Articles | Volume 22, issue 20
https://doi.org/10.5194/bg-22-6153-2025
© Author(s) 2025. 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-22-6153-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Savanna ecosystem structure and productivity along a rainfall gradient: the role of competition and stress tolerance mediated by plant functional traits
Prashant Paudel
Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia
Stefan Olin
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Mark Tjoelker
Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia
Mikael Pontarp
Department of Biology, Lund University, Lund, Sweden
Daniel Metcalfe
Department of Ecology and Environment Science, Umeå University, Umeå, Sweden
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia
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Chansopheaktra Sovann, Torbern Tagesson, Patrik Vestin, Sakada Sakhoeun, Soben Kim, Sothea Kok, and Stefan Olin
Biogeosciences, 22, 4649–4677, https://doi.org/10.5194/bg-22-4649-2025, https://doi.org/10.5194/bg-22-4649-2025, 2025
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We offer pairwise observed datasets that compare the characteristics of tropical ecosystems, specifically pristine forests, regrowth forests, and cashew plantations. Our findings uncover some key differences in their characteristics, emphasizing the influence of human activities on these ecosystems. By sharing our unique datasets, we hope to improve the knowledge of tropical forest ecosystems in Southeast Asia, advancing tropical research and tackling global environmental challenges.
Zitong Jia, Shouzhi Chen, Yongshuo H. Fu, David Martín Belda, David Wårlind, Stefan Olin, Chongyu Xu, and Jing Tang
EGUsphere, https://doi.org/10.5194/egusphere-2025-4064, https://doi.org/10.5194/egusphere-2025-4064, 2025
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Groundwater sustains vegetation and regulates land-atmosphere exchanges, but most Earth system models oversimplify its movement. Our study develops an integrated framework coupling LPJ-GUESS with the 3D hydrological model ParFlow to explicitly represent groundwater-vegetation interactions. Our results add to the evidence that three-dimensional groundwater flow strongly regulates water exchanges, and provides a powerful tool to improve simulations of water cycles in Earth system models.
John Marshall, Jose Gutierrez-Lopez, Daniel Metcalfe, Nataliia Kozii, and Hjalmar Laudon
EGUsphere, https://doi.org/10.5194/egusphere-2025-3328, https://doi.org/10.5194/egusphere-2025-3328, 2025
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The "two water-worlds hypothesis" has attracted significant public attention because it is an accessible way to describe the partitioning of water sources within catchments. This manuscript adds a new degree of complexity to that idea by recognizing that co-occurring tree species, which root at different depths, also use different water sources. So it leads to at least three water worlds.
Jette Elena Stoebke, David Wårlind, Stefan Olin, Annemarie Eckes-Shephard, Bogdan Brzeziecki, Mikko Peltoniemi, and Thomas A. M. Pugh
EGUsphere, https://doi.org/10.5194/egusphere-2025-2995, https://doi.org/10.5194/egusphere-2025-2995, 2025
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Forests are shaped by how trees compete for resources like sunlight. We improved a widely used vegetation model to better capture how light filters through the forest canopy, especially after tree death or harvesting. By assigning trees explicit positions, the model captures forest structure and change more realistically. This advances our understanding of tree competition and forest responses to management, providing a better tool to predict future forest dynamics.
Konstantin Gregor, Benjamin F. Meyer, Tillmann Gaida, Victor Justo Vasquez, Karina Bett-Williams, Matthew Forrest, João P. Darela-Filho, Sam Rabin, Marcos Longo, Joe R. Melton, Johan Nord, Peter Anthoni, Vladislav Bastrikov, Thomas Colligan, Christine Delire, Michael C. Dietze, George Hurtt, Akihiko Ito, Lasse T. Keetz, Jürgen Knauer, Johannes Köster, Tzu-Shun Lin, Lei Ma, Marie Minvielle, Stefan Olin, Sebastian Ostberg, Hao Shi, Reiner Schnur, Urs Schönenberger, Qing Sun, Peter E. Thornton, and Anja Rammig
EGUsphere, https://doi.org/10.5194/egusphere-2025-1733, https://doi.org/10.5194/egusphere-2025-1733, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Geoscientific models are crucial for understanding Earth’s processes. However, they sometimes do not adhere to highest software quality standards, and scientific results are often hard to reproduce due to the complexity of the workflows. Here we gather the expertise of 20 modeling groups and software engineers to define best practices for making geoscientific models maintainable, usable, and reproducible. We conclude with an open-source example serving as a reference for modeling communities.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev., 18, 3131–3155, https://doi.org/10.5194/gmd-18-3131-2025, https://doi.org/10.5194/gmd-18-3131-2025, 2025
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Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Chansopheaktra Sovann, Torbern Tagesson, Patrik Vestin, Sakada Sakhoeun, Soben Kim, Sothea Kok, and Stefan Olin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-98, https://doi.org/10.5194/essd-2024-98, 2024
Revised manuscript not accepted
Short summary
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We offer pairwise observed datasets that compare the characteristics of tropical ecosystems, specifically pristine forests, regrowth forests, and cashew plantations. Our findings uncover some key differences in their characteristics, emphasizing the influence of human activities on these ecosystems. By sharing our unique datasets, we hope to improve the knowledge of tropical forest ecosystems in Southeast Asia, advancing tropical research, and tackling global environmental challenges.
