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What ecologists should know before using land use/cover change projections for biodiversity and ecosystem service assessments

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Abstract

Scenarios of biodiversity and ecosystem services (BES) are key for decision-makers to understand the consequences of future environmental change on BES. Though a major driver of terrestrial biodiversity loss, land use and land cover changes (LUCC) have been largely overlooked in previous BES assessments. But ecologists lack practical guidance for the general use of LUCC projections. We review the practices in use in LUCC-driven BES assessments and summarize the questions ecologists should address before using LUCC projections. LUCC-driven BES scenarios rely on a substantial set of different socioeconomic storylines (> 200 for 166 papers). Studies explore different futures, but generally concentrate on projections obtained from a single LUCC model. The rationale regarding time horizon, spatial resolution, or the set of storylines used is rarely made explicit. This huge heterogeneity and low transparency regarding the what, why, and how of using LUCC projections for the study of BES futures could discourage researchers from engaging in the design of such biodiversity scenarios. Our results call on those using LUCC projections to more systematically report on the choices they make when designing LUCC-based BES scenarios (e.g. time horizon, spatial and thematic resolutions, scope of contrasted futures). Beyond the improvement of reliability, reproducibility, and comparability of these scenarios, this could also greatly benefit others wanting to use the same LUCC projections, and help land use modellers better meet the needs of their intended audiences. The uncertainties in LUCC-driven BES futures should also be explored more comprehensively, including different socioeconomic storylines and different LUCC models, as recommended in studies dealing with climate-driven BES futures.

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References

  • Alexander P, Prestele R, Verburg PH, Arneth A, Baranzelli C, Batista e Silva F, Brown C, Butler A, Calvin K, Dendoncker N, Doelman JC, Dunford R, Engstrom K, Eitelberg D, Fujimori S, Harrison PA, Hasegawa T, Havlik P, Holzhauer S, Humpenoder F, Jacobs-Crisoni C, Jain AK, Krisztin T, Kyle P, Lavalle C, Lenton T, Liu J, Meiyappan P, Popp A, Powell T, Sands RD, Schaldach R, Stehfest E, Steinbuks J, Tabeau A, Van Meijl H, Wise MA, Rounsevell MDA (2017) Assessing uncertainties in land cover projections. Glob Change Biol 23:767–781. https://doi.org/10.1111/gcb.13447

  • Biggs R, Raudsepp-Hearne C, Atkinson-Palombo C, Bohensky E, Boyd E, Cundill G, Fox H, Ingram S, Kok K, Spehar S, Tengö M,Timmer D, Zurek M (2007) Linking futures across scales: a dialog on multiscale scenarios. Ecol Soc 12:17. http://www.ecologyandsociety.org/vol12/iss1/art17/

  • Brockerhoff EG, Jactel H, Parrotta JA, Quine CP, Sayer J (2008) Plantation forests and biodiversity: oxymoron or opportunity? Biodivers Conserv 17:925–951. https://doi.org/10.1007/s10531-008-9380-x

  • Brunner SH, Huber R, Grêt-Regamey A (2016) A backcasting approach for matching regional ecosystem services supply and demand. Environ Model Softw 75:439–458. https://doi.org/10.1016/j.envsoft.2015.10.018

    Article  Google Scholar 

  • Dale VH, Pearson SM, Offerman HL, O’Neill RV (1994) Relating patterns of land-use change to faunal biodiversity in the Central Amazon. Conserv Biol 8:1027–1036. https://doi.org/10.1046/j.1523-1739.1994.08041027.x

    Article  Google Scholar 

  • de Chazal J, Rounsevell MDA (2009) Land-use and climate change within assessments of biodiversity change: a review. Glob Environ Change 19:306–315. https://doi.org/10.1016/j.gloenvcha.2008.09.007

    Article  Google Scholar 

  • Dendoncker N, Bogaert P, Rounsevell MDA (2006) A statistical method to downscale aggregated land use data and scenarios. J Land Use Sci 1:63–82. https://doi.org/10.1080/17474230601058302

