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Forests
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Forests Ecosystem Services: Mapping, Assessment and Policy Implications
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Forests Ecosystem Services: Mapping, Assessment and Policy Implications

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Economics, Policy, and Social Science".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 14062

Special Issue Editors

Prof. Dr. Panayotis Dimopoulos

E-Mail Website
Guest Editor
Laboratory of Botany, Department of Biology, University of Patras, GR-26504 Patras, Greece
Interests: mapping and assessment of ecosystems and ecosystem services; biodiversity and ecosystem services; inventory and mapping of flora and habitat types/vegetation types; monitoring and conservation status assessment of habitats and species; conservation management of species and habitat types; conservation policy and national biodiversity strategy
Special Issues, Collections and Topics in MDPI journals
Dr. Ioannis P. Kokkoris

E-Mail Website
Guest Editor
Laboratory of Botany, Department of Biology, University of Patras, GR-26504 Patras, Greece
Interests: conservation ecology; biodiversity; biomonitoring; inventory and mapping of flora and habitat types/vegetation types; mapping and assessment of ecosystems and ecosystem services; GIS and remote sensing; environmental management; sustainable development; environmental policy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Forest ecosystems, covering ca. thirty percent of our planets’ surface and hosting more than 80% of species living on land, are among the most productive in the world, providing multitude and critical benefits to people from the local to global level. Timber supply, medicine, climate and water regulation, erosion control, biodiversity conservation, recreation opportunities, are among the various forest ecosystem services on which human societies have relied on since the antiquity. However, the loss of forest land is continuing worldwide and the projections to 2050, provided by the Millennium Ecosystem Assessment, are disappointing. Moreover, European Union data suggest that although forest cover has increased in the EU in recent decades, the list of the main natural and human-induced pressures on European forests is large; there is also evidence pinpointing an increase of some pressures in terms of severity and frequency in the future, which threatens vulnerable forest species, habitats and their services. The aforementioned facts urge for long-term planning and management, as well as for a holistic approach on policy priorities and decision making, worldwide. This Special Issue (SI) of Forests deals with the mapping and assessment of woodland and forest ecosystems and their services, highlighting their important role in modern spatial planning schemes and conservation strategies, and aims to: (a) promote best practices from the local to the international level, (b) provide guidance on ecosystem services indicators development to inform decision making, (c) present mapping and remote sensing techniques for ecosystem condition and ecosystem services assessments, (d) integrate ecosystem services into natural capital accounting, (e) identify spatial and temporal knowledge gaps, (f) identify and interpret the role of stakeholders in the decision-making process, and (e) provide policy implications and governance practices. Finally, manuscripts that deal with landscape restoration, the interplay among forests and other ecosystems and land uses, as well as with cultural landscapes delineation, assessment and management, are also welcome. Papers published in this SI will contribute to better understanding the contemporary role of forest ecosystem services, as a crucial parameter of decision and policy drafting, with the aim to protect and properly manage these natural assets.

Prof. Dr. Panayotis Dimopoulos
Dr. Ioannis P. Kokkoris
Guest Editors

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

  • Biodiversity
  • Biophysical data
  • Conservation
  • Fauna
  • Flora
  • GIS
  • Monitoring
  • Management
  • Natural capital accounting
  • Policy making
  • Recreation
  • Remote sensing

Published Papers (6 papers)