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.
Lina Teckentrup, Martin G. De Kauwe, Gab Abramowitz, Andrew J. Pitman, Anna M. Ukkola, Sanaa Hobeichi, Bastien François, and Benjamin Smith
Earth Syst. Dynam., 14, 549–576, https://doi.org/10.5194/esd-14-549-2023, https://doi.org/10.5194/esd-14-549-2023, 2023
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Studies analyzing the impact of the future climate on ecosystems employ climate projections simulated by global circulation models. These climate projections display biases that translate into significant uncertainty in projections of the future carbon cycle. Here, we test different methods to constrain the uncertainty in simulations of the carbon cycle over Australia. We find that all methods reduce the bias in the steady-state carbon variables but that temporal properties do not improve.
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.
H. E. Markus Meier, Marcus Reckermann, Joakim Langner, Ben Smith, and Ira Didenkulova
Earth Syst. Dynam., 14, 519–531, https://doi.org/10.5194/esd-14-519-2023, https://doi.org/10.5194/esd-14-519-2023, 2023
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The Baltic Earth Assessment Reports summarise the current state of knowledge on Earth system science in the Baltic Sea region. The 10 review articles focus on the regional water, biogeochemical and carbon cycles; extremes and natural hazards; sea-level dynamics and coastal erosion; marine ecosystems; coupled Earth system models; scenario simulations for the regional atmosphere and the Baltic Sea; and climate change and impacts of human use. Some highlights of the results are presented here.
David Martín Belda, Peter Anthoni, David Wårlind, Stefan Olin, Guy Schurgers, Jing Tang, Benjamin Smith, and Almut Arneth
Geosci. Model Dev., 15, 6709–6745, https://doi.org/10.5194/gmd-15-6709-2022, https://doi.org/10.5194/gmd-15-6709-2022, 2022
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We present a number of augmentations to the ecosystem model LPJ-GUESS, which will allow us to use it in studies of the interactions between the land biosphere and the climate. The new module enables calculation of fluxes of energy and water into the atmosphere that are consistent with the modelled vegetation processes. The modelled fluxes are in fair agreement with observations across 21 sites from the FLUXNET network.
Johannes Oberpriller, Christine Herschlein, Peter Anthoni, Almut Arneth, Andreas Krause, Anja Rammig, Mats Lindeskog, Stefan Olin, and Florian Hartig
Geosci. Model Dev., 15, 6495–6519, https://doi.org/10.5194/gmd-15-6495-2022, https://doi.org/10.5194/gmd-15-6495-2022, 2022
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Understanding uncertainties of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyzed these across European forests. We find that uncertainties are dominantly induced by parameters related to water, mortality, and climate, with an increasing importance of climate from north to south. These results highlight that climate not only contributes uncertainty but also modifies uncertainties in other ecosystem processes.
Johan A. Eckdahl, Jeppe A. Kristensen, and Daniel B. Metcalfe
Biogeosciences, 19, 2487–2506, https://doi.org/10.5194/bg-19-2487-2022, https://doi.org/10.5194/bg-19-2487-2022, 2022
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This study found climate to be a driving force for increasing per area emissions of greenhouse gases and removal of important nutrients from high-latitude forests due to wildfire. It used detailed direct measurements over a large area to uncover patterns and mechanisms of restructuring of forest carbon and nitrogen pools that are extrapolatable to larger regions. It also takes a step forward in filling gaps in global knowledge of northern forest response to climate-change-strengthened wildfires.
Jianyong Ma, Sam S. Rabin, Peter Anthoni, Anita D. Bayer, Sylvia S. Nyawira, Stefan Olin, Longlong Xia, and Almut Arneth
Biogeosciences, 19, 2145–2169, https://doi.org/10.5194/bg-19-2145-2022, https://doi.org/10.5194/bg-19-2145-2022, 2022
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Improved agricultural management plays a vital role in protecting soils from degradation in eastern Africa. We simulated the impacts of seven management practices on soil carbon pools, nitrogen loss, and crop yield under different climate scenarios in this region. This study highlights the possibilities of conservation agriculture when targeting long-term environmental sustainability and food security in crop ecosystems, particularly for those with poor soil conditions in tropical climates.
