The rapid-developed scale of China’s trade in wood forest products has undergone a considerable uptick. Concomitant with the evolution of high-quality development paradigms, product quality within trade fraforest products. Specifically, Chimeworks has gained escalating scrutiny. Based on the statistical analysis of the export characteristics of China’s wood forest products, this study leverages BACI data spanning from 1998 to 2017. Utilizing regression-based inverse methods, the study quantifies the quality attributes of these export products, dissects fluctuations in quality, and places particular emphasis on the markets within “Belt and Road Initiative” economies to elucidate dynamic trends and spatial distribution characteristics of export quality in this geoeconomic domain. Based on this, the fixed effect model, random effect model, and system GMM are used to empirically examine the influencing factors of China’s wood forest product export quality. This study found that wood-based panel products have the highest quality, followed by paper products and wood furniture among the three major categories of wood forest products. Besides, the overall quality levels of the three products exported to countries participating in the Belt and Road initiative haven’t significantly changed, while notable changes are evident across divergent export destination markets. In addition, an empirical study on the influencing factors of the export product quality of wood forest products is conducted, which indicates that total factor productivity, R&D investment, capital intensity, labor costs, and foreign direct investment are influencing factors. Finally, based on the research conclusions, suggestions are provided on how to improve the export quality of wood forest products.
{"title":"Export Growth and Quality Determination of Wood Forest Products: Evidence from China","authors":"Lu Wan, Nannan Ban, Yizhong Fu, Luyao Yuan","doi":"10.3390/f14122451","DOIUrl":"https://doi.org/10.3390/f14122451","url":null,"abstract":"The rapid-developed scale of China’s trade in wood forest products has undergone a considerable uptick. Concomitant with the evolution of high-quality development paradigms, product quality within trade fraforest products. Specifically, Chimeworks has gained escalating scrutiny. Based on the statistical analysis of the export characteristics of China’s wood forest products, this study leverages BACI data spanning from 1998 to 2017. Utilizing regression-based inverse methods, the study quantifies the quality attributes of these export products, dissects fluctuations in quality, and places particular emphasis on the markets within “Belt and Road Initiative” economies to elucidate dynamic trends and spatial distribution characteristics of export quality in this geoeconomic domain. Based on this, the fixed effect model, random effect model, and system GMM are used to empirically examine the influencing factors of China’s wood forest product export quality. This study found that wood-based panel products have the highest quality, followed by paper products and wood furniture among the three major categories of wood forest products. Besides, the overall quality levels of the three products exported to countries participating in the Belt and Road initiative haven’t significantly changed, while notable changes are evident across divergent export destination markets. In addition, an empirical study on the influencing factors of the export product quality of wood forest products is conducted, which indicates that total factor productivity, R&D investment, capital intensity, labor costs, and foreign direct investment are influencing factors. Finally, based on the research conclusions, suggestions are provided on how to improve the export quality of wood forest products.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"222 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138996982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yoonkoo Jung, Yoonseong Chang, Joungwon You, Dayoung Kim, Hee Han
Poor bucking decisions in forest stands can result in underestimating the profitability of timber sales. This study focuses on Pinus densiflora, commonly known as a red pine in Korea, which has often been underutilized as pulp and chips, leading to reduced profit margins. This study aimed to improve bucking decisions for red pine by analyzing the potential values in different log types and the profitability of manufacturing lumber products compared to pulp chips. A log sawing simulation model was developed using dynamic programming. This study optimized sawing patterns and estimated net profits for varying log sizes within the lumber market in Korea. The findings reveal that manufacturing lumber products from 3.6 m and 2.7 m logs can yield net profits 861% and 723% higher, respectively, than producing pulp chips from 1.8 m logs. Notably, sawing 3.6 m logs resulted in an average net profit 24% higher than from 2.7 m logs. These results advocate for more strategic bucking decisions based on potential timber sale profits and the end-uses of logs, especially in trees with large diameters at breast height (DBH), which can produce high-quality logs and should be bucked into long sawlogs whenever possible. Additionally, the study emphasizes the importance of practicing timber cruise to appraise the stumpage value of forest stands more accurately, moving beyond mere volume estimation to include tree type and expected volume. By implementing these practices, timber sale profits and the overall value of forest stands in Korea can be significantly enhanced. This approach not only benefits the economic aspect of forestry but also encourages sustainable and efficient resource management.
