Encouraging adaptation is an essential aspect of the policy response to climate change. Adaptation seeks to reduce the harmful consequences and harness any beneficial opportunities arising from the changing climate. However, given that human activities are the main cause of environmental transformations worldwide, it follows that adaptation itself also has the potential to generate further pressures, creating new threats for both local and global ecosystems. From this perspective, policies designed to encourage adaptation may conflict with regulation aimed at preserving or enhancing environmental quality. This aspect of adaptation has received relatively little consideration in either policy design or academic debate. To highlight this issue, we analyse the trade-offs between two fundamental ecosystem services that will be impacted by climate change: provisioning services derived from agriculture and regulating services in the form of freshwater quality. Results indicate that climate adaptation in the farming sector will generate fundamental changes in river water quality. In some areas, policies that encourage adaptation are expected to be in conflict with existing regulations aimed at improving freshwater ecosystems. These findings illustrate the importance of anticipating the wider impacts of human adaptation to climate change when designing environmental policies.

We combine natural science modelling and valuation techniques to present economic analyses of a variety of land use change scenarios generated for the UK National Ecosystem Assessment. Specifically, the agricultural, greenhouse gas, recreational and urban greenspace impacts of the envisioned land use changes are valued. Particular attention is given to the incorporation of spatial variation in the natural environment and to addressing issues such as biodiversity impacts where reliable values are not available. Results show that the incorporation of ecosystem services and their values within analyses can substantially change decisions. © 2013 Springer Science+Business Media Dordrecht.

The opportunity Value of Travel Time (VTT) is one of the most important elements of the total cost of recreation day-trips and arguably the most difficult to estimate. Most studies build upon the theoretical framework proposed by Becker (1965) by using a combination of revealed and stated preference data to estimate a value of time which is uniform in all activities and under all circumstances. This restriction is relaxed by DeSerpa's (1971) model which allows the value of saving time to be activity-specific. We present the first analysis which uses actual driving choices between open access and toll roads to estimate a VTT specific for recreation trips, thereby providing a value which conforms to both Becker's and DeSerpa's theoretical models. Using these findings we conduct a Monte Carlo simulation to identify generalizable results for subsequent valuation studies. Our results indicate that 3/4 of the wage rate provides a reasonable approximation of the average VTT for recreation trips, while the commonly implemented assumption of 1/3 of the wage rate generates downward biased results. © 2013 the Authors.

This article provides estimates of the physical and economic value of changes in greenhouse gas (GHG) emissions projected to arise from climate change induced shifts in UK agricultural land use during the period 2004-2060. In physical terms, significant regional differences are predicted with the intensity of agricultural GHG emissions increasing in the upland north and western parts of the UK and decreasing in the lowland south and east of the country. Overall these imply relative modest increases in the physical quantity of emissions. However, rapid rises in the expected marginal value of such emissions translate these trends into major increases in their economic costs over the period considered. © 2013 European Union.

This paper provides an estimate of the contribution of the ecosystem to the provisioning services generated by agriculture. This is achieved by valuing the changes in productivity generated by a marginal alteration in ecosystem inputs. As an example, we consider the variation in rainfall and temperature projected by the recent UK Climate Impacts Programme. The analysis implements a spatially explicit, econometric model of agricultural land use based on the methodology recently developed by Fezzi and Bateman (Am J Agric Econ 93:1168-1188, 2011). Land use area and livestock stocking rates are then employed to calculate farm gross margin estimates of the value of changes in provisioning ecosystem services. Findings suggest that the variation in ecosystem inputs induced by climate change will have substantial influence on agricultural productivity. Interestingly, within the UK context climate change generates mainly positive effects, although losses are forecasted for those southern areas most vulnerable to heat-stress and drought. © 2013 Springer Science+Business Media Dordrecht.

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 United Kingdom, 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, although decisions that focus solely on agriculture reduce overall ecosystem service values, highly significant value increases can be obtained from targeted planning by incorporating all potential services and their values and that this approach also conserves wild-species diversity.

BACKGROUND: There is much uncertainty about the future impact of climate change on vector-borne diseases. Such uncertainty reflects the difficulties in modelling the complex interactions between disease, climatic and socioeconomic determinants. We used a comprehensive panel dataset from Mexico covering 23 years of province-specific dengue reports across nine climatic regions to estimate the impact of weather on dengue, accounting for the effects of non-climatic factors. METHODS AND FINDINGS: Using a Generalized Additive Model, we estimated statistically significant effects of weather and access to piped water on dengue. The effects of weather were highly nonlinear. Minimum temperature (Tmin) had almost no effect on dengue incidence below 5 °C, but Tmin values above 18 °C showed a rapidly increasing effect. Maximum temperature above 20 °C also showed an increasing effect on dengue incidence with a peak around 32 °C, after which the effect declined. There is also an increasing effect of precipitation as it rose to about 550 mm, beyond which such effect declines. Rising access to piped water was related to increasing dengue incidence. We used our model estimations to project the potential impact of climate change on dengue incidence under three emission scenarios by 2030, 2050, and 2080. An increase of up to 40% in dengue incidence by 2080 was estimated under climate change while holding the other driving factors constant. CONCLUSIONS: Our results indicate that weather significantly influences dengue incidence in Mexico and that such relationships are highly nonlinear. These findings highlight the importance of using flexible model specifications when analysing weather-health interactions. Climate change may contribute to an increase in dengue incidence. Rising access to piped water may aggravate dengue incidence if it leads to increased domestic water storage. Climate change may therefore influence the success or failure of future efforts against dengue.

