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Forests
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Quantitative Forest Management to Build Adaptive Capacity against Climate Change...
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Quantitative Forest Management to Build Adaptive Capacity against Climate Change and Forest Disturbances

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 (25 April 2019)

Special Issue Editor

Dr. Steve Chhin

E-Mail Website
Guest Editor
Division of Forestry and Natural Resources, West Virginia University, 322 Percival Hall, 1145 Evansdale Dr, Morgantown, WV 26506, USA
Interests: quantitative forest management; climate change; forest health; dendrochronology; silviculture
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The productivity and health of forest ecosystems in the 21st century will be threatened by the direct effects of climate change, primarily through the effects of elevated temperatures and increases in water stress. Furthermore, climate change is also expected to increase the incidences and severity of disturbance agents such as fire, insect pests, and fungal pathogens, which in turn can reduce tree productivity and increase tree mortality in forests. Climate change is expected to lead to milder winter temperatures and thus lead to increased overwintering survival and expansion of the habitat range of many insect pests and fungal diseases. It is unclear whether different tree populations will be able to cope with environmental change, and there is growing concern that the unprecedented rate of climate change will very likely exceed the ecological, adaptive capacity of many tree species. It is essential to address these environmental challenges in a proactive manner by identifying effective forest management practices that have the capacity to promote resiliency to environmental change. Effective adaptation to climate change and pressing forest health disturbances also requires effective methods of long-term monitoring and early detection of these concerns. This Special Issue welcomes studies that utilize quantitative monitoring and modelling approaches to examine how forest management practices can help build adaptive capacity against the interactive impacts of climate change and forest disturbances.

Dr. Sophan Chhin
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • climate change
  • forest disturbances
  • forest health
  • forest management
  • modelling
  • monitoring
  • quantitative methods
  • silviculture

Published Papers (2 papers)

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Research

20 pages, 3249 KiB  
Article
Climate Effect on Ponderosa Pine Radial Growth Varies with Tree Density and Shrub Removal
by Kaelyn Finley and Jianwei Zhang
Forests 2019, 10(6), 477; https://doi.org/10.3390/f10060477 - 31 May 2019
Cited by 11 | Viewed by 3164
Abstract
With increasing temperatures and projected changes in moisture availability for the Mediterranean climate of northern California, empirical evidence of the long-term responses of forests to climate are important for managing these ecosystems. We can assess forest treatment strategies to improve climate resilience by [...] Read more.
With increasing temperatures and projected changes in moisture availability for the Mediterranean climate of northern California, empirical evidence of the long-term responses of forests to climate are important for managing these ecosystems. We can assess forest treatment strategies to improve climate resilience by examining past responses to climate for both managed and unmanaged plantations. Using an experimental, long-term density and shrub removal study of ponderosa pine (Pinus ponderosa Lawson & C. Lawson) on a poor-quality site with low water-holding capacity and high runoff of the North Coastal mountain range in California, we examined the relationships between radial growth and climate for these trees over a common interval of 1977–2011. Resistance indices, defined here as the ratio between current year radial growth and the performance of the four previous years, were correlated to climatic variables during the same years. We found that all treatments’ radial growth benefited from seasonal spring moisture availability during the current growing year. Conversely, high spring and early summer temperatures had detrimental effects on growth. High-density treatments with manzanita understories were sensitive to summer droughts while lower densities and treatments with full shrub removal were not. The explanatory power of the climate regression models was generally more consistent for the same shrub treatments across the four different densities. The resistance indices for the lower density and complete shrub removal treatment groups were less dependent on previous years’ climatic conditions. We conclude that, for ponderosa pine plantations with significant manzanita encroachment, understory removal and heavy thinning treatments increase subsequent growth for remaining trees and decrease sensitivity to climate. Full article
(This article belongs to the Special Issue Quantitative Forest Management to Build Adaptive Capacity against Climate Change and Forest Disturbances)
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17 pages, 6608 KiB  
Article
Recent Deforestation Pattern Changes (2000–2017) in the Central Carpathians: A Gray-Level Co-Occurrence Matrix and Fractal Analysis Approach
by Ana-Maria Ciobotaru, Ion Andronache, Helmut Ahammer, Herbert F. Jelinek, Marko Radulovic, Radu-Daniel Pintilii, Daniel Peptenatu, Cristian-Constantin Drăghici, Adrian-Gabriel Simion, Răzvan-Mihail Papuc, Marian Marin, Roxana-Andreea Radu, Alexandra Grecu, Andreea Karina Gruia, Ioan-Vlad Loghin and Rasmus Fensholt
Forests 2019, 10(4), 308; https://doi.org/10.3390/f10040308 - 03 Apr 2019
Cited by 11 | Viewed by 4547
Abstract
The paper explores the distribution of tree cover and deforested areas in the Central Carpathians in the central-east part of Romania, in the context of the anthropogenic forest disturbances and sustainable forest management. The study aims to evaluate the spatiotemporal changes in deforested [...] Read more.
The paper explores the distribution of tree cover and deforested areas in the Central Carpathians in the central-east part of Romania, in the context of the anthropogenic forest disturbances and sustainable forest management. The study aims to evaluate the spatiotemporal changes in deforested areas due to human pressure in the Carpathian Mountains, a sensitive biodiverse European ecosystem. We used an analysis of satellite imagery with Landsat-7 Enhanced Thematic Mapper Plus (Landsat-7 ETM+) from the University of Maryland (UMD) Global Forest Change (GFC) dataset. The workflow started with the determination of tree cover and deforested areas from 2000–2017, with an overall accuracy of 97%. For the monitoring of forest dynamics, a Gray-Level Co-occurrence Matrix analysis (Entropy) and fractal analysis (Fractal Fragmentation-Compaction Index and Tug-of-War Lacunarity) were utilized. The increased fragmentation of tree cover (annually 2000–2017) was demonstrated by the highest values of the Fractal Fragmentation-Compaction Index, a measure of the degree of disorder (Entropy) and heterogeneity (Lacunarity). The principal outcome of the research reveals the dynamics of disturbance of tree cover and deforested areas expressed by the textural and fractal analysis. The results obtained can be used in the future development and adaptation of forestry management policies to ensure sustainable management of exploited forest areas. Full article
(This article belongs to the Special Issue Quantitative Forest Management to Build Adaptive Capacity against Climate Change and Forest Disturbances)
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