is highest in temperate regions. Supporting Janzen's ‘mountain passes’ hypothesis, tropical mountainous regions had higher β diversity than temperate regions for taxonomic and tip-weighted metrics. The strongest climatic predictors of turnover were average temperature and temperature seasonality. Taken together, these results suggest β diversity is coupled to latitudinal richness gradients and that temperature is a major driver of plant community composition and change.

Much ecological research aims to explain how climate impacts biodiversity and ecosystem-level processes through functional traits that link environment with individual performance. However, the specific climatic drivers of functional diversity across space and time remain unclear due largely to limitations in the availability of paired trait and climate data. We compile and analyze a global forest dataset using a method based on abundance-weighted trait moments to assess how climate influences the shapes of whole-community trait distributions. Our approach combines abundance-weighted metrics with diverse climate factors to produce a comprehensive catalog of trait–climate relationships that differ dramatically—27% of significant results change in sign and 71% disagree on sign, significance, or both—from traditional species-weighted methods. We find that ( i ) functional diversity generally declines with increasing latitude and elevation, ( ii ) temperature variability and vapor pressure are the strongest drivers of geographic shifts in functional composition and ecological strategies, and ( iii ) functional composition may currently be shifting over time due to rapid climate warming. Our analysis demonstrates that climate strongly governs functional diversity and provides essential information needed to predict how biodiversity and ecosystem function will respond to climate change.

Tropical forest leaf albedo (reflectance) greatly impacts how much energy the planet absorbs; however; little is known about how it might be impacted by climate change. Here, we measure leaf traits and leaf albedo at ten 1-ha plots along a 3,200-m elevation gradient in Peru. Leaf mass per area (LMA) decreased with warmer temperatures along the elevation gradient; the distribution of LMA was positively skewed at all sites indicating a shift in LMA towards a warmer climate and future reduced tropical LMA. Reduced LMA was significantly (P

To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature’s contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally. We found that selecting the top-ranked 30% and 50% of terrestrial land area would conserve respectively 60.7% and 85.3% of the estimated total carbon stock and 66% and 89.8% of all clean water, in addition to meeting conservation targets for 57.9% and 79% of all species considered. Our data and prioritization further suggest that adequately conserving all species considered (vertebrates and plants) would require giving conservation attention to ~70% of the terrestrial land surface. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to meet conservation targets for 81.3% of the terrestrial plant and vertebrate species considered. Our results provide a global assessment of where land could be optimally managed for conservation. We discuss how such a spatial prioritization framework can support the implementation of the biodiversity and climate conventions.

Tropical forest ecosystems are undergoing rapid transformation as a result of changing environmental conditions and direct human impacts. However, we cannot adequately understand, monitor or simulate tropical ecosystem responses to environmental changes without capturing the high diversity of plant functional characteristics in the species-rich tropics. Failure to do so can oversimplify our understanding of ecosystems responses to environmental disturbances. Innovative methods and data products are needed to track changes in functional trait composition in tropical forest ecosystems through time and space. This study aimed to track key functional traits by coupling Sentinel-2 derived variables with a unique data set of precisely located in-situ measurements of canopy functional traits collected from 2434 individual trees across the tropics using a standardised methodology. The functional traits and vegetation censuses were collected from 47 field plots in the countries of Australia, Brazil, Peru, Gabon, Ghana, and Malaysia, which span the four tropical continents. The spatial positions of individual trees above 10 cm diameter at breast height (DBH) were mapped and their canopy size and shape recorded. Using geo-located tree canopy size and shape data, community-level trait values were estimated at the same spatial resolution as Sentinel-2 imagery (i.e. 10 m pixels). We then used the Geographic Random Forest (GRF) to model and predict functional traits across our plots. We demonstrate that key plant functional traits can be accurately predicted across the tropicsusing the high spatial and spectral resolution of Sentinel-2 imagery in conjunction with climatic and soil information. Image textural parameters were found to be key components of remote sensing information for predicting functional traits across tropical forests and woody savannas. Leaf thickness (R2 = 0.52) obtained the highest prediction accuracy among the morphological and structural traits and leaf carbon content (R2 = 0.70) and maximum rates of photosynthesis (R2 = 0.67) obtained the highest prediction accuracy for leaf chemistry and photosynthesis related traits, respectively. Overall, the highest prediction accuracy was obtained for leaf chemistry and photosynthetic traits in comparison to morphological and structural traits. Our approach offers new opportunities for mapping, monitoring and understanding biodiversity and ecosystem change in the most species-rich ecosystems on Earth.

The sizes and shapes of tree crowns are of fundamental importance in ecology, yet understanding the forces that determine them remains elusive. A cardinal question facing ecologists is the degree to which general and non-specific versus ecological and context-dependent processes are responsible for shaping tree crowns. Here, we test this question for the first time across diverse tropical ecosystems. Using trees from 20 plots varying in elevation, precipitation, and ecosystem type (savanna-forest transitions) across the paleo- and neo-tropics, we test the relationship between crown dimensions and tree size. By analyzing these scaling relationships across environmental gradients, biogeographic regions, and phylogenetic distance, we extend Metabolic Scaling Theory (MST) predictions to include how local selective pressures shape variation in crown dimensions. Across all sites, we find strong agreement between mean trends and MST predictions for the scaling of crown size and shape, but large variation around the mean. While MST explained approximately half of the observed variation in tree crown dimensions, we find that local, ecosystem, and phylogenetic predictors account for the half of the residual variation. Crown scaling does not change significantly across regions, but does change across ecosystem types, where savanna tree crowns grow more quickly with tree girth than forest tree crowns. Crowns of legumes were wider and more voluminous than those of other taxa. Thus, while MST can accurately describe the central tendency of tree crown size, local ecological conditions and evolutionary history appear to modify the scaling of crown shape. Importantly, our extension of MST incorporating these differences accounts for the mechanisms driving variation in the scaling of crown dimensions across the tropics. We present allometric equations for the prediction of crown dimensions across tropical ecosystems. These results are critical when scaling the function of individual trees to larger spatial scales or incorporating the size and shape of tree crowns in global biogeochemical models.

