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Multifractal Spatial Patterns and Diversity in an Ecological Succession
Author(s) -
Leonardo Saravia,
Adonis Giorgi,
Fernando Momo
Publication year - 2012
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0034096
Subject(s) - ecological succession , biomass (ecology) , diversity index , spatial heterogeneity , multifractal system , ecology , biodiversity , abundance (ecology) , spatial ecology , ecosystem , species diversity , environmental science , spatial analysis , spatial variability , homogeneous , biology , geography , statistics , remote sensing , mathematics , fractal , species richness , combinatorics , mathematical analysis
We analyzed the relationship between biodiversity and spatial biomass heterogeneity along an ecological succession developed in the laboratory. Periphyton (attached microalgae) biomass spatial patterns at several successional stages were obtained using digital image analysis and at the same time we estimated the species composition and abundance. We show that the spatial pattern was self-similar and as the community developed in an homogeneous environment the pattern is self-organized. To characterize it we estimated the multifractal spectrum of generalized dimensions D q . Using D q we analyze the existence of cycles of heterogeneity during succession and the use of the information dimension D 1 as an index of successional stage. We did not find cycles but the values of D 1 showed an increasing trend as the succession developed and the biomass was higher. D 1 was also negatively correlated with Shannon's diversity. Several studies have found this relationship in different ecosystems but here we prove that the community self-organizes and generates its own spatial heterogeneity influencing diversity. If this is confirmed with more experimental and theoretical evidence D 1 could be used as an index, easily calculated from remote sensing data, to detect high or low diversity areas.

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