A biodiversity evaluation framework for restoration of aquatic macrophyte communities in shallow lakes driven by hydrological process management     

Shuhan Li  Tao Sun  Wei Yang  Baoshan Cui  Xinan Yin 《水文研究》2021,35(1):e13983

Macrophyte community diversity and composition respond to ecosystem conservation and local environmental factors. In this study, we developed a multidimensional diversity framework for macrophyte communities, including the taxonomic and functional alpha and beta diversity. We used the framework to explore the relationships among water level regimes and these diversity parameters in a case study of China's Baiyangdian Lake. Analysis of indicators of hydrologic alteration divided the water level from 1959 to 2019 into four regimes (dry, <6.42 m; low, 6.42–7.23 m; medium, 7.23–8.19 m; high, >8.19 m). Alpha and beta diversity were significantly higher in the medium regime than in the low and high regimes. Redundancy analysis indicated that the maximum water depth significantly affected taxonomic alpha diversity, and total nitrogen (TN) and chemical oxygen demand (COD) concentration significantly affected functional alpha diversity, respectively. Mantel tests showed that TN, Secchi depth (SD), and water depth in the high water level regime significantly increased the total beta diversity and turnover components. TN was the main factor that increased total taxonomic beta diversity. Water level regime mainly influenced interspecific relationships by changing the TN and COD concentration. The water level should be maintained between the medium and high water level regimes to promote restoration of the macrophyte community and improve ecosystem stability. The biodiversity evaluation framework would provide a deeper insight into the hydrological process management for restoration of aquatic macrophyte communities in shallow lakes.  相似文献   

Exploring the stemflow dynamics and driving factors at both inter- and intra-event scales in a typical subtropical deciduous forest     

Haixia Zhang  Congsheng Fu  Aimin Liao  Can Zhang  Jiufu Liu  Niu Wang  Bin He 《水文研究》2021,35(3):e14091

Numerous efforts have been made to understand stemflow dynamics under different types of vegetation at the inter-event scale, but few studies have explored the stemflow characteristics and corresponding influencing factors at the intra-event scale. An in-depth investigation of the inter- and intra-event dynamics of stemflow is important for understanding the ecohydrological processes in forest ecosystems. In this study, stemflow volume (F_V), stemflow funnelling ratio (F_R), and stemflow ratio (F_%) from Quercus acutissima and Broussonetia papyrifera trees were measured at both inter- and intra-event scales in a subtropical deciduous forest, and the driving factors, including tree species and meteorological factors were further explored. Specifically, the F_V, F_R and F_% of Q. acutissima (52.3 L, 47.2, 9.6%) were lower than those of B. papyrifera (85.1 L, 91.2, 12.4%). The effect of tree species on F_V and F_% was more obvious under low intensity rainfall types. At the inter-event scale, F_V had a strong positive linear correlation with rainfall amount (G_P) and event duration (D_E) for both tree species, whereas F_R and F_% had a positive logarithmic correlation with G_P and D_E only under high-intensity, short-duration rainfall type. F_R and F_% were mainly affected by wind speed and the maximum 30-min rainfall intensity under low-intensity, long-duration rainfall type. At the intra-event scale, for both tree species, the mean lag time between the start of rainfall and stemflow was the shortest under high-intensity, short-duration rainfall type, while the mean duration and amount of stemflow after rain cessation were the greatest under high-amount, long-duration rainfall type. The relationship between stemflow intensity and rainfall intensity at the 5-min interval scale also depended greatly on rainfall type. These findings can help clarify stemflow dynamics and driving factors at both inter- and intra-event scales, and also provide abundant data and parameters for ecohydrological simulations in subtropical forests.  相似文献   

Gully erosion spatial modelling: Role of machine learning algorithms in selection of the best controlling factors and modelling process     

