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Explaining Local-Scale Species Distributions: Relative Contributions of Spatial Autocorrelation and Landscape Heterogeneity for an Avian Assemblage

Overview of attention for article published in PLoS ONE, February 2013
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Title
Explaining Local-Scale Species Distributions: Relative Contributions of Spatial Autocorrelation and Landscape Heterogeneity for an Avian Assemblage
Published in
PLoS ONE, February 2013
DOI 10.1371/journal.pone.0055097
Pubmed ID
Authors

Brady J. Mattsson, Elise F. Zipkin, Beth Gardner, Peter J. Blank, John R. Sauer, J. Andrew Royle

Abstract

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 8%
Canada 3 3%
Brazil 2 2%
Spain 1 <1%
Czechia 1 <1%
India 1 <1%
Latvia 1 <1%
Costa Rica 1 <1%
Portugal 1 <1%
Other 4 4%
Unknown 85 78%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 29%
Student > Ph. D. Student 25 23%
Student > Master 21 19%
Student > Bachelor 9 8%
Unspecified 5 5%
Other 17 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 56 51%
Environmental Science 32 29%
Unspecified 12 11%
Earth and Planetary Sciences 4 4%
Social Sciences 2 2%
Other 3 3%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 February 2013.
All research outputs
#10,721,872
of 12,091,208 outputs
Outputs from PLoS ONE
#113,225
of 133,026 outputs
Outputs of similar age
#246,676
of 291,889 outputs
Outputs of similar age from PLoS ONE
#5,286
of 6,623 outputs
Altmetric has tracked 12,091,208 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 133,026 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 291,889 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6,623 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.