Articles | Volume 20, issue 22
https://doi.org/10.5194/bg-20-4511-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-20-4511-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Leaf carbon and nitrogen stoichiometric variation along environmental gradients
Huiying Xu
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
Han Wang
CORRESPONDING AUTHOR
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
Iain Colin Prentice
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
Department of Life Sciences, Georgina Mace Centre for the Living Planet, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, SL5 7PY, UK
Sandy P. Harrison
Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
School of Archaeology, Geography and Environmental Sciences (SAGES), University of Reading, Reading, RG6 6AH, UK
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Luke Sweeney, Sandy P. Harrison, and Marc Vander Linden
Biogeosciences, 22, 4903–4922, https://doi.org/10.5194/bg-22-4903-2025, https://doi.org/10.5194/bg-22-4903-2025, 2025
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Changes in tree cover across Europe during the Holocene are reconstructed from fossil pollen data using a model developed with modern observations of tree cover and modern pollen assemblages. There is a rapid increase in tree cover after the last glacial period, with maximum cover during the mid-Holocene and a decline thereafter; the timing of the maximum and the speed of the increase and subsequent decrease vary regionally, likely reflecting differences in climate trajectories and human influence.
Joseph Ovwemuvwose, Ian Colin Prentice, and Heather Graven
EGUsphere, https://doi.org/10.5194/egusphere-2025-3785, https://doi.org/10.5194/egusphere-2025-3785, 2025
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This work examines the role of cropland representation and the treatment of photosynthetic pathways in the uncertainties in the carbon flux simulations in Earth System Models (ESMs). Our results show that reducing these uncertainties will require improvement of the representation of C3 and C4 crops and natural vegetation area coverage as well as the theories underpinning the simulation of their carbon uptake and storage processes.
Amin Hassan, Iain Colin Prentice, and Xu Liang
EGUsphere, https://doi.org/10.5194/egusphere-2025-622, https://doi.org/10.5194/egusphere-2025-622, 2025
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Evapotranspiration (ET) is the evaporation occurring from plants, soil, and water bodies. Separating these components is challenging due to the lack of measurements and uncertainty of existing ET partitioning methods. We propose a method that utilizes hydrological measurements such as streamflow to determine the ratio of transpiration (evaporation from plants) to evapotranspiration. The results provide a better understanding of plant-water interactions and new perspective on a challenging topic.
Kieran M. R. Hunt and Sandy P. Harrison
Clim. Past, 21, 1–26, https://doi.org/10.5194/cp-21-1-2025, https://doi.org/10.5194/cp-21-1-2025, 2025
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In this study, we train machine learning models on tree rings, speleothems, and instrumental rainfall to estimate seasonal monsoon rainfall over India over the last 500 years. Our models highlight multidecadal droughts in the mid-17th and 19th centuries, and we link these to historical famines. Using techniques from explainable AI (artificial intelligence), we show that our models use known relationships between local hydroclimate and the monsoon circulation.
Jierong Zhao, Boya Zhou, Sandy P. Harrison, and I. Colin Prentice
EGUsphere, https://doi.org/10.5194/egusphere-2024-3897, https://doi.org/10.5194/egusphere-2024-3897, 2025
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We used eco-evolutionary optimality modelling to examine how climate and CO2 impacted vegetation at the Last Glacial Maximum (LGM, 21,000 years ago) and the mid-Holocene (MH, 6,000 years ago). Low CO2 at the LGM was as important as climate in reducing tree cover and productivity, and increasing C4 plant abundance. Climate had positive effects on MH vegetation, but the low CO2 was a constraint on plant growth. These results show it is important to consider changing CO2 to model ecosystem changes.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
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Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Nikita Kaushal, Franziska A. Lechleitner, Micah Wilhelm, Khalil Azennoud, Janica C. Bühler, Kerstin Braun, Yassine Ait Brahim, Andy Baker, Yuval Burstyn, Laia Comas-Bru, Jens Fohlmeister, Yonaton Goldsmith, Sandy P. Harrison, István G. Hatvani, Kira Rehfeld, Magdalena Ritzau, Vanessa Skiba, Heather M. Stoll, József G. Szűcs, Péter Tanos, Pauline C. Treble, Vitor Azevedo, Jonathan L. Baker, Andrea Borsato, Sakonvan Chawchai, Andrea Columbu, Laura Endres, Jun Hu, Zoltán Kern, Alena Kimbrough, Koray Koç, Monika Markowska, Belen Martrat, Syed Masood Ahmad, Carole Nehme, Valdir Felipe Novello, Carlos Pérez-Mejías, Jiaoyang Ruan, Natasha Sekhon, Nitesh Sinha, Carol V. Tadros, Benjamin H. Tiger, Sophie Warken, Annabel Wolf, Haiwei Zhang, and SISAL Working Group members
Earth Syst. Sci. Data, 16, 1933–1963, https://doi.org/10.5194/essd-16-1933-2024, https://doi.org/10.5194/essd-16-1933-2024, 2024
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Speleothems are a popular, multi-proxy climate archive that provide regional to global insights into past hydroclimate trends with precise chronologies. We present an update to the SISAL (Speleothem Isotopes
Synthesis and AnaLysis) database, SISALv3, which, for the first time, contains speleothem trace element records, in addition to an update to the stable isotope records available in previous versions of the database, cumulatively providing data from 365 globally distributed sites.
Synthesis and AnaLysis) database, SISALv3, which, for the first time, contains speleothem trace element records, in addition to an update to the stable isotope records available in previous versions of the database, cumulatively providing data from 365 globally distributed sites.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Mengmeng Liu, Iain Colin Prentice, and Sandy P. Harrison
Clim. Past Discuss., https://doi.org/10.5194/cp-2024-12, https://doi.org/10.5194/cp-2024-12, 2024
Preprint under review for CP
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Dansgaard-Oeschger events were large and rapid warming events that occurred multiple times during the last ice age. We show that changes in the northern extratropics and the southern extratropics were anti-phased, with warming over most of the north and cooling in the south. The reconstructions do not provide evidence for a change in seasonality in temperature. However, they do indicate that warming was generally accompanied by wetter conditions and cooling by drier conditions.
Esmeralda Cruz-Silva, Sandy P. Harrison, I. Colin Prentice, Elena Marinova, Patrick J. Bartlein, Hans Renssen, and Yurui Zhang
Clim. Past, 19, 2093–2108, https://doi.org/10.5194/cp-19-2093-2023, https://doi.org/10.5194/cp-19-2093-2023, 2023
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We examined 71 pollen records (12.3 ka to present) in the eastern Mediterranean, reconstructing climate changes. Over 9000 years, winters gradually warmed due to orbital factors. Summer temperatures peaked at 4.5–5 ka, likely declining because of ice sheets. Moisture increased post-11 kyr, remaining high from 10–6 kyr before a slow decrease. Climate models face challenges in replicating moisture transport.
