مقاله انگلیسی رایگان در مورد نقشه برداری از ارزش اقتصادی قوانین رانش زمین – الزویر ۲۰۱۸

The role of forests in regulating landslide risks is well established but estimates of the economic value of this ecosystem service are limited. In order to incorporate the role of forests for landslide risk mitigation in spatial planning and other decision-making contexts, there is a need for spatially explicit information regarding the value of this service. We develop a methodological framework to combine bio-physical modelling of natural hazard risk and socio-economic exposure in a predictive model to estimate and map of the economic value of forest regulation of landslides. This method is applied in a case study of Adjara Autonomous Republic of Georgia to examine alternative scenarios for forest management and associated land cover change. The approach produces credible spatially explicit results to inform policy decisions regarding investment in forest management; and has the potential for replication in other data scarce regions.

Introduction

It is expected that damages from landslides will increase steadily over the coming years (Dai et al., 2002). Underlying this trend is an increase in human activity in landslide prone areas, which increases risk through two channels: development generally involves deforestation, which increases the probability of landslides occurring; and more human activity generally means more assets that are exposed to damage (Nadim et al., 2006). An additional factor that will drive increasing landslide damage is that climate change is predicted to cause increased precipitation in many areas already prone to landslides and may result in additional areas facing the risk of slope erosion and landslides (Dale et al., 2001; Ciabatta et al., 2016; Crozier 2010). The role of forests in regulating landslide risks is well established (Endo and Tsuruta, 1969; Megahan et al., 1978; Wu and Swanston, 1980; Preston and Crozier, 1999; Jakob, 2000). The economic value of this regulating service has, however, received limited attention in the economic valuation and ecosystem services literature (Chiabai et al., 2011; de Groot et al., 2012; Häyhä et al., 2015). Existing research has tended to focus on the value of forests for timber (Phan et al., 2014; Pohjanmies et al., 2017), non-timber forest products (Schaafsma et al., 2014; Mutoko et al., 2015), water supply (Ojea et al., 2012; Wang et al., 2017), recreation (Zandersen and Tol, 2009) and carbon storage (Triviño et al., 2015). The relatively limited number of studies that do estimate the economic value of landslide regulation by forests tend to be for small-scale study sites (e.g. Olschewski et al., 2012; Dominati et al., 2014). Information on the economic value of forests in regulating landslides is useful for informing forest management decisions (Langner et al., 2017). Quantification of the damage costs of deforestation (or avoided damage costs resulting from reforestation) provides input for the appraisal of investments in conservation and restoration. Mapping ecosystem service values delivers additional information to support decision making, particularly for land use policy development, spatial planning and resource allocation (Schägner et al., 2013; Nahuelhual et al., 2015). In order to incorporate the role of forests for landslide risk mitigation in spatial planning and other decision-making contexts, spatially explicit information related to the value of forest landslide regulation needs to be developed. Many regional governments, especially in the developing world, do not have the resources to create and gather such data in usable forms, in the absence of which, policy attention is not paid to investments in forests as a landslide mitigation measure. While reliable techniques for assessing landslide hazard often require detailed geotechnical information on existing conditions, the high cost of which means they are available only where high risk is already anticipated, more exploratory techniques of hazard and risk can provide frameworks for development planning and environmental protection measures (Gaprindashvili and Van Westen, 2016).