Mapping and Modeling the Future of O&G Development in Relation to the Conservation of GR Sage Grouse
Summary
The effects of oil and gas development on the conservation of greater sage grouse (Centrocercus urophasianus) concerns wildlife managers. Effects of development are difficult to ascertain, a situation typical where cause-effect relationships are complex, multivariate, and involve landscape perspectives. Understanding the potential effects of development on grouse requires predicting where development is expected to occur on a landscape level. We gathered “reasonable foreseeable development” spatial data from the USDI’s Bureau of Land Management that were available for Montana, North Dakota, South Dakota, Wyoming, and Northwestern Colorado. These data were disparate across the study area, and we standardized them across mapping units [...]
Summary
The effects of oil and gas development on the conservation of greater sage grouse (Centrocercus urophasianus) concerns wildlife managers. Effects of development are difficult to ascertain, a situation typical where cause-effect relationships are complex, multivariate, and involve landscape perspectives. Understanding the potential effects of development on grouse requires predicting where development is expected to occur on a landscape level. We gathered “reasonable foreseeable development” spatial data from the USDI’s Bureau of Land Management that were available for Montana, North Dakota, South Dakota, Wyoming, and Northwestern Colorado. These data were disparate across the study area, and we standardized them across mapping units to establish consistent and quantitative categories. We describe the GIS processes used to accomplish that and to display the number of wells per township as projected in the BLM data. The data were then overlain with the priority areas for conservation for greater sage grouse. Our data, metadata, and data processing (standardization) documentation are available via the Landscape Conservation Management and Analysis Portal. Using Bayesian belief network methods, we are modelling the relative spatial risk to greater sage grouse from oil and gas development based on the published literature. Risk analyses from site specific studies were linked to a conceptual model of the annual life cycle events of grouse. Using the density of the predicted number ofwells, we present a regional-scale view of where the effects of development are expected to occur. The constraints to representing this in a spatial model using GIS are delineated.
