Articles | Volume 21, issue 11
https://doi.org/10.5194/bg-21-2731-2024
© Author(s) 2024. 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-21-2731-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
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11 Jun 2024
Research article | Highlight paper |
| 11 Jun 2024
| 11 Jun 2024
The effect of temperature on photosystem II efficiency across plant functional types and climate
Patrick Neri
Hydrology and Atmospheric Sciences Department, University of Arizona, Tucson, AZ 85721, USA
Lianhong Gu
Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Hydrology and Atmospheric Sciences Department, University of Arizona, Tucson, AZ 85721, USA
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Christian Mark Garcia Salvador, Jeffrey D. Wood, Emma Grace Cochran, Hunter A. Seubert, Bella D. Kamplain, Sam S. Overby, Kevin R. Birdwell, Lianhong Gu, and Melanie A. Mayes
EGUsphere, https://doi.org/10.5194/egusphere-2024-1808, https://doi.org/10.5194/egusphere-2024-1808, 2024
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Critical volatile organic compounds were continuously measured in a temperate deciduous and juniper forest in the midwestern US using PTR-ToF-MS. The forest included several sources of biogenic compounds and was influenced by short- and long-range transport of anthropogenic emissions. Extreme heat and wildfire emissions impacted the atmospheric conditions of the forest during the field measurement; such emissions are vital phenomena that provide insights into future climate.
Junyi Liang, Gangsheng Wang, Daniel M. Ricciuto, Lianhong Gu, Paul J. Hanson, Jeffrey D. Wood, and Melanie A. Mayes
Geosci. Model Dev., 12, 1601–1612, https://doi.org/10.5194/gmd-12-1601-2019, https://doi.org/10.5194/gmd-12-1601-2019, 2019
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Soil respiration, the second largest carbon fluxes between the atmosphere and land, is not well represented in global land models. In this study, using long-term observations at a temperate forest, we identified a solution for using better soil water potential simulations to improve predictions of soil respiration in the E3SM land model. In addition, parameter calibration further improved model performance.
Anthony P. Walker, Ming Ye, Dan Lu, Martin G. De Kauwe, Lianhong Gu, Belinda E. Medlyn, Alistair Rogers, and Shawn P. Serbin
Geosci. Model Dev., 11, 3159–3185, https://doi.org/10.5194/gmd-11-3159-2018, https://doi.org/10.5194/gmd-11-3159-2018, 2018
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Large uncertainty is inherent in model predictions due to imperfect knowledge of how to describe the processes that a model is intended to represent. Yet methods to quantify and evaluate this model hypothesis uncertainty are limited. To address this, the multi-assumption architecture and testbed (MAAT) automates the generation of all possible models by combining multiple representations of multiple processes. MAAT provides a formal framework for quantification of model hypothesis uncertainty.
Paul J. Hanson, Jeffery S. Riggs, W. Robert Nettles, Jana R. Phillips, Misha B. Krassovski, Leslie A. Hook, Lianhong Gu, Andrew D. Richardson, Donald M. Aubrecht, Daniel M. Ricciuto, Jeffrey M. Warren, and Charlotte Barbier
Biogeosciences, 14, 861–883, https://doi.org/10.5194/bg-14-861-2017, https://doi.org/10.5194/bg-14-861-2017, 2017
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This paper describes operational methods to achieve whole-ecosystem warming (WEW) for tall-stature, high-carbon, boreal forest peatlands. The methods enable scientists to study immediate and longer-term (1 decade) responses of organisms (microbes to trees) and ecosystem functions (carbon, water and nutrient cycles). The WEW technology allows researchers to have a plausible glimpse of future environmental conditions for study that are not available in the current observational record.
Jinxin Zhang, Lianhong Gu, Jingbo Zhang, Rina Wu, Feng Wang, Guanghui Lin, Bo Wu, Qi Lu, and Ping Meng
Biogeosciences, 14, 131–144, https://doi.org/10.5194/bg-14-131-2017, https://doi.org/10.5194/bg-14-131-2017, 2017
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Plant nitrogen (N) isotope composition is an indicator of N cycling. How N isotopes are distributed within plants is not well understood. We found intra-plant variations in N isotopes were related to organ N and phosphorous (P) contents and predicted by the N–P interaction. We hypothesized that plant N volatilization, resorption and remobilization of N and P from senescing leaves, and mixing of the re-translocated foliar N and P, are responsible for the observed intra-plant N isotope variations.
J. Zhang, L. Gu, J. Zhang, R. Wu, F. Wang, G. Lin, B. Wu, Q. Lu, and P. Meng
Biogeosciences Discuss., https://doi.org/10.5194/bgd-12-18769-2015, https://doi.org/10.5194/bgd-12-18769-2015, 2015
Revised manuscript not accepted
G. Wohlfahrt, C. Amelynck, C. Ammann, A. Arneth, I. Bamberger, A. H. Goldstein, L. Gu, A. Guenther, A. Hansel, B. Heinesch, T. Holst, L. Hörtnagl, T. Karl, Q. Laffineur, A. Neftel, K. McKinney, J. W. Munger, S. G. Pallardy, G. W. Schade, R. Seco, and N. Schoon
Atmos. Chem. Phys., 15, 7413–7427, https://doi.org/10.5194/acp-15-7413-2015, https://doi.org/10.5194/acp-15-7413-2015, 2015
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Methanol is the second most abundant volatile organic compound in the troposphere and plays a significant role in atmospheric chemistry. While there is consensus about the dominant role of plants as the major source and the reaction with OH as the major sink, global methanol budgets diverge considerably in terms of source/sink estimates. Here we present micrometeorological methanol flux data from eight sites in order to provide a first cross-site synthesis of the terrestrial methanol exchange.
L. Gu, S. G. Pallardy, K. P. Hosman, and Y. Sun
Biogeosciences, 12, 2831–2845, https://doi.org/10.5194/bg-12-2831-2015, https://doi.org/10.5194/bg-12-2831-2015, 2015
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Co-occurring tree species with varying physiologies were continuously monitored for mortality with concurrent observations of key physiological and environmental variables for a decade in a central US forest. New predictors of drought-induced mortality were developed. Time-delayed mortality was shown to be nonlinearly related to drought intensity and species’ capacities in regulating their internal hydraulic status, with elevated risk associated with extreme isohydric and anisohydric behaviors.
J. Zhang, L. Gu, F. Bao, Y. Cao, Y. Hao, J. He, J. Li, Y. Li, Y. Ren, F. Wang, R. Wu, B. Yao, Y. Zhao, G. Lin, B. Wu, Q. Lu, and P. Meng
Biogeosciences, 12, 15–27, https://doi.org/10.5194/bg-12-15-2015, https://doi.org/10.5194/bg-12-15-2015, 2015
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Biogeosciences, 21, 5745–5771, https://doi.org/10.5194/bg-21-5745-2024, https://doi.org/10.5194/bg-21-5745-2024, 2024
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Drainage of boreal peatlands strongly influences soil methane fluxes, with important implications for climatic impacts. Here we simulate methane fluxes in forestry-drained and restored peatlands during the 21st century. We found that restoration turned peatlands into a source of methane, but the magnitude varied regionally. In forests, changes in the water table level influenced methane fluxes, and in general, the sink was weaker under rotational forestry compared to continuous cover forestry.
Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler
Biogeosciences, 21, 5539–5560, https://doi.org/10.5194/bg-21-5539-2024, https://doi.org/10.5194/bg-21-5539-2024, 2024
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Climate change is causing an increase in extreme wildfires in Europe, but drivers of fire are not well understood, especially across different land cover types. We used statistical models with satellite data, climate data, and socioeconomic data to determine what affects burning in cropland and non-cropland areas of Europe. We found different drivers of burning in cropland burning vs. non-cropland to the point that some variables, e.g. population density, had the complete opposite effects.
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Biogeosciences, 21, 5321–5360, https://doi.org/10.5194/bg-21-5321-2024, https://doi.org/10.5194/bg-21-5321-2024, 2024
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This study investigates present-day carbon cycle variables in CMIP5 and CMIP6 simulations. Overall, CMIP6 models perform better but also show many remaining biases. A significant improvement in the simulation of photosynthesis in models with a nitrogen cycle is found, with only small differences between emission- and concentration-based simulations. Thus, we recommend using emission-driven simulations in CMIP7 by default and including the nitrogen cycle in all future carbon cycle models.
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Plants at the land surface mediate between soil and the atmosphere regarding water and carbon transport. Since plant growth is a dynamic process, models need to consider these dynamics. Two models that predict water and carbon fluxes by considering plant temporal evolution were tested against observational data. Currently, dynamizing plants in these models did not enhance their representativeness, which is caused by a mismatch between implemented physical relations and observable connections.
