Towards effective Private Land Conservation schemes

The backbone of biodiversity conservation has been the preservation of natural habitats with protected areas. Despite decades of conservation efforts, only 12.5% of Earth’s surface is currently protected. These areas alone cannot stop biodiversity decline, and many countries, including Finland, face notable socio-economic challenges in meeting international targets, such as the proposed 30% protected area coverage in the EU 2030 Biodiversity Strategy. It is evident that Private Land Conservation (PLC), where people are paid, offered access to markets, or given discounts to encourage them to manage their land to benefit biodiversity, will play a central role in the conservation efforts needed to meet these targets. More broadly, PLC provides us with the opportunity to halt the extinction crisis and mass habitat loss, especially in the face of climate change. PLC is complex by nature. The effectiveness of PLC programs is dependent on the complex interactions between people’s willingness to participate, program design and their impact on biodiversity. This PhD project will map i) the drivers within each of the social, economic, and ecological dimensions that affect the effectiveness of PLC schemes, ii) the uncertainties associated to each driver, and iii) establish which of the uncertainties are most important to solve in order to improve scheme effectiveness. Additionally, I will test how these factors may change under future climate scenarios. By improving the understanding of the connections between the different drivers, this project will help design better incentives schemes. The theoretical basis for this research is the Value of Information analysis, a concept for measurable value for known and unknown information (uncertainty). I will work closely with project designers and stakeholders from two case studies: the Finnish private forest owners and pastoralists in Mongolia. Forestry and pastoralism are some of the greatest drivers of biodiversity loss globally.