Rapid Urbanization Induced Extensive Forest Loss to Urban Land in the Guangdong-Hong Kong-Macao Greater Bay Area, China

China has experienced rapid urbanizations with dramatic land cover changes since 1978. Forest loss is one of land cover changes, and it induces various eco-environmental degradation issues. As one of China’s hotspot regions, the Guangdong-Hong KongMacao Greater Bay Area(GBA) has undergone a dramatic urban expansion. To better understand forest dynamics and protect forest ecosystem, revealing the processes, patterns and underlying drivers of forest loss is essential. This study focused on the spatiotemporal evolution and potential driving factors of forest loss in the GBA at regional and city level. The Landsat time-series images from 1987 to2017 were used to derive forest, and landscape metrics and geographic information system(GIS) were applied to implement further spatial analysis. The results showed that: 1) 14.86% of the total urban growth area of the GBA was obtained from the forest loss in1987–2017;meanwhile, the forest loss area of the GBA reached 4040.6 km2, of which 25.60%(1034.42 km2) was converted to urban land;2) the percentages of forest loss to urban land in Dongguan(19.14%), Guangzhou(18.35%) and Shenzhen(15.81%) were higher than those in other cities;3) the forest became increasingly fragmented from 1987–2007, and then the fragmentation decreased from2007 to 2017);4) the landscape responses to forest changes varied with the scale;and 5) some forest loss to urban regions moved from low-elevation and gentle-slope terrains to higher-elevation and steep-slope terrains over time, especially in Shenzhen and Hong Kong.Urbanization and industrialization greatly drove forest loss and fragmentation, and, notably, hillside urban land expansion may have contributed to hillside forest loss. The findings will help policy makers in maintaining the stability of forest ecosystems, and provide some new insights into forest management and conservation.

Spatiotemporal changes in forest loss and its linkage to burned areas in China

Fire-induced forest loss has substantially increased worldwide over the last decade.In China,the connection between forest loss and frequent fi res on a national scale remains largely unexplored.In this study,we used a data set for a time-series of forest loss from the Global Forest Watch and for a MODIS-derived burned area for 2003–2015 to ascertain variations in forest loss and to explore its relationship with forest fi res(represented by burned areas)at the country-and forest-zone levels.We quantifi ed trends in forest loss during 2003–2015 using linear regression analysis and assessed the relation between forest loss and burned areas using Spearman’s correlation.Forest loss increased signifi cantly(264.8 km 2 a−1;R 2=0.54,p<0.01)throughout China,with an average annual increase of 11.4%during 2003–2015.However,the forest loss trend had extensive spatial heterogeneity.Forest loss increased mainly in the subtropical evergreen broadleaf forest zone(315.0 km 2 a−1;R 2=0.69,p<0.01)and tropical rainforest zone(38.8 km 2 a−1;R 2=0.66,p<0.01),but the loss of forest decreased in the cold temperate deciduous coniferous forest zone(−70.8 km 2 year−1;R 2=0.75,p<0.01)and the temperate deciduous mixed broadleaf and coniferous forest zone(−14.4 km 2 a−1;R 2=0.45,p<0.05).We found that 1.0%of China’s area had a signifi cant positive correlation(r≥0.55,p<0.05)with burned areas and 0.3%had a signifi cant negative correlation(r≤−0.55,p<0.05).In particular,forest loss had a signifi cant positive relationship with the burned area in the cold temperate deciduous coniferous forest zone(16.9% of the lands)and the subtropical evergreen broadleaf forest zone(7.8%).These results provide a basis for future predictions of fi re-induced forest loss in China.

