Measuring fragmentation of seagrass landscapes: which indices are most appropriate for detecting change?

J Sleeman, G Kendrick, Guy Boggs, B Hegge

    Research output: Contribution to journalArticlepeer-review


    Many indices are available for assessment of spatial patterns in landscape ecology, yet there is presently no consensus about which ones effectively quantify habitat fragmentation. Research that has been carried out to date has evaluated indices primarily using computer-simulated models of terrestrial environments, but how they perform when applied to real landscapes, particularly in the marine environment, has received little attention. Eleven indices that are commonly used for quantifying habitat fragmentation were assessed for their abilities to measure different levels of fragmentation in 16-ha landscape windows of mapped seagrass. The landscape windows were grouped into five categories, from highly fragmented to continuous seagrass landscapes. Nested within the fragmentation categories were high and low levels of seagrass cover. Hierarchical analysis of variance techniques were used to differentiate between the different fragmentation categories and levels of seagrass cover within the fragmentation categories. Principal component analysis was also employed to determine strong correlations between the indices. The results suggest that (1) landscape division and (2) area-weighted mean perimeter to area ratio were the most appropriate indices for differentiating between independent levels of seagrass fragmentation. The splitting index may also be useful when the detection of small differences in cover is important. � CSIRO 2005.
    Original languageEnglish
    Pages (from-to)851-864
    Number of pages14
    JournalMarine and Freshwater Research
    Issue number6
    Publication statusPublished - 2005


    Dive into the research topics of 'Measuring fragmentation of seagrass landscapes: which indices are most appropriate for detecting change?'. Together they form a unique fingerprint.

    Cite this