Synthesis has become ubiquitous in ecology. Despite its widespread application to a broad range of research topics, it remains unclear how synthesis has affected the discipline. Using a case study of publications (n = 2304) from the National Center for Ecological Analysis and Synthesis compared with papers with similar keywords from the Web of Science (n = 320,000), we address several questions about the comparative impact of synthesis, the role of synthesis in driving key research themes, and whether synthesis is focused on different topics than is the broader ecological literature. We found much higher citation rates for synthesis papers overall (fivefold more) and within eleven key topic themes (e.g., species richness, biodiversity, climate change, global change). Synthesis papers often played key roles in driving, redirecting, or resolving core questions and exhibited much greater cross-theme connectivity. Together, these results indicate that synthesis in science has played a crucial role in accelerating and advancing ecological knowledge.

Limiting climate change to less than 2°C is the focus of international policy under the climate convention (UNFCCC), and is essential to preventing extinctions, a focus of the Convention on Biological Diversity (CBD). The post-2020 biodiversity framework drafted by the CBD proposes conserving 30% of both land and oceans by 2030. However, the combined impact on extinction risk of species from limiting climate change and increasing the extent of protected and conserved areas has not been assessed. Here we create conservation spatial plans to minimize extinction risk in the tropics using data on 289 219 species and modeling two future greenhouse gas concentration pathways (RCP2.6 and 8.5) while varying the extent of terrestrial protected land and conserved areas from

Although trees are key to ecosystem functioning, many forests and tree species across the globe face strong threats. Preserving areas of high biodiversity is a core priority for conservation; however, different dimensions of biodiversity and varied conservation targets make it difficult to respond effectively to this challenge. Here, we (i) identify priority areas for global tree conservation using comprehensive coverage of tree diversity based on taxonomy, phylogeny, and functional traits; and (ii) compare these findings to existing protected areas and global biodiversity conservation frameworks. We find that ca. 51% of the top-priority areas for tree biodiversity are located in current protected areas. The remaining half top-priority areas are subject to moderate to high human pressures, indicating conservation actions are needed to mitigate these human impacts. Our findings emphasize the effectiveness of using tree conservation priority areas for future global conservation planning.

Foliar trait adaptation to sun and shade has been extensively studied in the context of photosynthetic performance of plants, focusing on nitrogen allocation, light capture and use via chlorophyll pigments and leaf morphology; however, less is known about the potential sun-shade dichotomy of other functionally important foliar traits. In this study, we measured 19 traits in paired sun and shade leaves along a 3,500-m elevation gradient in southern Peru to test whether the traits differ with canopy position, and to assess if relative differences vary with species composition and/or environmental filters. We found significant sun-shade differences in leaf mass per area (LMA), photosynthetic pigments (Chl ab and Car), and δ13C. Sun-shade offsets among these traits remained constant with elevation, soil substrates, and species compositional changes. However, other foliar traits related to structure and chemical defense, and those defining general metabolic processes, did not differ with canopy position. Our results suggest that whole-canopy function is captured in many traits of sun leaves; however, photosynthesis-related traits must be scaled based on canopy light extinction. These findings show that top-of-canopy measurements of foliar chemistry from spectral remote sensing approaches map directly to whole-canopy foliar traits including shaded leaves that cannot be directly observed from above.

A key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10 480 woody dicots in China and 2374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem primary productivity, independent of plant life form. These relationships likely reflect how natural selection modifies leaf size across varying climates in conjunction with how climate influences canopy total leaf area. We find that the leaf size‒primary productivity functions based on the Chinese dataset can predict productivity in North America and vice‐versa. In addition to advancing understanding of the relationship between a climate‐driven trait and ecosystem functioning, our findings suggest that leaf size can also be a promising tool in palaeoecology for scaling from fossil leaves to palaeo‐primary productivity of woody ecosystems., Based on leaf size and distribution data for 10 480 woody dicots in China and 2374 in North America, we found that leaf size of woody dicots well predicts ecosystem primary productivity both in China and North America, and its independent and direct effects on primary productivity is higher than (or in a few cases comparable to) those of climate, soil characteristics and leaf area index. Our results suggest that leaf size provides a promising surrogate to reconstruct palaeo‐primary productivity of terrestrial woody ecosystems based on fossil leaf deposits.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Summary paragraphTo meet the ambitious objectives of biodiversity and climate conventions, countries and the international community require clarity on how these objectives can be operationalized spatially, and multiple targets be pursued concurrently1. To support governments and political conventions, spatial guidance is needed to identify which areas should be managed for conservation to generate the greatest synergies between biodiversity and nature’s contribution to people (NCP). Here we present results from a joint optimization that maximizes improvements in species conservation status, carbon retention and water provisioning and rank terrestrial conservation priorities globally. We found that, selecting the top-ranked 30% (respectively 50%) of areas would conserve 62.4% (86.8%) of the estimated total carbon stock and 67.8% (90.7%) of all clean water provisioning, in addition to improving the conservation status for 69.7% (83.8%) of all species considered. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to improve the conservation status of 86.3% of plant and vertebrate species on Earth. Our results provide a global baseline on where land could be managed for conservation. We discuss how such a spatial prioritisation framework can support the implementation of the biodiversity and climate conventions.

[Aim] Intraspecific trait variation (ITV) within natural plant communities can be large, influencing local ecological processes and dynamics. Here, we shed light on how ITV in vegetative and floral traits responds to large‐scale abiotic and biotic gradients (i.e., climate and species richness). Specifically, we tested whether associations of ITV with temperature, precipitation and species richness were consistent with any of four hypotheses relating to stress tolerance and competition. Furthermore, we estimated the degree of correlation between ITV in vegetative and floral traits and how they vary along the gradients., [Location] Global., [Time period] 1975–2016., [Major taxa studied] Herbaceous and woody plants., [Methods] We compiled a dataset of 18,401 measurements of the absolute extent of ITV (measured as the coefficient of variation) in nine vegetative and seven floral traits from 2,822 herbaceous and woody species at 2,372 locations., [Results] Large‐scale associations between ITV and climate were trait specific and more prominent for vegetative traits, especially leaf morphology, than for floral traits. The ITV showed pronounced associations with climate, with lower ITV values in colder areas and higher values in drier areas. The associations of ITV with species richness were inconsistent across traits. Species‐specific associations across gradients were often idiosyncratic, and covariation in ITV was weaker between vegetative and floral traits than within the two trait groups. [Main conclusions] Our results show that, depending on the traits considered, ITV either increased or decreased with climate stress and species richness, suggesting that both factors can constrain or enhance ITV, which might foster plant‐population persistence in stressful conditions. Given the species‐specific responses and covariation in ITV, associations can be hard to predict for traits and species not yet studied. We conclude that consideration of ITV can improve our understanding of how plants cope with stressful conditions and environmental change across spatial and biological scales., Open Access funding was provided by Ulm University under the DEAL‐agreement.

