193 results on '"I. Colin Prentice"'
Search Results
2. Global variation in the ratio of sapwood to leaf area explained by optimality principles
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Huiying Xu, Han Wang, I. Colin Prentice, Sandy P. Harrison, Lucy Rowland, Maurizio Mencuccini, Pablo Sanchez-Martinez, Pengcheng He, Ian J. Wright, Stephen Sitch, and Qing Ye
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The sapwood area supporting a given leaf area (vH) reflects a coordinated coupling between carbon uptake, water transport and loss at a whole plant level. Worldwide variation in vH reflects diverse plants strategies adapt to prevailing environments, and impact the evolution of global carbon and water cycles. Why such a variation has not been convincingly explained yet, thus hinder its representation in Earth System Models. Here we hypothese that optimal vH tends to mediate between sapwood conductance and climates so that leaf water loss matches both sapwood hydraulics and leaf photosynthesis. By compiling and testing against two extensive datasets, we show that our hypothesis explains nearly 60% of vH variation responding to light, vapor pressure deficit, temperature, and sapwood conductance in a quantitively predictable manner. Sapwood conductance or warming-enhanced hydraulic efficiency reduces the demand on sapwood area for a given total leaf area and, whereas brightening and air dryness enhance photosynthetic capacities consequently increasing the demand. This knowledge can enrich Earth System Models where carbon allocation and water hydraulics play key roles in predicting future climate-carbon feedback.
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- 2023
3. Ecosystem C and N cycle interactions – diverse model representations and divergent model predictions versus collective empirical constraints
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Benjamin D. Stocker, Hugo de Boer, Ning Dong, Sandy P. Harrison, Evan A. Perkowski, I. Colin Prentice, Karin T. Rebel, Pascal Schneider, Nicholas G. Smith, Kevin Van Sundert, Han Wang, and Huiying Xu
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Representations of interactions between the C and N cycles in terrestrial ecosystems are now implemented in a majority of state-of-the-art Dynamic Global Vegetation Models (C-N models). Standard models for simulating the response of individual processes to changes in N availability have not yet emerged and widely used models have not been tested against the full diversity of empirical data. Large remaining model structural uncertainty has important implications for projections and hindcasts of the land C uptake.Here, we summarise the current state of global land C balance simulations by comparing C-N models to C-only models; summarise data from field surveys and experiments to elucidate the role of soil N in controlling photosynthesis and its acclimation, stoichiometry, allocation, and growth; and demonstrate how optimality principles can guide the representation of acclimation and allocation for simulating ecosystem responses to experimental treatments of CO2 and soil N – consistent with observations. Promising model results are achieved by assuming that the atmospheric environment, including CO2, is the principal driver for photosynthetic capacities and leaf N following optimality theory of photosynthetic acclimation (Prentice et al., 2014). In turn, the functional balance hypothesis (Bloom et al., 1985) yields accurate predictions for how soil N availability and CO2 influence allocation and growth in different tissues.Our results show how confronting new theoretical approaches to simulating ecosystem C-N interactions against the collective constraints from diverse types of observations can guide model development and potentially reduce the large uncertainty in global carbon cycle projections.ReferencesBloom, Arnold J, F Stuart Chapin, and Harold A Mooney. “Resource Limitation in Plants--An Economic Analogy” Annual Review of Ecology and Systematics, 16, no. 1 (1985): 363–92. https://doi.org/10.1146/annurev.es.16.110185.002051.Prentice, I. Colin, Ning Dong, Sean M. Gleason, Vincent Maire, and Ian J. Wright. “Balancing the Costs of Carbon Gain and Water Transport: Testing a New Theoretical Framework for Plant Functional Ecology.” Ecology Letters 17, 1 (2014): 82–91. https://doi.org/10.1111/ele.12211.
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- 2023
4. Reconstructing burnt area during the Holocene: an Iberian case study
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I. Colin Prentice, José Antonio López Sáez, Luke Sweeney, Gonzalo Jiménez-Moreno, Mengmeng Liu, Sebastián Pérez-Díaz, Sandy P. Harrison, Reyes Luelmo-Lautenschlaeger, Heike Schneider, Graciela Gil-Romera, Yicheng Shen, Dana Hoefer, Universidad de Cantabria, European Commission, Ministerio de Economía y Competitividad (España), López Sáez, José Antonio, Luelmo Lautenschlaeger, Reyes, Pérez Díaz, Sebastián, Commission of the European Communities, Leverhulme Trust, and The Leverhulme Trust
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geography ,Global and Planetary Change ,geography.geographical_feature_category ,Fire regime ,Stratigraphy ,Climate change ,Paleontology ,Vegetation ,medicine.disease_cause ,Abundance (ecology) ,visual_art ,Pollen ,visual_art.visual_art_medium ,medicine ,Physical geography ,Charcoal ,0406 Physical Geography and Environmental Geoscience ,Bog ,Holocene ,Geology - Abstract
This research has been supported by the European Research Council (GC2.0 (grant no. 694481)), the European Research Council (REALM (grant no. 787203)), Imperial College through the Lee Family Scholarship, the Leverhulme Centre for Wildfires, Environment and Society (grant no. RC-2018-023), and the REDISCO (grant no. HAR2017-88035-P) project., Charcoal accumulated in lake, bog or other anoxic sediments through time has been used to document the geographical patterns in changes in fire regimes. Such reconstructions are useful to explore the impact of climate and vegetation changes on fire during periods when human influence was less prevalent than today. However, charcoal records only provide semi-quantitative estimates of change in biomass burning. Here we derive quantitative estimates of burnt area from vegetation data in two stages. First, we relate the modern charcoal abundance to burnt area using a conversion factor derived from a generalised linear model of burnt area probability based on eight environmental predictors. Then, we establish the relationship between fossil pollen assemblages and burnt area using tolerance-weighted weighted averaging partial least-squares regression with a sampling frequency correction (fxTWA-PLS). We test this approach using the Iberian Peninsula as a case study because it is a fire-prone region with abundant pollen and charcoal records covering the Holocene. We derive the vegetation-burnt area relationship using the 31 records that have both modern and fossil charcoal and pollen data and then reconstruct palaeoburnt area for the 113 records with Holocene pollen records. The pollen data predict charcoal-derived burnt area relatively well (R-2 = 0.44), and the changes in reconstructed burnt area are synchronous with known climate changes through the Holocene. This new method opens up the possibility of reconstructing changes in fire regimes quantitatively from pollen records, after regional calibration of the vegetation-burnt area relationship, in regions where pollen records are more abundant than charcoal records., European Research Council (ERC) European Commission 694481 787203, Imperial College through the Lee Family Scholarship, Leverhulme Centre for Wildfires, Environment and Society RC-2018-023 REDISCO HAR2017-88035-P
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- 2022
5. Towards a general monitoring system for terrestrial primary production: a test spanning the European drought of 2018
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Keith J. Bloomfield, Roel van Hoolst, Manuela Balzarolo, Ivan A. Janssens, Sara Vicca, Darren Ghent, and I. Colin Prentice
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Chemistry ,Economics ,Physics ,General Earth and Planetary Sciences ,Biology ,Engineering sciences. Technology - Abstract
(1) Land surface models require inputs of temperature and moisture variables to generate predictions of gross primary production (GPP). Differences between leaf and air temperature vary temporally and spatially and may be especially pronounced under conditions of low soil moisture availability. The Sentinel-3 satellite mission offers estimates of the land surface temperature (LST), which for vegetated pixels can be adopted as the canopy temperature. Could remotely sensed estimates of LST offer a parsimonious input to models by combining information on leaf temperature and hydration? (2) Using a light use efficiency model that requires only a handful of input variables, we generated GPP simulations for comparison with eddy-covariance inferred estimates available from flux sites within the Integrated Carbon Observation System. Remotely sensed LST and greenness data were input from Sentinel-3. Gridded air temperature data were obtained from the European Centre for Medium-Range Weather Forecasts. We chose the years 2018–2019 to exploit the natural experiment of a pronounced European drought. (3) Simulated GPP showed good agreement with flux-derived estimates. During dry conditions, simulations forced with LST performed better than those with air temperature for shrubland, grassland and savanna sites. (4) This study advances the prospect for a global GPP monitoring system that will rely primarily on remotely sensed inputs.
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- 2023
6. The global spectrum of plant form and function: enhanced species-level trait dataset
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Sandra Díaz, Jens Kattge, Johannes H. C. Cornelissen, Ian J. Wright, Sandra Lavorel, Stéphane Dray, Björn Reu, Michael Kleyer, Christian Wirth, I. Colin Prentice, Eric Garnier, Gerhard Bönisch, Mark Westoby, Hendrik Poorter, Peter B. Reich, Angela T. Moles, John Dickie, Amy E. Zanne, Jérôme Chave, S. Joseph Wright, Serge N. Sheremetiev, Hervé Jactel, Christopher Baraloto, Bruno E. L. Cerabolini, Simon Pierce, Bill Shipley, Fernando Casanoves, Julia S. Joswig, Angela Günther, Valeria Falczuk, Nadja Rüger, Miguel D. Mahecha, Lucas D. Gorné, Bernard Amiaud, Owen K. Atkin, Michael Bahn, Dennis Baldocchi, Michael Beckmann, Benjamin Blonder, William Bond, Ben Bond-Lamberty, Kerry Brown, Sabina Burrascano, Chaeho Byun, Giandiego Campetella, Jeannine Cavender-Bares, F. Stuart Chapin, Brendan Choat, David Anthony Coomes, William K. Cornwell, Joseph Craine, Dylan Craven, Matteo Dainese, Alessandro Carioca de Araujo, Franciska T. de Vries, Tomas Ferreira Domingues, Brian J. Enquist, Jaime Fagúndez, Jingyun Fang, Fernando Fernández-Méndez, Maria T. Fernandez-Piedade, Henry Ford, Estelle Forey, Gregoire T. Freschet, Sophie Gachet, Rachael Gallagher, Walton Green, Greg R. Guerin, Alvaro G. Gutiérrez, Sandy P. Harrison, Wesley Neil Hattingh, Tianhua He, Thomas Hickler, Steven I. Higgins, Pedro Higuchi, Jugo Ilic, Robert B. Jackson, Adel Jalili, Steven Jansen, Fumito Koike, Christian König, Nathan Kraft, Koen Kramer, Holger Kreft, Ingolf Kühn, Hiroko Kurokawa, Eric G. Lamb, Daniel C. Laughlin, Michelle Leishman, Simon Lewis, Frédérique Louault, Ana C. M. Malhado, Peter Manning, Patrick Meir, Maurizio Mencuccini, Julie Messier, Regis Miller, Vanessa Minden, Jane Molofsky, Rebecca Montgomery, Gabriel Montserrat-Martí, Marco Moretti, Sandra Müller, Ülo Niinemets, Romà Ogaya, Kinga Öllerer, Vladimir Onipchenko, Yusuke Onoda, Wim A. Ozinga, Juli G. Pausas, Begoña Peco, Josep Penuelas, Valério D. Pillar, Clara Pladevall, Christine Römermann, Lawren Sack, Norma Salinas, Brody Sandel, Jordi Sardans, Brandon Schamp, Michael Scherer-Lorenzen, Ernst-Detlef Schulze, Fritz Schweingruber, Satomi Shiodera, Ênio Sosinski, Nadejda Soudzilovskaia, Marko J. Spasojevic, Emily Swaine, Nathan Swenson, Susanne Tautenhahn, Ken Thompson, Alexia Totte, Rocío Urrutia-Jalabert, Fernando Valladares, Peter van Bodegom, François Vasseur, Kris Verheyen, Denis Vile, Cyrille Violle, Betsy von Holle, Patrick Weigelt, Evan Weiher, Michael C. Wiemann, Mathew Williams, Justin Wright, Gerhard Zotz, Biology, General Botany and Nature Management, 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], Universidad Nacional de Córdoba [Argentina], Ecologie quantitative et évolutive des communautés, Département écologie évolutive [LBBE], Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-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)-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, 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)-Université de Montpellier (UM), Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, 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), Etude et Compréhension de la biodiversité (ECODIV), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), TRY initiative on plant traits (https://www.try-db.org).TRY is an initiative of the Max Planck Institute for Biogeochemistry, bioDISCOVERY/Future Earth (ICSU), the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig and Nucleo DiverSus (CONICET-Universidad Nacional de Cordoba, Argentina)., The Global Spectrum of Plant Form and Function study has been supported by the European BACI project (Towards a Biosphere Atmosphere change Index, EU grant ID 640176), FONCyT, CONICET, Universidad Nacional de Cordoba, the Inter-American Institute for Global Change Research, and The Newton Fund (NERC UK -CONICET ARG), Díaz, Sandra [0000-0003-0012-4612], Kattge, Jens [0000-0002-1022-8469], Wright, Ian J [0000-0001-8338-9143], Lavorel, Sandra [0000-0002-7300-2811], Dray, Stéphane [0000-0003-0153-1105], Wirth, Christian [0000-0003-2604-8056], Garnier, Eric [0000-0002-9392-5154], Westoby, Mark [0000-0001-7690-4530], Reich, Peter B [0000-0003-4424-662X], Moles, Angela T [0000-0003-2041-7762], Zanne, Amy E [0000-0001-6379-9452], Chave, Jérôme [0000-0002-7766-1347], Wright, S