Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments, but most studies use GIS-based classification methods to conduct susceptibility zonation.This study pres...Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments, but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT) model and the K-means cluster algorithm to produce a regional landslide susceptibility map. Yanchang County, a typical landslide-prone area located in northwestern China, was taken as the area of interest to introduce the proposed application procedure. A landslide inventory containing 82 landslides was prepared and subsequently randomly partitioned into two subsets: training data(70% landslide pixels) and validation data(30% landslide pixels). Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means cluster algorithm. The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC) curve) of the proposed model was the highest, reaching 0.88,compared with traditional models(support vector machine(SVM) = 0.85, Bayesian network(BN) = 0.81,frequency ratio(FR) = 0.75, weight of evidence(WOE) = 0.76). The landslide frequency ratio and frequency density of the high susceptibility zones were 6.76/km^(2) and 0.88/km^(2), respectively, which were much higher than those of the low susceptibility zones. The top 20% interval of landslide occurrence probability contained 89% of the historical landslides but only accounted for 10.3% of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without containing more " stable" pixels. Therefore, the obtained susceptibility map is suitable for application to landslide risk management practices.展开更多
The competition-density (C-D) effects for mean mass for tree, stem, branch and leaf were analyzed in Acacia auriculiformis stands. Mean tree mass-density and mean organ mass-density were well explained by the C-D equa...The competition-density (C-D) effects for mean mass for tree, stem, branch and leaf were analyzed in Acacia auriculiformis stands. Mean tree mass-density and mean organ mass-density were well explained by the C-D equation of tree and the C-D equation of tree organ, respectively. An equation describing the relationship between mean leaf area u and density was formulated that fit the u-data well. The relationship between mean tree mass w and the ratio of each organ to mean tree mass (wo/ w) was examined. With increasing w, the stem mass ratio wS/w increased, whereas the branch mass ratio wB/w and the leaf mass ratio wL/w decreased. The yield difference between the lowest-density stand and the high-density stand became greater with stand growth. However, the yield of the mid-density stand was slightly lower than the yield of the high-density stand during the experimental period. To produce the most desirable combination of demanding individual-tree size and relative high stem yield, the mid-density is recommended as proper planting density for future management of A. auriculiformis stands.展开更多
A knowledge of the tree-ring stable nitrogen isotope ratio(δ^(15)N)can deepen our understanding of forest ecosystem dynamics by indicating the long-term availability,cycling and sources of nitrogen(N).However,the rad...A knowledge of the tree-ring stable nitrogen isotope ratio(δ^(15)N)can deepen our understanding of forest ecosystem dynamics by indicating the long-term availability,cycling and sources of nitrogen(N).However,the radial mobility of N blurs the interannual variations in the long-term N records.Previous studies of the chemical extraction of tree rings before analysis had produced inconsistent results and it is still unclear whether it is necessary to pre-treat wood samples from specific tree species to remove soluble N compounds before determining theδ^(15)N values.We compared the effects of pre-treatment with organic solvents and hot ultrapure water on the N concentration andδ^(15)N of tree rings from endemic Qinghai spruce(Picea crassifolia)growing in the interior of the central Qilian Mountains,China,during the last 60 a.We assessed the effects of different preparation protocols on the removal of the labile N compounds and investigated the need to pre-treat wood samples before determining theδ^(15)N values of tree rings.Increasing trends of the tree-ring N concentration were consistently observed in both the extracted and unextracted wood samples.The total N removed by extraction with organic solvents was about 17.60%,with a significantly higher amount in the sapwood section(P<0.01).Theδ^(15)N values of tree rings decreased consistently from 1960 to 2019 in both the extracted and unextracted wood samples.Extraction with organic solvents increased theδ^(15)N values markedly by about 5.2‰and reduced the variations in theδ^(15)N series.However,extraction with hot ultrapure water had little effect,with only a slight decrease in theδ^(15)N values of about 0.5‰.Our results showed that the radial pattern in the inter-ring movement of N in Qinghai spruce was not minimized by extraction with either organic solvents or hot ultrapure water.It is unnecessary to conduct hot ultrapure water extraction for the wood samples from Qinghai spruce because of its negligible effect on the removal of the labile N.Theδ^(15)N variation trend of tree rings in the unextracted wood samples was not influenced by the heartwood-sapwood transition zone.We suggest that theδ^(15)N values of the unextracted wood samples of the climate-sensitive Qinghai spruce could be used to explore the ecophysiological dynamics while focusing on the long-term variations.展开更多
