Szvetlana Acs's research while affiliated with University of Stirling and other places

Abstract Spatially heterogeneous costs of securing conservation agreements should be accounted for when prioritizing properties for conservation investment. Most researchers incorporating conservation costs into analyses have relied on estimates of landowners' opportunity costs of accepting a conservation agreement. Implicitly assumed in such studies is therefore that those who “produce” biodiversity (landowners) receive none of the surplus available from trade. Instead, landowners could use their bargaining power to gain profits from conservation investments. We employ game theory to determine the surplus landowners could obtain in negotiations over conservation agreements, and the consequent effects on conservation outcomes, when enrolment decisions are governed by continuous variables (e.g. the proportion of a property to enrol). In addition, we consider how landowner uncertainty regarding the opportunity costs of other landowners affects these outcomes. Landowners' ability to gain surplus is highly variable and reflects variation in the substitutability of different properties for achieving a specified conservation objective. The ability of landowners to obtain profits from conservation agreements results in conservation outcomes that are substantially diminished relative to when landowners accept investment at opportunity costs. Uncertainty increases landowner profits, leading to a greater diminution in conservation benefits.

Background/Question/Methods Incentive payment programs to private landowners provide a center-piece of conservation strategies in many parts of the world. For example, the EU and US spend billions of dollars each year on payments intended to encourage farmers to undertake environmentally friendly production techniques. However, past assessments of the ecological and economic effectiveness of such payment programs have been equivocal. We examine how payment programs can be designed to provide cost effective improvements in biodiversity. We first estimate the "true" supply price to farmers of producing a given level of improvement in different biodiversity indicators. We then derive the optimal (i.e. most cost effective) program design for each biodiversity indicator. This provides a benchmark against which to compare the cost effectiveness of simpler, but more readily implemented, payment programs. We focus on 44 extensive livestock farms in the Peak District in northern England and use bird species as an indicator of biodiversity. We conducted detailed surveys of the economics of farm businesses and combined these with property-scale surveys of species responses to farm management. We parameterized nonlinear programming models of farm businesses that allow the production of biodiversity improvements on farms alongside the production of more conventional agricultural commodities (like livestock). Results/Conclusions The models suggest existing payment schemes are highly cost ineffective. Rather than compensating farmers for income forgone as a consequence of changing management practices, current schemes primarily subsidize farm profits. The optimal policy exploits variation in costs of producing biodiversity enhancements within and among farms. However such a policy would be prohibitively complex to administer. By comparing alternative simpler policies to the optimal policy, we show that common simplifications in payment scheme design can result in 49-100% of promised biodiversity gains being given up. Moreover, we are able to identify which policy simplifications are most problematic. Spatially differentiating pricing for biodiversity improvements is critical to the success of such programs, a finding that is robust to idiosyncratic responses of different biodiversity targets to management actions.

Recent decades have witnessed substantial losses of biodiversity in Europe, partly driven by the ecological changes associated with intensification of agricultural production. These changes have particularly affected avian (bird) diversity in marginal areas such as the uplands of the UK. Future trends for upland birds will likely be impacted by changes in agricultural support regimes, such as those currently envisaged in on-going reforms of the Common Agricultural Policy. We developed integrated ecological-economic models, using seven different indicators of biodiversity based on avian species richness and individual bird densities. The models represent six different types of farms which are typical for the UK uplands, and were used to assess the outcomes of different agricultural futures. Our results show that the impacts of these future agricultural scenarios on farm incomes, land use and biodiversity are very diverse across policy scenarios and farm types. Moreover, each policy scenario produces un-equal distributions of farm income changes and gains and losses in alternative biodiversity indicators. This shows that generalisations of the effects of policy and pricing changes on farm incomes, land uses and biodiversity can be misleading. Our results also suggest that a focus on umbrella species or biodiversity indicators (such as total species richness) can miss important compositional effects.