Olivia Haas, Iain Colin Prentice, and Sandy P. Harrison
Biogeosciences, 20, 3981–3995, https://doi.org/10.5194/bg-20-3981-2023, https://doi.org/10.5194/bg-20-3981-2023, 2023
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We quantify the impact of CO2 and climate on global patterns of burnt area, fire size, and intensity under Last Glacial Maximum (LGM) conditions using three climate scenarios. Climate change alone did not produce the observed LGM reduction in burnt area, but low CO2 did through reducing vegetation productivity. Fire intensity was sensitive to CO2 but strongly affected by changes in atmospheric dryness. Low CO2 caused smaller fires; climate had the opposite effect except in the driest scenario.
Giulia Mengoli, Sandy P. Harrison, and I. Colin Prentice
EGUsphere, https://doi.org/10.5194/egusphere-2023-1261, https://doi.org/10.5194/egusphere-2023-1261, 2023
Preprint archived
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Soil water availability affects plant carbon uptake by reducing leaf area and/or by closing stomata, which reduces its efficiency. We present a new formulation of how climatic dryness reduces both maximum carbon uptake and the soil-moisture threshold below which it declines further. This formulation illustrates how plants adapt their water conservation strategy to thrive in dry climates, and is step towards a better representation of soil-moisture effects in climate models.
Mengmeng Liu, Yicheng Shen, Penelope González-Sampériz, Graciela Gil-Romera, Cajo J. F. ter Braak, Iain Colin Prentice, and Sandy P. Harrison
Clim. Past, 19, 803–834, https://doi.org/10.5194/cp-19-803-2023, https://doi.org/10.5194/cp-19-803-2023, 2023
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We reconstructed the Holocene climates in the Iberian Peninsula using a large pollen data set and found that the west–east moisture gradient was much flatter than today. We also found that the winter was much colder, which can be expected from the low winter insolation during the Holocene. However, summer temperature did not follow the trend of summer insolation, instead, it was strongly correlated with moisture.
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, and Ning Dong
Earth Syst. Sci. Data, 14, 4077–4093, https://doi.org/10.5194/essd-14-4077-2022, https://doi.org/10.5194/essd-14-4077-2022, 2022
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Green leaves contain chlorophyll pigments that harvest light for photosynthesis and also emit chlorophyll fluorescence as a byproduct. Both chlorophyll pigments and fluorescence can be measured by Earth-orbiting satellite sensors. Here we demonstrate that leaf photosynthetic capacity can be reliably derived globally using these measurements. This new satellite-based information overcomes a bottleneck in global ecological research where such spatially explicit information is currently lacking.
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
Clim. Past, 18, 1189–1201, https://doi.org/10.5194/cp-18-1189-2022, https://doi.org/10.5194/cp-18-1189-2022, 2022
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We present a method to reconstruct burnt area using a relationship between pollen and charcoal abundances and the calibration of charcoal abundance using modern observations of burnt area. We use this method to reconstruct changes in burnt area over the past 12 000 years from sites in Iberia. We show that regional changes in burnt area reflect known changes in climate, with a high burnt area during warming intervals and low burnt area when the climate was cooler and/or wetter than today.
Sandy P. Harrison, Roberto Villegas-Diaz, Esmeralda Cruz-Silva, Daniel Gallagher, David Kesner, Paul Lincoln, Yicheng Shen, Luke Sweeney, Daniele Colombaroli, Adam Ali, Chéïma Barhoumi, Yves Bergeron, Tatiana Blyakharchuk, Přemysl Bobek, Richard Bradshaw, Jennifer L. Clear, Sambor Czerwiński, Anne-Laure Daniau, John Dodson, Kevin J. Edwards, Mary E. Edwards, Angelica Feurdean, David Foster, Konrad Gajewski, Mariusz Gałka, Michelle Garneau, Thomas Giesecke, Graciela Gil Romera, Martin P. Girardin, Dana Hoefer, Kangyou Huang, Jun Inoue, Eva Jamrichová, Nauris Jasiunas, Wenying Jiang, Gonzalo Jiménez-Moreno, Monika Karpińska-Kołaczek, Piotr Kołaczek, Niina Kuosmanen, Mariusz Lamentowicz, Martin Lavoie, Fang Li, Jianyong Li, Olga Lisitsyna, José Antonio López-Sáez, Reyes Luelmo-Lautenschlaeger, Gabriel Magnan, Eniko Katalin Magyari, Alekss Maksims, Katarzyna Marcisz, Elena Marinova, Jenn Marlon, Scott Mensing, Joanna Miroslaw-Grabowska, Wyatt Oswald, Sebastián Pérez-Díaz, Ramón Pérez-Obiol, Sanna Piilo, Anneli Poska, Xiaoguang Qin, Cécile C. Remy, Pierre J. H. Richard, Sakari Salonen, Naoko Sasaki, Hieke Schneider, William Shotyk, Migle Stancikaite, Dace Šteinberga, Normunds Stivrins, Hikaru Takahara, Zhihai Tan, Liva Trasune, Charles E. Umbanhowar, Minna Väliranta, Jüri Vassiljev, Xiayun Xiao, Qinghai Xu, Xin Xu, Edyta Zawisza, Yan Zhao, Zheng Zhou, and Jordan Paillard
Earth Syst. Sci. Data, 14, 1109–1124, https://doi.org/10.5194/essd-14-1109-2022, https://doi.org/10.5194/essd-14-1109-2022, 2022
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We provide a new global data set of charcoal preserved in sediments that can be used to examine how fire regimes have changed during past millennia and to investigate what caused these changes. The individual records have been standardised, and new age models have been constructed to allow better comparison across sites. The data set contains 1681 records from 1477 sites worldwide.
Alexander Kuhn-Régnier, Apostolos Voulgarakis, Peer Nowack, Matthias Forkel, I. Colin Prentice, and Sandy P. Harrison
Biogeosciences, 18, 3861–3879, https://doi.org/10.5194/bg-18-3861-2021, https://doi.org/10.5194/bg-18-3861-2021, 2021
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Along with current climate, vegetation, and human influences, long-term accumulation of biomass affects fires. Here, we find that including the influence of antecedent vegetation and moisture improves our ability to predict global burnt area. Additionally, the length of the preceding period which needs to be considered for accurate predictions varies across regions.
