Longleaf pine (Pinus palustris Mill.) is a conifer historically associated with an open forest ecosystem that extended across much of the coastal plain of the Southeastern United States. It now exists mainly in isolated fragments following the conversion of forests and the long-term disruption of the low-intensity fire regime upon which the species depends. Recent decades have seen efforts to restore longleaf pine forests by government and private landowners. This was reflected in analyses of national forest inventory data during two time periods, ca. 2009–2015 and 2016–2021, that showed increases in the estimated number of longleaf pine trees, the area of the longleaf pine forest type, and the number and area of planted longleaf pine, along with growth in mean plot-level longleaf pine carbon and importance value. At the same time, we found a decrease in the overall forest area containing longleaf pine, manifested across a variety of other forest types. These results point to a dynamic through which forests dominated by longleaf pine are becoming more widespread via restoration, while forests in which the species is a less important component are transitioning to other forest types or land uses. We also detected a decrease over time in the estimated number of longleaf seedlings across most states and forest types and a decline in naturally regenerated longleaf pine. To further assess regeneration trends in longleaf pine, we calculated the estimated proportion of small trees (seedlings and saplings) for the entire species and for seed zone sub-populations. We found a species-wide decrease in the proportion of small trees, from 82.1 percent to 75.1 percent. This reduction was most pronounced along the edges of the species distribution and could indicate less sustainable levels of regeneration in some areas. These results underscore the challenges of facilitating natural regeneration in this important species.
{"title":"Range-Wide Assessment of Recent Longleaf Pine (Pinus palustris Mill.) Area and Regeneration Trends","authors":"Kevin M. Potter, C. Oswalt, J. Guldin","doi":"10.3390/f15071255","DOIUrl":"https://doi.org/10.3390/f15071255","url":null,"abstract":"Longleaf pine (Pinus palustris Mill.) is a conifer historically associated with an open forest ecosystem that extended across much of the coastal plain of the Southeastern United States. It now exists mainly in isolated fragments following the conversion of forests and the long-term disruption of the low-intensity fire regime upon which the species depends. Recent decades have seen efforts to restore longleaf pine forests by government and private landowners. This was reflected in analyses of national forest inventory data during two time periods, ca. 2009–2015 and 2016–2021, that showed increases in the estimated number of longleaf pine trees, the area of the longleaf pine forest type, and the number and area of planted longleaf pine, along with growth in mean plot-level longleaf pine carbon and importance value. At the same time, we found a decrease in the overall forest area containing longleaf pine, manifested across a variety of other forest types. These results point to a dynamic through which forests dominated by longleaf pine are becoming more widespread via restoration, while forests in which the species is a less important component are transitioning to other forest types or land uses. We also detected a decrease over time in the estimated number of longleaf seedlings across most states and forest types and a decline in naturally regenerated longleaf pine. To further assess regeneration trends in longleaf pine, we calculated the estimated proportion of small trees (seedlings and saplings) for the entire species and for seed zone sub-populations. We found a species-wide decrease in the proportion of small trees, from 82.1 percent to 75.1 percent. This reduction was most pronounced along the edges of the species distribution and could indicate less sustainable levels of regeneration in some areas. These results underscore the challenges of facilitating natural regeneration in this important species.","PeriodicalId":505742,"journal":{"name":"Forests","volume":" 777","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vegetation is a crucial component of ecosystems, and understanding the drivers and spatial optimization patterns of its ecological quality is vital for environmental management in the middle reaches of the Yangtze River Urban Agglomeration. Traditional evaluations employing single indices may not fully capture the complexity of vegetation elements and require evaluation through various indicators. Therefore, this study introduced the Multi Criteria Vegetation Ecological Quality Index (VEQI), coupled with vegetation cover and vegetation ecological function indicators, to explore the driving factors of vegetation quality in the middle reaches of the Yangtze River and identify key areas where vegetation quality declines or improves. By constructing a Bayesian network for VEQI, we identified the driving variables that influence the index. Additionally, we delineated spatial optimization zones for VEQI. The results indicate that the VEQI exhibits a trend of transitioning from low values in urban centers to high values in suburban and rural areas. Over 20 years, the average VEQI of the study region ranged from 10.85% to 94.94%. Slope, DEM, and vegetation type were identified as significant drivers of VEQI, while precipitation, temperature, and nighttime light were considered secondary factors. Notably, areas in Hunan, Jiangxi, and Hubei provinces, especially the western part of Hunan, were pinpointed as spatial optimization regions. This research not only enhances the understanding of vegetation’s ecological quality in the urban agglomeration of the middle reaches of the Yangtze River but also provides scientific insights for the protection and management of vegetation.