Joseph [0000-0003-4260-5676], Sheremetiev, Serge N [0000-0002-0318-6766], Baraloto, Christopher [0000-0001-7322-8581], Cerabolini, Bruno EL [0000-0002-3793-0733], Casanoves, Fernando [0000-0001-8765-9382], Joswig, Julia S [0000-0002-7786-1728], Mahecha, Miguel D [0000-0003-3031-613X], Atkin, Owen K [0000-0003-1041-5202], Bahn, Michael [0000-0001-7482-9776], Bond, William [0000-0002-3441-2084], Bond-Lamberty, Ben [0000-0001-9525-4633], Byun, Chaeho [0000-0003-3209-3275], Campetella, Giandiego [0000-0001-6126-522X], Cavender-Bares, Jeannine [0000-0003-3375-9630], Chapin, F Stuart [0000-0002-2558-9910], Choat, Brendan [0000-0002-9105-640X], Coomes, David Anthony [0000-0002-8261-2582], Cornwell, William K [0000-0003-4080-4073], Craine, Joseph [0000-0001-6561-3244], Craven, Dylan [0000-0003-3940-833X], Dainese, Matteo [0000-0001-7052-5572], Domingues, Tomas Ferreira [0000-0003-2857-9838], Enquist, Brian J [0000-0002-6124-7096], Gallagher, Rachael [0000-0002-4680-8115], Harrison, Sandy P [0000-0001-5687-1903], Hattingh, Wesley Neil [0000-0002-3626-5137], He, Tianhua [0000-0002-0924-3637], Higuchi, Pedro [0000-0002-3855-555X], Jackson, Robert B [0000-0001-8846-7147], Jansen, Steven [0000-0002-4476-5334], Kreft, Holger [0000-0003-4471-8236], Kühn, Ingolf [0000-0003-1691-8249], Kurokawa, Hiroko [0000-0001-8778-8045], Laughlin, Daniel C [0000-0002-9651-5732], Manning, Peter [0000-0002-7940-2023], Mencuccini, Maurizio [0000-0003-0840-1477], Müller, Sandra [0000-0003-4289-755X], Pausas, Juli G [0000-0003-3533-5786], Penuelas, Josep [0000-0002-7215-0150], Pillar, Valério D [0000-0001-6408-2891], Sack, Lawren [0000-0002-7009-7202], Salinas, Norma [0000-0001-9941-2109], Sardans, Jordi [0000-0003-2478-0219], Scherer-Lorenzen, Michael [0000-0001-9566-590X], Sosinski, Ênio [0000-0001-6310-9474], Spasojevic, Marko J [0000-0003-1808-0048], Weigelt, Patrick [0000-0002-2485-3708], Williams, Mathew [0000-0001-6117-5208], Zotz, Gerhard [0000-0002-6823-2268], Apollo - University of Cambridge Repository, 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), Diaz, S, Kattge, J, Cornelissen, JHC, Wright, IJ, Lavorel, S, Dray, S, Reu, B, Kleyer, M, Wirth, C, Prentice, IC, Garnier, E, Bonisch, G, Westoby, M, Poorter, H, Reich, PB, Moles, AT, Dickie, J, Zanne, AE, Chave, J, Wright, SJ, Sheremetiev, SN, Jactel, H, Baraloto, C, Cerabolini, BEL, Pierce, S, Shipley, B, Casanoves, F, Joswig, JS, Gunther, A, Falczuk, V, Ruger, N, Mahecha, MD, Gorne, LD, Amiaud, B, Atkin, OK, Bahn, M, Baldocchi, D, Beckmann, M, Blonder, B, Bond, W, Bond-Lamberty, B, Brown, K, Burrascano, S, Byun, C, Campetella, G, Cavender-Bares, J, Chapin, FS, Choat, B, Coomes, DA, Cornwell, WK, Craine, J, Craven, D, Dainese, M, de Araujo, AC, de Vries, FT, Domingues, TF, Enquist, BJ, Fagundez, J, Fang, J, Fernandez-Mendez, F, Fernandez-Piedade, MT, Ford, H, Forey, E, Freschet, GT, Gachet, S, Gallagher, R, Green, W, Guerin, GR, Gutierrez, AG, Harrison, SP, Hattingh, WN, He, T, Hickler, T, Higgins, SI, Higuchi, P, Ilic, J, Jackson, RB, Jalili, A, Jansen, S, Koike, F, Konig, C, Kraft, N, Kramer, K, Kreft, H, Kuhn, I, Kurokawa, H, Lamb, EG, Laughlin, DC, Leishman, M, Lewis, S, Louault, F, Malhado, ACM, Manning, P, Meir, P, Mencuccini, M, Messier, J, Miller, R, Minden, V, Molofsky, J, Montgomery, R, Montserrat-Marti, G, Moretti, M., Muller, S, Niinemets, U, Ogaya, R, Ollerer, K, Onipchenko, V, Onoda, Y, Ozinga, WA, Pausas, JG, Peco, B, Penuelas, J, Pillar, VD, Pladevall, C, Romermann, C, Sack, L, Salinas, N, Sandel, B, Sardans, J, Schamp, B, Scherer-Lorenzen, M, Schulze, ED, Schweingruber, F, Shiodera, S, Sosinski, E, SOUDZILOVSKAIA, Nadia, Spasojevic, MJ, Swaine, E, Swenson, N, Tautenhahn, S, Thompson, K, Totte, A, Urrutia-Jalabert, R, Valladares, F, van Bodegom, P, Vasseur, F, Verheyen, K, Vile, D, Violle, C, von Holle, B, Weigelt, P, Weiher, E, Wiemann, MC, Williams, M, Wright, J, Zotz, G, and Systems Ecology
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Statistics and Probability ,Data Descriptor ,[SDV]Life Sciences [q-bio] ,Bos- en Landschapsecologie ,Library and Information Sciences ,Education ,SIZE-REDUCTION ,QUERCUS-ILEX ,WIDE-RANGE ,Life Science ,Forest and Landscape Ecology ,Macroecology ,Vegetatie ,Vegetation ,ENVIRONMENT RELATIONSHIPS ,3103 Ecology ,Biology and Life Sciences ,Biodiversity ,3108 Plant Biology ,Computer Science Applications ,Biogeography ,631/158/852 ,FOLIAR NITROGEN ISOTOPES ,631/158/851 ,[SDE]Environmental Sciences ,Vegetatie, Bos- en Landschapsecologie ,Vegetation, Forest and Landscape Ecology ,LEAF ECONOMICS SPECTRUM ,Statistics, Probability and Uncertainty ,data-descriptor ,ELEVATED CO2 ,WOODY-PLANTS ,PHOTOSYNTHETIC CAPACITY ,631/158/670 ,RELATIVE GROWTH-RATE ,Information Systems ,31 Biological Sciences - Abstract
[Abstract] Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date. The study has been supported by the TRY initiative on plant traits (https://www.try-db.org). TRY is an initiative of the Max Planck Institute for Biogeochemistry, bioDISCOVERY/Future Earth (ICSU), the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig and Núcleo DiverSus (CONICET- Universidad Nacional de Córdoba, Argentina). The Global Spectrum of Plant Form and Function study has been supported by the European BACI project (Towards a Biosphere Atmosphere change Index, EU grant ID 640176), and grants to SD by FONCyT, CONICET, Universidad Nacional de Córdoba, the Inter-American Institute for Global Change Research, and The Newton Fund (NERC UK – CONICET ARG). VO thanks RSF (#19-14-00038p). Open Access funding enabled and organized by Projekt DEAL
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- 2022
7. Leaf economics fundamentals explained by optimality principles
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Han Wang, I. Colin Prentice, Ian J. Wright, David I. Warton, Shengchao Qiao, Xiangtao Xu, Jian Zhou, Kihachiro Kikuzawa, and Nils Chr. Stenseth
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Multidisciplinary - Abstract
The life span of leaves increases with their mass per unit area (LMA). It is unclear why. Here, we show that this empirical generalization (the foundation of the worldwide leaf economics spectrum) is a consequence of natural selection, maximizing average net carbon gain over the leaf life cycle. Analyzing two large leaf trait datasets, we show that evergreen and deciduous species with diverse construction costs (assumed proportional to LMA) are selected by light, temperature, and growing-season length in different, but predictable, ways. We quantitatively explain the observed divergent latitudinal trends in evergreen and deciduous LMA and show how local distributions of LMA arise by selection under different environmental conditions acting on the species pool. These results illustrate how optimality principles can underpin a new theory for plant geography and terrestrial carbon dynamics.
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- 2022
8. Community Abundance of Resprouting in Woody Plants Reflects Fire Return Time, Intensity, and Type
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Yicheng Shen, Wenjia Cai, I. Colin Prentice, and Sandy P. Harrison
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Forestry ,post-fire resprouting ,fire regime ,fire resilience ,fire ecology ,fire-related plant traits - Abstract
Plants in fire-prone ecosystems have evolved a variety of mechanisms to resist or adapt to fire. Post-fire resprouting is a key adaptation that promotes rapid ecosystem recovery and hence has a major impact on the terrestrial carbon cycle. However, our understanding of how the incidence of resprouting varies in different fire regimes is largely qualitative. The increasing availability of plant trait data and plot-based species cover data provides an opportunity to quantify the relationships between fire-related traits and fire properties. We investigated the quantitative relationship between fire frequency (expressed as the fire return time) and the proportion of resprouters in woody plants using plot data on species cover from Australia and Europe. We also examined the relationship between the proportion of resprouters and gross primary production (GPP) and grass cover, where GPP was assumed to reflect fuel loads and hence fire intensity, while grass cover was considered to be an indicator of the likelihood of ground fire and the speed of fire spread, using generalised linear modelling. The proportion of resprouting species decreased significantly as the fire return time increased. When the fire return time was considered along with other aspects of the fire regime, the proportion of resprouters had significant negative relationships with the fire return time and grass cover and a significant positive relationship with GPP. These findings demonstrate that plants with the ability to resprout occur more often where fire regimes are characterised by high-frequency and high-intensity crown fires. Establishing quantitative relationships between the incidence of resprouting and the fire return time and fire type provides a basis for modelling resprouting as a consequence of the characteristics of the fire regime, which in turn makes it possible to model the consequences of changing fire regimes on ecosystem properties.
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- 2023
9. Three global products of leaf photosynthetic capacity derived from satellite observations
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Chen, Jing M., Wang, Rong, Yihong Liu, Liming He, Croft, Holly, Xiangzhong Luo, Wang, Han, Smith, Nicholas G., Keenan, Trevor F., I. Colin Prentice, Yongguang Zhang, Weimin Ju, and Dong, Ning
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leaf photosynthetic capacity ,remote sensing ,solar induced fluorescence - Abstract
There are three global 0.5 degree Vcmax datasets at growth temperature included: 1) Vcmax from GOME-2 SIF: GOME2_Vcmax_Tg_05deg.tif 2) Vcmax from TROPOMI SIF + LCC: TROPOMI_Vmax_Tg_mean.mat 3) Vcmax from global leaf chlorophyll content (LCC) map (Croft et al., 2020, RSE): LCC_Vcmax_Tg_mean.mat The geographic reference isthe same for all three datasets, conforming to that in the geotiff file. For any questions on the dataset, please contact: Dr. Jing M. Chen jing.chen@utoronto.ca
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- 2022
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10. Optimality-based modelling of wheat sowing dates globally
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Shengchao Qiao, Sandy P. Harrison, I. Colin Prentice, and Han Wang
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Wheat sowing dates are currently used as an input for crop models that simulated wheat production. However, the optimal time for planting wheat will be affected by climate changes and human adaptations to these changes. In this paper, we present an optimality-based modelling approach, with additional constraints from low temperature and precipitation intensity, to estimate wheat sowing dates globally. This approach assumes that wheat could be sown at any time when the climate conditions are suitable, but the optimal sowing date that would be adopted by farmers would be that which maximises overall grain yields. We therefore run the model starting on every possible sowing date as determined by the climate constraints and then select the date which gives the highest yield in each location. We compare the modelled optimal sowing dates with an updated version of observed sowing dates created by merging census-based datasets and local agronomic information. Cold season temperatures are the major determinant of sowing dates in the extra-tropics, whereas the seasonal cycle of monsoon rainfall plays an important role in determining sowing dates in the tropics. The model captures the timing of reported sowing dates, with difference between estimated and observed sowing dates of less than one month (< 30 days) over much of the world; maximum errors in tropical regions with large altitudinal gradients, such as Ethiopia, Bolivia and Peru, are up to two months. Discrepancies between the predictions and observations are larger in tropical regions than temperate and cold regions. Our approach for estimating optimal wheat sowing dates provides a way to examine human management decisions could mitigate the impacts of climate change on crop systems.
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- 2022
11. Nighttime temperature and optimal photosynthetic capacity over the past fortnight jointly control the acclimation of leaf respiration
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Yanghang Ren, Han Wang, Sandy P. Harrison, I. Colin Prentice, Peter B. Reich, Nicholas G. Smith, and Artur Stefanski
- Abstract
Leaf dark respiration (Rd) accounts for approximately 50% of plant respiration. The acclimation of plant respiration to temperature weakens the positive feedback to global warming. Most existing land surface models (LSMs) adopt an empirical leaf respiration scheme with a constant Rd25 (leaf dark respiration rate at 25°C) for each vegetation type, since there is no acceptable theory of Rd acclimation and how it varies temporally and spatially. Here we propose that Rd25 adjusts to prior nighttime temperature (Tnight) to maintain the ratio of Rd to photosynthesis capacity (Vcmax) approximately constant. To test this hypothesis and explore the time scale of acclimation, we predict Rd25 over different time windows and evaluate these predictions using data from 14 sites from two datasets (Boreal Forest Warming at an Ecotone in Danger (B4WarmED) experiment and Leaf Carbon Exchange dataset (LCE)), one of which provides measurements through time and the other across spatial gradients. Predictions that account for the combined effects of Vcmax and Tnight have better predictive power for all species (mean R2=0.4) than considering the effect of one factor alone. Predictions of acclimation on different timescales show that Vcmax and Tnight averaged over the past fortnight explain the most variation in observed Rd25. These results could provide an alternative solution to the leaf respiration schemes used in LSMs.