Sarah E. Parker, Sandy P. Harrison, Laia Comas-Bru, Nikita Kaushal, Allegra N. LeGrande, and Martin Werner
Clim. Past, 17, 1119–1138, https://doi.org/10.5194/cp-17-1119-2021, https://doi.org/10.5194/cp-17-1119-2021, 2021
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Regional trends in the oxygen isotope (δ18O) composition of stalagmites reflect several climate processes. We compare stalagmite δ18O records from monsoon regions and model simulations to identify the causes of δ18O variability over the last 12 000 years, and between glacial and interglacial states. Precipitation changes explain the glacial–interglacial δ18O changes in all monsoon regions; Holocene trends are due to a combination of precipitation, atmospheric circulation and temperature changes.
Masa Kageyama, Sandy P. Harrison, Marie-L. Kapsch, Marcus Lofverstrom, Juan M. Lora, Uwe Mikolajewicz, Sam Sherriff-Tadano, Tristan Vadsaria, Ayako Abe-Ouchi, Nathaelle Bouttes, Deepak Chandan, Lauren J. Gregoire, Ruza F. Ivanovic, Kenji Izumi, Allegra N. LeGrande, Fanny Lhardy, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, André Paul, W. Richard Peltier, Christopher J. Poulsen, Aurélien Quiquet, Didier M. Roche, Xiaoxu Shi, Jessica E. Tierney, Paul J. Valdes, Evgeny Volodin, and Jiang Zhu
Clim. Past, 17, 1065–1089, https://doi.org/10.5194/cp-17-1065-2021, https://doi.org/10.5194/cp-17-1065-2021, 2021
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The Last Glacial Maximum (LGM; ~21 000 years ago) is a major focus for evaluating how well climate models simulate climate changes as large as those expected in the future. Here, we compare the latest climate model (CMIP6-PMIP4) to the previous one (CMIP5-PMIP3) and to reconstructions. Large-scale climate features (e.g. land–sea contrast, polar amplification) are well captured by all models, while regional changes (e.g. winter extratropical cooling, precipitations) are still poorly represented.
Laia Comas-Bru, Kira Rehfeld, Carla Roesch, Sahar Amirnezhad-Mozhdehi, Sandy P. Harrison, Kamolphat Atsawawaranunt, Syed Masood Ahmad, Yassine Ait Brahim, Andy Baker, Matthew Bosomworth, Sebastian F. M. Breitenbach, Yuval Burstyn, Andrea Columbu, Michael Deininger, Attila Demény, Bronwyn Dixon, Jens Fohlmeister, István Gábor Hatvani, Jun Hu, Nikita Kaushal, Zoltán Kern, Inga Labuhn, Franziska A. Lechleitner, Andrew Lorrey, Belen Martrat, Valdir Felipe Novello, Jessica Oster, Carlos Pérez-Mejías, Denis Scholz, Nick Scroxton, Nitesh Sinha, Brittany Marie Ward, Sophie Warken, Haiwei Zhang, and SISAL Working Group members
Earth Syst. Sci. Data, 12, 2579–2606, https://doi.org/10.5194/essd-12-2579-2020, https://doi.org/10.5194/essd-12-2579-2020, 2020
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This paper presents an updated version of the SISAL (Speleothem Isotope Synthesis and Analysis) database. This new version contains isotopic data from 691 speleothem records from 294 cave sites and new age–depth models, including their uncertainties, for 512 speleothems.
Chris M. Brierley, Anni Zhao, Sandy P. Harrison, Pascale Braconnot, Charles J. R. Williams, David J. R. Thornalley, Xiaoxu Shi, Jean-Yves Peterschmitt, Rumi Ohgaito, Darrell S. Kaufman, Masa Kageyama, Julia C. Hargreaves, Michael P. Erb, Julien Emile-Geay, Roberta D'Agostino, Deepak Chandan, Matthieu Carré, Partrick J. Bartlein, Weipeng Zheng, Zhongshi Zhang, Qiong Zhang, Hu Yang, Evgeny M. Volodin, Robert A. Tomas, Cody Routson, W. Richard Peltier, Bette Otto-Bliesner, Polina A. Morozova, Nicholas P. McKay, Gerrit Lohmann, Allegra N. Legrande, Chuncheng Guo, Jian Cao, Esther Brady, James D. Annan, and Ayako Abe-Ouchi
Clim. Past, 16, 1847–1872, https://doi.org/10.5194/cp-16-1847-2020, https://doi.org/10.5194/cp-16-1847-2020, 2020
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This paper provides an initial exploration and comparison to climate reconstructions of the new climate model simulations of the mid-Holocene (6000 years ago). These use state-of-the-art models developed for CMIP6 and apply the same experimental set-up. The models capture several key aspects of the climate, but some persistent issues remain.
Cited articles
Ackerly, D. D. and Cornwell, W. K.: A trait-based approach to community assembly: partitioning of species trait values into within- and among-community components, Ecol. Lett., 10, 135–145, https://doi.org/10.1111/j.1461-0248.2006.01006.x, 2007.
Ahrens, C. W., Rymer, P. D., and Tissue, D. T.: Intra-specific trait variation remains hidden in the environment, New Phytol., 229, 1183–1185, https://doi.org/10.1111/nph.16959, 2021.
Anderegg, L. D. L.: Why can't we predict traits from the environment?, New Phytol., 237, 1998–2004, https://doi.org/10.1111/nph.18586, 2023.
Bartlett, M. K., Zhang, Y., Kreidler, N., Sun, S., Ardy, R., Cao, K., and Sack, L.: Global analysis of plasticity in turgor loss point, a key drought tolerance trait, Ecol. Lett., 17, 1580–1590, https://doi.org/10.1111/ele.12374, 2014.
Bernacchi, C. J., Singsaas, E. L., Pimentel, C., Portis Jr., A. R., and Long, S. P.: Improved temperature response functions for models of Rubisco-limited photosynthesis, Plant Cell Environ., 24, 253–259, 2001.
Bernacchi, C. J., Pimentel, C., and Long, S. P.: In vivo temperature response functions of parameters required to model RuBP-limited photosynthesis, Plant Cell Environ., 26, 1419–1430, https://doi.org/10.1046/j.0016-8025.2003.01050.x, 2003.
Bonan, G. B. and Doney, S. C.: Climate, ecosystems, and planetary futures: The challenge to predict life in Earth system models, Science, 359, aam8328, https://doi.org/10.1126/science.aam8328, 2018.
