Mapping socio-economic scenarios of land cover change: A GIS method to enable ecosystem service modelling R.D. Swetnam a, * , B. Fisher b, c , B.P. Mbilinyi d , P.K.T. Munishi d , S. Willcock e , T. Ricketts f , S. Mwakalila g , A. Balmford a , N.D. Burgess a, f , A.R. Marshall h, i , S.L. Lewis e a Conservation Science Group, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, United Kingdom b Centre for Social and Economic Research on the Global Environment, University of East Anglia, Norwich NR4 7TJ, United Kingdom c Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ 08544, USA d Faculty of Agriculture, Sokoine University of Agriculture, Chuo Kikuu, Morogoro, Tanzania e School of Geography, University of Leeds, Leeds LS2 9JT, United Kingdom f World Wildlife Fund, 1250 24th St NW, Washington, DC 20037, USA g Department of Geography, University of Dar es Salaam, P.O. Box 35049, Dar es Salaam, Tanzania h Environment Department, University of York, Heslington, York YO10 5DD, United Kingdom i Flamingo Land Ltd., Kirby Misperton, Malton, North Yorkshire YO17 6UX, United Kingdom article info Article history: Received 13 January 2010 Received in revised form 5 August 2010 Accepted 6 September 2010 Available online xxx Keywords: Carbon Ecosystem services GIS Scenarios Spatial modelling Tanzania abstract We present a GIS method to interpret qualitatively expressed socio-economic scenarios in quantitative map-based terms. (i) We built scenarios using local stakeholders and experts to define how major land cover classes may change under different sets of drivers; (ii) we formalised these as spatially explicit rules, for example agriculture can only occur on certain soil types; (iii) we created a future land cover map which can then be used to model ecosystem services. We illustrate this for carbon storage in the Eastern Arc Mountains of Tanzania using two scenarios: the first based on sustainable development, the second based on ‘business as usual’ with continued forestewoodland degradation and poor protection of existing forest reserves. Between 2000 and 2025 4% of carbon stocks were lost under the first scenario compared to a loss of 41% of carbon stocks under the second scenario. Quantifying the impacts of differing future scenarios using the method we document here will be important if payments for ecosystem services are to be used to change policy in order to maintain critical ecosystem services. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction It is widely accepted that intact ecosystems provide an array of services e from immediate and tangible benefits such as water flow regulation and provision of harvested goods through to biodiversity preservation and climate stabilisation via carbon storage in vegetation and soils (Costanza et al., 1997; Daily, 1997; de Groot et al., 2002). Although there remains much theoretical debate about the definition of such services and approaches to their valuation (Ruhl et al., 2007; Wallace, 2007; Costanza, 2008; Boyd and Banzhaf, 2007; Fisher et al., 2009) one common thread is clear: ecosystem service production and flow is spatially explicit and temporally dependent. It matters not only how much of a service is produced, but also when and where, so any economic values we assign to these services will therefore also vary across space and time. The spatially variable nature of service generation and flow means that mapping and modelling of ecosystem services for planning purposes is becoming increasingly important (Naidoo and Ricketts, 2006; Egoh et al., 2008). Datasets have become more sophisticated, shifting from a simple benefits-transfer approach (Zhao et al., 2004; Troy and Wilson, 2006) to values derived from biophysical and economic models (Eade and Moran, 1996; Bateman et al., 1999; Mallawaarachchi et al., 1996; Soares-Filho et al., 2004, 2006). Typically, the links between models of different services are made through synoptic land cover datasets. The distribution and value of services can be expressed spatially in this way and changes modelled by altering land cover patterns and extent. Sometimes these land cover driven futures operate over large regions with notable examples from the USA including ICLUS which was developed by the Environmental Protection Agency (US EPA, 2009) drawing on the earlier work of Theobald (2001, 2005), and * Corresponding author. Tel.: þ44 1223 762979. E-mail address: rds40@cam.ac.uk (R.D. Swetnam). Contents lists available at ScienceDirect Journal of Environmental Management journal homepage: www.elsevier.com/locate/jenvman 0301-4797/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.jenvman.2010.09.007 Journal of Environmental Management xxx (2010) 1e12 Please cite this article in press as: Swetnam, R.D., et al., Mapping socio-economic scenarios of land cover change: A GIS method to enable ecosystem service modelling, Journal of Environmental Management (2010), doi:10.1016/j.jenvman.2010.09.007