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Current Advances on Ecological Modeling for Sustainable Forest Management

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Forestry".

Deadline for manuscript submissions: closed (28 July 2021) | Viewed by 9275

Special Issue Editors


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Guest Editor
Laboratory of Forest Biometrics, Department of Forestry & Natural Environment, School of Geotechnical Sciences, International Hellenic University, 66100 Drama, Greece
Interests: forest growth; tree and stand structure modelling; forest management; mixed-effects models; remote sensing
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Guest Editor
Laboratory of Forest Resource Management and Bioeconomics, Department of Forestry & Natural Environment, School of Geotechnical Sciences, International Hellenic University, Drama 66100, Greece
Interests: multipurpose forest management; decision support systems; expert systems; multicriteria analysis; valuation of forest externalities; ecosystem servisesservices; urban forestry; spatial statistics; adaptive governance

Special Issue Information

Dear colleagues,

The implementation and monitoring of sustainable forest management, particularly in relation to climate change and socio-economic demands, remains a major challenge for forest managers, stakeholders, and policy-makers in Europe and other regions of the world. Ecological modelling at different spatial and temporal scales has been used over the past few decades to explore the complexity of the concept and practice of forest management sustainability. Ecological models have been aimed in particular at enabling the rational use of forest resources by focusing on the dynamics of forest growth and structure, production of wood and non-wood products, and ecosystem services (e.g., water and soil protection, biodiversity conservation, nutrient cycling, carbon storage, air-filtering, and other socio-economic benefits). Moreover, ecological models are important components for building multi-criteria decision-making tools, which aim at providing impact support information on natural disturbances such as wildfires and forest pests; forest management or restoration regimes such as planting, thinning, and harvesting; as well as optimal resource allocation schemes. The current Special Issue, Current Advances in Ecological Modelling for Sustainable Forest Management, seeks high-quality works and topics focusing on the state-of-the-art forest ecological modelling approaches at relevant spatial and temporal scales; the identification and mathematical description of the main driving forces and attributes; and optimization of forest resource use and restoration to assess the implementation and monitoring of forest management sustainability.

Ass. Prof. Dimitrios I. Raptis
Prof. Vassiliki Kazana
Guest Editors

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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • Sustainable forest management
  • Forest Ecosystem Services
  • Yield modeling
  • Climate change forest impacts
  • Forest sequestration
  • Forest restoration
  • Forest sustainability assessment
  • Forest sustainability monitoring
  • Forest productivity
  • Forest resource impact modeling
  • Forest ecosystem modeling
  • Tree and Forest growth modeling
  • Forest structure modeling
  • Forest multi-criteria modeling

Published Papers (4 papers)

