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Forests
Special Issues
Forest and Climate Change Adaptation
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Forest and Climate Change Adaptation

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

Deadline for manuscript submissions: closed (15 June 2024) | Viewed by 11061

Special Issue Editors

Dr. Alexandre Behling

E-Mail Website
Guest Editor
Graduate Program in Forestry, Universidade Federal do Parana, Curitiba, Brazil
Interests: forest management; forest inventory; statistics; programming languages; modeling
Dr. Ana Paula Dalla Corte

E-Mail Website
Guest Editor
Graduate Program in Forestry, Universidade Federal do Parana, Curitiba, Brazil
Interests: lidar remote sensing; digital aerial photogrammetry; tropical and forest plantations; forest inventory and spatial analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Carlos Sanquetta

E-Mail Website
Guest Editor
Graduate Program in Forestry, Universidade Federal do Parana, Curitiba, Brazil
Interests: forest management; forest inventory; carbon; carbon market; climate change
Dr. Sheri Andrews-Key

E-Mail Website
Guest Editor
Innovative Climate Strategies, Saskatoon, SK, Canada
Interests: climate change

Special Issue Information

Dear Colleagues,

This Special Issue includes contributions to the theme: “Forest and Climate Change Adaptation”. Research articles may focus on any aspect of the theme, including: i) methods to assess forest carbon stocks and dynamics; ii) climate change and carbon markets: challenges and opportunities for forest development; iii) climate vulnerability and adaptation; and iv) the components, role, and status of forest carbon projects. These topics were discussed in the Webinar, “Forest and Climate Change Adaptation” (21 March 2023), sponsored by the University of British Columbia and the Graduate Program in Forestry at the Federal University of Paraná, conducted by Prof. Dr. Carlos Roberto Sanquetta, Prof. Dr. Ana Paula Dalla Corte, Prof. Dr. Sheri Andrews-Key and Prof. Dr. Trevor Gareth Jones.

We would like to receive new insights on the proposed topics. All researchers are encouraged to participate in this Special Issue, not only the participants of the Webinar.

Dr. Alexandre Behling
Dr. Ana Paula Dalla Corte
Dr. Carlos Roberto Sanquetta
Dr. Sheri Andrews-Key
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

  • forest Inventory
  • remote sensing
  • LIDAR
  • modeling
  • biomass
  • carbon evaluation
  • carbon market
  • carbon projects
  • climate change

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Published Papers (5 papers)