  • Dislich C, Hettig E, Salecker J, Heinonen J, Lay J, Meyer KM, Wiegand K, Tarigan S (2018) Land-use change in oil palm dominated tropical landscapes—an agent-based model to explore ecological and socio-economic trade-offs. PLoS One 13:1–20. https://doi.org/10.1371/journal.pone.0190506

  • Eigenbrod F, Bell VA, Davies HN, Heinemeyer A, Armsworth PR, Gaston KJ (2011) The impact of projected increases in urbanization on ecosystem services. Proc R Soc B-Biol Sci 278:3201–3208. https://doi.org/10.1098/rspb.2010.2754

  • Galvani AP, Bauch CT, Anand M, Singer BH, Levin SA (2016) Human–environment interactions in population and ecosystem health. Proc Natl Acad Sci 113:14502–14506. https://doi.org/10.1073/pnas.1618138113

  • Gil-Tena A, Lecerf R, Ernoult A (2013) Disentangling community assemblages to depict an indicator of biological connectivity: a regional study of fragmented semi-natural grasslands. Ecol Indic 24:48–55. https://doi.org/10.1016/j.ecolind.2012.05.022

    Article  Google Scholar 

  • Gonzalez A, Thompson P, Loreau M (2017) Spatial ecological networks: planning for sustainability in the long-term. Curr Opin Environ Sustain 29:187–197. https://doi.org/10.1016/j.cosust.2018.03.012

    Article  Google Scholar 

  • Graham LJ, Haines-Young RH, Field R (2017) Metapopulation modelling of long-term urban habitat-loss scenarios. Landsc Ecol 32:989–1003. https://doi.org/10.1007/s10980-017-0504-0

    Article  Google Scholar 

  • Groeneveld J, Müller B, Buchmann CM, Dressler G, Guoc C, Hase N, Hoffmann F, John F, Klassert C, Laufe T, Liebelt V, Nolzen H, Pannicke N, Schulze J, Weiseg H, Schwarz N (2017) Theoretical foundations of human decision-making in agent-based land use models – a review. Environ Model Softw 87:39–48. https://doi.org/10.1016/j.envsoft.2016.10.008

  • Harfoot M, Tittensor DP, Newbold T, McInerny G, Smith MJ, Scharlemann JPW (2014) Integrated assessment models for ecologists: the present and the future. Glob Ecol Biogeogr 23:124–143. https://doi.org/10.1111/geb.12100

  • Harmáčková ZV, Vačkář D (2018) Future uncertainty in scenarios of ecosystem services provision: linking differences among narratives and outcomes. Ecosyst Serv 33:134–145. https://doi.org/10.1016/j.ecoser.2018.06.005

    Article  Google Scholar 

  • Hervé M, Albert CH, Bondeau A (2016) On the importance of taking into account agricultural practices when defining conservation priorities for regional planning. J Nat Conserv 33:76–84. https://doi.org/10.1016/j.jnc.2016.08.001

    Article  Google Scholar 

  • Houet T, Grémont M, Vacquié L, Forget Y, Marriotti A, Puissant A, Bernardie S, Thiery Y, Vandromme R, Grandjean G (2017) Downscaling scenarios of future land use and land cover changes using a participatory approach: an application to mountain risk assessment in the Pyrenees (France). Reg Environ Chang. 17:2293-2307 https://doi.org/10.1007/s10113-017-1171-z

  • Hunt DVL, Lombardi DR, Atkinson S, Barber ARG, Barnes M, Boyko CT, Brown J, Bryson J, Butler D, Caputo S, Caserio M, Coles R, Cooper RFD, Farmani R, Gaterell M, Hale J, Hales C, Hewitt CN, Jankovic L, Jefferson I, Leach J, MacKenzie AR, Memon FA, Sadler JP, Weingaertner C, Whyatt JD, Rogers CDF (2012) Scenario archetypes: converging rather than diverging themes. Sustainability 4:740–772. https://doi.org/10.3390/su4040740