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Biogeosciences, 21, 5173–5183, https://doi.org/10.5194/bg-21-5173-2024, https://doi.org/10.5194/bg-21-5173-2024, 2024
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Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Using machine learning, we develop and compare predictive relationships in observations (Obs) and ESMs. We find different relationships between environmental factors and SOC stocks in Obs and ESMs. SOC prediction in ESMs may be improved by representing the functional relationships of environmental controllers in a way consistent with observations.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
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The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Xin Chen, Tiexi Chen, Xiaodong Li, Yuanfang Chai, Shengjie Zhou, Renjie Guo, and Jie Dai
Biogeosciences, 21, 4285–4300, https://doi.org/10.5194/bg-21-4285-2024, https://doi.org/10.5194/bg-21-4285-2024, 2024
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We provide an ensemble-model-based GPP dataset (ERF_GPP) that explains 85.1 % of the monthly variation in GPP across 170 sites, which is higher than other GPP estimate models. In addition, ERF_GPP improves the phenomenon of “high-value underestimation and low-value overestimation” in GPP estimation to some extent. Overall, ERF_GPP provides a more reliable estimate of global GPP and will facilitate further development of carbon cycle research.
Reza Kusuma Nurrohman, Tomomichi Kato, Hideki Ninomiya, Lea Végh, Nicolas Delbart, Tatsuya Miyauchi, Hisashi Sato, Tomohiro Shiraishi, and Ryuichi Hirata
Biogeosciences, 21, 4195–4227, https://doi.org/10.5194/bg-21-4195-2024, https://doi.org/10.5194/bg-21-4195-2024, 2024
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SPITFIRE (SPread and InTensity of FIRE) was integrated into a spatially explicit individual-based dynamic global vegetation model to improve the accuracy of depicting Siberian forest fire frequency, intensity, and extent. Fires showed increased greenhouse gas and aerosol emissions in 2006–2100 for Representative Concentration Pathways. This study contributes to understanding fire dynamics, land ecosystem–climate interactions, and global material cycles under the threat of escalating fires.
Stefano Manzoni and M. Francesca Cotrufo
Biogeosciences, 21, 4077–4098, https://doi.org/10.5194/bg-21-4077-2024, https://doi.org/10.5194/bg-21-4077-2024, 2024
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Organic carbon and nitrogen are stabilized in soils via microbial assimilation and stabilization of necromass (in vivo pathway) or via adsorption of the products of extracellular decomposition (ex vivo pathway). Here we use a diagnostic model to quantify which stabilization pathway is prevalent using data on residue-derived carbon and nitrogen incorporation in mineral-associated organic matter. We find that the in vivo pathway is dominant in fine-textured soils with low organic matter content.
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
Biogeosciences, 21, 3735–3760, https://doi.org/10.5194/bg-21-3735-2024, https://doi.org/10.5194/bg-21-3735-2024, 2024
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Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across ecosystems with the Biosphere-atmosphere Exchange Process Simulator (BEPS), which was developed for simulating the canopy COS uptake under its state-of-the-art two-leaf modeling framework. Our results showcased the efficacy of COS in improving model prediction and reducing prediction uncertainty of GPP and enhanced insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Moritz Laub, Magdalena Necpalova, Marijn Van de Broek, Marc Corbeels, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Rebecca Yegon, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
Biogeosciences, 21, 3691–3716, https://doi.org/10.5194/bg-21-3691-2024, https://doi.org/10.5194/bg-21-3691-2024, 2024
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We used the DayCent model to assess the potential impact of integrated soil fertility management (ISFM) on maize production, soil fertility, and greenhouse gas emission in Kenya. After adjustments, DayCent represented measured mean yields and soil carbon stock changes well and N2O emissions acceptably. Our results showed that soil fertility losses could be reduced but not completely eliminated with ISFM and that, while N2O emissions increased with ISFM, emissions per kilogram yield decreased.
Hazel Cathcart, Julian Aherne, Michael D. Moran, Verica Savic-Jovcic, Paul A. Makar, and Amanda Cole
EGUsphere, https://doi.org/10.5194/egusphere-2024-2371, https://doi.org/10.5194/egusphere-2024-2371, 2024
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Deposition from sulfur and nitrogen pollution can harm ecosystems, and recovery from this type of pollution can take decades or longer. To identify risk to Canadian soils, we created maps showing sensitivity to sulfur and nitrogen pollution. Results show that some ecosystems are at risk from acid and nutrient nitrogen deposition; 10 % of protected areas are receiving acid deposition beyond their damage threshold and 70 % may be receiving nitrogen deposition that could cause biodiversity loss.
Erik Schwarz, Samia Ghersheen, Salim Belyazid, and Stefano Manzoni
Biogeosciences, 21, 3441–3461, https://doi.org/10.5194/bg-21-3441-2024, https://doi.org/10.5194/bg-21-3441-2024, 2024
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The occurrence of unstable equilibrium points (EPs) could impede the applicability of microbial-explicit soil organic carbon models. For archetypal model versions we identify when instability can occur and describe mathematical conditions to avoid such unstable EPs. We discuss implications for further model development, highlighting the important role of considering basic ecological principles to ensure biologically meaningful models.
Sian Kou-Giesbrecht, Vivek K. Arora, Christian Seiler, and Libo Wang
Biogeosciences, 21, 3339–3371, https://doi.org/10.5194/bg-21-3339-2024, https://doi.org/10.5194/bg-21-3339-2024, 2024
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Terrestrial biosphere models can either prescribe the geographical distribution of biomes or simulate them dynamically, capturing climate-change-driven biome shifts. We isolate and examine the differences between these different land cover implementations. We find that the simulated terrestrial carbon sink at the end of the 21st century is twice as large in simulations with dynamic land cover than in simulations with prescribed land cover due to important range shifts in the Arctic and Amazon.
Elizabeth S. Duan, Luciana Chavez Rodriguez, Nicole Hemming-Schroeder, Baptiste Wijas, Habacuc Flores-Moreno, Alexander W. Cheesman, Lucas A. Cernusak, Michael J. Liddell, Paul Eggleton, Amy E. Zanne, and Steven D. Allison
Biogeosciences, 21, 3321–3338, https://doi.org/10.5194/bg-21-3321-2024, https://doi.org/10.5194/bg-21-3321-2024, 2024
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Understanding the link between climate and carbon fluxes is crucial for predicting how climate change will impact carbon sinks. We estimated carbon dioxide (CO2) fluxes from deadwood in tropical Australia using wood moisture content and temperature. Our model predicted that the majority of deadwood carbon is released as CO2, except when termite activity is detected. Future models should also incorporate wood traits, like species and chemical composition, to better predict fluxes.
Daniel Nadal-Sala, Rüdiger Grote, David Kraus, Uri Hochberg, Tamir Klein, Yael Wagner, Fedor Tatarinov, Dan Yakir, and Nadine K. Ruehr
Biogeosciences, 21, 2973–2994, https://doi.org/10.5194/bg-21-2973-2024, https://doi.org/10.5194/bg-21-2973-2024, 2024
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A hydraulic model approach is presented that can be added to any physiologically based ecosystem model. Simulated plant water potential triggers stomatal closure, photosynthesis decline, root–soil resistance increases, and sapwood and foliage senescence. The model has been evaluated at an extremely dry site stocked with Aleppo pine and was able to represent gas exchange, soil water content, and plant water potential. The model also responded realistically regarding leaf senescence.
Liyuan He, Jorge L. Mazza Rodrigues, Melanie A. Mayes, Chun-Ta Lai, David A. Lipson, and Xiaofeng Xu
Biogeosciences, 21, 2313–2333, https://doi.org/10.5194/bg-21-2313-2024, https://doi.org/10.5194/bg-21-2313-2024, 2024
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Soil microbes are the driving engine for biogeochemical cycles of carbon and nutrients. This study applies a microbial-explicit model to quantify bacteria and fungal biomass carbon in soils from 1901 to 2016. Results showed substantial increases in bacterial and fungal biomass carbon over the past century, jointly influenced by vegetation growth and soil temperature and moisture. This pioneering century-long estimation offers crucial insights into soil microbial roles in global carbon cycling.
Tao Chen, Félicien Meunier, Marc Peaucelle, Guoping Tang, Ye Yuan, and Hans Verbeeck
Biogeosciences, 21, 2253–2272, https://doi.org/10.5194/bg-21-2253-2024, https://doi.org/10.5194/bg-21-2253-2024, 2024
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Chinese subtropical forest ecosystems are an extremely important component of global forest ecosystems and hence crucial for the global carbon cycle and regional climate change. However, there is still great uncertainty in the relationship between subtropical forest carbon sequestration and its drivers. We provide first quantitative estimates of the individual and interactive effects of different drivers on the gross primary productivity changes of various subtropical forest types in China.
