Data from: Responses of sympatric canids to human development revealed through citizen science
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https://datadryad.org/dataset/doi:10.5061/dryad.0cfxpnvzs
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资源简介:
Measuring wildlife responses to anthropogenic activities often requires
long-term, large-scale datasets that are difficult to collect. This is
particularly true for rare or cryptic species, which includes many
mammalian carnivores. Citizen science, in which members of the public
participate in scientific work, can facilitate collection of large
datasets while increasing public awareness of wildlife research and
conservation. Hunters provide unique benefits for citizen science given
their knowledge and interest in outdoor activities. We examined how
anthropogenic changes to land cover impacted relative abundance of two
sympatric canids, coyote (Canis latrans) and red fox (Vulpes vulpes) at a
large spatial scale. In order to assess how land cover affected canids at
this scale, we used citizen science data from bow hunter sighting logs
collected throughout New York State, USA, during 2004–2017. We found that
the two species had contrasting responses to development, with red foxes
positively correlated and coyotes negatively correlated with the
percentage of low-density development. Red foxes also responded positively
to agriculture, but less so when agricultural habitat was fragmented.
Agriculture provides food and denning resources for red foxes, whereas
coyotes may select forested areas for denning. Though coyotes and red
foxes compete in areas of sympatry, we did not find a relationship between
species abundance, likely a consequence of the coarse spatial resolution
used. Red foxes may be able to coexist with coyotes by altering their
diets and habitat use, or by maintaining territories in small areas
between coyote territories. Our study shows the value of citizen science,
and particularly hunters, in collection of long-term data across large
areas (i.e., the entire state of New York) that otherwise would unlikely
be obtained.
提供机构:
Dryad
创建时间:
2020-07-06