  • Hurtt GC, Chini LP, Frolking S, Betts RA, Feddema J, Fischer G, Fisk JP, Hibbard K, Houghton RA, Janetos A, Jones CD, Kindermann G, Kinoshita T, Goldewijk KK, Riahi K, Shevliakova E, Smith S, Stehfest E, Thomson A, Thornton P, van Vuuren DP, Wang YP (2011) Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Clim Chang 109:117. https://doi.org/10.1007/s10584-011-0153-2

  • IPBES (2016) The methodological assessment report on scenarios and models of biodiversity and ecosystem services. S. Ferrier, K. N. Ninan, P. Leadley, R. Alkemade, L.A. Acosta, H. R. Akçakaya, L. Brotons, W. Cheung, V. Christensen, K. A. Harhash, J. Kabubo-Mariara, C. Lundquist, M. Obersteiner, H. Pereira, G. Peterson, R. Pichs-Madruga, N. H. Ravindranath, C. Rondinini, B. Wintle, Secretariat of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, Bonn, Germany

  • IPBES (2019) Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. E. S. Brondizio, J. Settele, S. Díaz, and H. T. Ngo (editors). IPBES secretariat, Bonn, Germany

  • IPCC (2014) Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC. Core Writing Team, R.K. Pachauri and L.A. Meyer, Geneva, Switzerland

  • Jepsen MR, Kuemmerle T, Müller D, Erb K, Verburg PH, Haberl H, Vesterager JP, Andric M, Antrop M, Austrheim G, Björn I, Bondeau A, Bürgi M, Bryson J, Caspar G, Cassar LF, Conrad E, Chromy P, Daugirdas V, Van Eetvelde V, Elena-Rosselló R, Gimmi U, Izakovicova Z, Jancák V, Jansson U, Kladnik D, Kozak J, Konkoly-Gyuró E, Krausmann F, Mander U, McDonagh J, Pärn J, Niedertscheider M, Nikodemus O, Ostapowicz K, Pérez-Soba M, Pinto-Correia T, Ribokas G, Rounsevell MDA, Schistou D, Schmit C, Terkenli TS, Tretvik AM, Trzepacz P, Vadineanu A, Walz A, Zhllima E, Reenberg A (2015) Transitions in European land-management regimes between 1800 and 2010. Land Use Policy 49:53–64. https://doi.org/10.1016/j.landusepol.2015.07.003

  • Jiang W, Deng Y, Tang Z, Lei X, Chen Z (2017) Modelling the potential impacts of urban ecosystem changes on carbon storage under different scenarios by linking the CLUE-S and the InVEST models. Ecol Model 345:30–40. https://doi.org/10.1016/j.ecolmodel.2016.12.002

  • Kim H, Rosa IMD, Alkemade R, Leadley P, Hurtt G, Popp A, van Vuuren DP, Anthoni P, Arneth A, Baisero D, Caton E, Chaplin-Kramer R, Chini L, De Palma A, Di Fulvio F, Di Marco M, Espinoza F, Ferrier S, Fujimori S, Gonzalez RE, Gueguen M, Guerra C, Harfoot M, Harwood TD, Hasegawa T, Haverd V, Havlík P, Hellweg S, Hill SLL, Hirata A, Hoskins AJ, Janse JH, Jetz W, Johnson JA, Krause A, Leclère D, Martins IS, Matsui T, Merow C, Obersteiner M, Ohashi H, Poulter B, Purvis A, Quesada B, Rondinini C, Schipper AM, Sharp R, Takahashi K, Thuiller W, Titeux N, Visconti P, Ware C, Wolf F, Pereira HM (2018) A protocol for an intercomparison of biodiversity and ecosystem services models using harmonized land-use and climate scenarios. Geosci Model Dev 11:4537–4562. https://doi.org/10.5194/gmd-11-4537-2018

