Skip to main content
Have a personal or library account? Click to login
Capturing Human-Biodiversity-Ecosystem Interactions in Advanced Models of the Land-System Cover

Capturing Human-Biodiversity-Ecosystem Interactions in Advanced Models of the Land-System

Open Access
|Jul 2026

References

  1. Alexander, P., Rabin, S., Anthoni, P., Henry, R., Pugh, T. A. M., Rounsevell, M. D. A., & Arneth, A. (2018). Adaptation of global land use and management intensity to changes in climate and atmospheric carbon dioxide. Global Change Biology, 24(7), 27912809. 10.1111/gcb.14110
  2. Anderegg, W. R. L., Trugman, A. T., Badgley, G., Anderson, C. M., Bartuska, A., Ciais, P., Cullenward, D., Field, C. B., Freeman, J., Goetz, S. J., Hicke, J. A., Huntzinger, D., Jackson, R. B., Nickerson, J., Pacala, S., & Randerson, J. T. (2020). Climate-driven risks to the climate mitigation potential of forests. Science, 368(6497), 1327. 10.1126/science.aaz7005
  3. Anderegg, W. R. L., Wu, C., Acil, N., Carvalhais, N., Pugh, T. A. M., Sadler, J. P., & Seidl, R. (2022). A climate risk analysis of Earth’s forests in the 21st century. Science, 377(6610), 10991103. 10.1126/science.abp9723
  4. Anderson, K., Buck, H. J., Fuhr, L., Geden, O., Peters, G. P., & Tamme, E. (2023). Controversies of carbon dioxide removal. Nature Reviews Earth & Environment, 4, 808814. 10.1038/s43017-023-00493-y
  5. Arneth, A., Sitch, S., Pongratz, J., Stocker, B. D., Ciais, P., Poulter, B., Bayer, A. D., Bondeau, A., Calle, L., Chini, L. P., Gasser, T., Fader, M., Friedlingstein, P., Kato, E., Li, W., Lindeskog, M., Nabel, J., Pugh, T. A. M., Robertson, E., … Zaehle, S. (2017). Historical carbon dioxide emissions caused by land-use changes are possibly larger than assumed. Nature Geoscience, 10(2), 7984. 10.1038/ngeo2882
  6. Asner, G. P., Levick, S. R., Kennedy-Bowdoin, T., Knapp, D. E., Emerson, R., Jacobson, J., Colgan, M. S., & Martin, R. E. (2009). Large-scale impacts of herbivores on the structural diversity of African savannas. Proceedings of the National Academy of Sciences, 106(12), 49474952. 10.1073/pnas.0810637106
  7. Bacour, C., MacBean, N., Chevallier, F., Léonard, S., Koffi, E. N., & Peylin, P. (2023). Assimilation of multiple datasets results in large differences in regional- to global-scale NEE and GPP budgets simulated by a terrestrial biosphere model. Biogeosciences, 20(6), 10891111. 10.5194/bg-20-1089-2023
  8. Bayer, A. D., Fuchs, R., Mey, R., Krause, A., Verburg, P. H., Anthoni, P., & Arneth, A. (2021). Diverging land-use projections cause large variability in their impacts on ecosystems and related indicators for ecosystem services. Earth System Dynamics, 12(1), 327351. 10.5194/esd-12-327-2021
  9. Berzaghi, F., Longo, M., Ciais, P., Blake, S., Bretagnolle, F., Vieira, S., Scaranello, M., Scarascia-Mugnozza, G., & Doughty, C. E. (2019). Carbon stocks in central African forests enhanced by elephant disturbance. Nature Geoscience, 12(9), 725729. 10.1038/s41561-019-0395-6
  10. Bolyn, C., Lejeune, P., Michez, A., & Latte, N. (2022). Mapping tree species proportions from satellite imagery using spectral–spatial deep learning. Remote Sensing of Environment, 280, 113205. 10.1016/j.rse.2022.113205
  11. Bond, W. J., & Keeley, J. E. (2005). Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems. Trends in Ecology & Evolution, 20(7), 387394. 10.1016/j.tree.2005.04.025
  12. Brown, C., Alexander, P., Arneth, A., Holman, I. P., & Rounsevell, M. (2019). Achieving the Paris climate goals is challenged by time lags in the land system. Nature Climate Change. 10.1038/s41558-019-0400-5
  13. Brown, C., Holman, I., & Rounsevell, M. (2021). How modelling paradigms affect simulated future land use change. Earth Syst. Dynam., 12(1), 211231. 10.5194/esd-12-211-2021
  14. Brown, C., Seo, B., & Rounsevell, M. (2019). Societal breakdown as an emergent property of large-scale behavioural models of land use change. Earth Syst. Dynam., 10(4), 809845. 10.5194/esd-10-809-2019
  15. Brun, P., Zimmermann, N. E., Graham, C. H., Lavergne, S., Pellissier, L., Münkemüller, T., & Thuiller, W. (2019). The productivity-biodiversity relationship varies across diversity dimensions. Nature Communications, 10(1), 5691. 10.1038/s41467-019-13678-1
  16. Cabral, J. S., Mendoza-Ponce, A., da Silva, A. P., Oberpriller, J., Mimet, A., Kieslinger, J., Berger, T., Blechschmidt, J., Brönner, M., Classen, A., Fallert, S., Hartig, F., Hof, C., Hoffmann, M., Knoke, T., Krause, A., Lewerentz, A., Pohle, P., Raeder, U., … Zurell, D. (2024). The road to integrate climate change projections with regional land-use–biodiversity models. People and Nature, 6(5), 17161741. 10.1002/pan3.10472