{"title":"Analysis of Driving Factors for Vegetation Ecological Quality Based on Bayesian Network","authors":"Jin Cai, Xiaojian Wei, Fuqing Zhang, Yuanping Xia","doi":"10.3390/f15071263","DOIUrl":"https://doi.org/10.3390/f15071263","url":null,"abstract":"Vegetation is a crucial component of ecosystems, and understanding the drivers and spatial optimization patterns of its ecological quality is vital for environmental management in the middle reaches of the Yangtze River Urban Agglomeration. Traditional evaluations employing single indices may not fully capture the complexity of vegetation elements and require evaluation through various indicators. Therefore, this study introduced the Multi Criteria Vegetation Ecological Quality Index (VEQI), coupled with vegetation cover and vegetation ecological function indicators, to explore the driving factors of vegetation quality in the middle reaches of the Yangtze River and identify key areas where vegetation quality declines or improves. By constructing a Bayesian network for VEQI, we identified the driving variables that influence the index. Additionally, we delineated spatial optimization zones for VEQI. The results indicate that the VEQI exhibits a trend of transitioning from low values in urban centers to high values in suburban and rural areas. Over 20 years, the average VEQI of the study region ranged from 10.85% to 94.94%. Slope, DEM, and vegetation type were identified as significant drivers of VEQI, while precipitation, temperature, and nighttime light were considered secondary factors. Notably, areas in Hunan, Jiangxi, and Hubei provinces, especially the western part of Hunan, were pinpointed as spatial optimization regions. This research not only enhances the understanding of vegetation’s ecological quality in the urban agglomeration of the middle reaches of the Yangtze River but also provides scientific insights for the protection and management of vegetation.","PeriodicalId":505742,"journal":{"name":"Forests","volume":" 1174","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Sirgedaitė-Šėžienė, Ieva Čėsnienė, Dorotėja Vaitiekūnaitė
Betula pendula Roth. (silver birch) is a pioneer species in the Northern Hemisphere forests. It plays a significant role in various ecosystems, human industries, and biodiversity. Taking all this into account, understanding the genetic diversity within B. pendula populations is crucial for fully exploiting their potential, particularly regarding their production of phenolic compounds and antioxidants. We tested the non-enzymatic and enzymatic antioxidant activity in seven silver birch half-sib family leaves. Spectrophotometric data from leaf extracts showed that there was a significant variation between families in terms of total phenol content (TPC) and antioxidant enzyme (superoxide dismutase, peroxidase (POX), catalase, glutathione reductase, and ascorbate peroxidase) levels. The data were gathered during two consecutive seasons, resulting in a variance in antioxidant production, which generally increased in the tested families during the second year (except for POX) as opposed to the first vegetative season. For example, SOD levels increased in the second year by 15% to 243% and TPC increased by 46%–189%, depending on the half-sib family. A more thorough study of this variation should prove beneficial in various research fields, ranging from climate change to cosmetics.