活立木茎干水分状况是植物生命状态的有效体现,其中茎干含水率(Stem water content,StWC)和液流密度(Sap flux density,SFD)是研究植物体内水分变化规律的重要参数。准确检测活立木茎干同一空间位置的含水率和液流密度可以更有效地分析...活立木茎干水分状况是植物生命状态的有效体现,其中茎干含水率(Stem water content,StWC)和液流密度(Sap flux density,SFD)是研究植物体内水分变化规律的重要参数。准确检测活立木茎干同一空间位置的含水率和液流密度可以更有效地分析2个参数的关系、评估植物生长状况。将基于驻波率(Standing wave ratio,SWR)原理的茎干水分检测方法和基于热比率法(Heat ratio method,HRM)原理的茎干液流检测方法结合,设计了活立木茎干含水率和液流复合参数检测传感器,复合传感器的含水率检测单元和液流检测单元复用一套三针式探针,可对活立木茎干同一位置的含水率和液流实时精准检测。含水率检测单元输出电压与介电常数(6~53.3范围内,对应茎干含水率为0~85%)具有良好的线性关系(决定系数R^(2)=0.9701),静态稳定性良好(长时间测试最大波动为0.6%全量程)。以杨树为研究对象,含水率检测单元与BD-IV型植物茎体水分传感器的对比实验结果一致(决定系数R^(2)=0.9800)。液流检测单元与ST1221型热扩散式液流计对比,二者检测的杨树液流密度具有显著的线性关系(决定系数R^(2)=0.8991),热扩散式液流计不能准确判断零液流条件而低估了液流密度,ST1221型液流计检测的平均值比本系统液流检测单元低1.1 cm/h,液流检测单元使用的热比率法可以准确检测低速液流。复合传感器对杨树茎干含水率和液流的长时间监测结果与前人研究一致且符合植物生理规律。茎干含水率和液流存在极显著的负相关性(Pearson相关系数为-0.7951)。展开更多
Little is known about C-N-P stoichiometries and content in teak(Tectona grandis)plantations in South China,which are mostly sited on hilly areas with lateritic soil,and the effect of slope position on the accumulation...Little is known about C-N-P stoichiometries and content in teak(Tectona grandis)plantations in South China,which are mostly sited on hilly areas with lateritic soil,and the effect of slope position on the accumulation of these elements in trees and rhizosphere soils.Here we analyzed the C,N,P content and stoichiometry in leaves,fine roots and rhizosphere soils of trees on the upper and lower slopes of a 12-year-old teak plantation.The Kraft classification system of tree status was used to sample dominant,subdominant and mean trees at each slope position.The results showed that the C,N and P contents in leaves were higher than in fine roots and rhizosphere soils.The lowest C/N,C/P and N/P ratios were found in rhizosphere soils,and the C/N and C/P ratios in fine roots were higher than in leaves.Nutrient accumulation in leaves,fine roots and rhizosphere soils were significantly influenced by slope position and tree class with their interaction mainly showing a greater effect on rhizosphere soils.Leaf C content and C/N ratio,fine root C and P contents,and C/N and C/P ratios all increased distinctly with declining slope position.The contents of organic matter(SOM),ammonium(NH4+-N),nitrate-nitrogen(NO3--N)and available potassium(AK)in rhizosphere soils were mainly enriched on upper slopes,but exchange calcium(ECa),available phosphorus(AP),and pH were relatively lower.Variations in the C,N and P stoichiometries in trees were mainly attributed to the differences in rhizosphere soil properties.N and P contents showed significant positive linear relationships between leaf and rhizosphere soil,and C content negative linear correlation among leaves,fine roots and rhizosphere soils.Chemical properties of rhizosphere soils,particularly C/N and NH4+-N,had significant effects on the leaf nutrients in trees on the upper slope.Correspondingly,rhizosphere soil properties mainly influenced fine root nutrients on the lower slope,and soil AK was the major influencing factor.Overall,these results offer new insights for the sustainability and management of teak plantations in hilly areas.展开更多
基金This research is funded by the National Natural Science Foundation of China(Grant Nos.41807285 and 51679117)Key Project of the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(SKLGP2019Z002)+3 种基金the National Science Foundation of Jiangxi Province,China(20192BAB216034)the China Postdoctoral Science Foundation(2019M652287 and 2020T130274)the Jiangxi Provincial Postdoctoral Science Foundation(2019KY08)Fundamental Research Funds for National Universities,China University of Geosciences(Wuhan)。