Simulating long-term effect of Hyrcanian forest loss on phosphorus loading at the sub-watershed level

Conversion of forest land to farmland in the Hyrcanian forest of northern Iran increases the nutrient input, especially the phosphorus（P） nutrient, thus impacting the water quality. Modeling the effect of forest loss on surface water quality provides valuable information for forest management. This study predicts the future impacts of forest loss between 2010 and 2040 on P loading in the Tajan River watershed at the sub-watershed level. To understand drivers of the land cover, we used Land Change Modeler（LCM） combining with the Soil Water Assessment Tool（SWAT） model to simulate the impacts of land use change on P loading. We characterized priority management areas for locating comprehensive and cost-effective management practices at the sub-watershed level. Results show that agricultural expansion has led to an intense deforestation. During the future period 2010–2040, forest area is expected to decrease by 34,739 hm^2. And the areas of pasture and agriculture are expected to increase by 7668 and 27,071 hm^2, respectively. In most sub-watersheds, P pollution will be intensified with the increase in deforestation by the year 2040. And the P concentration is expected to increase from 0.08 to 2.30 mg/L in all of sub-watersheds by the year 2040. It should be noted that the phosphorous concentration exceeds the American Public Health Association′s water quality standard of 0.2 mg/L for P in drinking water in both current and future scenarios in the Tajan River watershed. Only 30% of sub-watersheds will comply with the water quality standards by the year 2040. The finding of the present study highlights the importance of conserving forest area to maintain a stable water quality.

LOSS ASSESSMENT OF BURNED FOREST USING REMOTE SENSING AND GEOGRAPHICAL INFORMATION TECHNIQUES

After forest fire, it is very needed to locate fire position and assess the loss of forest resources. In this paper, a method of burned forest assessment with satellite remote sensing data and over-laying techniques is discussed and used in the assessment of the burned forest in Malin Forest Farm after the large forest fire of May, 1987.

Swamp Forest Use and Loss in the Niger Delta: Contextual and Underlying Issues

Forest ecosystems are vital not only for the ecosystem and biogeochemical processes, but also for the livelihood of forest dependent communities for which its continual existence is a necessity. This study explored the pattern of forest use in the hinterlands of the Niger Delta and sought to elucidate the drivers of forest loss and how the ownership and management of the forest plots influenced the changes in the forest ecosystem. Ecosystem services reduction and forest loss/degradation were found to be increasing over the years due to crude oil activities, urbanization/developments, population increase, agricultural activities and natural causes like flood. While each factor contributed to forest loss directly and indirectly, and varied from community to community, agricultural activities and population growth were responsible for most of the losses across the landscape. Even though agricultural activities were essential and thrived in the region, sustainable forest (land) uses could have reduced the associated implications of such land uses;but this was however hampered by the farming practises (shifting cultivation) across most of the communities. Lack of proper, effective and sustainable forest management structures, poor individual commitment and monitoring of forest activities were found to encourage forest loss at different spatial scales. Provision of alternative sources of livelihood and ensuring that suitable guidelines on forest abstraction and harvest are enforced across the region, are steps to promoting biodiversity conservation and resource management.

中国农田磷流失风险评价及其关键驱动因素

农田面源磷流失是农业面源污染的重要原因之一,识别流域内农田磷流失风险的关键源区及其影响因子是面源污染控制的重要手段。基于磷指数模型开展2000—2020年中国农田磷流失风险评估,选取土壤有效磷含量、磷肥施用量为源因子,土壤侵蚀模数、年径流深、农田和水体间归一化距离指数为迁移因子,结合GIS技术评估了中国农田磷流失的关键源区;在此基础上,利用随机森林法分析影响中国农田磷流失的关键因子,并通过结构方程模型揭示了农田磷流失风险指数与各因子的关系。结果表明:1)2000—2020年中国农田的磷流失的低、中、高、极高风险面积分别占农田总面积的43.8%、40.5%、13.4%、2.4%。2)中国农田磷流失在2000、2005、2010、2015、2020年高风险和极高风险总面积的年平均占比从大到小依次为:淮河流域、长江流域、珠江流域、东南诸河流域、松辽河流域、西南诸河流域、黄河流域、内陆河流域、海河流域。3)影响农田磷流失风险的关键源因子和迁移因子分别为土壤有效磷含量和归一化距离指数,其重要性特征值分别为129.53和65.12,土壤有效磷含量是农田磷流失最主要影响因子。4)磷流失风险指数与源因子指数、迁移因子指数呈极显著正相关,选取的14个指标对磷指数的解释度达0.62,其中源因子和迁移因子对磷指数的贡献率分别为0.77、0.19(P <0.001)。研究结果可为中国农田磷流失风险评估提供科学参考,对中国农业面源污染的宏观防控及战略决策具有重要意义。