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- 2022
12. CO
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Chi, Chen, William J, Riley, I Colin, Prentice, and Trevor F, Keenan
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SignificanceThe magnitude of the CO
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- 2022
13. Atmospheric dryness reduces photosynthesis along a large range of soil water deficits
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Zheng Fu, Philippe Ciais, I. Colin Prentice, Pierre Gentine, David Makowski, Ana Bastos, Xiangzhong Luo, Julia K. Green, Paul C. Stoy, Hui Yang, Tomohiro Hajima, AXA Research Fund, Commission of the European Communities, 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), ICOS-ATC (ICOS-ATC), 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), Imperial College London, Macquarie University, Tsinghua University [Beijing] (THU), Columbia University [New York], Mathématiques et Informatique Appliquées (MIA Paris-Saclay), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, National University of Singapore (NUS), University of Wisconsin-Madison, and Japan Agency for Marine-Earth Science and Technology (JAMSTEC)
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[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,Multidisciplinary ,Vapor Pressure ,Air ,Ecological Parameter Monitoring ,Datasets as Topic ,Water ,General Physics and Astronomy ,General Chemistry ,General Biochemistry, Genetics and Molecular Biology ,Droughts ,Europe ,Plant Leaves ,Soil ,Neural Networks, Computer ,Photosynthesis ,[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment - Abstract
Both low soil water content (SWC) and high atmospheric dryness (vapor pressure deficit, VPD) can negatively affect terrestrial gross primary production (GPP). The sensitivity of GPP to soil versus atmospheric dryness is difficult to disentangle, however, because of their covariation. Using global eddy-covariance observations, here we show that a decrease in SWC is not universally associated with GPP reduction. GPP increases in response to decreasing SWC when SWC is high and decreases only when SWC is below a threshold. By contrast, the sensitivity of GPP to an increase of VPD is always negative across the full SWC range. We further find canopy conductance decreases with increasing VPD (irrespective of SWC), and with decreasing SWC on drier soils. Maximum photosynthetic assimilation rate has negative sensitivity to VPD, and a positive sensitivity to decreasing SWC when SWC is high. Earth System Models underestimate the negative effect of VPD and the positive effect of SWC on GPP such that they should underestimate the GPP reduction due to increasing VPD in future climates.
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- 2022
14. Ecosystem Photosynthesis in Land‐Surface Models: A First‐Principles Approach Incorporating Acclimation
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Giulia Mengoli, Anna Agustí‐Panareda, Souhail Boussetta, Sandy P. Harrison, Carlo Trotta, I. Colin Prentice, and Commission of the European Communities
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Global and Planetary Change ,Physical geography ,land surface model ,sub‐daily simulations ,GC1-1581 ,acclimation ,Oceanography ,gross primary production ,GB3-5030 ,PFT‐independent ,General Earth and Planetary Sciences ,Environmental Chemistry ,0401 Atmospheric Sciences ,optimality‐based model - Abstract
Vegetation regulates land‐atmosphere, water, and energy exchanges and is an essential component of land‐surface models (LSMs). However, LSMs have been handicapped by assumptions that equate acclimated photosynthetic responses to the environment with the fast responses observable in the laboratory. The effects of acclimation can be taken into account by including PFT‐specific values of photosynthetic parameters, but at the cost of increasing parameter requirements. Here, we develop an alternative approach for including acclimation in LSMs by adopting the P model, an existing light‐use efficiency model for gross primary production (GPP) that implicitly predicts the acclimation of photosynthetic parameters on a weekly to monthly timescale via optimality principles. We demonstrate that it is possible to explicitly separate the fast and slow photosynthetic responses to environmental conditions, allowing the simulation of GPP at the sub‐daily timesteps required for coupling in an LSM. The resulting model reproduces the diurnal cycles of GPP recorded by eddy‐covariance flux towers in a temperate grassland and boreal, temperate and tropical forests. The best performance is achieved when biochemical capacities are adjusted to match recent midday conditions. Comparison between this model and the operational LSM in the European Centre for Medium‐range Weather Forecasts climate model shows that the new model has better predictive power in most of the sites and years analyzed, particularly in summer and autumn. Our analyses suggest a simple and parameter‐sparse method to include both instantaneous and acclimated responses within an LSM framework, with potential applications in weather, climate, and carbon‐cycle modeling.
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- 2022
15. Global datasets of leaf photosynthetic capacity for ecological and earth system research
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Jing M. Chen, Rong Wang, Yihong Liu, Liming He, Holly Croft, Xiangzhong Luo, Han Wang, Nicholas G. Smith, Trevor F. Keenan, I. Colin Prentice, Yongguang Zhang, Weimin Ju, Ning Dong, and Commission of the European Communities
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SPECTRUM ,Science & Technology ,Geology ,MODEL ,CLIMATE ,Physical Sciences ,CHLOROPHYLL CONTENT ,General Earth and Planetary Sciences ,Meteorology & Atmospheric Sciences ,SCATTERING ,GROWTH ,0402 Geochemistry ,0401 Atmospheric Sciences ,Geosciences, Multidisciplinary ,PLANT ,FLUORESCENCE ,ELEVATED CO2 ,0406 Physical Geography and Environmental Geoscience ,TRAITS - Abstract
The maximum rate of Rubisco carboxylation (Vcmax) determines leaf photosynthetic capacity and is a key parameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecological research. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to Vcmax, based on plants' optimal distribution of nitrogen between light harvesting and carboxylation pathways. We also derive Vcmax from satellite (GOME-2) observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis using a data assimilation technique. These two independent global Vcmax products agree well (r2=0.79,RMSE=15.46µmol m−2 s−1, P<0.001) and compare well with 3672 ground-based measurements (r2=0.69,RMSE=13.8µmol m−2 s−1 and P<0.001 for SIF; r2=0.55,RMSE=18.28µmol m−2 s−1 and P<0.001 for LCC). The LCC-derived Vcmax product is also used to constrain the retrieval of Vcmax from TROPical Ozone Mission (TROPOMI) SIF data to produce an optimized Vcmax product using both SIF and LCC information. The global distributions of these products are compatible with Vcmax computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH, and leaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial Vcmax products are primed to play a major role in global ecosystem research. The three remote sensing Vcmax products based on SIF, LCC, and SIF+LCC are available at https://doi.org/10.5281/zenodo.6466968 (Chen et al., 2022), and the code for implementing the ecological optimality theory is available at https://github.com/SmithEcophysLab/optimal_vcmax_R and https://doi.org/10.5281/zenodo.5899564 (last access: 31 August 2022) (Smith et al., 2022).
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- 2022
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16. Global variation in the fraction of leaf nitrogen allocated to photosynthesis
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Jing M. Chen, Holly Croft, Chonggang Xu, Trevor F. Keenan, Yao Zhang, Xiangzhong Luo, Han Wang, Rong Wang, I. Colin Prentice, Anthony P. Walker, Nicholas G. Smith, and Commission of the European Communities
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Chlorophyll ,Rubisco ,Internationality ,Nitrogen ,Science ,Ecophysiology ,Climate ,Ribulose-Bisphosphate Carboxylase ,General Physics and Astronomy ,Photosynthesis ,General Biochemistry, Genetics and Molecular Biology ,Article ,Phosphorus metabolism ,chemistry.chemical_compound ,Soil ,CARBON GAIN ,Theoretical ,PLANT FUNCTIONAL TYPES ,ACCLIMATION ,Models ,Soil pH ,LEAVES ,Ecosystem ,Nitrogen cycle ,Ecological modelling ,Science & Technology ,Multidisciplinary ,biology ,RuBisCO ,Phosphorus ,General Chemistry ,Models, Theoretical ,Photosynthetic capacity ,TRAIT DATABASE ,Multidisciplinary Sciences ,V-CMAX ,MODEL ,Plant Leaves ,chemistry ,Agronomy ,PHOSPHORUS LIMITATION ,biology.protein ,Science & Technology - Other Topics ,Environmental science - Abstract
Plants invest a considerable amount of leaf nitrogen in the photosynthetic enzyme ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO), forming a strong coupling of nitrogen and photosynthetic capacity. Variability in the nitrogen-photosynthesis relationship indicates different nitrogen use strategies of plants (i.e., the fraction nitrogen allocated to RuBisCO; fLNR), however, the reason for this remains unclear as widely different nitrogen use strategies are adopted in photosynthesis models. Here, we use a comprehensive database of in situ observations, a remote sensing product of leaf chlorophyll and ancillary climate and soil data, to examine the global distribution in fLNR using a random forest model. We find global fLNR is 18.2 ± 6.2%, with its variation largely driven by negative dependence on leaf mass per area and positive dependence on leaf phosphorus. Some climate and soil factors (i.e., light, atmospheric dryness, soil pH, and sand) have considerable positive influences on fLNR regionally. This study provides insight into the nitrogen-photosynthesis relationship of plants globally and an improved understanding of the global distribution of photosynthetic potential., The fraction of leaf nitrogen allocated to RuBisCO indicates differing nitrogen use strategies of plants and varies considerably. Here the authors show that this variation is largely driven by leaf thickness and phosphorus content with light intensity, atmospheric dryness and soil pH also having considerable influence.
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- 2021
17. Data-driven surrogate model with latent data assimilation: Application to wildfire forecasting
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Sibo Cheng, I. Colin Prentice, Yuhan Huang, Yufang Jin, Yi-Ke Guo, Rossella Arcucci, Leverhulme Trust, and The Leverhulme Trust
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Computational Mathematics ,Numerical Analysis ,02 Physical Sciences ,Physics and Astronomy (miscellaneous) ,Applied Mathematics ,Modeling and Simulation ,Physics::Atmospheric and Oceanic Physics ,01 Mathematical Sciences ,09 Engineering ,Computer Science Applications - Abstract
The large and catastrophic wildfires have been increasing across the globe in the recent decade, highlighting the importance of simulating and forecasting fire dynamics in near real-time. This is extremely challenging due to the complexities of physical models and geographical features. Running physics-based simulations for large wildfire events in near real-time are computationally expensive, if not infeasible. In this work, we develop and test a novel data-model integration scheme for fire progression forecasting, that combines Reduced-order modelling, recurrent neural networks (Long-Short-Term Memory), data assimilation, and error covariance tuning. The Reduced-order modelling and the machine learning surrogate model ensure the efficiency of the proposed approach while the data assimilation enables the system to adjust the simulation with observations. We applied this algorithm to simulate and forecast three recent large wildfire events in California from 2017 to 2020. The deep-learning-based surrogate model runs around 1000 times faster than the Cellular Automata simulation which is used to generate training data-sets. The daily fire perimeters derived from satellite observation are used as observation data in Latent Assimilation to adjust the fire forecasting in near real-time. An error covariance tuning algorithm is also performed in the reduced space to estimate prior simulation and observation errors. The evolution of the averaged relative root mean square error (R-RMSE) shows that data assimilation and covariance tuning reduce the RMSE by about 50% and considerably improves the forecasting accuracy. As a first attempt at a reduced order wildfire spread forecasting, our exploratory work showed the potential of data-driven machine learning models to speed up fire forecasting for various applications.
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- 2022
18. Quantifying the Importance of antecedent fuel-related vegetation properties for burnt area using random forests
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Alexander Kuhn-Régnier, Apostolos Voulgarakis, Peer Nowack, Sandy P. Harrison, I. Colin Prentice, and Matthias Forkel
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Fire season ,Moisture ,Antecedent (logic) ,Biome ,04 Earth Sciences ,05 Environmental Sciences ,Antecedent moisture ,Vegetation ,Seasonality ,06 Biological Sciences ,medicine.disease ,Atmospheric sciences ,Random forest ,medicine ,Environmental science ,Meteorology & Atmospheric Sciences - Abstract
The seasonal and longer-term dynamics of fuel accumulation affect fire seasonality and the occurrence of extreme wildfires. Failure to account for their influence may help to explain why state-of-the-art fire models do not simulate the length and timing of the fire season or interannual variability in burnt area well. We investigated the impact of accounting for different timescales of fuel production and accumulation on burnt area using a suite of random forest regression models that included the immediate impact of climate, vegetation, and human influences in a given month and tested the impact of various combinations of antecedent conditions in four productivity-related vegetation indices and in antecedent moisture conditions. Analyses were conducted for the period from 2010 to 2015 inclusive. Inclusion of antecedent vegetation conditions representing fuel build-up led to an improvement of the global, climatological out-of-sample R 2 from 0.579 to 0.701, but the inclusion of antecedent vegetation conditions on timescales ≥ 1 year had no impact on simulated burnt area. Current moisture levels were the dominant influence on fuel drying. Additionally, antecedent moisture levels were important for fuel build-up. The models also enabled the visualisation of interactions between variables, such as the importance of antecedent productivity coupled with instantaneous drying. The length of the period which needs to be considered varies across biomes; fuel-limited regions are sensitive to antecedent conditions that determine fuel build-up over longer time periods (∼ 4 months), while moisture-limited regions are more sensitive to current conditions that regulate fuel drying.