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Research

15 pages, 2295 KiB  
Article
A Comparison of Raster-Based Forestland Data in Cropland Data Layer and the National Land Cover Database
by Chinazor S. Azubike, Lyubov A. Kurkalova and Timothy J. Mulrooney
Forests 2022, 13(7), 1023; https://doi.org/10.3390/f13071023 - 29 Jun 2022
Cited by 1 | Viewed by 1348
Abstract
The National Agricultural Statistics Service, the statistical arm of the US Department of Agriculture, and the Multi-Resolution Land Characteristics Consortium, a group of the US federal agencies, collect and publish several land-use and land-cover data sets. The aim of this study is to [...] Read more.
The National Agricultural Statistics Service, the statistical arm of the US Department of Agriculture, and the Multi-Resolution Land Characteristics Consortium, a group of the US federal agencies, collect and publish several land-use and land-cover data sets. The aim of this study is to analyze the consistency of forestland estimates based on two widely used, publicly available products: the National Land-Cover Database (NLCD) and Cropland Data Layer (CDL). Both remote-sensing-based products provide raster-formatted land-cover categorization at a spatial resolution of 30 m. Although the processing of the yearly published CDL non-agricultural land-cover data is based on less frequently updated NLCD, the consistency of large-area forestland mapping between these two datasets has not been assessed. To assess the similarities and the differences between CDL- and NLCD-based forestland mappings for the state of North Carolina, we overlay the two data products for the years 2011 and 2016 in ArcMap 10.5.1 and analyze the location and attributes of the matched and mismatched forestland. We find that the mismatch is relatively smaller for the areas of the state where forests occupy larger shares of the total land, and that the relative mismatch is smaller in 2011 when compared to 2016. We also find that a large portion of the forestland mismatch is attributable to the dynamics of re-growth of periodically harvested and otherwise disturbed forests. Our results underscore the need for a holistic approach to data preparation, data attribution, and data accuracy when performing high-scale map-based analyses using each of these products. Full article
(This article belongs to the Special Issue Forests Ecosystem Services: Mapping, Assessment and Policy Implications)
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28 pages, 3570 KiB  
Article
Evaluating Potential Respiratory Benefits of Forest-Based Experiences: A Regional Scale Approach
by Maurizio Droli, Maurizia Sigura, Fabio Giuseppe Vassallo, Giovanni Droli and Luca Iseppi
Forests 2022, 13(3), 387; https://doi.org/10.3390/f13030387 - 26 Feb 2022
Cited by 1 | Viewed by 2799
Abstract
Background: Several studies have suggested the possibility of obtaining specific respiratory benefits by experiencing forests and other natural resources. Despite this, forests have never been considered according to such potential. This study aims to compare municipalities by considering the absence/presence of tree species [...] Read more.
Background: Several studies have suggested the possibility of obtaining specific respiratory benefits by experiencing forests and other natural resources. Despite this, forests have never been considered according to such potential. This study aims to compare municipalities by considering the absence/presence of tree species generating ‘above threshold’ potential respiratory benefits. Methods: The autonomous Region of Friuli Venezia Giulia in Italy has been assumed as a research area. The natural resource based view (NRBV), postulating the strategic role played by natural resources in achieving both above-average (thus ‘valuable’) and ‘concentrated’ (thus ‘rare’ among competitors) performance, has been adopted. The literature reviews dealing with potential respiratory benefits of biogenic organic compounds (BVOCs) emitted by trees, published within the ‘forest therapy’ research field, have been adopted. Three analysis models rating tree species by their potential respiratory benefits in ‘holistic-general’ (P1), ‘particular’ (P2), and ‘dynamic” terms (P3) have been outlined. The resulting overall potentials of tree species have been assessed by adopting the well-rooted Hollerith distance (HD) model. Tree species have been rated “1” when they satisfy one or more of 58 potential respiratory benefits. Municipalities have been ranked by considering the surface area covered by forest types whose dominant tree species achieve above-average potential respiratory benefits. QGIS software has been adopted to geographically reference the results obtained. Results: (P1) Valuable municipalities include those covered by both coniferous and deciduous forests; (P2–3) Municipalities achieving the highest potential respiratory benefits, in both particular and dynamic terms, have been mapped. Discussion: Forest-based initiatives that are running in the preselected municipalities can be both further improved and diversified in a targeted way. Conclusions: Despite some limitations mostly embedded in the concept of ‘model’, this study allows scholars to reduce uncertainties when locating municipalities in which to conduct local-scale experiments. Full article
(This article belongs to the Special Issue Forests Ecosystem Services: Mapping, Assessment and Policy Implications)
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11 pages, 883 KiB  