Pritha Pande, Sam Bland, Nathan Booth, Jo Cook, Zhaozhong Feng, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-694, https://doi.org/10.5194/egusphere-2024-694, 2024
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The DO3SE-crop model extends the DO3SE to simulate ozone's impact on crops with modules for ozone uptake, damage, and crop growth from JULES-Crop. It's versatile, suits China's varied agriculture, and improves yield predictions under ozone stress. It is essential for policy, water management, and climate response, it integrates into Earth System Models for a comprehensive understanding of agriculture's interaction with global systems.
Ke Liu, Yujie Wang, Troy S. Magney, and Christian Frankenberg
Biogeosciences, 21, 1501–1516, https://doi.org/10.5194/bg-21-1501-2024, https://doi.org/10.5194/bg-21-1501-2024, 2024
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Stomata are pores on leaves that regulate gas exchange between plants and the atmosphere. Existing land models unrealistically assume stomata can jump between steady states when the environment changes. We implemented dynamic modeling to predict gradual stomatal responses at different scales. Results suggested that considering this effect on plant behavior patterns in diurnal cycles was important. Our framework also simplified simulations and can contribute to further efficiency improvements.
Melanie A. Thurner, Silvia Caldararu, Jan Engel, Anja Rammig, and Sönke Zaehle
Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024, https://doi.org/10.5194/bg-21-1391-2024, 2024
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Due to their crucial role in terrestrial ecosystems, we implemented mycorrhizal fungi into the QUINCY terrestrial biosphere model. Fungi interact with mineral and organic soil to support plant N uptake and, thus, plant growth. Our results suggest that the effect of mycorrhizal interactions on simulated ecosystem dynamics is minor under constant environmental conditions but necessary to reproduce and understand observed patterns under changing conditions, such as rising atmospheric CO2.
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, https://doi.org/10.5194/bg-21-1061-2024, 2024
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A chemical kinetics theory is proposed to explain the non-monotonic relationship between temperature and biochemical rates. It incorporates the observed thermally reversible enzyme denaturation that is ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution and three well-established theories: (1) law of mass action, (2) diffusion-limited chemical reaction theory, and (3) transition state theory.
Nina Raoult, Louis-Axel Edouard-Rambaut, Nicolas Vuichard, Vladislav Bastrikov, Anne Sofie Lansø, Bertrand Guenet, and Philippe Peylin
Biogeosciences, 21, 1017–1036, https://doi.org/10.5194/bg-21-1017-2024, https://doi.org/10.5194/bg-21-1017-2024, 2024
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Observations are used to reduce uncertainty in land surface models (LSMs) by optimising poorly constraining parameters. However, optimising against current conditions does not necessarily ensure that the parameters treated as invariant will be robust in a changing climate. Manipulation experiments offer us a unique chance to optimise our models under different (here atmospheric CO2) conditions. By using these data in optimisations, we gain confidence in the future projections of LSMs.
Kelsey T. Foster, Wu Sun, Yoichi P. Shiga, Jiafu Mao, and Anna M. Michalak
Biogeosciences, 21, 869–891, https://doi.org/10.5194/bg-21-869-2024, https://doi.org/10.5194/bg-21-869-2024, 2024
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Assessing agreement between bottom-up and top-down methods across spatial scales can provide insights into the relationship between ensemble spread (difference across models) and model accuracy (difference between model estimates and reality). We find that ensemble spread is unlikely to be a good indicator of actual uncertainty in the North American carbon balance. However, models that are consistent with atmospheric constraints show stronger agreement between top-down and bottom-up estimates.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
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We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Bertrand Guenet, Jérémie Orliac, Lauric Cécillon, Olivier Torres, Laura Sereni, Philip A. Martin, Pierre Barré, and Laurent Bopp
Biogeosciences, 21, 657–669, https://doi.org/10.5194/bg-21-657-2024, https://doi.org/10.5194/bg-21-657-2024, 2024
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Heterotrophic respiration fluxes are a major flux between surfaces and the atmosphere, but Earth system models do not yet represent them correctly. Here we benchmarked Earth system models against observation-based products, and we identified the important mechanisms that need to be improved in the next-generation Earth system models.
Shuyue Li, Bonnie Waring, Jennifer Powers, and David Medvigy
Biogeosciences, 21, 455–471, https://doi.org/10.5194/bg-21-455-2024, https://doi.org/10.5194/bg-21-455-2024, 2024
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We used an ecosystem model to simulate primary production of a tropical forest subjected to 3 years of nutrient fertilization. Simulations parameterized such that relative allocation to fine roots increased with increasing soil phosphorus had leaf, wood, and fine root production consistent with observations. However, these simulations seemed to over-allocate to fine roots on multidecadal timescales, affecting aboveground biomass. Additional observations across timescales would benefit models.
Stephen Björn Wirth, Arne Poyda, Friedhelm Taube, Britta Tietjen, Christoph Müller, Kirsten Thonicke, Anja Linstädter, Kai Behn, Sibyll Schaphoff, Werner von Bloh, and Susanne Rolinski
Biogeosciences, 21, 381–410, https://doi.org/10.5194/bg-21-381-2024, https://doi.org/10.5194/bg-21-381-2024, 2024
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In dynamic global vegetation models (DGVMs), the role of functional diversity in forage supply and soil organic carbon storage of grasslands is not explicitly taken into account. We introduced functional diversity into the Lund Potsdam Jena managed Land (LPJmL) DGVM using CSR theory. The new model reproduced well-known trade-offs between plant traits and can be used to quantify the role of functional diversity in climate change mitigation using different functional diversity scenarios.
Joe R. McNorton and Francesca Di Giuseppe
Biogeosciences, 21, 279–300, https://doi.org/10.5194/bg-21-279-2024, https://doi.org/10.5194/bg-21-279-2024, 2024
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Wildfires have wide-ranging consequences for local communities, air quality and ecosystems. Vegetation amount and moisture state are key components to forecast wildfires. We developed a combined model and satellite framework to characterise vegetation, including the type of fuel, whether it is alive or dead, and its moisture content. The daily data is at high resolution globally (~9 km). Our characteristics correlate with active fire data and can inform fire danger and spread modelling efforts.
Brooke A. Eastman, William R. Wieder, Melannie D. Hartman, Edward R. Brzostek, and William T. Peterjohn
Biogeosciences, 21, 201–221, https://doi.org/10.5194/bg-21-201-2024, https://doi.org/10.5194/bg-21-201-2024, 2024
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We compared soil model performance to data from a long-term nitrogen addition experiment in a forested ecosystem. We found that in order for soil carbon models to accurately predict future forest carbon sequestration, two key processes must respond dynamically to nitrogen availability: (1) plant allocation of carbon to wood versus roots and (2) rates of soil organic matter decomposition. Long-term experiments can help improve our predictions of the land carbon sink and its climate impact.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
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The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
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Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023, https://doi.org/10.5194/bg-20-4087-2023, 2023
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A better understanding of O2 fluxes, their exchange ratios with CO2 and their interrelations with environmental conditions would provide further insights into biogeochemical ecosystem processes. We, therefore, used the multilayer canopy model CANVEG to simulate and analyze the flux exchange for our forest study site for 2012–2016. Based on these simulations, we further successfully tested the application of various micrometeorological methods and the prospects of real O2 flux measurements.
Jie Zhang, Elisabeth Larsen Kolstad, Wenxin Zhang, Iris Vogeler, and Søren O. Petersen
Biogeosciences, 20, 3895–3917, https://doi.org/10.5194/bg-20-3895-2023, https://doi.org/10.5194/bg-20-3895-2023, 2023
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Manure application to agricultural land often results in large and variable N2O emissions. We propose a model with a parsimonious structure to investigate N transformations around such N2O hotspots. The model allows for new detailed insights into the interactions between transport and microbial activities regarding N2O emissions in heterogeneous soil environments. It highlights the importance of solute diffusion to N2O emissions from such hotspots which are often ignored by process-based models.
Jukka Alm, Antti Wall, Jukka-Pekka Myllykangas, Paavo Ojanen, Juha Heikkinen, Helena M. Henttonen, Raija Laiho, Kari Minkkinen, Tarja Tuomainen, and Juha Mikola
Biogeosciences, 20, 3827–3855, https://doi.org/10.5194/bg-20-3827-2023, https://doi.org/10.5194/bg-20-3827-2023, 2023
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In Finland peatlands cover one-third of land area. For half of those, with 4.3 Mha being drained for forestry, Finland reports sinks and sources of greenhouse gases in forest lands on organic soils following its UNFCCC commitment. We describe a new method for compiling soil CO2 balance that follows changes in tree volume, tree harvests and temperature. An increasing trend of emissions from 1.4 to 7.9 Mt CO2 was calculated for drained peatland forest soils in Finland for 1990–2021.
