Articles | Volume 21, issue 14
https://doi.org/10.5194/bg-21-3305-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-21-3305-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Distinguishing mature and immature trees allows estimating forest carbon uptake from stand structure
Dept. of Ecological Modelling, Helmholtz Centre for Environmental Research – UFZ, Permoserstr. 15, 04318 Leipzig, Germany
Institute of Environmental Systems Research, Osnabrück University, Barbarastr. 12, 49076 Osnabrück, Germany
Xugao Wang
Institute of Applied Ecology, Chinese Academy of Sciences, P.O. Box 417, Shenyang, 110016, China
Andreas Huth
Dept. of Ecological Modelling, Helmholtz Centre for Environmental Research – UFZ, Permoserstr. 15, 04318 Leipzig, Germany
Institute of Environmental Systems Research, Osnabrück University, Barbarastr. 12, 49076 Osnabrück, Germany
German Centre for Integrative Biodiversity Research (iDiv) Halle–Jena–Leipzig, Puschstr. 4, 04103 Leipzig, Germany
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Kevin Wolf, Evelyn Jäkel, André Ehrlich, Michael Schäfer, Hannes Feilhauer, Andreas Huth, Alexandra Weigelt, and Manfred Wendisch
Biogeosciences, 22, 2909–2933, https://doi.org/10.5194/bg-22-2909-2025, https://doi.org/10.5194/bg-22-2909-2025, 2025
Short summary
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This paper reports an investigation of the influence of clouds on vegetation albedo using a coupled atmosphere–vegetation radiative transfer model. Both models are iteratively linked to simulate cloud–vegetation–radiation interactions over canopies more realistically. Solar, spectral, and broadband irradiances have been simulated under varying cloud conditions. The simulated irradiances were used to investigate the spectral and broadband effect of clouds on vegetation albedo.
Kevin Wolf, Evelyn Jäkel, André Ehrlich, Michael Schäfer, Hannes Feilhauer, Andreas Huth, and Manfred Wendisch
EGUsphere, https://doi.org/10.5194/egusphere-2025-2082, https://doi.org/10.5194/egusphere-2025-2082, 2025
Short summary
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This paper presents combined atmosphere-vegetation radiative transfer simulations to systematically investigate cloud-induced biases in remotely sensed vegetation indices (VIs) derived from below-cloud measurements. The biases in VIs have been investigated for the general case of two-band VIs, and for the special cases of the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), and the enhanced vegetation index (EVI).
Nikolai Knapp, Sabine Attinger, and Andreas Huth
Biogeosciences, 19, 4929–4944, https://doi.org/10.5194/bg-19-4929-2022, https://doi.org/10.5194/bg-19-4929-2022, 2022
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The biomass of forests is determined by forest growth and mortality. These quantities can be estimated with different methods such as inventories, remote sensing and modeling. These methods are usually being applied at different spatial scales. The scales influence the obtained frequency distributions of biomass, growth and mortality. This study suggests how to transfer between scales, when using forest models of different complexity for a tropical forest.
Ulrike Hiltner, Andreas Huth, and Rico Fischer
Biogeosciences, 19, 1891–1911, https://doi.org/10.5194/bg-19-1891-2022, https://doi.org/10.5194/bg-19-1891-2022, 2022
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Short summary
Quantifying biomass loss rates due to stem mortality is important for estimating the role of tropical forests in the global carbon cycle. We analyse the consequences of long-term elevated stem mortality for tropical forest dynamics and biomass loss. Based on simulations, we developed a statistical model to estimate biomass loss rates of forests in different successional states from forest attributes. Assuming a doubling of tree mortality, biomass loss increased from 3.2 % yr-1 to 4.5 % yr-1.
J. Pacheco-Labrador, U. Weber, X. Ma, M. D. Mahecha, N. Carvalhais, C. Wirth, A. Huth, F. J. Bohn, G. Kraemer, U. Heiden, FunDivEUROPE members, and M. Migliavacca
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-1-W1-2021, 49–55, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-49-2022, https://doi.org/10.5194/isprs-archives-XLVI-1-W1-2021-49-2022, 2022
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Short summary
Understanding the drivers of forest productivity is key for accurately assessing forests’ role in the global carbon cycle. Yet, despite significant research effort, it is not fully understood how the productivity of a forest can be deduced from its stand structure. We suggest tackling this problem by identifying the share and structure of immature trees within forests and show that this approach could significantly improve estimates of forests’ net productivity and carbon uptake.
Understanding the drivers of forest productivity is key for accurately assessing forests’ role...
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