Preprints
https://doi.org/10.5194/bg-2020-264
https://doi.org/10.5194/bg-2020-264

  13 Aug 2020

13 Aug 2020

Review status: this preprint was under review for the journal BG but the revision was not accepted.

Importance of succession in estimating biomass loss: Combining remote sensing and individual-based forest models

Ulrike Hiltner1,2,3, Andreas Huth2,4,5, and Rico Fischer2 Ulrike Hiltner et al.
  • 1Institute of Geography, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, 91058, Germany
  • 2Department of Ecological Modelling, Helmholtz-Centre for Environmental Research GmbH − UFZ, 04318 Leipzig, Germany
  • 3Department Environmental System Sciences, ETH Zurich, 8092 Zurich, Switzerland
  • 4German Centre for Integrative Biodiversity Research − iDiv Halle-Jena-Leipzig, Leipzig, 04103 Leipzig, Germany
  • 5Institute for Environmental Systems Research, University Osnabruck, Osnabruck, 49076 Osnabruck, Germany

Abstract. Disturbances can have strong impacts on the dynamics and structure of tropical forests. They often lead to increased tree mortality and affect their behaviour as carbon sinks. In the future, the intensity of disturbances, such as extreme weather events, fires, floods, and biotic agents, will probably even increase, with more serious consequences for tropical forests than we have already observed. However, impacts of altering disturbances on rates of forest biomass loss through tree mortality (hereinafter: biomass mortality) have been little described yet. This complicates progress in quantifying the effects of climate change on forests globally.

This study aims to analyse the consequences of elevated tree mortality on forest dynamics and to provide a methodology that can reduce uncertainties in estimating biomass mortality rates at local and country level. We achieved this by linking benefits of individual-based forest model-ling, statistical linear regression, and remote sensing. We applied an individual-based forest model to investigate the impact of varying disturbance regimes on the succession dynamic of a humid Terra Firma forest at the Paracou study site in French Guiana. By simulating increased tree mortality rates, we were able to investigate their influence on several forest attributes, namely biomass, leaf area index, forest height, gross primary production, net primary production, and biomass mortality. Based on simulations of leaf area index and forest height, we developed a linear multivariate regression model to project biomass mortality.

Our findings demonstrate that severe disturbances altered the succession pattern of the forests in favour of fast-growing species, which changed gross primary production, but net primary production remained stable. We also observed a strong influence on biomass mortality rates as well as observed complex relationships between these rates and single forest attributes (leaf area index, forest height, and biomass). By combining leaf area index and forest height we obtained relationships that allow an estimation of the biomass mortality. Based on these findings, we mapped the biomass mortality for whole French Guiana. We found a nation-wide biomass mortality of 3 % per year (standard deviation = 1.4 % per year).

The approach we describe here, provides a novel methodology for quantifying the spatial-temporal distribution of biomass loss, which has recently been identified as particularly critical for monitoring mortality hot spots. Quantifying biomass mortality rates may help reducing uncertainties in the terrestrial component of the global carbon cycle.

Ulrike Hiltner et al.

 
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Status: closed
Status: closed
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Ulrike Hiltner et al.

Ulrike Hiltner et al.

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Short summary
The aim of our study is to to analyze the consequences of elevated tree mortality on tropical forest dynamics and to provide a methodology that can reduce uncertainties in estimating biomass loss due to tree mortality at local and country levels.
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