Articles | Volume 18, issue 13
https://doi.org/10.5194/bg-18-4143-2021
© Author(s) 2021. 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-18-4143-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Jul 2021
Research article |
| 13 Jul 2021
| 13 Jul 2021
A novel representation of biological nitrogen fixation and competitive dynamics between nitrogen-fixing and non-fixing plants in a land model (GFDL LM4.1-BNF)
Department of Ecology, Evolution and Environmental Biology, Columbia University, New York, 10027, USA
Sergey Malyshev
Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Princeton, 08540, USA
Isabel Martínez Cano
Department of Ecology and Evolutionary Biology, Princeton University, Princeton, 08544, USA
Stephen W. Pacala
Department of Ecology and Evolutionary Biology, Princeton University, Princeton, 08544, USA
Elena Shevliakova
Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Princeton, 08540, USA
Thomas A. Bytnerowicz
Department of Integrative Biology, The University of Texas, Austin, 78712, USA
Duncan N. L. Menge
Department of Ecology, Evolution and Environmental Biology, Columbia University, New York, 10027, USA
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Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
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Bing Pu, Paul Ginoux, Huan Guo, N. Christina Hsu, John Kimball, Beatrice Marticorena, Sergey Malyshev, Vaishali Naik, Norman T. O'Neill, Carlos Pérez García-Pando, Juliette Paireau, Joseph M. Prospero, Elena Shevliakova, and Ming Zhao
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Ensheng Weng, Ray Dybzinski, Caroline E. Farrior, and Stephen W. Pacala
Biogeosciences, 16, 4577–4599, https://doi.org/10.5194/bg-16-4577-2019, https://doi.org/10.5194/bg-16-4577-2019, 2019
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Our study illustrates that the competition processes for light and soil resources in a game-theoretic vegetation demographic model can substantially change the prediction of the contribution of ecosystems to the global carbon cycle. The model that tracks the competitive allocation strategies can generate significantly different ecosystem-level predictions than those with fixed allocation strategies.
Isabel Martínez Cano, Helene C. Muller-Landau, S. Joseph Wright, Stephanie A. Bohlman, and Stephen W. Pacala
Biogeosciences, 16, 847–862, https://doi.org/10.5194/bg-16-847-2019, https://doi.org/10.5194/bg-16-847-2019, 2019
Fabien Paulot, Sergey Malyshev, Tran Nguyen, John D. Crounse, Elena Shevliakova, and Larry W. Horowitz
Atmos. Chem. Phys., 18, 17963–17978, https://doi.org/10.5194/acp-18-17963-2018, https://doi.org/10.5194/acp-18-17963-2018, 2018
Nathaniel W. Chaney, Marjolein H. J. Van Huijgevoort, Elena Shevliakova, Sergey Malyshev, Paul C. D. Milly, Paul P. G. Gauthier, and Benjamin N. Sulman
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Sam S. Rabin, Daniel S. Ward, Sergey L. Malyshev, Brian I. Magi, Elena Shevliakova, and Stephen W. Pacala
Geosci. Model Dev., 11, 815–842, https://doi.org/10.5194/gmd-11-815-2018, https://doi.org/10.5194/gmd-11-815-2018, 2018
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This paper describes a new fire model that for the first time simulates how fire is used on cropland and pasture in the modern day, as imposed using a recently developed dataset. A non-agricultural fire module is fit algorithmically against non-agricultural burned area. Fitting improves performance and the general global pattern of fire is represented, but some gaps remain. The novel separation of agricultural burning from other fire may necessitate new design thinking in the future.
David M. Lawrence, George C. Hurtt, Almut Arneth, Victor Brovkin, Kate V. Calvin, Andrew D. Jones, Chris D. Jones, Peter J. Lawrence, Nathalie de Noblet-Ducoudré, Julia Pongratz, Sonia I. Seneviratne, and Elena Shevliakova
Geosci. Model Dev., 9, 2973–2998, https://doi.org/10.5194/gmd-9-2973-2016, https://doi.org/10.5194/gmd-9-2973-2016, 2016
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Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The goal of LUMIP is to take the next steps in land-use change science, and enable, coordinate, and ultimately address the most important land-use science questions in more depth and sophistication than possible in a multi-model context to date.
S. S. Rabin, B. I. Magi, E. Shevliakova, and S. W. Pacala
Biogeosciences, 12, 6591–6604, https://doi.org/10.5194/bg-12-6591-2015, https://doi.org/10.5194/bg-12-6591-2015, 2015
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People worldwide use fire to manage agriculture, but often also suppress fire in the landscape surrounding their fields. Here, we estimate the net result of these effects of cropland and pasture on fire at a regional, monthly level. Pasture is shown, for the first time, to contribute strongly to global patterns of burning. Our results could be used to improve representations of burning in global vegetation and climate models, improving our understanding of how people affect the Earth system.
E. S. Weng, S. Malyshev, J. W. Lichstein, C. E. Farrior, R. Dybzinski, T. Zhang, E. Shevliakova, and S. W. Pacala
Biogeosciences, 12, 2655–2694, https://doi.org/10.5194/bg-12-2655-2015, https://doi.org/10.5194/bg-12-2655-2015, 2015
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We present a model, LM3-PPA, which simulates vegetation dynamics and biogeochemical processes by explicitly scaling from individual plants to ecosystems using the perfect plasticity approximation. It includes height-structured competition for light- and root-allocation-dependent competition for belowground resources. Because of the tractability of the PPA, the coupled LM3-PPA model is able to retain computational tractability, as well as close linkages to mathematically tractable special cases.
M. Lee, S. Malyshev, E. Shevliakova, P. C. D. Milly, and P. R. Jaffé
Biogeosciences, 11, 5809–5826, https://doi.org/10.5194/bg-11-5809-2014, https://doi.org/10.5194/bg-11-5809-2014, 2014
Z. M. Subin, P. C. D. Milly, B. N. Sulman, S. Malyshev, and E. Shevliakova
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-8443-2014, https://doi.org/10.5194/hessd-11-8443-2014, 2014
Preprint withdrawn
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We provide a framework for including the effects of fine-scale hydrology on biogeochemistry in Earth-system models (ESMs). We simulate a representative hillslope in each ESM grid cell. While including the hillslope does not change the average hydrology, it causes greater vegetation and soil carbon to accumulate in lowlands. This is important for understanding how soil carbon might be affected by climate change, particularly in wetlands.
K. E. O. Todd-Brown, J. T. Randerson, F. Hopkins, V. Arora, T. Hajima, C. Jones, E. Shevliakova, J. Tjiputra, E. Volodin, T. Wu, Q. Zhang, and S. D. Allison
Biogeosciences, 11, 2341–2356, https://doi.org/10.5194/bg-11-2341-2014, https://doi.org/10.5194/bg-11-2341-2014, 2014
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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.