Siqi Li, Bo Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Jihui Fan, Tao Wang, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, Wei Zhang, and Yong Li
Biogeosciences, 20, 3555–3572, https://doi.org/10.5194/bg-20-3555-2023, https://doi.org/10.5194/bg-20-3555-2023, 2023
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Physical soil erosion and particulate carbon, nitrogen and phosphorus loss modules were incorporated into the process-oriented hydro-biogeochemical model CNMM-DNDC to realize the accurate simulation of water-induced erosion and subsequent particulate nutrient losses at high spatiotemporal resolution.
Ivan Cornut, Nicolas Delpierre, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, Otavio Campoe, Jose Luiz Stape, Vitoria Fernanda Santos, and Guerric le Maire
Biogeosciences, 20, 3093–3117, https://doi.org/10.5194/bg-20-3093-2023, https://doi.org/10.5194/bg-20-3093-2023, 2023
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Potassium is an essential element for living organisms. Trees are dependent upon this element for certain functions that allow them to build their trunks using carbon dioxide. Using data from experiments in eucalypt plantations in Brazil and a simplified computer model of the plantations, we were able to investigate the effect that a lack of potassium can have on the production of wood. Understanding nutrient cycles is useful to understand the response of forests to environmental change.
Ivan Cornut, Guerric le Maire, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, and Nicolas Delpierre
Biogeosciences, 20, 3119–3135, https://doi.org/10.5194/bg-20-3119-2023, https://doi.org/10.5194/bg-20-3119-2023, 2023
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After simulating the effects of low levels of potassium on the canopy of trees and the uptake of carbon dioxide from the atmosphere by leaves in Part 1, here we tried to simulate the way the trees use the carbon they have acquired and the interaction with the potassium cycle in the tree. We show that the effect of low potassium on the efficiency of the trees in acquiring carbon is enough to explain why they produce less wood when they are in soils with low levels of potassium.
Xiaojuan Yang, Peter Thornton, Daniel Ricciuto, Yilong Wang, and Forrest Hoffman
Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, https://doi.org/10.5194/bg-20-2813-2023, 2023
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We evaluated the performance of a land surface model (ELMv1-CNP) that includes both nitrogen (N) and phosphorus (P) limitation on carbon cycle processes. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. We show that global C sources and sinks are significantly affected by P limitation. Our study suggests that introduction of P limitation in land surface models is likely to have substantial consequences for projections of future carbon uptake.
Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William Pockman, Zheng Shi, Melinda D. Smith, and Yiqi Luo
Biogeosciences, 20, 2707–2725, https://doi.org/10.5194/bg-20-2707-2023, https://doi.org/10.5194/bg-20-2707-2023, 2023
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The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems store carbon in the future. Here, we employ novel data–model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C, so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, https://doi.org/10.5194/bg-20-2573-2023, 2023
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Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.
Yunyao Ma, Bettina Weber, Alexandra Kratz, José Raggio, Claudia Colesie, Maik Veste, Maaike Y. Bader, and Philipp Porada
Biogeosciences, 20, 2553–2572, https://doi.org/10.5194/bg-20-2553-2023, https://doi.org/10.5194/bg-20-2553-2023, 2023
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We found that the modelled annual carbon balance of biocrusts is strongly affected by both the environment (mostly air temperature and CO2 concentration) and physiology, such as temperature response of respiration. However, the relative impacts of these drivers vary across regions with different climates. Uncertainty in driving factors may lead to unrealistic carbon balance estimates, particularly in temperate climates, and may be explained by seasonal variation of physiology due to acclimation.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
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This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Libo Wang, Vivek K. Arora, Paul Bartlett, Ed Chan, and Salvatore R. Curasi
Biogeosciences, 20, 2265–2282, https://doi.org/10.5194/bg-20-2265-2023, https://doi.org/10.5194/bg-20-2265-2023, 2023
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Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
Veronika Kronnäs, Klas Lucander, Giuliana Zanchi, Nadja Stadlinger, Salim Belyazid, and Cecilia Akselsson
Biogeosciences, 20, 1879–1899, https://doi.org/10.5194/bg-20-1879-2023, https://doi.org/10.5194/bg-20-1879-2023, 2023
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In a future climate, extreme droughts might become more common. Climate change and droughts can have negative effects on soil weathering and plant health.
In this study, climate change effects on weathering were studied on sites in Sweden using the model ForSAFE, a climate change scenario and an extreme drought scenario. The modelling shows that weathering is higher during summer and increases with global warming but that weathering during drought summers can become as low as winter weathering.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771, https://doi.org/10.5194/bg-20-1759-2023, https://doi.org/10.5194/bg-20-1759-2023, 2023
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Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers
Biogeosciences, 20, 1635–1648, https://doi.org/10.5194/bg-20-1635-2023, https://doi.org/10.5194/bg-20-1635-2023, 2023
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Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht
Biogeosciences, 20, 1313–1355, https://doi.org/10.5194/bg-20-1313-2023, https://doi.org/10.5194/bg-20-1313-2023, 2023
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The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how nature works. Of course, nature does not care about our understanding. Since our understanding is not perfect, evaluating models is challenging, and there are uncertainties. This paper illustrates this uncertainty for land models and argues that evaluating models in light of the uncertainty in various components provides useful information.
Benjamin S. Felzer
Biogeosciences, 20, 573–587, https://doi.org/10.5194/bg-20-573-2023, https://doi.org/10.5194/bg-20-573-2023, 2023
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The future of the terrestrial carbon sink depends upon the legacy of past land use, which determines the stand age of the forest and nutrient levels in the soil, both of which affect vegetation growth. This study uses a modeling approach to determine the effects of land-use legacy in the conterminous US from 1750 to 2099. Not accounting for land legacy results in a low carbon sink and high biomass, while water variables are not as highly affected.
Cited articles
Adams III, W. W. and Demmig-Adams, B.: Carotenoid composition and down regulation of photosystem II in three conifer species during the winter, Physiol. Plantarum, 92, 451–458, https://doi.org/10.1111/j.1399-3054.1994.tb08835.x, 1994.
Ashraf, M. and Harris, P. J. C.: Photosynthesis under stressful environments: An overview, Photosynthetica, 51, 163–190, https://doi.org/10.1007/s11099-013-0021-6, 2013.
Bacour, C., Maignan, F., Peylin, P., MacBean, N., Bastrikov, V., Joiner, J., Köhler, P., Guanter, L., and Frankenberg, C.: Differences Between OCO-2 and GOME-2 SIF Products From a Model-Data Fusion Perspective, J. Geophys. Res.-Biogeo., 124, 3143–3157, https://doi.org/10.1029/2018JG004938, 2019a.
Bacour, C., Maignan, F., MacBean, N., Porcar-Castell, A., Flexas, J., Frankenberg, C., Peylin, P., Chevallier, F., Vuichard, N., and Bastrikov, V.: Improving Estimates of Gross Primary Productivity by Assimilating Solar-Induced Fluorescence Satellite Retrievals in a Terrestrial Biosphere Model Using a Process-Based SIF Model, J. Geophys. Res.-Biogeo., 124, 3281–3306, https://doi.org/10.1029/2019JG005040, 2019b.
Baker, N. R., Harbinson, J., and Kramer, D. M.: Determining the limitations and regulation of photosynthetic energy transduction in leaves, Plant Cell Environ., 30, 1107–1125, https://doi.org/10.1111/j.1365-3040.2007.01680.x, 2007.
Ball, J. T., Woodrow, I. E., and Berry, J. A.: A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions, in: Progress in Photosynthesis Research, edited by: Biggins, J., Springer, Dordrecht, https://doi.org/10.1007/978-94-017-0519-6_48, 221–224, 1987.
Basu, P. S., Ali, M., and Chaturvedi, S. K.: Terminal heat stress adversely affects chickpea productivity in Northern India-strategies to improve thermotolerance in the crop under climate change, W3 Workshop proceedings: Impact of Climate Change on Agriculture, Vol 23, International Society for Photogrammetry and Remote Sensing, New Delhi, 2009.
Berg, M. P., Kiers, E. T., Driessen, G., van der Heijden, M., Kooi, B. W., Kuenen, F., Liefting, M., Verhoef, H. A., and Ellers, J.: Adapt or disperse: understanding species persistence in a changing world, Glob. Change Biol., 16, 587–598, https://doi.org/10.1111/j.1365-2486.2009.02014.x, 2010..
Berry, J. and Björkman, O.: Photosynthetic Response and Adaptation to Temperature in Higher Plants, Annu. Rev. Plant Phys., 31, 491–543, https://doi.org/10.1146/annurev.pp.31.060180.002423, 1980.
Björkman, O. and Demmig, B.: Photon yield of O2 evolution and chlorophyll fluorescence characteristics at 77 K among vascular plants of diverse origins, Planta, 170, 489–504, https://doi.org/10.1007/BF00402983, 1987.
