Biodiversity dynamics underpin the regulation and provisioning of many ecosystem services (ES), but ES models used commonly in decision-support tools do not adequately represent the relationships between different levels biodiversity (genes, species, ecosystems) and ES. Most ES tools use land-use/land cover (LULC) as the sole input representing ecosystem contribution to ES, and therefore neglect the potential impacts of within-habitat variation or changes in diversity. The Essential Biodiversity Variable (EBV) framework establishes metrics for spatially-explicit representation of biodiversity change over time and addresses these multiple dimensions of biodiversity. This project’s two-stage effort first linked EO to the EBVs most relevant to ES, and second linked the EBVs to ES and their benefits to people.
Key Results Include:
- Leveraged this project and the partnership with MINAE to secure $60k in cloud credits on Amazon AWS which enabled running ES models globally at 300 m resolution and at 10 m resolution for Costa Rica.
- Developed a new hybrid approach to modeling bird biodiversity that bridged global (GBIF occurrence and broad climate variables) and local (long-term transect observation and fine-scale habitat variables) data. While general patterns of climate are still apparent, spatial projections now also show clear signals of local land-use characteristics. In particular, the traditional species distribution modeling approach (using only global data) undervalued the importance of Amistad International Park and the Nicoya Peninsula in terms of their ability to support species richness.
- Applied NASA Project (Epstein) Ecosystem Functional Type (EFT) approach to improve pollination modeling in nesting and floral resources in habitat surrounding croplands across Costa Rico. This approach reduced overall error from 21% to 14% and reduced the underestimation error from 44% to 17%.
- Mapped tourism (predicted by bird biodiversity) and above ground carbon storage (estimated with lidar) for Costa Rica at the national scale; both approaches were refined using improved local data. The use of lidar for the carbon map reduced error by 50% compared to the more common approach of using LULC type.
- Demonstrated that without considering biodiversity, the tourism value of large, intact tracts of forests such as La Amistad National Park are underestimated, and their easier to access (but less diverse) park edges are overestimated.