Data from: Identifying priority areas to guide management planning of a protected area network to support snow leopard (Panthera uncia) in Asia
Data files
Jun 08, 2026 version files 273.48 KB
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PA_centroid_all.csv
112.11 KB
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PA_e2e_all.csv
112.11 KB
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PA_e2e_centroid_mean.csv
42.76 KB
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README.md
6.50 KB
Aug 20, 2026 version files 3.69 MB
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PA_conefor_centroid_all.csv
112.11 KB
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PA_conefor_e2e_all.csv
112.11 KB
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PA_conefor_e2e_centroid_mean.csv
42.76 KB
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PA_costdistance_centroid.csv
3.34 MB
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PA_costdistance_e2e.csv
34.68 KB
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PA_kernelweight.csv
40.09 KB
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README.md
8.55 KB
Abstract
Protected areas (PAs) remain central to global biodiversity strategies to reduce accelerating declines in biodiversity; ensuring proper management, coverage, and placement of PAs is key to facilitating connectivity for wildlife populations. Graph theory approaches provide a rigorous framework to evaluate the connectivity performance of existing or proposed PAs. This study aimed to evaluate the effectiveness of an existing protected area network across Central Asia in providing functional connectivity for the snow leopard (Panthera uncia). We used the Integral Index of Connectivity (IIC) and its fractions to rank each PA’s contribution to functional connectivity of the network, and to prioritize individual PAs. We also analyzed PA’s degree of protection in relation to their importance for connectivity, and compared the current PA network to previously identified conservation areas. We found that some PAs that ranked as of high importance for connectivity showed lower degrees of official protection, including PAs that were deemed irreplaceable as connectors. Protected areas critical to maintaining and increasing connectivity were identified and ranked across the range, as well as areas of conservation interest that may not be currently protected. Practical implication: our findings provide decision support for revising PA boundaries and elevating the egal status of high-value sites. We anticipate upgraded protection status, a nd selective expansion or addition of PAs can enhance and protect functional connectivity for not only snow leopard, but other high-altitude species as well, and assist countries in meeting global biodiversity goals as outlined in the Kunming-Montreal Global Biodiversity Framework, particularly Target 3 (30x30) and Target 12 (enhancing connectivity).
Dataset DOI: 10.5061/dryad.7d7wm389t
Description of the data and file structure
Values generated via ArcGIS, R packages, and Conefor software, using two separate distance measurements.
Note: The dataset does not contain any data concerning the specific location of any individual snow leopard or other species that are endangered, threatened, rare, or commercially valuable. All values herein are derived from previously published habitat suitability models and general protected area spatial data available publicly or by request. The authors do not believe that the results identifying high-value protected areas pose any risk to the species, its habitat, or ongoing conservation efforts.
Files and variables
File: PA_conefor_centroid_all.csv
Description: varIIC and its associated fraction values generated via Conefor for all protected areas using centroid-centroid least-cost distance measurements, for each resistance threshold (100, 500, and 1000km) and their mean.
Variables
- Node ID: unique ID number for each protected area
- PAname: protected area name
- Country: protected area governing country
- IUCNcat: protected area assigned IUCN category
- Area_sqkm: area in km2
- varIIC_mean: mean of varIIC values across resistance thresholds
- varIICintra_mean: mean of varIICintra fraction values across resistance thresholds
- varIICflux_mean: mean of varIICflux fraction values across resistance thresholds
- varIICconn_mean: mean of varIICconnector fraction values across resistance thresholds
- varBCIIC_mean: mean of varBCIIC values across resistance thresholds
- varIIC_100: varIIC values at the 100km resistance threshold
- varIICintra_100: varIICintra fraction values at the 100km resistance threshold
- varIICflux_100: varIICflux fraction values at the 100km resistance threshold
- varIICconnector_100: varIICconnector fraction values at the 100km resistance threshold
- varBC_IIC_100: varBCIIC values at the 100km resistance threshold
- varIIC_500: varIIC values at the 500km resistance threshold
- varIICintra_500: varIICintra fraction values at the 500km resistance threshold
- varIICflux_500: varIICflux fraction values at the 500km resistance threshold
- varIICconnector_500: varIICconnector fraction values at the 500km resistance threshold
- varBC_IIC_500: varBCIIC values at the 500km resistance threshold
- varIIC_1k: varIIC values at the 1000km resistance threshold
- varIICintra_1k: varIICintra fraction values at the 1000km resistance threshold
- varIICflux_1k: varIICflux fraction values at the 1000km resistance threshold
- varIICconnector_1k: varIICconnector fraction values at the 1000km resistance threshold
- varBC_IIC_1k: varBCIIC values at the 1000km resistance threshold
File: PA_conefor_e2e_all.csv
Description: varIIC and its associated fraction values generated via Conefor for all protected areas using edge-to-edge least-cost distance measurements, for each resistance threshold (100, 500, and 1000km) and their mean.
