Predicting Biodiversity for Ecosystem Services Payments

In addition to the growing number of ecosystem services represented in portfolios of natural capital, biodiversity continues to be difficult to estimate and value across space. Here, we develop empirically based models for quantifying biodiversity across space for guiding investments in ecosystems services and safeguarding biodiversity. We use Costa Rica as a case study, because it is a country that contains a lot of biodiversity and pays landowners for ecosystem services since 1996. To make predictive biodiversity models for Costa Rica, first, we explore what characteristics of a Costa Rican landscape can be remotely sensed to predict biodiversity change? And, second, how does Costa Rican biodiversity change from protected forests to deforested habitats? We find answers to these questions in the forests and biodiversity across 934 km2 region in Southern Costa Rica made up of coffee plantations, pastures, and rainforests. We find general ecological patterns using of 908 species and 65,000 captures across a gradient of deforestation and present spatial models for estimating the amount and value of plant, non-flying mammal, bat, bird, reptile, and amphibian biodiversity.

Speaker: Dr. Chase Mendenhall, Stanford