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Research

18 pages, 22664 KiB  
Article
Natural Factors Rather Than Anthropogenic Factors Control the Greenness Pattern of the Stable Tropical Forests on Hainan Island during 2000–2019
by Binbin Zheng and Rui Yu
Forests 2024, 15(8), 1334; https://doi.org/10.3390/f15081334 - 1 Aug 2024
Viewed by 632
Abstract
Vegetation, being a core component of ecosystems, is known to be influenced by natural and anthropogenic factors. This study used the annual mean Normalized Difference Vegetation Index (NDVI) as the vegetation greenness indicator. The variation in NDVI on Hainan Island was analyzed using [...] Read more.
Vegetation, being a core component of ecosystems, is known to be influenced by natural and anthropogenic factors. This study used the annual mean Normalized Difference Vegetation Index (NDVI) as the vegetation greenness indicator. The variation in NDVI on Hainan Island was analyzed using the Theil–Sen median trend analysis and Mann–Kendall test during 2000–2019. The influence of natural and anthropogenic factors on the driving mechanism of the spatial pattern of NDVI was explored by the Multiscale Weighted Regression (MGWR) model. Additionally, we employed the Boosted Regression Tree (BRT) model to explore their contribution to NDVI. Then, the MGWR model was utilized to predict future greenness patterns based on precipitation and temperature data from different Shared Socioeconomic Pathway (SSP) scenarios for the period 2021–2100. The results showed that: (1) the NDVI of Hainan Island forests significantly increased from 2000 to 2019, with an average increase rate of 0.0026/year. (2) the R2 of the MGWR model was 0.93, which is more effective than the OLS model (R2 = 0.42) in explaining the spatial relationship. The spatial regression coefficients of the NDVI with temperature ranged from −10.05 to 0.8 (p < 0.05). Similarly, the coefficients of Gross Domestic Product (GDP) with the NDVI varied between −5.98 and 3.28 (p < 0.05); (3) The natural factors played the most dominant role in influencing vegetation activities as a result of the relative contributions of 83.2% of forest NDVI changes (16.8% contributed by anthropogenic activities). (4) under SSP119, SSP245, and SSP585 from 2021 to 2100, the NDVI is projected to have an overall decreasing pattern under all scenarios. This study reveals the trend of greenness change and the spatial relationship with natural and anthropogenic factors, which can guide the medium and long-term dynamic monitoring and evaluation of tropical forests on Hainan Island. Full article
(This article belongs to the Special Issue Forest and Climate Change Adaptation)
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18 pages, 19919 KiB  
Article
Carbon Allocation to Leaves and Its Controlling Factors and Impacts on Gross Primary Productivity in Forest Ecosystems of Northeast China
by Zhiru Li, Quan Lai, Yuhai Bao, Bilige Sude, Zhengyi Bao and Xinyi Liu
Forests 2024, 15(1), 129; https://doi.org/10.3390/f15010129 - 8 Jan 2024
Cited by 3 | Viewed by 1429
Abstract
Carbon allocation in forest ecosystems is essential for the optimization of growth. However, remote-sensing-based research on the estimation of carbon allocation in forests is inadequate. This article considers forests in northeastern China as the research area and uses leaf area index (LAI) data [...] Read more.
Carbon allocation in forest ecosystems is essential for the optimization of growth. However, remote-sensing-based research on the estimation of carbon allocation in forests is inadequate. This article considers forests in northeastern China as the research area and uses leaf area index (LAI) data combined with random forest and structural equation modelling methods to study the spatiotemporal distribution characteristics and driving factors of carbon allocation to leaves (ΔLAI) in deciduous broad-leaved forests (DBF), deciduous coniferous forests (DNF), and mixed forests (MF) during the green-up period (GUP) at a monthly scale during April, May, June, and July from 2001 to 2021, and clarifies the impact of leaf carbon allocation on gross primary productivity (GPP). The ΔLAI was the highest in DBF in April and in DNF and MF in May. The ΔLAI in April with an increasing trend year by year in DBF and MF, and the ΔLAI in May with an increasing trend in DNF. Among all the direct and indirect relationships that affect ΔLAI, temperature (TEM) has the highest path coefficient for DBF’s ΔLAI in April (−1.213) and the start of the season (SOS) has the highest path coefficient for DNF (−1.186) and MF (0.815). ΔLAI in the GUP has a significant positive impact on the GPP. In the MF, the higher ΔLAI in May was most conducive to an increase in GPP. During the critical period, that is April and May, carbon allocation to leaves effectively improves the carbon sequestration capacity of forestland. This information is of great value for the development and validation of terrestrial ecosystem models. Full article
(This article belongs to the Special Issue Forest and Climate Change Adaptation)
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26 pages, 4028 KiB  
Article
Canada’s Green Gold: Unveiling Challenges, Opportunities, and Pathways for Sustainable Forestry Offsets
by Chunyu Pan, Chong Li, Alexander An, George Deng, Jerry KuiJie Lin, Junran He, Jonelle Fangyu Li, Xilai Zhu, Guomo Zhou, Anil Kumar Shrestha, Robert Kozak and Guangyu Wang
Forests 2023, 14(11), 2206; https://doi.org/10.3390/f14112206 - 7 Nov 2023
Cited by 2 | Viewed by 3196
Abstract
Forestry offsets, recognized for their diverse environmental and social co-benefits, are gaining a growing interest as nature-based solutions to combat climate change. Despite Canada’s extensive forest resources, its potential for carbon credit remains largely untapped. This study aims to unveil the prevailing challenges [...] Read more.
Forestry offsets, recognized for their diverse environmental and social co-benefits, are gaining a growing interest as nature-based solutions to combat climate change. Despite Canada’s extensive forest resources, its potential for carbon credit remains largely untapped. This study aims to unveil the prevailing challenges in developing forestry offsets in Canada and propose potential solutions, drawing on insights from in-depth semi-structured interviews (SSIs) with 23 experts in the field. A qualitative thematic analysis highlighted 14 challenges under four major frequently discussed themes: methodological (37%), social (29%), economic (22%), and implementation challenges (12%). Our findings highlighted the urgency of addressing key obstacles, including the impermanent nature of forestry carbon offsets, substantial public knowledge gaps, uncertainties in the cost-effectiveness impacting financial viability, and the need for enhanced capacity for project implementation. Building on the discussions on the identified challenges, this study further presented a comprehensive analysis of the future directions for Canada, emphasizing the importance of addressing key methodological issues, enhancing public and Indigenous education and engagement, and leveraging advanced technologies and innovative approaches like ton-year accounting for economic viability. This paper delivers pivotal insights that have the potential to shape the direction and integrity of the forestry offset markets in both Canada and globally. Full article
