Biocrust morphogroups provide an effective and rapid assessment tool for drylands.

Published online
14 Jan 2015
Content type
Journal article
Journal title
Journal of Applied Ecology
DOI
10.1111/1365-2664.12336

Author(s)
Read, C. F. & Duncan, D. H. & Vesk, P. A. & Elith, J.
Contact email(s)
cassiaread@gmail.com

Publication language
English
Location
Australia

Abstract

Biological soil crusts (biocrusts) occur across most of the world's drylands and are sensitive indicators of dryland degradation. Accounting for shifts in biocrust composition is important for quantifying integrity of arid and semi-arid ecosystems, but the best methods for assessing biocrusts are uncertain. We investigate the utility of surveying biocrust morphogroups, a reduced set of biotic classes, compared to species data, for detecting shifts in biocrust composition and making inference about dryland degradation. We used multivariate regression tree (MRT) analyses to model morphogroup abundance, species abundance and species occurrence data from two independent studies in semi-arid open woodlands of south-eastern Australia. We advanced the MRT method with a 'best subsets' model selection procedure, which improved model stability and prediction. Biocrust morphogroup composition responded strongly to surrogate variables of ecological degradation. Further, MRT models of morphogroup data had stronger explanatory power and predictive power than MRT models of species abundance or occurrence data. We also identified morphogroup indicators of degraded and less degraded sites in our study region. Synthesis and applications. Sustainable management of drylands requires methods to assess shifts in ecological integrity. We suggest that biocrust morphogroups are highly suitable for assessment of dryland integrity because they allow for non-expert, rapid survey and are informative about ecological function. Furthermore, morphogroups were more robust than biocrust species data, showed a strong response to ecological degradation and were less influenced by environmental variation, and models of morphogroup abundance were more predictive.

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