Preprints
https://doi.org/10.5194/bg-2022-24
https://doi.org/10.5194/bg-2022-24
 
22 Feb 2022
22 Feb 2022
Status: this preprint is currently under review for the journal BG.

A question of scale: modelling biomass, gain and mortality distributions of a tropical forest

Nikolai Knapp1,3, Sabine Attinger2,4, and Andreas Huth1,5,6 Nikolai Knapp et al.
  • 1Department of Ecological Modelling, Helmholtz Centre for Environmental Research – UFZ, Leipzig, 04318, Germany
  • 2Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research – UFZ, Leipzig, 04318, Germany
  • 3Thünen Institute of Forest Ecosystems, Eberswalde, 16225, Germany
  • 4Institute of Environmental Sciences and Geography, University of Potsdam, Potsdam, 14476, Germany
  • 5German Centre for Integrative Biodiversity Research (idiv), Halle-Jena-Leipzig, 04103, Germany
  • 6Institute of Environmental Systems Research, University of Osnabrück, Osnabrück, 49076, Germany

Abstract. The quantification of forest carbon budgets is important for understanding the role of forests in the global climate system. Given the variety of different methodologies (inventories, remote sensing, modelling) and spatial resolutions involved, methods for consistent transfer between scales are needed. In this study, the scaling of variables, which drive the carbon budget, was investigated for a tropical forest in Panama.

Based on field inventory data from Barro Colorado Island, spanning 50 ha over 30 years, the distributions of aboveground biomass, biomass gain and mortality were derived at different spatial resolutions, ranging from 10 to 100 m. Methods for fitting parametric distribution functions were compared. Further, it was tested under which assumptions about the distributions a simple stochastic simulation forest model could best reproduce observed biomass distributions at all scales. Also, an analytical forest model for calculating biomass distributions at equilibrium and assuming mortality as a white shot noise process is presented.

Scaling exponents of about −0.47 were found for the standard deviations of the biomass and gain distributions, while mortality showed a different scaling relationship with an exponent of −0.3. Lognormal and gamma distribution functions fitted with the moments matching estimation method allowed for consistent parameter transfers between scales. Both forest models (stochastic simulation and analytical solution) were able to reproduce observed biomass distributions across scales, when combined with the derived scaling relationships.

The study provides insights about transferring between scales and its effect on frequency distributions of forest attributes, which is particularly important for the increasing efforts to combine information from sources such as inventories, remote sensing and modelling.

Nikolai Knapp et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2022-24', Anonymous Referee #1, 04 Mar 2022
    • AC1: 'Reply on RC1', Nikolai Knapp, 27 Apr 2022
  • RC2: 'Comment on bg-2022-24', Anonymous Referee #2, 16 Mar 2022
    • AC2: 'Reply on RC2', Nikolai Knapp, 27 Apr 2022

Nikolai Knapp et al.

Nikolai Knapp et al.

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Short summary
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 modelling. 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.
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