Data from: Assessing the permeability of landscape features to animal movement: using genetic structure to infer functional connectivity

Anderson SJ, Kierepka EM, Swihart RK, Latch EK, Rhodes Jr. OE

Date Published: March 3, 2015

DOI: http://dx.doi.org/10.5061/dryad.p5hd0

 

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Title Bootstrap31
Downloaded 9 times
Description Example of Bootstrap Iteration for 3 m segment width. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 3 m segment, ntc = proportion of non-treed corridors in 3 m segment, road = proportion of roads in 3 m segment, grass = proportion of grassland in 3 m segment, shrub = proportion of shrubland in 3 m segment, treedcorr = proportion of treed corridors in 3 m segment, urban = proportion of urban land in 3 m segment, water = proportion of water/wetland in 3 m segment
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Title Bootstrap101
Downloaded 4 times
Description Example of Bootstrap Iteration for 10 m segment width. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 10 m segment, ntc = proportion of non-treed corridors in 10 m segment, road = proportion of roads in 10 m segment, grass = proportion of grassland in 10 m segment, shrub = proportion of shrubland in 10 m segment, treedcorr = proportion of treed corridors in 10 m segment, urban = proportion of urban land in 10 m segment, water = proportion of water/wetland in 10 m segment
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Title Bootstrap251
Downloaded 2 times
Description Example of Bootstrap Iteration for 25 m segment width. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 25 m segment, ntc = proportion of non-treed corridors in 25 m segment, road = proportion of roads in 25 m segment, grass = proportion of grassland in 25 m segment, shrub = proportion of shrubland in 25 m segment, treedcorr = proportion of treed corridors in 25 m segment, urban = proportion of urban land in 25 m segment, water = proportion of water/wetland in 25 m segment
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Title Bootstrap501
Downloaded 3 times
Description Example of Bootstrap Iteration for 50 m segment width. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 50 m segment, ntc = proportion of non-treed corridors in 50 m segment, road = proportion of roads in 50 m segment, grass = proportion of grassland in 50 m segment, shrub = proportion of shrubland in 50 m segment, treedcorr = proportion of treed corridors in 50 m segment, urban = proportion of urban land in 50 m segment, water = proportion of water/wetland in 50 m segment
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Title Bootstrap1001
Downloaded 5 times
Description Example of Bootstrap Iteration for 100 m segment width. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 100 m segment, ntc = proportion of non-treed corridors in 100 m segment, road = proportion of roads in 100 m segment, grass = proportion of grassland in 100 m segment, shrub = proportion of shrubland in 100 m segment, treedcorr = proportion of treed corridors in 100 m segment, urban = proportion of urban land in 100 m segment, water = proportion of water/wetland in 100 m segment
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Title Bootstrap2001
Downloaded 6 times
Description Example of Bootstrap Iteration for 200 m segment width. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 200 m segment, ntc = proportion of non-treed corridors in 200 m segment, road = proportion of roads in 200 m segment, grass = proportion of grassland in 200 m segment, shrub = proportion of shrubland in 200 m segment, treedcorr = proportion of treed corridors in 200 m segment, urban = proportion of urban land in 200 m segment, water = proportion of water/wetland in 200 m segment
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Title Bootstrap4001
Downloaded 6 times
Description Example of Bootstrap Iteration for 400 m segment width. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 400 m segment, ntc = proportion of non-treed corridors in 400 m segment, road = proportion of roads in 400 m segment, grass = proportion of grassland in 400 m segment, shrub = proportion of shrubland in 400 m segment, treedcorr = proportion of treed corridors in 400 m segment, urban = proportion of urban land in 400 m segment, water = proportion of water/wetland in 400 m segment
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Title Bootstrap10001
Downloaded 7 times
Description Example of Bootstrap Iteration for 1000 m segment width. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 1000 m segment, ntc = proportion of non-treed corridors in 1000 m segment, road = proportion of roads in 1000 m segment, grass = proportion of grassland in 1000 m segment, shrub = proportion of shrubland in 1000 m segment, treedcorr = proportion of treed corridors in 1000 m segment, urban = proportion of urban land in 1000 m segment, water = proportion of water/wetland in 1000 m segment
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Title Chip_LogisticRegressionResults
Downloaded 4 times
Description Results of logistic regression models across 1000 bootstrap iterations. This file includes estimates, z values and p-values for parameter estimates and full models.
Download Chip_LogisticRegressionResults.xlsx (2.672 Mb)
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Title Chip_MultipleRegressionResults
Downloaded 40 times
Description Results of multiple regression models across 1000 bootstrap iterations. This file includes estimates, t values and p-values for parameter estimates and full models.
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Title ChipmunkFull3
Downloaded 6 times
Description Full dataset for 3 m segment. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 3 m segment, ntc = proportion of non-treed corridors in 3 m segment, road = proportion of roads in 3 m segment, grass = proportion of grassland in 3 m segment, shrub = proportion of shrubland in 3 m segment, treedcorr = proportion of treed corridors in 3 m segment, urban = proportion of urban land in 3 m segment, water = proportion of water/wetland in 3 m segment
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Title ChipmunkFull10
Downloaded 5 times
Description Full dataset for 10 m segment. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 10 m segment, ntc = proportion of non-treed corridors in 10 m segment, road = proportion of roads in 10 m segment, grass = proportion of grassland in 10 m segment, shrub = proportion of shrubland in 10 m segment, treedcorr = proportion of treed corridors in 10 m segment, urban = proportion of urban land in 10 m segment, water = proportion of water/wetland in 10 m segment