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- 2021
19. Ecosystem photosynthesis in land-surface models: a first-principles approach
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Anna Agusti-Panareda, Giulia Mengoli, Sandy P. Harrison, Carlo Trotta, I. Colin Prentice, and Souhail Boussetta
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Stomatal conductance ,Vapour Pressure Deficit ,Biome ,Primary production ,Environmental science ,Ecosystem ,Climate model ,Vegetation ,Atmospheric sciences ,Photosynthetic capacity - Abstract
Vegetation regulates land-atmosphere water and energy exchanges and is an essential component of land-surface models (LSMs). However, LSMs have been handicapped by assumptions that equate acclimated photosynthetic responses to environment with fast responses observable in the laboratory. These time scales can be distinguished by including specific representations of acclimation, but at the cost of further increasing parameter requirements. Here we develop an alternative approach based on optimality principles that predict the acclimation of carboxylation and electron-transport capacities, and a variable controlling the response of leaf-level carbon dioxide drawdown to vapour pressure deficit (VPD), to variations in growth conditions on a weekly to monthly time scale. In the “P model”, an optimality-based light-use efficiency model for gross primary production (GPP) on this time scale, these acclimated responses are implicit. Here they are made explicit, allowing fast and slow response time-scales to be separated and GPP to be simulated at sub-daily timesteps. The resulting model mimics diurnal cycles of GPP recorded by eddy-covariance flux towers in a temperate grassland and boreal, temperate and tropical forests, with no parameter changes between biomes. Best performance is achieved when biochemical capacities are adjusted to match recent midday conditions. This model suggests a simple and parameter-sparse method to include both instantaneous and acclimated responses within an LSM framework, with many potential applications in weather, climate and carbon - cycle modelling.Plain Language SummaryVegetation regulates the exchanges of energy, water and carbon dioxide between the land and the atmosphere. Numerical climate models represent these processes, focusing mainly on their rapid variations in response to changes in the environment (including temperature and light) on timescales of seconds to hours. However, plants also adjust their physiology to environmental changes over longer periods within the season. Here we have adapted a simple model that formulates plant behaviour in terms of optimal trade-offs between different processes, so it simulates processes on both time scales. This model correctly reproduces the daily cycle of carbon dioxide uptake by plants, as recorded in different kinds of vegetation. We show that plants optimize their behaviour for midday conditions, when the light is greatest, and adjust to longer-term environmental variations on a timescale of about a week to a month. The model conveniently avoids the need to give specific, fixed values to physiological variables (such as photosynthetic capacity) for different types of plants. The optimality assumptions mean that the model gives equally good results in tropical, temperate and boreal forests, and in grasslands, using the same equations, and a very small number of input variables that are constant across the world.Key PointsOptimality theory is used to develop a simple model incorporating fast and acclimated responses of photosynthesis and stomatal conductanceBiogeochemical photosynthetic capacities adjust to midday light conditionsThe new model simulates gross primary production on sub-daily timesteps across a range of different vegetation types and climate
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- 2021
20. Supplementary material to 'Reconstructing burnt area during the Holocene: an Iberian case study'
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Yicheng Shen, Luke Sweeney, Mengmeng Liu, Jose Antonio Lopez Saez, Sebastián Pérez-Díaz, Reyes Luelmo-Lautenschlaeger, Graciela Gil-Romera, Dana Hoefer, Gonzalo Jiménez-Moreno, Heike Schneider, I. Colin Prentice, and Sandy P. Harrison
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- 2021
21. Global photosynthetic capacity is optimized to the environment
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I. Colin Prentice, Tomas F. Domingues, Trevor F. Keenan, Philip A. Townsend, Rossella Guerrieri, Henrique Furstenau Togashi, Meng Wang, Shuangxi Zhou, F. Yoko Ishida, Shawn P. Serbin, Ülo Niinemets, Han Wang, Vincent Maire, Eric L. Kruger, Kristine Y. Crous, Ian J. Wright, Nicholas G. Smith, Lasantha K. Weerasinghe, Alistair Rogers, Jens Kattge, Lasse Tarvainen, Niu, Shuli, AXA Research Fund, Smith N.G., Keenan T.F., Colin Prentice I., Wang H., Wright I.J., Niinemets U., Crous K.Y., Domingues T.F., Guerrieri R., Yoko Ishida F., Kattge J., Kruger E.L., Maire V., Rogers A., Serbin S.P., Tarvainen L., Togashi H.F., Townsend P.A., Wang M., Weerasinghe L.K., and Zhou S.-X.
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0106 biological sciences ,V-cmax ,Letter ,coordination ,Acclimatization ,Ecophysiology ,nitrogen availability ,Nitrogen availability ,Atmospheric sciences ,01 natural sciences ,Vcmax ,WATER ,electron transport ,light availability ,Photosynthesis ,CO2 ASSIMILATION ,Ecology ,biology ,TEMPERATURE RESPONSE ,Temperature ,cmax ,Carbon cycle ,Adaptation, Physiological ,LEAF NITROGEN ,0501 Ecological Applications ,Resource use ,Plant Leave ,Life Sciences & Biomedicine ,TRAITS ,ecophysiology ,Nitrogen ,Physiological ,Ribulose-Bisphosphate Carboxylase ,Environmental Sciences & Ecology ,010603 evolutionary biology ,THERMAL-ACCLIMATION ,Carboxylation ,Jmax ,Letters ,Adaptation ,Ecology, Evolution, Behavior and Systematics ,Evolutionary Biology ,Science & Technology ,QUANTUM YIELD ,CONDUCTANCE ,0602 Ecology ,Contraception/Reproduction ,Electron transport ,010604 marine biology & hydrobiology ,RuBisCO ,BIOCHEMICAL-MODEL ,temperature ,Carbon Dioxide ,15. Life on land ,Photosynthetic capacity ,Climate Action ,Plant Leaves ,13. Climate action ,Ecological Applications ,Coordination ,Light availability ,biology.protein ,Environmental science ,Soil fertility - Abstract
Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (V cmax), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co‐optimization of carboxylation and water costs for photosynthesis, suggests that optimal V cmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field‐measured V cmax dataset for C3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first‐order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.
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- 2019
22. The validity of optimal leaf traits modelled on environmental conditions
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Belinda E. Medlyn, Michael J. Liddell, Lingling Zhu, Matthias M. Boer, I. Colin Prentice, Rizwana Rumman, Bradley Evans, Michael F. Hutchinson, Tim Wardlaw, David S. Ellsworth, Lucas A. Cernusak, James Cleverly, Ian J. Wright, Derek Eamus, Peter Cale, John J. G. Egerton, Keith J. Bloomfield, Henrique Furstenau Togashi, Lucy Hayes, Craig Macfarlane, Owen K. Atkin, Wayne S. Meyer, and AXA Research Fund
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0106 biological sciences ,0301 basic medicine ,Stomatal conductance ,stomatal conductance (g(s)) ,Physiology ,MESOPHYLL CONDUCTANCE ,STOMATAL CONDUCTANCE ,Plant Biology & Botany ,stable isotopes ,Plant Science ,Environment ,CARBON-ISOTOPE DISCRIMINATION ,Models, Biological ,01 natural sciences ,Electron Transport ,03 medical and health sciences ,Quantitative Trait, Heritable ,07 Agricultural and Veterinary Sciences ,Botany ,water-use efficiency ,ATMOSPHERIC CO2 ,Photosynthesis ,Carbon Isotopes ,Science & Technology ,TEMPERATURE RESPONSE ,Philosophy ,Plant Sciences ,temperature ,BIOCHEMICAL-MODEL ,stomatal conductance (gs) ,Reproducibility of Results ,06 Biological Sciences ,15. Life on land ,Photosynthetic capacity ,Plant Leaves ,030104 developmental biology ,aridity ,13. Climate action ,Plant Stomata ,Linear Models ,OPTIMIZATION THEORY ,Life Sciences & Biomedicine ,PHOTOSYNTHETIC CAPACITY ,Temperature response ,GAS-EXCHANGE ,010606 plant biology & botany - Abstract
© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust The ratio of leaf intercellular to ambient CO 2 (χ) is modulated by stomatal conductance (g s ). These quantities link carbon (C) assimilation with transpiration, and along with photosynthetic capacities (V cmax and J max ) are required to model terrestrial C uptake. We use optimization criteria based on the growth environment to generate predicted values of photosynthetic and water-use efficiency traits and test these against a unique dataset. Leaf gas-exchange parameters and carbon isotope discrimination were analysed in relation to local climate across a continental network of study sites. Sun-exposed leaves of 50 species at seven sites were measured in contrasting seasons. Values of χ predicted from growth temperature and vapour pressure deficit were closely correlated to ratios derived from C isotope (δ 13 C) measurements. Correlations were stronger in the growing season. Predicted values of photosynthetic traits, including carboxylation capacity (V cmax ), derived from δ 13 C, growth temperature and solar radiation, showed meaningful agreement with inferred values derived from gas-exchange measurements. Between-site differences in water-use efficiency were, however, only weakly linked to the plant's growth environment and did not show seasonal variation. These results support the general hypothesis that many key parameters required by Earth system models are adaptive and predictable from plants’ growth environments.
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- 2018
23. Latitudinal limits to the predicted increase of the peatland carbon sink with warming
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Nicole K. Sanderson, Maara S. Packalen, Eric S. Klein, Robert K. Booth, Esther Githumbi, Joan Bunbury, Svante Björck, Julie Loisel, Katarzyna Marcisz, Donna Carless, I. Colin Prentice, Christopher Bochicchio, Colin J Courtney-Mustaphi, Jonathan E. Nichols, Rodney A. Chimner, John Hribjlan, Joana Zaragoza-Castells, Michael J. Clifford, Joanna Uglow, Patrick Moss, D. Mauquoy, James R. Holmquist, Charly Massa, Markku Mäkilä, Michelle Garneau, T. Edward Turner, David Large, Tim Mighall, Rob Marchant, Fraser J.G. Mitchell, Mariusz Lamentowicz, Sarah A. Finkelstein, Paul Mathijssen, Zicheng Yu, Antonio Martínez Cortizas, François De Vleeschouwer, Lisa C. Orme, Steve Moreton, Rixt de Jong, Chris D. Jones, Edgar Karofeld, A. Britta K. Sannel, Pirita Oksanen, Atte Korhola, Gaël Le Roux, Graeme T. Swindles, Ulla Kokfelt, Matthew J. Amesbury, Philip Camill, Thomas P. Roland, Helen Mackay, Tatiana Blyakharchuk, Susan Page, Gabriel Magnan, Glen M. MacDonald, Simon Brewer, Barbara Fiałkiewicz-Kozieł, Terri Lacourse, Noemí Silva-Sánchez, Paul D.M. Hughes, Stephen Robinson, Natascha Steinberg, Miriam C. Jones, Dan J. Charman, Angela V. Gallego-Sala, Martin Lavoie, Marjolein van der Linden, Elizabeth L. Cressey, Simon van Bellen, Guoping Wang, Yan Zhao, David W. Beilman, Bas van Geel, Pierre Friedlingstein, Minna Väliranta, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), University of Bristol [Bristol], University of Utah, Department of Geography [Leicester], University of Leicester, Macquarie University, 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), Lund University [Lund], Centre National de la Recherche Scientifique (CNRS), University of Toronto, Université du Québec à Montréal = University of Québec in Montréal (UQAM), York Institute for Tropical Ecosystems, Environment Department, Wentworth Way, University of York [York, UK], University of Tartu, Geological Survey of Denmark and Greenland (GEUS), University of Helsinki, Department of Geography, University of Victoria [Canada] (UVIC), Argiles, Géochimie et Environnements sédimentaires - AGES (Liège, Belgium) (AGEs), Université de Liège, Uniwersytet im. Adama Mickiewicza w Poznaniu, Department of Chemical and Environmental Engineering, University of Nottingham, University of Nottingham, UK (UON), Université Laval [Québec] (ULaval), Lehigh University [Bethlehem], GEOTOP Research Center, Universite du Quebec a Montreal, Montreal, QC, Canada, Laboratoire Chrono-environnement - CNRS - UBFC (UMR 6249) (LCE), Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), University of Aberdeen, Universidade de Santiago de Compostela [Spain] (USC ), University of New South Wales [Canberra Campus] (UNSW), BIAX Consult (NETHERLANDS), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Key Laboratory of Machine Perception (MOE), Peking University [Beijing], School of Geosciences [Edinburgh], University of Edinburgh, VU University Amsterdam, Natural Environment Research Council (NERC), AXA Research Fund, 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), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Laboratoire Chrono-environnement (UMR 6249) (LCE), Vrije Universiteit Amsterdam [Amsterdam] (VU), and Ecosystem and Landscape Dynamics (IBED, FNWI)
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Peat ,010504 meteorology & atmospheric sciences ,Peatland ,[SDE.MCG]Environmental Sciences/Global Changes ,Climate change ,Growing season ,010501 environmental sciences ,Environmental Science (miscellaneous) ,Atmospheric sciences ,01 natural sciences ,Sink (geography) ,Carbon cycle ,Tropical peat ,Geosciences, Multidisciplinary ,ComputingMilieux_MISCELLANEOUS ,0105 earth and related environmental sciences ,Ecologie, Environnement ,geography ,geography.geographical_feature_category ,Biogeochemistry ,Carbon sink ,15. Life on land ,Multidisciplinär geovetenskap ,13. Climate action ,[SDE]Environmental Sciences ,Environmental science ,Social Sciences (miscellaneous) - Abstract
The carbon sink potential of peatlands depends on the balance of carbon uptake by plants and microbial decomposition. The rates of both these processes will increase with warming but it remains unclear which will dominate the global peatland response. Here we examine the global relationship between peatland carbon accumulation rates during the last millennium and planetary-scale climate space. A positive relationship is found between carbon accumulation and cumulative photosynthetically active radiation during the growing season for mid- to high-latitude peatlands in both hemispheres. However, this relationship reverses at lower latitudes, suggesting that carbon accumulation is lower under the warmest climate regimes. Projections under Representative Concentration Pathway (RCP)2.6 and RCP8.5 scenarios indicate that the present-day global sink will increase slightly until around AD 2100 but decline thereafter. Peatlands will remain a carbon sink in the future, but their response to warming switches from a negative to a positive climate feedback (decreased carbon sink with warming) at the end of the twenty-first century.
