Predicting at-sea distribution of Razorbill in the St. Lawrence Gulf and Estuary, Québec, Canada during the breeding period using GPS telemetry

Abstract

Seabirds in the St. Lawrence Gulf and Estuary are vulnerable to anthropogenic threats such as oil spills and fisheries bycatch. A better understanding of their at-sea distribution is needed to determine occurrence and abundance hotspots where protection and conservation efforts should be concentrated. The goal of this study was to develop an at-sea distribution map of Razorbills (Alca torda) during the breeding period throughout the St. Lawrence to respond efficiently in the event of an environmental emergency. We tracked breeding Razorbills using GPS transmitters (n = 58) in six colonies located in the province of Québec along the St. Lawrence between 2015 and 2018. Two sets of models and maps (habitat suitability and density) were developed for Razorbills from GPS locations and a set of eight environmental covariates using a machine-learning approach (boosted regression trees). We then predicted at-sea habitat suitability and density around all known and active Razorbill colonies throughout the St. Lawrence (n = 85). The main covariates affecting habitat suitability and density of Razorbills were distance to the colony and distance to shore. Sea surface temperature and chlorophyll-a concentration were also important for habitat suitability. The model allowed generating at-sea maps for the entire targeted area during the breeding period. We identified large areas of high suitability (hotspots) to determine locations where Razorbills are most at risk and where conservation efforts should be focused. This work will be important to assess risk and minimize impacts in the case of an environmental emergency such as oil spills occurring in the St. Lawrence.