Boonman, C. C. F., Benitez-Lopez, A., Schipper, A. M., Thuiller, W., Anand, M., Cerabolini, B. E. L., Cornelissen, J. H. C., Gonzalez-Melo, A., Hattingh, W. N., Higuchi, P., Laughlin, D. C., Onipchenko, V. G., Penuelas, J., Poorter, L., Soudzilovskaia, N. A., Huijbregts, M. A. J., and Santini, L.: Assessing the reliability of predicted plant trait distributions at the global scale, Glob. Ecol. Biogeogr., 29, 1034–1051, https://doi.org/10.1111/geb.13086, 2020.
Breheny, P. and Burchett, W.: Visualization of regression models using visreg, R J., 9, 56–71, 2017.
Caldararu, S., Thum, T., Yu, L., and Zaehle, S.: Whole-plant optimality predicts changes in leaf nitrogen under variable CO2 and nutrient availability, New Phytol., 225, 2331–2346, https://doi.org/10.1111/nph.16327, 2020.
Cernusak, L. A., Ubierna, N., Winter, K., Holtum, J. A., Marshall, J. D., and Farquhar, G. D.: Environmental and physiological determinants of carbon isotope discrimination in terrestrial plants, New Phytol., 200, 950–965, https://doi.org/10.1111/nph.12423, 2013.
Charles-Edwards, D. A., Stutzel, H., Ferraris, R., and Beech, D. F.: An Analysis of Spatial Variation in the Nitrogen Content of Leaves from Different Horizons Within a Canopy, Ann. Bot., 60, 421–426, https://doi.org/10.1093/oxfordjournals.aob.a087463, 1987.
Chen, J.-L., Reynolds, J. F., Harley, P. C., and Tenhunen, J. D.: Coordination theory of leaf nitrogen distribution in a canopy, Oecologia, 93, 63–69, 1993.
Chen, Y., Han, W., Tang, L., Tang, Z., and Fang, J.: Leaf nitrogen and phosphorus concentrations of woody plants differ in responses to climate, soil and plant growth form, Ecography, 36, 178–184, https://doi.org/10.1111/j.1600-0587.2011.06833.x, 2013.
Chen, Z., Zhang, Y., Yuan, W., Zhu, S., Pan, R., Wan, X., and Liu, S.: Coordinated variation in stem and leaf functional traits of temperate broadleaf tree species in the isohydric–anisohydric spectrum, Tree Physiol., 41, 1601–1610, https://doi.org/10.1093/treephys/tpab028, 2021.
Cornelissen, J. H. C., Lavorel, S., Garnier, E., Díaz, S., Buchmann, N., Gurvich, D. E., Reich, P. B., Ter Steege, H., Morgan, H. D., Van Der Heijden, M. G. A., Pausas, J. G., and Poorter, H.: A handbook of protocols for standardised and easy measurement of plant functional traits worldwide, Austr. J. Bot., 51, 335–380, https://doi.org/10.1071/BT02124, 2003.
Cornwell, W. K., Wright, I. J., Turner, J., Maire, V., Barbour, M. M., Cernusak, L. A., Dawson, T., Ellsworth, D., Farquhar, G. D., Griffiths, H., Keitel, C., Knohl, A., Reich, P. B., Williams, D. G., Bhaskar, R., Cornelissen, J. H. C., Richards, A., Schmidt, S., Valladares, F., Körner, C., Schulze, E.-D., Buchmann, N., and Santiago, L. S.: Climate and soils together regulate photosynthetic carbon isotope discrimination within C3 plants worldwide, Glob. Ecol. Biogeogr., 27, 1056–1067, https://doi.org/10.1111/geb.12764, 2018.
De Kauwe, M. G., Lin, Y. S., Wright, I. J., Medlyn, B. E., Crous, K. Y., Ellsworth, D. S., Maire, V., Prentice, I. C., Atkin, O. K., Rogers, A., Niinemets, U., Serbin, S. P., Meir, P., Uddling, J., Togashi, H. F., Tarvainen, L., Weerasinghe, L. K., Evans, B. J., Ishida, F. Y., and Domingues, T. F.: A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis, New Phytol., 210, 1130–1144, https://doi.org/10.1111/nph.13815, 2016.
de Oliveira, A. C. P., Nunes, A., Rodrigues, R. G., and Branquinho, C.: The response of plant functional traits to aridity in a tropical dry forest, Sci. Total Environ., 747, 141177, https://doi.org/10.1016/j.scitotenv.2020.141177, 2020.
Delgado-Baquerizo, M., Eldridge, D. J., Maestre, F. T., Ochoa, V., Gozalo, B., Reich, P. B., and Singh, B. K.: Aridity Decouples Stoichiometry Across Multiple Trophic Levels in Terrestrial Ecosystems, Ecosystems, 21, 459–468, https://doi.org/10.1007/s10021-017-0161-9, 2017.
Dong, N., Prentice, I. C., Evans, B. J., Caddy-Retalic, S., Lowe, A. J., and Wright, I. J.: Leaf nitrogen from first principles: field evidence for adaptive variation with climate, Biogeosciences, 14, 481–495, https://doi.org/10.5194/bg-14-481-2017, 2017.
Dong, N., Prentice, I. C., Wright, I. J., Wang, H., Atkin, O. K., Bloomfield, K. J., Domingues, T. F., Gleason, S. M., Maire, V., Onoda, Y., Poorter, H., and Smith, N. G.: Leaf nitrogen from the perspective of optimal plant function, J. Ecol., 110, 2585–2602, https://doi.org/10.1111/1365-2745.13967, 2022.
Du, Z., Weng, E., Jiang, L., Luo, Y., Xia, J., and Zhou, X.: Carbon–nitrogen coupling under three schemes of model representation: a traceability analysis, Geosci. Model Dev., 11, 4399–4416, https://doi.org/10.5194/gmd-11-4399-2018, 2018.
Elser, J. J., Fagan, W. F., Kerkhoff, A. J., Swenson, N. G., and Enquist, B. J.: Biological stoichiometry of plant production: metabolism, scaling and ecological response to global change, New Phytol., 186, 593–608, https://doi.org/10.1111/j.1469-8137.2010.03214.x, 2010.
Fang, Z., Li, D.-D., Jiao, F., Yao, J., and Du, H.-T.: The Latitudinal Patterns of Leaf and Soil Stoichiometry in the Loess Plateau of China, Front. Plant Sci., 10, 85, https://doi.org/10.3389/fpls.2019.00085, 2019.