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- 2018
24. Vegetation dynamics of the eastern Mediterranean region during the Holocene
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Esmeralda Cruz-Silva, I. Colin Prentice, Elena Marinova, and Sandy P. Harrison
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Eastern mediterranean ,Physical geography ,Vegetation dynamics ,Geology ,Holocene - Abstract
The circum-Mediterranean region is characterized by high climatic diversity derived from its orographic heterogeneity and the influence of global marine and atmospheric circulation patterns. The region also has a long and dynamic history of human occupation dating back to ~ 8000 years BP. The complexity of this area is a challenge for reconstructing the dynamics of the vegetation through the Holocene. Rule-based approaches to reconstructing changing vegetation patterns through time are insufficient as they require the imposition of subjective boundaries between biomes and can be affected by known biases in pollen representation. We have developed and tested a new method that characterises biomes as a function of observed pollen assemblages based on a similarity index, conceptually related to the likelihood function, which takes account of within-biome variability in taxon abundances. We use 1181 modern pollen samples from the EMBSeCBIO database and assign these samples to biomes as represented in a map of potential natural vegetation that was developed using machine learning. The method was applied down-core to reconstruct past vegetation changes. Preliminary results show that this new methodology produces more accurate biome assignments under modern conditions (
- Published
- 2021
25. Global climate and nutrient controls of photosynthetic capacity
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Yunke Peng, Lucas A. Cernusak, I. Colin Prentice, Keith J. Bloomfield, Tomas F. Domingues, Natural Environment Research Council (NERC), AXA Research Fund, and Commission of the European Communities
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0106 biological sciences ,010504 meteorology & atmospheric sciences ,Environmental change ,QH301-705.5 ,Climate ,Irradiance ,Medicine (miscellaneous) ,chemistry.chemical_element ,Photosynthesis ,Atmospheric sciences ,01 natural sciences ,General Biochemistry, Genetics and Molecular Biology ,Article ,Atmosphere ,C3 photosynthesis ,Nutrient ,Ecosystem ,Biology (General) ,0105 earth and related environmental sciences ,Ecological modelling ,Phosphorus ,food and beverages ,Nutrients ,15. Life on land ,Plants ,Photosynthetic capacity ,chemistry ,13. Climate action ,Environmental science ,PLANTAS ,General Agricultural and Biological Sciences ,010606 plant biology & botany - Abstract
There is huge uncertainty about how global exchanges of carbon between the atmosphere and land will respond to continuing environmental change. A better representation of photosynthetic capacity is required for Earth System models to simulate carbon assimilation reliably. Here we use a global leaf-trait dataset to test whether photosynthetic capacity is quantitatively predictable from climate, based on optimality principles; and to explore how this prediction is modified by soil properties, including indices of nitrogen and phosphorus availability, measured in situ. The maximum rate of carboxylation standardized to 25 °C (Vcmax25) was found to be proportional to growing-season irradiance, and to increase—as predicted—towards both colder and drier climates. Individual species’ departures from predicted Vcmax25 covaried with area-based leaf nitrogen (Narea) but community-mean Vcmax25 was unrelated to Narea, which in turn was unrelated to the soil C:N ratio. In contrast, leaves with low area-based phosphorus (Parea) had low Vcmax25 (both between and within communities), and Parea increased with total soil P. These findings do not support the assumption, adopted in some ecosystem and Earth System models, that leaf-level photosynthetic capacity depends on soil N supply. They do, however, support a previously-noted relationship between photosynthesis and soil P supply., Yunke Peng et al. use in-situ measurements and leaf trait data at 266 global sites for 1637 species and find that the maximum rate of carboxylation standardized to 25 °C is proportional to growing-season irradiance, and covaries with area-based leaf nitrogen and area-based phosphorus on the species level. These results challenge the assumption that leaf-level photosynthetic capacity depends on soil N supply yet supports the relationship between photosynthesis and soil P supply.
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- 2021
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26. Mycorrhizal association as a primary control of the CO2 fertilization effect
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Bruce A. Hungate, I. Colin Prentice, Richard P. Phillips, Sara Vicca, César Terrer, and AXA Research Fund
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0106 biological sciences ,010504 meteorology & atmospheric sciences ,Nitrogen ,General Science & Technology ,Climate Change ,Biology ,01 natural sciences ,BIOMASS ,Carbon Cycle ,Carbon cycle ,CARBON-DIOXIDE ,chemistry.chemical_compound ,Human fertilization ,Mycorrhizae ,Ecosystem ,ATMOSPHERIC CO2 ,Nitrogen cycle ,0105 earth and related environmental sciences ,ENRICHMENT FACE ,Carbon dioxide in Earth's atmosphere ,Biomass (ecology) ,Science & Technology ,Multidisciplinary ,fungi ,FOREST PRODUCTIVITY ,Soil carbon ,Carbon Dioxide ,Multidisciplinary Sciences ,Agronomy ,chemistry ,13. Climate action ,Fertilization ,Carbon dioxide ,Science & Technology - Other Topics ,GROWTH ,ELEVATED CO2 ,SOIL CARBON ,RESPONSES ,010606 plant biology & botany - Abstract
Fungi relieve nitrogen limitation Rising concentrations of atmospheric CO 2 stimulate plant growth; an effect that could reduce the pace of anthropogenic climate change. But plants also need nitrogen for growth. So far, experimental nitrogen addition has had equivocal effects on the magnitude of CO 2 fertilization. Terrer et al. explain that the impact of nitrogen on plant growth depends on the relationship between nitrogen availability and symbioses with mycorrhizal soil fungi. Only plants with ectomycorrhizal fungi associated with their roots can overcome nitrogen limitation. Science , this issue p. 72
- Published
- 2021
27. Supplementary material to 'Quantifying the Importance of Antecedent Fuel-Related Vegetation Properties for Burnt Area using Random Forests'
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Alexander Kuhn-Régnier, Apostolos Voulgarakis, Peer Nowack, Matthias Forkel, I. Colin Prentice, and Sandy P. Harrison
- Published
- 2020
28. Supplementary material to 'Quantitative assessment of fire and vegetation properties in historical simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project'
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Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P. Harrison, Sally Archibald, Dominique Bachelet, Matthew Forrest, Thomas Hickler, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Lars Nieradzik, Sam S. Rabin, I. Colin Prentice, Tim Sheehan, Stephen Sitch, Lina Teckentrup, Apostolos Voulgarakis, and Chao Yue
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- 2020
29. Quantitative assessment of fire and vegetation properties in historical simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project
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Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P. Harrison, Sally Archibald, Dominique Bachelet, Matthew Forrest, Thomas Hickler, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Lars Nieradzik, Sam S. Rabin, I. Colin Prentice, Tim Sheehan, Stephen Sitch, Lina Teckentrup, Apostolos Voulgarakis, and Chao Yue
- Abstract
Global fire-vegetation models are widely used to assess impacts of environmental change on fire regimes and the carbon cycle, and to infer relationships between climate, land use, and fire. However, differences in model structure and parameterizations, in both the vegetation and fire components of these models, could influence overall model performance, and to date there has been limited evaluation of how well different models represent various aspects of fire regimes. The Fire Model Intercomparison Project (FireMIP) is coordinating the evaluation of state-of-the-art global fire models, with the aim of improving projections of fire regime characteristic and fire impacts on ecosystems and human societies under the context of global environmental change. Here we perform a systematic evaluation of historical simulations made by nine FireMIP models in order to quantify their ability to reproduce a range of fire and vegetation benchmarks. The FireMIP models simulate a wide range in global annual total burnt area (39–536 Mha), and global annual fire carbon emission (0.91–4.75 Pg C a−1) for modern conditions (2002–2012), but most of the range in burnt area is within observational uncertainty (345–468 Mha). Benchmarking scores indicate that seven out of nine FireMIP models are able to represent the spatial pattern in burnt area. The models also reproduce the seasonality in burnt area reasonably well but struggle to simulate fire season length and are largely unable to represent inter-annual variations in burnt area. However, models that represent cropland fires see improved simulation of fire seasonality in the northern hemisphere. The three FireMIP models which explicitly simulate individual fires are able to reproduce the spatial pattern in number of fires, but fire sizes are too small in key regions and this results in an underestimation of burnt area. The correct representation of spatial and seasonal patterns in vegetation appears to correlate with a better representation of burnt area. While some FireMIP models are better at representing certain aspects of the fire regime, no model clearly outperforms all other models across the full range of variables assessed.
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- 2020
30. Organizing principles for vegetation dynamics
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Stephan A. Pietsch, Elena Rovenskaya, Ehud Meron, Guy F. Midgley, Josep Peñuelas, Peter M. van Bodegom, Karin T. Rebel, Ian J. Wright, Sandy P. Harrison, Philippe Ciais, Marcel van Oijen, Daniel S. Falster, I. Colin Prentice, Michel Loreau, Sönke Zaehle, Caroline E. Farrior, Oskar Franklin, Wolfgang Cramer, Stefano Manzoni, Florian Hofhansl, César Terrer, Nadejda A. Soudzilovskaia, Åke Brännström, Han Wang, Ulf Dieckmann, Roderick C. Dewar, Annikki Mäkelä, Benjamin D. Stocker, Stanislaus J. Schymanski, Global Ecohydrology and Sustainability, Environmental Sciences, International Institute for Applied Systems Analysis (IIASA), Ecosystems Services and Management, Schlossplatz 1, A-2361 Laxenburg, Austria, Department of Forest Ecology and Management, Swedish University of Agricultural Sciences (SLU), Department of Geography and Environmental Science, University of Reading, Plant Sciences Division, Research School of Biology, The Australian National University, Institute for Atmospheric and Earth System Research (INAR), University of Helsinki, Department of Integrative Biology, University of Texas at Austin, Department of Mathematics and Mathematical Statistics, Umeå University, Department of Evolutionary Studies of Biosystems, The Graduate University for Advanced Studies (Sokendai), Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, University of New South Wales, 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), Station d'écologie théorique et expérimentale (SETE), Université Toulouse III - Paul Sabatier (UT3), 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), Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Copernicus Institute of Sustainable Development, Environmental Sciences, Faculty of Geosciences, Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Department of Physics, Ben-Gurion University of the Negev, Department of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, Department of Environmental Systems Sciences [Zürich], Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), CREAF CERDANYOLA DEL VALLES ESP, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Department of Physical Geography, Stockholm University, Bolin Centre for Climate Research, Stockholm University, Centre for Ecology and Hydrology (CEH-Edinburgh), Department of Biological Sciences, Macquarie University, 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), ICOS-ATC (ICOS-ATC), 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), Universiteit Leiden [Leiden], Global Ecology Unit CREAF-CEAB-CSIC, Universitat Autònoma de Barcelona (UAB), Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Stellenbosch University, ANR-11-IDEX-0002,UNITI,Université Fédérale de Toulouse(2011), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Umeå University, 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), Ben-Gurion University of the Negev (BGU), 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)-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), Universiteit Leiden, AXA Research Fund, and Commission of the European Communities
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0106 biological sciences ,0301 basic medicine ,Stomatal conductance ,Ecosystem ecology ,0607 Plant Biology ,0703 Crop and Pasture Production ,Plant Development ,Plant Science ,Theoretical ecology ,01 natural sciences ,03 medical and health sciences ,medicine ,Temporal scales ,Plant ecology ,Biological sciences ,Ecosystem ,Plant Physiological Phenomena ,Ecosytem ecology ,Ecology ,15. Life on land ,Plants ,Vegetation dynamics ,Biological Evolution ,030104 developmental biology ,13. Climate action ,[SDE]Environmental Sciences ,Environmental science ,medicine.symptom ,[SDE.BE]Environmental Sciences/Biodiversity and Ecology ,Vegetation (pathology) ,010606 plant biology & botany - Abstract
Plants and vegetation play a critical-but largely unpredictable-role in global environmental changes due to the multitude of contributing processes at widely different spatial and temporal scales. In this Perspective, we explore approaches to master this complexity and improve our ability to predict vegetation dynamics by explicitly taking account of principles that constrain plant and ecosystem behaviour: natural selection, self-organization and entropy maximization. These ideas are increasingly being used in vegetation models, but we argue that their full potential has yet to be realized. We demonstrate the power of natural selection-based optimality principles to predict photosynthetic and carbon allocation responses to multiple environmental drivers, as well as how individual plasticity leads to the predictable self-organization of forest canopies. We show how models of natural selection acting on a few key traits can generate realistic plant communities and how entropy maximization can identify the most probable outcomes of community dynamics in space- and time-varying environments. Finally, we present a roadmap indicating how these principles could be combined in a new generation of models with stronger theoretical foundations and an improved capacity to predict complex vegetation responses to environmental change.Integrating natural selection and other organizing principles into next-generation vegetation models could render them more theoretically sound and useful for earth system applications and modelling climate impacts.
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- 2020
31. N2O changes from the Last Glacial Maximum to the preindustrial – Part 2: terrestrial N2O emissions and carbon–nitrogen cycle interactions
- Author
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Fortunat Joos, Renato Spahni, Benjamin D. Stocker, Sebastian Lienert, Jurek Müller, Hubertus Fischer, Jochen Schmitt, I. Colin Prentice, Bette Otto-Bliesner, Zhengyu Liu
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- 2020
- Full Text
- View/download PDF
32. Quantifying leaf-trait covariation and its controls across climates and biomes
- Author
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I. Colin Prentice, Hang Wang, Changhui Peng, Sandy P. Harrison, Ian J. Wright, Yanzheng Yang, Guanghui Lin, and AXA Research Fund
- Subjects
0106 biological sciences ,0301 basic medicine ,China ,Multivariate analysis ,Specific leaf area ,Nitrogen ,Physiology ,ADAPTIVE VARIATION ,Climate ,Plant Biology & Botany ,Biome ,Plant Science ,Biology ,phylogeny ,CARBON-ISOTOPE DISCRIMINATION ,01 natural sciences ,03 medical and health sciences ,LEADING DIMENSIONS ,Photosynthesis ,Ecosystem ,vegetation modelling ,2. Zero hunger ,Principal Component Analysis ,Functional ecology ,Science & Technology ,plant functional traits ,Ecology ,leaf economics spectrum ,Plant Sciences ,BIOCHEMICAL-MODEL ,Vegetation ,06 Biological Sciences ,15. Life on land ,Photosynthetic capacity ,Plant Leaves ,multivariate analysis ,030104 developmental biology ,13. Climate action ,Principal component analysis ,Trait ,VEGETATION ,07 Agricultural And Veterinary Sciences ,COMMUNITIES ,Life Sciences & Biomedicine ,PHOTOSYNTHETIC CAPACITY ,RESPONSES ,010606 plant biology & botany - Abstract
Plant functional ecology requires the quantification of trait variation and its controls. Field measurements on 483 species at 48 sites across China were used to analyse variation in leaf traits, and assess their predictability. Principal components analysis (PCA) was used to characterize trait variation, redundancy analysis (RDA) to reveal climate effects, and RDA with variance partitioning to estimate separate and overlapping effects of site, climate, life-form and family membership. Four orthogonal dimensions of total trait variation were identified: leaf area (LA), internal-to-ambient CO2 ratio (χ), leaf economics spectrum traits (specific leaf area (SLA) versus leaf dry matter content (LDMC) and nitrogen per area (Narea )), and photosynthetic capacities (Vcmax , Jmax at 25°C). LA and χ covaried with moisture index. Site, climate, life form and family together explained 70% of trait variance. Families accounted for 17%, and climate and families together 29%. LDMC and SLA showed the largest family effects. Independent life-form effects were small. Climate influences trait variation in part by selection for different life forms and families. Trait values derived from climate data via RDA showed substantial predictive power for trait values in the available global data sets. Systematic trait data collection across all climates and biomes is still necessary.
