The estimation of the economic value of ecosystem services is expected to play an increasingly important role in conservation planning and ecosystem-based management (Plummer 2009; Stenger et al. 2009) in order to ensure that human actions do not damage the ecological processes necessary to support the continued flow of ecosystem services on which welfare of present and future generations depends (MEA 2005; Daily andMatson 2008). This becomes particularly relevant under the threat of climate change, where a 3°C warming is estimated to transform about one-fifth of the world’s ecosystems (Fischlin et al. 2007). Economic valuation of ecosystem services requires up-to-date and reliable
information and considerably better understanding of the landscapes that provide such services (Troy and Wilson 2006, in Baral et al. 2009). In this line, several studies have given attention to the landscape functions in order to calculate benefits associated to ecosystem services. Based on these needs, the focus of economics has so far been placed on single resources with commercial use (land, fisheries, forests, energy, etc.) and goods and services provided by nature in the absence of markets (clean air, aesthetics, recreation). However, recent work is shifting the stand of economic analyses, and attention is now being paid to understand the biophysical underpinning of ecosystem functioning and how land use affects this, to predict the provision of services and their value (Polasky and Segerson 2009; Naidoo et al. 2009; Naidoo and Iwamura 2007). Therefore, complex ecological functions and processes have started to be considered from an economic perspective where traditionally that ecological level wasn’t part of an economic analysis. This awareness lead to the recent interest in integrating ecological and economic sciences (Polasky and Segerson 2009), but both the quantification of the service provision and the values of these services has proven difficult (Nelson et al. 2009). These developments combine the use of spatial data such as vegetation types, land use, productivity, etc. with economic valuation in order to provide more accurate estimates of ecosystem services (Naidoo et al. 2009; Egoh et al. 2008; Nelson et al. 2009). Despite the previous work on spatially based ecosystem service valuation (e.g. Brouwer et al. 2010; Martin-Ortega et al. 2012; Nelson et al. 2009; Bateman et al. 2013), there is a lack of studies looking at how the economic value of
ecosystem services is expected to change under expected climate change (Ding et al. 2010). Some methodologies of environmental valuation allow researchers to under-
stand the benefits of ecosystem services that are not traded in existing economic markets. This is needed to better understand the role of ecosystem services and help policy-makers to plan for the sustainability of natural resources. A lack of economic valuation could underestimate the importance of such resources and leave to a detriment on the ecosystem services supply. Non-market values are associated with many ecosystem services such as water quality, recreation, flow regulation, conservation of wild species, and they amount to an important share of the benefits from ecosystem services (TEEB 2010). However, only certain methodologies can provide information on their economic value as they are usually not traded in existing markets, as in the case of recreation or carbon sequestration (Zandersen and Tol 2009; TEEB 2010). This chapter focuses on recreation and water services provided by forest ecosystems as these entail important economic values that are many times omitted from policy decision-making. The aim of this chapter is to estimate the potential economic impacts of climate
change on water and recreation services in tropical forests of Central America. We conduct this analysis by looking at how forests provide economic benefits through water and recreation services and, based on their dependence on forest types and area, we estimate changes in their economic value under different climate scenarios altering those forest types, and therefore, the change in economic benefits derived from them.We do this by collecting primary valuation studies on the region and conducting a meta-analysis where economic data is enriched with geographic information and a vegetation model. By means of benefit transfer techniques, we project economic values under different scales and scenarios of climate change. The chapter begins by introducing the methodology used, including details on
the database construction, the addition of biophysical information, the econometric analysis, the scaling-up and the ecosystem benefits estimation under the projected scenarios of climate change. We then present the final results with the changes in ecosystem services benefits due to climate change, before summarizing the conclusions and presenting recommendations for future research.