Remote sensing of trait-based ecology can improve our understanding of the effect of trait diversity on ecosystem functioning., Spatially continuous data on functional diversity will improve our ability to predict global change impacts on ecosystem properties. We applied methods that combine imaging spectroscopy and foliar traits to estimate remotely sensed functional diversity in tropical forests across an Amazon-to-Andes elevation gradient (215 to 3537 m). We evaluated the scale dependency of community assembly processes and examined whether tropical forest productivity could be predicted by remotely sensed functional diversity. Functional richness of the community decreased with increasing elevation. Scale-dependent signals of trait convergence, consistent with environmental filtering, play an important role in explaining the range of trait variation within each site and along elevation. Single- and multitrait remotely sensed measures of functional diversity were important predictors of variation in rates of net and gross primary productivity. Our findings highlight the potential of remotely sensed functional diversity to inform trait-based ecology and trait diversity-ecosystem function linkages in hyperdiverse tropical forests.

Author(s): Weiser, MD; Swenson, NG; Enquist, BJ; Michaletz, S; Waide, RB; Zhou, J; Kaspari, M | Abstract: Aim: To test the latitudinal gradient in plant species diversity for self-similarity across taxonomic scales and amongst taxa. Location: North America. Methods: We used species richness data from 245 local vascular plant floras to quantify the slope and shape of the latitudinal gradients in species diversity (LGSD) across all plant species as well as within each family and order. We calculated the contribution of each family and order to the empirical LGSD. Results: We observed the canonical LGSD when all plants were considered with floras at the lowest latitudes having, on average, 451 more species than floras at the highest latitudes. When considering slope alone, most orders and families showed the expected negative slope, but 31.7% of families and 27.7% of orders showed either no significant relationship between latitude and diversity or a reverse LGSD. Latitudinal patterns of family diversity account for at least 14% of this LGSD. Most orders and families did not show the negative slope and concave-down quadratic shape expected by the pattern for all plant species. A majority of families did not make a significant contribution in species to the LGSD with 53% of plant families contributing little to nothing to the overall gradient. Ten families accounted for more than 70% of the gradient. Two families, the Asteraceae and Fabaceae, contributed a third of the LGSD. Main Conclusions: The empirical LGSD we describe here is a consequence of a gradient in the number of families and diversification within relative few plant families. Macroecological studies typically aim to generate models that are general across taxa with the implicit assumption that the models are general within taxa. Our results strongly suggest that models of the latitudinal gradient in plant species richness that rely on environmental covariates (e.g. temperature, energy) are likely not general across plant taxa.

Aim: Tropical forests account for a quarter of the global carbon storage and a third of the terrestrial productivity. Few studies have teased apart the relative importance of environmental factors and forest attributes for ecosystem functioning, especially for the tropics. This study aims to relate aboveground biomass (AGB) and biomass dynamics (i.e., net biomass productivity and its underlying demographic drivers: biomass recruitment, growth and mortality) to forest attributes (tree diversity, community-mean traits and stand basal area) and environmental conditions (water availability, soil fertility and disturbance). Location: Neotropics. Methods: We used data from 26 sites, 201 1-ha plots and >92,000 trees distributed across the Neotropics. We quantified for each site water availability and soil total exchangeable bases and for each plot three key community-weighted mean functional traits that are important for biomass stocks and productivity. We used structural equation models to test the hypothesis that all drivers have independent, positive effects on biomass stocks and dynamics. Results: Of the relationships analysed, vegetation attributes were more frequently associated significantly with biomass stocks and dynamics than environmental conditions (in 67 vs. 33% of the relationships). High climatic water availability increased biomass growth and stocks, light disturbance increased biomass growth, and soil bases had no effect. Rarefied tree species richness had consistent positive relationships with biomass stocks and dynamics, probably because of niche complementarity, but was not related to net biomass productivity. Community-mean traits were good predictors of biomass stocks and dynamics. Main conclusions: Water availability has a strong positive effect on biomass stocks and growth, and a future predicted increase in (atmospheric) drought might, therefore, potentially reduce carbon storage. Forest attributes, including species diversity and community-weighted mean traits, have independent and important relationships with AGB stocks, dynamics and ecosystem functioning, not only in relatively simple temperate systems, but also in structurally complex hyper-diverse tropical forests.

UK Natural Environment Research Council [NE/J023418/1, NE/M019160/1]; European Research Council [321131, 291585]; John D. and Catherine T. MacArthur Foundation; U.S. National Science Foundation [DEB - 1209287]; Carnegie Institution for Science; National Science Foundation [DEB - 1146206]; Leverhulme Trust, UK; Jackson Foundation; European Community [290605]; John Fell Fund; Google Earth Engine award

The Arctic is warming twice as fast as the rest of the planet, leading to rapid changes in species composition and plant functional trait variation. Landscape-level maps of vegetation composition and trait distributions are required to expand spatially-limited plot studies, overcome sampling biases associated with the most accessible research areas, and create baselines from which to monitor environmental change. Unmanned aerial vehicles (UAVs) have emerged as a low-cost method to generate high-resolution imagery and bridge the gap between fine-scale field studies and lower resolution satellite analyses. Here we used field spectroscopy data (400–2500 nm) and UAV multispectral imagery to test spectral methods of species identification and plant water and chemistry retrieval near Longyearbyen, Svalbard. Using the field spectroscopy data and Random Forest analysis, we were able to distinguish eight common High Arctic plant tundra species with 74% accuracy. Using partial least squares regression (PLSR), we were able to predict corresponding water, nitrogen, phosphorus and C:N values (r 2 = 0.61–0.88, RMSEmean = 12%–64%). We developed analogous models using UAV imagery (five bands: Blue, Green, Red, Red Edge and Near-Infrared) and scaled up the results across a 450 m long nutrient gradient located underneath a seabird colony. At the UAV level, we were able to map three plant functional groups (mosses, graminoids and dwarf shrubs) at 72% accuracy and generate maps of plant chemistry. Our maps show a clear marine-derived fertility gradient, mediated by geomorphology. We used the UAV results to explore two methods of upscaling plant water content to the wider landscape using Sentinel-2A imagery. Our results are pertinent for high resolution, low-cost mapping of the Arctic.