- Published
- 2018
33. When and where soil is important to modify the carbon and water economy of leaves
- Author
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Andrea C. Westerband, Laurent J. Lamarque, Steeve Pepin, Han Wang, Vincent Maire, William K. Cornwell, Jennifer Paillassa, Gilbert Ethier, Ian J. Wright, I. Colin Prentice, Nicholas G. Smith, and Commission of the European Communities
- Subjects
0106 biological sciences ,0301 basic medicine ,PH ,Physiology ,Plant Biology & Botany ,LEAF RESPIRATION ,Plant Science ,Silt ,Photosynthesis ,01 natural sciences ,nitrogen ,soil pH ,03 medical and health sciences ,Alkali soil ,Soil ,Nutrient ,07 Agricultural and Veterinary Sciences ,Soil pH ,ISOTOPE DISCRIMINATION ,ATMOSPHERIC CO2 ,2. Zero hunger ,Science & Technology ,plant functional traits ,soil fertility ,DATA SET ,Plant Sciences ,Water ,06 Biological Sciences ,15. Life on land ,Carbon Dioxide ,Photosynthetic capacity ,Carbon ,CLIMATE ,MODEL ,Plant Leaves ,PHOSPHORUS ,030104 developmental biology ,Agronomy ,stomatal conductance ,13. Climate action ,Soil water ,Environmental science ,Soil fertility ,Life Sciences & Biomedicine ,least-cost theory ,010606 plant biology & botany - Abstract
Photosynthetic 'least-cost' theory posits that the optimal trait combination for a given environment is that where the summed costs of photosynthetic water and nutrient acquisition/use are minimised. The effects of soil water and nutrient availability on photosynthesis should be stronger as climate-related costs for both resources increase. Two independent datasets of photosynthetic traits, Globamax (1509 species, 288 sites) and Glob13C (3645 species, 594 sites), were used to quantify biophysical and biochemical limitations of photosynthesis and the key variable Ci /Ca (CO2 drawdown during photosynthesis). Climate and soil variables were associated with both datasets. The biochemical photosynthetic capacity was higher on alkaline soils. This effect was strongest at more arid sites, where water unit-costs are presumably higher. Higher values of soil silt and depth increased Ci /Ca , likely by providing greater H2 O supply, alleviating biophysical photosynthetic limitation when soil water is scarce. Climate is important in controlling the optimal balance of H2 O and N costs for photosynthesis, but soil properties change these costs, both directly and indirectly. In total, soil properties modify the climate-demand driven predictions of Ci /Ca by up to 30% at a global scale.
- Published
- 2019
34. A new multivariable benchmark for Last Glacial Maximum climate simulations
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Ian Roulstone, S. F. Cleator, Sandy P. Harrison, Nancy Nichols, and I. Colin Prentice
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010506 paleontology ,010504 meteorology & atmospheric sciences ,lcsh:Environmental protection ,Stratigraphy ,CIRCULATION ,MIDHOLOCENE CLIMATE ,01 natural sciences ,Data assimilation ,lcsh:Environmental pollution ,Evapotranspiration ,Meteorology & Atmospheric Sciences ,lcsh:TD169-171.8 ,RECONSTRUCTION ,Precipitation ,Mean radiant temperature ,Geosciences, Multidisciplinary ,ATMOSPHERIC CO2 ,lcsh:Environmental sciences ,0105 earth and related environmental sciences ,lcsh:GE1-350 ,Global and Planetary Change ,Carbon dioxide in Earth's atmosphere ,Science & Technology ,CONSTRAINTS ,Paleontology ,Last Glacial Maximum ,Geology ,Vegetation ,Growing degree-day ,15. Life on land ,13. Climate action ,POLLEN DATA ,Climatology ,PRECIPITATION ,lcsh:TD172-193.5 ,Physical Sciences ,PALEOCLIMATE ,Environmental science ,VEGETATION ,0406 Physical Geography and Environmental Geoscience ,SYSTEM MODEL - Abstract
We present a new global reconstruction of seasonal climates at the Last Glacial Maximum (LGM, 21 000 years BP) made using 3-D variational data assimilation with pollen-based site reconstructions of six climate variables and the ensemble average of the PMIP3—CMIP5 simulations as a prior (initial estimate of LGM climate). We assume that the correlation matrix of the uncertainties in the prior is both spatially and temporally Gaussian, in order to produce a climate reconstruction that is smoothed both from month to month and from grid cell to grid cell. The pollen-based reconstructions include mean annual temperature (MAT), mean temperature of the coldest month (MTCO), mean temperature of the warmest month (MTWA), growing season warmth as measured by growing degree days above a baseline of 5 ∘C (GDD5), mean annual precipitation (MAP), and a moisture index (MI), which is the ratio of MAP to mean annual potential evapotranspiration. Different variables are reconstructed at different sites, but our approach both preserves seasonal relationships and allows a more complete set of seasonal climate variables to be derived at each location. We further account for the ecophysiological effects of low atmospheric carbon dioxide concentration on vegetation in making reconstructions of MAP and MI. This adjustment results in the reconstruction of wetter climates than might otherwise be inferred from the vegetation composition. Finally, by comparing the uncertainty contribution to the final reconstruction, we provide confidence intervals on these reconstructions and delimit geographical regions for which the palaeodata provide no information to constrain the climate reconstructions. The new reconstructions will provide a benchmark created using clear and defined mathematical procedures that can be used for evaluation of the PMIP4–CMIP6 entry-card LGM simulations and are available at https://doi.org/10.17864/1947.244 (Cleator et al., 2020b).
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- 2019
35. Quantifying soil moisture impacts on light use efficiency across biomes
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I. Colin Prentice, Sonia I. Seneviratne, Josep Peñuelas, Jakob Zscheischler, Trevor F. Keenan, and Benjamin D. Stocker
- Subjects
0106 biological sciences ,Time Factors ,Light ,Vapor Pressure ,vapour pressure deficit ,010504 meteorology & atmospheric sciences ,Physiology ,Vapour Pressure Deficit ,Rain ,Biome ,Plant Science ,Atmospheric sciences ,01 natural sciences ,drought impacts ,Soil ,eddy covariance ,gross primary productivity (GPP) ,light use efficiency ,photosynthesis ,soil moisture ,standardized precipitation index ,vapour pressure deficit (VPD) ,Flue ,Water content ,2. Zero hunger ,Full Paper ,Vegetation ,Biological Sciences ,Full Papers ,Droughts ,gross primary productivity ,Neural Networks ,Plant Biology & Botany ,Eddy covariance ,Carbon cycle ,Computer ,Ecosystem ,0105 earth and related environmental sciences ,Agricultural and Veterinary Sciences ,Research ,Gross primary productivity () ,Water ,Humidity ,Plant Transpiration ,06 Biological Sciences ,15. Life on land ,Arid ,13. Climate action ,vapour pressure deficit (VPD ,Remote Sensing Technology ,Environmental science ,Neural Networks, Computer ,07 Agricultural And Veterinary Sciences ,010606 plant biology & botany - Abstract
Summary Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology.Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness.This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub‐humid, semi‐arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly‐based drought indices. Counter to common assumptions, fLUE reductions are largest in drought‐deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought‐related assessments., See also the Commentary on this article by https://doi.org/10.1111/nph.15176.
- Published
- 2018
36. Ecosystem responses to elevated <scp>CO</scp> 2 governed by plant–soil interactions and the cost of nitrogen acquisition
- Author
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Peter B. Reich, Adrien C. Finzi, Benjamin D. Stocker, Bruce A. Hungate, César Terrer, Sara Vicca, Richard P. Phillips, I. Colin Prentice, and AXA Research Fund
- Subjects
0106 biological sciences ,010504 meteorology & atmospheric sciences ,Physiology ,Plant Biology & Botany ,Plant Science ,Biology ,Photosynthesis ,01 natural sciences ,nitrogen ,Ectosymbiosis ,soil organic matter (SOM) ,Ecosystem ,soil carbon ,N2-fixation ,Free-Air CO2 enrichment (FACE) ,0105 earth and related environmental sciences ,2. Zero hunger ,photosynthesis ,Ecology ,Soil organic matter ,fungi ,food and beverages ,Global change ,mycorrhizas ,Soil carbon ,06 Biological Sciences ,15. Life on land ,Photosynthetic capacity ,Agronomy ,13. Climate action ,CO 2 ,07 Agricultural And Veterinary Sciences ,Offset (botany) ,010606 plant biology & botany - Abstract
Contents Summary 507 I. Introduction 507 II. The return on investment approach 508 III. CO2 response spectrum 510 IV. Discussion 516 Acknowledgements 518 References 518 SUMMARY: Land ecosystems sequester on average about a quarter of anthropogenic CO2 emissions. It has been proposed that nitrogen (N) availability will exert an increasingly limiting effect on plants' ability to store additional carbon (C) under rising CO2 , but these mechanisms are not well understood. Here, we review findings from elevated CO2 experiments using a plant economics framework, highlighting how ecosystem responses to elevated CO2 may depend on the costs and benefits of plant interactions with mycorrhizal fungi and symbiotic N-fixing microbes. We found that N-acquisition efficiency is positively correlated with leaf-level photosynthetic capacity and plant growth, and negatively with soil C storage. Plants that associate with ectomycorrhizal fungi and N-fixers may acquire N at a lower cost than plants associated with arbuscular mycorrhizal fungi. However, the additional growth in ectomycorrhizal plants is partly offset by decreases in soil C pools via priming. Collectively, our results indicate that predictive models aimed at quantifying C cycle feedbacks to global change may be improved by treating N as a resource that can be acquired by plants in exchange for energy, with different costs depending on plant interactions with microbial symbionts.
- Published
- 2017
37. Towards a universal model for carbon dioxide uptake by plants
- Author
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William K. Cornwell, Trevor F. Keenan, I. Colin Prentice, Han Wang, Bradley Evans, Changhui Peng, Ian J. Wright, Tyler W. Davis, and AXA Research Fund
- Subjects
0106 biological sciences ,010504 meteorology & atmospheric sciences ,Vapour Pressure Deficit ,Climate ,MESOPHYLL CONDUCTANCE ,Biome ,Plant Science ,PHYSIOLOGICAL-BASIS ,Biology ,Atmospheric sciences ,01 natural sciences ,chemistry.chemical_compound ,Theoretical ,Models ,ISOTOPE DISCRIMINATION ,Ecosystem ,Photosynthesis ,CO2 ASSIMILATION ,TERRESTRIAL BIOSPHERE ,Macroecology ,0105 earth and related environmental sciences ,Carbon Isotopes ,Science & Technology ,Ecology ,Plant Sciences ,BIOCHEMICAL-MODEL ,Biogeochemistry ,Primary production ,GROSS PRIMARY PRODUCTION ,Models, Theoretical ,Plants ,Carbon Dioxide ,C-13 DISCRIMINATION ,Plant Leaves ,Earth system science ,chemistry ,LIGHT-USE EFFICIENCY ,Carbon dioxide ,Life Sciences & Biomedicine ,WATER-USE EFFICIENCY ,010606 plant biology & botany - Abstract
Gross primary production (GPP)-the uptake of carbon dioxide (CO2) by leaves, and its conversion to sugars by photosynthesis-is the basis for life on land. Earth System Models (ESMs) incorporating the interactions of land ecosystems and climate are used to predict the future of the terrestrial sink for anthropogenic CO21 . ESMs require accurate representation of GPP. However, current ESMs disagree on how GPP responds to environmental variations 1,2 , suggesting a need for a more robust theoretical framework for modelling 3,4 . Here, we focus on a key quantity for GPP, the ratio of leafinternal to external CO2 (χ). χ is tightly regulated and depends on environmental conditions, but is represented empirically and incompletely in today's models. We show that a simple evolutionary optimality hypothesis 5,6 predicts specific quantitative dependencies of χ on temperature, vapour pressure deficit and elevation; and that these same dependencies emerge from an independent analysis of empirical χ values, derived from a worldwide dataset of >3,500 leaf stable carbon isotope measurements. A single global equation embodying these relationships then unifies the empirical light-use efficiency model 7 with the standard model of C3 photosynthesis 8 , and successfully predicts GPP measured at eddy-covariance flux sites. This success is notable given the equation's simplicity and broad applicability across biomes and plant functional types. It provides a theoretical underpinning for the analysis of plant functional coordination across species and emergent properties of ecosystems, and a potential basis for the reformulation of the controls of GPP in next-generation ESMs.