福建省县域森林损失时空演变特征及其影响因素分析

森林是陆地生物圈重要的生态资源,厘清区域长期森林损失状况及其影响因素,对森林资源保护和社会经济协调发展具有重要意义。基于全球森林变化(Global Forest Change)数据集,利用ArcGIS 10.8空间分析技术,对2001—2019年福建省58个县域森林损失的时空演变特征进行分析,并结合时空地理加权回归模型,探究县域森林损失的主要影响因素及其时空分异特征。结果表明:(1)2001—2019年福建省县域森林损失率呈波动上升的基本态势,森林损失面积累计达112.89万hm^(2),森林损失情况可划分为显著上升阶段、先降后升阶段和显著下降阶段。(2)整体上,福建省县域森林损失具有较强的空间正相关性和空间集聚性特征,相邻区域森林损失率的空间相关性显著,而其空间集聚效应呈现西北低、东南高的基本态势。(3)城镇化率、人均GDP、公路通车里程、人口密度和木材产量对福建省县域森林损失均具有一定的影响,但存在明显的时空异质性特征。该研究有效揭示了福建省县域森林损失时空动态特征及其影响因素,可为森林资源可持续经营提供理论依据。

基于随机森林方法的地震损失预测

针对现有的基于实际震害评估的大多研究仅限于某特定区域和某种结构类型,且所采用的数据样本量也十分有限,本文基于随机森林模型,采用2011年3月11日东日本MW9.0地震的37万8037条建筑物实际震害数据,利用美国应用技术协会发布的地震震害等级划分标准(ATC-13)预测了建筑物地震破坏所引起的损失,对建筑物损失的影响因素进行了特征重要性分析。结果显示:通过合成少数类过采样技术(SMOTE)解决数据不均衡和贝叶斯优化超参数之后,得到了基于随机森林的预测模型测试集的准确率为68.8%,轻微破坏、中等破坏、严重破坏、倒塌等四种破坏等级的召回率分别为65.0%,53.6%,74.8%,81.8%;考虑生命安全性能将模型转换为二分类之后,模型准确率进一步提高至87.5%,极大地改善了现有研究应用于建筑损失预测中数据样本量受限、数据不均衡等导致的最严重破坏等级精度低等问题。对随机森林模型特征重要性的研究表明:震中距、峰值加速度和vS30是最影响模型输出的特征。

基于随机森林的地震灾害直接经济损失评估研究——以中国西部地区为例

为快速评估地震直接经济损失,针对我国西部地区,尝试采用随机森林机器学习回归算法,以1993—2017年震害数据为基础,结合各年份经济数据与抗震设计数据,经特征选择与参数优化后,进行模型的训练与测试。实验结果表明,在减少模型输入特征的情况下,优化后的随机森林模型可得到更优的评估结果。通过删除含有缺失特征样本的数据预处理方法,评估模型的决定系数R2达到0.86,优于中值补齐缺失特征数据预处理下的评估模型,更适用于地震直接经济损失的评估。实例验证表明该模型评估结果与实际经济损失有较好的一致性,可为抗震救灾提供决策支持。