Arguably the greatest challenge to contemporary research is to capture the inter-relatedness and complexity of the real world environment within models so at to better inform decision makers of the accurate and complete consequences of differing options. The paper presents an integrated model of the consequence of climate change upon land use and the secondary and subsequent effects arising subsequently. The model predicts the shift in land use which climate change is likely to induce and the impacts upon farm gross margins arising from this. However, both the direct driver of climate change and the induced shift in land use patterns will cause secondary effects upon the water environment for which agriculture is the major source of diffuse pollution. We model the consequent impact of changes in such pollution upon water ecology showing that these will be spatially specific and significant. These impacts are likely to cause further knock-on effects upon the recreational benefits of water environments and these are assessed using a spatially explicit revealed preference database. Taken together this analysis permits a holistic examination of a much wider range of effects and net value consequences arising from climate change impacts upon land use.

The paper seeks to contribute to the expanding literature on ecosystem service assessment by considering its integration with economic analyses of such services. Focussing upon analyses for future orientated policy and decision making, we initially consider a single period during which ecological stocks are maintained at sustainable levels. The flow of ecosystems services and their contribution to welfare bearing goods is considered and methods for valuing resultant benefits are reviewed and illustrated via a case study of land use change. We then broaden our time horizon to discuss the treatment of future costs and benefits. Finally we relax our sustainability assumption and consider economic approaches to the incorporation of depleting ecological assets with a particular focus upon stocks which exhibit thresholds below which restoration is compromised. © 2010 the Author(s).

This paper develops a spatially disaggregated, structural econometric model of agricultural land use and production based on the joint multi-output technology representation introduced by Chambers and Just (1989). Starting from a flexible specification of the farm profit function, we derive land use allocation, input application, crop yield, and livestock intensity equations in a joint and theoretically consistent framework. To account for the presence of censored observations in micro-level data, the model is estimated as a system of two-limit Tobit equations via quasi-maximum likelihood. We present an empirical application using fine-scale spatial data covering the entirety of England and Wales and including the main economic, policy, and environmental drivers of land use change in the past forty years. A simulation of the effects of diffuse pollution reduction measures illustrates how our approach can be applied for agro-environmental policy appraisal. © the Author (2011). Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved.

This article illustrates a statistical approach for deriving farm economic impacts of policy options aiming to reduce nitrate diffuse pollution. Building upon Fezzi et al. (2008), who assess the costs of Water Framework Directive-related measures on farm accounts data, we estimate regression models allowing such costs to be predicted for any region for which land use patterns and livestock numbers are known. We derive economic impacts in terms of changes in farm gross margin for (a) reducing inorganic fertilizer application, (b) reducing livestock stocking rates, and (c) converting arable land to ungrazed grassland. A case study of the agriculturally diverse Yorkshire Derwent catchment, in the North of England, demonstrates the overall approach. In addition, for this illustration, we combine these cost estimates with prediction of the water quality changes arising from each measure, derived via an integrated hydrological model of the Derwent. This allows a comparison of cost-effectiveness. Finally, we implement our spatially explicit approach to target the measures to specific subcatchments identified as being of particular environmental policy interest. © 2010 International Association of Agricultural Economists.

The Water Framework Directive has caused a paradigm shift towards the integrated management of recreational water quality through the development of drainage basin-wide programmes of measures. This has increased the need for a cost-effective diagnostic tool capable of accurately predicting riverine faecal indicator organism (FIO) concentrations. This paper outlines the application of models developed to fulfil this need, which represent the first transferrable generic FIO models to be developed for the UK to incorporate direct measures of key FIO sources (namely human and livestock population data) as predictor variables. We apply a recently developed transfer methodology, which enables the quantification of geometric mean presumptive faecal coliforms and presumptive intestinal enterococci concentrations for base- and high-flow during the summer bathing season in unmonitored UK watercourses, to predict FIO concentrations in the Humber river basin district. Because the FIO models incorporate explanatory variables which allow the effects of policy measures which influence livestock stocking rates to be assessed, we carry out empirical analysis of the differential effects of seven land use management and policy instruments (fiscal constraint, production constraint, cost intervention, area intervention, demand-side constraint, input constraint, and micro-level land use management) all of which can be used to reduce riverine FIO concentrations. This research provides insights into FIO source apportionment, explores a selection of pollution remediation strategies and the spatial differentiation of land use policies which could be implemented to deliver river quality improvements. All of the policy tools we model reduce FIO concentrations in rivers but our research suggests that the installation of streamside fencing in intensive milk producing areas may be the single most effective land management strategy to reduce riverine microbial pollution.