  17. Chapman, M., Goldstein, B. R., Schell, C. J., Brashares, J. S., Carter, N. H., Ellis-Soto, D., Faxon, H. O., Goldstein, J. E., Halpern, B. S., Longdon, J., Norman, K. E. A., O’Rourke, D., Scoville, C., Xu, L., & Boettiger, C. (2024). Biodiversity monitoring for a just planetary future. Science, 383(6678), 3436. 10.1126/science.adh8874
  18. Creutzig, F., Erb, K. H., Haberl, H., Hof, C., Hunsberger, C., & Roe, S. (2021). Considering sustainability thresholds for BECCS in IPCC and biodiversity assessments. Global Change Biology Bioenergy, 13(4), 510515. 10.1111/gcbb.12798
  19. Cui, S., Gao, Y., Huang, Y., Shen, L., Zhao, Q., Pan, Y., & Zhuang, S. (2023). Advances and applications of machine learning and deep learning in environmental ecology and health. Environmental Pollution, 335, 122358. 10.1016/j.envpol.2023.122358
  20. Cummins, J. (2025). The threat of analytic flexibility in using large language models to simulate human data: A call to attention. arxiv. 10.48550/arXiv.2509.13397
  21. Dangal, S. R. S., Tian, H. Q., Lu, C. Q., Ren, W., Pan, S. F., Yang, J., Di Cosmo, N., & Hessl, A. (2017). Integrating herbivore population dynamics into a global land biosphere model: Plugging animals into the earth system. Journal of Advances in Modeling Earth Systems, 9(8), 29202945. 10.1002/2016ms000904
  22. Davison, C. W., Rahbek, C., & Morueta-Holme, N. (2021). Land-use change and biodiversity: Challenges for assembling evidence on the greatest threat to nature. Global Change Biology, 27(21), 54145429. 10.1111/gcb.15846
  23. Dullinger, I., Essl, F., Moser, D., Erb, K., Haberl, H., & Dullinger, S. (2021). Biodiversity models need to represent land-use intensity more comprehensively. Global Ecology and Biogeography, 30(5), 924932. 10.1111/geb.13289
  24. de Paula, M. D., Forrest, M., Langan, L., Bendix, J., Homeier, J., Velescu, A., Wilcke, W., & Hickler, T. (2021). Nutrient cycling drives plant community trait assembly and ecosystem functioning in a tropical mountain biodiversity hotspot. New Phytologist, 232(2), 551566. 10.1111/nph.17600
  25. Deprez, A., Leadley, P., Dooley, K., Williamson, P., Cramer, W., Gattuso, J. P., … Creutzig, F. (2024). Sustainability limits needed for CO2 removal. Science, 383(6682), 484486. 10.1126/science.adj6171
  26. Diaz General, E., Brown, C., & Rounsevell, M. D. A. (2025). Using socio-ecological interactions in the land system to estimate Quality of Life for people and nature. Ecosystems & People, in press. in press
  27. Dooley, K., Pelz, S., & Norton, A. (2024). Understanding land-based carbon dioxide removal in the context of the Rio Conventions. One Earth, 7(9), 15011514. 10.1016/j.oneear.2024.08.009
  28. Erb, K.-H., Luyssaert, S., Meyfroidt, P., Pongratz, J., Don, A., Kloster, S., Kuemmerle, T., Fetzel, T., Fuchs, R., Herold, M., Haberl, H., Jones, C. D., Marín-Spiotta, E., McCallum, I., Robertson, E., Seufert, V., Fritz, S., Valade, A., Wiltshire, A., & Dolman, A. J. (2016). Land management: data availability and process understanding for global change studies. Global Change Biology, 23(2), 512533. 10.1111/gcb.13443
  29. Fang, J., & Gentine, P. (2024). Exploring Optimal Complexity for Water Stress Representation in Terrestrial Carbon Models: A Hybrid-Machine Learning Model Approach. Journal of Advances in Modeling Earth Systems, 16(12), e2024MS004308. 10.1029/2024MS004308
  30. Farahbakhsh, I., Bauch, C. T., & Anand, M. (2022). Modelling coupled human–environment complexity for the future of the biosphere: strengths, gaps and promising directions. Philosophical Transactions of the Royal Society B: Biological Sciences, 377(1857), 20210382. 10.1098/rstb.2021.0382
  31. Farrell, M. J., Le Guillarme, N., Brierley, L., Hunter, B., Scheepens, D., Willoughby, A., … Mideo, N. (2024). The changing landscape of text mining: a review of approaches for ecology and evolution. Proceedings of the Royal Society B: Biological Sciences, 291(2027), 20240423. 10.1098/rspb.2024.0423
  32. Ferretto, A., Anthoni, P., Pugh, T. A. M., Gregor, K., Thurner, M., Natel, C., … Arneth, A. (2025). The impact of changing forest composition in Europe – longest carbon turnover time in unmanaged and broadleaved deciduous forests. Plos One. 10.1371/journal.pone.0334118
  33. Flombaum, P., Yahdjian, L., & Sala, O. E. (2017). Global-change drivers of ecosystem functioning modulated by natural variability and saturating responses. Global Change Biology, 23(2), 503511. 10.1111/gcb.13441
