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Proceedings of the National Academy of Sciences - PNAS, 2014-09, Vol.111 (38), p.13697-13702
2014
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Details

Autor(en) / Beteiligte
Titel
Linking plant and ecosystem functional biogeography
Ist Teil von
  • Proceedings of the National Academy of Sciences - PNAS, 2014-09, Vol.111 (38), p.13697-13702
Ort / Verlag
United States: National Academy of Sciences
Erscheinungsjahr
2014
Quelle
MEDLINE
Beschreibungen/Notizen
  • Significance This article defines ecosystem functional properties, which can be derived from long-term observations of gas and energy exchange between ecosystems and the atmosphere, and shows that variations of those cannot be easily explained by classical climatological or biogeographical approaches such as plant functional types. Instead, we argue that plant traits have the potential to explain this variation, and we call for a stronger integration of research communities dedicated to plant traits and to ecosystem–atmosphere exchange. Classical biogeographical observations suggest that ecosystems are strongly shaped by climatic constraints in terms of their structure and function. On the other hand, vegetation function feeds back on the climate system via biosphere–atmosphere exchange of matter and energy. Ecosystem-level observations of this exchange reveal very large functional biogeographical variation of climate-relevant ecosystem functional properties related to carbon and water cycles. This variation is explained insufficiently by climate control and a classical plant functional type classification approach. For example, correlations between seasonal carbon-use efficiency and climate or environmental variables remain below 0.6, leaving almost 70% of variance unexplained. We suggest that a substantial part of this unexplained variation of ecosystem functional properties is related to variations in plant and microbial traits. Therefore, to progress with global functional biogeography, we should seek to understand the link between organismic traits and flux-derived ecosystem properties at ecosystem observation sites and the spatial variation of vegetation traits given geoecological covariates. This understanding can be fostered by synergistic use of both data-driven and theory-driven ecological as well as biophysical approaches.

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