Data from: Integrating passive acoustic and visual data to model spatial patterns of occurrence in coastal dolphins
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https://datadryad.org/dataset/doi:10.5061/dryad.3dd4d
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资源简介:
Fine-scale information on the occurrence of coastal cetaceans is required
to support regulation of offshore energy developments and marine spatial
planning. In particular, the EU Habitats Directive requires an
understanding of the extent to which animals from Special Areas of
Conservation (SAC) use adjacent waters, where survey effort is often
sparse. Designing survey regimes that can be used to support these
assessments is especially challenging because visual sightings are
expected to be rare in peripheral parts of a population's range.
Consequently, even intensive visual line-transect surveys can result in
few encounters. Static passive acoustic monitoring (PAM) provides new
opportunities to extend survey effort by using echolocation click
detections to quantify levels of occurrence of coastal dolphins, but this
does not provide information on species identity. In NE Scotland,
assessments of proposed offshore energy developments required information
on spatial patterns of occurrence of bottlenose dolphins in waters in and
next to the Moray Firth SAC. Here, we illustrate how this can be achieved
by integrating data from broad-scale PAM arrays with presence-only data
from visual surveys. Generalized estimating equations were used with PAM
data to model the occurrence of dolphins in relation to depth, distance to
coast, slope, and sediment, and to predict the spatial variation in the
cumulative occurrence of all dolphin species across a 4 × 4 km grid of the
study area. Classification tree analysis was then applied to available
visual sightings data to estimate the likely species identity of dolphins
sighted in each grid cell in relation to local habitat. By multiplying
these probabilities, it was possible to provide advice on spatial
variation in the probability of encountering bottlenose dolphins from this
protected population at a regional scale, complementing data from surveys
that estimate average density or overall abundance within a region.
提供机构:
Dryad
创建时间:
2014-05-22



