Landscape and forest structural controls on wood density and aboveground biomass along a tropical elevation gradient in Costa Rica
Abstract:This research seeks to understand how tree wood density and taxonomic diversity relate to topography and three-dimensional vegetation structure in the tropical montane forest of Braulio Carrillo National Park in Costa Rica. The study utilized forest inventory and botanical data from twenty 1-ha plots ranging from 55 m to 2800 m above sea level and remote sensing data from an airborne lidar sensor (NASA’s Land, Vegetation, and Ice Sensor [LVIS]) to quantify variations in forest structure. There is growing evidence that ecosystem structure plays an important role in defining patterns of species diversity and help to control the phenotypic and functional variations across landscapes. Elevation gradients along mountains provide landscape-size scales through which variations in topography, climate, and edaphic conditions as drivers of biodiversity can be tested. In this study we report on the effectiveness of relating patterns of tree wood density and alpha diversity to three-dimensional structure of a tropical montane forest using remote sensing observations of forest structure. Wood density is an important parameter for aboveground biomass and carbon estimations. Tree cores were analyzed for wood density and compared to existing database values for the same species. In this manner we were able to test the effect of the gradient on wood density and on the subsequent aboveground biomass estimations. Understanding these patterns has implications for conservation of both ecosystem services and biodiversity.
Our results indicate that there is a strong relationship between LVIS-derived forest 3D-structure and alpha diversity, likely controlled controlled by variations in abiotic factors and topography along the elevation. Using spatial analysis with the aid of remote sensing data, we found distinct patterns along the environmental gradients defining species composition and forest structure. Wood density values were found to vary significantly from database values for the same species. This variation in tree growth has repercussions on overall forest structure, and subsequent carbon estimates extrapolated from field measurements. Because these wood density values are directly tied to biomass estimates, it is possible that carbon storage has been overestimated along this gradient using prior methods.