Jianyong Ma, Stefan Olin, Peter Anthoni, Sam S. Rabin, Anita D. Bayer, Sylvia S. Nyawira, and Almut Arneth
Geosci. Model Dev., 15, 815–839, https://doi.org/10.5194/gmd-15-815-2022, https://doi.org/10.5194/gmd-15-815-2022, 2022
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The implementation of the biological N fixation process in LPJ-GUESS in this study provides an opportunity to quantify N fixation rates between legumes and to better estimate grain legume production on a global scale. It also helps to predict and detect the potential contribution of N-fixing plants as
green manureto reducing or removing the use of N fertilizer in global agricultural systems, considering different climate conditions, management practices, and land-use change scenarios.
Adrian Gustafson, Paul A. Miller, Robert G. Björk, Stefan Olin, and Benjamin Smith
Biogeosciences, 18, 6329–6347, https://doi.org/10.5194/bg-18-6329-2021, https://doi.org/10.5194/bg-18-6329-2021, 2021
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We performed model simulations of vegetation change for a historic period and a range of climate change scenarios at a high spatial resolution. Projected treeline advance continued at the same or increased rates compared to our historic simulation. Temperature isotherms advanced faster than treelines, revealing a lag in potential vegetation shifts that was modulated by nitrogen availability. At the year 2100 projected treelines had advanced by 45–195 elevational metres depending on the scenario.
Mats Lindeskog, Benjamin Smith, Fredrik Lagergren, Ekaterina Sycheva, Andrej Ficko, Hans Pretzsch, and Anja Rammig
Geosci. Model Dev., 14, 6071–6112, https://doi.org/10.5194/gmd-14-6071-2021, https://doi.org/10.5194/gmd-14-6071-2021, 2021
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Forests play an important role in the global carbon cycle and for carbon storage. In Europe, forests are intensively managed. To understand how management influences carbon storage in European forests, we implement detailed forest management into the dynamic vegetation model LPJ-GUESS. We test the model by comparing model output to typical forestry measures, such as growing stock and harvest data, for different countries in Europe.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, and Benjamin Smith
Biogeosciences, 18, 2181–2203, https://doi.org/10.5194/bg-18-2181-2021, https://doi.org/10.5194/bg-18-2181-2021, 2021
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The El Niño–Southern Oscillation (ENSO) describes changes in the sea surface temperature patterns of the Pacific Ocean. This influences the global weather, impacting vegetation on land. There are two types of El Niño: central Pacific (CP) and eastern Pacific (EP). In this study, we explored the long-term impacts on the carbon balance on land linked to the two El Niño types. Using a dynamic vegetation model, we simulated what would happen if only either CP or EP El Niño events had occurred.
Cited articles
Argles, A. P. K., Moore, J. R., and Cox, P. M.: Dynamic Global Vegetation Models: Searching for the balance between demographic process representation and computational tractability, PLOS Clim., 1, e0000068, https://doi.org/10.1371/journal.pclm.0000068, 2022.
Asner, G. P., Anderson, C. B., Martin, R. E., Knapp, D. E., Tupayachi, R., Sinca, F., and Malhi, Y.: Landscape-scale changes in forest structure and functional traits along an Andes-to-Amazon elevation gradient, Biogeosciences, 11, 843–856, https://doi.org/10.5194/bg-11-843-2014, 2014.
Baudena, M., D'Andrea, F., and Provenzale, A.: An idealized model for tree-grass coexistence in savannas: The role of life stage structure and fire disturbances, J. Ecol., 98, 74–80, https://doi.org/10.1111/j.1365-2745.2009.01588.x, 2010.
Baudena, M., Dekker, S. C., van Bodegom, P. M., Cuesta, B., Higgins, S. I., Lehsten, V., Reick, C. H., Rietkerk, M., Scheiter, S., Yin, Z., Zavala, M. A., and Brovkin, V.: Forests, savannas, and grasslands: bridging the knowledge gap between ecology and Dynamic Global Vegetation Models, Biogeosciences, 12, 1833–1848, https://doi.org/10.5194/bg-12-1833-2015, 2015.