Patrick Neri, Lianhong Gu, and Yang Song
Biogeosciences, 21, 2731–2758, https://doi.org/10.5194/bg-21-2731-2024, https://doi.org/10.5194/bg-21-2731-2024, 2024
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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.
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.
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.
Erik Schwarz, Samia Ghersheen, Salim Belyazid, and Stefano Manzoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-348, https://doi.org/10.5194/egusphere-2024-348, 2024
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Occurrence of unstable equilibrium points (EPs) could impede applicability of microbial-explicit soil organic carbon models. For archetypal model versions we identified 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.
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.
Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
EGUsphere, https://doi.org/10.5194/egusphere-2023-3032, https://doi.org/10.5194/egusphere-2023-3032, 2024
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In this study, ecosystem COS fluxes data were employed to optimize GPP estimation across various ecosystems with the Boreal Ecosystem Productivity Simulator (BEPS), which was further developed for simulating the leaf COS uptake under its state-of-the-art ‘two-leaf’ framework. our results showcased the efficacy of COS in enhancing model prediction and reducing prediction uncertainty of GPP, and deepened insights into the sensitivity, identifiability, and interactions of parameters related to COS.
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.
Sian Kou-Giesbrecht, Vivek Arora, Christian Seiler, and Libo Wang
EGUsphere, https://doi.org/10.5194/egusphere-2023-2711, https://doi.org/10.5194/egusphere-2023-2711, 2023
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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.
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2023-1952, https://doi.org/10.5194/egusphere-2023-1952, 2023
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Understanding the link between climate and carbon fluxes is crucial in predicting how climate change will impact carbon sinks. We estimated CO2 fluxes from deadwood in tropical Australia using wood microclimate variables (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.
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2023-1738, https://doi.org/10.5194/egusphere-2023-1738, 2023
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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 needed adjustments, DayCent could adequately represent the measured mean yields, soil carbon stock changes, and N2O emissions. Our results showed that soil fertility losses could be reduced with ISFM and that, while N2O emissions increased with ISFM, emissions per kg of yield decreased.
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.
Bailu Zhao and Qianlai Zhuang
Biogeosciences, 20, 251–270, https://doi.org/10.5194/bg-20-251-2023, https://doi.org/10.5194/bg-20-251-2023, 2023
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In this study, we use a process-based model to simulate the northern peatland's C dynamics in response to future climate change during 1990–2300. Northern peatlands are projected to be a C source under all climate scenarios except for the mildest one before 2100 and C sources under all scenarios afterwards.
We find northern peatlands are a C sink until pan-Arctic annual temperature reaches −2.09 to −2.89 °C. This study emphasizes the vulnerability of northern peatlands to climate change.
Lin Yu, Silvia Caldararu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, Julian Helfenstein, Chiara Pistocchi, and Sönke Zaehle
Biogeosciences, 20, 57–73, https://doi.org/10.5194/bg-20-57-2023, https://doi.org/10.5194/bg-20-57-2023, 2023
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In this study, we addressed a key weakness in current ecosystem models regarding the phosphorus exchange in the soil and developed a new scheme to describe this process. We showed that the new scheme improved the model performance for plant productivity, soil organic carbon, and soil phosphorus content at five beech forest sites in Germany. We claim that this new model could be used as a better tool to study ecosystems under future climate change, particularly phosphorus-limited systems.
Bimal K. Bhattacharya, Kaniska Mallick, Devansh Desai, Ganapati S. Bhat, Ross Morrison, Jamie R. Clevery, William Woodgate, Jason Beringer, Kerry Cawse-Nicholson, Siyan Ma, Joseph Verfaillie, and Dennis Baldocchi
Biogeosciences, 19, 5521–5551, https://doi.org/10.5194/bg-19-5521-2022, https://doi.org/10.5194/bg-19-5521-2022, 2022
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Evaporation retrieval in heterogeneous ecosystems is challenging due to empirical estimation of ground heat flux and complex parameterizations of conductances. We developed a parameter-sparse coupled ground heat flux-evaporation model and tested it across different limits of water stress and vegetation fraction in the Northern/Southern Hemisphere. The model performed particularly well in the savannas and showed good potential for evaporative stress monitoring from thermal infrared satellites.
Jie Zhang, Wenxin Zhang, Per-Erik Jansson, and Søren O. Petersen
Biogeosciences, 19, 4811–4832, https://doi.org/10.5194/bg-19-4811-2022, https://doi.org/10.5194/bg-19-4811-2022, 2022
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In this study, we relied on a properly controlled laboratory experiment to test the model’s capability of simulating the dominant microbial processes and the emissions of one greenhouse gas (nitrous oxide, N2O) from agricultural soils. This study reveals important processes and parameters that regulate N2O emissions in the investigated model framework and also suggests future steps of model development, which have implications on the broader communities of ecosystem modelers.
Jan De Pue, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Manuela Balzarolo, Fabienne Maignan, and Françoise Gellens-Meulenberghs
Biogeosciences, 19, 4361–4386, https://doi.org/10.5194/bg-19-4361-2022, https://doi.org/10.5194/bg-19-4361-2022, 2022
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The functioning of ecosystems involves numerous biophysical processes which interact with each other. Land surface models (LSMs) are used to describe these processes and form an essential component of climate models. In this paper, we evaluate the performance of three LSMs and their interactions with soil moisture and vegetation. Though we found room for improvement in the simulation of soil moisture and drought stress, the main cause of errors was related to the simulated growth of vegetation.
Jarmo Mäkelä, Laura Arppe, Hannu Fritze, Jussi Heinonsalo, Kristiina Karhu, Jari Liski, Markku Oinonen, Petra Straková, and Toni Viskari
Biogeosciences, 19, 4305–4313, https://doi.org/10.5194/bg-19-4305-2022, https://doi.org/10.5194/bg-19-4305-2022, 2022
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Soils account for the largest share of carbon found in terrestrial ecosystems, and accurate depiction of soil carbon decomposition is essential in understanding how permanent these carbon storages are. We present a straightforward way to include carbon isotope concentrations into soil decomposition and carbon storages for the Yasso model, which enables the model to use 13C as a natural tracer to track changes in the underlying soil organic matter decomposition.
Vasileios Myrgiotis, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 19, 4147–4170, https://doi.org/10.5194/bg-19-4147-2022, https://doi.org/10.5194/bg-19-4147-2022, 2022
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This study shows that livestock grazing and grass cutting can determine whether a grassland is adding (source) or removing (sink) carbon (C) to/from the atmosphere. The annual C balance of 1855 managed grassland fields in Great Britain was quantified for 2017–2018 using process modelling and earth observation data. The examined fields were, on average, small C sinks, but the summer drought of 2018 led to a 9-fold increase in the number of fields that became C sources in 2018 compared to 2017.