Article
COVID-19 Anxiety as a Moderator of the Relationship between Organizational Change and Perception of Organizational Politics in Forestry Public Sector
by Pipiet Larasatie, Triana Fitriastuti, Efi Yuliati Yovi, Herry Purnomo and Dodik Ridho Nurrochmat
Forests 2022, 13(2), 356; https://doi.org/10.3390/f13020356 - 20 Feb 2022
Cited by 7 | Viewed by 2443
Abstract
In addition to an outstanding commitment to the Sustainable Development Goals’ (SDG) agenda to good governance (goal no. 16), there is an argument that the SDGs can only be achieved through good governance with strong political institutions and processes. In Indonesia, a new [...] Read more.
In addition to an outstanding commitment to the Sustainable Development Goals’ (SDG) agenda to good governance (goal no. 16), there is an argument that the SDGs can only be achieved through good governance with strong political institutions and processes. In Indonesia, a new era in politics has been marked with the new leadership of Joko Widodo (the current Indonesian President) who has a vision to reform the Indonesian bureaucracy. One of the bureaucratic reform implementations is the merging of the Ministry of Forestry and the Ministry of Environment into the Ministry of Environment and Forestry (MoE). In this kind of organizational change, employees may have increased perceptions of organizational politics and feelings of uncertainty and anxiety. This effect is suspected to be exacerbated by the impact of the COVID-19 pandemic. This article, therefore, aims to investigate the effects of organizational change in the public sector. Based on a survey of 112 state civil apparatuses in the forestry sector in Indonesia, we found that organizational change is positively related to employees’ perception of organizational politics. Nevertheless, our most intriguing finding is that the COVID pandemic situation has decreased employees’ perception of organizational politics. This is because political behaviors are difficult to perform in virtual working settings due to reduced face-to-face interaction and limited non-verbal cues. Full article
(This article belongs to the Special Issue Forests Ecosystem Services: Mapping, Assessment and Policy Implications)
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31 pages, 12618 KiB  
Article
Classifying Forest Types over a Mountainous Area in Southwest China with Landsat Data Composites and Multiple Environmental Factors
by Ruonan Li, Panfei Fang, Weiheng Xu, Leiguang Wang, Guanglong Ou, Wanqiu Zhang and Xin Huang
Forests 2022, 13(1), 135; https://doi.org/10.3390/f13010135 - 17 Jan 2022
Cited by 9 | Viewed by 3090
Abstract
Accurate information about forest type and distribution is critical for many scientific applications. It is possible to make a forest type map from the satellite data in a cost effective way. However, forest type mapping over a large and mountainous geographic area is [...] Read more.
Accurate information about forest type and distribution is critical for many scientific applications. It is possible to make a forest type map from the satellite data in a cost effective way. However, forest type mapping over a large and mountainous geographic area is still challenging, due to complex forest type compositions, spectral similarity among various forest types, poor quality images with clouds or cloud shadows and difficulties in managing and processing large amount data. Based on the Google Earth Engine (GEE) cloud platform, a method of forest types mapping using Landsat-8 OLI imagery and multiple environmental factors was developed and tested within Yunnan Province (about 390,000 km2) of China. The proposed approach employed a pixel-based seasonal image compositing method to produce two types of seasonal composite images, i.e., four 7-spectral-band composite images and four 5-VI-band composite images associated in spring, summer, autumn, and winter. Then, single-season feature bands and multi-seasonal feature bands were combined with the feature bands of topography, temperature, and precipitation, respectively, and resulting in 17 feature combinations. Finally, using a random forest (RF) classifier, 17 feature combinations were separately experimented to classify the forest type over the study area. The study area was firstly classified into the forest and the non-forest, and then the forest was sub-classified into five forest types (evergreen needleleaf forest, deciduous needleleaf forest, evergreen broadleaf forest, deciduous broadleaf forest, and mixed forest). The results showed that the pixel-based multi-seasonal median composite can produce a cloud-free image for the entire region and is suitable for forest type mapping. Compared with a single-season composite, a multi-seasonal composite can distinguish different forest types more effectively. The environmental factors also improve the accuracy of forest type mapping. With the ground survey samples as reference values, the classification performance of 17 feature combinations was compared, and the optimal feature combination was found out. For the optimal feature combination, its overall accuracy of the forest/non-forest cover map and the forest type map reached 97.57% (Kappa = 0.950) and 70.30% (Kappa = 0.628), respectively. The proposed approach has demonstrated strong potential of high classification accuracy and convenient calculation when mapping forest types over a national or global scale, and its product of 30 m resolution forest type map is capable of contributing to forest resource management. Full article
