This dataset is a predictive model of Wyoming wind energy development potential. The model represents where new wind development is most likely to occur, with lowest development potential represented by values of 0 and highest development potential values represented by 1. The model incorporated wind resource potential, near-term development indicators and current development restrictions. First, we fit a predictive model using maximum entropy methods and Maxent?software version 3.3.3e.The model used existing wind turbines as the response variable. Predictor variables were the average 50-m wind resource potential, percent slope, and topographic position. We used 67% of the data (643 turbines, 32 farms) to train the model and 33% to test the model (319 turbines, 8 farms), including all turbines within individual wind farms as either training or test data. The model performed well, with a test area under the ROC curve (AUC) of 0.91 and omission error of 6%. The Maxent?model represented the quality of wind resources but did not prioritize where development would most likely occur in the near term. Therefore, we adjusted the model using short-term development indicators, including density of existing meteorological towers, distance to proposed transmission lines, proposed wind farm boundaries and land tenure. Finally, we excluded locations where development was precluded due to legal or operational constraints, including protected lands (e.g. wilderness areas, conservation easements), airport runway space, urban areas, mountainous areas above 2743-m, and open water. We applied the Boyce index to measure observed versus expected occurrence for the final, adjusted model, using independent validation data points and binned versions of the models. Results indicated a highly significant model with a Boyce index of 0.89 (p=0.001). Further modeling details are provided in Copeland et al. (In Review).Citation:Copeland, HE, A Pocewicz, DE Naugle, T Griffiths, D Keinath, J Evans, J Platt (In Review). Measuring the effectiveness of conservation: A novel framework to quantify the benefits of sage-grouse conservation policy and easements in Wyoming. PLoS ONE
The model represents the relative potential for new wind energy development at a landscape scale
Copeland, HE, A Pocewicz, DE Naugle, T Griffiths, D Keinath, J Evans, J Platt (In Review). Measuring the effectiveness of conservation: A novel framework to quantify the benefits of sage-grouse conservation policy and easements in Wyoming. PLoS ONE
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This dataset is intended for regional broad-scale analyses and not to predict local-scale impacts or potential. No warranty is expressed or implied in the data. The distributor makes no claims about the suitability of this dataset beyond the published analysis.