  • Kok K, Pedde S, Gramberger M, Harrison PA, Holman IP (2018) New European socio-economic scenarios for climate change research: operationalising concepts to extend the shared socio-economic pathways. Reg Environ Chang 19: 643–654 https://doi.org/10.1007/s10113-018-1400-0

  • Kok MTJ, Kok K, Peterson GD, Hill R, Agard J, Carpenter SR (2017) Biodiversity and ecosystem services require IPBES to take novel approach to scenarios. Sustain Sci 12:177–181. https://doi.org/10.1007/s11625-016-0354-8

  • Kuemmerle T, Levers C, Erb K, Estel S, Jepsen MR, Müller D, Plutzar C, Stürck J, Verkerk PJ, Verburg PH, Reenberg A (2016) Hotspots of land use change in Europe. Environ Res Lett 11:064020. https://doi.org/10.1088/1748-9326/11/6/064020

  • McPherson JM, Jetz W, Rogers DJ (2006) Using coarse-grained occurrence data to predict species distributions at finer spatial resolutions—possibilities and limitations. Ecol Model 192:499–522. https://doi.org/10.1016/j.ecolmodel.2005.08.007

    Article  Google Scholar 

  • Metzger MJ, Leemans R, Schröter D, Cramer W (2004) The ATEAM vulnerability mapping tool: explore the vulnerability of different sectors to global change impacts in Europe. C.T. de Wit Graduate School for Production Ecology & Resource Conservation (PE & RC), Wageningen

  • Millennium Ecosystem Assessment (2005) Ecosystems and human well-being. Island Press, USA

    Google Scholar 

  • Morán-Ordóñez A, Roces-Díaz JV, Otsu K, Ameztegui A, Coll L, Lefevre F, Retana J, Brotons L (2018) The use of scenarios and models to evaluate the future of nature values and ecosystem services in Mediterranean forests. Reg Environ Chang. 19:415-428 https://doi.org/10.1007/s10113-018-1408-5

  • Nakićenović N and Swart R (2000) Special report on emissions scenarios, intergovernmental panel on climate change, Cambridge University Press. Cambridge, United Kingdom and New York

  • Newbold T, Hudson LN, Arnell AP, Contu S, De Palma A, Ferrier S, Hill SLL, Hoskins AJ, Lysenko I, Phillips HRP, Burton VJ, Chang CWT, Emerson S, Gao D, Pask-Hale G, Hutton J, Jung M, Sanchez-Ortiz K, Simmons BI, Whitmee S, Zhang H, Scharlemann JPW, Purvis A (2016) Has land use pushed terrestrial biodiversity beyond the planetary boundary? A global assessment. Science 353:288–291. https://doi.org/10.1126/science.aaf2201

  • O’Neill BC, Kriegler E, Ebi KL, Kemp-Benedict E, Riahi K, Rothman DS, van Ruijven BJ, van Vuuren DP, Birkmann J, Kok K, Levy M, Solecki W (2017) The roads ahead: narratives for shared socioeconomic pathways describing world futures in the 21st century. Glob Environ Change 42:169–180. https://doi.org/10.1016/j.gloenvcha.2015.01.004

  • Opdam P, Wascher D (2004) Climate change meets habitat fragmentation: linking landscape and biogeographical scale levels in research and conservation. Biol Conserv 117:285–297. https://doi.org/10.1016/j.biocon.2003.12.008

    Article  Google Scholar 

  • Pereira HM, Leadley PW, Proença V, Alkemade R, Scharlemann JPW, Fernandez-Manjarrés JF, Araújo MB, Balvanera P, Biggs R, Cheung WWL, Chini L, Cooper HD, Gilman EL, Guénette S, Hurtt GC, Huntington HP, Mace GM, Oberdorff T, Revenga C, Rodrigues P, Scholes RJ, Sumaila UR, Walpole M (2010) Scenarios for global biodiversity in the 21st century. Science 330:1496–1501. https://doi.org/10.1126/science.1196624