林下三七种植对坡面水土及碳氮流失的影响

【目的】探究天然降雨条件下不同坡度三七种植林地和自然林地的水土及碳氮流失特征,为林下种植模式的水土及碳、氮流失评估和控制提供理论依据和数据支撑。【方法】采用野外径流小区原位观测试验,以云南省寻甸县三七(Panax notoginseng(Burkill)F.H.Chen)种植林地为研究对象,对2020和2021年天然降雨条件下不同坡度(5°,10°,15°)三七种植林地和自然林地的水土及碳、氮流失特征进行对比分析,并在此基础上对水土及碳、氮流失量与降雨特征和坡度的关系进行探究。【结果】(1)三七种植林地平均总径流量、总土壤流失量分别为17.35 mm/a和14.91 t/(km^(2)·a),比自然林地分别增加了173.79%和249.43%,其中以15°坡面水土流失量最大,分别为24.10 mm/a和24.32 kg/(km^(2)·a)。(2)三七种植林地平均有机碳、全氮(TN)、氨氮(NH_(4)^(+)-N)、硝态氮(NO-3-N)流失量分别为740.62,75.97,9.55和7.26 kg/(km^(2)·a),比自然林地分别显著增加了251.44%,203.15%,220.47%和224.11%,其径流中TN和NH_(4)^(+)-N平均含量分别为0.77和0.33 mg/L。三七种植林地中,以侵蚀泥沙形式流失的有机碳和TN分别占各自总流失量的93.50%和82.01%,以地表径流流失的NH_(4)^(+)-N、NO-3-N分别占各自总流失量的62.09%和87.47%。(3)降雨量、降雨历时、5 min最大降雨强度(I 5)、10 min最大降雨强度(I 10)、30 min最大降雨强度(I 30)均与径流量、土壤流失量及碳、氮流失量呈显著或极显著正相关关系。坡度与水土和碳、氮流失量呈极显著正相关(P<0.01),可用二次函数拟合二者之间的关系(R^(2)>0.93)。【结论】三七种植林地土壤侵蚀强度属于微度侵蚀,最大土壤流失量远低于西南土石山区容许土壤流失量,且径流中TN、NH_(4)^(+)-N平均质量浓度分别低于Ⅲ、Ⅱ类地表水环境质量标准限值。三七种植林地水土及碳、氮流失量较自然林地显著增加,且随着坡度的增大急剧增大。建议在缓坡地段种植三七,以减少水土与养分流失。

基于随机森林算法的建筑物构件对地震损失的重要度分析

建筑物地震损失是从构件破坏开始的,确定建筑物构件对地震损失的重要度有助于寻找结构的抗震薄弱构件。传统的抗震研究多数关注建筑物的结构构件破坏,对非结构构件的重要性研究不足,这也造成非结构构件的地震损失远超过结构构件的地震损失。基于新西兰地震保险数据集中大量详实的建筑物地震构件损失数据,采用随机森林的特征重要性(feature importance,FI)、排列重要性(permutation importance,PI)以及SHAP值(shap_values)这3种重要性分析方法对建筑物各损失构件在总体损失中的重要性大小进行排序,并采用赋值排序相加法和归一化相加的方法统筹表示重要性排序。归一化相加法不仅能判别构件的相对重要性,还可以定量地表达不同构件的重要性差异。结果表明,在所分析的12种构件类型中,非结构构件的重要度明显高于结构构件的重要度,其中墙面装修最重要,板式基础次之,屋顶框架的重要性最弱,未来需要更加注意墙面装修和建筑基础的抗震性能。

基于Logistic回归模型的噪声作业工人高频听力损伤影响因素分析

为确定造成听力损伤的关键原因,本研究采用Logistic回归模型,探究噪声环境下作业工人高频听力损伤的关键因素。通过对比噪声环境与非噪声环境工人的听力、血压等数据,结合随机森林算法评估影响因素的重要性。最后选取同时满足重要性评分最高、袋外数据袋外预测残差均方最小的影响因素作为自变量,以是否为高频听力损伤为因变量,通过Logistic回归模型分析噪声作业工人高频听力损伤的影响因素。试验结果表明,噪声对噪声作业人员身体健康具有负面影响,高频听力损伤发生率达到45.71%。经常或总是采取抗噪防护措施可降低高频听力损伤风险,而长时间噪声暴露、高强度噪声、高龄、特定工种和长时间耳机使用等因素增加了高频听力损伤的风险。

基于RF-FL-LightGBM算法的信用风险评估模型研究

为了解决大数据环境下高维度稀疏的客户信用特征以及样本不平衡问题,从而提高客户的信用评估准确度,论文提出了基于RF-FL-LightGBM算法的信用风险评估模型。首先利用随机森林(RF)对高维数据进行重要性排序和筛选,剔除容易引起模型过度拟合和冗余无效的特征;其次将基于Focal Loss函数改进后的二分类平衡交叉嫡损失函数(FL)作为LightGBM模型的损失函数,以此改善正负样本不平衡导致模型准确度降低的情况,从而提高模型的分类性能。使用某金融租赁公司的历史客户数据集进行实验,结果表明,RF-FL-LightGBM模型的F1值、AUC值都明显高于XGBoost和LigthGBM模型。RF-FL-LightGBM算法不仅有效处理了高维稀疏不平衡样本数据,还提高了客户属性的分类精确度且执行效率更高。