(This article belongs to the Special Issue Forests Ecosystem Services: Mapping, Assessment and Policy Implications)
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25 pages, 35579 KiB  
Article
Spatial–Temporal Changes and Driving Force Analysis of Ecosystems in the Loess Plateau Ecological Screen
by Kai Su, Hongjun Liu and Huiyuan Wang
Forests 2022, 13(1), 54; https://doi.org/10.3390/f13010054 - 03 Jan 2022
Cited by 9 | Viewed by 1614
Abstract
The ecological degradation caused by unreasonable development and prolonged utilization threatens economic development. In response to the development crisis triggered by ecological degradation, the Chinese government launched the National Barrier Zone (NBZ) Construction Program in 2006. However, few in-depth studies on the Loess [...] Read more.
The ecological degradation caused by unreasonable development and prolonged utilization threatens economic development. In response to the development crisis triggered by ecological degradation, the Chinese government launched the National Barrier Zone (NBZ) Construction Program in 2006. However, few in-depth studies on the Loess Plateau Ecological Screen (LPES) have been conducted since the implementation of that program. To address this omission, based on the remote sensing image as the primary data, combined with meteorological, soil, hydrological, social, and economic data, and using GIS spatial analysis technology, this paper analyzes the change characteristics of the ecosystem pattern, quality, and dominant services of the ecosystem in the LPES from 2005 to 2015. The results show that from 2005 to 2015, the ecosystem structure in the study area was relatively stable, and the area of each ecosystem fluctuated slightly. However, the evaluation results based on FVC, LAI, and NPP showed that the quality of the ecosystem improved. The vegetation coverage (FVC) increased significantly at a rate of 0.91% per year, and the net primary productivity (NPP) had increased significantly at a rate of 6.94 gC/(m2∙a) per year. The leaf area index (LAI) in more than 66% of the regions improved, but there were still about 8% of the local regions that were degraded. During these 10 years, the soil erosion situation in LPES improved overall, and the amount of soil conservation (ASC) of the ecosystem in the LPES increased by about 0.18 billion tons. Grassland and forest played important roles in soil conservation in this area. Pearson correlation analysis and redundancy analysis showed that the soil conservation services (SCS) in the LPES were mainly affected by climate change, economic development, and urban construction. The precipitation (P), total solar radiation (SOL), and temperature (T) can explain 52%, 30.1%, and 17% of the change trends of SCS, respectively. Construction land and primary industry were negatively correlated with SCS, accounting for 22% and 8% of the change trends, respectively. Overall, from 2005 to 2015, the ecological environment of LPES showed a gradual improvement trend, but the phenomenon of destroying grass and forests and reclaiming wasteland still existed. Full article
(This article belongs to the Special Issue Forests Ecosystem Services: Mapping, Assessment and Policy Implications)
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22 pages, 10631 KiB  
Article
Prediction of Ecosystem Service Function of Grain for Green Project Based on Ensemble Learning
by Huijie Li, Xiang Niu and Bing Wang
Forests 2021, 12(5), 537; https://doi.org/10.3390/f12050537 - 26 Apr 2021
Cited by 5 | Viewed by 1736
Abstract
The Grain for Green Project (GGP) was implemented over 20 years ago as one of six major forestry projects in China, and its scope of implementation is still expanding. However, it is still unclear how many ecosystem services (ESs) the project will produce [...] Read more.
The Grain for Green Project (GGP) was implemented over 20 years ago as one of six major forestry projects in China, and its scope of implementation is still expanding. However, it is still unclear how many ecosystem services (ESs) the project will produce in the future. The GGP’s large-scale ecological monitoring officially started in 2015 and there is a lack of early monitoring data, making it challenging to predict the future ecological benefits. Therefore, this paper proposes a method to predict future ESs by using ecological monitoring data. First, a new ensemble learning system, auto-XGBoost-ET-DT, is developed based on ensemble learning theory. Using the GGP’s known ESs in 2015, 2017, and 2019, the missing ESs of the past decade have been evaluated via reverse regression. Data from 2020 to 2022 within a convolution neural network and the coupling coordination degree model have been used to analyze the coupling between the prediction results and economic development. The results show that the growth distributions of ESs in three years were as follows: soil consolidation, 3.70–6.34%; forest nutrient retention, 2.72–.71%; water conservation, 2.52–6.09%; carbon fixation and oxygen release, 3.00–4.64%; and dust retention, 3.82–5.75%. The coupling coordination degree of the ESs and economic development has been improved in 97% of counties in 2020 compared with 2019. The results verify a feasible ES prediction method and provide a basis for the progressive implementation of the GGP. Full article
(This article belongs to the Special Issue Forests Ecosystem Services: Mapping, Assessment and Policy Implications)
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