Identifying Greater Sage‐Grouse source and sink habitats for conservation planning in an energy development landscape

Abstract

Conserving a declining species that is facing many threats, including overlap of its habitats with energy extraction activities, depends upon identifying and prioritizing the value of the habitats that remain. In addition, habitat quality is often compromised when source habitats are lost or fragmented due to anthropogenic development. Our objective was to build an ecological model to classify and map habitat quality in terms of source or sink dynamics for Greater Sage-Grouse (Centrocercus urophasianus) in the Atlantic Rim Project Area (ARPA), a developing coalbed natural gas field in south-central Wyoming, USA. We used occurrence and survival modeling to evaluate relationships between environmental and anthropogenic variables at multiple spatial scales and for all female summer life stages, including nesting, brood-rearing, and non-brooding females. For each life stage, we created resource selection functions (RSFs). We weighted the RSFs and combined them to form a female summer occurrence map. We modeled survival also as a function of spatial variables for nest, brood, and adult female summer survival. Our survival-models were mapped as survival probability functions individually and then combined with fixed vital rates in a fitness metric model that, when mapped, predicted habitat productivity (productivity map). Our results demonstrate a suite of environmental and anthropogenic variables at multiple scales that were predictive of occurrence and survival. We created a source-sink map by overlaying our female summer occurrence map and productivity map to predict habitats contributing to population surpluses (source habitats) or deficits (sink habitat) and low-occurrence habitats on the landscape. The source-sink map predicted that of the Sage-Grouse habitat within the ARPA, 30% was primary source, 29% was secondary source, 4% was primary sink, 6% was secondary sink, and 31% was low occurrence. Our results provide evidence that energy development and avoidance of energy infrastructure were probably reducing the amount of source habitat within the ARPA landscape. Our source-sink map provides managers with a means of prioritizing habitats for conservation planning based on source and sink dynamics. The spatial identification of high value (i.e., primary source) as well as suboptimal (i.e., primary sink) habitats allows for informed energy development to minimize effects on local wildlife populations.

Mitigation effectiveness for improving nesting success of greater sage‐grouse influenced by energy development

“…This finding contrasts with studies in which nests closer to energy wells were more likely to fail (Dzialak et al 2011, Webb et al. 2012), but corroborated by others that did not detect a direct association between energy wells and nest survival (Aldridge and Boyce 2007, Dinkins 2013, Kirol et al in press). Predation is a regular factor affecting sage-grouse nesting success and anthropogenic changes to the environment can affect predation (Hagen 2011).…”

“…Relationships between environmental characteristics (i.e., vegetation and terrain features) and sage-grouse nest survival have been well documented in previous research (Holloran 2005, Aldridge and Boyce 2007, Dzialak et al 2011, Webb et al 2012, Kirol et al. in press).…”

“…Reducing impacts of NG wells was a mitigation target because research has demonstrated that energy wells can have negative effects on nest productivity (Dzialak et al 2011, Webb et al 2012, Kirol et al in press). We obtained data about active, plugged, and abandoned wells from the Wyoming Oil and Gas Conservation Commission that included location, status date, and spud date (initiation of drilling) updated to December 2011 (Table 1).…”

A Bayesian method for assessing multi-scale species-habitat relationships

“…Coefficient effect size-based model selection was performed by estimating models containing all predictors separately by scale (i.e., each model contained all predictors measured at the same single scale) and selecting the scale with the strongest estimated coefficient for each predictor individually (e.g., Jorgensen et al 2014). Information criterionbased model selection was performed by calculating AIC and WAIC for independent predictor by scale models (i.e., each model contained only 1 predictor measured at 1 scale for 12 total models) and selecting the scale model with the lowest AIC (Akaike and Hirotogu 1998) or WAIC (Watanabe 2013;Gelman et al 2014) for each predictor (e.g., Kirol et al 2015).…”

Identifying critical habitat for threatened species: concepts and challenges

“…Unsuitable sites may therefore need to be made suitable, for instance, through habitat creation or restoration, to provide additional habitat to support desired increases in population sizes. In particular, unsuitable occupied sites may be a priority for restoration as these sites can act as population sinks (Pulliam 1988), as in the use of suboptimal habitat by female greater sage-grouse (Centrocercus urophasianus) in Wyoming (Kirol et al 2015), and may be indicative of recent habitat change that can result in an extinction debt unless managed or restored. The persistence of species that thrive in dynamic habitats, such as the Ord's kangaroo rat (Dipodomys ordii) found on actively eroding sand dunes in Canada , or species that are affected by climate change, such as the Quino checkerspot butterfly (Euphydryas editha) (Parmesan et al 2015), may also depend on management or protection of sites that currently appear to be unsuitable or of low quality, but may provide good habitat in the future as environmental conditions change and ecological communities shift (Dawson et al 2011;McDonald-Madden et al 2011).…”