Hypervolume approaches are used to quantify functional diversity and quantify environmental niches for species distribution modelling. Recently, Qiao et al. (2016) criticized our geometrical kernel density estimation (KDE) method for measuring hypervolumes. They used a simulation analysis to argue that the method yields high error rates and makes biased estimates of fundamental niches. Here, we show that (a) KDE output depends in useful ways on dataset size and bias, (b) other species distribution modelling methods make equally stringent but different assumptions about dataset bias, (c) simulation results presented by Qiao et al. (2016) were incorrect, with revised analyses showing performance comparable to other methods, and (d) hypervolume methods are more general than KDE and have other benefits for niche modelling. As a result, our KDE method remains a promising tool for species distribution modelling.

While community-weighted means of plant traits have been linked to mean environmental conditions at large scales, the drivers of trait variation within communities are not well understood. Local environmental heterogeneity (such as microclimate variability), in addition to mean environmental conditions, may decrease the strength of environmental filtering and explain why communities support different amounts of trait variation. Here, we assess two hypotheses: first, that more heterogeneous local environments and second, that less extreme environments, should support a broader range of plant strategies and thus higher trait variation. We quantified drivers of trait variation across a range of environmental conditions and spatial scales ranging from sub-meter to tens of kilometers in montane and alpine plant communities. We found that, within communities, both environmental heterogeneity and environmental means are drivers of trait variation. However, the importance of each environmental factor varied depending on the trait. Our results indicate that larger-scale trait-climate linkages that hold across communities also apply at small spatial scales, suggesting that microclimate variation within communities is a key driver of community functional diversity. Microclimatic variation provides a potential mechanism for helping to maintaining diversity in local communities and also suggests that small-scale environmental heterogeneity should be measured as a better predictor of functional diversity. This article is protected by copyright. All rights reserved.

Correlative species distribution models are based on the observed relationship between species’ occurrence and macroclimate or other environmental variables. In climates predicted less favourable populations are expected to decline, and in favourable climates they are expected to persist. However, little comparative empirical support exists for a relationship between predicted climate suitability and population performance. We found that the performance of 93 populations of 34 plant species worldwide – as measured by in situ population growth rate, its temporal variation and extinction risk – was not correlated with climate suitability. However, correlations of demographic processes underpinning population performance with climate suitability indicated both resistance and vulnerability pathways of population responses to climate: in less suitable climates, plants experienced greater retrogression (resistance pathway) and greater variability in some demographic rates (vulnerability pathway). While a range of demographic strategies occur within species’ climatic niches, demographic strategies are more constrained in climates predicted to be less suitable.

Shrub communities have expanded in arctic and alpine tundra during recent decades. Changes in shrub abundance may alter ecosystem carbon (C) sequestration and storage, with potential positive or negative feedback on global C cycling. To assess potential implications of shrub expansion in different alpine plant communities, we compared C fluxes and pools in one Empetrum-dominated heath, one herb- and cryptogam-dominated meadow, and one Salix-shrub community in Central Norway. Over two growing seasons, we measured Gross Ecosystem Photosynthesis, Ecosystem Respiration (ER), and C pools for above-ground vegetation, litter, roots, and soil separated into organic and mineral horizons. Both the meadow and shrub communities had higher rates of C fixation and ER, but the total ecosystem C pool in the meadow was twice that of the shrub community because of more C in the organic soil horizon. Even though the heath community had the lowest rates of C fixation, it stored one and a half times more C than the shrub community. The results indicate that the relatively high above-ground biomass sequestering C during the growing season is not associated with high C storage in shrub-dominated communities. Instead, shrub-dominated areas may be draining the carbon-rich alpine soils because of high rates of decomposition. These processes were not shown by mid-growing season C fluxes, but were reflected by the very different distribution of C pools in the three habitats.

The abundance–adaptation hypothesis argues that taxa with more individuals and faster generation times will have more evolutionary ‘experiments’ allowing expansion into, and diversification within, novel habitats. Thus, as older taxa have produced more individuals over time, and smaller taxa have higher population sizes and faster generation times, the Latitudinal Diversity Gradients (LDGs) of these clades should show shallower slopes. We describe the LDGs for archaea, bacteria, fungi, invertebrates and trees from six North American forests. For three focal groups – bacteria, ants, and trees – older taxa had shallower LDG slopes than the more recent, terminal taxa. Across 12 orders of magnitude of body mass, LDG slopes were steeper in larger taxa. The slopes of LDGs vary systematically with body size and clade age, underscoring the non-canonical nature of LDGs. The steepest LDG slopes were found for the largest organisms while the smallest, from bacteria to small litter-soil invertebrates, have shallower- to zero-slope LDGs. If tropical niche conservatism is the failure of clades to adapt to, and diversify in temperate habitats, then the steep LDGs of chordates and plants likely arise from the decreased ability of clades with large individuals to adapt to the multiple challenges of extra-tropical life.

