Measuring landscape configuration with normalized metrics

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.