J. Robert Logan, Kathe E. Todd-Brown, Kathryn M. Jacobson, Peter J. Jacobson, Roland Vogt, and Sarah E. Evans
Biogeosciences, 19, 4129–4146, https://doi.org/10.5194/bg-19-4129-2022, https://doi.org/10.5194/bg-19-4129-2022, 2022
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Understanding how plants decompose is important for understanding where the atmospheric CO2 they absorb ends up after they die. In forests, decomposition is controlled by rain but not in deserts. We performed a 2.5-year study in one of the driest places on earth (the Namib desert in southern Africa) and found that fog and dew, not rainfall, closely controlled how quickly plants decompose. We also created a model to help predict decomposition in drylands with lots of fog and/or dew.
Carlos A. Sierra, Verónika Ceballos-Núñez, Henrik Hartmann, David Herrera-Ramírez, and Holger Metzler
Biogeosciences, 19, 3727–3738, https://doi.org/10.5194/bg-19-3727-2022, https://doi.org/10.5194/bg-19-3727-2022, 2022
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Empirical work that estimates the age of respired CO2 from vegetation tissue shows that it may take from years to decades to respire previously produced photosynthates. However, many ecosystem models represent respiration processes in a form that cannot reproduce these observations. In this contribution, we attempt to provide compelling evidence, based on recent research, with the aim to promote a change in the predominant paradigm implemented in ecosystem models.
César Dionisio Jiménez-Rodríguez, Mauro Sulis, and Stanislaus Schymanski
Biogeosciences, 19, 3395–3423, https://doi.org/10.5194/bg-19-3395-2022, https://doi.org/10.5194/bg-19-3395-2022, 2022
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Vegetation relies on soil water reservoirs during dry periods. However, when this source is depleted, the plants may access water stored deeper in the rocks. This rock moisture contribution is usually omitted in large-scale models, which affects modeled plant water use during dry periods. Our study illustrates that including this additional source of water in the Community Land Model improves the model's ability to reproduce observed plant water use at seasonally dry sites.
Cited articles
Adams, M. A., Turnbull, T. L., Sprent, J. I., and Buchmann, N.: Legumes are different: Leaf nitrogen, photosynthesis, and water use efficiency, P. Natl. Acad. Sci. USA, 113, 4098–4103, https://doi.org/10.1073/pnas.1523936113, 2016.
Anderson-Teixeira, K. J., Wang, M. M. H., McGarvey, J. C., Herrmann, V., Tepley, A. J., Bond-Lamberty, B., and LeBauer, D. S.: ForC: a global database of forest carbon stocks and fluxes, Ecology, 99, 1507, https://doi.org/10.1002/ecy.2229, 2018.
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., Krasting, J. P., Law, R. M., Lawrence, D. M., Lenton, A., Lindsay, K., Pongratz, J., Raddatz, T., Séférian, R., Tachiiri, K., Tjiputra, J. F., Wiltshire, A., Wu, T., and Ziehn, T.: Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models, Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, 2020.
Asner, G. P., Scurlock, J. M. O., and Hicke, J. A.: Global synthesis of leaf area index observations: implications for ecological and remote sensing studies, Global Ecol. Biogeogr., 12, 191–205, 2003.
Averill, C., Bhatnagar, J. M., Dietze, M. C., Pearse, W. D., and Kivlin, S. N.: Global imprint of mycorrhizal fungi on whole-plant nutrient economics, P. Natl. Acad. Sci. USA, 116, 23163–23168, https://doi.org/10.1073/pnas.1906655116, 2019.
Batterman, S. A., Hedin, L. O., van Breugel, M., Ransijn, J., Craven, D. J., and Hall, J. S.: Key role of symbiotic dinitrogen fixation in tropical forest secondary succession, Nature, 502 , 224–227, https://doi.org/10.1038/nature12525, 2013.
Binkley, D., Sollins, P.,
Bell, R., Sachs, D., and Myrold, D.: Biogeochemistry of adjacent conifer and alder‐conifer stands, Ecology, 73, 2022–2033, 1992.
Boring, L. R. and Swank, W. T.: The Role of Black Locust (Robinia Pseudo-Acacia) in Forest Succession, J. Ecol., 72, 749–766, 1984.
Bytnerowicz, T. A., Akana, P. R., Griffin, K. L., and Menge, D. N. L.: The temperature sensitivity of woody dinitrogen fixation across species and growing temperatures, in review, 2021.
Canarini, A., Kaiser, C., Merchant, A., Richter, A., and Wanek, W.: Root exudation of primary metabolites: Mechanisms and their roles in plant responses to environmental stimuli, Front. Plant Sci., 10, 1–19, https://doi.org/10.3389/fpls.2019.00157, 2019.
Chan, Y. K.: Temperature response of an associative N2-fixing Pseudomonas species in pure culture, Can. J. Microbiol., 37, 715–718, https://doi.org/10.1139/m91-122, 1991.
Chapin, D. M., Bliss, L. C., and Bledsoe, L. J.: Environmental regulation of nitrogen fixation in a high arctic lowland ecosystem, Can. J. Botany, 69, 2744–2755, https://doi.org/10.1139/b91-345, 1991.
Chapin, F. S., Matson, P. A., and Vitousek, P. M.: Principles of Terrestrial Ecosystem Ecology, Springer Science & Business Media, New York, NY, 2011.
Chapin III, F. S., Walker, L. R., Fastie, C. L., and Sharman, L. C.: Mechanisms of Primary Succession Following Deglaciation at Glacier Bay, Alaska, Ecol. Monogr., 64, 149–175, 1994.
Chapin III, F. S., Conway, A. J., Johnstone, J. F., Hollingsworth, T. N., and Hollingsworth, J.: Absence of net long-term successional facilitation by alder in a boreal Alaska floodplain, Ecology, 97, 2986–2997, https://doi.org/10.1002/ecy.1529, 2016.
Cheng, W., Parton, W. J., Gonzalez-Meler, M. A., Phillips, R., Asao, S., Mcnickle, G. G., Brzostek, E., and Jastrow, J. D.: Synthesis and modeling perspectives of rhizosphere priming, New Phytol., 201, 31–44, https://doi.org/10.1111/nph.12440, 2014.
Cierjacks, A., Kowarik, I., Joshi, J., Hempel, S., Ristow, M., von der Lippe, M., and Weber, E.: Biological flora of the british isles: Robinia pseudoacacia, J. Ecol., 101, 1623–1640, https://doi.org/10.1111/1365-2745.12162, 2013.
