Development of a forest structure Essential Biodiversity Variable for Colombia's Biodiversity Observation Network

Habitat vertical structure has emerged over the last several decades as an important predictor of biodiversity. Habitat structure predicts habitat use for a range of animals and is correlated with plant species diversity in a range of forest ecosystems. Currently, national biodiversity assessments in developing tropical countries rely on field inventories or aircraft lidar measurements to characterize habitat vertical structure. These data have proven vital for understanding how land use and biophysical factors influence habitat structure but tend to be sparsely sampled, allowing only coarse grained reporting on habitat structure. Densely sampled lidar data from the Global Ecosystem Dynamics Investigation (GEDI) promise to fill important gaps in our understanding of habitat vertical structure. The Colombian government, in collaboration with GEO BON, is currently developing a national biodiversity observation network. Here we describe development of a forest structure Essential Biodiversity Variable (EBV) designed to inform this network. Using an extensive database of aircraft and spaceborne lidar, we characterized and classified forest vertical structure using variables that represent primary dimensions of forest structure: canopy height, canopy cover, and canopy vertical distribution. Initial results indicate that hierarchical clustering approaches distinguish ecologically meaningful classes, especially those classes that represent tall, vertically complex forest which are conservation priorities in areas dominated by secondary growth. The forest structure EBV framework provides a quantitative basis for defining and estimating the extent of locally relevant forest structure types, a critical step forward for assessing national progress towards Aichi biodiversity targets and Sustainable Development goals.