A flexible approach for assessing functional landscape connectivity, with application to greater sage-grouse (Centrocercus urophasianus).

Connectivity of animal populations is an increasingly prominent concern in fragmented landscapes, yet existing methodological and conceptual approaches implicitly assume the presence of, or need for, discrete corridors. We tested this assumption by developing a flexible conceptual approach that does not assume, but allows for, the presence of discrete movement corridors. We quantified functional connectivity habitat for greater sage-grouse (Centrocercus urophasianus) across a large landscape in central western North America. We assigned sample locations to a movement state (encamped, traveling and relocating), and used Global Positioning System (GPS) location data and conditional logistic regression to estimate state-specific resource selection functions. Patterns of resource selection during different movement states reflected selection for sagebrush and general avoidance of rough topography and anthropogenic features. Distinct connectivity corridors were not common in the 5,625 km(2) study area. Rather, broad areas functioned as generally high or low quality connectivity habitat. A comprehensive map predicting the quality of connectivity habitat across the study area validated well based on a set of GPS locations from independent greater sage-grouse. The functional relationship between greater sage-grouse and the landscape did not always conform to the idea of a discrete corridor. A more flexible consideration of landscape connectivity may improve the efficacy of management actions by aligning those actions with the spatial patterns by which animals interact with the landscape

Map of study area boundary in central Wyoming, USA.

<p>Map of study area boundary in central Wyoming, USA.</p

Histogram of 24-hr steplengths by greater sage-grouse in central Wyoming, USA, 2008–2010.

<p>Figure was right-truncated for display; longest 24-h steplength was 17,852 m. The movement states encamped, traveling and relocating were assigned to the shortest 25%, middle 50% and longest 25% of 24-hr steplengths, respectively.</p

Resource selection by male greater sage-grouse in relation to topographic roughness during different movement states in Wyoming, USA.

<p>Topographic roughness was calculated as the standard deviation of elevation within an 800% confidence intervals.</p

Difference in the number of observed versus expected independent greater sage-grouse GPS locations central Wyoming, USA.

<p>Fewer observations than expected (negative values) and more observations than expected (positive values) in lower and higher use categories, respectively, indicate the connectivity model performed well at predicting occurrence and resource selection of independent greater sage-grouse. Only locations from traveling and relocating movement states of independent birds were used for validation.</p

Standardized coefficient estimates of selection for topographic roughness and road density by traveling and relocating greater sage-grouse in central Wyoming, USA, 2008–2010.

<p>β_i) = β_i * SD(x_i).^a X-Standardized coefficient calculated as: X-std(</p

Female greater sage-grouse (<i>Centrocercus urophasianus</i>) in central Wyoming, USA, wearing rump-mount GPS unit.

<p>Photo credit T. Dorval.</p

Map of connectivity habitat quality for greater sage-grouse in central Wyoming, USA.

<p>Panel ‘a’ is the entire study area. Panel ‘b’ illustrates a practical application of the map where critical seasonal use layers are overlaid on top of the two highest connectivity habitat quality layers. The nesting <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082271#pone.0082271-Dzialak2" target="_blank">[33]</a> and winter <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082271#pone.0082271-Cooper1" target="_blank">[34]</a> layers are from companion analyses conducted on the same population of sage-grouse during the same time period.</p

Odds ratios of selection for predictor variables during different movement states by greater sage-grouse in central Wyoming, USA, 2008–2010.

<p>^a No. of mesic grid cells w/in 2.01 km window.</p><p>^b Degres.</p><p>^c Std. dev. of elevation (m) w/in 810 m window.</p><p>².^d Total length (km) w/in 1 km</p><p>².^e No. w/in 1 km</p><p>^f Percent sagebrush w/in 810 m window.</p><p>^g Std. dev. of percent sagebrush w/in 810 m window.</p><p>% CI does not overlap 1.0. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082271#pone.0082271.s001" target="_blank">Table S1</a> for detailed results. Bold values indicate estimates where 95</p