Cleveland, C. C., Townsend, A. R., Schimel, D. S., Fisher, H., Hedin, L. O., Perakis, S., Latty, E. F., Von Fischer, C., Elseroad, A., and Wasson, M. F.: Global patterns of terrestrial biological nitrogen (N2) fixation in natural ecosystems, Global Biochem. Cy., 13, 623–645, https://doi.org/10.1029/1999GB900014, 1999.
Coxson, D. S. and Kershaw, K. A.: Rehydration response of nitrogenase activity and carbon fixation in terrestrial Nostoc commune from Stipa-Bouteola grassland, Can. J. Botany, 61, 2658–2668, https://doi.org/10.1139/b83-293, 1983.
Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., Smith, J. R., Hintler, G., Duguid, M. C., Amatulli, G., Tuanmu, M.-N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S. J., Wiser, S. K., Huber, M. O., Hengeveld, G. M., Nabuurs, G.-J., Tikhonova, E., Borchardt, P., Li, C.-F., Powrie, L. W., Fischer, M., Hemp, A., Homeier, J., Cho, P., Vibrans, A. C., Umunay, P. M., Piao, S. L., Rowe, C. W., Ashton, M. S., Crane, P. R., and Bradford, M. A.: Mapping tree density at a global scale, Nature, 525, 201–205, https://doi.org/10.1038/nature14967, 2015.
Davies-Barnard, T. and Friedlingstein, P.: The Global Distribution of Biological Nitrogen Fixation in Terrestrial Natural Ecosystems, Global Biogeochem. Cy., 34, 1–17, https://doi.org/10.1029/2019GB006387, 2020.
Davies-Barnard, T., Meyerholt, J., Zaehle, S., Friedlingstein, P., Brovkin, V., Fan, Y., Fisher, R. A., Jones, C. D., Lee, H., Peano, D., Smith, B., Wårlind, D., and Wiltshire, A. J.: Nitrogen cycling in CMIP6 land surface models: progress and limitations, Biogeosciences, 17, 5129–5148, https://doi.org/10.5194/bg-17-5129-2020, 2020.
DeLuca, T. H., Zackrisson, O., Nilsson, M.-C., and Sellstedt, A.: Quantifying nitrogen-fixation in feather moss carpets of boreal forests, Nature, 419, 917–920, https://doi.org/10.1038/nature01051, 2002.
Dentener, F. J.: Global Maps of Atmospheric Nitrogen Deposition, 1860, 1993, and 2050, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/830, 2006.
Dlugokencky, E. and Tans, P.: Trends in atmospheric carbon dioxide, online, available at: https://www.esrl.noaa.gov/gmd/ccgg/trends/gl_data.html (last access: November 2019), 2020.
Elser, J. J., Bracken, M. E. S., Cleland, E. E., Gruner, D. S., Harpole, W. S., Hillebrand, H., Ngai, J. T., Seabloom, E. W., Shurin, J. B., and Smith, J. E.: Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems, Ecol. Lett., 10, 1135–1142, https://doi.org/10.1111/j.1461-0248.2007.01113.x, 2007.
Finzi, A. C., Abramoff, R. Z., Spiller, K. S., Brzostek, E. R., Darby, B. A., Kramer, M. A., and Phillips, R. P.: Rhizosphere processes are quantitatively important components of terrestrial carbon and nutrient cycles, Glob. Change Biol., 21, 2082–2094, https://doi.org/10.1111/gcb.12816, 2015.
Fowler, D., Coyle, M., Skiba, U., Sutton, M. A., Cape, J. N., Reis, S., Sheppard, L. J., Jenkins, A., Grizzetti, B., Galloway, J. N., Vitousek, P., Leach, A., Bouwman, A. F., Butterbach-Bahl, K., Dentener, F., Stevenson, D., Amann, M., and Voss, M.: The global nitrogen cycle in the twenty-first century, Philos. T. R. Soc. B, 368, 20130164, https://doi.org/10.1098/rstb.2013.0164, 2013.
Goll, D. S., Winkler, A. J., Raddatz, T., Dong, N., Prentice, I. C., Ciais, P., and Brovkin, V.: Carbon–nitrogen interactions in idealized simulations with JSBACH (version 3.10), Geosci. Model Dev., 10, 2009–2030, https://doi.org/10.5194/gmd-10-2009-2017, 2017.
Gutschick, V. P.: Evolved Strategies in Nitrogen Acquisition by Plants, Am. Nat., 118, 607–637, 1981.
Haverd, V., Smith, B., Nieradzik, L., Briggs, P. R., Woodgate, W., Trudinger, C. M., Canadell, J. G., and Cuntz, M.: A new version of the CABLE land surface model (Subversion revision r4601) incorporating land use and land cover change, woody vegetation demography, and a novel optimisation-based approach to plant coordination of photosynthesis, Geosci. Model Dev., 11, 2995–3026, https://doi.org/10.5194/gmd-11-2995-2018, 2018.
Hoch, G., Richter, A., and Körner, C.: Non-structural carbon compounds in temperate forest trees, Plant Cell Environ., 26, 1067–1081, https://doi.org/10.1046/j.0016-8025.2003.01032.x, 2003.
Houlton, B. Z., Wang, Y. P., Vitousek, P. M., and Field, C. B.: A unifying framework for dinitrogen fixation in the terrestrial biosphere, Nature, 454, 327–330, https://doi.org/10.1038/nature07028, 2008.
Huang, Y. and Gerber, S.: Global soil nitrous oxide emissions in a dynamic carbon-nitrogen model, Biogeosciences, 12, 6405–6427, https://doi.org/10.5194/bg-12-6405-2015, 2015.
Hulvey, K. B., Hobbs, R. J., Standish, R. J., Lindenmayer, D. B., Lach, L., and Perring, M. P.: Benefits of tree mixes in carbon plantings, Nat. Clim. Change, 3, 869–874, https://doi.org/10.1038/nclimate1862, 2013.
Jackson, R. B., Mooney, H. A., and Schulze, E.-D.: A global budget for fine root biomass, surface area, and nutrient contents, P. Natl. Acad. Sci. USA, 94, 7362–7366, 1997.
Johnson, N. C.: Resource Stoichiometry Elucidates the Structure and Function of Arbuscular Mycorrhizas across Scales, New Phytol., 185, 631–647, https://doi.org/10.1111/j.1469-8137.2009.03110.x, 2010.
Jones, D. L., Nguyen, C., and Finlay, R. D.: Carbon flow in the rhizosphere: Carbon trading at the soil-root interface, Plant Soil, 321, 5–33, https://doi.org/10.1007/s11104-009-9925-0, 2009.