基于水土保持率目标导向的温州市林地水土流失防治优化策略研究

水土保持率为新时期生态保护与高质量发展的一项约束性指标,林地是温州市主要用地类型,其水土流失优化治理是提升未来一段时间内温州市水土保持率的关键。参照水利部的水土保持率目标确定方法,基于GIS/RS研究温州市林地水土流失空间分布状况。结果表明:温州市现状林地水土流失中,可完全治理水土流失面积为197.03 km^(2);不可完全治理水土流失面积为919.87 km^(2)。根据坡度、植被覆盖度等因素量化林地水土流失防治目标,结合林地建设优化温州市林地水土流失防治策略。

改良剂对红壤水土流失恢复林地土壤细菌群落结构的影响

为探究不同改良剂对红壤恢复林地土壤细菌群落结构的影响差异,提高红壤恢复林地的土壤质量和水土保持效能,本研究以亚热带红壤区马尾松(Pinus massoniana Lamb.)恢复林地为研究对象,设置原状林地(CK)和施加有机改良剂(OF)、生物炭(BF)、复合改良剂(CF)3种处理,研究其土壤化学性质、土壤细菌群落相对丰度与多样性,探讨红壤区侵蚀退化恢复林地土壤肥力与细菌群落结构微生物群落结构对不同土壤改良剂的响应,分析土壤化学性质与细菌群落结构间的相关性。结果表明:(1)不同改良剂使土壤pH值与有机碳含量分别显著(P<0.05)提高了4.20%~6.72%与40.20%~102.37%,有机改良剂使土壤全磷含量提高了56.98%(P<0.05),生物炭使土壤全氮含量提高了73.09%(P<0.05),复合改良剂使土壤全磷与全氮含量分别提高了64.57%与72.09%(P<0.05);(2)施加不同改良剂土壤细菌群落优势菌门均为变形菌门、放线菌门与酸杆菌门,优势菌纲均为酸杆菌纲、α-变形菌纲与放线菌纲;(3)所有土壤改良剂均降低了细菌群落多样性,而施加生物炭提高了土壤细菌群落丰富度;(4)土壤全磷含量对细菌群落组成产生显著影响,有机碳含量与细菌群落多样性呈负相关;(5)施加复合改良剂提高了土壤细菌群落新陈代谢通路相对丰度。本研究结果可为提升红壤区恢复林地土壤肥力,合理调节细菌群落结构提供理论支撑与数据支撑。

Optimal plot design in a multipurpose forest inventory

Background： We explore the factors affecting the optimal plot design （size and type as well as the subsample tree selection strategies within a plot） and their relative importance in defining the optimal plot design in amultipurpose forest inventory. The factors include time used to lay out the plot and to make the tree measurements within the plot, the between-plot variation of each of the variables of interest in the area, and the measurement and model errors for the different variables. Methods： We simulate different plot types and sizes and subsample tree selection strategies on measuredtest areas from North Lapland. The plot types used are fixed-radius, concentric and relascope plots. Weselect the optimal type and size first at plot level using a cost-plus-loss approach and then at cluster level byminimizing the weighted standard error with fixed budget. Results： As relascope plots are ve~/efficient at the plot level for volume and basal area, and fixed-radius plots for stems per ha, the optimal plot type strongly depends on the relative importance of these variables. The concentric plot seems to be a good compromise between these two in many cases. The subsample tree selection strategy was more important in selecting optimal plot than many other factors. In cluster level, the most important factor is the transfer time between plots. Conclusions： While the optimal radius of plots and other parameters were sensitive to the measurement times and other cost factors, the concentric plot type was optimal in almost all studied cases. Subsample tree measurement strategies need further studies, as they were an important cost factor. However, their importance to the precision was not as clear.

Effects of acid deposition on forests in south China

Acid deposition has caused serious damage to the forests of China. In this paper, the quantification theory I is used to calculate the forest volume loss caused by acid disposition in seven provinces of south China. The results showed that contribution rates of acid deposition to forest volume loss in seven provinces of south China vary from 24 5% to 37 91%; the volume loss rates range from 7% to 20%. Total volume losses per year are 1 0145×10 6 m 3, of which Zhejiang Province is the greatest, totalling 3 841×10 5 m 3, while Anhui Province is the least, amounting to 1 59×10 4 m 3.

