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Journal Article

Terrestrial ecosystems buffer inputs through storage and recycling of elements


Spohn,  Marie
External Organizations;

Aburto,  Felipe
External Organizations;

Ehlers,  Todd A.
External Organizations;

Farwig,  Nina
External Organizations;


Frings,  P.
3.3 Earth Surface Geochemistry, 3.0 Geochemistry, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Hartmann,  Henrik
External Organizations;

Hoffmann,  Thomas
External Organizations;

Larsen,  Annegret
External Organizations;

Oelmann,  Yvonne
External Organizations;

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Spohn, M., Aburto, F., Ehlers, T. A., Farwig, N., Frings, P., Hartmann, H., Hoffmann, T., Larsen, A., Oelmann, Y. (2021 online): Terrestrial ecosystems buffer inputs through storage and recycling of elements. - Biogeochemistry.

Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5008431
This study presents a conceptual framework of buffering through storage and recycling of elements in terrestrial ecosystems and reviews the current knowledge about storage and recycling of elements in plants and ecosystems. Terrestrial ecosystems, defined here as plant-soil systems, buffer inputs from the atmosphere and bedrock through storage and recycling of elements, i.e., they dampen and delay their responses to inputs. Our framework challenges conventional paradigms of ecosystem resistance derived from plant community dynamics, and instead shows that element pools and fluxes have an overriding effect on the sensitivity of ecosystems to environmental change. While storage pools allow ecosystems to buffer variability in inputs over short to intermediate periods, recycling of elements enables ecosystems to buffer inputs over longer periods. The conceptual framework presented here improves our ability to predict the responses of ecosystems to environmental change. This is urgently needed to define thresholds which must not be exceeded to guarantee ecosystem functioning. This study provides a framework for future research to explore the extent to which ecosystems buffer variability in inputs.