Beringer, J., Moore, C. E., Cleverly, J., Campbell, D. I., Cleugh, H., De Kauwe, M. G., Kirschbaum, M. U. F., Griebel, A., Grover, S., Huete, A., Hutley, L. B., Laubach, J., Van Niel, T., Arndt, S. K., Bennett, A. C., Cernusak, L. A., Eamus, D., Ewenz, C. M., Goodrich, J. P., Jiang, M., Hinko-Najera, N., Isaac, P., Hobeichi, S., Knauer, J., Koerber, G. R., Liddell, M., Ma, X., Macfarlane, C., McHugh, I. D., Medlyn, B. E., Meyer, W. S., Norton, A. J., Owens, J., Pitman, A., Pendall, E., Prober, S. M., Ray, R. L., Restrepo-Coupe, N., Rifai, S. W., Rowlings, D., Schipper, L., Silberstein, R. P., Teckentrup, L., Thompson, S. E., Ukkola, A. M., Wall, A., Wang, Y. P., Wardlaw, T. J., and Woodgate, W.: Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network, Glob. Change Biol., 28, 3489–3514, https://doi.org/10.1111/gcb.16141, 2022.
Bird, M. I., Brand, M., Comley, R., Fu, X., Hadeen, X., Jacobs, Z., Rowe, C., Wurster, C. M., Zwart, C., and Bradshaw, C. J. A.: Late Pleistocene emergence of an anthropogenic fire regime in Australia's tropical savannahs, Nat. Geosci., 17, 233–240, https://doi.org/10.1038/s41561-024-01388-3, 2024.
Bond, W. J.: What limits trees in C4 grasslands and savannas?, Annu. Rev. Ecol. Evol. Syst., 39, 641–659, https://doi.org/10.1146/annurev.ecolsys.39.110707.173411, 2008.
Bureau of Meteorology (BOM): Climate Data Services, http://www.bom.gov.au, last access: 31 March 2024.
Canadell, J. G., Meyer, C. P., Cook, G. D., Dowdy, A., Briggs, P. R., Knauer, J., Pepler, A., and Haverd, V.: Multi-decadal increase of forest burned area in Australia is linked to climate change, Nat. Commun., 12, https://doi.org/10.1038/s41467-021-27225-4, 2021.
Chen, X., Eamus, D., and Hutley, L. B.: Seasonal patterns of soil carbon dioxide efflux from a wet-dry tropical savanna of northern Australia, Aust. J. Bot., 50, 43, https://doi.org/10.1071/BT01049, 2002.
Chen, X., Eamus, D., and Hutley, L. B.: Seasonal patterns of fine-root productivity and turnover in a tropical savanna of northern Australia, J. Trop. Ecol., 20, 221–224, https://doi.org/10.1017/S0266467403001135, 2004.
Clark, D. B., Hurtado, J., and Saatchi, S. S.: Tropical rain forest structure, tree growth and dynamics along a 2700-m elevational transect in Costa Rica, PLoS ONE, 10, 1–18, https://doi.org/10.1371/journal.pone.0122905, 2015.
Damgaard, C.: Modeling plant competition along an environmental gradient, Ecol. Model., 170, 45–53, https://doi.org/10.1016/S0304-3800(03)00299-0, 2003.
Deceukelier, R.: MODELLING AUSTRALIAN SAVANNA BUSHFIRES USING LPJ-GUESS, Masters Thesis, Ghent University, 102 pp., 2021.
Department of Climate Change, Energy, the Environment and Water (DCCEEW): Australian National Vegetation Information System (NVIS), http://www.dcceew.gov.au, last access: 10 March 2024.
Eamus, D. and Prior, L.: Ecophysiology of trees of seasonally dry tropics: Comparisons among phenologies, in: Advances in Ecological Research, vol. 32, Elsevier, 113–197, https://doi.org/10.1016/S0065-2504(01)32012-3, 2001.
Emmett, K. D., Renwick, K. M., and Poulter, B.: Adapting a dynamic vegetation model for regional biomass, plant biogeography, and fire modeling in the Greater Yellowstone Ecosystem: Evaluating LPJ-GUESS-LMfireCF, Ecol. Model., 440, 109417, https://doi.org/10.1016/j.ecolmodel.2020.109417, 2021.
Falster, D., Gallagher, R., Wenk, E., and Sauquet, H.: AusTraits: a curated plant trait database for the Australian flora, Zenodo [data set], https://doi.org/10.5281/zenodo.7368074, 2022.
Falster, D. S., Kunstler, G., Fitz John, R. G., and Westoby, M.: Emergent shapes of trait-based competition functions from resource-based models: A gaussian is not normal in plant communities, Am. Nat., 198, 253–267, https://doi.org/10.1086/714868, 2021b.