《地学前缘(英文版)》2020,11(6):2207-2219

This investigation assessed the efficacy of 10 widely used machine learning algorithms (MLA) comprising the least absolute shrinkage and selection operator (LASSO), generalized linear model (GLM), stepwise generalized linear model (SGLM), elastic net (ENET), partial least square (PLS), ridge regression, support vector machine (SVM), classification and regression trees (CART), bagged CART, and random forest (RF) for gully erosion susceptibility mapping (GESM) in Iran. The location of 462 previously existing gully erosion sites were mapped through widespread field investigations, of which 70% (323) and 30% (139) of observations were arbitrarily divided for algorithm calibration and validation. Twelve controlling factors for gully erosion, namely, soil texture, annual mean rainfall, digital elevation model (DEM), drainage density, slope, lithology, topographic wetness index (TWI), distance from rivers, aspect, distance from roads, plan curvature, and profile curvature were ranked in terms of their importance using each MLA. The MLA were compared using a training dataset for gully erosion and statistical measures such as RMSE (root mean square error), MAE (mean absolute error), and R-squared. Based on the comparisons among MLA, the RF algorithm exhibited the minimum RMSE and MAE and the maximum value of R-squared, and was therefore selected as the best model. The variable importance evaluation using the RF model revealed that distance from rivers had the highest significance in influencing the occurrence of gully erosion whereas plan curvature had the least importance. According to the GESM generated using RF, most of the study area is predicted to have a low (53.72%) or moderate (29.65%) susceptibility to gully erosion, whereas only a small area is identified to have a high (12.56%) or very high (4.07%) susceptibility. The outcome generated by RF model is validated using the ROC (Receiver Operating Characteristics) curve approach, which returned an area under the curve (AUC) of 0.985, proving the excellent forecasting ability of the model. The GESM prepared using the RF algorithm can aid decision-makers in targeting remedial actions for minimizing the damage caused by gully erosion.  相似文献   

Farmland Abandonment Research Progress: Influencing Factors and Simulation Model     

SONG Wei  ZHANG Ying 《资源与生态学报(英文版)》2019,10(4):345-352

Farmland abandonment is a global problem and considered one of the most important areas in land use change research. Farmland abandonment research currently focuses on understanding the factors that affect farmland abandonment and developing scientific models to simulate farmland abandonment. The study reviewed the natural and political factors driving farmland abandonment and summarized the main models for farmland abandonment simulation together with their advantages and disadvantages. We discuss the main ecological effects of farmland abandonment and propose farmland abandonment research directions. The study found that: (1) the influence of labor cost change and ageing labor force on farmland abandonment needs further investigation, (2) simulation models for farmland abandonment must include the decision-making mechanism of individual farmers and focus on macro large-scale abandonment prediction models, and (3) the influence of farmland abandonment on landscape culture must be investigated in detail.  相似文献   

Spatial and Temporal Distribution of Dust‐Bound Trace Metal Elements around Kuhdasht Watershed Area in Iran     

Hamid Alipour  Ahmad Jalalian  Naser Honarjoo  Norair Tommanian  Fereidoon Sarmadian 《洁净——土壤、空气、水》2019,47(10)

Dust, as a source of trace metal elements, affects the health of society. The spatial and temporal concentrations of dust‐bound trace metals (Cd, Pb, Ni, Zn, Cu, and Mn) in Kuhdasht watershed (456 km²), Lorestan Province, Iran, is investigated. Dust is collected using glass traps placed in ten research stations in the region. The spatial and temporal distribution of dust trace metals are plotted using ARC‐GIS. The highest and the lowest concentrations of Zn (9751150 mg kg^?1), Pb (46.352.9 mg kg^?1), and Cd (2.443.30 mg kg^?1) are obtained in winter, of Ni (98110 mg kg^?1) and Cu in autumn (16.053.5 mg kg^?1), and of Mn in summer (385505 mg kg^?1). The spatial concentrations of dust‐bound trace metals indicate all, except Cu, show a decreasing trend from the mountains toward the plains, similar to that of soil and of dust, except for Zn, which shows higher concentrations in dust than in soil. The potential sources of dust‐bound trace metals and their rate of contamination are also investigated using the enrichment and contamination factors. The major sources of Cd and Zn in the dust of watershed are due to anthropogenic activities or from activities outside the borders.  相似文献   

桂林-阳朔地区DEM地形特征与岩性相关性分析及分类研究     

陈霄燕  潘军  邢立新  蒋立军  孙也涵  仲伟敬  范博文 《地球信息科学学报》2019,21(12):1867-1876

地形地貌是岩性解译的重要信息,地形因子作为描述DEM数字曲面几何特征的定量指标参数,可用来定量化表达不同岩性所在地区地形地貌特征。本文以桂林-阳朔地区为研究区,研究地形因子数学、地质意义,建立岩性与地形因子组合间的定量关联,进而实现岩石类型划分。本文基于ASTERGDEM提取坡度、起伏度等12个地形因子,在分析各个地形因子地质意义基础上,通过聚类分析及方差分析的多元统计分析方法,研究各岩性地形因子特性及其关联性,建立研究区岩性之间的定量差异;此外,利用因子分析方法研究岩性分类过程中的主导因素,确定适宜岩性分类方法以实现定量化岩性分类。实验结果表明：不同岩性、不同地形地貌的地形因子（组合）之间具有显著差异,基于因子分析得到的宏观地形复杂度指数（MTI）以及微观曲率指数（MCI）对岩石类型的分类精度达77.36%。研究表明,地形复杂度等地形因子可用于岩性分类,采用因子分析方法可获取反映地形地貌宏观、微观特征的定量指标,且岩性分类效果良好。  相似文献   