{"title":"Optimizing Bucking Decisions in Korean Red Pine: A Dynamic Programming Approach to Timber Profitability","authors":"Yoonkoo Jung, Yoonseong Chang, Joungwon You, Dayoung Kim, Hee Han","doi":"10.3390/f14122450","DOIUrl":"https://doi.org/10.3390/f14122450","url":null,"abstract":"Poor bucking decisions in forest stands can result in underestimating the profitability of timber sales. This study focuses on Pinus densiflora, commonly known as a red pine in Korea, which has often been underutilized as pulp and chips, leading to reduced profit margins. This study aimed to improve bucking decisions for red pine by analyzing the potential values in different log types and the profitability of manufacturing lumber products compared to pulp chips. A log sawing simulation model was developed using dynamic programming. This study optimized sawing patterns and estimated net profits for varying log sizes within the lumber market in Korea. The findings reveal that manufacturing lumber products from 3.6 m and 2.7 m logs can yield net profits 861% and 723% higher, respectively, than producing pulp chips from 1.8 m logs. Notably, sawing 3.6 m logs resulted in an average net profit 24% higher than from 2.7 m logs. These results advocate for more strategic bucking decisions based on potential timber sale profits and the end-uses of logs, especially in trees with large diameters at breast height (DBH), which can produce high-quality logs and should be bucked into long sawlogs whenever possible. Additionally, the study emphasizes the importance of practicing timber cruise to appraise the stumpage value of forest stands more accurately, moving beyond mere volume estimation to include tree type and expected volume. By implementing these practices, timber sale profits and the overall value of forest stands in Korea can be significantly enhanced. This approach not only benefits the economic aspect of forestry but also encourages sustainable and efficient resource management.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"74 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138996350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In 2022, the Russian forest sector was severely affected by the government’s ban on the export of unprocessed timber and trade sanctions imposed by several countries. It is generally recognized that the regions of the Russian North-West are the most affected by trade barriers that have emerged. Against this background, the impact of bilateral trade restrictions on timber companies in the Asian part of Russia is not discussed. Nevertheless, the forest industry is an important sector of the Siberian economy that has an economic, social and environmental impact on the life of local communities. This paper analyzes the differences among Siberian timber companies in their response to the crisis depending on three factors: industrial specialization, scale of revenue and regional location. The results show that in 2022 the highest median revenues and net profits were generated by small firms that were focused on the domestic market and benefited from reduced competition due to sanctions. There is also evidence that spatial heterogeneity in the response to the crisis may be due to the different support measures of regional authorities and the proximity of the region to border points. We argue that the current conditions may become a new driver for the timber industry development, aimed at the growth of added value and expansion of domestic demand for wood products.
{"title":"Impact of Trade Restrictions on the Russian Forest Industry: Evidence from Siberian Timber Producers","authors":"R. Gordeev, A. Pyzhev","doi":"10.3390/f14122452","DOIUrl":"https://doi.org/10.3390/f14122452","url":null,"abstract":"In 2022, the Russian forest sector was severely affected by the government’s ban on the export of unprocessed timber and trade sanctions imposed by several countries. It is generally recognized that the regions of the Russian North-West are the most affected by trade barriers that have emerged. Against this background, the impact of bilateral trade restrictions on timber companies in the Asian part of Russia is not discussed. Nevertheless, the forest industry is an important sector of the Siberian economy that has an economic, social and environmental impact on the life of local communities. This paper analyzes the differences among Siberian timber companies in their response to the crisis depending on three factors: industrial specialization, scale of revenue and regional location. The results show that in 2022 the highest median revenues and net profits were generated by small firms that were focused on the domestic market and benefited from reduced competition due to sanctions. There is also evidence that spatial heterogeneity in the response to the crisis may be due to the different support measures of regional authorities and the proximity of the region to border points. We argue that the current conditions may become a new driver for the timber industry development, aimed at the growth of added value and expansion of domestic demand for wood products.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"20 35","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139000786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mia Marušić, I. Seletković, Mladen Ognjenović, M. Jonard, Krunoslav Sever, M. Schaub, Arthur Gessler, Mario Šango, Ivana Sirovica, Ivana Zegnal, Robert Bogdanić, N. Potočić
The increased frequency of climate change-induced droughts poses a survival challenge for forest trees, particularly for the common beech (Fagus sylvatica L.). Drought conditions adversely affect water supply and nutrient uptake, yet there is limited understanding of the intricate interplay between nutrient availability and drought stress on the physiology, growth, and biomass accumulation in young trees. We aimed to address this knowledge gap by examining the effects of irrigation and fertilisation and their interaction with various parameters in common beech saplings, including foliar and root N, P, and K concentrations; height and diameter increments; and aboveground and belowground biomass production. Our findings revealed that a higher fertilisation dose increased nutrient availability, also partially mitigating immediate drought impacts on foliar N concentrations. Also, higher fertilisation supported the post-drought recovery of foliar phosphorus levels in saplings. Prolonged drought affected nitrogen and potassium foliar concentrations, illustrating the lasting physiological impact of drought on beech trees. While drought-stressed beech saplings exhibited reduced height increment and biomass production, increased nutrient availability positively impacted root collar diameters. These insights have potential implications for forest management practices, afforestation strategies, and our broader understanding of the ecological consequences of climate change on forests.