February, E. C., Higgins, S. I., Newton, R., and West, A. G.: Tree distribution on a steep environmental gradient in an arid savanna, J. Biogeogr., 34, 270–278, https://doi.org/10.1111/j.1365-2699.2006.01583.x, 2007.
Fisher, R. A., McDowell, N., Purves, D., Moorcroft, P., Sitch, S., Cox, P., Huntingford, C., Meir, P., and Ian Woodward, F.: Assessing uncertainties in a second-generation dynamic vegetation model caused by ecological scale limitations, New Phytol., 187, 666–681, https://doi.org/10.1111/j.1469-8137.2010.03340.x, 2010.
Fisher, R. A., Koven, C. D., Anderegg, W. R. L., Christoffersen, B. O., Dietze, M. C., Farrior, C. E., Holm, J. A., Hurtt, G. C., Knox, R. G., Lawrence, P. J., Lichstein, J. W., Longo, M., Matheny, A. M., Medvigy, D., Muller-Landau, H. C., Powell, T. L., Serbin, S. P., Sato, H., Shuman, J. K., Smith, B., Trugman, A. T., Viskari, T., Verbeeck, H., Weng, E., Xu, C., Xu, X., Zhang, T., and Moorcroft, P. R.: Vegetation demographics in Earth System Models: A review of progress and priorities, Glob. Change Biol., 24, 35–54, https://doi.org/10.1111/gcb.13910, 2018.
Giglio, L., Randerson, J. T., and Van Der Werf, G. R.: Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4), J. Geophys. Res.-Biogeosciences, 118, 317–328, https://doi.org/10.1002/jgrg.20042, 2013.
Harrison, S. P., Prentice, I. C., Bloomfield, K. J., Dong, N., Forkel, M., Forrest, M., Ningthoujam, R. K., Pellegrini, A., Shen, Y., Baudena, M., Cardoso, A. W., Huss, J. C., Joshi, J., Oliveras, I., Pausas, J. G., and Simpson, K. J.: Understanding and modelling wildfire regimes: an ecological perspective, Environ. Res. Lett., 16, 125008, https://doi.org/10.1088/1748-9326/ac39be, 2021.
Haverd, V., Smith, B., Nieradzik, L. P., and Briggs, P. R.: A stand-alone tree demography and landscape structure module for Earth system models: integration with inventory data from temperate and boreal forests, Biogeosciences, 11, 4039–4055, https://doi.org/10.5194/bg-11-4039-2014, 2014.
Haverd, V., Smith, B., Raupach, M., Briggs, P., Nieradzik, L., Beringer, J., Hutley, L., Trudinger, C. M., and Cleverly, J.: Coupling carbon allocation with leaf and root phenology predicts tree–grass partitioning along a savanna rainfall gradient, Biogeosciences, 13, 761–779, https://doi.org/10.5194/bg-13-761-2016, 2016.
Haverd, V., Smith, B., Raupach, M., Briggs, P., Nieradzik, L., Beringer, J., Hutley, L., Trudinger, C. M., and Cleverly, J.: Coupling carbon allocation with leaf and root phenology predicts tree–grass partitioning along a savanna rainfall gradient, Biogeosciences, 13, 761–779, https://doi.org/10.5194/bg-13-761-2016, 2016.
Holdo, R. M.: Revisiting the Two-Layer Hypothesis: Coexistence of Alternative Functional Rooting Strategies in Savannas, PLoS ONE, 8, https://doi.org/10.1371/journal.pone.0069625, 2013.
Holdo, R. M. and Nippert, J. B.: Linking resource- and disturbance-based models to explain tree–grass coexistence in savannas, New Phytol., 237, 1966–1979, https://doi.org/10.1111/nph.18648, 2023.
Hutley, L. B., O'Grady, A. P., and Eamus, D.: Evapotranspiration from Eucalypt open-forest savanna of Northern Australia, Funct. Ecol., 14, 183–194, https://doi.org/10.1046/j.1365-2435.2000.00416.x, 2000.
Hutley, L. B., Beringer, J., Isaac, P. R., Hacker, J. M., and Cernusak, L. A.: A sub-continental scale living laboratory: Spatial patterns of savanna vegetation over a rainfall gradient in northern Australia, Agric. For. Meteorol., 151, 1417–1428, https://doi.org/10.1016/j.agrformet.2011.03.002, 2011.
Isaac, P., Cleverly, J., McHugh, I., van Gorsel, E., Ewenz, C., and Beringer, J.: OzFlux data: network integration from collection to curation, Biogeosciences, 14, 2903–2928, https://doi.org/10.5194/bg-14-2903-2017, 2017.
