The behavior of landscape metrics commonly used in the study of habitat fragmentation
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A meaningful interpretation of landscape metrics is possible only when the limitations of each measure are fully understood, the range of attainable values is known, and the user is aware of potential shifts in the range of values due to characteristics of landscape patches. To examine the behavior of landscape metrics, we generated artificial landscapes that mimicked fragmentation processes while controlling the size and shape of patches in the landscape and the mode of disturbance growth. We developed nine series of increasingly fragmented landscapes and used these to investigate the behavior of edge density, contagion, mean nearest neighbor distance, mean proximity index, perimeter-area fractal dimension, and mass fractal dimension. We found that most of the measures were highly correlated, especially contagion and edge density, which had a near-perfect inverse correspondence. Many of the measures were linearly-associated with increasing disturbance until the proportion of disturbance on the landscape was approximately 0.40, with non-linear associations at higher proportions. None of the measures was able to differentiate between landscape patterns characterized by dispersed versus aggregated patches. The highest attainable value of each measure was altered by either patch size or shape, and in some cases, by both attributes. We summarize our findings by discussing the utility of each metric.
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- The behavior of landscape metrics commonly used in the study of habitat fragmentation
Volume 13, Issue 3 , pp 167-186
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- Kluwer Academic Publishers
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- landscape ecology
- landscape measures
- mean proximity index
- perimeter-area fractal dimension
- mass fractal dimension
- Industry Sectors
- Author Affiliations
- 1. Utah Cooperative Fish and Wildlife Research Unit, U.S. Geological Survey Biological Resources Division, College of Natural Resources, Utah State University, Logan, UT, 84322–5290, USA
- 2. Foundation for Ecological Restoration, Monitoring, and Assessment, 3213 Montreal N.E., Albuquerque, NM, 87111, USA