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Globally, most biodiversity conservation programmes are not currently evaluated in terms of their costs and benefits, or their rate of return on the original investment. Assessing the cost-effectiveness of such schemes is challenging as the relationship between spending and the effectiveness of conservation is dependent on many biological and socioeconomic factors. Here, we evaluate the cost-effectiveness of a selection of species and habitat conservation schemes undertaken through the Scotland Rural Development Programme. We use a combination of quantitative and qualitative data, based on expert knowledge, to estimate effectiveness and cost-effectiveness of different schemes and understand variations in the results. Our findings highlight a lack of geographical targeting in terms of where the funding might achieve the most conservation benefit, which may be contributing to high costs per unit of effectiveness. Recommendations include the need for improved advice on appropriate management and monitoring programmes that are linked closely to objectives. Conservation schemes within Scotland were used as the focus of the study, but the approaches used, interpretations drawn and improvements identified could be applied to any regional, national or international biodiversity conservation programmes. 123Biodivers Conserv (2015) 24:1359-1375 DOI 10.1007 Cost and effectiveness data can be subject to a high degree of uncertainty and hence any cost-effectiveness estimate is subject to a number of caveats. There is therefore a need to focus not only on improving the cost-effectiveness of biodiversity conservation programmes, but also to improve the robustness of cost-effectiveness assessments, in terms of data availability and accuracy and improved monitoring of the outcomes of interventions.

Context. Some species that are perceived by certain stakeholders as a valuable resource can also cause ecological or economic damage, leading to contrasting management objectives and subsequent conflict between stakeholder groups. There is increasing recognition that the integration of stakeholder knowledge with formal scientific data can enhance the information available for use in management. This is especially true where scientific understanding is incomplete, as is frequently the case for wide-ranging species, which can be difficult to monitor directly at the landscape scale.Aims. The aim of the research was to incorporate stakeholder knowledge with data derived from formal quantitative models to modify predictions of wildlife distribution and abundance, using wild deer in the UK as an example.Methods. We use selected predictor variables from a deer-vehicle collision model to estimate deer densities at the 10-km square level throughout the East of England. With these predictions as a baseline, we illustrate the use of participatory GIS as a methodological framework for enabling stakeholder participation in the refinement of landscape-scale deer abundance maps.Key results. Stakeholder participation resulted in modifications to modelled abundance patterns for all wild deer species present in the East of England, although the modifications were minor and there was a high degree of consistency among stakeholders in the adjustments made. For muntjac, roe and fallow deer, the majority of stakeholder changes represented an increase in density, suggesting that populations of these species are increasing in the region.Conclusions. Our results show that participatory GIS is a useful technique for enabling stakeholders to contribute to incomplete scientific knowledge, especially where up-to-date species distribution and abundance data are needed to inform wildlife research and management.Implications. The results of the present study will serve as a valuable information base for future research on deer management in the region. The flexibility of the approach makes it applicable to a range of species at different spatial scales and other wildlife conflict issues. These may include the management of invasive species or the conservation of threatened species, where accurate spatial data and enhanced community involvement are necessary in order to facilitate effective management.