Farquhar, G. D., Ehleringer, J. R., and Hubick, K. T.: Carbon isotope discrimination and photosynthesis, Annu. Rev. Plant Biol., 40, 503–537, 1989.
Fernández-Martínez, M., Vicca, S., Janssens, I. A., Sardans, J., Luyssaert, S., Campioli, M., Chapin Iii, F. S., Ciais, P., Malhi, Y., Obersteiner, M., Papale, D., Piao, S. L., Reichstein, M., Rodà, F., and Peñuelas, J.: Nutrient availability as the key regulator of global forest carbon balance, Nat. Clim. Change, 4, 471–476, https://doi.org/10.1038/nclimate2177, 2014.
Field, C.: Allocating leaf nitrogen for the maximization of carbon gain: Leaf age as a control on the allocation program, Oecologia, 56, 341–347, https://doi.org/10.1007/BF00379710, 1983.
Fyllas, N. M., Patiño, S., Baker, T. R., Bielefeld Nardoto, G., Martinelli, L. A., Quesada, C. A., Paiva, R., Schwarz, M., Horna, V., Mercado, L. M., Santos, A., Arroyo, L., Jiménez, E. M., Luizão, F. J., Neill, D. A., Silva, N., Prieto, A., Rudas, A., Silviera, M., Vieira, I. C. G., Lopez-Gonzalez, G., Malhi, Y., Phillips, O. L., and Lloyd, J.: Basin-wide variations in foliar properties of Amazonian forest: phylogeny, soils and climate, Biogeosciences, 6, 2677–2708, https://doi.org/10.5194/bg-6-2677-2009, 2009.
Ghimire, B., Riley, W. J., Koven, C. D., Mu, M., and Randerson, J. T.: Representing leaf and root physiological traits in CLM improves global carbon and nitrogen cycling predictions, J. Adv. Model. Earth Sy., 8, 598–613, https://doi.org/10.1002/2015ms000538, 2016.
Ghimire, B., Riley, W. J., Koven, C. D., Kattge, J., Rogers, A., Reich, P. B., and Wright, I. J.: A global trait-based approach to estimate leaf nitrogen functional allocation from observations, Ecol. Appl.s, 27, 1421–1434, https://doi.org/10.1002/eap.1542, 2017.
Groemping, U.: Relative Importance for Linear Regression in R: The Package relaimpo, J. Stat. Softw., 17, 925–933, 2006.
Hadfield, J. D.: MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package, J. Stat. Softw., 33, 1–22, 2010.
Han, W., Fang, J., Guo, D., and Zhang, Y.: Leaf nitrogen and phosphorus stoichiometry across 753 terrestrial plant species in China, New Phytol., 168, 377–385, https://doi.org/10.1111/j.1469-8137.2005.01530.x, 2005.
Harrison, S. P., Cramer, W., Franklin, O., Prentice, I. C., Wang, H., Brannstrom, A., de Boer, H., Dieckmann, U., Joshi, J., Keenan, T. F., Lavergne, A., Manzoni, S., Mengoli, G., Morfopoulos, C., Penuelas, J., Pietsch, S., Rebel, K. T., Ryu, Y., Smith, N. G., Stocker, B. D., and Wright, I. J.: Eco-evolutionary optimality as a means to improve vegetation and land-surface models, New Phytol., 231, 2125–2141, https://doi.org/10.1111/nph.17558, 2021.
He, J. S., Fang, J., Wang, Z., Guo, D., Flynn, D. F., and Geng, Z.: Stoichiometry and large-scale patterns of leaf carbon and nitrogen in the grassland biomes of China, Oecologia, 149, 115–122, https://doi.org/10.1007/s00442-006-0425-0, 2006.
He, J. S., Wang, L., Flynn, D. F., Wang, X., Ma, W., and Fang, J.: Leaf nitrogen:phosphorus stoichiometry across Chinese grassland biomes, Oecologia, 155, 301–310, https://doi.org/10.1007/s00442-007-0912-y, 2008.
He, J. S., Wang, X., Schmid, B., Flynn, D. F., Li, X., Reich, P. B., and Fang, J.: Taxonomic identity, phylogeny, climate and soil fertility as drivers of leaf traits across Chinese grassland biomes, J. Plant Res., 123, 551–561, https://doi.org/10.1007/s10265-009-0294-9, 2010.
Hirose, T. and Werger, M. J. A.: Maximizing daily canopy photosynthesis with respect to the leaf nitrogen allocation pattern in the canopy, Oecologia, 72, 520–526, https://doi.org/10.1007/BF00378977, 1987.
Hoch, G. and Körner, C.: Global patterns of mobile carbon stores in trees at the high-elevation tree line, Global Ecol. Biogeogr., 21, 861–871, https://doi.org/10.1111/j.1466-8238.2011.00731.x, 2012.
Hutchinson, M. F. and Xu, T.: Anusplin Version 4.4 User Guide, Centre for Resource and Environment Studies, Canberra: Australian National University, http://fennerschool.anu.edu.au/files/anusplin44.pdf (last access: 21 August 2020), 2013.
Kikuzawa, K., Onoda, Y., Wright, I. J., and Reich, P. B.: Mechanisms underlying global temperature-related patterns in leaf longevity, Glob. Ecol. Biogeogr., 22, 982–993, https://doi.org/10.1111/geb.12042, 2013.
Körner, C.: The cold range limit of trees, Trend. Ecol. Evol., 36, 979–989, https://doi.org/10.1016/j.tree.2021.06.011, 2021.
Lawrence, D. M., Oleson, K. W., Flanner, M. G., Thornton, P. E., Swenson, S. C., Lawrence, P. J., Zeng, X., Yang, Z.-L., Levis, S., Sakaguchi, K., Bonan, G. B., and Slater, A. G.: Parameterization improvements and functional and structural advances in Version 4 of the Community Land Model, J. Adv. Model. Earth Sy., 3, M03001, https://doi.org/10.1029/2011ms000045, 2011.
Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C., Bonan, G., Collier, N., Ghimire, B., van Kampenhout, L., Kennedy, D., Kluzek, E., Lawrence, P. J., Li, F., Li, H., Lombardozzi, D., Riley, W. J., Sacks, W. J., Shi, M., Vertenstein, M., Wieder, W. R., Xu, C., Ali, A. A., Badger, A. M., Bisht, G., van den Broeke, M., Brunke, M. A., Burns, S. P., Buzan, J., Clark, M., Craig, A., Dahlin, K., Drewniak, B., Fisher, J. B., Flanner, M., Fox, A. M., Gentine, P., Hoffman, F., Keppel-Aleks, G., Knox, R., Kumar, S., Lenaerts, J., Leung, L. R., Lipscomb, W. H., Lu, Y., Pandey, A., Pelletier, J. D., Perket, J., Randerson, J. T., Ricciuto, D. M., Sanderson, B. M., Slater, A., Subin, Z. M., Tang, J., Thomas, R. Q., Val Martin, M., and Zeng, X.: The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty, J. Adv. Model. Earth Sy., 11, 4245–4287, https://doi.org/10.1029/2018MS001583, 2019.