- Published
- 2017
38. Global climatic drivers of leaf size
- Author
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Ülo Niinemets, Han Wang, Sandra Díaz, Lawren Sack, Peter B. Reich, Ning Dong, I. Colin Prentice, Rafael Villar, Robert M. Kooyman, Elizabeth A. Law, Rachael V. Gallagher, Peter Wilf, Ian J. Wright, Bonnie F. Jacobs, Mark Westoby, Michelle R. Leishman, Vincent Maire, and AXA Research Fund
- Subjects
0106 biological sciences ,Daytime ,General Science & Technology ,Climate ,Climate Change ,Otras Ciencias Biológicas ,CLIMATE CHANGE ,Climate change ,Photosynthesis ,010603 evolutionary biology ,01 natural sciences ,Latitude ,ENERGY ,Ciencias Biológicas ,LEAF ,TEMPERATURES ,MD Multidisciplinary ,LEAVES ,PLANTS ,Leaf size ,RAINFALL ,2. Zero hunger ,ENVIRONMENT ,Science & Technology ,Multidisciplinary ,Ecology ,Temperature ,CONSTRAINTS ,Water ,Vegetation ,15. Life on land ,Arid ,Multidisciplinary Sciences ,Plant Leaves ,FUNCTIONAL TRAITS ,PATTERNS ,Sunlight ,Science & Technology - Other Topics ,MORPHOLOGY ,Environmental science ,TRAITS ,CIENCIAS NATURALES Y EXACTAS ,Water use ,010606 plant biology & botany - Abstract
Leaf size varies by over a 100,000-fold among species worldwide. Although 19th-century plant geographers noted that the wet tropics harbor plants with exceptionally large leaves,the latitudinal gradient of leaf size has not been well quantified nor the key climatic drivers convincingly identified. Here, we characterize worldwide patterns in leaf size. Large-leaved species predominate in wet, hot, sunny environments; small-leaved species typify hot,sunny environments only in arid conditions; small leaves are also found in high latitudes and elevations. By modeling the balance of leaf energy inputs and outputs, we show that daytime and nighttime leaf-to-air temperature differences are key to geographic gradients in leaf size. This knowledge can enrich ?next-generation? vegetation models in which leaf temperature and water use during photosynthesis play key roles. Fil: Wright, Ian J.. Macquarie University; Australia Fil: Dong, Ning. Macquarie University; Australia. University of Reading, Whiteknights; Reino Unido Fil: Maire, Vincent. Université du Québec à Trois-Rivières; Canadá. Macquarie University; Australia Fil: Prentice, I. Colin. Macquarie University; Australia. Imperial College London; Reino Unido Fil: Westoby, Mark. Macquarie University; Australia 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: Gallagher, Rachel V.. Macquarie University; Australia Fil: Jacobs, Bonnie F.. Southern Methodist University; Estados Unidos Fil: Kooyman, Robert. Macquarie University; Australia Fil: Law, Elizabeth A.. Macquarie University; Australia. The University Of Queensland; Australia Fil: Leishman, Michelle R.. Macquarie University; Australia Fil: Niinemets, Ülo. Estonian University of Life Sciences; Estonia Fil: Reich, Peter B.. University of Minnesota; Estados Unidos. Western Sydney University; Australia Fil: Sack, Lawren. University of California. Department of Ecology and Evolutionary Biology; Estados Unidos Fil: Villar, Rafael. Universidad de Córdoba. Facultad de Ciencias. Área de Ecología; España Fil: Wang, Han. Northwest A & F University. College of Forestry; China Fil: Wilf, Peter. Pennsylvania State University. Department of Geosciences; Estados Unidos
- Published
- 2017
39. Transforming conservation science and practice for a postnormal world
- Author
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I. Colin Prentice, Paul Leadley, Ioan Fazey, Sandra Lavorel, Lorrae van Kerkhoff, Patrick Degeorges, John Crowley, Carina Wyborn, Russell Gorddard, Michael Dunlop, Georgina M. Mace, Matthew J. Colloff, and Wendy Foden
- Subjects
0106 biological sciences ,010504 meteorology & atmospheric sciences ,Ecology ,Corporate governance ,Conservation psychology ,Context (language use) ,Environmental ethics ,Cognitive reframing ,Social learning ,010603 evolutionary biology ,01 natural sciences ,Coproduction ,Problematization ,Intergenerational equity ,Sociology ,Ecology, Evolution, Behavior and Systematics ,0105 earth and related environmental sciences ,Nature and Landscape Conservation - Abstract
We examine issues to consider when reframing conservation science and practice in the context of global change. New framings of the links between ecosystems and society are emerging that are changing peoples’ values and expectations of nature, resulting in plural perspectives on conservation. Reframing conservation for global change can thus be regarded as a stage in the evolving relationship between people and nature rather than some recent trend. New models of how conservation links with transformative adaptation include how decision contexts for conservation can be reframed and integrated with an adaptation pathways approach to create new options for global‐change‐ready conservation. New relationships for conservation science and governance include coproduction of knowledge that supports social learning. New processes for implementing adaptation for conservation outcomes include deliberate practices used to develop new strategies, shift world views, work with conflict, address power and intergenerational equity in decisions, and build consciousness and creativity that empower agents to act. We argue that reframing conservation for global change requires scientists and practitioners to implement approaches unconstrained by discipline and sectoral boundaries, geopolitical polarities, or technical problematization. We consider a stronger focus on inclusive creation of knowledge and the interaction of this knowledge with societal values and rules is likely to result in conservation science and practice that meets the challenges of a postnormal world.
- Published
- 2017
40. Author Correction: Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass
- Author
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César Terrer, Peter B. Reich, Benjamin D. Stocker, Christoph Müller, Sara Vicca, Shilong Piao, Robert B. Jackson, Paul C. D. Newton, Takayoshi Koike, Oskar Franklin, Marcel R. Hoosbeek, H. Wayne Polley, Dana M. Blumenthal, Alan F. Talhelm, Wolfgang Viechtbauer, Josep Peñuelas, Klaus Winter, Trevor F. Keenan, Caspar J. van Lissa, Kevin Van Sundert, I. Colin Prentice, Joshua B. Fisher, Lucas A. Cernusak, Bruce A. Hungate, Christopher B. Field, Makoto Watanabe, Yi Y. Liu, Nadejda A. Soudzilovskaia, Mark J. Hovenden, Christina Kaiser, Ian McCallum, and Victor O. Leshyk
- Subjects
WIMEK ,Bodemscheikunde en Chemische Bodemkwaliteit ,Phosphorus ,chemistry.chemical_element ,Biomass ,Environmental Science (miscellaneous) ,Nitrogen ,Human fertilization ,Agronomy ,chemistry ,Life Science ,Environmental science ,Social Sciences (miscellaneous) ,Soil Chemistry and Chemical Soil Quality - Published
- 2020
41. The climatic space of European pollen taxa
- Author
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Sandy P. Harrison, I. Colin Prentice, and Dongyang Wei
- Subjects
0106 biological sciences ,Climate Change ,Climate change ,medicine.disease_cause ,010603 evolutionary biology ,01 natural sciences ,Pteridophyte ,Abundance (ecology) ,Pollen ,medicine ,Ecology, Evolution, Behavior and Systematics ,Models, Statistical ,biology ,Ecology ,010604 marine biology & hydrobiology ,Generalized additive model ,Temperature ,Growing degree-day ,15. Life on land ,biology.organism_classification ,Data set ,Cold Temperature ,Taxon ,Geography ,13. Climate action ,Physical geography ,Seasons - Abstract
Pollen data are widely used to reconstruct past climate changes, using relationships between modern pollen abundance in surface samples and climate at the surface-sample sites as a calibration. Visualization of modern pollen data in multidimensional climate space provides a way to establish that taxon abundances are well behaved before using them in climate reconstructions. Visualization is also helpful for ecological interpretation of variations in pollen abundance in space and time. Here, we present Generalized Additive Models for the distribution of 195 European pollen and pteridophyte spore taxa in a bioclimate space defined by seasonal temperatures (as mean temperature of the coldest month and annual growing degree days) and an annual moisture index. These models can be used to explore the realized climate niche of pollen taxa and to build statistical models for palaeoclimate reconstruction. The data set is released under a Creative Commons BY license. When using the data set, we kindly request that you cite this article.
- Published
- 2019
42. Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass
- Author
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Caspar J. van Lissa, Benjamin D. Stocker, Oskar Franklin, Peter B. Reich, I. Colin Prentice, Kevin Van Sundert, Alan F. Talhelm, Josep Peñuelas, Mark J. Hovenden, Christina Kaiser, Takayoshi Koike, Paul C. D. Newton, Joshua B. Fisher, Robert B. Jackson, Sara Vicca, Klaus Winter, Nadejda A. Soudzilovskaia, Marcel R. Hoosbeek, H. Wayne Polley, Makoto Watanabe, Christoph Müller, Ian McCallum, Lucas A. Cernusak, Bruce A. Hungate, Christopher B. Field, Victor O. Leshyk, Trevor F. Keenan, Dana M. Blumenthal, Yi Y. Liu, Wolfgang Viechtbauer, César Terrer, Shilong Piao, AXA Research Fund, Commission of the European Communities, Psychiatrie & Neuropsychologie, and RS: MHeNs School for Mental Health and Neuroscience
- Subjects
010504 meteorology & atmospheric sciences ,Environmental Studies ,01 natural sciences ,Physical Geography and Environmental Geoscience ,CARBON ,Human fertilization ,Nutrient ,Meteorology & Atmospheric Sciences ,0502 Environmental Science and Management ,2. Zero hunger ,0303 health sciences ,Biomass (ecology) ,Physics ,FOREST PRODUCTIVITY ,Vegetation ,Nitrogen ,Chemistry ,Physical Sciences ,GROWTH ,0406 Physical Geography and Environmental Geoscience ,Ecosystem ecology ,Life Sciences & Biomedicine ,Bodemscheikunde en Chemische Bodemkwaliteit ,Environmental Science and Management ,chemistry.chemical_element ,Environmental Sciences & Ecology ,Environmental Science (miscellaneous) ,Atmospheric Sciences ,03 medical and health sciences ,ENHANCEMENT ,Life Science ,ATMOSPHERIC CO2 ,Biology ,METAANALYSIS ,030304 developmental biology ,0105 earth and related environmental sciences ,Science & Technology ,WIMEK ,Phosphorus ,Biogeochemistry ,MOJAVE DESERT ,15. Life on land ,CLIMATE ,Climate Action ,Agronomy ,chemistry ,13. Climate action ,Environmental science ,0401 Atmospheric Sciences ,ELEVATED CO2 ,Environmental Sciences ,Soil Chemistry and Chemical Soil Quality ,Social Sciences (miscellaneous) ,RESPONSES - Abstract
Elevated CO2 (eCO(2)) experiments provide critical information to quantify the effects of rising CO2 on vegetation 1-6 . Many eCO(2) experiments suggest that nutrient limitations modulate the local magnitude of the eCO(2) effect on plant biomass(1,3,5), but the global extent of these limitations has not been empirically quantified, complicating projections of the capacity of plants to take up CO27,9. Here, we present a data-driven global quantification of the eCO(2) effect on biomass based on 138 eCO(2) experiments. The strength of CO2 fertilization is primarily driven by nitrogen (N) in similar to 65% of global vegetation and by phosphorus (P) in similar to 25% of global vegetation, with N- or P-limitation modulated by mycorrhizal association. Our approach suggests that CO2 levels expected by 2100 can potentially enhance plant biomass by 12 +/- 3% above current values, equivalent to 59 +/- 13 PgC. The globalscale response to eCO(2) we derive from experiments is similar to past changes in greenness(9) and bio-mass(10) with rising CO2, suggesting that CO2 will continue to stimulate plant biomass in the future despite the constraining effect of soil nutrients. Our research reconciles conflicting evidence on CO2 fertilization across scales and provides an empirical estimate of the biomass sensitivity to eCO(2) that may help to constrain climate projections.
- Published
- 2019
43. Acclimation of leaf respiration consistent with optimal photosynthetic capacity
- Author
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Trevor F. Keenan, Peter B. Reich, Nicholas G. Smith, Keith J. Bloomfield, Ian J. Wright, Jens Kattge, I. Colin Prentice, Han Wang, Owen K. Atkin, AXA Research Fund, and Commission of the European Communities
- Subjects
0106 biological sciences ,010504 meteorology & atmospheric sciences ,Biodiversity & Conservation ,05 Environmental Sciences ,PLANT RESPIRATION ,NITROGEN LIMITATION ,acclimation ,Atmospheric sciences ,01 natural sciences ,co-ordination ,General Environmental Science ,Global and Planetary Change ,Ecology ,Plant functional type ,VARIABILITY ,climate change ,LIGHT ,Biodiversity Conservation ,TEMPERATURE RESPONSES ,Life Sciences & Biomedicine ,TRAITS ,Environmental Sciences & Ecology ,leaf mass per area ,Photosynthesis ,land-surface model ,010603 evolutionary biology ,Acclimatization ,carboxylation capacity (V-cmax) ,Degree (temperature) ,Carbon cycle ,THERMAL-ACCLIMATION ,carbon cycle ,Respiration ,nitrogen cycle ,Environmental Chemistry ,Ecosystem ,0105 earth and related environmental sciences ,Science & Technology ,photosynthesis ,leaf nitrogen ,BIOCHEMICAL-MODEL ,carboxylation capacity (Vcmax) ,06 Biological Sciences ,15. Life on land ,Photosynthetic capacity ,CLIMATE ,optimality ,13. Climate action ,ECOSYSTEM RESPONSES ,Environmental Sciences - Abstract
Plant respiration is an important contributor to the proposed positive global carbon-cycle feedback to climate change. However, as a major component, leaf mitochondrial ('dark') respiration (Rd ) differs among species adapted to contrasting environments and is known to acclimate to sustained changes in temperature. No accepted theory explains these phenomena or predicts its magnitude. Here we propose that the acclimation of Rd follows an optimal behaviour related to the need to maintain long-term average photosynthetic capacity (Vcmax ) so that available environmental resources can be most efficiently used for photosynthesis. To test this hypothesis, we extend photosynthetic co-ordination theory to predict the acclimation of Rd to growth temperature via a link to Vcmax , and compare predictions to a global set of measurements from 112 sites spanning all terrestrial biomes. This extended co-ordination theory predicts that field-measured Rd and Vcmax accessed at growth temperature (Rd,tg and Vcmax,tg ) should increase by 3.7% and 5.5% per degree increase in growth temperature. These acclimated responses to growth temperature are less steep than the corresponding instantaneous responses, which increase 8.1% and 9.9% per degree of measurement temperature for Rd and Vcmax respectively. Data-fitted responses proof indistinguishable from the values predicted by our theory, and smaller than the instantaneous responses. Theory and data are also shown to agree that the basal rates of both Rd and Vcmax assessed at 25°C (Rd,25 and Vcmax,25 ) decline by ~4.4% per degree increase in growth temperature. These results provide a parsimonious general theory for Rd acclimation to temperature that is simpler-and potentially more reliable-than the plant functional type-based leaf respiration schemes currently employed in most ecosystem and land-surface models.