  34. Friedlingstein, P., Dufresne, J. L., Cox, P., & Rayner, P. (2003). How positive is the feedback between climate change and the carbon cycle? Tellus B, 55, 692700. 10.1034/j.1600-0889.2003.01461.x
  35. Friedlingstein, P., Le Quéré, C., O’Sullivan, M., Hauck, J., Landschützer, P., Luijkx, I. T., Li, H., van der Woude, A., Schwingshackl, C., Pongratz, J., Regnier, P., Andrew, R. M., Bakker, D. C. E., Canadell, J. G., Ciais, P., Gasser, T., Jones, M. W., Lan, X., Morgan, E., … Tian, H. (2026). Emerging climate impact on carbon sinks in a consolidated carbon budget. Nature, 649(8095), 98103. 10.1038/s41586-025-09802-5
  36. Friedlingstein, P., O’Sullivan, M., Jones, M. W., Andrew, R. M., Hauck, J., Landschützer, P., Le Quéré, C., Li, H. M., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., … Zeng, J. Y. (2025). Global carbon budget 2024. Earth Syst. Sci. Data, 17(3), 9651039. 10.5194/essd-17-965-2025
  37. Gabud, R., Lapitan, P., Mariano, V., Mendoza, E., Pampolina, N., Clariño, M. A. A., & Batista-Navarro, R. (2024). Unsupervised literature mining approaches for extracting relationships pertaining to habitats and reproductive conditions of plant species. Frontiers in Artificial Intelligence, 7, 1371411. 10.3389/frai.2024.1371411
  38. Gao, Y., Lee, D., Burtch, G., & Fazelpour, S. (2025). Take caution in using LLMs as human surrogates. Proceedings of the National Academy of Sciences, 122(24), e2501660122. 10.1073/pnas.2501660122
  39. Gougherty, A. V., & Clipp, H. L. (2024). Testing the reliability of an AI-based large language model to extract ecological information from the scientific literature. NPJ Biodiversity, 3(1), 13. 10.1038/s44185-024-00043-9
  40. Hantson, S., Kelley, D. I., Arneth, A., Harrison, S. P., Archibald, S., Bachelet, D., Forrest, M., Hickler, T., Lasslop, G., Li, F., Mangeon, S., Melton, J. R., Nieradzik, L., Rabin, S. S., Prentice, I. C., Sheehan, T., Sitch, S., Teckentrup, L., Voulgarakis, A., & Yue, C. (2020). Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project. Geoscientific Model Development, 13(7), 32993318. 10.5194/gmd-13-3299-2020
  41. Harfoot, M. B. J., Newbold, T., Tittensor, D. P., Emmott, S., Hutton, J., Lyutsarev, V., Smith, M. J., Scharlemann, J. P. W., & Purves, D. W. (2014). Emergent Global Patterns of Ecosystem Structure and Function from a Mechanistic General Ecosystem Model. Plos Biology, 12(4). 10.1371/journal.pbio.1001841
  42. Harrison, S. P., Prentice, I. C., Barboni, D., Kohfeld, K. E., Ni, J., & Sutra, J. P. (2010). Ecophysiological and bioclimatic foundations for a global plant functional classification [Review]. Journal of Vegetation Science, 21(2), 300317. 10.1111/j.1654-1103.2009.01144.x
  43. Herberstein, M. E., McLean, D. J., Lowe, E., Wolff, J. O., Khan, M. K., Smith, K., Allen, A. P., Bulbert, M., Buzatto, B. A., Eldridge, M. D. B., Falster, D., Fernandez Winzer, L., Griffith, S. C., Madin, J. S., Narendra, A., Westoby, M., Whiting, M. J., Wright, I. J., & Carthey, A. J. R. (2022). AnimalTraits – a curated animal trait database for body mass, metabolic rate and brain size. Scientific Data, 9(1), 265. 10.1038/s41597-022-01364-9
  44. Hoeks, S., Huijbregts, M. A. J., Busana, M., Harfoot, M. B. J., Svenning, J. C., & Santini, L. (2020), Mechanistic insights into the role of large carnivores for ecosystem structure and functioning. Ecography, 43(12), 17521763. 10.1111/ecog.05191
  45. Hooper, D. U., Adair, E. C., Cardinale, B. J., Byrnes, J. E. K., Hungate, B. A., Matulich, K. L., … O’Connor, M. I. (2012). A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature, 486, 105. 10.1038/nature11118
  46. Houghton, R. A. (1999). The annual net flux of carbon to the atmosphere from changes in land use 1850–1990. Tellus Series B, 51(2), 298313. 10.3402/tellusb.v51i2.16288
  47. Houghton, R. A. (2003). Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850–2000. Tellus B, 55, 378390. 10.1034/j.1600-0889.2003.01450.x
  48. Huang, Y., Chen, Y., Castro-Izaguirre, N., Baruffol, M., Brezzi, M., Lang, A., Li, Y., Härdtle, W., von Oheimb, G., Yang, X., Liu, X., Pei, K., Both, S., Yang, B., Eichenberg, D., Assmann, T., Bauhus, J., Behrens, T., Buscot, F., … Schmid, B. (2018). Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science, 362(6410), 8083. 10.1126/science.aat6405
  49. Ienco, D., Interdonato, R., Gaetano, R., & Ho Tong Minh, D. (2019). Combining sentinel-1 and sentinel-2 satellite image time series for land cover mapping via a multi-source deep learning architecture. ISPRS Journal of Photogrammetry and Remote Sensing, 158, 1122. 10.1016/j.isprsjprs.2019.09.016