Buchanan, B. B.: The carbon (formerly dark) reactions of photosynthesis, Photosynth. Res., 128, 215–217, https://doi.org/10.1007/s11120-015-0212-z, 2016.
Buckley, T. N.: Modeling Stomatal Conductance, Plant Physiol., 174, 572–582, https://doi.org/10.1104/pp.16.01772, 2017.
Cleveland, W. S., Devlin, S. J., and Grosse, E.: Regression by local fitting: Methods, Properties, and Computational Algorithms, J. Econometrics, 37, 87–114, https://doi.org/10.1016/0304-4076(88)90077-2, 1988.
Corcuera, L., Gil-Pelegrin, E., and Notivol, E.: Intraspecific Variation in Pinus Pinaster PSII Photochemical Efficiency in Response to Winter Stress and Freezing Temperatures, PLoS ONE, 6, e28772, https://doi.org/10.1371/journal.pone.0028772, 2011.
Curtis, E.: Spatiotemporal Dynamics of High-Temperature Tolerance in Australian Arid-Zone Plants, PhD thesis, University of Technology Sydney, http://hdl.handle.net/10453/120274 (last access: 22 February 2023), 2017.
Demmig-Adams, B. and Adams III, W. W.: Photoprotection in an ecological context: the remarkable complexity of thermal energy dissipation, New Phytol., 172, 11–21, https://doi.org/10.1111/j.1469-8137.2006.01835.x, 2006.
Dietze, M. C.: Gaps in knowledge and data driving uncertainty in models of photosynthesis, Photosynth. Res., 119, 3–14, https://doi.org/10.1007/s11120-013-9836-z, 2014.
Dusenge, M. E., Duarte, A. G., and Way, D. A.: Plant carbon metabolism and climate change: elevated CO2 and temperature impacts on photosynthesis, photorespiration and respiration, New Phytol., 221, 32–49, https://doi.org/10.1111/nph.15283, 2019.
Ehlert, B. and Hincha, D. K.: Chlorophyll fluorescence imaging accurately quantifies freezing damage and cold acclimation responses in Arabidopsis leaves, Plant Methods, 4, 12, https://doi.org/10.1186/1746-4811-4-12, 2008.
Fadrique, B., Baraloto, C., Bravo-Avila, C. H., and Feeley, K. J.: Bamboo climatic tolerances are decoupled from leaf functional traits across an Andean elevation gradient, Oikos, 11, 1–13, https://doi.org/10.1111/oik.09229, 2022.
Farquhar, G. D., von Caemmerer, S., and Berry, J. A.: A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149, 78–90, https://doi.org/10.1007/BF00386231, 1980.
Ferguson, J. N., McAusland, L., Smith, K. E., Price, A. H., Wilson, Z. A., and Murchie, E. H.: Rapid temperature responses of photosystem II efficiency forecast genotypic variation in rice vegetative heat tolerance, Plant J., 104, 839–855, https://doi.org/10.1111/tpj.14956, 2020.
Filho, J., Gaspar de Oliveira, C. M., Caramori, P. H., Nagashima, G. T., Hernandez, F. B. T.: Cold tolerance of forage plant species, Semin. Cienc. Agrar., 39, 1469–1476, https://doi.org/10.5433/1679-0359.2018v39n4p1469, 2018.
Francis, J. A. and Vavrus, S. J.: Evidence for a wavier jet stream in response to rapid Arctic warming, Environ. Res. Lett., 10, 014005, https://doi.org/10.1088/1748-9326/10/1/014005, 2015.
Franks, P. J., Berry, J. A., Lombardozzi, D. L., and Bonan, G. B.: Stomatal Function across Temporal and Spatial Scales: Deep-Time Trends, Land-Atmosphere Coupling and Global Models, Plant Physiol., 174, 583–602, https://doi.org/10.1104/pp.17.00287, 2017.
Freedman, D. and Diaconis, P.: On the histogram as a density estimator: L2 theory, Z. Wahrscheinlichkeit., 57, 453–476, https://doi.org/10.1007/BF01025868, 1981.
Genty, B., Briantais, J.-M., and Baker, N. R.: The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence, BBA-Gen. Subjects, 990, 87–92, https://doi.org/10.1016/S0304-4165(89)80016-9, 1989.
Gu, L., Han, J., Wood, J. D., Chang, C. Y-Y., Sun, Y.: Sun-induced Chl fluorescence and its importance for biophysical modeling of photosynthesis based on light reactions, New Phytol., 223, 1179–1191, https://doi.org/10.1111/nph.15796, 2019.
Gu, L., Grodzinski, B., Han, J., Zhang, J., Song, Y. C., Sun, Y., and Marie, T.: An exploratory steady‐state redox model of photosynthetic linear electron transport for use in complete modelling of photosynthesis for broad applications, Plant Cell Environ., 46, 1540–1561, https://doi.org/10.1111/pce.14563, 2023.
Han, J., Chang, C. Y., Gu, L., Zhang, Y., Meeker, E. W., Magney, T. S., Walker, A. P., Wen, J., Kira, O., McNaull, S., and Sun, Y.: The physiological basis for estimating photosynthesis from Chl a fluorescence, New Phytol., 234, 1206–1219, https://doi.org/10.1111/nph.18045, 2022.
Hajihashemi, S., Noedoost, F., Geuns, J. M. C., Djalovic, I., and Siddique, K. H. M.: Effect of Cold Stress on Photosynthetic Traits, Carbohydrates, Morphology, and Anatomy in Nine Cultivars of Stevia rebaudiana, Front. Plant Sci., 9, 1430, https://doi.org/10.3389/fpls.2018.01430, 2018.
Hatfield, J. L., Antle, J., Garrett, K. A., Izaurralde, R. C., Mader, T., Marshall, E., Nearing, M., Robertson, G. P., and Ziska, L.: Indicators of climate change in agricultural systems, Climatic Change, 163, 1719–1732, https://doi.org/10.1007/s10584-018-2222-2, 2020.
Havaux, M.: A theoretical and experimental analysis of the qt, and qN coefficients of chlorophyll fluorescence quenching and their relation to photochemical and nonphotochemical events, Photosynth. Res., 27, 41–55, https://doi.org/10.1007/BF00029975, 1991.
Havaux, M.: Stress Tolerance of Photosystem II in Vivo. Antagonistic Effects of Water, Heat, and Photoinhibition Stress, Plant Physiol., 100, 424–432, https://doi.org/10.1104/pp.100.1.424, 1992.
Heinze, C., Eyring, V., Friedlingstein, P., Jones, C., Balkanski, Y., Collins, W., Fichefet, T., Gao, S., Hall, A., Ivanova, D., Knorr, W., Knutti, R., Löw, A., Ponater, M., Schultz, M. G., Schulz, M., Siebesma, P., Teixeira, J., Tselioudis, G., and Vancoppenolle, M.: ESD Reviews: Climate feedbacks in the Earth system and prospects for their evaluation, Earth Syst. Dynam., 10, 379–452, https://doi.org/10.5194/esd-10-379-2019, 2019.
Heskel, M. A., O'Sullivan, O. S., Reich, P. B., Tjoelker, M. G., Weerasinghe, L. K., Penillard, A., Egerton, J. J. G., Creek, D., Bloomfield, K. J., Xiang, J., Sinca, F., Stangl, Z. R., Martinez-de la Torre, A., Griffin, K. L., Huntingford, C., Hurry, V., Meir, P., Turnbull, M. H., and Atkin, O. K.: Convergence in the temperature response of leaf respiration across biomes and plant functional types, P. Natl. Acad. Sci. USA, 113, 3832–3837, https://doi.org/10.1073/pnas.1520282113, 2016.
IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896, 2021.
Johnson, G. N., Young, A. J., Scholes, J. D., and Horton, P.: The dissipation of excess excitation energy in British plant species, Plant Cell Environ., 16, 673–679, https://doi.org/10.1111/j.1365-3040.1993.tb00485.x, 1993.
Kadir, S., Sidhu, G., and Al-Khatib, K.: Strawberry (Fragaria × ananassa Duch.) Growth and Productivity as Affected by Temperature, HortScience, 41, 1423–1430, https://doi.org/10.21273/HORTSCI.41.6.1423, 2006.
Kamen, M. D.: Primary Processes in Photosynthesis, edited by: San Pietro, A., Elsevier, 196 pp., ISBN 9781483274454, 1963.
Ke, Y., Leung, L. R., Huang, M., Coleman, A. M., Li, H., and Wigmosta, M. S.: Development of high resolution land surface parameters for the Community Land Model, Geosci. Model Dev., 5, 1341–1362, https://doi.org/10.5194/gmd-5-1341-2012, 2012.