文摘Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments, but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT) model and the K-means cluster algorithm to produce a regional landslide susceptibility map. Yanchang County, a typical landslide-prone area located in northwestern China, was taken as the area of interest to introduce the proposed application procedure. A landslide inventory containing 82 landslides was prepared and subsequently randomly partitioned into two subsets: training data(70% landslide pixels) and validation data(30% landslide pixels). Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means cluster algorithm. The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC) curve) of the proposed model was the highest, reaching 0.88,compared with traditional models(support vector machine(SVM) = 0.85, Bayesian network(BN) = 0.81,frequency ratio(FR) = 0.75, weight of evidence(WOE) = 0.76). The landslide frequency ratio and frequency density of the high susceptibility zones were 6.76/km^(2) and 0.88/km^(2), respectively, which were much higher than those of the low susceptibility zones. The top 20% interval of landslide occurrence probability contained 89% of the historical landslides but only accounted for 10.3% of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without containing more " stable" pixels. Therefore, the obtained susceptibility map is suitable for application to landslide risk management practices.
基金supported by the Forestry Technology Popularization Demonstration Project of the Central Government of China(No.[2015]GDTK-07)
文摘The competition-density (C-D) effects for mean mass for tree, stem, branch and leaf were analyzed in Acacia auriculiformis stands. Mean tree mass-density and mean organ mass-density were well explained by the C-D equation of tree and the C-D equation of tree organ, respectively. An equation describing the relationship between mean leaf area u and density was formulated that fit the u-data well. The relationship between mean tree mass w and the ratio of each organ to mean tree mass (wo/ w) was examined. With increasing w, the stem mass ratio wS/w increased, whereas the branch mass ratio wB/w and the leaf mass ratio wL/w decreased. The yield difference between the lowest-density stand and the high-density stand became greater with stand growth. However, the yield of the mid-density stand was slightly lower than the yield of the high-density stand during the experimental period. To produce the most desirable combination of demanding individual-tree size and relative high stem yield, the mid-density is recommended as proper planting density for future management of A. auriculiformis stands.
基金supported by the National Natural Science Foundation of China (41971104)the Open Foundation of the State Key Laboratory of Loess and Quaternary Geology,Institute of Earth Environment+1 种基金Chinese Academy of Sciences (CASSKLLQG1817)the Qilian Mountain National Park Research Center (Qinghai)(GKQ2019-01)。
文摘A knowledge of the tree-ring stable nitrogen isotope ratio(δ^(15)N)can deepen our understanding of forest ecosystem dynamics by indicating the long-term availability,cycling and sources of nitrogen(N).However,the radial mobility of N blurs the interannual variations in the long-term N records.Previous studies of the chemical extraction of tree rings before analysis had produced inconsistent results and it is still unclear whether it is necessary to pre-treat wood samples from specific tree species to remove soluble N compounds before determining theδ^(15)N values.We compared the effects of pre-treatment with organic solvents and hot ultrapure water on the N concentration andδ^(15)N of tree rings from endemic Qinghai spruce(Picea crassifolia)growing in the interior of the central Qilian Mountains,China,during the last 60 a.We assessed the effects of different preparation protocols on the removal of the labile N compounds and investigated the need to pre-treat wood samples before determining theδ^(15)N values of tree rings.Increasing trends of the tree-ring N concentration were consistently observed in both the extracted and unextracted wood samples.The total N removed by extraction with organic solvents was about 17.60%,with a significantly higher amount in the sapwood section(P<0.01).Theδ^(15)N values of tree rings decreased consistently from 1960 to 2019 in both the extracted and unextracted wood samples.Extraction with organic solvents increased theδ^(15)N values markedly by about 5.2‰and reduced the variations in theδ^(15)N series.However,extraction with hot ultrapure water had little effect,with only a slight decrease in theδ^(15)N values of about 0.5‰.Our results showed that the radial pattern in the inter-ring movement of N in Qinghai spruce was not minimized by extraction with either organic solvents or hot ultrapure water.It is unnecessary to conduct hot ultrapure water extraction for the wood samples from Qinghai spruce because of its negligible effect on the removal of the labile N.Theδ^(15)N variation trend of tree rings in the unextracted wood samples was not influenced by the heartwood-sapwood transition zone.We suggest that theδ^(15)N values of the unextracted wood samples of the climate-sensitive Qinghai spruce could be used to explore the ecophysiological dynamics while focusing on the long-term variations.
