Researchers Develop Predictive Model to Improve Legislation
Federal laws that designate so-called Critical Habitat for Steller sea lions have played a key role in driving conservation policy for these marine mammals in Alaska, but the information this designation was based on is now dated. Consortium researchers have used more recent knowledge to better predict the occurrence of sea lions at sea, providing policy makers with new tools to refine and update current legislation designating Critical Habitat.
Legislation such as the US Endangered Species Act (1972) plays an important role in designating and protecting habitat that is critical to the survival of a population or species. In the case of western Alaska’s endangered Steller sea lion populations, areas designated as Critical Habitat currently include all major haulouts and rookeries and their associated aquatic zones extending 20nmi (37km) seaward, in addition to some larger presumed foraging areas in the Bering Sea (Figure 1).
Building a Predictive Model
“We used published information about foraging behavior, terrestrial resting sites, bathymetry, and seasonal ocean climate to develop hypotheses relating life history traits and physical variables to the at-sea habitat of Steller sea lions,” the authors write. One hypothesis predicted, for example, that optimal foraging opportunities for Steller sea lions occur near depths of 200m (656ft), based on consistent reports that maximum densities of both bottom-dwelling and free-swimming fish also occur at that depth.
Figure 1: The spatial extents of the study area showing major Steller sea lion terrestrial sites (black symbols), platform of opportunity (POP) sightings of Steller sea lions (green symbols), and designated Critical Habitat (black line). The coastline is in gray and the marine portion is shaded from light to dark in increasing depth.
When this Critical Habitat was designated in 1993 it was likely based on the best available knowledge. This model of Critical Habitat has formed the basis for all subsequent protective legislation for Steller sea lions. However, the rationale for selecting these particular boundaries has never been fully explained or justified. Do they accurately represent habitat that sea lions frequent and rely upon year-round? Or could knowledge gained in the intervening years be used to develop a more robust and defensible definition of Critical Habitat for this species?
To answer these and other questions, Consortium researchers Edward Gregr and Andrew Trites (both of the University of British Columbia) developed a series of habitat models to predict the probability of sea lions occurring on a fine scale within the Gulf of Alaska and Bering Sea. The study was recently published in Marine Ecology Progress Series.
Building a Predictive Model
“We used published information about foraging behavior, terrestrial resting sites, bathymetry, and seasonal ocean climate to develop hypotheses relating life history traits and physical variables to the at-sea habitat of Steller sea lions,” the authors write. One hypothesis predicted, for example, that optimal foraging opportunities for Steller sea lions occur near depths of 200m (656ft), based on consistent reports that maximum densities of both bottom-dwelling and free-swimming fish also occur at that depth.
The researchers then divided the survey area – from Southeast Alaska to the end of the Aleutian Island chain – into grids of 3 x 3 km2 (3.47 square miles). Applying the eight broad hypotheses, which considered both the accessibility and suitability of sea lion habitat, they developed a series of habitat models predicting the probability of sea lions occurring at sea within each grid (e.g., Fig 2). These models were then compared with actual at-sea observations of sea lions (Fig. 3) using a skewness test to assess how the predicted probabilities related to the observations.
Figure 2 – The best performing habitat prediction for adult females during winter
(non-breeding season). The model was based on depth and sea surface height variability. Model
predictions of 0.0 are shown as white to clearly delimit the spatial extent of non-zero values.
Figure 3 – A comparison of the designated model for Steller sea lions (red line) to the best performing predictive model based on hypothesized depth and front suitability. The HS1 model captured 43.7% of the POP observations, while the designated model captured 36.1%. The POP data are overlaid in (b) to support comparisons of the relative model performance.
The results were encouraging. The habitat maps produced for adult female sea lions, for example, captured a higher proportion (43.7%) of actual at-sea observations than did the current Critical Habitat model (36.1%).
A Novel Technique
Many studies have described pinniped foraging behavior, but few have used the information gleaned from such studies to develop predictions of where sea lions will occur. The quantitative approach used by Gregr and Trites to describe fine-scale, at-sea distributions of Steller sea lions across their Alaskan range has not been previously attempted, but the authors maintain that such a prediction is necessary to effectively design, implement and evaluate any measures intended to protect Steller sea lion populations.
“Our results show that explicitly stating a priori hypotheses about the relationships between species distributions and physical and biological factors, and subsequently validating the resulting predictions, moves conservation biology and resource management closer to understanding ecosystem function, and places the debate of delineating habitat where it should be—on the state of available knowledge and how the animals are believed to be distributed.”
The skewness test played a key role in the model development. Developed by the authors, this test allows presence-only data to be used as a measure of model performance. The authors write “Our goal was to demonstrate that a deductive model could be built with some quantitative rigor in the absence of range-wide survey data. Skewness provides both a quantitative and visual interpretation of how well the predictive models achieve this.”
This study opens the door for future habitat models with higher resolutions and smaller spatial extents to address more local movements of sea lions, and eventually, of other wide-ranging marine predators. However, the authors note that a more comprehensive habitat-based definition of Critical Habitat will require developing hypotheses for other age and sex classes, such as juveniles, but this will require more complex at-sea data than is currently available.
November 24, 2008
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