Jackson, R. B., Canadell, J., Ehleringer, J. R., Mooney, H. A., Sala, O. E., and Schulze, E. D.: A global analysis of root distributions for terrestrial biomes, Oecologia, 108, 389–411, https://doi.org/10.1007/BF00333714, 1996.
Janos, D. P., Scott, J., and Bowman, D. M. J. S.: Temporal and spatial variation of fine roots in a northern Australian Eucalyptus tetrodonta savanna, J. Trop. Ecol., 24, 177–188, https://doi.org/10.1017/S0266467408004860, 2008.
Kanniah, K. D., Beringer, J., and Hutley, L. B.: Environmental controls on the spatial variability of savanna productivity in the Northern Territory, Australia, Agric. For. Meteorol., 151, 1429–1439, https://doi.org/10.1016/j.agrformet.2011.06.009, 2011.
Kelley, D. I., Harrison, S. P., and Prentice, I. C.: Improved simulation of fire–vegetation interactions in the Land surface Processes and eXchanges dynamic global vegetation model (LPX-Mv1), Geosci. Model Dev., 7, 2411–2433, https://doi.org/10.5194/gmd-7-2411-2014, 2014.
Knorr, W., Kaminski, T., Arneth, A., and Weber, U.: Impact of human population density on fire frequency at the global scale, Biogeosciences, 11, 1085–1102, https://doi.org/10.5194/bg-11-1085-2014, 2014.
Koch, G. W., Vitousek, P. M., Steffen, W. L., and Walker, B. H.: Terrestrial transects for global change research, Vegetatio, 121, 53–65, https://doi.org/10.1007/BF00044672, 1995.
Kuppler, J., Albert, C. H., Ames, G. M., Armbruster, W. S., Boenisch, G., Boucher, F. C., Campbell, D. R., Carneiro, L. T., Chacón-Madrigal, E., Enquist, B. J., Fonseca, C. R., Gómez, J. M., Guisan, A., Higuchi, P., Karger, D. N., Kattge, J., Kleyer, M., Kraft, N. J. B., Larue-Kontić, A. C., Lázaro, A., Lechleitner, M., Loughnan, D., Minden, V., Niinemets, Ü., Overbeck, G. E., Parachnowitsch, A. L., Perfectti, F., Pillar, V. D., Schellenberger Costa, D., Sletvold, N., Stang, M., Alves-dos-Santos, I., Streit, H., Wright, J., Zych, M., and Junker, R. R.: Global gradients in intraspecific variation in vegetative and floral traits are partially associated with climate and species richness, Glob. Ecol. Biogeogr., 29, 992–1007, https://doi.org/10.1111/geb.13077, 2020.
Ma, X., Huete, A., Moore, C. E., Cleverly, J., Hutley, L. B., Beringer, J., Leng, S., Xie, Z., Yu, Q., and Eamus, D.: Spatiotemporal partitioning of savanna plant functional type productivity along NATT, Remote Sens. Environ., 246, 111855, https://doi.org/10.1016/j.rse.2020.111855, 2020.
Maharjan, S. K., Sterck, F. J., Dhakal, B. P., Makri, M., and Poorter, L.: Functional traits shape tree species distribution in the Himalayas, J. Ecol., 109, 3818–3834, https://doi.org/10.1111/1365-2745.13759, 2021.
Matsuo, T., Bongers, F., Martínez-Ramos, M., Van Der Sande, M. T., and Poorter, L.: Height growth and biomass partitioning during secondary succession differ among forest light strata and successional guilds in a tropical rainforest, Oikos, 2024, e10486, https://doi.org/10.1111/oik.10486, 2024.
Michalet, R., Delerue, F., Liancourt, P., and Pugnaire, F. I.: Are complementarity effects of species richness on productivity the strongest in species-rich communities?, J. Ecol., 109, 2038–2046, https://doi.org/10.1111/1365-2745.13658, 2021.
Moore, C. E., Beringer, J., Evans, B., Hutley, L. B., McHugh, I., and Tapper, N. J.: The contribution of trees and grasses to productivity of an Australian tropical savanna, Biogeosciences, 13, 2387–2403, https://doi.org/10.5194/bg-13-2387-2016, 2016.
Muñoz Mazón, M., Klanderud, K., Finegan, B., Veintimilla, D., Bermeo, D., Murrieta, E., Delgado, D., and Sheil, D.: How forest structure varies with elevation in old growth and secondary forest in Costa Rica, For. Ecol. Manag., 469, 118191, https://doi.org/10.1016/j.foreco.2020.118191, 2020.