{"title":"Nutrient and Growth Response of Fagus sylvatica L. Saplings to Drought Is Modified by Fertilisation","authors":"Mia Marušić, I. Seletković, Mladen Ognjenović, M. Jonard, Krunoslav Sever, M. Schaub, Arthur Gessler, Mario Šango, Ivana Sirovica, Ivana Zegnal, Robert Bogdanić, N. Potočić","doi":"10.3390/f14122445","DOIUrl":"https://doi.org/10.3390/f14122445","url":null,"abstract":"The increased frequency of climate change-induced droughts poses a survival challenge for forest trees, particularly for the common beech (Fagus sylvatica L.). Drought conditions adversely affect water supply and nutrient uptake, yet there is limited understanding of the intricate interplay between nutrient availability and drought stress on the physiology, growth, and biomass accumulation in young trees. We aimed to address this knowledge gap by examining the effects of irrigation and fertilisation and their interaction with various parameters in common beech saplings, including foliar and root N, P, and K concentrations; height and diameter increments; and aboveground and belowground biomass production. Our findings revealed that a higher fertilisation dose increased nutrient availability, also partially mitigating immediate drought impacts on foliar N concentrations. Also, higher fertilisation supported the post-drought recovery of foliar phosphorus levels in saplings. Prolonged drought affected nitrogen and potassium foliar concentrations, illustrating the lasting physiological impact of drought on beech trees. While drought-stressed beech saplings exhibited reduced height increment and biomass production, increased nutrient availability positively impacted root collar diameters. These insights have potential implications for forest management practices, afforestation strategies, and our broader understanding of the ecological consequences of climate change on forests.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"10 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138973242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chuping Wu, Jianzhong Fan, Yonghong Xu, Bo Jiang, Jiejie Jiao, Liangjin Yao
In recent years, frequent global climate change has led to extreme weather events, such as high temperatures and droughts. Under the backdrop of climate change, the potential distribution zones of plants will undergo alterations. Therefore, it is necessary to predict the potential geographical distribution patterns of plants under climate change. Schima superba, a plant species with significant ecological and economic value, plays a crucial role in ecological restoration and maintaining environmental stability. Therefore, predicting potential changes in its suitable habitat in Zhejiang Province is significant. The MaxEnt model and combined data from 831 monitoring sites where Schima superba is distributed in Zhejiang Province with 12 selected bioclimatic variables were used to predict habitat suitability adaptability. We found that (1) the average AUC value of the MaxEnt model in repeated experiments was 0.804, with a standard deviation of 0.014, which indicates high reliability in predictions. (2) The total suitable habitat area for Schima superba in Zhejiang Province (suitability value > 0.05) is 87,600 km2, with high-suitability, moderate-suitability, and low-suitability areas covering 29,400 km2, 25,700 km2, and 32,500 km2, respectively. (3) Likewise, elevation, precipitation, and temperature are the dominant climatic variables that influence the distribution of Schima superba. Schima superba mainly occurs in areas with an elevation above 500 m and precipitation over 140 mm during the hottest season. The probability of Schima superba distribution reaches its peak at elevations between 1200 and 1400 m. Here, the precipitation ranges from 300 to 350 mm with high humidity, between 160 and 170 mm during the hottest season, and an annual temperature range between 28 and 31 °C. Therefore, our results indicate that climate change significantly affects the suitable habitat area of Schima superba. We also reveal the ecological characteristics and adaptation mechanisms of Schima superba in different geographical regions of Zhejiang Province. Future research should focus on the relationship between plant adaptation strategies and environmental changes, as well as applications in ecosystem protection and sustainable development, to promote the development and application of plant habitat adaptability research.