Ecology Letters (2012) 15: 406–414 Incentive payments to private landowners provide a common strategy to conserve biodiversity and enhance the supply of goods and services from ecosystems. To deliver cost-effective improvements in biodiversity, payment schemes must trade-off inefficiencies that result from over-simplified policies with the administrative burden of implementing more complex incentive designs. We examine the effectiveness of different payment schemes using field parameterized, ecological economic models of extensive grazing farms. We focus on profit maximising farm management plans and use bird species as a policy-relevant indicator of biodiversity. Common policy simplifications result in a 49–100% loss in biodiversity benefits depending on the conservation target chosen. Failure to differentiate prices for conservation improvements in space is particularly problematic. Additional implementation costs that accompany more complicated policies are worth bearing even when these constitute a substantial proportion (70% or more) of the payments that would otherwise have been given to farmers.

Crofting is a low intensity agricultural system restricted to the Highlands and Islands of northern Scotland typified by small scale mixed livestock production and rotational cropping activities. As with other low intensity farming systems across Europe, crofting is changing in response to a range of socio-economic factors. This is having a negative impact on the populations of rare bumblebees that are associated with this agricultural system. In this paper we use an ecological-economic modelling approach to examine the likely impacts of introducing two different management options for conserving bumblebees on croft land-use and income. Two linear programming models were constructed to represent the predominant crofting systems found in the Outer Hebrides, and varying constraints on bumblebee abundance were imposed to examine the trade-off between conservation and agricultural incomes. The model outputs illustrate that in some instances it is likely that both agricultural profits and bumblebee densities can be enhanced. We conclude that policy-makers should take into consideration the type of farming system when designing cost-effective agri-environment policies for low intensity farming systems, and that improvements in bee conservation are not necessarily in conflict with maintaining farm income.

Recent decades have witnessed substantial losses of biodiversity in Europe, partly driven by the ecological changes associated with intensification of agricultural production. These changes have particularly affected avian (bird) diversity in marginal areas such as the uplands of the UK. We developed integrated ecological-economic models, using eight different indicators of biodiversity based on avian species richness and individual bird densities. The models represent six different types of farms which are typical for the UK uplands, and were used to assess the outcomes of different agricultural futures. Our results show that the impacts of these future agricultural scenarios on farm incomes, land use and biodiversity are very diverse across policy scenarios and farm types. Moreover, each policy scenario produces un-equal distributions of farm income changes, and gains and losses in alternative biodiversity indicators. This shows that generalisations of the effects of land use change on biodiversity can be misleading. Our results also suggest that a focus on umbrella species or indicators (such as total richness) can miss important compositional effects.

Despite two decades of agri-environment schemes (AESs) aimed at mitigating farmland biodiversity losses, the evidence that such programmes actually benefit biodiversity remains limited. Using field-level surveys, we assess the effectiveness of AESs in enhancing bird abundances in an upland area of England, where schemes have been operating for over 20 years. In such a region, the effects of AESs should be readily apparent, and we predict that bird abundances will co-vary with both field- and landscape-scale measures of implementation. Using an information theoretic approach, we found that, for abundances of species of conservation concern and upland specialists, measures of AES implementation and habitat type at both scales appear in the most parsimonious models. Field-level bird abundances are higher where more of the surrounding landscape is included in an AES. While habitat remains a more influential predictor, we suggest that landscape-scale implementation results in enhanced bird abundances. Hence, measures of the success of AESs should consider landscape-wide benefits as well as localized impacts.

Although the benefits of organic farming are already well known, the conversion to organic farming does not proceed as the Dutch government expected. In order to investigate the conversion decisions of Dutch arable farms, a discrete stochastic dynamic utility-efficient programming (DUEP) model is developed with special attention for yield and price risk of conventional, conversion and organic crops. The model maximizes the expected utility of the farmer depending on the farmer's risk attitude. The DUEP model is an extension of a dynamic linear programming model that maximized the labour income of conversion from conventional to organic farming over a 10 year planning horizon. The DUEP model was used to model a typical farm for the central clay region in the Netherlands. The results show that for a risk-neutral farmer it is optimal to convert to organic farming. However, for a more risk-averse farmer it is only optimal to fully convert if policy incentives are applied such as taxes on pesticides or subsidies on conversion, or if the market for the organic products becomes more stable. Copyright 2009 The Authors. Journal compilation 2009 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd.