Li, Y., He, W., Wu, J., Zhao, P., Chen, T., Zhu, L., Ouyang, L., Ni, G., and Hölscher, D.: Leaf stoichiometry is synergistically-driven by climate, site, soil characteristics and phylogeny in karst areas, Southwest China, Biogeochemistry, 155, 283–301, https://doi.org/10.1007/s10533-021-00826-3, 2021.
Lichstein, J. W.: Multiple regression on distance matrices: a multivariate spatial analysis tool, Plant Ecol., 188, 117–131, https://doi.org/10.1007/s11258-006-9126-3, 2006.
Liu, G., Ye, X., Huang, Z., Dong, M., Cornelissen, J. H. C., and Bello, F.: Leaf and root nutrient concentrations and stoichiometry along aridity and soil fertility gradients, J. Veg. Sci., 30, 291–300, https://doi.org/10.1111/jvs.12717, 2019.
Liu, H., Ye, Q., Simpson, K. J., Cui, E., and Xia, J.: Can evolutionary history predict plant plastic responses to climate change?, New Phytol., 235, 1260–1271, https://doi.org/10.1111/nph.18194, 2022.
Luong, J. C., Holl, K. D., and Loik, M. E.: Leaf traits and phylogeny explain plant survival and community dynamics in response to extreme drought in a restored coastal grassland, J. Appl. Ecol., 58, 1670–1680, https://doi.org/10.1111/1365-2664.13909, 2021.
Ma, S., He, F., Tian, D., Zou, D., Yan, Z., Yang, Y., Zhou, T., Huang, K., Shen, H., and Fang, J.: Variations and determinants of carbon content in plants: a global synthesis, Biogeosciences, 15, 693–702, https://doi.org/10.5194/bg-15-693-2018, 2018.
Medvigy, D., Wofsy, S. C., Munger, J. W., Hollinger, D. Y., and Moorcroft, P. R.: Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2, J. Geophys. Res., 114, G01002, https://doi.org/10.1029/2008jg000812, 2009.
Meloni, F., Lopes, N. P., and Varanda, E. M.: The relationship between leaf nitrogen, nitrogen metabolites and herbivory in two species of Nyctaginaceae from the Brazilian Cerrado, Environ. Exp. Bot., 75, 268–276, https://doi.org/10.1016/j.envexpbot.2011.07.010, 2012.
Meng, T. T., Wang, H., Harrison, S. P., Prentice, I. C., Ni, J., and Wang, G.: Responses of leaf traits to climatic gradients: adaptive variation versus compositional shifts, Biogeosciences, 12, 5339–5352, https://doi.org/10.5194/bg-12-5339-2015, 2015.
Meyerholt, J. and Zaehle, S.: The role of stoichiometric flexibility in modelling forest ecosystem responses to nitrogen fertilization, New Phytol., 208, 1042–1055, https://doi.org/10.1111/nph.13547, 2015.
Meyerholt, J., Sickel, K., and Zaehle, S.: Ensemble projections elucidate effects of uncertainty in terrestrial nitrogen limitation on future carbon uptake, Glob. Change Biol., 26, 3978–3996, https://doi.org/10.1111/gcb.15114, 2020.
Moran, E. V., Hartig, F., and Bell, D. M.: Intraspecific trait variation across scales: implications for understanding global change responses, Glob. Change Biol., 22, 137–150, https://doi.org/10.1111/gcb.13000, 2016.
Münkemüller, T., Lavergne, S., Bzeznik, B., Dray, S., Jombart, T., Schiffers, K., and Thuiller, W.: How to measure and test phylogenetic signal, Method. Ecol. Evol., 3, 743–756, https://doi.org/10.1111/j.2041-210X.2012.00196.x, 2012.
Nakagawa, S. and Schielzeth, H.: A general and simple method for obtaining R2 from generalized linear mixed-effects models, Method. Ecol. Evol., 4, 133–142, 2013.
Nakagawa, S., Johnson, P. C., and Schielzeth, H.: The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded, J. Roy. Soc. Int., 14, 20170213, https://doi.org/10.1098/rsif.2017.0213, 2017.
Niinemets, U., Keenan, T. F., and Hallik, L.: A worldwide analysis of within-canopy variations in leaf structural, chemical and physiological traits across plant functional types, New Phytol., 205, 973–993, https://doi.org/10.1111/nph.13096, 2015.
Niu, S., Song, L., Wang, J., Luo, Y., and Yu, G.: Dynamic carbon-nitrogen coupling under global change, Sci. China Life Sci., 66, 771–782, https://doi.org/10.1007/s11427-022-2245-y, 2023.
Ordoñez, J. C., Van Bodegom, P. M., Witte, J.-P. M., Wright, I. J., Reich, P. B., and Aerts, R.: A global study of relationships between leaf traits, climate and soil measures of nutrient fertility, Glob. Ecol. Biogeogr., 18, 137–149, https://doi.org/10.1111/j.1466-8238.2008.00441.x, 2009.
Paradis, E., Claude, J., and Strimmer, K.: APE: analyses of phylogenetics and evolution in R language, Bioinformatics, 20, 289–290, 2004.
Peng, Y., Bloomfield, K. J., and Prentice, I. C.: A theory of plant function helps to explain leaf-trait and productivity responses to elevation, New Phytol., 226, 1274–1284, https://doi.org/10.1111/nph.16447, 2020.
Prentice, I. C., Dong, N., Gleason, S. M., Maire, V., and Wright, I. J.: Balancing the costs of carbon gain and water transport: testing a new theoretical framework for plant functional ecology, Ecol. Lett., 17, 82–91, https://doi.org/10.1111/ele.12211, 2014.
Qian, H. and Jin, Y.: An updated megaphylogeny of plants, a tool for generating plant phylogenies and an analysis of phylogenetic community structure, J. Plant Ecol., 9, 233–239, https://doi.org/10.1093/jpe/rtv047, 2016.
R Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 2 September 2023), 2021.
Raggi, V.: Changes in free amino acids and osmotic adjustment in leaves of water-stressed bean, Physiol. Plantarum, 91, 427–434, https://doi.org/10.1111/j.1399-3054.1994.tb02970.x, 1994.
