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Integrating quantitative and qualitative data in assessing the cost-effectiveness of biodiversity conservation programmes

Austin, Zoё, McVittie, Alistair, McCracken, Davy, Moxey, Andrew, Moran, Dominic, White, Piran C. L.
Biodiversity and conservation 2015 v.24 no.6 pp. 1359-1375
biodiversity, conservation programs, cost effectiveness, expert opinion, funding, habitat conservation, monitoring, rural development, socioeconomic factors, uncertainty, Scotland
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 socio-economic 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. 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.