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Termites promote resistance of decomposition to spatiotemporal variability in rainfall
Author(s) -
Veldhuis Michiel P.,
Laso Francisco J.,
Olff Han,
Berg Matty P.
Publication year - 2017
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1002/ecy.1658
Subject(s) - abiotic component , ecosystem , resistance (ecology) , ecology , decomposition , environmental science , soil biology , biology , soil water
The ecological impact of rapid environmental change will depend on the resistance of key ecosystems processes, which may be promoted by species that exert strong control over local environmental conditions. Recent theoretical work suggests that macrodetritivores increase the resistance of African savanna ecosystems to changing climatic conditions, but experimental evidence is lacking. We examined the effect of large fungus‐growing termites and other non‐fungus‐growing macrodetritivores on decomposition rates empirically with strong spatiotemporal variability in rainfall and temperature. Non‐fungus‐growing larger macrodetritivores (earthworms, woodlice, millipedes) promoted decomposition rates relative to microbes and small soil fauna (+34%) but both groups reduced their activities with decreasing rainfall. However, fungus‐growing termites increased decomposition rates strongest (+123%) under the most water‐limited conditions, making overall decomposition rates mostly independent from rainfall. We conclude that fungus‐growing termites are of special importance in decoupling decomposition rates from spatiotemporal variability in rainfall due to the buffered environment they create within their extended phenotype (mounds), that allows decomposition to continue when abiotic conditions outside are less favorable. This points at a wider class of possibly important ecological processes, where soil‐plant‐animal interactions decouple ecosystem processes from large‐scale climatic gradients. This may strongly alter predictions from current climate change models.

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