We specify a structural asymmetric vector error-correction model to identify and estimate the demand and supply functions in hourly day-ahead wholesale electricity markets. In doing so, we provide, inter alia, new insights into a well-established but unresolved issue concerning the extent of the demand elasticity to price in these markets. We show that whilst demand appears to be inelastic in the short-run, the quantity traded on the market is significantly influenced by the price level and responds to previous disequilibria in the supply curve through an asymmetric error-correction mechanism, reacting to a positive disequilibrium but not to a negative one. © Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2010.

A case study of the Yorkshire Derwent (UK) catchment is used to illustrate an integrated approach for assessing the viability of policy options for reducing diffuse nitrate losses to waterbodies. For a range of options, modeling methods for simulating river nitrate levels are combined with techniques for estimating the economic costs to agriculture of modifying those levels. By incorporating spatially explicit data and information on catchment residence times (which may span many decades particularly in areas of groundwater discharge) a method is developed for efficient spatial targeting of measures, for example, to the most at-risk freshwater environments. Combining hydrological and economic findings, the analysis reveals that, in terms of cost-effectiveness, the ranking of options is highly sensitive to both (i) whether or not specific stretches of river within a catchment are regarded as a priority for protection, and (ii) the criterion of nitrate concentration deemed most appropriate as an indicator of the health of the environment. Therefore, given the focus under European legislation upon ecological status of freshwaters, these conclusions highlight the need to improve understanding of mechanistic linkages between the chemical and biological dynamics of aquatic systems.

Declining agricultural incomes, increasing concern over rural poverty and sporadic crises such as those of Bovine Spongiform Encephalopathy (BSE) and Foot and Mouth Disease mean that the imposition of further costs on U.K. agriculture are likely to be politically and socially sensitive. Such additional costs are however on the agenda with the implementation of the Water Framework Directive (WFD; European Commission, 2000). The WFD aims to achieve "good ecological status" in EU water bodies reducing, inter alia, diffuse pollution from agriculture. In this study, we assess four possible WFD measures proposed to the U.K. Department for Environment, Food, and Rural Affairs: reducing inorganic fertilizer application, conversion of arable land to ungrazed grassland, reducing livestock stocking rates, and reducing livestock dietary N and P intakes. For each measure, changes in farm gross margins (FGMs) are estimated using a dataset of over 2000 farms. In contrast to previous analyses, which have focussed upon mean responses on stylized farms, our approach allows the analysis of the range of impacts across a wide variety of real-world farms and farm types. Findings reveal high variability in impacts. Cost-effectiveness analysis indicates that, on average, cropping farms seem capable of reducing nutrient leaching in a more cost-efficient way than livestock or dairy enterprises. © 2008 International Association of Agricultural Economists.

The paper develops a spatially explicit method for integrated assessment of alternative measures to reduce nitrate leaching into rivers and lakes from farms, a key objective of the European Union Water Framework Directive (WFD). This approach combines regression models, based on Farm Business Survey and June Agricultural Census data, for predicting the economic costs to agriculture of nitrate reduction measures with a hydrological model encompassing both diffuse and point source pollution to estimate the water quality changes arising from such instruments. A case study of the agriculturally diverse Yorkshire Derwent catchment in the north of England illustrates the overall approach. We consider three measures previously proposed to the UK Department for Environment, Food and Rural Affairs (Defra) for tackling diffuse agricultural pollution: (i) reducing inorganic fertilizer application, (ii) reducing livestock stocking rates and (iii) converting arable land to un-grazed grassland. The results reveal marked variability in the economic impacts and nitrate leaching reductions, with the cost effectiveness of these measures varying by up to a factor of three. Furthermore, the analysis suggests that WFD implementation may entail major land use changes resulting in substantial economic impacts. The spatially explicit aspect of our approach permits assessment of the optimal targeting of policy implementation to areas of particular environmental interest.

We argue that the literature concerning the valuation of non-market, spatially defined goods (such as those provided by the natural environment) is crucially deficient in two respects. First, it fails to employ a theoretically consistent structural model of utility to the separate and hence correct definition of use and non-use values. Second, applications (particularly those using stated preference methods) typically fail to capture the spatially complex distribution of resources and their substitutes within analyses, again leading to error. This paper proposes a new methodology for addressing both issues simultaneously. We combine revealed (travel cost) and stated preference (choice experiment) data within a random utility model formulated from first principles to yield a theoretically consistent distinction between the use and non-use value of improvements in a non-market natural resource. The model is specified to relate both types of value to the attributes of the good in question including the spatial arrangement of the resource under consideration and its substitutes. We test the properties of the model using data simulated from a real world case study examining an improvement of open-access waters to good ecological standards. Through a Monte Carlo experiment we show that both use and non-use parameters can be precisely estimated from a modest sample of observations.