Kattge, J., Bönisch, G., Díaz, S., et al.: TRY plant trait database–enhanced coverage and open access, Glob. Change Biol., 26, 119–188, 2020.
Knoepp, J.: Measurements of Soil Bulk Density at the Coweeta Terrestrial Gradient Sites, online, available at: https://coweeta.uga.edu/ResearchData.html (last access: November 2019), 2009a.
Knoepp, J.: Measurements of Soil Nitrogen Transformations at the Coweeta Terrestrial Gradient Sites, online, available at: https://coweeta.uga.edu/ResearchData.html (last access: November 2019), 2009b.
Knoepp, J.: Measurements of Soil %C and %N at the Coweeta Terrestrial Gradient Sites, online, available at: https://coweeta.uga.edu/ResearchData.html (last access: November 2019), 2018.
Kou-Giesbrecht, S. and Menge, D. N. L.: Nitrogen-fixing trees increase soil nitrous oxide emissions: a meta-analysis, Ecology, accepted, https://doi.org/10.1002/ecy.3415, 2021.
Lai, H. R., Hall, J. S., Batterman, S. A., Turner, B. L., and van Breugel, M.: Nitrogen fixer abundance has no effect on biomass recovery during tropical secondary forest succession, J. Ecol., 106, 1415–1427, https://doi.org/10.1111/1365-2745.12979, 2018.
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.
LeBauer, D. S. and Treseder, K. K.: Nitrogen Limitation of Net Primary Productivity in Terrestrial Ecosystems is Globally Distributed, Ecology, 89, 371–379, https://doi.org/10.1016/j.agee.2013.04.020, 2008.
Levy-Varon, J. H., Batterman, S. A., Medvigy, D., Hall, J. S., Van Breugel, M., and Hedin, L. O.: Tropical carbon sink accelerated by symbiotic dinitrogen fixation, Nat. Commun., 10, 1–8, https://doi.org/10.1038/s41467-019-13656-7, 2019.
Liang, J., Qi, X., Souza, L., and Luo, Y.: Processes regulating progressive nitrogen limitation under elevated carbon dioxide: a meta-analysis, Biogeosciences, 13, 2689–2699, https://doi.org/10.5194/bg-13-2689-2016, 2016.
Liengen, T. and Olsen, R. A.: Seasonal and site-specific variations in nitrogen fixation in a high arctic area, Ny-Alesund, Spitsbergen, Can. J. Microbiol., 43, 759–769, https://doi.org/10.1139/m97-109, 1997.
Martinez Cano, I., Shevliakova, E., Malyshev, S., Wright, S. J., Detto, M., Pacala, S. W., and Muller-Landau, H. C.: Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA-TV), Glob. Change Biol., 26, 4478–4494, https://doi.org/10.1111/gcb.15188, 2020.
Medlyn, B. E., Dreyer, E., Ellsworth, D., Forstreuter, M., Harley, P. C., Kirschbaum, M. U. F., Le Roux, X., Montpied, P., Strassemeyer, J., Walcroft, A., Wang, K., and Loustau, D.: Temperature response of parameters of a biochemically based model of photosynthesis. II. A review of experimental data, Plant Cell Environ., 25, 1167–1179, https://doi.org/10.1046/j.1365-3040.2002.00891.x, 2002.
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.-Biogeo., 114, G01002, https://doi.org/10.1029/2008JG000812, 2009.
Meerts, P.: Mineral nutrient concentrations in sapwood and heartwood: a literature review, Ann. For. Sci., 59, 713–722, 2002.
Meinshausen, M., Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D. M., Fraser, P. J., Montzka, S. A., Rayner, P. J., Trudinger, C. M., Krummel, P. B., Beyerle, U., Canadell, J. G., Daniel, J. S., Enting, I. G., Law, R. M., Lunder, C. R., O'Doherty, S., Prinn, R. G., Reimann, S., Rubino, M., Velders, G. J. M., Vollmer, M. K., Wang, R. H. J., and Weiss, R.: Historical greenhouse gas concentrations for climate modelling (CMIP6), Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, 2017.
Menge, D. N. L. and Hedin, L. O.: Nitrogen Fixation in Different Biogeochemical Niches along a 120 000-Year Chronosequence in New Zealand, Ecology, 90, 2190–2201, 2009.
Menge, D. N. L., Denoyer, J. L., and Lichstein, J. W.: Phylogenetic constraints do not explain the rarity of nitrogen-fixing trees in late-successional temperate forests, PLoS One, 5, e12056, https://doi.org/10.1371/journal.pone.0012056, 2010.
Menge, D. N. L., Wolf, A. A., and Funk, J. L.: Diversity of nitrogen fixation strategies in Mediterranean legumes, Nat. Plants, 1, 1–5, https://doi.org/10.1038/nplants.2015.64, 2015.
Menge, D. N. L., Chisholm, R. A., Davies, S. J., Abu Salim, K., Allen, D., Alvarez, M., Bourg, N., Brockelman, W. Y., Bunyavejchewin, S., Butt, N., Cao, M., Chanthorn, W., Chao, W. C., Clay, K., Condit, R., Cordell, S., da Silva, J. B., Dattaraja, H. S., de Andrade, A. C. S., de Oliveira, A. A., den Ouden, J., Drescher, M., Fletcher, C., Giardina, C. P., Savitri Gunatilleke, C. V., Gunatilleke, I. A. U. N., Hau, B. C. H., He, F., Howe, R., Hsieh, C. F., Hubbell, S. P., Inman-Narahari, F. M., Jansen, P. A., Johnson, D. J., Kong, L. S., Král, K., Ku, C. C., Lai, J., Larson, A. J., Li, X., Li, Y., Lin, L., Lin, Y. C., Liu, S., Lum, S. K. Y., Lutz, J. A., Ma, K., Malhi, Y., McMahon, S., McShea, W., Mi, X., Morecroft, M., Myers, J. A., Nathalang, A., Novotny, V., Ong, P., Orwig, D. A., Ostertag, R., Parker, G., Phillips, R. P., Abd. Rahman, K., Sack, L., Sang, W., Shen, G., Shringi, A., Shue, J., Su, S. H., Sukumar, R., Sun, I. F., Suresh, H. S., Tan, S., Thomas, S. C., Toko, P. S., Valencia, R., Vallejo, M. I., Vicentini, A., Vrška, T., Wang, B., Wang, X., Weiblen, G. D., Wolf, A., Xu, H., Yap, S., Zhu, L., and Fung, T.: Patterns of nitrogen-fixing tree abundance in forests across Asia and America, J. Ecol., 107, 2598–2610, https://doi.org/10.1111/1365-2745.13199, 2019.