  • Petchey OL, Pontarp M, Massie TM, Kefi S, Ozgul A, Weilenman M, Palamara GM, Altermatt F, Blake M, Levine JM, Childs DZ, McGill BJ, Schaepman ME, Schmid B, Spaak P, Beckerman AP, Pennekamp F, Pearse IS (2015) The ecological forecast horizon, and examples of its uses and determinants. Ecol Lett 18:597–611. https://doi.org/10.1111/ele.12443

  • Pickard BR, Van Berkel D, Petrasova A, Meentemeyer RK (2017) Forecasts of urbanization scenarios reveal trade-offs between landscape change and ecosystem services. Landsc Ecol 32:617–634. https://doi.org/10.1007/s10980-016-0465-8

    Article  Google Scholar 

  • Plieninger T, Draux H, Fagerholm N, Bieling C, Bürgi M, Kizose T, Kuemmerle T, Primdahl J, Verburg PH (2016) The driving forces of landscape change in Europe: a systematic review of the evidence. Land Use Policy 57:204–214. https://doi.org/10.1016/j.landusepol.2016.04.040

  • Popp A, Calvin K, Fujimori S, Havlik P, Humpenöder F, Stehfest E, Leon Bodirsky B, Dietrich JP, Doelmann J, Gusti M, Hasegawa T, Kyle P, Obersteiner M, Tabeau A, Takahashi A, Valin H, Waldhoff S, Weindla I, Wise M, Kriegler E, Lotze-Campena H, Fricko O, Riahid K, vanVuuren DP (2017) Land-use futures in the shared socio-economic pathways. Glob Environ Change 42:331–345. https://doi.org/10.1016/j.gloenvcha.2016.10.002

  • Prestele R, Alexander P, Rounsevell MDA, Arneth A, Calvin K, Doelman J, Eitelberg DA, Engström K, Fujimori S, Hasegawa T, Havlik P, Humpenöder F, Jain AK, Krisztin T, Kyle P, Meiyappan P, Popp A, Sands RD, Schaldach R, Schüngel J, Stehfest E, Tabeau A, Meijl HV, Van Vliet J, Verburg PH (2016) Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison. Glob Change Biol 22:3967–3983. https://doi.org/10.1111/gcb.13337

  • Prudhomme C, Giuntoli I, Robinson EL, Clark DB, Arnell NW, Dankers R, Fekete BM, Franssen W, Gerten D, Gosling SN, Hagemann S, Hannah DM, Kim H, Masaki Y, Satoh Y, Stacke T, Wada Y, Wisser D (2014) Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment. Proc Natl Acad Sci 111:3262–3267. https://doi.org/10.1073/pnas.1222473110

  • Radinger J, Hölker F, Horký P, Slavik O, Dendoncker N, Wolter C (2016) Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages. Glob Change Biol 22:1505–1522. https://doi.org/10.1111/gcb.13183

  • Rickebusch S, Metzger MJ, Xu G, Vogiatzakis IN, Potts SP, Stirpe MT, Rounsevell MDA (2011) A qualitative method for the spatial and thematic downscaling of land-use change scenarios. Environ Sci Pol 14:268–278. https://doi.org/10.1016/j.envsci.2010.11.003

  • Riordan EC, Gillespie TW, Pitcher L, Pincetl SS, Jenerette GD, Pataki DE (2015) Threats of future climate change and land use to vulnerable tree species native to Southern California. Environ Conserv 42:127–138. https://doi.org/10.1017/S0376892914000265