{"title":"Adaptability Analysis of the Evergreen Pioneer Tree Species Schima superba to Climate Change in Zhejiang Province","authors":"Chuping Wu, Jianzhong Fan, Yonghong Xu, Bo Jiang, Jiejie Jiao, Liangjin Yao","doi":"10.3390/f14122438","DOIUrl":"https://doi.org/10.3390/f14122438","url":null,"abstract":"In recent years, frequent global climate change has led to extreme weather events, such as high temperatures and droughts. Under the backdrop of climate change, the potential distribution zones of plants will undergo alterations. Therefore, it is necessary to predict the potential geographical distribution patterns of plants under climate change. Schima superba, a plant species with significant ecological and economic value, plays a crucial role in ecological restoration and maintaining environmental stability. Therefore, predicting potential changes in its suitable habitat in Zhejiang Province is significant. The MaxEnt model and combined data from 831 monitoring sites where Schima superba is distributed in Zhejiang Province with 12 selected bioclimatic variables were used to predict habitat suitability adaptability. We found that (1) the average AUC value of the MaxEnt model in repeated experiments was 0.804, with a standard deviation of 0.014, which indicates high reliability in predictions. (2) The total suitable habitat area for Schima superba in Zhejiang Province (suitability value > 0.05) is 87,600 km2, with high-suitability, moderate-suitability, and low-suitability areas covering 29,400 km2, 25,700 km2, and 32,500 km2, respectively. (3) Likewise, elevation, precipitation, and temperature are the dominant climatic variables that influence the distribution of Schima superba. Schima superba mainly occurs in areas with an elevation above 500 m and precipitation over 140 mm during the hottest season. The probability of Schima superba distribution reaches its peak at elevations between 1200 and 1400 m. Here, the precipitation ranges from 300 to 350 mm with high humidity, between 160 and 170 mm during the hottest season, and an annual temperature range between 28 and 31 °C. Therefore, our results indicate that climate change significantly affects the suitable habitat area of Schima superba. We also reveal the ecological characteristics and adaptation mechanisms of Schima superba in different geographical regions of Zhejiang Province. Future research should focus on the relationship between plant adaptation strategies and environmental changes, as well as applications in ecosystem protection and sustainable development, to promote the development and application of plant habitat adaptability research.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"1992 9","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138973955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chinese fir is one of the most widely distributed and extensively planted timber species in China. Therefore, monitoring pests and diseases in Chinese fir plantations is directly related to national timber forest security and forest ecological security. This study aimed to identify appropriate vegetation indices for the early monitoring of pests and diseases in Chinese fir plantations. For this purpose, the researchers used an imaging spectrometer to capture hyperspectral images of both experimental and control groups. The experimental group consisted of Chinese fir trees with two sections of bark stripped off, while the control group consisted of healthy Chinese fir trees. The study then assessed the sensitivity of 11 vegetation indices to the physiological differences between the two groups using the Mann–Whitney U test. The results showed that both the green-to-red region spectral angle index (GRRSGI) and the red edge position index (REP) were able to monitor the difference as early as 16 days after damage. However, GRRSGI performs best in monitoring early death changes in Chinese fir trees because it is less affected by noise and is more stable. The green–red spectral area index (GRSAI) also had high stability, but the monitoring effect was slightly worse than that of GRRSGI and REP. Compared with other indices, GRRSGI and GRSAI can better exploit the advantages of hyperspectral data.