Land Cover Change in a Freshwater Swamp Forest Landscape: Implications for Biodiversity Conservation

Forest landscapes are under much pressure globally due to changes in land use and their biodiversity and services are threatened at increasing magnitude especially in the tropics. Biodiversity and ample forest cover still remain in freshwater forest landscapes in the Niger basin of Nigeria, but are declining at astronomical scales across the region. To better understand the changes and modifications going on in the ecosystem at the landscape level, a thirty-year study (1987-2017) was conducted using remotely sensed Landsat imageries. These were processed and used to verify the dynamics in land cover changes and their major drivers. Land use change across the region reduced the forest extent and forest cover (up to 50.2 percent) of the natural ecosystems which served as the habitats for the indigenous species. Sparse vegetation and bare soil/farmlands increased over the study period and were seen as the major indices for modifications and forest loss in the area. Since land use indices such as agricultural activities were seen as one of the major factors of land cover change, sustainable forest use and management practices that accommodate agricultural practices were advocated. While the forest cover and ultimately their biodiversity and conservation prospects reduced following forest loss in the region, efforts should be targeted at conserving the pockets of vegetation seen in the sparsely vegetated zones and also maximize the potentials that the biodiversity in the agro-forested locations offers.

Effects of litter quality and climate change along an elevational gradient on litter decomposition of subalpine forests, Eastern Tibetan Plateau, China

Temperature and freeze-thaw events are two key factors controlling litter decomposition in cold biomes.Predicted global warming and changes in freeze-thaw cycles therefore may directly or indirectly impact litter decomposition in those ecosystems. Here, we conducted a2-year-long litter decomposition experiment along an elevational gradient from 3000 to 3600 m to determine the potential effects of litter quality, climate warming and freeze-thaw on the mass losses of three litter types [dragon spruce（Picea asperata Mast.）, red birch（Betula albosinensis Burk.）, and minjiang fir（Abies faxoniana Rehd. et Wild）]. Marked differences in mass loss were observed among the litter types and sampling dates. Decay constant（k） values of red birch were significantly higher than those of the needle litters. However, mass losses between elevations did not differ significantly for any litter type.During the winter, lost mass contributed 18.3-28.8 % of the net loss rates of the first year. Statistical analysis showed that the relationships between mass loss and litter chemistry or their ratios varied with decomposition periods. Our results indicated that short-term field incubations could overestimate the k value of litter decomposition.Considerable mass was lost from subalpine forest litters during the wintertime. Potential future warming may not affect the litter decomposition in the subalpine forest ecosystems of eastern Tibetan Plateau.

Runoff and sediment concentration of different parts of a road in Hyrcanian forests

Road prisms, such as cutslopes, fillslopes and road surfaces, can be important contributors of sediment to streams in forested watersheds. In this study rainfall simulations were carried out on cutslopes, fillslopes, road surfaces and forest grounds in hardwood forests of Lolet and Lat Talar, Iran. Water at intensity of 32.4 mm·h-1 was sprayed from a nozzle onto a square area of 0.48 m2. Runoff was collected by water gauge every 4 min and then runoff and sediment parameters were measured in each plot. Results indicated that on road surfaces, the runoff coefficient was 63.28%. On the cutslopes and fillslopes, the runoff coefficients were 35.14% and 10.23%, respectively. On the forest ground as a control, the runoff coefficient was 5.90%. Runoff volume was 2.73 mL·s^-1 on the road surfaces and 1.52 mL·s^-1 on cutslopes. On fillslopes the runoff volume was 0.44 mL·s^-1 and on the forest ground 0.25 mL·s^-1 The greatest rate of soil loss was found on the cutslope （280.79 g·m-2·h-1）. The total soil loss from the cutslopes was two times higher than that from the road surfaces and six times higher than that from the fillslopes. We conclude that cutslopes can be considered the main source of sediments in our study sites, but the function of road surface as a source of runoff generation is more important.