  • Rosa IMD, Pereira HM, Ferrier S, Alkemade R, Acosta LA, Akcakaya HR, den Belder E, Fazel AM, Fujimori S, Harfoot M, Harhash KA, Harrison PA, Hauck J, Hendriks RJJ, Hernández G, Jetz W, Karlsson-Vinkhuyzen SI, Kim HJ, King N, Kok MTJ, Kolomytsev GO, Lazarova T, Leadley P, Lundquist CJ, García Márquez J, Meyer C, Navarro LM, Nesshöver C, Ngo HT, Ninan KN, Palomo MG, Pereira LM, Peterson GD, Richs R, Popp A, Purvis A, Ravera F, Rondinini C, Sathyapalan J, Schipper AM, Seppelt R, Settele J, Sitas N, van Vuuren D (2017) Multiscale scenarios for nature futures. Nat Ecol Evol 1:1416–1419. https://doi.org/10.1038/s41559-017-0273-9

  • Rounsevell MDA, Metzger MJ (2010) Developing qualitative scenario storylines for environmental change assessment: developing qualitative scenario storylines. Wiley Interdiscip Rev Clim Chang 1:606–619. https://doi.org/10.1002/wcc.63

    Article  Google Scholar 

  • Schmitz C, van Meijl H, Kyle P, Nelson GC, Fujimori S, Gurgel A, Havlik P, Heyhoe E, d'Croz DM, Popp A, Sands R, Tabeau A, van der Mensbrugghe D, von Lampe M, Wise M, Blanc E, Hasegawa T, Kavallari A, Valin H (2014) Land-use change trajectories up to 2050: insights from a global agro-economic model comparison. Agric Econ 45:69–84. https://doi.org/10.1111/agec.12090

  • Schulze J, Frank K, Priess JA, Meyer MA (2016) Assessing regional-scale impacts of short rotation coppices on ecosystem services by modeling land-use decisions. PLoS One 11:e0153862. https://doi.org/10.1371/journal.pone.0153862

    Article  CAS  Google Scholar 

  • Seto KC, Guneralp B, Hutyra LR (2012) Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proc Natl Acad Sci 109:16083–16088. https://doi.org/10.1073/pnas.1211658109

    Article  Google Scholar 

  • Sexton JO, Noojipady P, Song XP, Feng M, Song DX, Kim DH, Anand A, Huang C, Channan S, Pimm SL, Townshend JR (2016) Conservation policy and the measurement of forests. Nat Clim Chang 6:192–196. https://doi.org/10.1038/nclimate2816

  • Sirami C, Caplat P, Popy S, Clamens A, Arlettaz R, Jiguet F, Brotons L, Martin JL (2017) Impacts of global change on species distributions: obstacles and solutions to integrate climate and land use. Glob Ecol Biogeogr 26:385–394. https://doi.org/10.1111/geb.12555

  • Sohl TL, Wimberly MC, Radeloff VC, Theobald DM, Sleeter BM (2016) Divergent projections of future land use in the United States arising from different models and scenarios. Ecol Model 337:281–297. https://doi.org/10.1016/j.ecolmodel.2016.07.016

  • Spangenberg JH, Bondeau A, Carter TR, Fronzek S, Jaeger J, Jylhä K, Kühn I, Omann I, Paul A, Reginster I, Rounsevell M, Schweiger O, Stocker A, Sykes MT, Settele J (2012) Scenarios for investigating risks to biodiversity. Glob Ecol Biogeogr 21:5–18. https://doi.org/10.1111/j.1466-8238.2010.00620.x

  • Stehfest E, van Zeist WJ, Valin H, Havlik P, Popp A, Kyle P, Tabeau A, Mason-D’Croz D, Hasegawa T, Bodirsky BL, Calvin K, Doelman JC, Fujimori S, Humpenöder F, Lotze-Campen H, van Meijl H, Wiebe K (2019) Key determinants of global land-use projections. Nat Commun 10:2166. https://doi.org/10.1038/s41467-019-09945-w

  • Sushinsky JR, Rhodes JR, Possingham HP, Gill TK, Fuller RA (2013) How should we grow cities to minimize their biodiversity impacts? Glob Change Biol 19:401–410. https://doi.org/10.1111/gcb.12055

  • Synes NW, Brown C, Palmer SCF, Bocedi G, Osborne PE, Watts K, Franklin J, Travis JMJ (2019) Coupled land use and ecological models reveal emergence and feedbacks in socio-ecological systems. Ecography 42:814–825. https://doi.org/10.1111/ecog.04039