{"title":"Temporal Variations in Enzymatic and Non-Enzymatic Antioxidant Activity in Silver Birch (Betula pendula Roth.): The Genetic Component","authors":"V. Sirgedaitė-Šėžienė, Ieva Čėsnienė, Dorotėja Vaitiekūnaitė","doi":"10.3390/f15071262","DOIUrl":"https://doi.org/10.3390/f15071262","url":null,"abstract":"Betula pendula Roth. (silver birch) is a pioneer species in the Northern Hemisphere forests. It plays a significant role in various ecosystems, human industries, and biodiversity. Taking all this into account, understanding the genetic diversity within B. pendula populations is crucial for fully exploiting their potential, particularly regarding their production of phenolic compounds and antioxidants. We tested the non-enzymatic and enzymatic antioxidant activity in seven silver birch half-sib family leaves. Spectrophotometric data from leaf extracts showed that there was a significant variation between families in terms of total phenol content (TPC) and antioxidant enzyme (superoxide dismutase, peroxidase (POX), catalase, glutathione reductase, and ascorbate peroxidase) levels. The data were gathered during two consecutive seasons, resulting in a variance in antioxidant production, which generally increased in the tested families during the second year (except for POX) as opposed to the first vegetative season. For example, SOD levels increased in the second year by 15% to 243% and TPC increased by 46%–189%, depending on the half-sib family. A more thorough study of this variation should prove beneficial in various research fields, ranging from climate change to cosmetics.","PeriodicalId":505742,"journal":{"name":"Forests","volume":"5 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Leaf Area Index (LAI) plays a crucial role in assessing the health of forest ecosystems. This study utilized ICESat-2/ATLAS as the primary information source, integrating 51 measured sample datasets, and employed the Sequential Gaussian Conditional Simulation (SGCS) method to derive surface grid information for the study area. The backscattering coefficient and texture feature factor from Sentinel-1, as well as the spectral band and vegetation index factors from Sentinel-2, were integrated. The random forest (RF), gradient-boosted regression tree (GBRT) model, and K-nearest neighbor (KNN) method were employed to construct the LAI estimation model. The optimal model, RF, was selected to conduct accuracy analysis of various remote sensing data combinations. The spatial distribution map of Dendrocalamus giganteus in Xinping County was then generated using the optimal combination model. The findings reveal the following: (1) Four key parameters—optimal fitted segmented terrain height, interpolated terrain surface height, absolute mean canopy height, and solar elevation angle—are significantly correlated. (2) The RF model constructed using a combination of ICESat-2/ATLAS, Sentinel-1, and Sentinel-2 data achieved optimal accuracy, with a coefficient of determination (R2) of 0.904, root mean square error (RMSE) of 0.384, mean absolute error (MAE) of 0.319, overall estimation accuracy (P1) of 88.96%, and relative root mean square error (RRMSE) of 11.04%. (3) The accuracy of LAI estimation using a combination of ICESat-2/ATLAS, Sentinel-1, and Sentinel-2 remote sensing data showed slight improvement compared to using either ICESat-2/ATLAS data combined with Sentinel-1 or Sentinel-2 data alone, with a significant enhancement in LAI estimation accuracy compared to using ICESat-2/ATLAS data alone. (4) LAI values in the study area ranged mainly from 2.29 to 2.51, averaging 2.4. Research indicates that employing ICESat-2/ATLAS spaceborne LiDAR data for regional-scale LAI estimation presents clear advantages. Incorporating SAR data and optical imagery and utilizing diverse data types for complementary information significantly enhances the accuracy of LAI estimation, demonstrating the feasibility of LAI inversion with multi-source remote sensing data. This approach offers an innovative framework for utilizing multi-source remote sensing data for regional-scale LAI inversion, demonstrates a methodology for integrating various remote sensing data, and serves as a reference for low-cost high-precision regional-scale LAI estimation.
叶面积指数（LAI）在评估森林生态系统健康状况方面起着至关重要的作用。本研究利用 ICESat-2/ATLAS 作为主要信息源，整合了 51 个实测样本数据集，并采用序列高斯条件模拟（SGCS）方法得出研究区域的地表网格信息。集成了哨兵-1 的后向散射系数和纹理特征因子，以及哨兵-2 的光谱波段和植被指数因子。采用随机森林（RF）、梯度增强回归树（GBRT）模型和 K-nearest neighbor（KNN）方法构建 LAI 估算模型。在对各种遥感数据组合进行精度分析时，选择了最优模型 RF。然后利用最优组合模型生成了新平县石斛的空间分布图。研究结果表明(1）四个关键参数--最佳拟合分割地形高度、内插地形表面高度、树冠绝对平均高度和太阳仰角--具有显著的相关性。(2）利用 ICESat-2/ATLAS、Sentinel-1 和 Sentinel-2 数据组合构建的射频模型达到了最佳精度，其判定系数（R2）为 0.904，均方根误差（RMSE）为 0.384，平均绝对误差（MAE）为 0.319，总体估计精度（P1）为 88.96%，相对均方根误差（RRMSE）为 11.04%。(3）与单独使用ICESat-2/ATLAS、Sentinel-1和Sentinel-2遥感数据相比，综合使用ICESat-2/ATLAS、Sentinel-1和Sentinel-2遥感数据估算LAI的精度略有提高，与单独使用ICESat-2/ATLAS数据相比，LAI估算精度显著提高。(4) 研究区域的 LAI 值主要介于 2.29 至 2.51 之间，平均值为 2.4。研究表明，利用 ICESat-2/ATLAS 星载激光雷达数据进行区域尺度 LAI 估算具有明显优势。结合合成孔径雷达数据和光学图像，利用不同数据类型的互补信息，大大提高了 LAI 估算的准确性，证明了利用多源遥感数据进行 LAI 反演的可行性。该方法为利用多源遥感数据进行区域尺度 LAI 反演提供了一个创新框架，展示了整合各种遥感数据的方法，为低成本高精度区域尺度 LAI 估算提供了参考。
