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Using Dynamic Global Vegetation Models (DGVMs) for Projecting Ecosystem Services at Regional Scales

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Abstract

Climate change and land-use change are two major drivers of vegetation change causing habitat and biodiversity loss and posing a threat to the sustained provisioning of ecosystem goods and services. Following-up on the Millennium Ecosystem Assessment, the Sustainable Development Goals have been a fresh stimulus to the current interest in ecosystem services. Dynamic Global Vegetation Models (DGVMs) offer the possibility of integrating large amounts of geospatial data to quantify and project a large range of ecological variables important for ecosystem service provisioning under future scenarios. We outline how such model output could be used for projecting ecosystem service provisioning.

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References

  1. Boit A, Sakschewski B, Boysen L, Cano-crespo A, Clement J, Garcia-Alaniz N, et al. Large-scale impact of climate change vs land-use change on future biome shifts in Latin America. Glob Chang Biol. 2016;22(11):3689–701.

    Article  Google Scholar 

  2. Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, van Vuuren DP, et al. The next generation of scenarios for climate change research and assessment. Nature. 2010;463:747–56.

    Article  CAS  Google Scholar 

  3. Sitch S, Smith B, Prentice IC, Arneth A, Bondeau A, Cramer W, et al. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob Chang Biol. 2003;9:161–85.

    Article  Google Scholar 

  4. Bondeau A, Smith PC, Zaehle S, Schaphoff S, Lucht W, Cramer W, et al. Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Glob Chang Biol. 2007;13:679–706.

    Article  Google Scholar 

  5. Yin L, Fu R, Shevliakova E, Dickinson R. How well can CMIP5 simulate precipitation and its controlling processes over tropical South America? Clim Dyn. 2013;41:3127–43.

    Article  Google Scholar 

  6. Haines-Young R, Potschin M. The links between biodiversity, ecosystem services and human well-being. In: Raffaelli C, Frid C, editors. Ecosystem ecology: a new synthesis. Cambridge: Cambridge University Press; 2010.

    Google Scholar 

  7. Bennett EM, Peterson GD, Gordon LJ. Understanding relationships among multiple ecosystem services. Ecol Lett. 2009;12:1394–404.

    Article  Google Scholar 

  8. Mouchet MA, Lamarque P, Martín-López B, Crouzat E, Gos P, Byczek C, et al. An interdisciplinary methodological guide for quantifying associations between ecosystem services. Glob Environ Chang. 2014;28:298–308.

    Article  Google Scholar 

  9. Lamarque P, Lavorel S, Mouchet M, Quétier F. Plant trait-based models identify direct and indirect effects of climate change on bundles of grassland ecosystem services. Proc Natl Acad Sci U S A. 2014;111:13751–6.

    Article  CAS  Google Scholar 

  10. Prentice IC, Bondeau A, Cramer W, Harrison SP, Hickler T, Lucht W, et al. Dynamic global vegetation modeling: quantifying terrestrial ecosystem responses to large-scale environmental change. In: Canadell JG, Pataki DE, Pitelka LF, editors. Terrestrial ecosystems in a changing world. Berlin: Springer; 2007. p. 175–92.

    Chapter  Google Scholar 

  11. Scheiter S, Langan L, Higgins SI. Next-generation dynamic global vegetation models: learning from community ecology. New Phytol. 2013;198:957–69.

    Article  Google Scholar 

  12. Sakschewski B, von Bloh W, Boit A, Poorter L, Pena-Claros M, Heinke J, et al. Resilience of Amazon forests emerges from plant trait diversity. Nat Clim Chang. 2016;6:1032–6.

    Article  Google Scholar 

  13. Oliver TH, Morecroft MD. 2014. Interactions between climate change and land use change on biodiversity: attribution problems, risks, and opportunities. WIREs Clim Change. 2014;5:317–35.

    Article  Google Scholar 

  14. Arneth A, Brown C, Rounsevell MDA. Global models of human decision-making for land-based mitigation and adaptation assessment. Nat Clim Chang. 2014;4:550–7.

