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The imprint of plants on ecosystem functioning: A data-driven approach

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Musavi,  Talie
Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;
IMPRS International Max Planck Research School for Global Biogeochemical Cycles, 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;

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Migliavacca,  Mirco
Biosphere-Atmosphere Interactions and Experimentation, Dr. M. Migliavacca, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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

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

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

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Citation

Musavi, T., Mahecha, M. D., Migliavacca, M., Reichstein, M., van de Weg, M. J., van Bodegom, P. M., et al. (2015). The imprint of plants on ecosystem functioning: A data-driven approach. International Journal of Applied Earth Observation and Geoinformation, 43, 119-131. doi:10.1016/j.jag.2015.05.009.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0027-BA33-5
Abstract
Terrestrial ecosystems strongly determine the exchange of carbon, water and energy between the biosphere and atmosphere. These exchanges are influenced by environmental conditions (e.g., local meteorology, soils), but generally mediated by organisms. Often, mathematical descriptions of these processes are implemented in terrestrial biosphere models. Model implementations of this kind should be evaluated by empirical analyses of relationships between observed patterns of ecosystem functioning, vegetation structure, plant traits, and environmental conditions. However, the question of how to describe the imprint of plants on ecosystem functioning based on observations has not yet been systematically investigated. One approach might be to identify and quantify functional attributes or responsiveness of ecosystems (often very short-term in nature) that contribute to the long-term (i.e., annual but also seasonal or daily) metrics commonly in use. Here we define these patterns as “ecosystem functional properties”, or EFPs. Such as the ecosystem capacity of carbon assimilation or the maximum light use efficiency of an ecosystem. While EFPs should be directly derivable from flux measurements at the ecosystem level, we posit that these inherently include the influence of specific plant traits and their local heterogeneity. We present different options of upscaling in situ measured plant traits to the ecosystem level (ecosystem vegetation properties – EVPs) and provide examples of empirical analyses on plants’ imprint on ecosystem functioning by combining in situ measured plant traits and ecosystem flux measurements. Finally, we discuss how recent advances in remote sensing contribute to this framework.