Modelling Growth of Mixed and Structured Forests

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Modeling and Remote Sensing".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 2369

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Institute of Meteorology and Climate Research (IMK-IFU), Karlsruhe Institute of Technology (KIT) Kreuzeckbahnstr, 19, 82467 Garmisch-Partenkirchen, Germany
Interests: modeling biosphere–atmosphere exchange; forest development under stress; drought impacts on trees
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Special Issue Information

Dear Colleagues,

The impacts of changed climatic conditions on tree growth and forest development are already evident worldwide and demand for tools and methods suitable for predicting and analyzing such impacts as well as designing effective management strategies. Responses of forest systems, however, strongly depend on system properties such as tree size distribution and species composition that affect light and temperature distribution as well as water demand and supply. Such structural forest properties thus define resistance and resilience properties at the stand level.

For long-term estimates, it is essential to acknowledge that forest structure is not constant but develops in time dependent on the environment and is also affected by disturbances and management. Examples for such dynamic developments encompass tree allometry which depends on stand density and tree size, the competition of ground vegetation, or the distribution of primary production and carbon allocation as functions of relative tree size or position. The latter is also important to define the success of regeneration, which might be facilitated or suppressed by larger trees depending on species.

However, it might be said with some confidence that current approaches to address changes in forest structure dynamically and in response to the environment are not well developed. While lumped models usually lack the ability to address structural changes, cohort- and single tree models are struggling with the representation of small-scale environmental conditions which are computational expensive and difficult to evaluate. While some new and exciting developments have been presented recently, experiments and measurement results are still urgently needed to enable scaling from leave to stand and vice versa, both to quantify relationships and feedback responses as well as to provide evaluation data.

In this Special Issue, we thus particularly invite modeling approaches for structured and/or mixed forests, including descriptions of lagged effects, disturbance and management effects, and recovery and regeneration (including ground vegetation) development. In addition, this issue is open for the submission of experimental studies and monitoring approaches that highlight the distribution of environmental conditions and physiological and growth responses dependent on forest structure.

Dr. Rüdiger Grote
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Mixed forests
  • Forest structure
  • Social tree classes
  • Lagged effects
  • Competition
  • Facilitation
  • Carbon sequestration
  • Regeneration
  • Ground vegetation
  • Disturbances
  • Forest management

Published Papers (1 paper)

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Research

26 pages, 4845 KiB  
Article
Analysis of Longitudinal Forest Data on Individual-Tree and Whole-Stand Attributes Using a Stochastic Differential Equation Model
by Petras Rupšys and Edmundas Petrauskas
Forests 2022, 13(3), 425; https://doi.org/10.3390/f13030425 - 08 Mar 2022
Cited by 5 | Viewed by 1913
Abstract
This paper focuses on individual-tree and whole-stand growth models for uneven-aged and mixed-species stands in Lithuania. All the growth models were derived using a single trivariate diffusion process defined by a mixed-effect parameters trivariate stochastic differential equation describing the tree diameter, potentially available [...] Read more.
This paper focuses on individual-tree and whole-stand growth models for uneven-aged and mixed-species stands in Lithuania. All the growth models were derived using a single trivariate diffusion process defined by a mixed-effect parameters trivariate stochastic differential equation describing the tree diameter, potentially available area, and height. The mixed-effect parameters of the newly developed trivariate transition probability density function were estimated using an approximate maximum likelihood procedure. Using the relationship between the multivariate probability density and univariate marginal (conditional) densities, the growth equations were derived to predict or forecast the individual-tree and whole-stand variables, such as diameter, potentially available area, height, basal area, and stand density. All the results are illustrated using an observed dataset from 53 permanent experimental plots remeasured from 1 to 7 times. The computed statistical measures showed high predictive and forecast accuracy compared with validation data that were not used to find parameter estimates. All the results were implemented in the Maple computer algebra system. Full article
(This article belongs to the Special Issue Modelling Growth of Mixed and Structured Forests)
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