Modern farmed landscapes have witnessed substantial losses in biodiversity principally driven by the ecological changes associated with agricultural intensification. The causes of declines are often well described, but current management practices seem unlikely to deliver the EU‐wide policy objective of halting biodiversity losses. Available evidence suggests that property‐scale factors can be influential in shaping patterns of biodiversity; however, they are rarely included in studies. Using 44 upland farms in the Peak District, northern England, we investigate the roles of ecological, agricultural and socio‐economic factors in determining avian species richness, for the first time incorporating information from all three influences. Although we might expect that habitat quality would be the main factor affecting species richness, these variables had little influence. The landscape context of each property was unimportant in explaining any of the three measures of species richness ( Total , Upland and Conservation Concern ) used here. Within‐property habitat quality did explain 42% of the variation in richness of upland specialist species, but had no influence on Total or Conservation Concern Richness. Socio‐economic circumstances of farms alone accounted for 24% of the variation in Total Richness, with land tenure and labour inputs important predictors of avian diversity. However, net income, rental value and the level of Agri‐Environment Scheme (AES) payments did not play a role in predicting species richness. Farm management variables, including many of the main prescriptions outlined in AES, accounted for 23% of the variation in the richness of species of Conservation Concern, but less than 10% for Total Richness. However, no farm management variable alone was shown to offer better predictive power of avian species richness than random. Synthesis and applications. The agricultural landscape is managed by a mosaic of landowners, all of whom can influence biodiversity conservation. We demonstrate that variation at the property‐scale in habitat, management and socio‐economics can feed into determining patterns of biodiversity. Currently, farmland conservation policy largely assumes that socio‐economic barriers and financial costs of implementing conservation measures are constant. Incorporating a consideration of the varying circumstances of individual properties into policy design is likely to result in substantial biodiversity gains.

1. The 20th century has witnessed substantial increases in the intensity of agricultural land management, much of which has been driven by policies to enhance food security and production. The knock-on effects in agriculturally dominated landscapes include habitat degradation and biodiversity loss. We examine long-term patterns of agricultural and habitat change at a regional scale, using the Peak District of northern England as a case study. As stakeholders are central to the implementation of successful land-use policy, we also assess their perceptions of historical changes. 2. In the period 1900 to 2000, there was a fivefold rise in sheep density, along with higher cattle density. We found a reduction in the number of farms, evidence of a shift in land ownership patterns, and increased agricultural specialization, including the virtual disappearance of upland arable production. 3. Despite previous studies showing a substantial loss in heather cover, we found that there had been no overall change in the proportion of land covered by dwarf shrub moor. Nonetheless, turnover rates were high, with only 55% of sampled sites maintaining dwarf shrub moor coverage between 1913 and 2000. 4. Stakeholders identified many of the changes revealed by the historical data, such as increased sheep numbers, fewer farms and greater specialization. However, other land-use changes were not properly described. For instance, although there had been no overall change in the proportion of dwarf shrub moor and the size of the rural labour force had not fallen, stakeholders reported a decline in both. Spatial heterogeneity of the changes, shifting baselines and problems with historical data sources might account for some of these discrepancies. 5. Synthesis and applications. A marked increase in sheep numbers, combined with general agricultural intensification, have been the dominant land-use processes in the Peak District during the 20th century. Stakeholders only correctly perceived some land-use changes. Policy and management objectives should therefore be based primarily on actual historical evidence. However, understanding stakeholder perceptions and how they differ from, or agree with, the available evidence will contribute to the successful uptake of land management policies and partly determine the costs of policy implementation.