Dataset Identification:
Resource Abstract:
- description: Cave-limited species display patchy and restricted distributions, but are challenging to study in-situ because
of the difficulty of sampling. It is often unclear whether the observed distribution is a sampling artifact or a true restriction
in range. Further, the drivers of the distribution could be local environmental conditions, such as cave humidity, or they
could be associated with surface features that are surrogates for cave conditions. If surface features can be used to predict
the distribution of important cave taxa, then conservation management goals can be more easily obtained. These GIS data represent
the input and results of a spatial statistical model used to examine the hypothesis that the presence of major faunal groups
of cave obligate species could be predicted based on features of the earth surface. Georeferenced records of cave obligate
amphipods, crayfish, fish, isopods, beetles, millipedes, pseudoscorpions, spiders, and springtails within the area of Appalachian
Landscape Conservation Cooperative (LCC) in the eastern United States (Illinois to Virginia, and New York to Alabama) were
assigned to 20 x 20 km grid cells. Habitat suitability for these faunal groups was modeled using logistic regression with
twenty predictor variables within each grid cell, such as percent karst, soil features, temperature, precipitation, and elevation.
The models successfully predicted the presence of a group greater than 65 percent of the time (mean=88 percent) for the presence
of single grid cell endemics, and for all faunal groups except pseudoscorpions. The most common predictor variables were latitude,
percent karst, and the standard deviation of the Topographic Position Index (TPI), a measure of landscape rugosity within
each grid cell. The overall success of these models points to a number of important connections between the surface and cave
environments, and some of these, especially soil features and topographic variability, suggest new research directions. These
models should prove to be useful tools in predicting the presence of species in understudied areas.; abstract: Cave-limited
species display patchy and restricted distributions, but are challenging to study in-situ because of the difficulty of sampling.
It is often unclear whether the observed distribution is a sampling artifact or a true restriction in range. Further, the
drivers of the distribution could be local environmental conditions, such as cave humidity, or they could be associated with
surface features that are surrogates for cave conditions. If surface features can be used to predict the distribution of important
cave taxa, then conservation management goals can be more easily obtained. These GIS data represent the input and results
of a spatial statistical model used to examine the hypothesis that the presence of major faunal groups of cave obligate species
could be predicted based on features of the earth surface. Georeferenced records of cave obligate amphipods, crayfish, fish,
isopods, beetles, millipedes, pseudoscorpions, spiders, and springtails within the area of Appalachian Landscape Conservation
Cooperative (LCC) in the eastern United States (Illinois to Virginia, and New York to Alabama) were assigned to 20 x 20 km
grid cells. Habitat suitability for these faunal groups was modeled using logistic regression with twenty predictor variables
within each grid cell, such as percent karst, soil features, temperature, precipitation, and elevation. The models successfully
predicted the presence of a group greater than 65 percent of the time (mean=88 percent) for the presence of single grid cell
endemics, and for all faunal groups except pseudoscorpions. The most common predictor variables were latitude, percent karst,
and the standard deviation of the Topographic Position Index (TPI), a measure of landscape rugosity within each grid cell.
The overall success of these models points to a number of important connections between the surface and cave environments,
and some of these, especially soil features and topographic variability, suggest new research directions. These models should
prove to be useful tools in predicting the presence of species in understudied areas.
Citation
- Title GIS data for predicting the occurrence of cave-inhabiting fauna based on features of the Earth surface environment in the
Appalachian Landscape Conservation Cooperative (LCC) Region.
-
- creation Date
2018-06-08T15:36:51.073625
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- URL: http://dx.doi.org/10.5066/F76D5R2H
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- URL: http://dx.doi.org/10.5066/F76D5R2H
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- URL: http://dx.doi.org/10.1371/journal.pone.0160408
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Metadata data stamp:
2018-08-06T20:57:34Z
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- notes: This metadata record was generated by an xslt transformation from a dc metadata record; Transform by Stephen M. Richard, based
on a transform by Damian Ulbricht. Run on 2018-08-06T20:57:34Z
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CINERGI Metadata catalog
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eng
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standard version:
2007
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urn:dciso:metadataabout:bb16df1b-f375-40ce-ac84-6f2b0437cdc1
Metadata record format is ISO19139 XML (MD_Metadata)