Improving Inferences About Private Land Conservation by Accounting for Incomplete Reporting.

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Conservation Biology : the Journal of the Society for Conservation Biology

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Despite the vital role of private lands as habitat for imperiled species and as important components of functioning protected area networks, incorporation of private lands into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid costly conflict and clarify trade-offs between ecological benefits and socio-political costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete which complicates these assessments. We use a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We illustrate the utility of the occupancy framework for modeling conservation on private land using a simulation study with a case study of easement data in Idaho and Montana (United States). We compared multiple formulations of occupancy models to a logistic regression model to predict the locations of conservation easements using a Spatially Explicit Social Ecological System framework. We found that occupancy models that explicitly account for variation in reporting produced substantially less biased estimates of predictors than logistic regression. Our results demonstrate that occupancy models produced substantially less biased estimates of the predictors of conservation than logistic regression. Results from our case study suggest that occupancy models also resulted in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression. These results highlight the importance of integrating variable and incomplete reporting of participation into empirical analysis of conservation initiatives through an occupancy approach. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting. Article impact statement: Occupancy models improve identification of private land conservation opportunities even with incompletely reported data. This article is protected by copyright. All rights reserved.


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