Habitat use of seven different species of cetaceans inhabiting the Pelagos Sanctuary was studied using 18-year summer shipboard surveys data, in an area of approximately 25,000 km2. 2940 sightings were collected: 1996 striped dolphins, 626 fin whales, 120 Risso’s dolphins, 114 sperm whales, 27 common bottlenose dolphins, 25 long-finned pilot whales, 23 Cuvier’s beaked whales. Stepwise Logistic Regression Analysis was used to develop presence/absence predictive models. Statistics of depth and slope were used as covariates. Significant correlations were outlined (P < 0.05) supporting the hypothesis that physiographic factors may be employed as predictors of the species presence. The temporal variability of the species habitat use was also analyzed, confirming the reliability of the physiographic predictors. Temporal trends and variability in the species distribution were also assessed through a GLM analysis. The understanding offered by this long-term study is essential for managing the conservation status of these wide-ranging species.
Predictive Habitat Models For Managing Marine Areas: Spatial And Temporal Distribution Of Marine Mammals Within The Pelagos Sanctuary (Northwestern Mediterranean Sea).
AZZELLINO, ARIANNA;LANFREDI, CATERINA;
2012-01-01
Abstract
Habitat use of seven different species of cetaceans inhabiting the Pelagos Sanctuary was studied using 18-year summer shipboard surveys data, in an area of approximately 25,000 km2. 2940 sightings were collected: 1996 striped dolphins, 626 fin whales, 120 Risso’s dolphins, 114 sperm whales, 27 common bottlenose dolphins, 25 long-finned pilot whales, 23 Cuvier’s beaked whales. Stepwise Logistic Regression Analysis was used to develop presence/absence predictive models. Statistics of depth and slope were used as covariates. Significant correlations were outlined (P < 0.05) supporting the hypothesis that physiographic factors may be employed as predictors of the species presence. The temporal variability of the species habitat use was also analyzed, confirming the reliability of the physiographic predictors. Temporal trends and variability in the species distribution were also assessed through a GLM analysis. The understanding offered by this long-term study is essential for managing the conservation status of these wide-ranging species.File | Dimensione | Formato | |
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OCMA Predictive models Azzellino et al.pdf
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