Remote Sensing‐Based Forest Modeling Reveals Positive Effects of Functional Diversity on Productivity at Local Spatial Scale

Schneider, Fabian D.; Longo, Marcos; Paul‐Limoges, Eugénie; Scholl, Victoria M.; Schmid, Bernhard; Morsdorf, Felix; Pavlick, Ryan P.; Schimel, David S.; Schaepman, Michael E.; Moorcroft, Paul R.

doi:10.1029/2023jg007421

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The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.

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Remote Sensing‐Based Forest Modeling Reveals Positive Effects of Functional Diversity on Productivity at Local Spatial Scale

2023
By Schneider, Fabian D. ; Longo, Marcos ; Paul‐Limoges, Eugénie ; ...
Source: Journal of Geophysical Research: Biogeosciences, 128(6)

[PDF-3.73 MB]

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Journal Title:

Journal of Geophysical Research: Biogeosciences
Personal Author:

Schneider, Fabian D. ; Longo, Marcos ; Paul‐Limoges, Eugénie ; Scholl, Victoria M. ; Schmid, Bernhard ; ... More +

Schneider, Fabian D. ; Longo, Marcos ; Paul‐Limoges, Eugénie ; Scholl, Victoria M. ; Schmid, Bernhard ; Morsdorf, Felix ; Pavlick, Ryan P. ; Schimel, David S. ; Schaepman, Michael E. ; Moorcroft, Paul R. Less -
NOAA Program & Office:

CIRES (Cooperative Institute for Research in Environmental Sciences)
Description:

Forest biodiversity is critical for many ecosystem functions and services. Yet, it remains uncertain how plant functional diversity influences ecosystem functioning across environmental gradients and contiguous larger areas. We integrated remote sensing and terrestrial biosphere modeling to explore functional diversity– productivity relationships at multiple spatial scales for a heterogeneous forest ecosystem in Switzerland. We initialized forest structure and composition in the ecosystem demography model (ED2) through a combination of ground-based surveys, airborne laser scanning and imaging spectroscopy for forest patches at 10 × 10-m spatial grain. We derived morphological and physiological forest traits and productivity from model simulations
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Aquatic Science Atmospheric Science Ecology Forestry Paleontology Soil Science Water Science And Technology
Source:

Journal of Geophysical Research: Biogeosciences, 128(6)
DOI:

https://doi.org/10.1029/2023jg007421
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2169-8953;2169-8961;
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PDF
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American Geophysical Union (AGU)
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Journal Article
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https://creativecommons.org/licenses/by-nc/4.0/
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CC BY-NC
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urn:sha256:4ff5ac1686f69a716e48534742660db24ec6ba0b4fb01d47742cbbf4adee9a02
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