{"title":"Estimation of Leaf Area Index for Dendrocalamus giganteus Based on Multi-Source Remote Sensing Data","authors":"Zhen Qin, Huanfen Yang, Qingtai Shu, Jinge Yu, Li Xu, Mingxing Wang, Cuifen Xia, Dandan Duan","doi":"10.3390/f15071257","DOIUrl":"https://doi.org/10.3390/f15071257","url":null,"abstract":"The Leaf Area Index (LAI) plays a crucial role in assessing the health of forest ecosystems. This study utilized ICESat-2/ATLAS as the primary information source, integrating 51 measured sample datasets, and employed the Sequential Gaussian Conditional Simulation (SGCS) method to derive surface grid information for the study area. The backscattering coefficient and texture feature factor from Sentinel-1, as well as the spectral band and vegetation index factors from Sentinel-2, were integrated. The random forest (RF), gradient-boosted regression tree (GBRT) model, and K-nearest neighbor (KNN) method were employed to construct the LAI estimation model. The optimal model, RF, was selected to conduct accuracy analysis of various remote sensing data combinations. The spatial distribution map of Dendrocalamus giganteus in Xinping County was then generated using the optimal combination model. The findings reveal the following: (1) Four key parameters—optimal fitted segmented terrain height, interpolated terrain surface height, absolute mean canopy height, and solar elevation angle—are significantly correlated. (2) The RF model constructed using a combination of ICESat-2/ATLAS, Sentinel-1, and Sentinel-2 data achieved optimal accuracy, with a coefficient of determination (R2) of 0.904, root mean square error (RMSE) of 0.384, mean absolute error (MAE) of 0.319, overall estimation accuracy (P1) of 88.96%, and relative root mean square error (RRMSE) of 11.04%. (3) The accuracy of LAI estimation using a combination of ICESat-2/ATLAS, Sentinel-1, and Sentinel-2 remote sensing data showed slight improvement compared to using either ICESat-2/ATLAS data combined with Sentinel-1 or Sentinel-2 data alone, with a significant enhancement in LAI estimation accuracy compared to using ICESat-2/ATLAS data alone. (4) LAI values in the study area ranged mainly from 2.29 to 2.51, averaging 2.4. Research indicates that employing ICESat-2/ATLAS spaceborne LiDAR data for regional-scale LAI estimation presents clear advantages. Incorporating SAR data and optical imagery and utilizing diverse data types for complementary information significantly enhances the accuracy of LAI estimation, demonstrating the feasibility of LAI inversion with multi-source remote sensing data. This approach offers an innovative framework for utilizing multi-source remote sensing data for regional-scale LAI inversion, demonstrates a methodology for integrating various remote sensing data, and serves as a reference for low-cost high-precision regional-scale LAI estimation.","PeriodicalId":505742,"journal":{"name":"Forests","volume":" 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The productivity of forests in sub-Saharan Africa is often summarized into large compartments or site classes. However, the classification of forest productivity levels based on the original site index model in Tanzania and the techniques applied to generate the model did not include the micro-toposequence variations within compartments. This may create false expectations of wood supply and hinder the estimation of sustainable harvesting processes. This study analyzed variations in forest productivity and the site index in P. patula stands in two forest plantations of Tanzania to assess the applicability and generality of the present site classification system. We used dominant height as a proxy for forest productivity in 48 plots at the Sao Hill forest plantation (SHFP) and 24 plots at the Shume forest plantation (SFP). We stratified the sampling plots in each site class along the soil catena and recorded the elevation, slope, and slope positions (summit, mid, and lower). Our results showed that the site classes did not generally match the previously assigned site classes and the productivity of a given site class varied between the two plantations. We found a consistently higher productivity than that implied by the original site index in SFP, while in SHFP, the productivity was both higher and lower than estimated in different compartments. Both elevations and slope significantly contributed to predicting the productivity variations within site classes. Overall, the results indicate that physiographic factors affect variations in forest productivity within the assigned site classes. We recommend a more comprehensive site productivity assessment that takes into account physiographic variations and hence provides more accurate information for sustainable forest plantation management in Tanzania and in the region at large.