Meyerholt, J., Zaehle, S., and Smith, M. J.: Variability of projected terrestrial biosphere responses to elevated levels of atmospheric CO2 due to uncertainty in biological nitrogen fixation, Biogeosciences, 13, 1491–1518, https://doi.org/10.5194/bg-13-1491-2016, 2016.
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.
Mooney, H. A., Winner, W. E., and Pell, E. J.: Response of plants to multiple stresses, Academic Press, 1991.
Nacry, P., Bouguyon, E., and Gojon, A.: Nitrogen acquisition by roots: Physiological and developmental mechanisms ensuring plant adaptation to a fluctuating resource, Plant Soil, 370, 1–29, https://doi.org/10.1007/s11104-013-1645-9, 2013.
Oishi, A. C.: AmeriFlux US-Cwt Coweeta, Ver. 1-5., https://doi.org/10.17190/AMF/1671890, 2020.
Oswalt, S. N., Smith, W. B., Miles, P. D., and Pugh, S. A.: Forest Resources of the United States, 2017, 2019.
Peng, J., Wang, Y. P., Houlton, B. Z., Dan, L., Pak, B., and Tang, X.: Global Carbon Sequestration Is Highly Sensitive to Model-Based Formulations of Nitrogen Fixation, Global Biogeochem. Cy., 34, e2019GB006296, https://doi.org/10.1029/2019GB006296, 2020.
Phillips, R. P., Brzostek, E., and Midgley, M. G.: The mycorrhizal-associated nutrient economy: A new framework for predicting carbon-nutrient couplings in temperate forests, New Phytol., 199, 41–51, https://doi.org/10.1111/nph.12221, 2013.
Poorter, H., Niinemets, Ü., Poorter, L., Wright, I. J., and Villar, R.: Causes and consequences of variation in leaf mass per area (LMA): a meta-analysis, New Phytol., 182, 565–588, https://doi.org/10.1111/j.1469-8137.2008.02681.x, 2009.
Poorter, H., Niklas, K. J., Reich, P. B., Oleksyn, J., Poot, P., and Mommer, L.: Biomass allocation to leaves, stems and roots: Meta-analyses of interspecific variation and environmental control, New Phytol., 193, 30–50, https://doi.org/10.1111/j.1469-8137.2011.03952.x, 2012.
Purves, D. W., Lichstein, J. W., Strigul, N., and Pacala, S. W.: Predicting and understanding forest dynamics using a simple tractable model, P. Natl. Acad. Sci. USA, 105, 17018–17022, https://doi.org/10.1073/pnas.0807754105, 2008.
Rastetter, E. B. and Shaver, G. R.: A model of multiple-element limitation for acclimating vegetation, Ecology, 73, 1157–1174, https://doi.org/10.2307/1940666, 1992.
Reay, D. S., Dentener, F. J., Smith, P., Grace, J., and Feely, R. A.: Global nitrogen deposition and carbon sinks, Nat. Geosci., 1, 430–437, https://doi.org/10.1038/ngeo230, 2008.
Reed, S. C., Cleveland, C. C., and Townsend, A. R.: Functional Ecology of Free-Living Nitrogen Fixation: A Contemporary Perspective, Annu. Rev. Ecol. Evol. S., 42, 489–512, https://doi.org/10.1146/annurev-ecolsys-102710-145034, 2011.
Richardson, A. D., Carbone, M. S., Keenan, T. F., Czimczik, C. I., Hollinger, D. Y., Murakami, P., Schaberg, P. G., and Xu, X.: Seasonal dynamics and age of stemwood nonstructural carbohydrates in temperate forest trees, New Phytol., 197, 850–861, https://doi.org/10.1111/nph.12042, 2013.
Roper, M. M.: Straw decomposition and nitrogenase activity (C2H2 reduction): Effects of soil moisture and temperature, Soil Biol. Biochem., 17, 65–71, https://doi.org/10.1016/0038-0717(85)90091-4, 1985.
Roumet, C., Birouste, M., Picon-Cochard, C., Ghestem, M., Osman, N., Vrignon-Brenas, S., Cao, K. F., and Stokes, A.: Root structure-function relationships in 74 species: Evidence of a root economics spectrum related to carbon economy, New Phytol., 210, 815–826, https://doi.org/10.1111/nph.13828, 2016.
Scharlemann, J. P. W., Tanner, E. V. J., Hiederer, R., and Kapos, V.: Global soil carbon: Understanding and managing the largest terrestrial carbon pool, Carbon Manag., 5, 81–91, https://doi.org/10.4155/cmt.13.77, 2014.
Schomberg, H. H. and Weaver, R. W.: Nodulation, Nitrogen Fixation, and Early Growth of Arrowleaf Clover in Response to Root Temperature and Starter Nitrogen, Agron. J., 84, 1046–1050, https://doi.org/10.2134/agronj1992.00021962008400060026x, 1992.
Schulte-Uebbing, L. and de Vries, W.: Global-scale impacts of nitrogen deposition on tree carbon sequestration in tropical, temperate, and boreal forests: A meta-analysis, Glob. Change Biol., 24, e416–e431, https://doi.org/10.1111/gcb.13862, 2018.
Sheffer, E., Batterman, S. A., Levin, S. A., and Hedin, L. O.: Biome-scale nitrogen fixation strategies selected by climatic constraints on nitrogen cycle, Nat. Plants, 1, 1–6, https://doi.org/10.1038/nplants.2015.182, 2015.
Sheffield, J., Goteti, G., and Wood, E. F.: Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling, J. Clim., 19, 3088–3111, https://doi.org/10.1175/JCLI3790.1, 2006.
Shevliakova, E., Malyshev, S., Martinez-Cano, I., Milly, P. C. D., Pacala, S. W., Ginoux, P., Dunne, K. A., Dunne, J. P., Dupuis, C., Findell, K., Ghannam, K., Horowitz, L. W., John, J. G., Knutson, T. R., Krasting, P. J., Naik, V., Zadeh, N., Zeng, F., and Zeng, Y.: The land component LM4.1 of the GFDL Earth System Model ESM4.1: biophysical and biogeochemical processes and interactions with climate, in preparation, 2021.
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, S. E. and Smith, F. A.: Roles of Arbuscular Mycorrhizas in Plant Nutrition and Growth: New Paradigms from Cellular to Ecosystem Scales, Annu. Rev. Plant Biol., 62, 227–250, https://doi.org/10.1146/annurev-arplant-042110-103846, 2011.