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Research

14 pages, 11806 KiB  
Article
Spatial Analysis of Mangrove Forest Management to Reduce Air Temperature and CO2 Emissions
by Sumarmi Sumarmi, Purwanto Purwanto and Syamsul Bachri
Sustainability 2021, 13(14), 8090; https://0-doi-org.brum.beds.ac.uk/10.3390/su13148090 - 20 Jul 2021
Cited by 5 | Viewed by 2322
Abstract
Surabaya is a coastal city that is still developing. Like other developing cities, Surabaya highly suppresses mangrove forests for residential, industrial, and other areas. Mangrove forests supply oxygen for the population of Surabaya. Forest mangroves reduce the effects of global warming and preserve [...] Read more.
Surabaya is a coastal city that is still developing. Like other developing cities, Surabaya highly suppresses mangrove forests for residential, industrial, and other areas. Mangrove forests supply oxygen for the population of Surabaya. Forest mangroves reduce the effects of global warming and preserve sustainable coastal ecosystems. This research aimed to (1) map temperature changes in Surabaya over a period of 20 years (1996–2016) by using remote sensing and GIS, and (2) examine mangrove forests’ ability to absorb CO2 and decrease the impact of global warming in Surabaya. Research results showed that: (1) on the basis of the analysis of the temperature surface area, temperatures changed significantly between 1996 and 2016. Temperature changes can be classified into low, moderate, or high. The low-temperature area of 21–30 °C followed a different pattern. Each year, changes in the high-surface-temperature area were in the range of 31–42 °C. Changes highly increased in the period of 2006–2016. This indicates that Surabaya experienced a significant temperature increase in 2016. (2) There was correlation between the change in mangrove forest cover and the change in temperature; CO2 concentration in mangrove, vegetation, and water areas decreased as it grew in areas used for construction, such as factories, residences, and roads. CO2 concentration in Surabaya showed a distribution in the “high” and “extremely high” categories. The high category was 27.5%, and the extremely high category was 67.5%. The sample point in both the moderate and low category was around 25%. Full article
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18 pages, 12612 KiB  
Article
Height Allometry of Pinus nigra Arn. in Troodos National Forest Park, Cyprus
by Dimitrios I. Raptis, Vassiliki Kazana, Nikolaos Onisiforou, Christos Stamatiou and Angelos Kazaklis
Sustainability 2021, 13(11), 5998; https://0-doi-org.brum.beds.ac.uk/10.3390/su13115998 - 26 May 2021
Cited by 3 | Viewed by 2043
Abstract
Total height is one of the basic morphometric tree variables included in all forest management inventories, because it is connected with several forest processes and functions related to the estimation of the woody tree volume and sustainable forest yield. The current research, based [...] Read more.
Total height is one of the basic morphometric tree variables included in all forest management inventories, because it is connected with several forest processes and functions related to the estimation of the woody tree volume and sustainable forest yield. The current research, based on a total sample of 1059 measured Black pine (Pinus nigra Arn.) trees from Cyprus, is an attempt to explore the biological processes related to the tree height allometry of this species and develop a generalized mixed-effects model for tree height prediction. The proposed model, with three additional basic covariates and two random parameters, explained almost 96% of the height variance. The model results showed that although competition and site-connected variables affected the total height, it was the crown base height that explained, to a large degree, the height expression. Through the mixed-effects modeling approach it was possible to explore the complex biological processes related to the tree allometry of Black pine and depict those within a mathematical formulation. The proposed generalized model decreased the error significantly, and therefore it can be used for operational forest management purposes. However, for marginal predictions, use of only the fixed part of the basic model could suffice, since this also provided unbiased parameter estimates. Full article
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15 pages, 2750 KiB  
Article
Modelling Individual Tree Diameter Growth of Quercus mongolica Secondary Forest in the Northeast of China
by Xuefan Hu, Guangshuang Duan and Huiru Zhang
Sustainability 2021, 13(8), 4533; https://0-doi-org.brum.beds.ac.uk/10.3390/su13084533 - 19 Apr 2021
Cited by 6 | Viewed by 1967
Abstract
Quercus mongolica secondary forest is widely distributed in the northeast of China, but it usually has low productivity, unstable structure, poor health, and low biodiversity. Diameter is a tree variable that is commonly used for forest growth measurement, to provide the basis for [...] Read more.
Quercus mongolica secondary forest is widely distributed in the northeast of China, but it usually has low productivity, unstable structure, poor health, and low biodiversity. Diameter is a tree variable that is commonly used for forest growth measurement, to provide the basis for forest management decision. Two level generalized linear mixed effects individual tree diameter growth model were developed using data from two times surveys of 12 Q. mongolica secondary forest permanent plots that were distributed among Wangqing forest farms. Random effects of 14 tree species and 12 plots were introduced into the basic model consisting of three factors: tree size, competition of surrounding trees, and site quality. The results showed that initial diameter at breast height(DBH) was the most important variable affecting diameter growth, followed by competition, while the effect of site quality on diameter growth was not significant. Compared with the basic model, the prediction accuracy of the mixed effect model was improved by 17.69 %, where R2 reached to 0.6805, indicating that it is suitable for the individual-tree diameter growth prediction of the secondary forest of Q. mongolica. Full article
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9 pages, 231 KiB  
Article
Heavy Metal Retention by Different Forest Species Used for Restoration of Post-Mining Landscapes, N. Greece
by Theano Samara, Ioannis Spanos, Panagiotis Platis and Thomas G. Papachristou
Sustainability 2020, 12(11), 4453; https://0-doi-org.brum.beds.ac.uk/10.3390/su12114453 - 30 May 2020
Cited by 7 | Viewed by 2111
Abstract
The main objective of this research was to study heavy metal absorption by the leaves of main forest species which were planted for that purpose at post-lignite mining landscapes in Northern Greece (Ptolemais, Prefecture of Kozani), as well as in a neighboring region [...] Read more.
The main objective of this research was to study heavy metal absorption by the leaves of main forest species which were planted for that purpose at post-lignite mining landscapes in Northern Greece (Ptolemais, Prefecture of Kozani), as well as in a neighboring region (Kato Grammatiko), 30 km far from the mining area. Four species were studied; two conifers (Pinus nigra Arn., Cupressus arizonica Greene) and two broad-leaved (Robinia pseudoacacia L., Populus nigra L.). The four species varied in their leaf morphology (needles, scale-like leaves, blade, compound or simple, with rough or smooth surfaces). Eighty (80) leaf samples were collected, (10 from each tree species at either site). The heavy metal concentrations measured were iron (Fe), copper (Cu), chromium (Cr), nickel (Ni), cadmium (Cd), manganese (Mn), zinc (Zn) and cobalt (Co). Statistically significant differences (p = 0.01) were found between the lignite deposit and control areas and among the studied species. Higher concentrations were measured for the studied species at the lignite deposit. Moreover, no species demonstrated maximum absorption for all metals. The metal absorption pattern by coniferous trees’ leaves at the mining landscape was similar, with highest concentrations observed for iron and lowest for cobalt [iron (Fe) > zinc (Zn) > manganese (Mn) > copper (Cu) > chromium (Cr) > nickel (Ni) > cobalt (Co)]. Both broadleaved species absorbed highest concentrations of iron, but differed in the amount of the remaining metals [black locust: iron (Fe) > manganese (Mn) > zinc (Zn) > copper (Cu) > nickel (Ni) > chromium (Cr); black poplar: iron (Fe) > zinc (Zn) > manganese (Mn) > copper (Cu) > nickel (Ni) > chromium (Cr) > cobalt (Co)]. Cadmium was detected only in black poplar at both sites. In general, black pine was found to absorb the highest concentration of iron (Fe), and black poplar zinc (Zn). We discuss the importance of carefully selecting the appropriate mixture of tree species in order to achieve maximum habitat restoration effect at heavy metal polluted sites. Full article
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