撒哈拉以南非洲地区的森林生产力通常被归纳为大型区块或地点等级。然而，根据坦桑尼亚最初的地点指数模型对森林生产力水平进行的分类以及用于生成该模型的技术并不包括区块内的微观地形变化。这可能会造成对木材供应的错误预期，并阻碍对可持续采伐过程的估计。本研究分析了坦桑尼亚两个人工林中 P. patula 林分的森林生产力和林地指数的变化，以评估现有林地分类系统的适用性和通用性。我们在 Sao Hill 人工林（SHFP）的 48 个地块和 Shume 人工林（SFP）的 24 个地块中使用优势高度作为森林生产力的替代指标。我们将每个地点等级的采样地块沿土壤导管分层，并记录了海拔、坡度和坡度位置（山顶、山中和山下）。我们的结果表明，地块等级与之前分配的地块等级基本不一致，而且两个种植园中特定地块等级的生产力也各不相同。我们发现，在南坡种植园，生产率始终高于原始地点指数所隐含的生产率，而在北坡种植园，生产率既高于也低于不同区域的估计值。海拔高度和坡度对预测不同地块内的生产力变化有重要作用。总之，研究结果表明，地貌因素会影响指定地点等级内森林生产力的变化。我们建议进行更全面的地点生产力评估，将地貌变化考虑在内，从而为坦桑尼亚乃至整个地区的可持续人工林管理提供更准确的信息。
{"title":"Variations in the Forest Productivity of Pinus patula Plantations in Tanzania: The Need for an Improved Site Classification System","authors":"J. Maguzu, U. Ilstedt, J. Katani, S. Maliondo","doi":"10.3390/f15071247","DOIUrl":"https://doi.org/10.3390/f15071247","url":null,"abstract":"The productivity of forests in sub-Saharan Africa is often summarized into large compartments or site classes. However, the classification of forest productivity levels based on the original site index model in Tanzania and the techniques applied to generate the model did not include the micro-toposequence variations within compartments. This may create false expectations of wood supply and hinder the estimation of sustainable harvesting processes. This study analyzed variations in forest productivity and the site index in P. patula stands in two forest plantations of Tanzania to assess the applicability and generality of the present site classification system. We used dominant height as a proxy for forest productivity in 48 plots at the Sao Hill forest plantation (SHFP) and 24 plots at the Shume forest plantation (SFP). We stratified the sampling plots in each site class along the soil catena and recorded the elevation, slope, and slope positions (summit, mid, and lower). Our results showed that the site classes did not generally match the previously assigned site classes and the productivity of a given site class varied between the two plantations. We found a consistently higher productivity than that implied by the original site index in SFP, while in SHFP, the productivity was both higher and lower than estimated in different compartments. Both elevations and slope significantly contributed to predicting the productivity variations within site classes. Overall, the results indicate that physiographic factors affect variations in forest productivity within the assigned site classes. We recommend a more comprehensive site productivity assessment that takes into account physiographic variations and hence provides more accurate information for sustainable forest plantation management in Tanzania and in the region at large.","PeriodicalId":505742,"journal":{"name":"Forests","volume":" 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141827046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Understanding the response of ecological quality (EQ) to forest landscape connectivity is essential to global biodiversity conservation and national ecological security. However, quantitatively measuring the properties and intensities within these relationships from a spatial heterogeneity perspective remains challenging. This study takes the Fujian Delta region as its case study. The Google Earth Engine platform was employed to compute the remote sensing ecological index (RSEI), the landscape metrics were applied to represent the structural connectivity of the forest landscape, and the minimum cumulative resistance model was adopted to measure the cost distance index representing the functional connectivity of the forest landscape. Then, the spatial correlation and heterogeneity between the EQ and forest landscape connectivity were analyzed based on spatial autocorrelation and geographical weighted regression at three scales (3, 4, and 5 km). The results showed the following: (1) from 2000 to 2020, the overall EQ increased, improving in 37.5% of the region and deteriorating in 13.8% of the region; (2) the forest landscape structural and functional connectivity showed a small decreasing trend from 2000 to 2020, decreasing by 1.3% and 0.9%, respectively; (3) eight forest landscape structural and functional connectivity change modes were detected under the conditions of an improving or degrading EQ based on the change in RSEI and forest landscape structural and functional connectivity; (4) the geographical weighted regression results showed that compared with the forest landscape structural connectivity index, the cost distance index had the highest explanatory power to RSEI in different scales. The effect of forest landscape functional connectivity on EQ is greater than that of structural connectivity. It provides a scientific reference for ecological environmental monitoring and the ecological conservation decision-making of managers.