Staccone, A., Liao, W., Perakis, S., Compton, J., Clark, C., and Menge, D.: A spatially explicit, empirical estimate of tree-based biological nitrogen fixation in forests of the United States, Global Biogeochem. Cy., 34, e2019GB006241, https://doi.org/10.1029/2019gb006241, 2020.
Staccone, A. P., Kou-Giesbrecht, S., Taylor, B. N., and Menge, D. N. L.: Nitrogen-fixing trees have no net effect on forest growth in the coterminous United States, J. Ecol., 109, 877–887, https://doi.org/10.1111/1365-2745.13513, 2021.
Stehfest, E. and Bouwman, L.: N2O and NO emission from agricultural fields and soils under natural vegetation: Summarizing available measurement data and modeling of global annual emissions, Nutr. Cycl. Agroecosy., 74, 207–228, https://doi.org/10.1007/s10705-006-9000-7, 2006.
Stocker, B. D., Prentice, I. C., Cornell, S. E., Davies-Barnard, T., Finzi, A. C., Franklin, O., Janssens, I., Larmola, T., Manzoni, S., Näsholm, T., Raven, J. A., Rebel, K. T., Reed, S., Vicca, S., Wiltshire, A., and Zaehle, S.: Terrestrial nitrogen cycling in Earth system models revisited, New Phytol., 210, 1165–1168, https://doi.org/10.1111/nph.13997, 2016.
Strigul, N., Pristinski, D., Purves, D., Dushoff, J., and Pacala, S.: Scaling from trees to forests: Tractable macroscopic equations for forest dynamics, Ecol. Monogr., 78, 523–545, https://doi.org/10.1890/08-0082.1, 2008.
Sullivan, B. W., Smith, W. K., Alan, R., Nasto, M. K., Reed, S. C., and Chazdon, R. L.: Spatially robust estimates of biological nitrogen (N) fixation imply substantial human alteration of the tropical N cycle, P. Natl. Acad. Sci. USA, 111, 8101–8106, https://doi.org/10.1073/pnas.1511978112, 2014.
Sulman, B. N., Shevliakova, E., Brzostek, E. R., Kivlin, S. N., Malyshev, S., Menge, D. N. L., and Zhang, X.: Diverse mycorrhizal associations enhance terrestrial C storage in a global model, Global Biogeochem. Cy., 33, 501–523, https://doi.org/10.1029/2018GB005973, 2019.
Swank, W. T. and Waide, J. B.: Characterization of Baseline Precipitation and Stream Chemistry and Nutrient Budgers for Control Watersheds, in: Forest Hydrology and Ecology at Coweeta, 1988.
Taylor, B. N., Chazdon, R. L., Bachelot, B., and Menge, D. N. L.: Nitrogen-fixing trees inhibit growth of regenerating Costa Rican rainforests, P. Natl. Acad. Sci. USA, 114, 8817–8822, https://doi.org/10.1073/pnas.1707094114, 2017.
Terrer, C., Vicca, S., Hungate, B. A., Phillips, R. P., and Prentice, I. C.: Mycorrhizal association as a primary control of the CO2 fertilization effect., Science, 353, 72–74, https://doi.org/10.1126/science.aaf4610, 2016.
Terrer, C., Vicca, S., Stocker, B. D., Hungate, B. A., Phillips, R. P., Reich, P. B., Finzi, A. C., and Prentice, I. C.: Ecosystem responses to elevated CO2 governed by plant-soil interactions and the cost of nitrogen acquisition, New Phytol., 217, 507–522, https://doi.org/10.1111/nph.14872, 2018.
Terrer, C., Prentice, I., Jackson, R., Keenan, T., Kaiser, C., Vicca, S., Fisher, J., Reich, P., Stocker, B., Hungate, B., Penuelos, J., McCallum, I., Soudzilovskala, N., Cernusak, L., Talhelm, A., Van, S. K., Piao, S., Newton, P., Hovenden, M., Blumenthal, D., Liu, Y., Muller, C., Winter, K., Field, C., Viechtbauer, W., Van, L. C., Hoosbeek, M., Watanabe, M., Koike, T., Leshyk, V., Polley, 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.
Thomas, R. Q., Brookshire, E. N. J., and Gerber, S.: Nitrogen limitation on land: How can it occur in Earth system models?, Glob. Change Biol., 21, 1777–1793, https://doi.org/10.1111/gcb.12813, 2015.
Tian, D. and Niu, S.: A global analysis of soil acidification caused by nitrogen addition, Environ. Res. Lett., 10, 24019, https://doi.org/10.1088/1748-9326/10/2/024019, 2015.
Todd, R. L., Meyer, R. D., and Waide, J. B.: Nitrogen Fixation in a Deciduous Forest in the South-Eastern United States, Ecol. Bull., 26, 172–177, 1978.
Treseder, K. K.: A meta-analysis of mycorrhizal responses to nitrogen, phosphorus, and atmospheric CO2 in field studies, New Phytol., 164, 347–355, https://doi.org/10.1111/j.1469-8137.2004.01159.x, 2004.
US Forest Service: US Forest Inventory and Analysis Database, available at: http://apps.fs.fed.us/fiadb-downloads/datamart.html (last access: 7 November 2019), 2020a.
US Forest Service: US Forest Inventory and Analysis Forest Health Monitoring Database, available at: http://apps.fs.fed.us/fiadb-downloads/datamart.html (last access: 7 November 2019), 2020b.
Vicca, S., Stocker, B. D., Reed, S., Wieder, W. R., Bahn, M., Fay, P. A., Janssens, I. A., Lambers, H., Peñuelas, J., Piao, S., Rebel, K. T., Sardans, J., Sigurdsson, B. D., Van Sundert, K., Wang, Y. P., Zaehle, S., and Ciais, P.: Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling, Environ. Res. Lett., 13, 125006, https://doi.org/10.1088/1748-9326/aaeae7, 2018.
Vitousek, P. M., Menge, D. N., Reed, S. C., and Cleveland, C. C.: Biological nitrogen fixation: rates, patterns and ecological controls in terrestrial ecosystems, Philos. T. R. Soc. B, 368, 20130119, https://doi.org/10.1098/rstb.2013.0119, 2013.
Wang, Y. P. and Houlton, B. Z.: Nitrogen constraints on terrestrial carbon uptake: Implications for the global carbon-climate feedback, Geophys. Res. Lett., 36, 1–5, https://doi.org/10.1029/2009GL041009, 2009.
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.
Weng, E. S., Malyshev, S., Lichstein, J. W., Farrior, C. E., Dybzinski, R., Zhang, T., Shevliakova, E., and Pacala, S. W.: Scaling from individual trees to forests in an Earth system modeling framework using a mathematically tractable model of height-structured competition, Biogeosciences, 12, 2655–2694, https://doi.org/10.5194/bg-12-2655-2015, 2015.