Aim: Determining the drivers of species rarity is fundamental for understanding and conserving biodiversity. Rarity of a given species within its community may arise due to exclusion by other ecologically similar species. Conversely, rare species may occupy habitats that are rare in the landscape or they may be ill-suited to all available habitats. The first mechanism would lead to common and rare species occupying similar ecological space defined by functional traits. The second mechanism would result in common and rare species occupying dissimilar ecological space and spatial aggregation of rare species, either because they are specialists in rare habitats or because rare species tend to be dispersal limited. Here, we quantified the contribution of locally rare species to community functional richness and the spatial aggregation of species across tree communities world-wide to address these hypotheses. Location: Asia and the Americas. Time period: 2002 to 2012 (period that considers the censuses for the plots used). Major taxa studied: Angiosperm and Gymnosperm trees. Methods: We compiled a dataset of functional traits from all the species present in eight tree plots around the world to evaluate the contribution of locally rare species to tree community functional richness using multi- and univariate approaches. We also quantified the spatial aggregation of individuals within species at several spatial scales as it relates to abundance. Results: Locally rare tree species in temperate and tropical forests tended to be functionally unique and are consistently spatially clustered. Furthermore, there is no evidence that this pattern is driven by pioneer species being locally rare. Main conclusions: This evidence shows that locally rare tree species disproportionately contribute to community functional richness, and we can therefore reject the hypothesis that locally rare species are suppressed by ecologically similar, but numerically dominant, species. Rather, locally rare species are likely to be specialists on spatially rare habitats or they may be ill-suited to the locally available environments.

The context of Open Biological Ontologies; (ii) whenever possible, the Entities and Qualities aretaken from existing terminology standards, mainly the Plant Ontology (PO) and Phenotypic QualityOntology (PATO) ontologies; and (iii) whenever a characteristic already has a definition, if appropriate,it is reused and referenced. The development of TOP, which complies with semantic web principles,was carried out through the involvement of experts from both the ecology and the semanticsresearch communities. Regular updates of TOP are planned, based on community feedback andinvolvement.3. TOP provides names, definitions, units, synonyms and related terms for about 850 plant characteristics.TOP is available online (www.top-thesaurus.org), and can be browsed using an alphabeticallist of characteristics, a hierarchical tree of characteristics, a faceted and a free-text search, andthrough an Application Programming Interface.4. Synthesis. Harmonizing definitions of concepts, as proposed by TOP, forms the basis for betterintegration of data across heterogeneous data sets and terminologies, thereby increasing the potentialfor data reuse. It also allows enhanced scientific synthesis. TOP therefore has the potential toimprove research and communication not only within the field of ecology, but also in related fieldswith interest in plant functioning and distribution Fil: Garnier, Eric. Université de Montpellier. Centre d'Ecologie Fonctionnelle et Evolutive; Francia Fil: Stahl, Ulrike. German Centre for Integrative Biodiversity Research; Alemania. Max-Planck-Institute for Biogeochemistry; Alemania. Department of Community Ecology, Helmholtz Centre for Environmental Research; Alemania Fil: Laporte, Marie-Angelique. Université de Montpellier. Centre d'Ecologie Fonctionnelle et Evolutive; Francia. German Centre for Integrative Biodiversity Research; Alemania. Bioversity International; Italia Fil: Kattge, Jens. Max-Planck-Institute for Biogeochemistry; Alemania. German Centre for Integrative Biodiversity Research; Alemania Fil: Mougenot, Isabelle. Maison de la Télédétection; Francia Fil: Kuhn, Ingolf. German Centre for Integrative Biodiversity Research; Alemania Fil: Laporte, Baptiste. Centre for the Synthesis and Analysis of Biodiversity; Francia Fil: Amiaud, Bernard. Université de Lorraine; Francia Fil: Ahrestani, Farshid S.. Columbia University; Estados Unidos Fil: Bonisch, Gerhard. Max-Planck-Institute for Biogeochemistry; Alemania Fil: Bunker, Daniel E.. New Jersey Institute of Technology. Department of Biological Sciences; Estados Unidos Fil: Cornelissen, Johannes H. C.. Vrije Universteit; Países Bajos Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Enquist, Brian J.. University of Arizona; Estados Unidos Fil: Gachet, Sophie. Avignon Université Avignon Université. Institut Méditerranéen de Biodiversité et d'Ecologie marine et continentale; Francia Fil: Jaureguiberry, Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Kleyer, Michael. University of Oldenburg. Institute of Biology and Environmental Sciences; Alemania Fil: Lavorel, Sandra. Université Joseph Fourier; Francia Fil: Maicher, Lutz. Universitat Jena; Alemania Fil: Pérez Harguindeguy, Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Poorter, Hendrik. Forschungszentrum Jülich; Alemania Fil: Schildhauer, Mark. University of California. National Center for Ecological Analysis and Synthesis; Estados Unidos Fil: Shipley, Bill. Université de Sherbrooke; Canadá Fil: Violle, Cyrille. Université de Montpellier; Francia Fil: Weiher, Evan. University of Wisconsin; Estados Unidos Fil: Wirth, Christian. German Centre for Integrative Biodiversity Research; Alemania Fil: Wright, Ian J.. Macquarie University; Australia Fil: Klotz, Stefan. Helmholtz Centre for Environmental Research; Alemania

Trait-based approaches have taken an increasingly dominant role in community ecology. Although trait-based strategy dimensions such as the leaf economic spectrum (LES) have been identified primarily at global-scales, trait variation at the community scale is often interpreted in this context. Here we argue from several lines of evidence that a research priority should be to determine whether global-scale trait relationships hold at more local scales. We review recent literature assessing trait variation at smaller scales, and then present a case study exploring the relationship between the correlation strength of leaf traits and their similarity in variation structure across ecological scales. We find that the correlation strength between pairs of leaf traits does not predict whether the traits respond similarly to different drivers of variation. Instead, correlation strength only sets an upper bound to the dissimilarity in trait variation structure. With moderate correlation strengths, LES traits largely retain the ability to respond independently to different drivers of phenotypic variation at different scales. Recent literature and our results suggest that LES relationships may not hold at local scales. Clarifying under what conditions and at which scales the LES is consistently expressed is necessary for us to make the most of the emerging trait toolbox.

