Carlos Ramirez-Reyes | USGS Science

USGS2023

Geographic distribution of the Puerto Rican Harlequin Butterfly (Atlantea tulita): An ensemble modeling approach

Species distribution models have become increasingly important tools for species conservation. This modeling approach can help guide conservation practitioners and inform decisions. Distribution models are particularly relevant for rare species, whose habitat associations are often not well understood. Using species occurrence data, and a variety of predictor variables, we developed three individual distribution models and a weighted ensemble model for the Puerto Rican harlequin butterfly ( Atlantea tulita ). The ensemble model had the greatest accuracy (AUC = 0.92). Further, the ensemble model indicated 7.1% of the main island of Puerto Rico encompassed suitable habitat for the harlequin butterfly. However, only 0.5% was classified as including the greatest suitability. Using an ensemble modeling approach to delineate areas of the island with suitable environmental conditions may improve habitat conservation efforts for the species.

Caribbean Journal of Science↗

USGS2019

Reimagining the potential of Earth observations for ecosystem service assessments

The benefits nature provides to people, called ecosystem services, are increasingly recognized and accounted for in assessments of infrastructure development, agricultural management , conservation prioritization, and sustainable sourcing. These assessments are often limited by data, however, a gap with tremendous potential to be filled through Earth observations (EO), which produce a variety of data across spatial and temporal extents and resolutions. Despite widespread recognition of this potential, in practice few ecosystem service studies use EO. Here, we identify challenges and opportunities to using EO in ecosystem service modeling and assessment. Some challenges are technical, related to data awareness, processing, and access. These challenges require systematic investment in model platforms and data management. Other challenges are more conceptual but still systemic; they are byproducts of the structure of existing ecosystem service models and addressing them requires scientific investment in solutions and tools applicable to a wide range of models and approaches. We also highlight new ways in which EO can be leveraged for ecosystem service assessments, identifying promising new areas of research. More widespread use of EO for ecosystem service assessment will only be achieved if all of these types of challenges are addressed. This will require non-traditional funding and partnering opportunities from private and public agencies to promote data exploration, sharing, and archiving. Investing in this integration will be reflected in better and more accurate ecosystem service assessments worldwide.

Science of the Total Environment↗