Reich, P. B.: Global biogeography of plant chemistry: filling in the blanks, New Phytol., 168, 263–266, https://doi.org/10.1111/j.1469-8137.2005.01562.x, 2005.
Reich, P. B. and Oleksyn, J.: Global patterns of plant leaf N and P in relation to temperature and latitude, P. Natl. Acad. Sci. USA, 101, 11001–11006, https://doi.org/10.1073/pnas.0403588101, 2004.
Revell, L. J.: phytools: an R package for phylogenetic comparative biology (and other things), Method. Ecol. Evol., 3, 217–223, 2012.
Sack, L. and Scoffoni, C.: Leaf venation: structure, function, development, evolution, ecology and applications in the past, present and future, New Phytol., 198, 983–1000, https://doi.org/10.1111/nph.12253, 2013.
Sardans, J. and Penuelas, J.: Climate and taxonomy underlie different elemental concentrations and stoichiometries of forest species: the optimum “biogeochemical niche”, Plant Ecol., 215, 441–455, https://doi.org/10.1007/s11258-014-0314-2, 2014.
Sardans, J., Vallicrosa, H., Zuccarini, P., Farre-Armengol, G., Fernandez-Martinez, M., Peguero, G., Gargallo-Garriga, A., Ciais, P., Janssens, I. A., Obersteiner, M., Richter, A., and Penuelas, J.: Empirical support for the biogeochemical niche hypothesis in forest trees, Nat. Ecol. Evol., 5, 184–194, https://doi.org/10.1038/s41559-020-01348-1, 2021.
Scoffoni, C., Rawls, M., McKown, A., Cochard, H., and Sack, L.: Decline of leaf hydraulic conductance with dehydration: relationship to leaf size and venation architecture, Plant Physiol., 156, 832–843, https://doi.org/10.1104/pp.111.173856, 2011.
Shangguan, W., Dai, Y., Liu, B., Zhu, A., Duan, Q., Wu, L., Ji, D., Ye, A., Yuan, H., Zhang, Q., Chen, D., Chen, M., Chu, J., Dou, Y., Guo, J., Li, H., Li, J., Liang, L., Liang, X., Liu, H., Liu, S., Miao, C., and Zhang, Y.: A China data set of soil properties for land surface modeling, J. Adv. Model. Earth Sy., 5, 212–224, https://doi.org/10.1002/jame.20026, 2013.
Sistla, S. A. and Schimel, J. P.: Stoichiometric flexibility as a regulator of carbon and nutrient cycling in terrestrial ecosystems under change, New Phytol., 196, 68–78, https://doi.org/10.1111/j.1469-8137.2012.04234.x, 2012.
Smith, B., Wårlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J., and Zaehle, S.: Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model, Biogeosciences, 11, 2027–2054, https://doi.org/10.5194/bg-11-2027-2014, 2014.
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.: Global photosynthetic capacity is optimized to the environment, Ecol. Lett., 22, 506–517, https://doi.org/10.1111/ele.13210, 2019.
Tang, Z., Xu, W., Zhou, G., Bai, Y., Li, J., Tang, X., Chen, D., Liu, Q., Ma, W., Xiong, G., He, H., He, N., Guo, Y., Guo, Q., Zhu, J., Han, W., Hu, H., Fang, J., and Xie, Z.: Patterns of plant carbon, nitrogen, and phosphorus concentration in relation to productivity in China's terrestrial ecosystems, P. Natl. Acad. Sci. USA, 115, 4033–4038, https://doi.org/10.1073/pnas.1700295114, 2018.
Terrer, C., Jackson, R. B., Prentice, I. C., Keenan, T. F., Kaiser, C., Vicca, S., Fisher, J. B., Reich, P. B., Stocker, B. D., Hungate, B. A., Peñuelas, J., McCallum, I., Soudzilovskaia, N. A., Cernusak, L. A., Talhelm, A. F., Van Sundert, K., Piao, S., Newton, P. C. D., Hovenden, M. J., Blumenthal, D. M., Liu, Y. Y., Müller, C., Winter, K., Field, C. B., Viechtbauer, W., Van Lissa, C. J., Hoosbeek, M. R., Watanabe, M., Koike, T., Leshyk, V. O., Polley, H. W., and Franklin, O.: Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass, Nat. Clim. Change, 9, 684–689, https://doi.org/10.1038/s41558-019-0545-2, 2019.
Vallicrosa, H., Sardans, J., Maspons, J., Zuccarini, P., Fernandez-Martinez, M., Bauters, M., Goll, D. S., Ciais, P., Obersteiner, M., Janssens, I. A., and Penuelas, J.: Global maps and factors driving forest foliar elemental composition: the importance of evolutionary history, New Phytol., 233, 169–181, https://doi.org/10.1111/nph.17771, 2021.
Violle, C., Enquist, B. J., McGill, B. J., Jiang, L., Albert, C. H., Hulshof, C., Jung, V., and Messier, J.: The return of the variance: intraspecific variability in community ecology, Trend. Ecol. Evol., 27, 244–252, https://doi.org/10.1016/j.tree.2011.11.014, 2012.
Wang, H., Prentice, I. C., Keenan, T. F., Davis, T. W., Wright, I. J., Cornwell, W. K., Evans, B. J., and Peng, C.: Towards a universal model for carbon dioxide uptake by plants, Nat. Plant., 3, 734–741, https://doi.org/10.1038/s41477-017-0006-8, 2017.
Wang, H., Harrison, S. P., Prentice, I. C., Yang, Y., Bai, F., Togashi, H. F., Wang, M., Zhou, S., and Ni, J.: The China plant trait database: Toward a comprehensive regional compilation of functional traits for land plants, Ecology, 99, 500–500, https://doi.org/10.1002/ecy.2091, 2018.
Wang, H., Harrison, S. P., Li, M., Prentice, I. C., Qiao, S., Wang, R., Xu, H., Mengoli, G., Peng, Y., and Yang, Y.: The China plant trait database version 2, Sci. Data, 9, 769, https://doi.org/10.1038/s41597-022-01884-4, 2022 (data available at https://figshare.com/articles/dataset/The_China_Plant_Trait_Database_Version_2_0/19448219, last access: 5 March 2022).
Wang, H., Harrison, S. P., Li, M., Prentice, I. C., Qiao, S., Wang, R., Xu, H., Mengoli, G., Peng, Y., and Yang, Y.: The China plant trait database version 2, Sci. Data, 9, 769, https://doi.org/10.1038/s41597-022-01884-4, 2022.