Ecosystem processes are driven by both environmental variables and the attributes of component species. The extent to which these effects are independent and/or dependent upon each other has remained unclear. We assess the extent to which climate affects net primary productivity (NPP) both directly and indirectly via its effect on plant size and leaf functional traits. Using species occurrences and functional trait databases for North and South America, we describe the upper limit of woody plant height within 200 × 200 km grid-cells. In addition to maximum tree height, we quantify grid-cell means of three leaf traits (specific leaf area, and leaf nitrogen and phosphorus concentration) also hypothesized to influence productivity. Using structural equation modelling, we test the direct and indirect effects of environment and plant traits on remotely sensed MODIS-derived estimates of NPP, using plant size (satellite-measured canopy height and potential maximum tree height), leaf traits, growing season length, soil nutrients, climate and disturbances as explanatory variables. Our results show that climate affects NPP directly as well as indirectly via plant size in both tropical and temperate forests. In tropical forests NPP further increases with leaf phosphorus concentration, whereas in temperate forests it increases with leaf nitrogen concentration. In boreal forests, NPP most strongly increases with increasing temperature and neither plant size nor leaf traits have a significant influence. Synthesis. Our results suggest that at large spatial scales plant size and leaf nutrient traits can improve predictions of forest productivity over those based on climate alone. However, at higher latitudes their role is overridden by stressful climate. Our results provide independent empirical evidence for where and how global vegetation models predicting carbon fluxes could benefit from including effects of plant size and leaf stoichiometry.

The inverse relationship between size and abundance is a well‐documented pattern in forests, and the form of size–density relationships depends on the balance between growth and mortality rates in the community. Traditionally, studies of plant size distributions have focused on single‐species populations and forests, but here we examine diverse communities dominated by plants with varied life histories, including grasses, forbs, shrubs, and succulents. In particular, we test whether the parameters of the individual size distribution differ systematically across community types, whether they fit the contrasting predictions of metabolic or demographic theories, and whether they share a common cross‐community scaling relationship with forest communities and crop populations. All thirteen of our study sites better fit the predictions of demographic equilibrium theory, but interestingly, fits of both demographic and metabolic models showed little systematic variation across community types, despite large differences in environmental conditions and dominant life forms. Finally, analysis of the cross‐community scaling relationship demonstrates that natural and restored non‐forest communities conform to patterns of size and abundance observed among forest, plantation, and crop systems. Taken together, our results suggest that common ecological mechanisms govern plant community size structure across broad environmental gradients, regardless of the dominant plant life forms or limiting resources.

Climatic changes have profound effects on the distribution of biodiversity, but untangling the links between climatic change and ecosystem functioning is challenging, particularly in high diversity systems such as tropical forests. Tropical forests may also show different responses to a changing climate, with baseline climatic conditions potentially inducing differences in the strength and timing of responses to droughts. Trait-based approaches provide an opportunity to link functional composition, ecosystem function and environmental changes. We demonstrate the power of such approaches by presenting a novel analysis of long-term responses of different tropical forest to climatic changes along a rainfall gradient. We explore how key ecosystem's biogeochemical properties have shifted over time as a consequence of multi-decadal drying. Notably, we find that drier tropical forests have increased their deciduous species abundance and generally changed more functionally than forests growing in wetter conditions, suggesting an enhanced ability to adapt ecologically to a drying environment.

The National Ecological Observatory Network (NEON) is designed to facilitate an understanding of the impact of environmental change on ecological systems. Observations of plant diversity—responsive to changes in climate, disturbance, and land use, and ecologically linked to soil, biogeochemistry, and organisms—result in NEON data products that cross a range of organizational levels. Collections include samples of plant tissue to enable investigations of genetics, plot-based observations of incidence and cover of native and non-native species, observations of plant functional traits, archived vouchers of plants, and remote sensing airborne observations. Spatially integrating many ecological observations allows a description of the relationship of plant diversity to climate, land use, organisms, and substrates. Repeating the observations over decades and across the United States will iteratively improve our understanding of those relationships and allow for the testing of system-level hypotheses as well as the development of predictions of future conditions.

© 2019 Recent work has shown that leaf traits and spectral properties change through time and/or seasonally as leaves age. Current field and hyperspectral methods used to estimate canopy leaf traits could, therefore, be significantly biased by variation in leaf age. To explore the magnitude of this effect, we used a phenological dataset comprised of leaves of different leaf age groups -developmental, mature, senescent and mixed-age- from canopy and emergent tropical trees in southern Peru. We tested the performance of partial least squares regression models developed from these different age groups when predicting traits for leaves of different ages on both a mass and area basis. Overall, area-based models outperformed mass-based models with a striking improvement in prediction observed for area-based leaf carbon (C area ) estimates. We observed trait-specific age effects in all mass-based models while area-based models displayed age effects in mixed-age leaf groups for P area and N area . Spectral coefficients and variable importance in projection (VIPs) also reflected age effects. Both mass- and area-based models for all five leaf traits displayed age/temporal sensitivity when we tested their ability to predict the traits of leaves of other age groups. Importantly, mass-based mature models displayed the worst overall performance when predicting the traits of leaves from other age groups. These results indicate that the widely adopted approach of using fully expanded mature leaves to calibrate models that estimate remotely-sensed tree canopy traits introduces error that can bias results depending on the phenological stage of canopy leaves. To achieve temporally stable models, spectroscopic studies should consider producing area-based estimates as well as calibrating models with leaves of different age groups as they present themselves through the growing season. We discuss the implications of this for surveys of canopies with synchronised and unsynchronised leaf phenology.

Branching in vascular networks and in overall organismic form is one of the most common and ancient features of multicellular plants, fungi, and animals. By combining machine-learning techniques with new theory that relates vascular form to metabolic function, we enable novel classification of diverse branching networks--mouse lung, human head and torso, angiosperm and gymnosperm plants. We find that ratios of limb radii--which dictate essential biologic functions related to resource transport and supply--are best at distinguishing branching networks. We also show how variation in vascular and branching geometry persists despite observing a convergent relationship across organisms for how metabolic rate depends on body mass., Comment: 55 pages, 8 figures, 8 tables

The U.S. Department of Energy's Watershed Function Scientific Focus Area (SFA), centered in the East River, Colorado, generates diverse datasets including hydrological, geological, geochemical, geophysical, ecological, microbiological and remote sensing data. The project has deployed extensive field infrastructure involving hundreds of sensors that measure highly diverse phenomena (e.g. stream and groundwater hydrology, water quality, soil moisture, weather) across the watershed. Data from the sensor network are telemetered and automatically ingested into a queryable database. The data are subsequently quality checked, integrated with the United States Geological Survey's stream monitoring network using a custom data integration broker, and published to a portal with interactive visualizations. The resulting data products are used in a variety of scientific modeling and analytical efforts. This paper describes the SFA's end-to-end infrastructure and services that support the generation of integrated datasets from a watershed sensor network. The development and maintenance of this infrastructure, presents a suite of challenges from practical field logistics to complex data processing, which are addressed through various solutions. In particular, the SFA adopts a holistic view for data collection, assessment and integration, which dramatically improves the products generated, and enables a co-design approach wherein data collection is informed by model results and vice-versa.