Munroe, S., Guerin, G., Saleeba, T., Martín-Forés, I., Blanco-Martin, B., Sparrow, B., and Tokmakoff, A.: ausplotsR: An R package for rapid extraction and analysis of vegetation and soil data collected by Australia's Terrestrial Ecosystem Research Network, J. Veg. Sci., 32, e13046, https://doi.org/10.1111/jvs.13046, 2021.
Murphy, B. P., Whitehead, P. J., Evans, J., Yates, C. P., Edwards, A. C., MacDermott, H. J., Lynch, D. C., and Russell-Smith, J.: Using a demographic model to project the long-term effects of fire management on tree biomass in Australian savannas, Ecol. Monogr., 93, e1564, https://doi.org/10.1002/ecm.1564, 2023.
Myneni, R., Knyazikhin, Y., and Park, T.: MYD15A2H MODIS/Aqua Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V006, NASA Land Processes Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MYD15A2H.006, 2015.
Nijzink, R. C., Beringer, J., Hutley, L. B., and Schymanski, S. J.: Does maximization of net carbon profit enable the prediction of vegetation behaviour in savanna sites along a precipitation gradient?, Hydrol. Earth Syst. Sci., 26, 525–550, https://doi.org/10.5194/hess-26-525-2022, 2022.
Ondei, S., Prior, L. D., Vigilante, T., and Bowman, D. M. J. S.: Post-fire resprouting strategies of rainforest and savanna saplings along the rainforest–savanna boundary in the Australian monsoon tropics, Plant Ecol., 217, 711–724, https://doi.org/10.1007/s11258-015-0531-3, 2016.
Paudel, P., Olin, S., and Smith, B.: LPJ-GUESS Model Code for Savanna Ecosystem of Northern Australia, Zenodo [code], https://doi.org/10.5281/zenodo.17081548, 2025a.
Paudel, P., Olin, S., and Smith, B.: Forcing_data_and_model_output_for_Savanna ecosystem_northern_Australia, Zenodo [data set], https://doi.org/10.5281/zenodo.17034489, 2025b.
Peel, D. R., Pitman, A. J., Hughes, L. A., Narisma, G. T., and Pielke, R. A.: The impact of realistic biophysical parameters for eucalypts on the simulation of the January climate of Australia, Environ. Model. Softw., 20, 595–612, https://doi.org/10.1016/j.envsoft.2004.03.004, 2005.
Pretzsch, H., Biber, P., Uhl, E., Dahlhausen, J., Rötzer, T., Caldentey, J., Koike, T., van Con, T., Chavanne, A., Seifert, T., Toit, B. du, Farnden, C., and Pauleit, S.: Crown size and growing space requirement of common tree species in urban centres, parks, and forests, Urban For. Urban Green., 14, 466–479, https://doi.org/10.1016/j.ufug.2015.04.006, 2015.
Pugh, T. A. M., Arneth, A., Kautz, M., Poulter, B., and Smith, B.: Important role of forest disturbances in the global biomass turnover and carbon sinks, Nat. Geosci., 12, 730–735, https://doi.org/10.1038/s41561-019-0427-2, 2019.
Rabin, S. S., Melton, J. R., Lasslop, G., Bachelet, D., Forrest, M., Hantson, S., Kaplan, J. O., Li, F., Mangeon, S., Ward, D. S., Yue, C., Arora, V. K., Hickler, T., Kloster, S., Knorr, W., Nieradzik, L., Spessa, A., Folberth, G. A., Sheehan, T., Voulgarakis, A., Kelley, D. I., Prentice, I. C., Sitch, S., Harrison, S., and Arneth, A.: The Fire Modeling Intercomparison Project (FireMIP), phase 1: experimental and analytical protocols with detailed model descriptions, Geosci. Model Dev., 10, 1175–1197, https://doi.org/10.5194/gmd-10-1175-2017, 2017.
Rees, M.: Competition on productivity gradients-what do we expect?, Ecol. Lett., 16, 291–298, https://doi.org/10.1111/ele.12037, 2013.
Rogers, C. D. W. and Beringer, J.: Describing rainfall in northern Australia using multiple climate indices, Biogeosciences, 14, 597–615, https://doi.org/10.5194/bg-14-597-2017, 2017.
Sauter, F., Albrecht, H., Kollmann, J., and Lang, M.: Competition components along productivity gradients – revisiting a classic dispute in ecology, Oikos, 130, 1326–1334, https://doi.org/10.1111/oik.07706, 2021.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model, Glob. Change Biol., 9, 161–185, https://doi.org/10.1046/j.1365-2486.2003.00569.x, 2003.
