Abstract

BackgroundSpatial scale is important when studying ecological processes. The Greater sage-grouse (Centrocercus urophasianus) is a large sexually dimorphic tetraonid that is endemic to the sagebrush biome of western North America. The impacts of oil and gas (OAG) development at individual leks has been well-documented. However, no previous studies have quantified the population-level response.MethodsHierarchical models were used to estimate the effects of the areal disturbance due to well pads as well as climatic variation on individual lek counts and Greater sage-grouse populations (management units) over 32 years. The lek counts were analyzed using generalized linear mixed models while the management units were analyzed using Gompertz population dynamic models. The models were fitted using frequentist and Bayesian methods. An information-theoretic approach was used to identify the most important spatial scale and time lags. The relative importance of OAG and climate at the local and population-level scales was assessed using information-theoretic (Akaike’s weights) and estimation (effect size) statistics.ResultsAt the local scale, OAG was an important negative predictor of the lek count. At the population scale, there was only weak support for OAG as a predictor of density changes but the estimated impacts on the long-term carrying capacity were consistent with summation of the local impacts. Regional climatic variation, as indexed by the Pacific Decadal Oscillation, was an important positive predictor of density changes at both the local and population level (particularly in the most recent part of the time series).ConclusionsAdditional studies to reduce the uncertainty in the range of possible effects of OAG at the population scale are required. Wildlife agencies need to account for the effects of regional climatic variation when managing sage-grouse populations.

Highlights

  • If we study a system at an inappropriate scale, we may not detect its actual dynamics and patterns but may instead identify patterns that are artifacts of scale

  • Local models The Akaike weights for the spatial scales indicate that 3.2 km is unanimously supported as the most important lek distance for predicting individual lek counts from the areal disturbance due to well pads (Table S1)

  • The situation with the Pacific Decadal Oscillation (PDO) index lags was less clear-cut (Table 2), a lag of 2 years received the majority of the support

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Summary

Introduction

If we study a system at an inappropriate scale, we may not detect its actual dynamics and patterns but may instead identify patterns that are artifacts of scale. Methods: Hierarchical models were used to estimate the effects of the areal disturbance due to well pads as well as climatic variation on individual lek counts and Greater sage-grouse populations (management units) over 32 years. The relative importance of OAG and climate at the local and population-level scales was assessed using information-theoretic (Akaike’s weights) and estimation (effect size) statistics. Results: At the local scale, OAG was an important negative predictor of the lek count. There was only weak support for OAG as a predictor of density changes but the estimated impacts on the long-term carrying capacity were consistent with summation of the local impacts. As indexed by the Pacific Decadal Oscillation, was an important positive predictor of density changes at both the local and population level ( in the most recent part of the time series). Wildlife agencies need to account for the effects of regional climatic variation when managing sage-grouse populations

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