Combining potential and realized distribution modeling of telemetry data for a bycatch risk assessment

Abstract

AbstractEstablishing marine species distributions is essential for guiding management and can be estimated by identifying potential favorable habitat at a population level and incorporating individual‐level information (e.g., movement constraints) to inform realized space use. In this research, we applied a combined modeling approach to tracking data of adult female and juvenile South American sea lions (Otaria flavescens; n = 9) from July to November 2011 to make habitat predictions for populations in northern Chile. We incorporated topographic and oceanographic predictors with sea lion locations and environmentally based pseudo‐absences in a generalized linear model for estimating population‐level distribution. For the individual approach, we used a generalized linear mixed‐effects model with a negative exponential kernel variable to quantify distance‐dependent movement from the colony. Spatial predictions from both approaches were combined in a bivariate color map to identify areas of agreement. We then used a GIS‐based risk model to characterize bycatch risk in industrial and artisanal purse‐seine fisheries based on fishing set data from scientific observers and artisanal fleet logs (2010–2015), the bivariate sea lion distribution map, and criteria ratings of interaction characteristics. Our results indicate population‐level associations with productive, shallow, low slope waters, near to river‐mouths, and with high eddy activity. Individual distribution was restricted to shallow slopes and cool waters. Variation between approaches may reflect intrinsic factors restricting use of otherwise favorable habitat; however, sample size was limited, and additional data are needed to establish the full range of individual‐level distributions. Our bycatch risk outputs identified highest risk from industrial fisheries operating nearshore (within 5 NM) and risk was lower, overall, for the artisanal fleet. This research demonstrates the potential for integrating potential and realized distribution models within a spatial risk assessment and fills a gap in knowledge on this species' distribution, providing a basis for targeting bycatch mitigation outreach and interventions.