(This article belongs to the Special Issue Forest and Climate Change Adaptation)
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16 pages, 4699 KiB  
Article
Measuring Tree Diameter with Photogrammetry Using Mobile Phone Cameras
by Aakash Ahamed, John Foye, Sanjok Poudel, Erich Trieschman and John Fike
Forests 2023, 14(10), 2027; https://doi.org/10.3390/f14102027 - 10 Oct 2023
Cited by 6 | Viewed by 3477
Abstract
Tree inventories are a cornerstone of forest science and management. Inventories are essential for quantifying forest growth rates, determining biomass and carbon stock variation, assessing species diversity, and evaluating the impacts of both forest management and climate change. Recent advances in digital sensing [...] Read more.
Tree inventories are a cornerstone of forest science and management. Inventories are essential for quantifying forest growth rates, determining biomass and carbon stock variation, assessing species diversity, and evaluating the impacts of both forest management and climate change. Recent advances in digital sensing technologies on mobile phones have the potential to improve traditional forest inventories through increased efficiency in measurement and transcription and potentially through increasing participation in data collection by non-experts. However, the degree to which digital sensing tools (e.g., camera-enabled smartphone applications) can accurately determine the tree parameters measured during forest inventories remains unclear. In this study, we assess the ability of a smartphone application to perform a user-assisted tree inventory and compare digital estimates of tree diameter to measurements made using traditional forestry field sampling approaches. The results suggest that digital sensing tools on mobile phones can accurately measure tree diameter (R2 = 0.95; RMSE = 2.71 cm compared to manual measurements) while saving time during both the data-collection stage and data-entry stage of field sampling. Importantly, we compare measurements of the same tree across users of the phone application in order to determine the per-user, per-tree, and per-species uncertainty associated with each form of measurement. Strong agreement between manual and digital measurements suggests that digital sensing technologies have the potential to facilitate the efficient collection of high-quality and auditable data collected by non-experts but with some important limitations compared to traditional tree measurement approaches. Most people in the world own a smartphone. Enabling accurate tree inventory data collection through mobile phones at scale can improve our understanding of tree growth and biomass accumulation and the key factors (e.g., climate change or management practices) that affect these processes, ultimately advancing forest science and management. Full article
(This article belongs to the Special Issue Forest and Climate Change Adaptation)
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18 pages, 6354 KiB  
Article
Divergent Responses of NPP to Climate Factors among Forest Types at Interannual and Inter-Monthly Scales: An Empirical Study on Four Typical Forest Types in Subtropical China
by Xu Song, Bofu Zheng, Fangqing Hu, Liliang Xu, Hanqing Wu, Zhong Liu and Wei Wan
Forests 2023, 14(7), 1474; https://doi.org/10.3390/f14071474 - 18 Jul 2023
Cited by 1 | Viewed by 1536
Abstract
Identifying the main climatic controls of productivity differences in different forest ecosystems is beneficial for revealing the patterns of carbon cycle changes in terrestrial ecosystems. Moreover, exploring the differences in their productivity responses to temperature and precipitation at interannual and inter-monthly scales is [...] Read more.
Identifying the main climatic controls of productivity differences in different forest ecosystems is beneficial for revealing the patterns of carbon cycle changes in terrestrial ecosystems. Moreover, exploring the differences in their productivity responses to temperature and precipitation at interannual and inter-monthly scales is conducive to identifying the mechanisms of carbon cycle changes in forest ecosystems, which can enhance the study of the forest ecosystem carbon cycle. In addition, the effect of climate factor changes on the net primary productivity (NPP) of typical forest types in subtropical areas remains unclear. Here, we simulated the dynamic changes in the NPP of four typical forest types (evergreen needleleaf forest (ENF), evergreen broadleaf forest (EBF), bamboo forest (BF), and evergreen needleleaf–broadleaf mixed forest (ENBMF)) in the Poyang Lake Basin from 1970 to 2021 using the Biome-BGC model where its parameters were adjusted according to the ecophysiological characteristics of forest types in this study. Then, the correlation between the NPP of the four typical forest types and climate factors was examined at interannual and inter-monthly scales; the response of the NPP of four typical forest types to future temperature and precipitation changes was explored. The results revealed that NPP showed a fluctuating downward trend after 2000 in ENF, EBF, and ENBMF. The NPP of the ENF was primarily driven by precipitation at the interannual and inter-monthly levels (p < 0.01). The impact of precipitation and accumulated temperature (AT) on NPP of EBF is not significant interannually; the NPP of BF demonstrated a minor correlation with AT and no significant correlation with precipitation. However, the NPP variation of EBF and BF was significantly affected by the temperature at the inter-monthly scale (p < 0.01), with R2 of 0.85 and 0.92, respectively. At the interannual scale, the NPP of ENBMF was mainly driven by precipitation (p < 0.01); at the inter-monthly scale, it was driven by precipitation (p < 0.01) and AT (p < 0.01), with R2 of 0.74 and 0.62, respectively. Under designed climate scenarios, the precipitation changes will have a greater impact on NPP of ENF; the NPP changes in the EBF, BF, and ENBMF will be mainly controlled by temperature increase, and only a 10% change in precipitation leads to its smaller impact on their NPP changes. Full article
(This article belongs to the Special Issue Forest and Climate Change Adaptation)
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