Kelly, R., Healy, K., Anand, M., Baudraz, M. E. A., Bahn, M., Cerabolini, B. E. L., Cornelissen, J. H. C., Dwyer, J. M., Jackson, A. L., Kattge, J., Niinemets, Ü., Penuelas, J., Pierce, S., Salguero-Gómez, R., and Buckley, Y. M.: Climatic and evolutionary contexts are required to infer plant life history strategies from functional traits at a global scale, Ecol. Lett., 24, 970–983, https://doi.org/10.1111/ele.13704, 2021.
Kitajima, M. and Butler, W. L.: Quenching of chlorophyll fluorescence and primary photochemistry in chloroplasts by dibromothymoquinone, BBA-Bioenergetics, 376, 105–115, https://doi.org/10.1016/0005-2728(75)90209-1, 1975.
Klughammer, C. and Schreiber, U.: Complementary PS II quantum yields calculated from simple fluorescence parameters measured by PAM fluorometry and the Saturation Pulse method, PAM Application Notes, 1, 27–35, 2008.
Knight, C. A. and Ackerly, D. D.: Correlated evolution of chloroplast heat shock protein expression in closely related plant species, Am. J. Bot., 88, 411–418, https://doi.org/10.2307/2657105, 2001.
Kumarathunge, D. P., Medlyn, B. E., Drake, J. E., Tjoelker, M. G., Aspinwall, M. J., Battaglia, M., Cano, F. J., Carter, K. R., Cavaleri, M. A., Cernusak, L. A., Chambers, J. Q., Crous, K. Y., De Kauwe, M. G., Dillaway, D. N., Dreyer, E., Ellsworth, D. S., Ghannoum, O., Han, Q., Hikosaka, K., Jensen, A. M., Kelly, J. W. G., Kruger, E. L., Mercado, L. M., Onoda, Y., Reich, P. B., Rogers, A., Slot, M., Smith, N. G., Tarvainen, L., Tissue, D. T., Togashi, H. F., Tribuzy, E. S., Uddling, J., Vårhammar, A., Wallin, G., Warren, J. M., and Way, D. A.: Acclimation and adaptation components of the temperature dependence of plant photosynthesis at the global scale, New Phytol., 222, 768–784, https://doi.org/10.1111/nph.15668, 2019.
Kunert, N., Hajek, P., Hietz, P., Morris, H., Rosner, S., and Tholen, D.: Summer temperatures reach the thermal tolerance threshold of photosynthetic decline in temperate conifers, Plant Biol., 24, 7, 1254–1261, https://doi.org/10.1111/plb.13349, 2022.
Lawrence, P. J. and Chase, T. N.: Representing a new MODIS consistent land surface in the Community Land Model (CLM 3.0), J. Geophys. Res.-Biogeo., 112, G01023, https://doi.org/10.1029/2006JG000168, 2007.
Lawrence, D. M., Hurtt, G. C., Arneth, A., Brovkin, V., Calvin, K. V., Jones, A. D., Jones, C. D., Lawrence, P. J., de Noblet-Ducoudré, N., Pongratz, J., Seneviratne, S. I., and Shevliakova, E.: The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design, Geosci. Model Dev., 9, 2973–2998, https://doi.org/10.5194/gmd-9-2973-2016, 2016.
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.
Lazár, D.: Parameters of photosynthetic energy partitioning, J. Plant Physiol., 175, 131–147, https://doi.org/10.1016/j.jplph.2014.10.021, 2015.
Lee, J.-E., Berry, J. A., van der Tol, C., Yang, X., Guanter, L., Damm, A., Baker, I., and Frankenberg, C.: Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4, Glob. Change Biol., 21, 3469–3477, https://doi.org/10.1111/gcb.12948, 2015.
Leon-Garcia, I. V. and Lasso, E.: High heat tolerance in plants from the Andean highlands: Implications for paramos in a warmer world, PLOS ONE, 14, e0224218, https://doi.org/10.1371/journal.pone.0224218, 2019.
Leister, D.: Enhancing the light reactions of photosynthesis: Strategies, controversies, and perspectives, Mol. Plant, 16, 4–22, https://doi.org/10.1016/j.molp.2022.08.005, 2022.
Leys, C. and Schumann, S.: A nonparametric method to analyze interactions: The adjusted rank transform test, J. Exp. Soc. Psychol., 46, 684–688, https://doi.org/10.1016/j.jesp.2010.02.007, 2010.
Li, H., Qiang, S., and Qian, Y.: Physiological Response of Different Croftonweed (Eupatorium adenophorum) Populations to Low Temperature, Weed Sci., 56, 196–202, https://doi.org/10.1614/WS-07-104.1, 2008.
Li, Y.-G., Li, L.-H., Jiang, G.-M., Niu, S.-L., Liu, M.-Z., Gao, L.-M., Peng, Y., and Jiang, C.-D.: Traits of Chlorophyll Fluorescence in 99 Plant Species from the Sparse-Elm Grassland in Hunshandak Sandland, Photosynthetica, 42, 243–249, https://doi.org/10.1023/B:PHOT.0000040596.39460.6f, 2004.
Lin, Y.-S., Medlyn, B. E., and Ellsworth, D. S.: Temperature responses of leaf net photosynthesis: the role of component processes, Tree Physiol., 32, 219–231, https://doi.org/10.1093/treephys/tpr141, 2012.
Lin, Y.-S., Medlyn, B. E., Duursma, R. A., Prentice, C., Wang, H., Baig, S., Eamus, D., de Dios, V. R., Mitchell, P., Ellsworth, D. S., de Beeck, M. O., Wallin, G., Udding, J., Tarvainen, L., Linderson, M.-L., Cernusak, L. A., Nippert, J. B., Ocheltree, T. W., Tissue, D. T., Martin-StPaul, N. K., Rogers, A., Warren, J. M., De Angelis, P., Hikosaka, K., Han, Q., Onoda, Y., Gimeno, T. E., Barton, C. V. M., Bennie, J., Bonal, D., Bosc, A., Löw, M., Macinins-Ng, C., Rey, A., Rowland, L., Setterfield, S. A., Tausz-Posch, S., Zaragoza-Castells, J., Broadmeadow, M. S. J., Drake, J. E., Freeman, M., Ghannoum, O., Hutley, L. B., Kelly, J. W., Kikuzawa, K., Kolari, P., Koyama, K., Limousin, J.-M., Meir, P., Lola da Costa, A. C., Mikkelsen, T. N., Salinas, N., Sun, W., and Wingate, L.: Optimal stomatal behaviour around the world, Nat. Clim. Change, 5, 459–464, https://doi.org/10.1038/NCLIMATE2550, 2015.
Lu, C. and Zhang, J.: Effects of water stress on photosystem II photochemistry and its thermostability in wheat plants, J. Exp. Biol., 50, 1199–1206, https://doi.org/10.1093/jxb/50.336.1199, 1999.
Marias, D. E., Meinzer, F. C., Woodruff, D. R., and McCulloh, K. A.: Thermotolerance and heat stress responses of Douglas-fir and ponderosa pine seedling populations from contrasting climates, Tree Physiol., 37, 301–315, https://doi.org/10.1093/treephys/tpw117, 2016.
McCallum, I., Franklin, O., Moltchanova, E., Merbold, L., Schmullius, C., Shvidenko, A., Schepaschenko, D., and Fritz, S.: Improved light and temperature responses for light-use-efficiency-based GPP models, Biogeosciences, 10, 6577–6590, https://doi.org/10.5194/bg-10-6577-2013, 2013.
Mohammed, G. H., Colombo, R., Middleton, E. M., Rascher, U., van der Tol, C., Nedbal, L., Goulas, Y., Pérez-Priego, O., Damm, A., Meroni, M., Joiner, J., Cogliati, S., Verhoef, W., Malenovský, Z., Gastellu-Etchegorry, J.-P., Miller, J. R., Guanter, L., Moreno, J., Moya, I., Berry, J. A., Frankenberg, C., and Zarco-Tejada, P. J.: Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress, Remote Sens. Environ., 231, 111177, https://doi.org/10.1016/j.rse.2019.04.030, 2019.
Molina-Bravo, R., Arellano, C., Sosinski, B. R., and Fernandez, G. E.: A protocol to assess heat tolerance in a segregating population of raspberry using chlorophyll fluorescence, Sci. Hortic.-Amsterdam, 130, 524–530, https://doi.org/10.1016/j.scienta.2011.07.022, 2011.
Murata, N., Takahashi, S., Nishiyama, Y., and Allakhverdiev, S. I.: Photoinhibition of photosystem II under environmental stress, BBA-Bioenergetics, 1767, 414–421, https://doi.org/10.1016/j.bbabio.2006.11.019, 2007.
Newville, M., Stensitzki, T., Allen, D. B., and Ingargiola, A.: LMFIT: Non-Linear Least-Square Minimization and Curve-Fitting for Python, Zenodo, https://doi.org/10.5281/zenodo.11813, 2014.