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Title ChipmunkFull25
Downloaded 4 times
Description Full dataset for 25 m segment width. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 25 m segment, ntc = proportion of non-treed corridors in 25 m segment, road = proportion of roads in 25 m segment, grass = proportion of grassland in 25 m segment, shrub = proportion of shrubland in 25 m segment, treedcorr = proportion of treed corridors in 25 m segment, urban = proportion of urban land in 25 m segment, water = proportion of water/wetland in 25 m segment
Download ChipmunkFull25.txt (2.895 Kb)
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Title ChipmunkFull50
Downloaded 6 times
Description Full Dataset for 50 m segment. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 50 m segment, ntc = proportion of non-treed corridors in 50 m segment, road = proportion of roads in 50 m segment, grass = proportion of grassland in 50 m segment, shrub = proportion of shrubland in 50 m segment, treedcorr = proportion of treed corridors in 50 m segment, urban = proportion of urban land in 50 m segment, water = proportion of water/wetland in 50 m segment
Download ChipmunkFull50.txt (2.935 Kb)
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Title ChipmunkFull100
Downloaded 5 times
Description Full dataset for 100 m segment. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 100 m segment, ntc = proportion of non-treed corridors in 100 m segment, road = proportion of roads in 100 m segment, grass = proportion of grassland in 100 m segment, shrub = proportion of shrubland in 100 m segment, treedcorr = proportion of treed corridors in 100 m segment, urban = proportion of urban land in 100 m segment, water = proportion of water/wetland in 100 m segment
Download ChipmunkFull100.txt (3.033 Kb)
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Title ChipmunkFull200
Downloaded 3 times
Description Full dataset for 200 m segment. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 200 m segment, ntc = proportion of non-treed corridors in 200 m segment, road = proportion of roads in 200 m segment, grass = proportion of grassland in 3 m segment, shrub = proportion of shrubland in 200 m segment, treedcorr = proportion of treed corridors in 200 m segment, urban = proportion of urban land in 200 m segment, water = proportion of water/wetland in 200 m segment
Download ChipmunkFull200.txt (3.136 Kb)
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Title ChipmunkFull400
Downloaded 5 times
Description Full dataset for 400 m segments. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 400 m segment, ntc = proportion of non-treed corridors in 400 m segment, road = proportion of roads in 400 m segment, grass = proportion of grassland in 400 m segment, shrub = proportion of shrubland in 400 m segment, treedcorr = proportion of treed corridors in 400 m segment, urban = proportion of urban land in 400 m segment, water = proportion of water/wetland in 400 m segment
Download ChipmunkFull400.txt (3.311 Kb)
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Title ChipmunkFull1000
Downloaded 6 times
Description Full dataset for 1000 m segments. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in 1000 m segment, ntc = proportion of non-treed corridors in 1000 m segment, road = proportion of roads in 1000 m segment, grass = proportion of grassland in 1000 m segment, shrub = proportion of shrubland in 1000 m segment, treedcorr = proportion of treed corridors in 1000 m segment, urban = proportion of urban land in 1000 m segment, water = proportion of water/wetland in 1000 m segment
Download ChipmunkFull1000.txt (3.464 Kb)
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Title ChipmunkValidation_Results
Downloaded 6 times
Description Validation results for each regression. LR = Logistic regression, MR = Multiple regression. Results are given as count data in 50 bootstrap increments and proportions of incorrect and correct data. Each bootstrap iteration was resampled 1000 times where 14 individuals were randomly selected.
Download ChipmunkValidation_Results.txt (2.325 Kb)
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Title Sub1
Downloaded 5 times
Description Example of subsample used for validation. ID = pair-wise comparison, cat = dependent variable for logistic regression, pmem = dependent variable for multiple regression, forest = proportion of forest in segment, ntc = proportion of non-treed corridors in segment, road = proportion of roads in segment, grass = proportion of grassland in segment, shrub = proportion of shrubland in segment, treedcorr = proportion of treed corridors in segment, urban = proportion of urban land in segment, water = proportion of water/wetland in segment
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Title Ts_295g
Downloaded 6 times
Description Geneland genotype input for cell 295.
Download Ts_295g.txt (13.86 Kb)
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Title Ts_295xy
Downloaded 10 times
Description Geneland coordinate input for cell 295.
Download Ts_295xy.txt (2.288 Kb)
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Title Ts_295L
Downloaded 8 times
Description Geneland ID file input for cell 295.
Download Ts_295L.txt (1.287 Kb)
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Title Ts_allfst1-fst
Downloaded 5 times
Description Fst/1-Fst between 33 study cells.
Download Ts_allfst1-fst.txt (3.907 Kb)
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Title Ts_allgeo
Downloaded 5 times
Description Euclidean distances between 33 study cells in meters.
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Title Ts_allgenotypesandcoord_use
Downloaded 7 times
Description Genalex genotype file and spatial coordinates for entire Tamias striatus dataset. Genotypes are separated by study cell.
Download Ts_allgenotypesandcoord_use.xlsx (194.1 Kb)
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Title Anderson_PloSOneCode copy
Downloaded 11 times
Description R code for regression and validation analyses.
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When using this data, please cite the original publication:

Anderson SJ, Kierepka EM, Swihart RK, Latch EK, Rhodes Jr OE (2015) Assessing the permeability of landscape features to animal movement: using genetic structure to infer functional connectivity. PLOS ONE 10(2): e0117500. http://dx.doi.org/10.1371/journal.pone.0117500

Additionally, please cite the Dryad data package:

Anderson SJ, Kierepka EM, Swihart RK, Latch EK, Rhodes Jr. OE (2015) Data from: Assessing the permeability of landscape features to animal movement: using genetic structure to infer functional connectivity. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.p5hd0
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