Forecasting biodiversity: A matter of data availability

In a previous post, we briefly discussed our internship experience with GEO BON, in which we developed a forecasting model of local contributions to beta diversity (LCBD) at the regional scale, using communities of warblers species in Quebec and Colombia as a case study. The first part of our endeavor was getting access to data. As typical grad students in quantitative ecology, we used data mostly openly available on the internet. As mentioned in the previous post, for species occurrence, we used data from the eBird database, while environmental and land-use data were obtained from the CHELSA database and the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), respectively. While these datasets are openly available, the steps required to actually use them and the digital space they occupy could represent a challenge for someone unfamiliar with such a task.

Forecasting biodiversity: Our internship experience with GEO BON

We recently completed a two-month internship with The Group on Earth Observations Biodiversity Observation Network (GEO BON). Its headquarters having recently moved to Montreal, we immediately wanted to be part of this new chapter by contributing to a project as exciting as it is ambitious: an integrated biodiversity information system. GEO BON is indeed currently developing such an information system that would, among other things, provide real-time estimates of many biodiversity indicators at the planetary scale. Another purpose of GEO BON’s information system is to facilitate the conduction of biodiversity forecasts under different socioeconomic scenarios and enhance the plausibility and precision of these models.