  50. IPCC. (2018). Global Warming of 1.5°C.
  51. Iversen, C., McCormack, M., Powell, A., Blackwood, C., Freschet, G., Kattge, J., … Violle, C. (2017). A global Fine-Root Ecology Database to address below-ground challenges in plant ecology. New Phytologist, 215. 10.1111/nph.14486
  52. Jarvie, S., & Svenning, J. C. (2018). Using species distribution modelling to determine opportunities for trophic rewilding under future scenarios of climate change. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1761). 10.1098/rstb.2017.0446
  53. Jones, C., Cox, P., & Huntingford, C. (2003). Uncertainty in climate carbon-cycle projections associated with the sensitivity of soil respiration to temperature. Tellus B, 55, 642648. 10.1034/j.1600-0889.2003.01440.x
  54. Kattge, J., Bönisch, G., Díaz, S., Lavorel, S., Prentice, I. C., Leadley, P., Tautenhahn, S., Werner, G. D. A., Aakala, T., Abedi, M., Acosta, A. T. R., Adamidis, G. C., Adamson, K., Aiba, M., Albert, C. H., Alcántara, J. M., Alcázar, C. C., Aleixo, I., Ali, H., … Wirth, C. (2020). TRY plant trait database – enhanced coverage and open access. Global Change Biology, 26(1), 119188. 10.1111/gcb.14904
  55. Kattge, J., Diaz, S., Lavorel, S., Prentice, I. C., Leadley, P., Bönisch, G., Garnier, E., Westoby, M., Reich, P. B., Wright, I. J., Cornelissen, J. H. C., Violle, C., Harrison, S. P., van Bodegom, P. M., Reichstein, M., Enquist, B. J., Soudzilovskaia, N. A., Ackerly, D. D., Anand, M., … Wirth, C. (2011). TRY – a global database of plant traits. Global Change Biology, 17, 29052935. 10.1111/j.1365-2486.2011.02451.x
  56. Kautz, M., Anthoni, P., Meddens, A. J. H., Pugh, T. A. M., & Arneth, A. (2018). Simulating the recent impacts of multiple biotic disturbances on forest carbon cycling across the United States. Global Change Biology, 24(5), 20792092. 10.1111/gcb.13974
  57. Kautz, M., Meddens, A. J. H., Hall, R. J., & Arneth, A. (2017). Biotic disturbances in Northern Hemisphere forests – a synthesis of recent data, uncertainties and implications for forest monitoring and modelling. Global Ecology and Biogeography, 26, 533552. 10.1111/geb.12558
  58. Keppo, I., Butnar, I., Bauer, N., Caspani, M., Edelenbosch, O., Emmerling, J., Fragkos, P., Guivarch, C., Harmsen, M., Lefevre, J., Le Gallic, T., Leimbach, M., McDowall, W., Mercure, J. F., Schaeffer, R., Trutnevyte, E., & Wagner, F. (2021). Exploring the possibility space: taking stock of the diverse capabilities and gaps in integrated assessment models. Environmental Research Letters, 16(5). 10.1088/1748-9326/abe5d8
  59. Koldasbayeva, D., Tregubova, P., Gasanov, M., Zaytsev, A., Petrovskaia, A., & Burnaev, E. (2024). Challenges in data-driven geospatial modeling for environmental research and practice. Nature Communications, 15(1), 10700. 10.1038/s41467-024-55240-8
  60. Krause, J., Anthoni, P., Harfoot, M., Kupisch, M., & Arneth, A. (2025). Modelling herbivory impacts on vegetation structure and productivity. Geoscientific Model Development, 2025, 18. 10.5194/gmd-18-9633-2025
  61. Krause, J., Harfoot, M., Hoeks, S., Anthoni, P., Brown, C., Rounsevell, M., & Arneth, A. (2022). How more sophisticated leaf biomass simulations can increase the realism of modelled animal populations. Ecological Modelling, 471. 10.1016/j.ecolmodel.2022.110061
  62. Lade, S. J., Norberg, J., Anderies, J. M., Beer, C., Cornell, S. E., Donges, J. F., Fetzer, I., Gasser, T., Richardson, K., Rockström, J., & Steffen, W. (2019). Potential feedbacks between loss of biosphere integrity and climate change. Global Sustainability, 2, Article e21. 10.1017/sus.2019.18
  63. Lang, N., Jetz, W., Schindler, K., & Wegner, J. D. (2023). A high-resolution canopy height model of the Earth. Nature Ecology & Evolution, 7(11), 17781789. 10.1038/s41559-023-02206-6
  64. Langan, L., Scheiter, S., Hickler, T., & Higgins, S. I. (2025). Amazon forest resistance to drought is increased by diversity in hydraulic traits. Nature Communications, 16(1), 8246. 10.1038/s41467-025-63600-1
  65. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436444. 10.1038/nature14539
  66. Luo, Y., Ahlström, A., Allison, S. D., Batjes, N. H., Brovkin, V., Carvalhais, N., Chappell, A., Ciais, P., Davidson, E. A., Finzi, A., Georgiou, K., Guenet, B., Hararuk, O., Harden, J. W., He, Y., Hopkins, F., Jiang, L., Koven, C., Jackson, R. B., … Zhou, T. (2016). Toward more realistic projections of soil carbon dynamics by Earth system models. Global Biogeochemical Cycles, 30(1), 4056. 10.1002/2015GB005239
