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Linking plant and ecosystem functional biogeography

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Reichstein,  Markus
Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Mahecha,  Miguel D.
Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

/persons/resource/persons62433

Kattge,  Jens
Interdepartmental Max Planck Fellow Group Functional Biogeography, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Reichstein, M., Bahn, M., Mahecha, M. D., Kattge, J., & Baldocchi, D. D. (2014). Linking plant and ecosystem functional biogeography. Proceedings of the National Academy of Sciences of the United States of America, 111(38), 13697-13702. doi:10.1073/pnas.1216065111.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0023-D0D1-3
Abstract
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.