  • Thompson JR, Lambert KF, Foster DR, Broadbent EN, Blumstein M, Almeyda Zambrano AM, Fan Y (2016) The consequences of four land-use scenarios for forest ecosystems and the services they provide. Ecosphere 7:1–22. https://doi.org/10.1002/ecs2.1469

  • Thuiller W, Albert CH, Araújo MB, Berry PM, Cabeza M, Guisan A, Hickler T, Midgley GF, Paterson J, Schurr FM, Sykes MT, Zimmermann NE (2008) Predicting global change impacts on plant species’ distributions: future challenges. Perspect Plant Ecol Evol Syst 9:137–152. https://doi.org/10.1016/j.ppees.2007.09.004

  • Thuiller W, Guéguen M, Renaud J, Karger DN, Zimmermann N (2019) Uncertainty in ensembles of global biodiversity scenarios. Nat Commun 10. https://doi.org/10.1038/s41467-019-09519-w

  • Titeux N, Henle K, Mihoub JB, Regos A, Geijzendorffer IR, Cramer W, Verburg PH, Brotons L (2016) Biodiversity scenarios neglect future land-use changes. Glob Change Biol 22:2505–2515. https://doi.org/10.1111/gcb.13272

  • Torres A, Jaeger JAG, Alonso JC (2016) Assessing large-scale wildlife responses to human infrastructure development. Proc Natl Acad Sci U S Am Proc Natl Acad Sci U S Am 113 113(8472):8472–8477. https://doi.org/10.1073/pnas.1522488113

    Article  CAS  Google Scholar 

  • Urban MC, Bocedi G, Hendry AP, Mihoub JB, Pe’er G, Singer A, Bridle JR, Crozier LG, De Meester L, Godsoe W, Gonzalez A, Hellmann JJ, Holt RD, Huth A, Johst K, Krug CB, Leadley PW, Palmer SCF, Pantel JH, Schmitz A, Zollner PA, Travis JMJ (2016) Improving the forecast for biodiversity under climate change. Science 353:aad8466. https://doi.org/10.1126/science.aad8466

  • Van Asselen S, Verburg PH (2013) Land cover change or land-use intensification: simulating land system change with a global-scale land change model. Glob Change Biol 19:3648–3667. https://doi.org/10.1111/gcb.12331

    Article  Google Scholar 

  • Visconti P, Bakkenes M, Baisero D, Brooks T, Butchart SHM, Joppa L, Alkemade R, Di Marco M, Santini L, Hoffmann M, Maiorano L, Pressey RL, Arponen A, Boitani L, Reside AE, van Vuuren DP, Rondinini C (2016) Projecting global biodiversity indicators under future development scenarios. Conserv Lett 9:5–13. https://doi.org/10.1111/conl.12159

  • Voiron-Canicio C (2012) L’anticipation du changement en prospective et des changements spatiaux en géoprospective. Espace Géographique 41:99. https://doi.org/10.3917/eg.412.0099

    Article  Google Scholar 

  • Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, AJG Gray, Groth P, Goble C, Grethe JS, Heringa J, Hoen PAC, Hooft R, Kuhn T, Kok R, Kok J, Lusher SC, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, van Schaik R, Sansone SA, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, van der Lei J, van Mulligen E, Velterop J, Waagmeester A, Wittenburg P, Wolstencroft P, Zhao J, Mons B (2016) The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3:160018. https://doi.org/10.1038/sdata.2016.18

  • Zarandian A, Baral H, Stork NE, Ling MA, Yavari AR, Jafari HR, Amirnejad H (2017) Modeling of ecosystem services informs spatial planning in lands adjacent to the Sarvelat and Javaherdasht protected area in northern Iran. Land Use Policy 61:487–500. https://doi.org/10.1016/j.landusepol.2016.12.003