- Published
- 2019
44. Historical changes in the stomatal limitation of photosynthesis: empirical support for an optimality principle
- Author
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Annette Menzel, Yunting Fang, Rory Clisby, I. Colin Prentice, Elisabet Martínez-Sancho, Steve Voelker, John S. Roden, Adam Z. Csank, Christopher J. Still, J. Julio Camarero, Iain Robertson, Heather Graven, Rachel Keen, Valérie Daux, Hugo J. de Boer, Todd E. Dawson, Frederick C. Meinzer, Keith J. Bloomfield, Isabel Dorado-Liñán, Aliénor Lavergne, Giovanna Battipaglia, AXA Research Fund, The Royal Society, Commission of the European Communities, 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), Géochrononologie Traceurs Archéométrie (GEOTRAC), 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), Glaces et Continents, Climats et Isotopes Stables (GLACCIOS), Geography, Swansea University, Centro de Investigacion Forestal (INIA-CIFOR), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria = National Institute for Agricultural and Food Research and Technology (INIA), Department of Environmental, Biological and Pharmaceutical Sciences and Technologies (DiSTABiF), University of Naples Federico II = Università degli studi di Napoli Federico II, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Max-Planck-Institut für Biogeochemie (MPI-BGC), 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)-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), University of Naples Federico II, Technical University of Munich (TUM), Lavergne, A., Voelker, S., Csank, A., Graven, H., de Boer, H. J., Daux, V., Robertson, I., Dorado-Linan, I., Martinez-Sancho, E., Battipaglia, G., Bloomfield, K. J., Still, C. J., Meinzer, F. C., Dawson, T. E., Julio Camarero, J., Clisby, R., Fang, Y., Menzel, A., Keen, R. M., Roden, J. S., and Prentice, I. C.
- Subjects
0106 biological sciences ,0301 basic medicine ,Physiology ,Vapour Pressure Deficit ,Plant Science ,Atmospheric sciences ,01 natural sciences ,Panoply ,TREE-RINGS ,water-use efficiency ,Photosynthesis ,ComputingMilieux_MISCELLANEOUS ,leaf-internal CO2 concentration ,Carbon Isotopes ,Atmospheric pressure ,TEMPERATURE RESPONSE ,Variance (accounting) ,Vegetation ,stable carbon isotope ,least-cost hypothesi ,LEAF NITROGEN ,Life Sciences & Biomedicine ,concentration ,Stomatal conductance ,[SDE.MCG]Environmental Sciences/Global Changes ,MESOPHYLL CONDUCTANCE ,Plant Biology & Botany ,CARBON-ISOTOPE DISCRIMINATION ,stable carbon isotopes ,least-cost hypothesis ,03 medical and health sciences ,07 Agricultural and Veterinary Sciences ,Water-use efficiency ,ATMOSPHERIC CO2 ,PLANT ,Science & Technology ,Plant Sciences ,leaf-internal CO ,Water ,tree ring ,15. Life on land ,06 Biological Sciences ,Carbon Dioxide ,MODEL ,Plant Leaves ,optimality ,tree rings ,030104 developmental biology ,13. Climate action ,Soil water ,Environmental science ,[SDV.EE.BIO]Life Sciences [q-bio]/Ecology, environment/Bioclimatology ,ELEVATED CO2 ,Water use ,010606 plant biology & botany - Abstract
The ratio of leaf internal (ci ) to ambient (ca ) partial pressure of CO2 , defined here as χ, is an index of adjustments in both leaf stomatal conductance and photosynthetic rate to environmental conditions. Measurements and proxies of this ratio can be used to constrain vegetation model uncertainties for predicting terrestrial carbon uptake and water use. We test a theory based on the least-cost optimality hypothesis for modelling historical changes in χ over the 1951-2014 period, across different tree species and environmental conditions, as reconstructed from stable carbon isotopic measurements across a global network of 103 absolutely dated tree-ring chronologies. The theory predicts optimal χ as a function of air temperature, vapour pressure deficit, ca and atmospheric pressure. The theoretical model predicts 39% of the variance in χ values across sites and years, but underestimates the intersite variability in the reconstructed χ trends, resulting in only 8% of the variance in χ trends across years explained by the model. Overall, our results support theoretical predictions that variations in χ are tightly regulated by the four environmental drivers. They also suggest that explicitly accounting for the effects of plant-available soil water and other site-specific characteristics might improve the predictions.
- Published
- 2019
45. N2O changes from the Last Glacial Maximum to the preindustrial – Part II: Terrestrial N2O emissions constrain carbon-nitrogen interactions
- Author
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Jurek Müller, Hubertus Fischer, Benjamin D. Stocker, Zhengyu Liu, Sebastian Lienert, Renato Spahni, Fortunat Joos, Bette L. Otto-Bliesner, I. Colin Prentice, and Jochen Schmitt
- Subjects
010504 meteorology & atmospheric sciences ,Environmental change ,Global warming ,Deglaciation ,Northern Hemisphere ,Carbon sink ,Environmental science ,Last Glacial Maximum ,Ecosystem ,Atmospheric sciences ,Dynamic global vegetation model ,01 natural sciences ,0105 earth and related environmental sciences - Abstract
Land ecosystems currently take up a quarter of the human-caused carbon dioxide emissions. Future projections of this carbon sink are strikingly divergent, leading to major uncertainties in projected global warming. This situation partly reflects our insufficient understanding of carbon-nitrogen (C-N) interactions and particularly of the controls on biological N fixation (BNF). It is difficult to infer ecosystem responses for century time scales, relevant for global warming, from the comparatively short instrumental records and laboratory or field experiments. Here we analyse terrestrial emissions of nitrous oxide (N2O) over the past 21,000 years as reconstructed from ice-core isotopic data and presented in part I of this study. Changing N2O emissions are interpreted to reflect changes in ecosystem N loss, plant available N, and BNF. The ice-core data reveal a 40 % increase in N2O emissions over the deglaciation, suggestive of a highly dynamic global N cycle whereby sources of plant-available N adjust to meet plant N demand and loss fluxes. Remarkably, the increase occurred in two steps, each realized within maximum two centuries, at the onsets of the northern hemisphere warming events around 14,600 and 11,700 years ago. We applied the LPX-Bern dynamic global vegetation model in deglacial simulations forced with Earth System Model climate data to investigate N2O emission patterns, mechanisms, and C-N coupling. The reconstructed increase in terrestrial emissions is broadly reproduced by the model, given the assumption that BNF positively responds to increasing N demand by plants. In contrast, assuming time- and demand-independent levels of BNF in the model to mimic progressive N limitation of plant growth results in N2O emissions that are incompatible with the reconstruction. Our results suggest the existence of (a) strong biological controls on ecosystem N acquisition, and (b) flexibility in the coupling of the C and N cycles during periods of rapid environmental change.
- Published
- 2019
46. Quantifying climatic influences on tree-ring width
- Author
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Sandy P. Harrison, I. Colin Prentice, and Guangqi Li
- Subjects
Canopy ,010504 meteorology & atmospheric sciences ,Growing season ,Primary production ,15. Life on land ,Random effects model ,Atmospheric sciences ,01 natural sciences ,Evapotranspiration ,Dendrochronology ,Shading ,Growth rate ,0105 earth and related environmental sciences ,Mathematics - Abstract
Before tree-ring series can be used to quantify climatic influences on growth, ontogenetic and microenvironmental effects must be removed. Existing statistical detrending methods struggle to eliminate bias, caused by the fact that older/larger trees are nearly always more abundantly sampled during the most recent decades – which happens also to have seen the strongest environmental changes. Here we develop a new approach to derive a productivity index (P*) from tree-ring series. The critical stem diameter, when an initial rapid increase in stem radial growth gives way to a gradual decrease, is estimated using a theoretical approximation; previous growth rings are removed from analysis. The subsequent dynamics of stem radial growth are assumed to be determined by: tree diameter and height; P* (gross primary production per unit leaf area, discounted by a "tax" due to the respiration and turnover of leaves and fine roots); and a quantity proportional to sapwood specific respiration (r1). The term r1 depends not only on the growth rate but also on tree height, because a given leaf area requires a greater volume of living sapwood to be maintained in taller trees. Height-diameter relationships were estimated from independent observations. P* values were then estimated from tree ring-width measurements on multiple trees, using a non-linear mixed-effects model in which the random effect of individual tree identity accounts for the impact of local environmental variability, due to soil or hydrological conditions, and canopy position (i.e. shading and competition). Year-by-year P* at a site should then represent the influence of year-by-year changes in environment, independently of the growth trend in individual trees. This approach was applied to tree-ring records from two genera (Picea and Pinus) at 492 sites across the Northern Hemisphere extratropics. Using a multiple linear mixed-effects regression with site as a random effect, it was found that estimated annual P* values for both genera show consistent, temporally stable positive responses of P* to total photosynthetically photon flux density during the growing season (PPFD5) and soil moisture availability (indexed by an estimate of the ratio of actual to potential evapotranspiration). The partial effect of mean temperature during the growing season (mGGD5) however was shown to follow a unimodal curve, being positive in climates with mGGD5
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- 2019
47. Supplementary material to 'Climate changes in interior semi-arid Spain from the last interglacial to the late Holocene'
- Author
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Dongyang Wei, Penélope González-Sampériz, Graciela Gil-Romera, Sandy P. Harrison, and I. Colin Prentice
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- 2019
48. Climate changes in interior semi-arid Spain from the last interglacial to the late Holocene
- Author
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Sandy P. Harrison, Graciela Gil-Romera, Penélope González-Sampériz, I. Colin Prentice, and Dongyang Wei
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010506 paleontology ,Climate change ,Seasonality ,medicine.disease ,01 natural sciences ,13. Climate action ,Evapotranspiration ,Interglacial ,Deglaciation ,medicine ,Environmental science ,Glacial period ,Precipitation ,Physical geography ,Holocene ,0105 earth and related environmental sciences - Abstract
The El Cañizar de Villarquemado sequence provides a palaeoenvironmental record from the western Mediterranean Basin spanning the interval from the last part of MIS6 to the late Holocene. The pollen and sedimentological records provide qualitative information about changes in temperature seasonality and moisture conditions. We use Weighted Averaging Partial Least-Squares (WA-PLS) regression to derive quantitative reconstructions of winter and summer temperature regimes from the pollen data, expressed in terms of the mean temperature of the coldest month (MTCO) and growing degree days above a baseline of 0 °C (GDD0) respectively. We also reconstruct a moisture index (MI), the ratio of annual precipitation to annual potential evapotranspiration, taking account of the effect of low CO2 on water use efficiency. We find a rapid summer warming at the transition to MIS5. Summers were cold during MIS4 and MIS2, but some intervals in MIS3 were characterized by summers as warm as the warmest phases of MIS5 or the Holocene. However, MIS3 was not significantly warmer in winter than other intervals, and there was a gradual decline in winter temperature from MIS4 through MIS3 to MIS2. The pronounced changes in temperature seasonality during MIS5 and MIS1 are consistent with changes in summer insolation. The ecophysiological effects of changing CO2 concentration through the glacial cycle has a significant impact on reconstructed MI. Conditions became progressively more humid during MIS5 and MIS4 was also relatively humid, while MIS3 was more arid. High MI values are reconstructed during the deglaciation and there was a pronounced increase in aridity during the Holocene. Changes in MI are anti-correlated with changes in GDD0, with increased MI during intervals of summer warming indicating a strong influence of temperature on evapotranspiration. Although our main focus here is on longterm changes in climate, the Villarquemado record also shows millennial-scale changes corresponding to Dansgaard-Oeschger cycles.
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- 2019
49. Drought impacts on terrestrial primary production underestimated by satellite monitoring
- Author
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Sonia I. Seneviratne, Benjamin D. Stocker, Jakob Zscheischler, Trevor F. Keenan, I. Colin Prentice, Josep Peñuelas, and AXA Research Fund
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010504 meteorology & atmospheric sciences ,Climate change ,010502 geochemistry & geophysics ,Photosynthesis ,Atmospheric sciences ,01 natural sciences ,USE EFFICIENCY ,MD Multidisciplinary ,NET PRIMARY PRODUCTION ,medicine ,Meteorology & Atmospheric Sciences ,Geosciences, Multidisciplinary ,WATER-STRESS ,Water content ,0105 earth and related environmental sciences ,2. Zero hunger ,Science & Technology ,CLIMATE-CHANGE ,Ecology ,PHOTOSYNTHESIS ,Water stress ,Direct effects ,Extreme events ,Primary production ,Geology ,GROSS PRIMARY PRODUCTION ,Carbon cycle ,Biogeochemistry ,15. Life on land ,FOREST ,ATMOSPHERIC DEMAND ,13. Climate action ,Physical Sciences ,RADIATION ,General Earth and Planetary Sciences ,Dryness ,Environmental science ,medicine.symptom ,CARBON UPTAKE - Abstract
Satellite retrievals of information about the Earth’s surface are widely used to monitor global terrestrial photosynthesis and primary production and to examine the ecological impacts of droughts. Methods for estimating photosynthesis from space commonly combine information on vegetation greenness, incoming radiation, temperature and atmospheric demand for water (vapour-pressure deficit), but do not account for the direct effects of low soil moisture. They instead rely on vapour-pressure deficit as a proxy for dryness, despite widespread evidence that soil moisture deficits have a direct impact on vegetation, independent of vapour-pressure deficit. Here, we use a globally distributed measurement network to assess the effect of soil moisture on photosynthesis, and identify a common bias in an ensemble of satellite-based estimates of photosynthesis that is governed by the magnitude of soil moisture effects on photosynthetic light-use efficiency. We develop methods to account for the influence of soil moisture and estimate that soil moisture effects reduce global annual photosynthesis by ~15%, increase interannual variability by more than 100% across 25% of the global vegetated land surface, and amplify the impacts of extreme events on primary production. These results demonstrate the importance of soil moisture effects for monitoring carbon-cycle variability and drought impacts on vegetation productivity from space. Soil moisture effects can substantially reduce photosynthesis and amplify the impacts of extreme events on primary production, potentially leading to biases in satellite-based estimates of photosynthesis, suggests an analysis of ground-based measurements.
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- 2019
- Full Text
- View/download PDF
50. Bridging Drought Experiment and Modeling: Representing the Differential Sensitivities of Leaf Gas Exchange to Drought
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Belinda E. Medlyn, Shuangxi Zhou, I. Colin Prentice, AXA Research Fund, and Commission of the European Communities
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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
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