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Mol Ecol ; 27(18): 3671-3685, 2018 09.
Article in English | MEDLINE | ID: mdl-30146795

ABSTRACT

Biological diversities of multiple kingdoms potentially respond in similar ways to environmental changes. However, studies either compare details of microbial diversity across general vegetation or land use classes or relate details of plant community diversity with the extent of microbially governed soil processes, via physiological profiling. Here, we test the hypothesis of shared responses of plant and rhizosphere bacterial, fungal and metazoan biodiversities (especially across-habitat ß-diversity patterns) along a disturbance gradient encompassing grazed to abandoned Alpine pasture, on acid soil in the European Central Alps. Rhizosphere biological diversity was inferred from eDNA fractions specific to bacteria, fungi and metazoans from contrasting plant habitats indicative of different disturbance levels. We found that soil ß-diversity patterns were weakly correlated with plant diversity measures and similarly ordinated along an evident edaphic (pH, C:N, assimilable P) and disturbance gradient but, contrary to our hypothesis, did not demonstrate the same diversity patterns. While plant communities were well separated along the disturbance gradient, correlating with fungal diversity, the majority of bacterial taxa were shared between disturbance levels (75% of bacteria were ubiquitous, cf. 29% plant species). Metazoa exhibited an intermediate response, with communities at the lowest levels of disturbance partially overlapping. Thus, plant and soil biological diversities were only loosely dependent and did not exhibit strictly linked environmental responses. This probably reflects the different spatial scales of organisms (and their habitats) and capacity to invest resources in persistent multicellular tissues, suggesting that vegetation responses to environmental change are unreliable indicators of below-ground biodiversity responses.


Subject(s)
Bacteria/classification , Biodiversity , Ecosystem , Fungi/classification , Plants/classification , Computational Biology , Italy , Rhizosphere , Soil Microbiology
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