Understanding variation in key functional traits across gradients in high diversity systems and the ecology of community changes along gradients in these systems is crucial in light of conservation and climate change. We examined inter- and intraspecific variation in leaf mass per area (LMA) of sun and shade leaves along a 3330-m elevation gradient in Peru, and in sun leaves across a forest–savanna vegetation gradient in Brazil. We also compared LMA variance ratios (T-statistics metrics) to null models to explore internal (i.e., abiotic) and environmental filtering on community structure along the gradients. Community-weighted LMA increased with decreasing forest cover in Brazil, likely due to increased light availability and water stress, and increased with elevation in Peru, consistent with the leaf economic spectrum strategy expected in colder, less productive environments. A very high species turnover was observed along both environmental gradients, and consequently, the first source of variation in LMA was species turnover. Variation in LMA at the genus or family levels was greater in Peru than in Brazil. Using dominant trees to examine possible filters on community assembly, we found that in Brazil, internal filtering was strongest in the forest, while environmental filtering was observed in the dry savanna. In Peru, internal filtering was observed along 80% of the gradient, perhaps due to variation in taxa or interspecific competition. Environmental filtering was observed at cloud zone edges and in lowlands, possibly due to water and nutrient availability, respectively. These results related to variation in LMA indicate that biodiversity in species rich tropical assemblages may be structured by differential niche-based processes. In the future, specific mechanisms generating these patterns of variation in leaf functional traits across tropical environmental gradients should be explored. Fil: Neyret, Margot. Ecole Normale Supérieure; Francia Fil: Bentley, Lisa Patrick. University of Oxford; Reino Unido. Sonoma State University; Estados Unidos Fil: Oliveras, Imma. University of Oxford; Reino Unido. Wageningen University; Alemania Fil: Marimon, Beatriz S.. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Marimon-Junior, Ben Hur. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Almeida de Oliveira, Edmar. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Barbosa Passos, Fabio. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Castro Ccoscco, Rosa. Universidad San Antonio Abad de Cusco; Perú Fil: Santos, Josias dos. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Matias Reis, Simone. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Morandi, Paulo S.. Universidade Federal do Mato Grosso do Sul; Brasil Fil: Rayme Paucar, Gloria. Universidad San Antonio Abad de Cusco; Perú Fil: Robles Caceres, Arturo. Universidad San Antonio Abad de Cusco; Perú Fil: Valdez Tejeira, Yolvi. Universidad San Antonio Abad de Cusco; Perú Fil: Yllanes Choque, Yovana. Universidad San Antonio Abad de Cusco; Perú Fil: Salinas, Norma Beatriz. University of Oxford; Reino Unido. Pontificia Universidad Católica de Perú; Perú Fil: Shenkin, Alexander. University of Oxford; Reino Unido Fil: Asner, Gregory P.. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Enquist, Brian J.. Arizona State University; Estados Unidos Fil: Malhi, Yadvinder. University of Oxford; Reino Unido

Predicting long-term trends in forest growth requires accurate characterisation of how the relationship between forest productivity and climatic stress varies across climatic regimes. Using a network of over two million tree-ring observations spanning North America and a space-for-time substitution methodology, we forecast climate impacts on future forest growth. We explored differing scenarios of increased water-use efficiency (WUE) due to CO2 -fertilisation, which we simulated as increased effective precipitation. In our forecasts: (1) climate change negatively impacted forest growth rates in the interior west and positively impacted forest growth along the western, southeastern and northeastern coasts; (2) shifting climate sensitivities offset positive effects of warming on high-latitude forests, leaving no evidence for continued 'boreal greening'; and (3) it took a 72% WUE enhancement to compensate for continentally averaged growth declines under RCP 8.5. Our results highlight the importance of locally adapted forest management strategies to handle regional differences in growth responses to climate change.

Average responses of forest foliar traits to elevation are well understood, but far less is known about trait distributional responses to elevation at multiple ecological scales. This limits our understanding of the ecological scales at which trait variation occurs in response to environmental drivers and change. We analyzed and compared multiple canopy foliar trait distributions using field sampling and airborne imaging spectroscopy along an Andes-to-Amazon elevation gradient. Field-estimated traits were generated from three community-weighting methods, and remotely sensed estimates of traits were made at three scales defined by sampling grain size and ecological extent. Field and remote sensing approaches revealed increases in average leaf mass per unit area (LMA), water, nonstructural carbohydrates (NSCs) and polyphenols with increasing elevation. Foliar nutrients and photosynthetic pigments displayed little to no elevation trend. Sample weighting approaches had little impact on field-estimated trait responses to elevation. Plot representativeness of trait distributions at landscape scales decreased with increasing elevation. Remote sensing indicated elevation-dependent increases in trait variance and distributional skew. Multiscale invariance of LMA, leaf water and NSC mark these traits as candidates for tracking forest responses to changing climate. Trait-based ecological studies can be greatly enhanced with multiscale studies made possible by imaging spectroscopy. Fil: Asner, Gregory P.. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Martin, Roberta E.. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Anderson, Christopher Brian. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Kryston, Katherine. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Vaughn, Nicholas. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Knapp, David E.. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Bentley, Lisa Patrick. University of Oxford; Reino Unido Fil: Shenkin, Alexander. University of Oxford; Reino Unido Fil: Salinas, Norma. University of Oxford; Reino Unido. Pontificia Universidad Católica de Perú; Perú Fil: Sinca, Felipe. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Tupayachi, Raul. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Quispe Huaypar, Katherine. Universidad Nacional de San Antonio Abad del Cusco; Perú Fil: Montoya Pillco, Milenka. Universidad Nacional de San Antonio Abad del Cusco; Perú Fil: Ccori Álvarez, Flor Delis. Universidad Nacional de San Antonio Abad del Cusco; Perú Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Enquist, Brian J.. Arizona State University; Estados Unidos Fil: Malhi, Yadvinder. University of Oxford; Reino Unido