Wang, H., Prentice, I. C., Wright, I. J., Warton, D. I., Qiao, S., Xu, X., Zhou, J., Kikuzawa, K., and Stenseth, N. C.: Leaf economics fundamentals explained by optimality principles, Sci. Adv., 9, eadd5667, https://doi.org/10.1126/sciadv.add5667, 2023.
Wang, Y. P., Law, R. M., and Pak, B.: A global model of carbon, nitrogen and phosphorus cycles for the terrestrial biosphere, Biogeosciences, 7, 2261–2282, https://doi.org/10.5194/bg-7-2261-2010, 2010.
Weih, M. and Karlsson, P. S.: Growth response of Mountain birch to air and soil temperature: is increasing leaf-nitrogen content an acclimation to lower air temperature?, New Phytol., 150, 147–155, https://doi.org/10.1046/j.1469-8137.2001.00078.x, 2001.
Westerband, A. C., Funk, J. L., and Barton, K. E.: Intraspecific trait variation in plants: a renewed focus on its role in ecological processes, Ann. Bot., 127, 397–410, https://doi.org/10.1093/aob/mcab011, 2021.
Westoby, M., Leishman, M. R., and Lord, J. M.: On misinterpreting thephylogenetic correction', J. Ecol., 83, 531–534, 1995.
Wiltshire, A. J., Burke, E. J., Chadburn, S. E., Jones, C. D., Cox, P. M., Davies-Barnard, T., Friedlingstein, P., Harper, A. B., Liddicoat, S., Sitch, S., and Zaehle, S.: JULES-CN: a coupled terrestrial carbon–nitrogen scheme (JULES vn5.1), Geosci. Model Dev., 14, 2161–2186, https://doi.org/10.5194/gmd-14-2161-2021, 2021.
Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z., Bongers, F. J. J. M., Cavenderbares, J., Chapin, T., Cornelissen, J. H. C., and Diemer, M.: The worldwide leaf economics spectrum, Nature, 428, 821–827, 2004.
Xing, K., Niinemets, Ü., Rengel, Z., Onoda, Y., Xia, J., Chen, H. Y. H., Zhao, M., Han, W., and Li, H.: Global patterns of leaf construction traits and their covariation along climate and soil environmental gradients, New Phytol., 232, 1648–1660, https://doi.org/10.1111/nph.17686, 2021.
Xiong, J., Dong, L., Lu, J., Hu, W., Gong, H., Xie, S., Zhao, D., Zhang, Y., Wang, X., Deng, Y., Ran, J., Niklas, K. J., Degen, A., and Deng, J.: Variation in plant carbon, nitrogen and phosphorus contents across the drylands of China, Funct. Ecol., 36, 174–186, https://doi.org/10.1111/1365-2435.13937, 2021.
Xu, H., Wang, H., Prentice, I. C., Harrison, S. P., Wang, G., and Sun, X.: Predictability of leaf traits with climate and elevation: a case study in Gongga Mountain, China, Tree Physiol., 41, 1336–1352, https://doi.org/10.1093/treephys/tpab003, 2021.
Yang, X., Chi, X., Ji, C., Liu, H., Ma, W., Mohhammat, A., Shi, Z., Wang, X., Yu, S., Yue, M., and Tang, Z.: Variations of leaf N and P concentrations in shrubland biomes across northern China: phylogeny, climate, and soil, Biogeosciences, 13, 4429–4438, https://doi.org/10.5194/bg-13-4429-2016, 2016.
Yao, G. Q., Nie, Z. F., Turner, N. C., Li, F. M., Gao, T. P., Fang, X. W., and Scoffoni, C.: Combined high leaf hydraulic safety and efficiency provides drought tolerance in Caragana species adapted to low mean annual precipitation, New Phytol., 229, 230–244, https://doi.org/10.1111/nph.16845, 2021.
Yu, G., Smith, D. K., Zhu, H., Guan, Y., and Lam, T. T. Y.: ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data, Method. Ecol. Evol., 8, 28–36, 2017.
Zaehle, S., Medlyn, B. E., De Kauwe, M. G., Walker, A. P., Dietze, M. C., Hickler, T., Luo, Y., Wang, Y. P., El-Masri, B., Thornton, P., Jain, A., Wang, S., Warlind, D., Weng, E., Parton, W., Iversen, C. M., Gallet-Budynek, A., McCarthy, H., Finzi, A., Hanson, P. J., Prentice, I. C., Oren, R., and Norby, R. J.: Evaluation of 11 terrestrial carbon-nitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment studies, New Phytol., 202, 803–822, https://doi.org/10.1111/nph.12697, 2014.
Zhang, J., Zhao, N., Liu, C., Yang, H., Li, M., Yu, G., Wilcox, K., Yu, Q., He, N., and Niu, S.: C:N:P stoichiometry in China's forests: From organs to ecosystems, Funct. Ecol., 32, 50–60, https://doi.org/10.1111/1365-2435.12979, 2017.
Zhang, J., He, N., Liu, C., Xu, L., Chen, Z., Li, Y., Wang, R., Yu, G., Sun, W., Xiao, C., Chen, H. Y. H., and Reich, P. B.: Variation and evolution of C:N ratio among different organs enable plants to adapt to N-limited environments, Glob. Change Biol., 26, 2534–2543, https://doi.org/10.1111/gcb.14973, 2019.
Zhang, S.-B., Zhang, J.-L., Slik, J. W. F., and Cao, K.-F.: Leaf element concentrations of terrestrial plants across China are influenced by taxonomy and the environment, Glob. Ecol. Biogeogr., 21, 809–818, https://doi.org/10.1111/j.1466-8238.2011.00729.x, 2012.
Zhao, W., Reich, P. B., Yu, Q., Zhao, N., Yin, C., Zhao, C., Li, D., Hu, J., Li, T., Yin, H., and Liu, Q.: Shrub type dominates the vertical distribution of leaf stoichiometry across an extensive altitudinal gradient, Biogeosciences, 15, 2033–2053, https://doi.org/10.5194/bg-15-2033-2018, 2018.
Short summary
Leaf carbon (C) and nitrogen (N) are crucial elements in leaf construction and physiological processes. This study reconciled the roles of phylogeny, species identity, and climate in stoichiometric traits at individual and community levels. The variations in community-level leaf N and C : N ratio were captured by optimality-based models using climate data. Our results provide an approach to improve the representation of leaf stoichiometry in vegetation models to better couple N with C cycling.
Leaf carbon (C) and nitrogen (N) are crucial elements in leaf construction and physiological...
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