  67. Mahecha, M. D., Bastos, A., Bohn, F. J., Eisenhauer, N., Feilhauer, H., Hickler, T., … Quaas, J. (2024). Biodiversity and climate extremes: Known interactions and research gaps. Earth’s Future, 12(6), e2023EF003963. 10.1029/2023EF003963
  68. Malek, Ž., Douw, B., Van Vliet, J., Van Der Zanden, E. H., & Verburg, P. H. (2019). Local land-use decision-making in a global context. Environmental Research Letters, 14(8), 083006. 10.1088/1748-9326/ab309e
  69. Malhi, Y., Lander, T., le Roux, E., Stevens, N., Macias-Fauria, M., Wedding, L., Girardin, C., Kristensen, J. Å., Sandom, C. J., Evans, T. D., Svenning, J.-C., & Canney, S. (2022). The role of large wild animals in climate change mitigation and adaptation. Current Biology, 32(4), R181R196. 10.1016/j.cub.2022.01.041
  70. Marcos, D., Vlasakker, R. v. d., Athanasiadis, I. N., Bonnet, P., Goeau, H., Joly, A., Kissling, W. D., Leblanc, C., Proosdij, A. S. J. v., & Panousis, K. P. (2025). Fully automatic extraction of morphological traits from the Web: utopia or reality? Arxiv. 10.48550/arXiv.2409.17179
  71. Matthews, R. B., Gilbert, N. G., Roach, A., Polhill, J. G., & Gotts, N. M. (2007). Agent-based land-use models: A review of applications [Article]. Landscape Ecology, 22(10), 14471459. 10.1007/s10980-007-9135-1
  72. Murphy, E. J., Williams, J. J., Myers-Smith, I. H., Groner, V. P., Jacoby, D. M. P., Kwiatkowski, L., Melbourne-Thomas, J., Ransome, E., Banks-Leite, C., Bopp, L., Gehlen, M., Hofmann, E. E., Hoogakker, B., Johnston, N. M., Malhi, Y., & Cavan, E. L. (2026). Ecological feedbacks in the earth system. Earths Future, 14(2), Article e2025EF006478. 10.1029/2025ef006478
  73. Mokany, K., Ferrier, S., Connolly, S. R., Dunstan, P. K., Fulton, E. A., Harfoot, M. B., Harwood, T. D., Richardson, A. J., Roxburgh, S. H., Scharlemann, J. P. W., Tittensor, D. P., Westcott, D. A., & Wintle, B. A. (2016). Integrating modelling of biodiversity composition and ecosystem function. Oikos, 125(1), 1019. 10.1111/oik.02792
  74. Mori, A. S., Dee, L. E., Gonzalez, A., Ohashi, H., Cowles, J., Wright, A. J., Loreau, M., Hautier, Y., Newbold, T., Reich, P. B., Matsui, T., Takeuchi, W., Okada, K.I., Seidl, R., & Isbell, F. (2021). Biodiversity – productivity relationships are key to nature-based climate solutions. Nature Climate Change, 11(6), 543550. 10.1038/s41558-021-01062-1
  75. Newman, S. J., & Furbank, R. T. (2021). A multiple species, continent-wide, million-phenotype agronomic plant dataset. Scientific Data, 8(1), 116. 10.1038/s41597-021-00898-8
  76. O’Sullivan, M., Sitch, S., Friedlingstein, P., Luijkx, I. T., Peters, W., Rosan, T. M., Arneth, A., Arora, V. K., Chandra, N., Chevallier, F., Ciais, P., Falk, S., Feng, L., Gasser, T., Houghton, R. A., Jain, A. K., Kato, E., Kennedy, D., Knauer, J., … Zaehle, S. (2024). The key role of forest disturbance in reconciling estimates of the northern carbon sink. Communications Earth & Environment, 5(1). 10.1038/s43247-024-01827-4
  77. Pachzelt, A., Forrest, M., Rammig, A., Higgins, S. I., & Hickler, T. (2015). Potential impact of large ungulate grazers on African vegetation, carbon storage and fire regimes. Global Ecology and Biogeography, 24(9), 9911002. 10.1111/geb.12313
  78. Pachzelt, A., Rammig, A., Higgins, S., & Hickler, T. (2013). Coupling a physiological grazer population model with a generalized model for vegetation dynamics. Ecological Modelling, 263, 92102. 10.1016/j.ecolmodel.2013.04.025
  79. Papastefanou, P., Pugh, T. A. M., Buras, A., Fleischer, K., Grams, T. E. E., Hickler, T., Lapola, D., Liu, D. J., Zang, C. S., & Rammig, A. (2024). Simulated sensitivity of the Amazon rainforest to extreme drought. Environmental Research Letters, 19(12). 10.1088/1748-9326/ad8f48
  80. Pearce, E. A., Mazier, F., Normand, S., Fyfe, R., Andrieu, V., Bakels, C., Balwierz, Z., Bińka, K., Boreham, S., Borisova, O. K., Brostrom, A., de Beaulieu, J.-L., Gao, C., González-Sampériz, P., Granoszewski, W., Hrynowiecka, A., Kołaczek, P., Kuneš, P., Magri, D., … Svenning, J.-C. (2023). Substantial light woodland and open vegetation characterized the temperate forest biome before Homo sapiens. Science Advances, 9(45), eadi9135. 10.1126/sciadv.adi9135
  81. Perkins, O., Alexander, P., Arneth, A., Brown, C., Millington, J. D. A., & Rounsevell, M. (2023). Toward quantification of the feasible potential of land-based carbon dioxide removal. One Earth, 6(12), 16381651. 10.1016/j.oneear.2023.11.011
  82. Perry, G. L. W., Seidl, R., Bellvé, A. M., & Rammer, W. (2022). An outlook for deep learning in ecosystem science. Ecosystems, 25(8), 17001718. 10.1007/s10021-022-00789-y