Neri, P., Gu, L., and Song, Y.: Plant functional types-specific and climatology-informed PSIImax temperature response models, the University of Arizona (UA) research data repository ReDATA [code], https://doi.org/10.25422/azu.data.24143064 (last access: 31 May 2024), 2024a.
Neri, P., Gu, L., and Song, Y.: A global-scale dataset of synthesized maximum photochemical quenching yields and the corresponding environmental information, the University of Arizona (UA) data repository ReDATA [dataset], https://doi.org/10.25422/azu.data.24142989 (last access: 31 May 2024), 2024b.
Norton, A. J., Rayner, P. J., Koffi, E. N., and Scholze, M.: Assimilating solar-induced chlorophyll fluorescence into the terrestrial biosphere model BETHY-SCOPE v1.0: model description and information content, Geosci. Model Dev., 11, 1517–1536, https://doi.org/10.5194/gmd-11-1517-2018, 2018.
Norton, A. J., Rayner, P. J., Koffi, E. N., Scholze, M., Silver, J. D., and Wang, Y.-P.: Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model, Biogeosciences, 16, 3069–3093, https://doi.org/10.5194/bg-16-3069-2019, 2019.
Oberhuber, W. and Edwards, C. E.: Temperature Dependence of the Linkage of Quantum Yield of Photosystem II to CO2 Fixation in C4 and C3 Plants, Plant Physiol., 101, 507–512, https://doi.org/10.1104/pp.101.2.507, 1993.
Ogaya, R., Peñuelas, J., Asensio, D., and Llusià, J.: Chlorophyll fluorescence responses to temperature and water availability in two co-dominant Mediterranean shrub and tree species in a long-term field experiment simulating climate change, Environ. Exp. Bot., 71, 123–127, https://doi.org/10.1016/j.envexpbot.2010.10.016, 2011.
Oliveira, G. and Peñuelas, J.: Comparative photochemical and phenomorphological responses to winter stress of an evergreen (Quercus ilex L.) and a semi-deciduous (Cistus albidus L.) Mediterranean woody species, Acta Oecol., 21, 97–107, https://doi.org/10.1016/S1146-609X(00)00121-1, 2000.
Parazoo, N. C., Magney, T., Norton, A., Raczka, B., Bacour, C., Maignan, F., Baker, I., Zhang, Y., Qiu, B., Shi, M., MacBean, N., Bowling, D. R., Burns, S. P., Blanken, P. D., Stutz, J., Grossmann, K., and Frankenberg, C.: Wide discrepancies in the magnitude and direction of modeled solar-induced chlorophyll fluorescence in response to light conditions, Biogeosciences, 17, 3733–3755, https://doi.org/10.5194/bg-17-3733-2020, 2020.
Perez, T. M. and Feeley, K. J.: Photosynthetic heat tolerances and extreme leaf temperatures, Funct. Ecol., 34, 2236–2245, https://doi.org/10.1111/1365-2435.13658, 2020.
Porcar-Castell, A.: A high-resolution portrait of the annual dynamics of photochemical and ono-photochemical quenching in needles of Pinus sylvestris, Physiol. Plantarum, 143, 139–153, https://doi.org/10.1111/j.1399-3054.2011.01488.x, 2011.
Porcar-Castell, A., Malenovský, Z., Magney, T., Van Wittenberghe, S., Fernández-Marín, B., Maignan, F., Zhang, Y., Maseyk, K., Atherton, J., Albert, L. P., Robson, T. M., Zhao, F., Garcia-Plazaola, J.-I., Ensminger, I., Rajewicz, P. A., Grebe, S., Tikkanen, M., Kellner, J. R., Ihalainen, J. A., Rascher, U., and Loban, B.: Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science, Nat. Plants, 7, 998–1009, https://doi.org/10.1038/s41477-021-00980-4, 2021.
Rapacz, M., Gasior, D., Zwierzykowski, Z., Lesniewska-Bocianowska, A., Humphreys, M. W., and Gay, A. P.: Changes in cold tolerance and the mechanisms of acclimation of photosystem II to cold hardening generated by anther culture of Festuca pratensis × Lolium multiflorum cultivars, New Phytol., 162, 105–114, https://doi.org/10.1111/j.1469-8137.2004.01024.x, 2004.
Rath, J. R., Pandey, J., Yadav, R. M., Zamal, M. Y., Ramachandran, P., Mekala, N. R., Allakhverdiev, S. I., and Subramanyam, R.: Temperature-induced reversible changes in photosynthesis efficiency and organization of thylakoid membranes from pea (Pisum sativum), Plant Physiol. Bioch., 185, 144–154, https://doi.org/10.1016/j.plaphy.2022.05.036, 2022.
Reich, P. B., Wright, I. J., Cavender-Bares, J., Craine, J. M., Oleksyn, J., Westoby, M., and Walters, M. B.: The Evolution of Plant Functional Variation: Traits, Spectra, and Strategies, Int. J. Plant Sci., 164, S143-S164, https://doi.org/10.1086/374368, 2003.
Rizza, F., Pagani, D., Stanca, A. M., and Cattivelli, L.: Use of chlorophyll fluorescence to evaluate the cold acclimation and freezing tolerance of winter and spring oats, Plant Breeding, 120, 389–396, https://doi.org/10.1046/j.1439-0523.2001.00635.x, 2001.
Rogers, A., Medlyn, B. E., Dukes, J. S., Bonan, G., von Caemmerer, S., Dietze, M. C., Kattge, J., Leakey, A. D. B., Mercado, L. M., Niinemets, Ü., Prentice, I. C., Serbin, S. P., Sitch, S., Way, D. A., and Zaehle, S.: A roadmap for improving the representation of photosynthesis in Earth system models, New Phytol., 213, 22–42, https://doi.org/10.1111/nph.14283, 2017.
Rohatgi, A.: WebPlotDigitizer (version 4.2) [Computer software], https://automeris.io/WebPlotDigitizer (last access: 25 April 2023), 2021.
Sakai, A.: Freezing Resistance of Broad-Leaved Evergreen Trees in the Warm-Temperate Zone, Low Temperature Science. Ser. B, Biological sciences, 38, 1–14, http://hdl.handle.net/2115/17854 (last access: 21 March 2023), 1980.
Sastry, A. and Barua, D.: Leaf thermotolerance in tropical trees from a seasonally dry climate varies along the slow-fast resource acquisition spectrum, Sci. Rep.-UK, 7, 11246, https://doi.org/10.1038/s41598-017-11343-5, 2017.
Schrader, S. M., Wise, R. R., Wacholtz, W. F., Ort, D. R., and Sharkey, T. D.: Thylakoid membrane responses to moderately high leaf temperature in Pima cotton, Plant Cell Environ., 27, 725–735, https://doi.org/10.1111/j.1365-3040.2004.01172.x, 2004.
Seng, M., Jeong, U., and Cheong, E. J.: Detection of responses to drought stress of dalbergia cochinchinensis seedlings using the physiological parameters and thermal imaging, Forest Sci. Technol., 19, 105–115, https://doi.org/10.1080/21580103.2023.2186956, 2023.
Sharma, D. K., Torp, A. M., Rosenqvist, E., Ottosen, C.-O., and Andersen, S. B.: QTLs and Potential Candidate Genes for Heat Stress Tolerance Identified from the Mapping Populations Specifically Segregating for Fv/Fm in Wheat, Front. Plant Sci., 8, 1668, https://doi.org/10.3389/fpls.2017.01668, 2017.
Shirke, P. A. and Pathre, U. V.: Diurnal and seasonal changes in photosynthesis and photosystem 2 photochemical efficiency in Prosopis juliflora leaves subjected to natural environmental stress, Photosynthetica, 41, 83–89, https://doi.org/10.1023/A:1025864513663, 2003.
Slot, M., Krause, G. H., Krause, B., Hernández, G. G., and Winter, K.: Photosynthetic heat tolerance of shade and sun leaves of three tropical tree species, Photosynth. Res., 141, 119–130, https://doi.org/10.1007/s11120-018-0563-3, 2019.
Smillie, R. and Nott, R.: Heat Injury in Leaves of Alpine, Temperate and Tropical Plants, Funct. Plant Biol., 6, 135, https://doi.org/10.1071/PP9790135, 1979.
Solhaug, K. A. and Haugen, J.: Seasonal variation of photoinhibition of photosynthesis in bark from Populus tremula L., Photosynthetica, 35, 411–417, https://doi.org/10.1023/A:1006968403331, 1998.
Soliman, W. S., Fujimori, M., Tase, K., and Sugiyama, S.: Heat tolerance and suppression of oxidative stress: Comparative analysis of 25 cultivars of the C3 grass Lolium perenne, Environ. Exp. Bot., 78, 10–17, https://doi.org/10.1016/j.envexpbot.2011.12.013, 2012.
