Spatially-explicit habitat models can impart a scientific basis for delineating critical habitats that relate species' distributions to physical and biological conditions, even in marine environments with vague and dynamic boundaries. We developed a habitat model of the relationship between the winter distribution of North Atlantic right whales Eubalaena glacialis, one of the most endangered large whales in the world, and environmental characteristics in its only identified calving ground, the waters off Florida and Georgia. Our objective was to provide a scientific basis for revising critical habitat boundaries in the southeastern USA (SEUS) and to predict potential habitat in the mid-Atlantic region north of the study area through a better understanding of the relationship of observed right whale distribution to environmental conditions. A long-term data set of right whale sightings from aerial surveys within the SEUS (conducted seasonally, December through March, from 1992March, from /1993March, from to 2000March, from /2001 was used in a generalized additive model to eval uate right whale distribution in relation to sea surface temperature, bathymetry, wind data, and several spatial variables. Model results indicated that sea surface temperature and water depth were significant predictors of calving right whale spatial distribution. The habitat relationships were unimodal, with peak sighting rates occurring at water temperatures of 13 to 15°C and water depths of 10 to 20 m. Model results indicated areas of potentially important calving habitat outside currently defined critical habitat. Our semi-monthly predicted distributions, based on model results, provide managers with a range of scientifically based choices for revising critical habitat boundaries to achieve the desired level of protection. Predictions extrapolated through the mid-Atlantic suggested appropriate habitat features north of the study site, although analysis of data from more recent surveys in this region would be required to validate model results.KEY WORDS: Eubalaena glacialis · Generalized additive model · GAM · Spatially-explicit model · Geographic Information System · GIS · Critical habitat · Primary constituent element · PCE Resale or republication not permitted without written consent of the publisher Contribution to the Theme Section 'Beyond marine mammal habitat modeling' OPEN PEN
A primary factor threatening the recovery of the North Atlantic right whale is the ongoing risk of collision with large ocean-going vessels. Hence, any viable conservation strategy must include mitigation of this risk. In particular, the critical wintering habitat off the Atlantic shores of the southeastern United States overlaps with the shipping routes of some of the region's busiest ports. As a first step in the process of ship strike risk mitigation for this region, we estimated the risk associated with current patterns of shipping traffic, and compared this with estimates of risk for a set of hypothetical alternative routes. As a measure of risk, we selected the co-occurrence of whales and vessels within cells of a 4 km grid. We performed parametric estimation of whale encounter rate and associated risk within a Bayesian hierarchical model, using data from aerial surveys and the Mandatory Ship Reporting System of the SE United States, along with a selection of environmental covariates. Importantly, we were able to account for annual and monthly variation in encounters in our estimates. All alternative routes provided reduced overall risk, ranging from a 27 to 44% reduction, relative to the estimated risk of observed traffic. The largest marginal gains in risk reduction were attained by restricting traffic associated with the busiest port, Jacksonville, Florida, but restrictions on all ports achieved the highest reduction. We emphasize the importance of accounting for temporal as well as spatial variation in whale encounter rates, given the migratory behavior of the species.
KEY WORDS: Bayesian model · Eubalaena glacialis · Hierarchical model · Right whale · Risk analysisResale or republication not permitted without written consent of the publisher OPEN PEN
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