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Landscape Ecology

, Volume 26, Issue 5, pp 723–736 | Cite as

Measuring landscape configuration with normalized metrics

  • Xianli Wang
  • Steven G. Cumming
Research Article

Abstract

Natural and anthropogenic disturbances on natural landscapes reduce the abundance and alter the spatial arrangement of certain habitat types. Measuring and modeling such alterations, and their biological effects, remains challenging in part because many widely used configuration metrics are correlated with habitat amount. In this paper, we consider the sources of such correlation, and distinguish process or sample-based correlation from functional correlation that may be an artifact of the metrics themselves. Process correlation is not necessarily a serious problem for statistical inference, but functional correlation would be. We propose that functional correlation may be reduced by normalizing metrics by habitat abundance. We illustrate with normalized versions of total core area, mean nearest neighbor distance, and mean shape index, and show informally that the standard versions of these metrics should exhibit functional correlation. We evaluate the normalized metrics on samples of harvested and undisturbed forested landscapes, and on simulated landscapes generated with varying degrees of spatial autocorrelation. Normalization markedly reduced correlations with habitat abundance on natural landscapes, but not on simulated landscapes. The reasons for this appear to be a combination of differing variances in metric values within levels of habitat abundance, and of the precise form of the relationships between habitat abundance and the un-normalized metrics. In all cases, the normalization changes the ordering of landscapes by metric values across levels of habitat abundance. In consequence, normalized and standard metrics cannot both be accurate measures of configuration. We conclude that statistical modeling of ecological response data is needed to finally determine the merits of the normalizations.

Keywords

Boreal forest Forest harvesting Habitat fragmentation Landscape configuration metrics Landscape dynamics Landscape pattern metrics Mean nearest neighbor distance Mean shape index Normalization Total core area 

Notes

Acknowledgements

This research was conducted to support the regional dynamic modeling initiatives of the Boreal Ecology and Economics Synthesis Team (BEEST), a research group funded by the Sustainable Forest Management Network. We thank BEEST members Grant Hauer, Wictor Adamowicz and Robert Jagodzinski for their support and technical assistance, Dr. Tarmo Remmel from York University for providing landscape simulation software, and Drs. Xinsheng Hu, Petro Bakak, Andreas Hamann, and Dan Mazerolle of the Department of Renewable Resources, University of Alberta, for their valuable suggestions and discussions. We thank the two anonymous reviewers for their thorough review and valuable comments and suggestions, which significantly contributed to improving the quality of this paper.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Department of Renewable ResourcesUniversity of AlbertaEdmontonCanada
  2. 2.Département des sciences du bois et de la forêtUniversité LavalQuebecCanada

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