Wieder, W. R., Cleveland, C. C., Lawrence, D. M., and Bonan, G. B.: Effects of model structural uncertainty on carbon cycle projections: biological nitrogen fixation as a case study, Environ. Res. Lett., 10, 044016, https://doi.org/10.1088/1748-9326/10/4/044016, 2015a.
Wieder, W. R., Cleveland, C. C., Smith, W. K., and Todd-Brown, K.: Future productivity and carbon storage limited by terrestrial nutrient availability, Nat. Geosci., 8, 441–444, https://doi.org/10.1038/ngeo2413, 2015b.
Wright, S. J., Turner, B. L., Yavitt, J. B., Harms, K. E., Kaspari, M., Tanner, E. V. J., Bujan, J., Griffin, E. A., Mayor, J. R., Pasquini, S. C., Sheldrake, M., and Garcia, M. N.: Plant responses to fertilization experiments in lowland, species-rich, tropical forests, Ecology, 99, 1129–1138, https://doi.org/10.1002/ecy.2193, 2018.
Xu, H., Detto, M., Fang, S., Chazdon, R. L., Li, Y., Hau, B. C. H., Fischer, G. A., Weiblen, G. D., Hogan, J. A., Zimmerman, J. K., Uriarte, M., Thompson, J., Lian, J., Cao, K., Kenfack, D., Alonso, A., Bissiengou, P., Memiaghe, H. R., Valencia, R., Yap, S. L., Davies, S. J., Mi, X., and Yao, T. L.: Soil nitrogen concentration mediates the relationship between leguminous trees and neighbor diversity in tropical forests, Communications Biology, 3, 1–8, https://doi.org/10.1038/s42003-020-1041-y, 2020.
Yan, W. and Hunt, L. A.: An equation for modelling the temperature response of plants using only the cardinal temperatures, Ann. Bot.-London, 84, 607–614, https://doi.org/10.1006/anbo.1999.0955, 1999.
Yang, X., Wittig, V., Jain, A. K., and Post, W.: Integration of nitrogen cycle dynamics into the Integrated Science Assessment Model for the study of terrestrial ecosystem responses to global change, Global Biogeochem. Cy., 23, 1–18, GB4029, https://doi.org/10.1029/2009GB003474, 2009.
Zaehle, S. and Friend, A. D.: Carbon and nitrogen cycle dynamics in the O–CN land surface model: 1. Model description, site-scale evaluation, and sensitivity to parameter estimates, Global Biogeochem. Cy., 24, 1–13, GB1006, https://doi.org/10.1029/2009GB003521, 2010.
Zhang, J. and Elser, J. J.:
Zhao, M., Golaz, J.-C., Held, I. M., Guo, H., Balaji, V., Benson, R., Chen, J.-H., Chen, X., Donner, L. J., Dunne, J. P., Dunne, K., Durachta, J., Fan, S.-M., Freidenreich, S. M., Garner, S. T., Ginoux, P., Harris, L. M., Horowitz, L. W., Krasting, J. P., Langenhorst, A. R., Liang, Z., Lin, P., Lin, S.-J., Malyshev, S. L., Mason, E., Milly, P. C. D., Ming, Y., Naik, V., Paulot, F., Paynter, D., Phillipps, P., Radhakrishnan, A., Ramaswamy, V., Robinson, T., Schwarzkopf, D., Seman, C. J., Shevliakova, E., Shen, Z., Shin, H., Silvers, L. G., Wilson, J. R., Winton, M., Wittenberg, A. T., Wyman, B., and Xiang, B.: The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 1. Simulation Characteristics With Prescribed SSTs, J. Adv. Model. Earth Sy., 10, 691–734, https://doi.org/10.1002/2017MS001208, 2018a.
Zhao, M., Golaz, J.-C., Held, I. M., Guo, H., Balaji, V., Benson, R., Chen, J.-H., Chen, X., Donner, L. J., Dunne, J. P., Dunne, K., Durachta, J., Fan, S.-M., Freidenreich, S. M., Garner, S. T., Ginoux, P., Harris, L. M., Horowitz, L. W., Krasting, J. P., Langenhorst, A. R., Liang, Z., Lin, P., Lin, S.-J., Malyshev, S. L., Mason, E., Milly, P. C. D., Ming, Y., Naik, V., Paulot, F., Paynter, D., Phillipps, P., Radhakrishnan, A., Ramaswamy, V., Robinson, T., Schwarzkopf, D., Seman, C. J., Shevliakova, E., Shen, Z., Shin, H., Silvers, L. G., Wilson, J. R., Winton, M., Wittenberg, A. T., Wyman, B., and Xiang, B.: The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 2. Model Description, Sensitivity Studies, and Tuning Strategies, J. Adv. Model. Earth Sy., 10, 735–769, https://doi.org/10.1002/2017MS001209, 2018b.
Zheng, M., Zhou, Z., Luo, Y., Zhao, P., and Mo, J.: Global pattern and controls of biological nitrogen fixation under nutrient enrichment: A meta-analysis, Glob. Change Biol., 25, 3018–3030, https://doi.org/10.1111/gcb.14705, 2019.
Zheng, M., Zhou, Z., Zhao, P., Luo, Y., Ye, Q., Zhang, K., Song, L., and Mo, J.: Effects of human disturbance activities and environmental change factors on terrestrial nitrogen fixation, Glob. Change Biol., 26, 6203–6217, https://doi.org/10.1111/gcb.15328, 2020.
Zhu, Q., Riley, W. J., Tang, J., Collier, N., Hoffman, F. M., Yang, X., and Bisht, G.: Representing Nitrogen, Phosphorus, and Carbon Interactions in the E3SM Land Model: Development and Global Benchmarking, J. Adv. Model. Earth Sy., 11, 2238–2258, https://doi.org/10.1029/2018MS001571, 2019.
Zhu, Y.-G. and Miller, R. M.: Carbon cycling by arbuscular mycorrhizal fungi in soil–plant systems, Trends Plant Sci., 8, 407–409, https://doi.org/10.1016/S1360-1385(03)00192-4, 2003.
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Representing biological nitrogen fixation (BNF) is an important challenge for land models. We present a novel representation of BNF and updated nitrogen cycling in a land model. It includes a representation of asymbiotic BNF by soil microbes and the competitive dynamics between nitrogen-fixing and non-fixing plants. It improves estimations of major carbon and nitrogen pools and fluxes and their temporal dynamics in comparison to previous representations of BNF in land models.
Representing biological nitrogen fixation (BNF) is an important challenge for land models. We...
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