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Landscapes generate a wide range of valuable ecosystem services, yet land use decisions often ignore the value of these services. Using the example of the UK, we show the significance of land use change not only for agricultural production but also for emissions and sequestration of greenhouse gases, open-access recreational visits, urban green space and wild species diversity. We use spatially explicit models in conjunction with valuation methods to estimate comparable economic values for these services, taking account of climate change impacts. We show that, while decisions which focus solely upon agriculture reduce overall ecosystem service values, highly significant value increases can be obtained from targeted planning incorporating all potential services and their values, and that this approach also conserves wild species diversity.One Sentence Summary: Valuation of ecosystem services within land-use planning creates significant gains relative to current, market-dominated, decision making. Main Text:The Millennium Ecosystem Assessment (1) provided important evidence of the ongoing global degradation of ecosystem services and highlighted the need to incorporate their value into the economic analyses which underpin real-world decision-making. Previous studies have shown that the overall values of unconverted natural habitats can exceed the private benefits following conversion (2, 3), that knowledge of landscape heterogeneity and ecological processes can support cost effective land planning (4-7), that trade-offs in land-use decisions affect values from ecosystem services and biodiversity at local level (8, 9), and that current land use is vulnerable to the impacts of global change (10, 11). In the UK National Ecosystem Assessment (NEA) (12), a comprehensive assessment of the UK's ecosystems was linked to a systematic, environmental and economic analysis of the benefits they generate. Here we show how taking account of multiple objectives in a changing environment (including, but not restricted to, climate change) fundamentally alters decisions regarding optimal land use. The NEA analyses are based upon highly detailed, spatially-referenced environmental data covering all of Great Britain. These data supported the design and parameterization of models of both the drivers and consequences of land use decisions, incorporating the complexity of the natural environment and its variation across space and time (13). Model outputs provide inputs to economic analyses which assess the value of both marketed and non-marketed goods (Table 1).The NEA specifically addressed the consequences of land use change driven by either just agricultural or a wider set of values, all within the context of ongoing climate change. To assess this, raw data on land use and its determinants were drawn from multiple sources to compile a 40 year dataset, spatially disaggregated at a resolution of 2km grid squares (400ha) or finer across all of Great Britain, forming more than ½ million sets of spatially referenced, time specific...

We review the literature regarding the aggregation of benefit value estimates for non-market goods. Two case studies are presented through which we develop an approach to aggregation which applies the spatial analytic capabilities of a geographical information system to combine geo-referenced physical, census and survey data to estimate a spatially sensitive valuation function. These case studies show that the common reliance upon political jurisdictions and the use of sample mean values within the aggregation process are liable to lead to significant errors in resultant values. We also highlight the fact that for resources with use values then we should expect overall values to reduce with increasing distance from such sites, but that changes in the choice of welfare measure will determine whether such 'distance decay' is to be expected within values stated by those who are presently non-users. The paper concludes by providing recommendations for future improvements to the methodology.

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Using a two-stage hedonic pricing methodology we estimate a system of structural demand equations for different sources of transport-related noise. In the first stage, we identify market segments using model-based clustering techniques and estimate separate hedonic price functions (HPFs) for each segment. In so doing, we show how a semiparametric spatial smoothing estimator outperforms other standard specifications of the HPF. In the second stage, we control for non-linearity of the budget constraint and identify demand relationships using techniques that account for problems of endogeneity and censoring of the dependent variable. Our estimated demand functions provide welfare estimates for peace and quiet that we believe to be the first derived from property market data in a theoretically consistent manner

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Rural-urban migration can have both positive and negative environmental consequences for tropical forests. Rural residents exert pressure on the environment through farming, fishing, and forest extraction, yet conversely, protecting rural livelihoods is often the motivation for conserving large areas of threatened forest. This research examines rural settlement within the Brazilian Amazon to shed light on the drivers of on-going rural exodus and its environmental implications. Specifically, we examine the relative importance of public service provision and natural resources in determining settlement patterns along, and rural-urban migration from, eight rivers in road-less regions of the Brazilian Amazon. Data include biophysical, social, and economic variables that were assessed in 184 riverine settlements along rural-urban gradients up to 740 km from the nearest urban center. Settlements were smaller upstream, and lacked key services such as schools and healthcare. We found that clustering of rural populations close to urban centers reflects the high costs of living in remote areas, despite abundant natural resources which previously justified migration to headwaters. Impeded dry-season navigability and transport costs restricted the flow of goods and services to and from remote areas, and transaction costs of trade exchange were higher upstream. A lack of school access was the main motivation for rural-urban migration and the abandonment of remote riverine settlements. A key policy implication is that while education services could provide a powerful tool to stabilize and support rural populations, delivery is challenging in remote areas and may also encourage further rural-urban migration in the longer term. Furthermore, river-dwellers in remote areas rarely visited remote urban centers, presumably because these journeys are too costly. We examine the implications of our findings for anti-poverty subsidies and payment for ecosystem services and conclude that transport costs required to receive payment could encourage further depopulation of remote areas