{"title":"Using a Vegetation Index to Monitor the Death Process of Chinese Fir Based on Hyperspectral Data","authors":"Xuemei Tang, Zhuo Zang, Hui Lin, Xu Wang, Zhang Wen","doi":"10.3390/f14122444","DOIUrl":"https://doi.org/10.3390/f14122444","url":null,"abstract":"Chinese fir is one of the most widely distributed and extensively planted timber species in China. Therefore, monitoring pests and diseases in Chinese fir plantations is directly related to national timber forest security and forest ecological security. This study aimed to identify appropriate vegetation indices for the early monitoring of pests and diseases in Chinese fir plantations. For this purpose, the researchers used an imaging spectrometer to capture hyperspectral images of both experimental and control groups. The experimental group consisted of Chinese fir trees with two sections of bark stripped off, while the control group consisted of healthy Chinese fir trees. The study then assessed the sensitivity of 11 vegetation indices to the physiological differences between the two groups using the Mann–Whitney U test. The results showed that both the green-to-red region spectral angle index (GRRSGI) and the red edge position index (REP) were able to monitor the difference as early as 16 days after damage. However, GRRSGI performs best in monitoring early death changes in Chinese fir trees because it is less affected by noise and is more stable. The green–red spectral area index (GRSAI) also had high stability, but the monitoring effect was slightly worse than that of GRRSGI and REP. Compared with other indices, GRRSGI and GRSAI can better exploit the advantages of hyperspectral data.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"5 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139001458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Identifying the changes in landscape pattern and ecosystem service value (ESV) and clarifying their relationship in temporal changes and spatial variations can provide insight into regional landscape features and scientific support for regional landscape planning. Leveraging land use data from the Yihe River Basin, we quantitatively assessed the landscape pattern and ESV shifts spanning from 2000 to 2018 using the landscape pattern indexes and the equivalence factor method. We employed Pearson correlation metrics and the geographically weighted regression model to explore the interrelation of their spatiotemporal variations. Our results show the following: (1) Forestland represents the most expansive land cover category. Apart from construction land, all other types experienced a decline in area. The most notable change occurred in the area of construction land. (2) The aggregation of the overall landscape shows a downward trend. The levels of fragmentation, landscape diversity, and richness increased. (3) Throughout the entire study period, the overall ESV gradually decreased, and the land cover type with the greatest contribution to the ESV was forestland. (4) In terms of temporal changes, the patch density and edge density of the overall area are significantly negatively correlated with total ESVs. The largest values for the patch index, perimeter–area fractal dimension (PAFRAC), and aggregation are significantly positively correlated with total ESVs. (5) In terms of spatial variation, the contagion index (CONTAG), PAFRAC, and the Shannon diversity index (SHDI) were noticeably correlated with ESVs. The CONTAG is positively correlated with ESVs upstream, but negatively midstream and downstream. The SHDI is negatively correlated with ESVs upstream, but positively midstream and downstream. The PAFRAC exhibits a positive correlation with ESVs for the most part. The association between the landscape pattern indexes and ESVs exhibits temporal and spatial inconsistencies in most instances, suggesting a spatiotemporal scale effect in their relationship. This study recommends that the local government devises a long-term strategy for urban development and exercises stringent control over the unregulated expansion of construction land. Through reasonable territorial spatial planning, government departments could enhance the connectivity of the overall landscape pattern of the Yihe River Basin to achieve the reasonable allocation and sustainable development of regional resources.