Smith, B., Prentice, I. C., and Sykes, M. T.: Representation of vegetation dynamics in the modelling of terrestrial ecosystems: Comparing two contrasting approaches within European climate space, Glob. Ecol. Biogeogr., 10, 621–637, https://doi.org/10.1046/j.1466-822X.2001.00256.x, 2001.
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.
Snell, R. S., Huth, A., Nabel, J. E. M. S., Bocedi, G., Travis, J. M. J., Gravel, D., Bugmann, H., Gutiérrez, A. G., Hickler, T., Higgins, S. I., Reineking, B., Scherstjanoi, M., Zurbriggen, N., and Lischke, H.: Using dynamic vegetation models to simulate plant range shifts, Ecography, 37, 1184–1197, https://doi.org/10.1111/ecog.00580, 2014.
Tangney, R., Paroissien, R., Le Breton, T. D., Thomsen, A., Doyle, C. A. T., Ondik, M., Miller, R. G., Miller, B. P., and Ooi, M. K. J.: Success of post-fire plant recovery strategies varies with shifting fire seasonality, Commun. Earth Environ., 3, 126, https://doi.org/10.1038/s43247-022-00453-2, 2022.
TERN Australia (Eds.): TERN AusPlots ecosystem surveillance monitoring dataset, TERN Australia, https://field.jrsrp.com/, last access: 10 March 2024.
Vernooij, R., Eames, T., Russell-Smith, J., Yates, C., Beatty, R., Evans, J., Edwards, A., Ribeiro, N., Wooster, M., Strydom, T., Giongo, M. V., Borges, M. A., Menezes Costa, M., Barradas, A. C. S., van Wees, D., and Van der Werf, G. R.: Dynamic savanna burning emission factors based on satellite data using a machine learning approach, Earth Syst. Dynam., 14, 1039–1064, https://doi.org/10.5194/esd-14-1039-2023, 2023.
Wang, B., Smith, B., Waters, C., Feng, P., and Liu, D. L.: Modelling changes in vegetation productivity and carbon balance under future climate scenarios in southeastern Australia, Sci. Total Environ., 924, 171748, https://doi.org/10.1016/j.scitotenv.2024.171748, 2024.
Werner, P. A. and Prior, L. D.: Demography and growth of subadult savanna trees: Interactions of life history, size, fire season, and grassy understory, Ecol. Monogr., 83, 67–93, https://doi.org/10.1890/12-1153.1, 2013.
Whitley, R., Beringer, J., Hutley, L. B., Abramowitz, G., De Kauwe, M. G., Duursma, R., Evans, B., Haverd, V., Li, L., Ryu, Y., Smith, B., Wang, Y.-P., Williams, M., and Yu, Q.: A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas, Biogeosciences, 13, 3245–3265, https://doi.org/10.5194/bg-13-3245-2016, 2016.
Whitley, R., Beringer, J., Hutley, L. B., Abramowitz, G., De Kauwe, M. G., Evans, B., Haverd, V., Li, L., Moore, C., Ryu, Y., Scheiter, S., Schymanski, S. J., Smith, B., Wang, Y.-P., Williams, M., and Yu, Q.: Challenges and opportunities in land surface modelling of savanna ecosystems, Biogeosciences, 14, 4711–4732, https://doi.org/10.5194/bg-14-4711-2017, 2017.
Williams, R. J., Myers, B. A., Muller, W. J., Duff, G. A., and Eamus, D.: Leaf Phenology of Woody Species in a North Australian Tropical Savanna, Ecology, 78, 2542–2558, 1997.
Woinarski, J. C. Z., Andersen, A. N., and Murphy, B. P.: The Tropical Savannas of Northern Australia, in: Encyclopedia of the World's Biomes, Elsevier, 827–834, https://doi.org/10.1016/B978-0-12-409548-9.12023-8, 2020.
Zhu, L., Zhang, Y., Ye, H., Li, Y., Hu, W., Du, J., and Zhao, P.: Variations in leaf and stem traits across two elevations in subtropical forests, Funct. Plant Biol., 49, 319–332, https://doi.org/10.1071/FP21220, 2022.
Short summary
Ecological processes respond to changes in rainfall conditions. Competition and stress created by water availability are two primary components at two ends of the rainfall gradient. In wetter areas, plants compete for resources, while in drier regions, stress limits growth. The complex interaction between plant characters and their response to growth conditions governs ecosystem processes. These findings can be used to understand how future rainfall changes could impact ecosystems.
Ecological processes respond to changes in rainfall conditions. Competition and stress created...
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