The imprint of plants on ecosystem functioning

a data-driven approach

Talie Musavi, Miguel D. Mahecha, Mirco Migliavacca, Markus Reichstein, Martine Janet van de Weg, Peter M. van Bodegom, Michael Bahn, Christian Wirth, Peter B. Reich, Franziska Schrodt, Jens Kattge

    Research output: Contribution to journalArticle

    17 Citations (Scopus)

    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.
    Original languageEnglish
    Pages (from-to)119-131
    Number of pages13
    JournalInternational Journal of Applied Earth Observation and Geoinformation
    Volume43
    Early online date2 Jul 2015
    DOIs
    Publication statusPublished - Dec 2015

    Fingerprint

    Ecosystems
    ecosystem
    flux measurement
    biosphere
    environmental conditions
    Fluxes
    light use efficiency
    upscaling
    Meteorology
    carbon
    Carbon
    vegetation structure
    terrestrial ecosystem
    meteorology
    Remote sensing
    remote sensing
    Soils
    atmosphere
    vegetation

    Cite this

    Musavi, T., Mahecha, M. D., Migliavacca, M., Reichstein, M., van de Weg, M. J., van Bodegom, P. M., ... Kattge, J. (2015). The imprint of plants on ecosystem functioning: a data-driven approach. International Journal of Applied Earth Observation and Geoinformation, 43, 119-131. https://doi.org/10.1016/j.jag.2015.05.009
    Musavi, Talie ; Mahecha, Miguel D. ; Migliavacca, Mirco ; Reichstein, Markus ; van de Weg, Martine Janet ; van Bodegom, Peter M. ; Bahn, Michael ; Wirth, Christian ; Reich, Peter B. ; Schrodt, Franziska ; Kattge, Jens. / The imprint of plants on ecosystem functioning : a data-driven approach. In: International Journal of Applied Earth Observation and Geoinformation. 2015 ; Vol. 43. pp. 119-131.
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    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.",
    author = "Talie Musavi and Mahecha, {Miguel D.} and Mirco Migliavacca and Markus Reichstein and {van de Weg}, {Martine Janet} and {van Bodegom}, {Peter M.} and Michael Bahn and Christian Wirth and Reich, {Peter B.} and Franziska Schrodt and Jens Kattge",
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    Musavi, T, Mahecha, MD, Migliavacca, M, Reichstein, M, van de Weg, MJ, van Bodegom, PM, Bahn, M, Wirth, C, Reich, PB, Schrodt, F & Kattge, J 2015, 'The imprint of plants on ecosystem functioning: a data-driven approach', International Journal of Applied Earth Observation and Geoinformation, vol. 43, pp. 119-131. https://doi.org/10.1016/j.jag.2015.05.009

    The imprint of plants on ecosystem functioning : a data-driven approach. / Musavi, Talie; Mahecha, Miguel D.; Migliavacca, Mirco; Reichstein, Markus; van de Weg, Martine Janet; van Bodegom, Peter M.; Bahn, Michael; Wirth, Christian; Reich, Peter B.; Schrodt, Franziska; Kattge, Jens.

    In: International Journal of Applied Earth Observation and Geoinformation, Vol. 43, 12.2015, p. 119-131.

    Research output: Contribution to journalArticle

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    T1 - The imprint of plants on ecosystem functioning

    T2 - a data-driven approach

    AU - Musavi, Talie

    AU - Mahecha, Miguel D.

    AU - Migliavacca, Mirco

    AU - Reichstein, Markus

    AU - van de Weg, Martine Janet

    AU - van Bodegom, Peter M.

    AU - Bahn, Michael

    AU - Wirth, Christian

    AU - Reich, Peter B.

    AU - Schrodt, Franziska

    AU - Kattge, Jens

    PY - 2015/12

    Y1 - 2015/12

    N2 - 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.

    AB - 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.

    U2 - 10.1016/j.jag.2015.05.009

    DO - 10.1016/j.jag.2015.05.009

    M3 - Article

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    SP - 119

    EP - 131

    JO - International Journal of Applied Earth Observation and Geoinformation

    JF - International Journal of Applied Earth Observation and Geoinformation

    SN - 1569-8432

    ER -