{"title":"Spatiotemporal Changes in Ecological Quality and Its Response to Forest Landscape Connectivity—A Study from the Perspective of Landscape Structural and Functional Connectivity","authors":"Miaomiao Liu, Guanmin Liang, Ziyi Wu, Xueman Zuo, Xisheng Hu, Sen Lin, Zhilong Wu","doi":"10.3390/f15071248","DOIUrl":"https://doi.org/10.3390/f15071248","url":null,"abstract":"Understanding the response of ecological quality (EQ) to forest landscape connectivity is essential to global biodiversity conservation and national ecological security. However, quantitatively measuring the properties and intensities within these relationships from a spatial heterogeneity perspective remains challenging. This study takes the Fujian Delta region as its case study. The Google Earth Engine platform was employed to compute the remote sensing ecological index (RSEI), the landscape metrics were applied to represent the structural connectivity of the forest landscape, and the minimum cumulative resistance model was adopted to measure the cost distance index representing the functional connectivity of the forest landscape. Then, the spatial correlation and heterogeneity between the EQ and forest landscape connectivity were analyzed based on spatial autocorrelation and geographical weighted regression at three scales (3, 4, and 5 km). The results showed the following: (1) from 2000 to 2020, the overall EQ increased, improving in 37.5% of the region and deteriorating in 13.8% of the region; (2) the forest landscape structural and functional connectivity showed a small decreasing trend from 2000 to 2020, decreasing by 1.3% and 0.9%, respectively; (3) eight forest landscape structural and functional connectivity change modes were detected under the conditions of an improving or degrading EQ based on the change in RSEI and forest landscape structural and functional connectivity; (4) the geographical weighted regression results showed that compared with the forest landscape structural connectivity index, the cost distance index had the highest explanatory power to RSEI in different scales. The effect of forest landscape functional connectivity on EQ is greater than that of structural connectivity. It provides a scientific reference for ecological environmental monitoring and the ecological conservation decision-making of managers.","PeriodicalId":505742,"journal":{"name":"Forests","volume":" 93","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141824480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yaroslav Lebedev, A. Drygval, Cam Nhung Pham, R. Gorbunov, T. Gorbunova, Andrei Kuznetsov, Svetlana Kuznetsova, Van Thinh Nguyen, V. Tabunshchik
Expeditionary studies of the functioning of landscapes of mid-mountain monsoon (including fog) forests have been being conducted within the landscape and ecological station in the territory of the Bidoup-Nui Ba National Park and the adjacent Hon Giao since 2018 and are currently underway. One of the research objectives is to clarify the biogeochemical migrations of the material composition of soils in the “leaf debris–soil” system. We have consistently studied natural objects for their material composition as well as the intensity and rate of involvement of chemical elements in physicochemical migration processes in the “leaf debris–soil” system. Our findings indicate an active influx of a select group of examined elements (Se, Pd, Ag, Cd, Sn, Bi), particularly Bi, Pd, Se, and Cd, through the leaf debris and the detachment of aboveground plant organs, warranting their integration into organogenic soil horizons. Subsequently, lateral migration (Pd, Cd, Se) ensues. Slope processes within subordinate landscape facets, in addition to soil moisture and aeration processes, contribute to the subsequent redistribution of elemental volumes introduced into organogenic soil horizons.