  83. Piazza, N., Malanchini, L., Nevola, E., & Vacchiano, G. (2024). Where to start with climate-smart forest management? Climatic risk for forest-based mitigation. Nat. Hazards Earth Syst. Sci., 24(10), 35793595. 10.5194/nhess-24-3579-2024
  84. Pongratz, J., Dolman, H., Don, A., Erb, K.-H., Fuchs, R., Herold, M., Jones, C., Kuemmerle, T., Luyssaert, S., Meyfroidt, P., & Naudts, K. (2018). Models meet data: Challenges and opportunities in implementing land management in Earth system models. Global Change Biology, 24(4), 14701487. 10.1111/gcb.13988
  85. Pugh, T. A. M., Arneth, A., Kautz, M., Poulter, B., & Smith, B. (2019). Important role of forest disturbances in the global biomass turnover and carbon sinks. Nature Geoscience, 12, 730735. 10.1038/s41561-019-0427-2
  86. Pugh, T. A. M., Arneth, A., Olin, S., Ahlstrom, A., Bayer, A. D., Goldewijk, K. K., … Schurgers, G. (2015). Simulated carbon emissions from land-use change are substantially enhanced by accounting for agricultural management. Environmental Research Letters, 10(12). 10.1088/1748-9326/10/12/124008
  87. 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., … Arneth, A. (2017). The fire modeling intercomparison Project (FireMIP), phase 1: Experimental and analytical protocols with detailed model descriptions. Geoscientific Model Development, 10(3), 11751197. 10.5194/gmd-10-1175–;2017
  88. Raich, J. W., & Schlesinger, W. H. (1992). The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate. Tellus, 44B, 8199. 10.3402/tellusb.v44i2.15428
  89. Raoult, N., Douglas, N., MacBean, N., Kolassa, J., Quaife, T., Roberts, A. G., Fisher, R., Fer, I., Bacour, C., Dagon, K., Hawkins, L., Carvalhais, N., Cooper, E., Dietze, M. C., Gentine, P., Kaminski, T., Kennedy, D., Liddy, H. M., Moore, D. J. P., … Zobitz, J. (2025). Parameter estimation in land surface models: Challenges and opportunities with data assimilation and machine learning. Journal of Advances in Modeling Earth Systems, 17(11). 10.1029/2024MS004733
  90. Rizzuto, M., Leroux, S. J., & Schmitz, O. J. (2024). Rewiring the carbon cycle: A Theoretical framework for animal-driven ecosystem carbon sequestration. Journal of Geophysical Research: Biogeosciences, 129(4), e2024 JG008026. 10.1029/2024JG008026
  91. Robinson, D. T., Di Vittorio, A., Alexander, P., Arneth, A., Barton, C. M., Brown, D. G., Kettner, A., Lemmen, C., O’Neill, B. C., Janssen, M., Pugh, T. A. M., Rabin, S. S., Rounsevell, M., Syvitski, J. P., Ullah, I., & Verburg, P. H. (2018). Modelling feedbacks between human and natural processes in the land system. Earth System Dynamics, 9(2), 895914. 10.5194/esd-9-895-2018
  92. Rounsevell, M. D. A., Arneth, A., Brown, C., Cheung, W. W. L., Gimenez, O., Holman, I., Leadley, P., Luján, C., Mahevas, S., Maréchaux, I., Pélissier, R., Verburg, P. H., Vieilledent, G., Wintle, B. A., & Shin, Y.-J. (2021). Identifying uncertainties in scenarios and models of socio-ecological systems in support of decision-making. One Earth, 4(7), 967985. 10.1016/j.oneear.2021.06.003
  93. Rubiano Rivadeneira, N., & Carton, W. (2022). (In)justice in modelled climate futures: A review of integrated assessment modelling critiques through a justice lens. Energy Research & Social Science, 92, 102781. 10.1016/j.erss.2022.102781
  94. Runting, R. K., Bryan, B. A., Dee, L. E., Maseyk, F. J. F., Mandle, L., Hamel, P., Wilson, K. A., Yetka, K., Possingham, H. P., & Rhodes, J. R. (2017). Incorporating climate change into ecosystem service assessments and decisions: A review. Global Change Biology, 23(1), 2841. 10.1111/gcb.13457
  95. Sakschewski, B., von Bloh, W., Boit, A., Poorter, L., Pena-Claros, M., Heinke, J., … Thonicke, K. (2016). Resilience of Amazon forests emerges from plant trait diversity. Nature Clim. Change, 6(11), 10321036. 10.1038/nclimate3109
  96. Sakschewski, B., von Bloh, W., Boit, A., Rammig, A., Kattge, J., Poorter, L., … Thonicke, K. (2015). Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model. Global Change Biology, 21(7), 27112725. 10.1111/gcb.12870
  97. Sani-Mohammed, A., Yao, W., & Heurich, M. (2022). Instance segmentation of standing dead trees in dense forest from aerial imagery using deep learning. ISPRS Open Journal of Photogrammetry and Remote Sensing, 6, 100024. 10.1016/j.ophoto.2022.100024
  98. Sato, H., Chaste, E., Girardin, M. P., Kaplan, J. O., Hély, C., Candau, J.-N., & Mayor, S. J. (2023). Dynamically simulating spruce budworm in eastern Canada and its interactions with wildfire. Ecological Modelling, 483, 110412. 10.1016/j.ecolmodel.2023.110412
  99. Saxena, A., Brown, C., Winkler, K., Arneth, A., & Rounsevell, M. (2026). Spatial patterns of global land management intensity are influenced by socioeconomic, biophysical and behavioural factors. Earth Syst. Sci. Data Discuss., 2026, 155. 10.5194/essd-2026-482