    Article  Google Scholar 

  15. Langerwisch F, Václavík T, von Bloh W, Vetter T, Thonicke K. Combined effects of climate and land-use change on the provision of ecosystem services in rice agro-ecosystems 2017 Environ. Res. Lett. 13 015003. https://doi.org/10.1088/1748-9326/aa954d

    Article  Google Scholar 

  16. Tallis H, Mooney H, Andelman S, Balvanera P, Cramer W, Karp D, et al. A global system for monitoring ecosystem service change. Bioscience. 2012;62:977–86.

    Article  Google Scholar 

  17. Karp DS, Tallis H, Sachse R, Halpern B, Thonicke K, Cramer W, et al. National indicators for observing ecosystem service change. Glob Environ Chang. 2015;35:12–21.

    Article  Google Scholar 

  18. Balvanera P, Quijas S, Karp D, Ash N, Bennett E, Boumans R, et al. The GEO handbook on biodiversity observation networks. In: Walters M, Scholes RJ, editors. The GEO handbook on biodiversity observation networks. Berlin: Springer Berlin; 2017. p. 39–78.

    Chapter  Google Scholar 

  19. Bagstad KJ, Semmens DJ, Waage S, Winthrop R. A comparative assessment of decision-support tools for ecosystem services quantification and valuation. Ecosyst Serv. 2013;5:27–39.

    Article  Google Scholar 

  20. Grima N, Singh SJ, Smetschka B, Ringhofer L. Payment for ecosystem services (PES) in Latin America: analysing the performance of 40 case studies. Ecosyst Serv. 2016;17:24–32.

    Article  Google Scholar 

  21. Pugh T, Arneth A, Olin S, Ahlström A, Bayer D, Goldewijk K, et al. Simulated carbon emissions from land-use change are substantially enhanced by accounting for agricultural management. Environ Res Lett. 2015;10:124008.

    Article  Google Scholar 

  22. Tian X, Sohngen B, Kim J, Ohrel S, Cole J. Global climate change impacts on forests and markets. Environ Res Lett. 2016;11:35011.

    Article  Google Scholar 

  23. Ukkola AM, Prentice IC. A worldwide analysis of trends in water-balance evapotranspiration. Hydrol Earth Syst Sci. 2013;17:4177–87.

    Article  Google Scholar 

  24. Mao J, Fu W, Shi X, Ricciuto D, Fisher J, Dickinson R, et al. Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends. Environ Res Lett. 2015;10:094008.

    Article  Google Scholar 

  25. Fader M, Rost S, Müller C, Bondeau A, Gerten D. Virtual water content of temperate cereals and maize: present and potential future patterns. J Hydrol. 2010;384:218–31.

    Article  CAS  Google Scholar 

  26. Sakschewski B, von Bloh W, Huber V, Müller C, Bondeau A. Feeding 10 billion people under climate change: how large is the production gap of current agricultural systems? Ecol Model. 2014;288:103–11.

    Article  Google Scholar 

  27. Rolinski S, Müller C, Heinke J, Weindl I, Biewald A, Bodirsky BL, et al. Modeling vegetation and carbon dynamics of managed grasslands at the global scale with LPJmL 3.6. Geosci Model Dev Discuss. Geosci. Model Dev. 2018; 11, 429–451. https://doi.org/10.5194/gmd-11-429-2018

    Article  Google Scholar 

  28. Boysen LR, Lucht W, Gerten D, Heck V. Impacts devalue the potential of large-scale terrestrial CO2 removal through biomass plantations. Environ Res Lett. 2016;11:095010.

    Article  Google Scholar 

  29. Fujii S, Kubota Y. Understory thinning reduces wood-production efficiency and tree species diversity in subtropical forest in southern Japan. J For Res. 2011;16:253–9.

    Article  Google Scholar 

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Correspondence to Alice Boit .

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Boit, A. et al. (2019). Using Dynamic Global Vegetation Models (DGVMs) for Projecting Ecosystem Services at Regional Scales. In: Schröter, M., Bonn, A., Klotz, S., Seppelt, R., Baessler, C. (eds) Atlas of Ecosystem Services. Springer, Cham. https://doi.org/10.1007/978-3-319-96229-0_10

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