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Integrating Multiple Distribution Models to Guide Conservation Efforts of an Endangered Toad

Overview of attention for article published in PLOS ONE, June 2015
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

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7 tweeters

Citations

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10 Dimensions

Readers on

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55 Mendeley
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Title
Integrating Multiple Distribution Models to Guide Conservation Efforts of an Endangered Toad
Published in
PLOS ONE, June 2015
DOI 10.1371/journal.pone.0131628
Pubmed ID
Authors

Michael L. Treglia, Robert N. Fisher, Lee A. Fitzgerald

Abstract

Species distribution models are used for numerous purposes such as predicting changes in species' ranges and identifying biodiversity hotspots. Although implications of distribution models for conservation are often implicit, few studies use these tools explicitly to inform conservation efforts. Herein, we illustrate how multiple distribution models developed using distinct sets of environmental variables can be integrated to aid in identification sites for use in conservation. We focus on the endangered arroyo toad (Anaxyrus californicus), which relies on open, sandy streams and surrounding floodplains in southern California, USA, and northern Baja California, Mexico. Declines of the species are largely attributed to habitat degradation associated with vegetation encroachment, invasive predators, and altered hydrologic regimes. We had three main goals: 1) develop a model of potential habitat for arroyo toads, based on long-term environmental variables and all available locality data; 2) develop a model of the species' current habitat by incorporating recent remotely-sensed variables and only using recent locality data; and 3) integrate results of both models to identify sites that may be employed in conservation efforts. We used a machine learning technique, Random Forests, to develop the models, focused on riparian zones in southern California. We identified 14.37% and 10.50% of our study area as potential and current habitat for the arroyo toad, respectively. Generally, inclusion of remotely-sensed variables reduced modeled suitability of sites, thus many areas modeled as potential habitat were not modeled as current habitat. We propose such sites could be made suitable for arroyo toads through active management, increasing current habitat by up to 67.02%. Our general approach can be employed to guide conservation efforts of virtually any species with sufficient data necessary to develop appropriate distribution models.

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Unknown 53 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 33%
Student > Ph. D. Student 11 20%
Student > Doctoral Student 8 15%
Student > Master 6 11%
Student > Bachelor 4 7%
Other 5 9%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 53%
Environmental Science 18 33%
Computer Science 1 2%
Earth and Planetary Sciences 1 2%
Medicine and Dentistry 1 2%
Other 0 0%
Unknown 5 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 July 2021.
All research outputs
#5,767,727
of 20,585,915 outputs
Outputs from PLOS ONE
#63,671
of 177,676 outputs
Outputs of similar age
#68,533
of 244,529 outputs
Outputs of similar age from PLOS ONE
#2,067
of 6,386 outputs
Altmetric has tracked 20,585,915 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 177,676 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one has gotten more attention than average, scoring higher than 63% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 244,529 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 6,386 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.