Abstract
Increasingly, natural resources agencies and organizations are using measures of ecological integrity to monitor and evaluate the status and condition of their landscapes, and numerous methods have been developed to map the pattern of human activities. In this paper I apply formal methods from decision theory to develop a transparent ecological indicator of landscape integrity. I developed a parsimonious set of stressors using an existing framework to minimize redundancy and overlap, mapping each variable as an individual data layer with values from 0 to 1.0, and then combined them using an “increasive” function called fuzzy sum. A novel detailed land use dataset is used to generate empirical measures of the degree of human modification to map important stressors such as land use, land cover, and presence, use, and distance from roads. I applied this general framework to the US and found that the overall average degree of human modification was 0.375. Regional variation was fairly predictable, but aggregation of these raw values into terrestrial or watershed units resulted in large differences at local to regional scales. I discuss three uses of these data by land managers to manage protected areas within a dynamic landscape context. This approach generates an internally-valid model that has a direct, empirical, and physical basis to estimate the degree of human modification.
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Acknowledgments
Thanks to the Western Governor’s Association Landscape Integrity working group members for discussions that helped to shape this work, particularly J. Pierce, R. Baldwin, P. Comer, B. Dickson, K. McKelvey, B. McRae, and S. Reed. I also appreciate comments by two peer-reviewers, earlier reviews by W. Monahan and L. Zachmann, and the interpretation and data collection efforts by I. Leinwand, D. Mueller, P. Holsinger, T. Andres, and L. Halvorson. This work was supported by a NASA Decision Support award through the Earth Science Research Results Program.
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Theobald, D.M. A general model to quantify ecological integrity for landscape assessments and US application. Landscape Ecol 28, 1859–1874 (2013). https://doi.org/10.1007/s10980-013-9941-6
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DOI: https://doi.org/10.1007/s10980-013-9941-6