Sommer, S. G., Han, E., Li, X., Rosenqvist, E., and Liu, F.: The Chlorophyll Fluorescence Parameter Fv/Fm Correlates with Loss of Grain Yield after Severe Drought in Three Wheat Genotypes Grown at Two CO2 Concentrations, Plants, 12, 436, https://doi.org/10.3390/plants12030436, 2023.
Song, Y.: Plant functional types-specific and climatology-informed PSIImax temperature response models, Figshare [code], https://doi.org/10.25422/azu.data.24143064, 2024a.
Song, Y.: A global-scale dataset of synthesized maximum photochemical quenching yields and the corresponding environmental information, Figshare [data set], https://doi.org/10.25422/azu.data.24142989, 2024b.
Song, Y., Chen, Q., Ci, D., Shao, X., and Zhang, D.: Effects of high temperature on photosynthesis and related gene expression in poplar, BMC Plant Biol., 14, 111, https://doi.org/10.1186/1471-2229-14-111, 2014.
Stirbet, A., Lazár, D., Guo, Y., and Govindjee, G.: Photosynthesis: basics, history and modelling, Ann. Bot., 126, 511–537, https://doi.org/10.1093/aob/mcz171, 2019.
Sun, Y., Gu, L., Wen, J., van der Tol, C., Porcar-Castell, A., Joiner, J., Chang, C. Y., Magney, T., Wang, L., Hu, L., Rascher, U., Zarco-Tejada, P., Barrett, C. B., Lai, J., Han, J., and Luo, Z.: From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I – Harnessing theory, Glob. Change Biol., 29, 2926–2952, https://doi.org/10.1111/gcb.16634, 2023a.
Sun, Y., Wen, J., Gu, L., Joiner, J., Chang, C. Y., van der Tol, C., Porcar-Castell, A., Magney, T., Wang, L., Hu, L., Rascher, U., Zarco-Tejada, P., Barrett, C. B., Lai, J., Han, J., and Luo, Z.: From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II – Harnessing data, Glob. Change Biol., 29, 2893–2925, https://doi.org/10.1111/gcb.16646, 2023b.
Sun, Z., Wang, X., Zhang, X., Tani, H., Guo, E., Yin, S., and Zhang, T.: Evaluating and comparing remote sensing terrestrial GPP models for their response to climate variability and CO2 trends, Sci. Total Environ., 668, 696–713, https://doi.org/10.1016/j.scitotenv.2019.03.025, 2019.
Takahashi, S. and Badger, M. R.: Photoprotection in plants: a new light on photosystem II damage, Trends Plant Sci., 16, 53–60, https://doi.org/10.1016/j.tplants.2010.10.001, 2011.
Taleisnik, E. and Grunherg, K.: Ion balance in tomato cultivars differing in salt tolerance. I. Sodium and potassium accumulation and fluxes under moderate salinity, Physiol. Plant., 92, 528–534, https://doi.org/10.1111/j.1399-3054.1994.tb08847.x, 1994.
Tietz, S., Hall, C. C., Cruz, J. A., and Kramer, D. M.: NPQ(T): a chlorophyll fluorescence parameter for rapid estimation and imaging of non-photochemical quenching of excitons in photosystem-II-associated antenna complexes, Plant Cell Environ., 40, 1243–1255, https://doi.org/10.1111/pce.12924, 2017.
Tiwari, R., Gloor, E., Cruz, W. J. A., Schwantes Marimon, B., Marimon-Junior, B. H., Reis, S. M., Souza, I. A., Krause, H. G., Slot, M., Winter, K., Ashley, D., Béu, R. G., Borges, C. S., Da Cunha, M., Fauset, S., Ferreira, L. D. S., Gonçalves, M. D. A., Lopes, T. T., Marques, E. Q., Mendonça, N. G., Mendonça, N. G., Noleto, P. T., Oliveira, C. H. L., Oliveira, M. A., Pireda, S., Santos Prestes, N. C. C., Santos, D. M., Santos, E. B., Silva, E. L. S., Souza, I. A., Souza, L. J., Vitória, A. P., Foyer, C. H., and Galbraith, D.: Photosynthetic quantum efficiency in South-Eastern Amazonian trees may be already affected by climate change, Plant Cell Environ., 44, 2428–2439, https://doi.org/10.1111/pce.13770, 2021.
van der Tol, C., Berry, J. A., Campbell, P. K. E., and Rascher, U.: Models of fluorescence and photosynthesis for interpreting measurements of solar-induced chlorophyll fluorescence, J. Geophys. Res.-Biogeo., 119, 2312–2327, https://doi.org/10.1002/2014JG002713, 2014.
Verhoeven, A. S., Adams, W. W., III, Demmig-Adams, B., Croce, R., and Bassi, R.: Xanthophyll Cycle Pigment Localization and Dynamics during Exposure to Low Temperatures and Light Stress in Vinca major, Plant Physiol., 120, 727–738, https://doi.org/10.1104/pp.120.3.727, 1999.
Viovy, N.: CRUNCEP Version 7 – Atmospheric forcing data for the community land model, Research Data Archive at the National Center for Atmospheric Research [dataset], https://rda.ucar.edu/datasets/ds314.3/ (last access: 15 September 2021), 2018.
Wahid, A., Gelani, S., Ashraf, M., and Foolad, M.: Heat tolerance in plants: An overview, Environ. Exp. Bot., 61, 199–223, https://doi.org/10.1016/j.envexpbot.2007.05.011, 2007.
Whatley, F. R., Tagawa, K., and Arnon, D. I.: Separation of the Light and Dark Reactions in Electron Transfer During Photosynthesis, P. Natl. Acad. Sci. USA, 49, 266–270, https://doi.org/10.1073/pnas.49.2.266, 1963.
Williams-Linera, G.: Phenology of deciduous and broadleaved-evergreen tree species in a Mexican tropical lower montane forest, Global Ecol. Biogeogr., 6, 115–127, https://doi.org/10.2307/2997568, 1997.
Wittmann, C. and Pfanz, H.: Temperature dependency of bark photosynthesis in beech (Fagus sylvatica L.) and birch (Betula pendula Roth.) trees, J. Exp. Bot., 58, 4293–4306, https://doi.org/10.1093/jxb/erm313, 2007.
Wobbrock, J. O., Findlater, L., Gergle, D., and Higgins, J. J.: The aligned rank transform for nonparametric factorial analyses using only anova procedures, in: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '11: CHI Conference on Human Factors in Computing Systems, Vancouver BC Canada, 143–146, https://doi.org/10.1145/1978942.1978963, 2011.
Yang, P., Prikaziuk, E., Verhoef, W., and van der Tol, C.: SCOPE 2.0: a model to simulate vegetated land surface fluxes and satellite signals, Geosci. Model Dev., 14, 4697–4712, https://doi.org/10.5194/gmd-14-4697-2021, 2021.
Yin, X., Busch, F. A., Struik, P. C., and Sharkey, T. D.: Evolution of a biochemical model of steady-state photosynthesis, Plant Cell Environ., 44, 2811–2837, https://doi.org/10.1111/pce.14070, 2021.
Zhang, Y. and Ye, A.: Would the obtainable gross primary productivity (GPP) products stand up? A critical assessment of 45 global GPP products, Sci. Total Environ., 783, 146965, https://doi.org/10.1016/j.scitotenv.2021.146965, 2021.
Zhou, R., Yu, X., Kjær, K. H., Rosenqvist, E., Ottosen, C.-O., and Wu, Z.: Screening and validation of tomato genotypes under heat stress using Fv/Fm to reveal the physiological mechanism of heat tolerance, Environ. Exp. Bot., 118, 1–11, https://doi.org/10.1016/j.envexpbot.2015.05.006, 2015.
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Temperature responses of plant photosynthesis are increasingly crucial under the climatic warming. This paper provides a new parameterization of the temperature response of a core mechanism of plant photosynthesis, photosystem II efficiency, to not only instantaneous but also middle- to long-term temperature variation, so-called acclimation. The authors provided response functions for each plant functional type, allowing researchers to implement them in their land vegetation models with a biochemical photosynthesis scheme. Using the new parameterization would effectively improve the simulation accuracy of plant responses, including tolerance and resilience, to climatic change. This study has implications for studies on plant physiology, remote sensing (SIF), biogeochemistry, and ecosystem/earth system models.
Temperature responses of plant photosynthesis are increasingly crucial under the climatic...
Short summary
A first-of-its-kind global-scale model of temperature resilience and tolerance of photosystem II maximum quantum yield informs how plants maintain their efficiency of converting light energy to chemical energy for photosynthesis under temperature changes. Our finding explores this variation across plant functional types and habitat climatology, highlighting diverse temperature response strategies and a method to improve global-scale photosynthesis modeling under climate change.
A first-of-its-kind global-scale model of temperature resilience and tolerance of photosystem II...
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