  100. Scheepens, D., Millard, J., Farrell, M., & Newbold, T. (2024). Large language models help facilitate the automated synthesis of information on potential pest controllers. Methods in Ecology and Evolution, 15(7), 12611273. 10.1111/2041-210X.14341
  101. Scheiter, S., Langan, L., & Higgins, S. I. (2013). Next-generation dynamic global vegetation models: learning from community ecology. New Phytologist, 198(3), 957969. 10.1111/nph.12210
  102. Schiefer, F., Kattenborn, T., Frick, A., Frey, J., Schall, P., Koch, B., & Schmidtlein, S. (2020). Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks. Isprs Journal of Photogrammetry and Remote Sensing, 170, 205215. 10.1016/j.isprsjprs.2020.10.015
  103. Schiefer, F., Schmidtlein, S., Frick, A., Frey, J., Klinke, R., Zielewska-Büttner, K., Junttila, S., Uhl, A., & Kattenborn, T. (2023). UAV-based reference data for the prediction of fractional cover of standing deadwood from Sentinel time series. ISPRS Open Journal of Photogrammetry and Remote Sensing, 8, 100034. 10.1016/j.ophoto.2023.100034
  104. Schiller, C., Költzow, J., Schwarz, S., Schiefer, F., & Fassnacht, F. E. (2024). Forest disturbance detection in Central Europe using transformers and Sentinel-2 time series. Remote Sensing of Environment, 315, 114475. 10.1016/j.rse.2024.114475
  105. Schmitz, O., & Leroux, S. (2020). Food Webs and Ecosystems: Linking Species Interactions to the Carbon Cycle. Annual Review of Ecology, Evolution, and Systematics, 51, 125. 10.1146/annurev-ecolsys-011720-104730
  106. Schmitz, O. J., Wilmers, C. C., Leroux, S. J., Doughty, C. E., Atwood, T. B., Galetti, M., Davies, A. B., & Goetz, S. J. (2018). Animals and the zoogeochemistry of the carbon cycle. Science, 362(6419), eaar3213. 10.1126/science.aar3213
  107. Schuldt, A., Assmann, T., Brezzi, M., Buscot, F., Eichenberg, D., Gutknecht, J., Härdtle, W., He, J.-S., Klein, A.-M., Kühn, P., Liu, X., Ma, K., Niklaus, P. A., Pietsch, K. A., Purahong, W., Scherer-Lorenzen, M., Schmid, B., Scholten, T., Staab, M., … Bruelheide, H. (2018). Biodiversity across trophic levels drives multifunctionality in highly diverse forests. Nature Communications, 9(1), 2989. 10.1038/s41467-018-05421-z
  108. Sevekari, M., Brown, C., Díaz-General, E., & Rounsevell, M. (2025). Justice can and should become a part of feasibility assessments for climate mitigation policies. npj Climate Action, 4(1), 48. 10.1038/s44168-025-00255-0
  109. Seo, B., Brown, C., Lee, H., & Rounsevell, M. (2024). Bioenergy in Europe is unlikely to make a timely contribution to climate change targets. Environmental Research Letters, 19(4), 044004. 10.1088/1748-9326/ad2d11
  110. Shin, Y. J., Midgley, G. F., Archer, E. R. M., Arneth, A., Barnes, D. K. A., Chan, L., Hashimoto, S., Hoegh-Guldberg, O., Insarov, G., Leadley, P., Levin, L. A., Ngo, H. T., Pandit, R., Pires, A. P. F., Portner, H. O., Rogers, A. D., Scholes, R. J., Settele, J., & Smith, P. (2022). Actions to halt biodiversity loss generally benefit the climate. Global Change Biology, 28(9), 28462874. 10.1111/gcb.16109
  111. Sitch, S., O’Sullivan, M., Robertson, E., Friedlingstein, P., Albergel, C., Anthoni, P., Arneth, A., Arora, V. K., Bastos, A., Bastrikov, V., Bellouin, N., Canadell, J. G., Chini, L., Ciais, P., Falk, S., Harris, I., Hurtt, G., Ito, A., Jain, A. K., … Zaehle, S. (2024). Trends and Drivers of Terrestrial Sources and Sinks of Carbon Dioxide: An Overview of the TRENDY Project. Global Biogeochemical Cycles, 38(7). 10.1029/2024gb008102
  112. Smith, P., Arneth, A., Barnes, D. K. A., Ichii, K., Marquet, P. A.,Popp, A., Portner, H. O., Rogers, A. D., Scholes, R. J., Strassburg, B., Wu, J. G., & Ngo, H. (2022). How do we best synergize climate mitigation actions to co-benefit biodiversity? Global Change Biology, 28(8), 25552577. DOI: 10.1111/gcb.16056
  113. Smith, S. W., Johnson, D., Quin, S. L. O., Munro, K., Pakeman, R. J., Van der Wal, R., & Woodin, S. J. (2015). Combination of herbivore removal and nitrogen deposition increases upland carbon storage. Global Change Biology, 21(8), 30363048. 10.1111/gcb.12902
  114. Sommerfeld, A., Senf, C., Buma, B., D’Amato, A. W., Després, T., Díaz-Hormazábal, I., Fraver, S., Frelich, L. E., Gutiérrez, A. G., Hart, S. J., Harvey, B. J., He, H. S., Hlásny, T., Holz, A., Kitzberger, T., Kulakowski, D., Lindenmayer, D., Mori, A. S., Müller, J., … Seidl, R. (2018). Patterns and drivers of recent disturbances across the temperate forest biome. Nature Communications, 9. 10.1038/s41467-018-06788-9