{"title":"Identifying the Relationships between Landscape Pattern and Ecosystem Service Value from a Spatiotemporal Variation Perspective in a Mountain–Hill–Plain Region","authors":"Qing Han, Ling Li, Hejie Wei, Xiaoli Wu","doi":"10.3390/f14122446","DOIUrl":"https://doi.org/10.3390/f14122446","url":null,"abstract":"Identifying the changes in landscape pattern and ecosystem service value (ESV) and clarifying their relationship in temporal changes and spatial variations can provide insight into regional landscape features and scientific support for regional landscape planning. Leveraging land use data from the Yihe River Basin, we quantitatively assessed the landscape pattern and ESV shifts spanning from 2000 to 2018 using the landscape pattern indexes and the equivalence factor method. We employed Pearson correlation metrics and the geographically weighted regression model to explore the interrelation of their spatiotemporal variations. Our results show the following: (1) Forestland represents the most expansive land cover category. Apart from construction land, all other types experienced a decline in area. The most notable change occurred in the area of construction land. (2) The aggregation of the overall landscape shows a downward trend. The levels of fragmentation, landscape diversity, and richness increased. (3) Throughout the entire study period, the overall ESV gradually decreased, and the land cover type with the greatest contribution to the ESV was forestland. (4) In terms of temporal changes, the patch density and edge density of the overall area are significantly negatively correlated with total ESVs. The largest values for the patch index, perimeter–area fractal dimension (PAFRAC), and aggregation are significantly positively correlated with total ESVs. (5) In terms of spatial variation, the contagion index (CONTAG), PAFRAC, and the Shannon diversity index (SHDI) were noticeably correlated with ESVs. The CONTAG is positively correlated with ESVs upstream, but negatively midstream and downstream. The SHDI is negatively correlated with ESVs upstream, but positively midstream and downstream. The PAFRAC exhibits a positive correlation with ESVs for the most part. The association between the landscape pattern indexes and ESVs exhibits temporal and spatial inconsistencies in most instances, suggesting a spatiotemporal scale effect in their relationship. This study recommends that the local government devises a long-term strategy for urban development and exercises stringent control over the unregulated expansion of construction land. Through reasonable territorial spatial planning, government departments could enhance the connectivity of the overall landscape pattern of the Yihe River Basin to achieve the reasonable allocation and sustainable development of regional resources.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"158 3","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139002364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
See Ven Lim, M. A. Zulkifley, Azlan Saleh, A. H. Saputro, Siti Raihanah Abdani
Deforestation remains one of the key concerning activities around the world due to commodity-driven extraction, agricultural land expansion, and urbanization. The effective and efficient monitoring of national forests using remote sensing technology is important for the early detection and mitigation of deforestation activities. Deep learning techniques have been vastly researched and applied to various remote sensing tasks, whereby fully convolutional neural networks have been commonly studied with various input band combinations for satellite imagery applications, but very little research has focused on deep networks with high-resolution representations, such as HRNet. In this study, an optimal semantic segmentation architecture based on high-resolution feature maps and an attention mechanism is proposed to label each pixel of the satellite imagery input for forest identification. The selected study areas are located in Malaysian rainforests, sampled from 2016, 2018, and 2020, downloaded using Google Earth Pro. Only a two-class problem is considered for this study, which is to classify each pixel either as forest or non-forest. HRNet is chosen as the baseline architecture, in which the hyperparameters are optimized before being embedded with an attention mechanism to help the model to focus on more critical features that are related to the forest. Several variants of the proposed methods are validated on 6120 sliced images, whereby the best performance reaches 85.58% for the mean intersection over union and 92.24% for accuracy. The benchmarking analysis also reveals that the attention-embedded high-resolution architecture outperforms U-Net, SegNet, and FC-DenseNet for both performance metrics. A qualitative analysis between the baseline and attention-based models also shows that fewer false classifications and cleaner prediction outputs can be observed in identifying the forest areas.