文摘活立木茎干水分状况是植物生命状态的有效体现,其中茎干含水率(Stem water content,StWC)和液流密度(Sap flux density,SFD)是研究植物体内水分变化规律的重要参数。准确检测活立木茎干同一空间位置的含水率和液流密度可以更有效地分析2个参数的关系、评估植物生长状况。将基于驻波率(Standing wave ratio,SWR)原理的茎干水分检测方法和基于热比率法(Heat ratio method,HRM)原理的茎干液流检测方法结合,设计了活立木茎干含水率和液流复合参数检测传感器,复合传感器的含水率检测单元和液流检测单元复用一套三针式探针,可对活立木茎干同一位置的含水率和液流实时精准检测。含水率检测单元输出电压与介电常数(6~53.3范围内,对应茎干含水率为0~85%)具有良好的线性关系(决定系数R^(2)=0.9701),静态稳定性良好(长时间测试最大波动为0.6%全量程)。以杨树为研究对象,含水率检测单元与BD-IV型植物茎体水分传感器的对比实验结果一致(决定系数R^(2)=0.9800)。液流检测单元与ST1221型热扩散式液流计对比,二者检测的杨树液流密度具有显著的线性关系(决定系数R^(2)=0.8991),热扩散式液流计不能准确判断零液流条件而低估了液流密度,ST1221型液流计检测的平均值比本系统液流检测单元低1.1 cm/h,液流检测单元使用的热比率法可以准确检测低速液流。复合传感器对杨树茎干含水率和液流的长时间监测结果与前人研究一致且符合植物生理规律。茎干含水率和液流存在极显著的负相关性(Pearson相关系数为-0.7951)。
基金funded by the National Key Research and Development Program(grant number 2017YFD0601100)。
文摘Little is known about C-N-P stoichiometries and content in teak(Tectona grandis)plantations in South China,which are mostly sited on hilly areas with lateritic soil,and the effect of slope position on the accumulation of these elements in trees and rhizosphere soils.Here we analyzed the C,N,P content and stoichiometry in leaves,fine roots and rhizosphere soils of trees on the upper and lower slopes of a 12-year-old teak plantation.The Kraft classification system of tree status was used to sample dominant,subdominant and mean trees at each slope position.The results showed that the C,N and P contents in leaves were higher than in fine roots and rhizosphere soils.The lowest C/N,C/P and N/P ratios were found in rhizosphere soils,and the C/N and C/P ratios in fine roots were higher than in leaves.Nutrient accumulation in leaves,fine roots and rhizosphere soils were significantly influenced by slope position and tree class with their interaction mainly showing a greater effect on rhizosphere soils.Leaf C content and C/N ratio,fine root C and P contents,and C/N and C/P ratios all increased distinctly with declining slope position.The contents of organic matter(SOM),ammonium(NH4+-N),nitrate-nitrogen(NO3--N)and available potassium(AK)in rhizosphere soils were mainly enriched on upper slopes,but exchange calcium(ECa),available phosphorus(AP),and pH were relatively lower.Variations in the C,N and P stoichiometries in trees were mainly attributed to the differences in rhizosphere soil properties.N and P contents showed significant positive linear relationships between leaf and rhizosphere soil,and C content negative linear correlation among leaves,fine roots and rhizosphere soils.Chemical properties of rhizosphere soils,particularly C/N and NH4+-N,had significant effects on the leaf nutrients in trees on the upper slope.Correspondingly,rhizosphere soil properties mainly influenced fine root nutrients on the lower slope,and soil AK was the major influencing factor.Overall,these results offer new insights for the sustainability and management of teak plantations in hilly areas.