  115. Son, R., Stacke, T., Gayler, V., Nabel, J. E. M. S., Schnur, R., Alonso, L., Requena-Mesa, C., Winkler, A. J., Hantson, S., Zaehle, S., Weber, U., & Carvalhais, N. (2024). Integration of a deep-learning-based fire model Into a global land surface model. Journal of Advances in Modeling Earth Systems, 16(1), e2023MS003710. 10.1029/2023MS003710
  116. Swart, R., Levers, C., Davis, J. T. M., & Verburg, P. H. (2023). Meta-analyses reveal the importance of socio- psychological factors for farmers adoption of sustainable agricultural practices. One Earth, 6(12), 17711783. 10.1016/j.oneear.2023.10.028
  117. Synes, N. W., Brown, C., Palmer, S. C. F., Bocedi, G., Osborne, P. E., Watts, K., Franklin, J., & Travis, J. M. J. (2019). Coupled land use and ecological models reveal emergence and feedbacks in socio-ecological systems. Ecography, 42(4), 814825. 10.1111/ecog.04039
  118. Talagrand, O., & Courtier, P. (1987). Variational assimilation of meteorological observations with the adjoint vorticity equation. I: Theory. Quarterly Journal of the Royal Meteorological Society, 113(478), 13111328. 10.1002/qj.49711347812
  119. Tanentzap, A. J., & Coomes, D. A. (2012). Carbon storage in terrestrial ecosystems: do browsing and grazing herbivores matter? Biological Reviews, 87(1), 7294. 10.1111/j.1469-185X.2011.00185.x
  120. Trepel, J., le Roux, E., Abraham, A. J., Buitenwerf, R., Kamp, J., Kristensen, J. A., Tietje, M., Lundgren, E. J., & Svenning, J.-C. (2024). Meta-analysis shows that wild large herbivores shape ecosystem properties and promote spatial heterogeneity. Nature Ecology & Evolution, 8(4), 705716. 10.1038/s41559-024-02327-6
  121. Tsiftsis, S., Štípková, Z., Rejmánek, M., & Kindlmann, P. (2024). Predictions of species distributions based only on models estimating future climate change are not reliable. Scientific Reports, 14(1), 25778. 10.1038/s41598-024-76524-5
  122. Turner, A. P., Field, C., Lobell, D., Sanchez, D., & Mach, K. (2018). Unprecedented rates of land-use transformation in modelled climate change mitigation pathways. Nature Sustainability, 1, 240245. 10.1038/s41893-018-0063-7
  123. van Bodegom, P. M., Douma, J. C., & Verheijen, L. M. (2014). A fully traits-based approach to modeling global vegetation distribution. Proceedings of the National Academy of Sciences, 111(38), 1373313738. 10.1073/pnas.1304551110
  124. Wegler, M., Kacic, P., Thonfeld, F., Holzwarth, S., Jaggy, N., Gessner, U., & Kuenzer, C. (2025). Tree species from space: a new product for Germany based on Sentinel-1 and –2 time series. International Journal of Remote Sensing, 46(16), 60756108. 10.1080/01431161.2025.2530236
  125. Weiskopf, S. R., Isbell, F., Arce-Plata, M. I., Di Marco, M., Harfoot, M., Johnson, J., Lerman, S. B., Miller, B. W., Morelli, T. L., Mori, A. S., Weng, E., & Ferrier, S. (2024). Biodiversity loss reduces global terrestrial carbon storage. Nature Communications, 15(1), 4354. 10.1038/s41467-024-47872-7
  126. Winkler, K., Fuchs, R., Rounsevell, M., & Herold, M. (2021). Global land use changes are four times greater than previously estimated. Nature Communications, 12(1), 2501. 10.1038/s41467-021-22702-2
  127. Wolf, S., Mahecha, M. D., Sabatini, F. M., Wirth, C., Bruelheide, H., Kattge, J., Moreno Martínez, Á., Mora, K., & Kattenborn, T. (2022). Citizen science plant observations encode global trait patterns. Nature Ecology & Evolution, 6(12), 18501859. 10.1038/s41559-022-01904-x
  128. Wu, L., Kato, T., Sato, H., Hirano, T., & Yazaki, T. (2019). Sensitivity analysis of the typhoon disturbance effect on forest dynamics and carbon balance in the future in a cool-temperate forest in northern Japan by using SEIB- DGVM. Forest Ecology and Management, 451. 10.1016/j.foreco.2019.117529
  129. Zeng, Y., Brown, C., Byari, M., Raymond, J., Schmitt, T., & Rounsevell, M. (2025). InsNet-CRAFTY v1.0: Integrating institutional network dynamics powered by large language models with land use change simulation. Geosci. Model Dev., 18(15), 49835013. 10.5194/gmd-18-4983-2025
  130. Zeng, Y., Brown, C., Raymond, J., Byari, M., Hotz, R., & Rounsevell, M. (2024). Exploring the opportunities and challenges of using large language models to represent institutional agency in land system modelling. EGUsphere, 2024, 135. 10.5194/egusphere-2024-449
Language: English
Page range: 147 - 159
Submitted on: Nov 5, 2025
Accepted on: May 29, 2026
Published on: Jul 20, 2026
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2026 Almut Arneth, Thomas Hickler, Jens Krause, Carolina Natel, Mark Rounsevell, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.