{"title":"Biogeochemical Migration of Some Rare Elements in the “Leaf Debris–Soil” System of the Catenary Landscapes in Tropical Mountainous Forests in Southern Vietnam","authors":"Yaroslav Lebedev, A. Drygval, Cam Nhung Pham, R. Gorbunov, T. Gorbunova, Andrei Kuznetsov, Svetlana Kuznetsova, Van Thinh Nguyen, V. Tabunshchik","doi":"10.3390/f15071251","DOIUrl":"https://doi.org/10.3390/f15071251","url":null,"abstract":"Expeditionary studies of the functioning of landscapes of mid-mountain monsoon (including fog) forests have been being conducted within the landscape and ecological station in the territory of the Bidoup-Nui Ba National Park and the adjacent Hon Giao since 2018 and are currently underway. One of the research objectives is to clarify the biogeochemical migrations of the material composition of soils in the “leaf debris–soil” system. We have consistently studied natural objects for their material composition as well as the intensity and rate of involvement of chemical elements in physicochemical migration processes in the “leaf debris–soil” system. Our findings indicate an active influx of a select group of examined elements (Se, Pd, Ag, Cd, Sn, Bi), particularly Bi, Pd, Se, and Cd, through the leaf debris and the detachment of aboveground plant organs, warranting their integration into organogenic soil horizons. Subsequently, lateral migration (Pd, Cd, Se) ensues. Slope processes within subordinate landscape facets, in addition to soil moisture and aeration processes, contribute to the subsequent redistribution of elemental volumes introduced into organogenic soil horizons.","PeriodicalId":505742,"journal":{"name":"Forests","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141825963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bursaphelenchus xylophilus is a pest that interferes with the health of forests and hinders the development of the forestry industry, and its spread is influenced by changes in abiotic factors and human activities. The potential distribution areas of B. xylophilus in China under four shared-economic pathways were predicted using the optimized MaxEnt model (version 3.4.3), combining data from a variety of environmental variables: (1) prediction of natural environmental variables predicted under current climate models; (2) prediction of natural environmental variables + human activities under current climate models; and (3) prediction of natural environmental variables under the future climate models (2050s and 2070s). Meanwhile, whether the niche of B. xylophilus has changed over time is analyzed. The results showed that human activities, precipitation in the driest month, annual precipitation, and elevation had significant effects on the distribution of B. xylophilus. In the current conditions, human activities greatly reduced the survival area of B. xylophilus, and its suitable distribution area was mainly concentrated in the southwestern and central regions of China. Under the influence of climate change in the future, the habitat of B. xylophilus will gradually spread to the northeast. In addition, the ecological niche overlap analysis showed that B. xylophilus in future climate was greater than 0.74. This study provides important information for understanding the ecological adaptation and potential risk of B. xylophilus, which can help guide the decision making of pest control and forest protection.
{"title":"Evaluating the Impact of Climate Change and Human Activities on the Potential Distribution of Pine Wood Nematode (Bursaphelenchus xylophilus) in China","authors":"Liang Zhang, Ping Wang, G. Xie, Wenkai Wang","doi":"10.3390/f15071253","DOIUrl":"https://doi.org/10.3390/f15071253","url":null,"abstract":"Bursaphelenchus xylophilus is a pest that interferes with the health of forests and hinders the development of the forestry industry, and its spread is influenced by changes in abiotic factors and human activities. The potential distribution areas of B. xylophilus in China under four shared-economic pathways were predicted using the optimized MaxEnt model (version 3.4.3), combining data from a variety of environmental variables: (1) prediction of natural environmental variables predicted under current climate models; (2) prediction of natural environmental variables + human activities under current climate models; and (3) prediction of natural environmental variables under the future climate models (2050s and 2070s). Meanwhile, whether the niche of B. xylophilus has changed over time is analyzed. The results showed that human activities, precipitation in the driest month, annual precipitation, and elevation had significant effects on the distribution of B. xylophilus. In the current conditions, human activities greatly reduced the survival area of B. xylophilus, and its suitable distribution area was mainly concentrated in the southwestern and central regions of China. Under the influence of climate change in the future, the habitat of B. xylophilus will gradually spread to the northeast. In addition, the ecological niche overlap analysis showed that B. xylophilus in future climate was greater than 0.74. This study provides important information for understanding the ecological adaptation and potential risk of B. xylophilus, which can help guide the decision making of pest control and forest protection.","PeriodicalId":505742,"journal":{"name":"Forests","volume":" 27","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141826410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jeong-Woo Seo, Kahye Kim, S. Kim, Jiyune Yi, Won-sop Shin, Jungmi Choi, Jaeuk U. Kim
The purpose of this study is to more quantitatively identify changes in body function through various bio-signal parameters. (1) Background: Forest therapy is effective in stabilizing cognitive, emotional, cardiovascular, and autonomic nervous systems. In particular, it is necessary to more quantitatively confirm changes in body functions through various bio signals. (2) Methods: As a forest therapy program (FTP) for the elderly, it consisted of strength training in the forest, respiratory aerobic exercises, and cognitive function training, and a total of 19 sessions were performed for 12 weeks. The electroencephalography (EEG) and Photoplethysmography (PPG) before and after the program were measured and compared between program participants (FTP group) and non-participants (control group). (3) Results: the FTP group showed increase in the alpha band power in EEG and a decrease in the PRV index, Tad, and Tae after the program compared to the control group; (4) Conclusions: Significant differences occurred in the physiological functioning of the elderly participants after the program. This is a result that can confirm the effectiveness of forest therapy more quantitatively. Forest therapy has a positive effect on mental stress reduction and cardiovascular function.