{"title":"Attention-Based Semantic Segmentation Networks for Forest Applications","authors":"See Ven Lim, M. A. Zulkifley, Azlan Saleh, A. H. Saputro, Siti Raihanah Abdani","doi":"10.3390/f14122437","DOIUrl":"https://doi.org/10.3390/f14122437","url":null,"abstract":"Deforestation remains one of the key concerning activities around the world due to commodity-driven extraction, agricultural land expansion, and urbanization. The effective and efficient monitoring of national forests using remote sensing technology is important for the early detection and mitigation of deforestation activities. Deep learning techniques have been vastly researched and applied to various remote sensing tasks, whereby fully convolutional neural networks have been commonly studied with various input band combinations for satellite imagery applications, but very little research has focused on deep networks with high-resolution representations, such as HRNet. In this study, an optimal semantic segmentation architecture based on high-resolution feature maps and an attention mechanism is proposed to label each pixel of the satellite imagery input for forest identification. The selected study areas are located in Malaysian rainforests, sampled from 2016, 2018, and 2020, downloaded using Google Earth Pro. Only a two-class problem is considered for this study, which is to classify each pixel either as forest or non-forest. HRNet is chosen as the baseline architecture, in which the hyperparameters are optimized before being embedded with an attention mechanism to help the model to focus on more critical features that are related to the forest. Several variants of the proposed methods are validated on 6120 sliced images, whereby the best performance reaches 85.58% for the mean intersection over union and 92.24% for accuracy. The benchmarking analysis also reveals that the attention-embedded high-resolution architecture outperforms U-Net, SegNet, and FC-DenseNet for both performance metrics. A qualitative analysis between the baseline and attention-based models also shows that fewer false classifications and cleaner prediction outputs can be observed in identifying the forest areas.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"58 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139003377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Belian (Eusideroxylon zwageri Teijsm. & Binn.) is a commercially important timber species in Southeast Asia that was listed on the IUCN Red List of threatened species in 1998. Six years ago, we published an article in Genome Biology Ecology entitled “Evolutionary Comparisons of the Chloroplast Genome in Lauraceae and Insights into Loss Events in the Magnoliids” in which one complete plastid genome of Belian was assembled for comparative analyses of the plastomes in Lauraceae. However, a recent study concluded that our sequenced Belian individual can be located in the clade of Myristicaceae instead of that of Lauraceae. Here, we performed reanalyses of an additional two Belian plastomes, along with 42 plastomes from plants spanning 10 families of the Magnoliids. The three Belian plastomes are 39% CG and vary in length from 157,535 to 157,577 bp. A total of 37 tRNA genes, 8 rRNA genes, and 85 protein-coding genes were among the 130 annotated genes. There were 95–101 repeat sequences and 56–61 simple repeat sequences (SSRs). Comparative genomic analysis revealed 170 mutation sites in their plastomes, which include 111 substitutions, 53 indels, and 6 microinversions. Phylogeny was reconstructed using maximum-likelihood and Bayesian approaches for 44 magnoliids species, indicating that the 3 Belian individuals were nested among the species in the Lauraceae family rather than Myristicaceae.
贝里棕（Eusideroxylon zwageri Teijsm. & Binn.）是东南亚的一种重要商业用材树种，1998年被列入世界自然保护联盟（IUCN）濒危物种红色名录。六年前，我们在《基因组生物学生态学》（Genome Biology Ecology）杂志上发表了一篇题为《月桂科植物叶绿体基因组的进化比较和木兰科植物损失事件的启示》（Evolutionary Comparisons of the Chloroplast Genome in Lauraceae and Insights into Loss Events in the Magnoliids）的文章，其中组装了贝利安的一个完整的质体基因组，用于月桂科植物质体的比较分析。然而，最近的一项研究认为，我们测序的贝利安个体可以归入肉豆蔻科而非月桂科。在此，我们对另外两个贝里安植物质粒以及来自木兰科 10 个科的 42 个植物质粒进行了重新分析。这三个贝利亚植物质粒的 CG 含量为 39%，长度从 157,535 到 157,577 bp 不等。在 130 个注释基因中，共有 37 个 tRNA 基因、8 个 rRNA 基因和 85 个蛋白质编码基因。有 95-101 个重复序列和 56-61 个简单重复序列（SSR）。比较基因组分析显示，它们的质粒中有 170 个突变位点，其中包括 111 个置换位点、53 个嵌合位点和 6 个微变位点。利用最大似然法和贝叶斯法重建了44种木兰科植物的系统发育，结果表明这3个贝里安个体嵌套在月桂科而不是肉豆蔻科的物种中。
