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Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species

Overview of attention for article published in Environmental Management, April 2016
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  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species
Published in
Environmental Management, April 2016
DOI 10.1007/s00267-016-0698-y
Pubmed ID
Authors

Dennis Rödder, Sven Nekum, Anna F. Cord, Jan O. Engler

Abstract

Climate change and anthropogenic habitat fragmentation are considered major threats for global biodiversity. As a direct consequence, connectivity is increasingly disrupted in many species, which might have serious consequences that could ultimately lead to the extinction of populations. Although a large number of reserves and conservation sites are designated and protected by law, potential habitats acting as inter-population connectivity corridors are, however, mostly ignored in the common practice of environmental planning. In most cases, this is mainly caused by a lack of quantitative measures of functional connectivity available for the planning process. In this study, we highlight the use of fine-scale potential connectivity models (PCMs) derived from multispectral satellite data for the quantification of spatially explicit habitat corridors for matrix-sensitive species of conservation concern. This framework couples a species distribution model with a connectivity model in a two-step framework, where suitability maps from step 1 are transformed into maps of landscape resistance in step 2 filtered by fragmentation thresholds. We illustrate the approach using the sand lizard (Lacerta agilis L.) in the metropolitan area of Cologne, Germany, as a case study. Our model proved to be well suited to identify connected as well as completely isolated populations within the study area. Furthermore, due to its fine resolution, the PCM was also able to detect small linear structures known to be important for sand lizards' inter-population connectivity such as railroad embankments. We discuss the applicability and possible implementation of PCMs to overcome shortcomings in the common practice of environmental impact assessments.

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

Mendeley readers

The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
Australia 1 <1%
Belize 1 <1%
Mexico 1 <1%
Belgium 1 <1%
United States 1 <1%
Unknown 115 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 18%
Researcher 21 17%
Student > Master 20 16%
Student > Bachelor 9 7%
Professor > Associate Professor 7 6%
Other 15 12%
Unknown 28 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 30%
Environmental Science 34 28%
Biochemistry, Genetics and Molecular Biology 4 3%
Earth and Planetary Sciences 4 3%
Social Sciences 2 2%
Other 4 3%
Unknown 37 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 08 September 2017.
All research outputs
#7,147,625
of 25,371,288 outputs
Outputs from Environmental Management
#608
of 1,913 outputs
Outputs of similar age
#94,684
of 313,426 outputs
Outputs of similar age from Environmental Management
#10
of 20 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 1,913 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has gotten more attention than average, scoring higher than 68% 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 313,426 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 69% of its contemporaries.
We're also able to compare this research output to 20 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 50% of its contemporaries.