Forest Growth and Yield under Environmental Changes

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Ecology and Management".

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 1368

Special Issue Editors


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Guest Editor
College of Forestry, Agriculture and Natural Resources, University of Arkansas at Monticello, Monticello, AR 71656, USA
Interests: forest growth and yield modeling; survival analysis; taper equation modeling; forest biomass and carbon; stand competition; climate impact; treatment impact on growth and yield

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Guest Editor
Department of Natural Resource Ecology and Management, Oklahoma State University, Stillwater, OK 74078, USA
Interests: forest growth modeling; tree taper, volume, weight, and biomass modeling; forest sampling; monte Carlo integration and stereology for estimation of tree and forest attributes

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Guest Editor
School of Natural Resources, University of Tennessee, Knoxville, TN 37996, USA
Interests: tree competition; stand dynamics; forest growth and yield; nonparametric methods; forest carbon; stem taper and bark thickness modeling

Special Issue Information

Dear Colleagues,

This Special Issue aims to publish original research articles focusing on modeling forest growth and yields under changing environments, as well as review articles with a comprehensive overview of the state-of-the-art evaluation of forest growth and yields under climate change. Under a changing environment, methods to accurately quantify tree growth, forest structure, and dynamics are critical when developing appropriate management strategies and silvicultural treatments. Data collected from long-term forest inventory, dendrochronology, or advanced measurement techniques (e.g., remote sensing) are valuable for developing reliable quantitative methods. Studies to be considered for publication should include both quantitative methods and an environmental component that provide guidelines and insights for forest managers and practitioners to select appropriate analytic approaches. Some examples of study topics are given below. Authors who are interested are welcome to discuss with the Editors prior to submission.

  • Comparison of empirical- and process-based modeling techniques in assessing tree growth under climate change;
  • Identifying key environmental variables in characterizing the change in tree allometry (e.g., height–diameter relationships, crown–diameter relationships) using a machine learning approach;
  • Assessing long-term stand dynamics after the insect outbreaks and ice storm events;
  • Modeling biomass and carbon sequestration modeling adjustments following prescribed fires and silvicultural treatments;
  • Quantifying tree mortality impacts of drought, insect pests, or diseases;
  • Evaluating forest growth and structure change under environmental stress using remote sensing (e.g., Lidar, UAV);
  • Assessing wind and ice damage to tree growth and allometry;
  • Monitoring and evaluating changes in forest structure and composition using ground-based Lidar.

Dr. Pradip Saud
Dr. Thomas B. Lynch
Dr. Sheng-I Yang
Guest Editors

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Keywords

  • forest growth and yield
  • growth models
  • height growth
  • mortality
  • biomass and carbon
  • site productivity
  • climate change and drought
  • environment impact
  • soil and fire
  • dendrochronology
  • wind, hurricane or ice storm impacts on growth

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Published Papers (1 paper)

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Research

15 pages, 3396 KiB  
Article
Variations in the Forest Productivity of Pinus patula Plantations in Tanzania: The Need for an Improved Site Classification System
by Joshua Maguzu, Ulrik Ilstedt, Josiah Zephaniah Katani and Salim S. M. Maliondo
Forests 2024, 15(7), 1247; https://doi.org/10.3390/f15071247 - 18 Jul 2024
Viewed by 992
Abstract
The productivity of forests in sub-Saharan Africa is often summarized into large compartments or site classes. However, the classification of forest productivity levels based on the original site index model in Tanzania and the techniques applied to generate the model did not include [...] Read more.
The productivity of forests in sub-Saharan Africa is often summarized into large compartments or site classes. However, the classification of forest productivity levels based on the original site index model in Tanzania and the techniques applied to generate the model did not include the micro-toposequence variations within compartments. This may create false expectations of wood supply and hinder the estimation of sustainable harvesting processes. This study analyzed variations in forest productivity and the site index in P. patula stands in two forest plantations of Tanzania to assess the applicability and generality of the present site classification system. We used dominant height as a proxy for forest productivity in 48 plots at the Sao Hill forest plantation (SHFP) and 24 plots at the Shume forest plantation (SFP). We stratified the sampling plots in each site class along the soil catena and recorded the elevation, slope, and slope positions (summit, mid, and lower). Our results showed that the site classes did not generally match the previously assigned site classes and the productivity of a given site class varied between the two plantations. We found a consistently higher productivity than that implied by the original site index in SFP, while in SHFP, the productivity was both higher and lower than estimated in different compartments. Both elevations and slope significantly contributed to predicting the productivity variations within site classes. Overall, the results indicate that physiographic factors affect variations in forest productivity within the assigned site classes. We recommend a more comprehensive site productivity assessment that takes into account physiographic variations and hence provides more accurate information for sustainable forest plantation management in Tanzania and in the region at large. Full article
(This article belongs to the Special Issue Forest Growth and Yield under Environmental Changes)
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