Dear Colleagues,
I would like to bring your attention to the following paper that was recently
published in Ecological Applications. In particular, I believe this paper will
be of interest to those who are working on predictive habitat models of marine
mammals. The article may be downloaded from
ftp://ecap-18-06-07_07-1455_rfp:[EMAIL PROTECTED] or by request to me.
Cheers,
Leigh Torres
Torres, L., Read, A., and Halpin, P. 2008. Fine-scale habitat modeling of a top
marine predator: Do prey data improve predictive capacity? Ecological
Applications. 18(7), 1702-1717.
Abstract:
Predators and prey assort themselves relative to each other, the availability
of resources and refuges, and the temporal and spatial scale of their
interaction. Predictive models of predator distributions often rely on these
relationships by incorporating data on environmental variability and prey
availability to determine predator habitat selection patterns. This approach to
predictive modeling holds true in marine systems where observations of
predators are logistically difficult, emphasizing the need for accurate models.
In this paper, we ask whether including prey distribution data in fine-scale
predictive models of bottlenose dolphin (Tursiops truncatus) habitat selection
in Florida Bay, Florida, USA, improves predictive capacity. Environmental
characteristics are often used as predictor variables in habitat models of top
marine predators with the assumption that they act as proxies of prey
distribution. We examine the validity of this assumption by
comparing the response of dolphin distribution and fish catch rates to the
same environmental variables. Next, the predictive capacities of four models,
with and without prey distribution data, are tested to determine whether
dolphin habitat selection can be predicted without recourse to describing the
distribution of their prey. The final analysis determines the accuracy of
predictive maps of dolphin distribution produced by modeling areas of high fish
catch based on significant environmental characteristics. We use spatial
analysis and independent data sets to train and test the models. Our results
indicate that, due to high habitat heterogeneity and the spatial variability of
prey patches, fine-scale models of dolphin habitat selection in coastal
habitats will be more successful if environmental variables are used as
predictor variables of predator distributions rather than relying on prey data
as explanatory variables. However, predictive modeling
of prey distribution as the response variable based on environmental
variability did produce high predictive performance of dolphin habitat
selection, particularly foraging habitat.
Leigh G. Torres
Post-doctoral researcher
National Institute of Water and Atmospheric Research (NIWA)
301 Evans Bay Parade, Greta Point,
Kilbirnie, Wellington, New Zealand.
E-mail: [EMAIL PROTECTED]
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