  • Zhou ZX, Li J, Guo ZZ, Li T (2017) Trade-offs between carbon, water, soil and food in Guanzhong-Tianshui economic region from remotely sensed data. Int J Appl Earth Obs Geoinformation 58:145–156. https://doi.org/10.1016/j.jag.2017.01.003

    Article  Google Scholar 

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Acknowledgements

This work contributes to the Labex OT-Med (no. ANR-11-LABX-0061) funded by the French Government “Investissements d’Avenir” program of the French National Research Agency (ANR) through the A*MIDEX project (no. ANR-11-IDEX-0001-02). We thank N. Dendoncker (Université de Namur, Belgium) and S. Zaehle (Max Planck Institute for Biogeochemistry, Germany) for the data on ALARM and ATEAM scenarios, E. Naiken for his help with the literature review, and F. Jabot for his friendly review of our manuscript.

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Correspondence to Cécile H. Albert.

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Glossary

Archetype

A storyline that is considered to be a perfect or typical example of a particular set of possible futures, because it has all their most important characteristics. Scenarios that have similar storylines could be grouped into few general archetypes.

Backcasting

Process of working backwards from the definition of a possible future (typically a vision), in order to determine what needs to happen to make this future unfold and connect to the present (typically a pathway).

Baseline

Set of reference data used to represent the initial conditions and that serve as a basis to compare alternative scenarios.

Business as usual

Scenario of—or pathway towards—a future considered to be the continuation of the current path.

Downscaling

The process of refining the spatial grain (resolution). For LUCC, downscaling means also incorporating more information on local constraints.

Driver, driving force

The underlying causes of change, affecting or shaping the future. For instance, can be a social (e.g. human population, inequalities), economic (e.g. prices), policy governance (e.g. fair-trade vs. market-based), technological (e.g. rate of innovation), or environmental (e.g. atmospheric CO2) factor.

Extrapolation

Application of a method or conclusion to a new situation assuming that existing trends will continue.

Family

Set of projections that comes from a given modelling team, a modelling framework, or a given research project. Note that our definition differs from the IPCC acception in which families are groups of scenarios following a given storyline (see “archetype”).

Foresight, Prospective

A systematic and multi-disciplinary approach to explore a multitude of mid- to long-term possible futures and drivers of change. Can be used as a guide in formulating public policy.

Participatory

Engaging representatives of local (and regional) actors (stakeholders) whose interests are varied and who may contribute to build visions of the future as a collective endeavour by sharing their know-how and knowledge about their common territory.

Pathway, Trajectory

A sequence of actions, events, and consequences taken over time to reach a specific future situation, or that leads to it.

Plausible

Judged to be reasonable because its underlying assumptions and internal consistency connect to reality.

Projection

An expected value of one indicator at a particular point in the future under a given scenario, based on assumptions regarding selected initial conditions and driving forces, and often computed with the aid of a model. Here, we focus on spatial projections, i.e. maps, of land use/cover at a given time.

Scenario

A description of how the future may unfold according to an explicit, coherent, and internally consistent set of assumptions about key drivers, relationships, and constraints. It is not a forecast about a most likely future state. The word “scenario” encompasses—and is sometimes used instead of—storyline, vision, and projection.

Storyline, Narrative

A coherent and qualitative description of a scenario, highlighting its main characteristics, the relationships between key driving forces and their dynamics.

Thematic resolution

The classification used to describe land use/cover in terms of number of classes and their definitions.

Time horizon, time frame

Farthest point in the future to be considered (e.g. 2080); complete period (past-to-future) of time considered.

Vision

The concise description of what the world might look like at some future time. A consensus can be drawn for a preferred and inspiring future, and a full strategy developed to reach this future (e.g. normative scenario).

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Albert, C.H., Hervé, M., Fader, M. et al. What ecologists should know before using land use/cover change projections for biodiversity and ecosystem service assessments. Reg Environ Change 20, 106 (2020). https://doi.org/10.1007/s10113-020-01675-w

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