{"title":"Evaluation of the Effectiveness of the Elderly Cognitive and Exercise Forest Therapy Program According to Brain Wave and Autonomic Nervous System Parameters","authors":"Jeong-Woo Seo, Kahye Kim, S. Kim, Jiyune Yi, Won-sop Shin, Jungmi Choi, Jaeuk U. Kim","doi":"10.3390/f15071249","DOIUrl":"https://doi.org/10.3390/f15071249","url":null,"abstract":"The purpose of this study is to more quantitatively identify changes in body function through various bio-signal parameters. (1) Background: Forest therapy is effective in stabilizing cognitive, emotional, cardiovascular, and autonomic nervous systems. In particular, it is necessary to more quantitatively confirm changes in body functions through various bio signals. (2) Methods: As a forest therapy program (FTP) for the elderly, it consisted of strength training in the forest, respiratory aerobic exercises, and cognitive function training, and a total of 19 sessions were performed for 12 weeks. The electroencephalography (EEG) and Photoplethysmography (PPG) before and after the program were measured and compared between program participants (FTP group) and non-participants (control group). (3) Results: the FTP group showed increase in the alpha band power in EEG and a decrease in the PRV index, Tad, and Tae after the program compared to the control group; (4) Conclusions: Significant differences occurred in the physiological functioning of the elderly participants after the program. This is a result that can confirm the effectiveness of forest therapy more quantitatively. Forest therapy has a positive effect on mental stress reduction and cardiovascular function.","PeriodicalId":505742,"journal":{"name":"Forests","volume":" 86","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141825058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aimed to evaluate the growth, wood properties, disease susceptibility, and sex traits of 1122 Populus deltoides clones to reveal the trait variability and correlations, providing a basis for genetic improvement and breeding. The measurements included the diameter at breast height (DBH), leaf area, basic wood density (BWD), content of cellulose, hemicellulose, lignin, and disease susceptibility index (DSI). The coefficients of variation ranged 6.91%–41.96%, with the BWD showing the lowest variability. Significant sexual dimorphism was observed, with male clones exhibiting higher DBH and hemicellulose content, and female clones displaying larger leaf areas and greater phenotypic variability. Correlation analysis revealed that the leaf area was positively correlated with the BWD and hemicellulose, and it was negatively correlated with the DBH and lignin; lignin was negatively correlated with cellulose. PCA confirmed these relationships and additionally highlighted a positive correlation between the DSI and DBH. These findings established links between the growth traits and wood properties, enhancing our understanding of trait diversity in P. deltoides and providing insights for breeding strategies to develop high-quality, high-yielding cultivars.
{"title":"Trait Assessment of 1122 Populus deltoides Clones: Unveiling Correlations among Growth, Wood Properties, and Disease Susceptibility","authors":"Tianyu Ma, Jing Hou","doi":"10.3390/f15071250","DOIUrl":"https://doi.org/10.3390/f15071250","url":null,"abstract":"This study aimed to evaluate the growth, wood properties, disease susceptibility, and sex traits of 1122 Populus deltoides clones to reveal the trait variability and correlations, providing a basis for genetic improvement and breeding. The measurements included the diameter at breast height (DBH), leaf area, basic wood density (BWD), content of cellulose, hemicellulose, lignin, and disease susceptibility index (DSI). The coefficients of variation ranged 6.91%–41.96%, with the BWD showing the lowest variability. Significant sexual dimorphism was observed, with male clones exhibiting higher DBH and hemicellulose content, and female clones displaying larger leaf areas and greater phenotypic variability. Correlation analysis revealed that the leaf area was positively correlated with the BWD and hemicellulose, and it was negatively correlated with the DBH and lignin; lignin was negatively correlated with cellulose. PCA confirmed these relationships and additionally highlighted a positive correlation between the DSI and DBH. These findings established links between the growth traits and wood properties, enhancing our understanding of trait diversity in P. deltoides and providing insights for breeding strategies to develop high-quality, high-yielding cultivars.","PeriodicalId":505742,"journal":{"name":"Forests","volume":" 41","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141827439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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