Plant leaf waxes have been found to record the hydrogen isotopic composition of precipitation and are thus used to reconstruct past climate. To assess how faithfully they record hydrological signals, we characterize leaf wax hydrogen isotopic compositions in forest canopy trees across a highly biodiverse, 3 km elevation range on the eastern flank of the Andes. We sampled the dominant tree species and assessed their relative abundance in the tree community. For each tree we collected xylem and leaf samples for analysis of plant water and plant leaf wax hydrogen isotopic compositions. In total, 176 individuals were sampled across 32 species and 5 forest plots that span the gradient. We find both xylem water and leaf wax δD values of individuals correlate (R2 = 0.8 and R2 = 0.3 respectively) with the isotopic composition of precipitation (with an elevation gradient of −21‰ km−1). Minimal leaf water enrichment means that leaf waxes are straightforward recorders of the isotopic composition of precipitation in wet climates. For these tropical forests we find the average fractionation between source water and leaf wax for C29 n-alkanes, −129 ± 2‰ (s.e.m., n = 136), to be indistinguishable from that of temperate moist forests. For C28 n-alkanoic acids the average fractionation is −121 ± 3‰ (s.e.m., n = 102). Sampling guided by community assembly within forest plots shows that integrated plant leaf wax hydrogen isotopic compositions faithfully record the gradient of isotopes in precipitation with elevation (R2 = 0.97 for n-alkanes and 0.60 for n-alkanoic acids). This calibration study supports the use of leaf waxes as recorders of the isotopic composition of precipitation in lowland tropical rainforest, tropical montane cloud forests and their sedimentary archives.

Positive and negative associations between species are a key outcome of community assembly from regional species pools. These associations are difficult to detect and can be caused by a range of processes such as species interactions, local environmental constraints and dispersal. We integrate new ideas around species distribution modeling, covariance matrix estimation, and network analysis to provide an approach to inferring non-random species associations from local-and regional-scale occurrence data. Specifically, we provide a novel framework for identifying species associations that overcomes three challenges: 1) correcting for indirect effects from other species, 2) avoiding spurious associations driven by regional-scale distributions, and 3) describing these associations in a multi-species context. We highlight a range of research questions and analyses that this framework is able to address. We show that the approach is statistically robust using simulated data. In addition, we present an empirical analysis of >1000 North American tree communities that gives evidence for weak positive associations among small groups of species. Finally, we discuss several possible extensions for identifying drivers of associations, predicting community assembly, and better linking biogeography and community ecology.

Plant functional group dominance has been linked to climate, topography and anthropogenic factors. Here, we assess existing theory linking functional group dominance patterns to their drivers by quantifying the spatial distribution of plant functional groups at a 100-km grid scale. We use a standardized plant species occurrence dataset of unprecedented size covering the entire New World. Functional group distributions were estimated from 3 648 533 standardized occurrence records for a total of 83 854 vascular plant species, extracted from the Botanical Information and Ecology Network (BIEN) database. Seven plant functional groups were considered, describing major differences in structure and function: epiphytes; climbers; ferns; herbs; shrubs; coniferous trees; and angiosperm trees. Two measures of dominance (relative number of occurrences and relative species richness) were analysed against a range of hypothesized predictors. The functional groups showed distinct geographical patterns of dominance across the New World. Temperature seasonality and annual precipitation were most frequently selected, supporting existing hypotheses for the geographical dominance of each functional group. Human influence and topography were secondarily important. Our results support the prediction that future climate change and anthropogenic pressures could shift geographical patterns in dominance of plant functional groups, with probable consequences for ecosystem functioning Plant functional group dominance has been linked to climate, topography and anthropogenic factors. Here, we assess existing theory linking functional group dominance patterns to their drivers by quantifying the spatial distribution of plant functional groups at a 100-km grid scale. We use a standardized plant species occurrence dataset of unprecedented size covering the entire New World. Functional group distributions were estimated from 3 648 533 standardized occurrence records for a total of 83 854 vascular plant species, extracted from the Botanical Information and Ecology Network (BIEN) database. Seven plant functional groups were considered, describing major differences in structure and function: epiphytes; climbers; ferns; herbs; shrubs; coniferous trees; and angiosperm trees. Two measures of dominance (relative number of occurrences and relative species richness) were analysed against a range of hypothesized predictors. The functional groups showed distinct geographical patterns of dominance across the New World. Temperature seasonality and annual precipitation were most frequently selected, supporting existing hypotheses for the geographical dominance of each functional group. Human influence and topography were secondarily important. Our results support the prediction that future climate change and anthropogenic pressures could shift geographical patterns in dominance of plant functional groups, with probable consequences for ecosystem functioning.

Author(s): Blonder, B; Baldwin, BG; Enquist, BJ; Robichaux, RH | Abstract: The Hawaiian silversword alliance is a spectacular example of plant adaptive radiation. The lineage includes 33 species in three endemic genera (Argyroxiphium, Dubautia and Wilkesia) that occupy almost all major habitats of the Hawaiian archipelago. Here, we quantitatively explore functional diversification in the lineage by linking measurements of multiple leaf functional traits with climate niche and phylogenetic data. We show that leaf functional trait variation (i) spans much of the global angiosperm range, (ii) is best explained by a white-noise evolutionary model and (iii) is integrated in ways consistent with both the global leaf economics spectrum and the predictions of leaf venation network theory. Our results highlight the importance of functional diversification and integration in rapidly evolving plant lineages. They also provide compelling additional support for the view that the Hawaiian silversword alliance is one of the world's premier examples of adaptive radiation in plants. The Hawaiian silversword alliance includes 33 species in three endemic genera (Argyroxiphium, Dubautia, and Wilkesia) that occupy almost all major habitats of the Hawaiian archipelago (top row). We show that leaf functional trait variation in the lineage spans much of the global angiosperm range, is best explained by a white-noise evolutionary model, and is integrated in ways consistent with both the global leaf economics spectrum and the predictions of leaf venation network theory (bottom row). The results provide compelling support for the view that the silversword alliance is one of the world's premier examples of adaptive radiation in plants. Journal of Ecology