Potential movement pathways between priority areas of conservation for sage-grouse, Results from Circuitscape modeling process
Dates
Publication Date
2015-07-25
Time Period
2015-07-25
Citation
Crist, M.R., Knick, S.T., and Hanser, S.E., 2017, Raster digital data sets identifying a range-wide network of priority areas for greater sage-grouse: U.S. Geological Survey data release, https://doi.org/10.5066/F7DB7ZZK.
Summary
Circuitscape software (v4.0, www.circuitscape.org) was applied to a range-wide habitat similarity index map for sage-grouse to model pathways between all priority areas of conservation network. We assumed that individual sage-grouse would move more easily through areas meeting their habitat requirements and used a scaled inverse of our mapped habitat scores as resistance to sage-grouse movements among the priority areas. Resistance values ranged from 1 representing the lowest resistance/highest habitat value to 100 (high resistance/lowest habitat value). Circuitscape (McRae et al. 2008) was run using the pairwise mode to calculate connectivity between all pairs of priority areas. Priority areas were treated as focal patches instead [...]
Summary
Circuitscape software (v4.0, www.circuitscape.org) was applied to a range-wide habitat similarity index map for sage-grouse to model pathways between all priority areas of conservation network. We assumed that individual sage-grouse would move more easily through areas meeting their habitat requirements and used a scaled inverse of our mapped habitat scores as resistance to sage-grouse movements among the priority areas. Resistance values ranged from 1 representing the lowest resistance/highest habitat value to 100 (high resistance/lowest habitat value). Circuitscape (McRae et al. 2008) was run using the pairwise mode to calculate connectivity between all pairs of priority areas. Priority areas were treated as focal patches instead of individual nodes in the modeling process: evaluating habitat pathways from priority area boundaries rather than nodes captures the delineated priority area structure and size in effectively reducing distance between priority areas. For each priority area pair in our network, one priority area was connected to a 1-amp current source and the other was connected to a ground. Effective resistance distances were calculated iteratively between all priority area pairs and maps of current densities between each pair, and cumulative and maximum current densities across all pairs were produced.
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Purpose
The goal was to model the relative isolation of priority areas across the historic range. Results from Circuitscape were used to map habitat linkages among all priority areas and identify clusters of connected priority areas. Circuit theory is advantageous for quantifying connectivity in this manner because of its ability to simultaneously evaluate the contributions of multiple dispersal pathways in heterogeneous landscapes, and identify areas important for connectivity conservation (McRae 2006; McRae et al. 2008). Visual observations of the maximum current densities and computed effective resistance distances resulting from Circuitscape were used to identify areas where habitat connectivity is high or low between priority areas. The maximum current density map was used in identifications of habitat linkages because maximum values help to remove the confounding effects of network configuration (halo effect) in the Circuitscape results. Again, greater connectivity among priority areas was indicated by a larger number of connected pathways and lower effective resistance distance values. Visual identifications of locations of high current densities that may function as bottlenecks (pinch points) to sage-grouse movements where alternative pathways are not available (McRae et al. 2008). These locations may represent conservation priorities for sage-grouse because their loss may disrupt connectivity among the priority area network.