{"title":"The Complete Plastid Genome Sequences of the Belian (Eusideroxylon zwageri): Comparative Analysis and Phylogenetic Relationships with Other Magnoliids","authors":"Wen Zhu, Yunhong Tan, Xinxin Zhou, Yu Song, Peiyao Xin","doi":"10.3390/f14122443","DOIUrl":"https://doi.org/10.3390/f14122443","url":null,"abstract":"The Belian (Eusideroxylon zwageri Teijsm. & Binn.) is a commercially important timber species in Southeast Asia that was listed on the IUCN Red List of threatened species in 1998. Six years ago, we published an article in Genome Biology Ecology entitled “Evolutionary Comparisons of the Chloroplast Genome in Lauraceae and Insights into Loss Events in the Magnoliids” in which one complete plastid genome of Belian was assembled for comparative analyses of the plastomes in Lauraceae. However, a recent study concluded that our sequenced Belian individual can be located in the clade of Myristicaceae instead of that of Lauraceae. Here, we performed reanalyses of an additional two Belian plastomes, along with 42 plastomes from plants spanning 10 families of the Magnoliids. The three Belian plastomes are 39% CG and vary in length from 157,535 to 157,577 bp. A total of 37 tRNA genes, 8 rRNA genes, and 85 protein-coding genes were among the 130 annotated genes. There were 95–101 repeat sequences and 56–61 simple repeat sequences (SSRs). Comparative genomic analysis revealed 170 mutation sites in their plastomes, which include 111 substitutions, 53 indels, and 6 microinversions. Phylogeny was reconstructed using maximum-likelihood and Bayesian approaches for 44 magnoliids species, indicating that the 3 Belian individuals were nested among the species in the Lauraceae family rather than Myristicaceae.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"26 S1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138972073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lei Li, Guangxing Ji, Qingsong Li, Jincai Zhang, Huishan Gao, Mengya Jia, Meng Li, Genming Li
Land-use change has a great impact on regional ecosystem balance and carbon storage, so it is of great significance to study future land-use types and carbon storage in a region to optimize the regional land-use structure. Based on the existing land-use data and the different scenarios of the shared socioeconomic pathway and the representative concentration pathway (SSP-RCP) provided by CMIP6, this study used the PLUS model to predict future land use and the InVEST model to predict the carbon storage in the study area in the historical period and under different scenarios in the future. The results show the following: (1) The change in land use will lead to a change in carbon storage. From 2000 to 2020, the conversion of cultivated land to construction land was the main transfer type, which was also an important reason for the decrease in regional carbon storage. (2) Under the three scenarios, the SSP126 scenario has the smallest share of arable land area, while this scenario has the largest share of woodland and grassland land area, and none of the three scenarios shows a significant decrease in woodland area. (3) From 2020 to 2050, the carbon stocks in the study area under the three scenarios, SSP126, SSP245, and SSP585, all show different degrees of decline, decreasing to 36,405.0204 × 104 t, 36,251.4402 × 104 t, and 36,190.4066 × 104 t, respectively. Restricting the conversion of land with a high carbon storage capacity to land with a low carbon storage capacity is conducive to the benign development of regional carbon storage. This study can provide a reference for the adjustment and management of future land-use structures in the region.
{"title":"Spatiotemporal Evolution and Prediction of Ecosystem Carbon Storage in the Yiluo River Basin Based on the PLUS-InVEST Model","authors":"Lei Li, Guangxing Ji, Qingsong Li, Jincai Zhang, Huishan Gao, Mengya Jia, Meng Li, Genming Li","doi":"10.3390/f14122442","DOIUrl":"https://doi.org/10.3390/f14122442","url":null,"abstract":"Land-use change has a great impact on regional ecosystem balance and carbon storage, so it is of great significance to study future land-use types and carbon storage in a region to optimize the regional land-use structure. Based on the existing land-use data and the different scenarios of the shared socioeconomic pathway and the representative concentration pathway (SSP-RCP) provided by CMIP6, this study used the PLUS model to predict future land use and the InVEST model to predict the carbon storage in the study area in the historical period and under different scenarios in the future. The results show the following: (1) The change in land use will lead to a change in carbon storage. From 2000 to 2020, the conversion of cultivated land to construction land was the main transfer type, which was also an important reason for the decrease in regional carbon storage. (2) Under the three scenarios, the SSP126 scenario has the smallest share of arable land area, while this scenario has the largest share of woodland and grassland land area, and none of the three scenarios shows a significant decrease in woodland area. (3) From 2020 to 2050, the carbon stocks in the study area under the three scenarios, SSP126, SSP245, and SSP585, all show different degrees of decline, decreasing to 36,405.0204 × 104 t, 36,251.4402 × 104 t, and 36,190.4066 × 104 t, respectively. Restricting the conversion of land with a high carbon storage capacity to land with a low carbon storage capacity is conducive to the benign development of regional carbon storage. This study can provide a reference for the adjustment and management of future land-use structures in the region.","PeriodicalId":12339,"journal":{"name":"Forests","volume":"29 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138972669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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