Variables
- Node ID: unique ID number for each protected area
- PAname: protected area name
- Country: protected area governing country
- IUCNcat: protected area assigned IUCN category
- Area_sqkm: area in km2
- varIIC_mean: mean of varIIC values across resistance thresholds
- varIICintra_mean: mean of varIICintra fraction values across resistance thresholds
- varIICflux_mean: mean of varIICflux fraction values across resistance thresholds
- varIICconn_mean: mean of varIICconnector fraction values across resistance thresholds
- varBCIIC_mean: mean of varBCIIC values across resistance thresholds
- varIIC_100: varIIC values at the 100km resistance threshold
- varIICintra_100: varIICintra fraction values at the 100km resistance threshold
- varIICflux_100: varIICflux fraction values at the 100km resistance threshold
- varIICconnector_100: varIICconnector fraction values at the 100km resistance threshold
- varBC_IIC_100: varBCIIC values at the 100km resistance threshold
- varIIC_500: varIIC values at the 500km resistance threshold
- varIICintra_500: varIICintra fraction values at the 500km resistance threshold
- varIICflux_500: varIICflux fraction values at the 500km resistance threshold
- varIICconnector_500: varIICconnector fraction values at the 500km resistance threshold
- varBC_IIC_500: varBCIIC values at the 500km resistance threshold
- varIIC_1k: varIIC values at the 1000km resistance threshold
- varIICintra_1k: varIICintra fraction values at the 1000km resistance threshold
- varIICflux_1k: varIICflux fraction values at the 1000km resistance threshold
- varIICconnector_1k: varIICconnector fraction values at the 1000km resistance threshold
- varBC_IIC_1k: varBCIIC values at the 1000km resistance threshold
File: PA_conefor_e2e_centroid_mean.csv
Description: Mean values of varIIC and its associated fraction values generated via Conefor for all protected areas across the three resistance thresholds (100, 500, and 1000km) and between the two distance measurements (centroid and edge-to-edge).
Variables
- Node ID: unique ID number for each protected area
- PAname: protected area name
- Country: protected area governing country
- IUCNcat: protected area assigned IUCN category
- Area_sqkm: area in km2
- varIIC_mean: mean of varIIC values across resistance thresholds/distance measurements
- varIICintra_mean: mean of varIICintra fraction values across resistance thresholds/distance measurements
- varIICflux_mean: mean of varIICflux fraction values across resistance thresholds/distance measurements
- varIICconn_mean: mean of varIICconnector fraction values across resistance thresholds/distance measurements
- varBCIIC_mean: mean of varBCIIC values across resistance thresholds/distance measurements
File: PA_costdistance_e2e.csv
Description: Edge-to-edge cost distance values between PA boundaries generated via LinkageMapper in ESRI ArcGIS Pro.
Variables
- #link: sequential number assigned to each PA pairwise link being measured
- nodeID1: unique ID number for the first protected area represented in each PA pair being measured
- nodeID2: unique ID number for the second protected area represented in each PA pair being measured
- costdist: measured cost distance between each pair of PAs
File: PA_kernelweight.csv
Description: Weighted score calculated as the resistant kernel strength for each dispersal threshold (sum of kernel values within the PA) divided by total area.
Variables
- Node ID: unique ID number for each protected area
- PAname: protected area name
- Country: protected area governing country
- IUCNcat: protected area assigned IUCN category
- Area_sqkm: area in km2
- Kernelsum_100: sum of kernel values at the 100km resistance threshold
- Kernelsum_500: sum of kernel values at the 500km resistance threshold
- Kernelsum_1k: sum of kernel values at the 1000km resistance threshold
- Kernelweight_100: weighted kernel values at the 100km resistance threshold
- Kernelweight_500: weighted kernel values at the 500km resistance threshold
- Kernelweight_1k: weighted kernel values at the 1000km resistance threshold
File: PA_costdistance_centroid.csv
Description: Cost distance values between PA centroids generated via the SGD package in RStudio.
Variables
- #link: sequential number assigned to each PA pairwise link being measured
- nodeID1: unique ID number for the first protected area represented in each PA pair being measured
- nodeID2: unique ID number for the second protected area represented in each PA pair being measured
- costdist: measured cost distance between each pair of PAs
Code/software
ESRI ArcGIS Pro 3.2.0, LinkageMapper plugin
R version 4.1.0, RStudio version 2023.03.0, SGD package
Conefor 2.6
Access information
Other publicly accessible locations of the data:
- None
Data was derived from the following sources:
- IUCN World Database of Protected Areas (WDPA)
- Birdlife Key Biodiversity Areas (KBA)
- Chinese Academy of Science
- Riordan P, Cushman SA, Mallon D, et al (2016). Predicting global population connectivity and targeting conservation action for the snow leopard across its range. Ecography (Cop) 39:419–426. https://doi.org/10.1111/ecog.01691
Changes after Jun 8, 2026: Slight renaming of files to provide better description and distinction. Upload of additional data files to complement previous data set.