山区农村土地利用转型与小农经济变迁耦合机理   总被引：1，自引：0，他引：1  

苏康传  杨庆媛  张佰林  张忠训 《地理研究》2019,38(2):399-413

通过山区土地利用转型与小农经济变迁的耦合关系分析,可以揭示山区人地关系的变化过程和机理。随着工业化、城镇化的快速推进,山区农村人地关系发生深刻变化,小农经济变迁驱动土地利用转型,土地利用转型进一步促进小农经济变迁。在阐述土地利用转型及小农经济变迁内涵和特征基础上,结合实证探讨二者间的耦合机理,以期为乡村振兴战略的实施提供理论支撑和现实参考。研究表明：① 山区农村土地利用转型与小农经济变迁相互影响,耦合演进。② 山区农村土地利用转型重点体现在农村宅基地、耕地及林地三类用地上。③ 中国小农经济已发生四次变迁,而山区小农经济变迁在第四次中表现较为明显,其阶段特征主要为农村人口向城镇迁移,土地流转频繁,土地规模经营趋势增强。④ 山区小农经济变迁引发耕地空间形态及功能转型,山区耕地转型进一步促进小农经济变迁。⑤ 山区小农经济变迁及农户生计策略非农化转变促使农户对宅基地结构及功能的需求发生变化;闲置废弃宅基地综合整治可显化农村土地资产价值,增加农民土地财产性收入,促进小农经济变迁。⑥ 通过云南省砚山县耕地利用转型案例剖析,验证了本文提出的山区农村土地利用转型与小农经济变迁的耦合机理。  相似文献   

由下扬子区海陆对比分析南黄海盆地下志留统烃源岩特征及其主控因素     

蔡来星  肖国林  郭兴伟  王蛟  吴志强  李宝刚 《吉林大学学报(地球科学版)》2019,49(1):39-52

针对南黄海盆地海相油气勘探的重大需求，在收集、整理下扬子苏、浙、皖地区地质和地化资料的基础上，依托科学钻探CSDP-2井岩心，系统对比了南黄海盆地与下扬子陆区早志留世古地理背景和沉积充填特征，进而利用一系列地化测试数据总结了南黄海盆地下志留统烃源岩特征并探讨其主控因素。研究结果表明：南黄海盆地大陆架科学钻探CSDP-2井目前已钻遇了坟头组和高家边组上部两套丰度很低的厚层、暗色（粉砂质）泥岩，其有机质类型主要为Ⅱ₂型，热演化程度已整体进入过成熟阶段；受控于全球海侵事件和扬子板块构造活动的发展阶段，早志留世初期深水陆棚环境逐渐向后期的浅水陆棚环境演变，加之早期较高的初级生产力和良好的保存条件，使得下扬子区高家边组下部烃源岩的品质明显高于上部，并以底部黑色笔石页岩段有机质丰度最高。因此，南黄海盆地高家边组底部理应存在一套优质烃源岩层，可作为下一步页岩气勘探的重点层位。  相似文献   

黄河干流头道拐河段凌汛期小流量过程变化及其影响因素研究     

全栋  李超  路新川  史小红  杨朝霞 《冰川冻土》2020,42(2):620-628

黄河干流内蒙古段河道冬季流凌封河期， 河道水量除一部分转化为冰量外， 很大一部分转化为槽蓄水量而贮存在河道中， 导致下游头道拐河段出现小流量过程， 上游河道流量转化为槽蓄水量和贮存的冰量越大， 小流量持续时间越长， 开河期发生凌汛洪水风险越高。通过对1998 - 2016年头道拐站凌讯期流量变化过程分析， 重新界定了小流量上限阈值为330 m³·s^-1， 并且以此值为标准进行小流量过程研究， 分别采用R/S极差分析法、 Fourier变换分析法对近年来小流量过程变化特征进行分析； 结合非线性概率Logit模型和Probit模型对小流量过程的影响因素进行讨论。结果表明： 小流量持续天数变化呈现缩短趋势； 同时， 小流量过程与上游相对来水之间变化关系显著且过程同步， 而滞后于河道槽蓄水量变化过程； 通过Logit模型和Probit模型分析各影响因素变化时相应小流量持续时间变化的响应概率大小， 明确河道冰流量是小流量过程第一影响因素， 气温条件是小流量过程的决定因素， 首封位置和相对来水量是小流量过程重要影响因素。  相似文献   

车辆碾压作用下戈壁地表起尘浓度   总被引：1，自引：1，他引：0  

孟小楠  严平  王振亭  董苗  王勇 《中国沙漠》2019,39(1):80-87

通过野外观测车辆碾压作用下戈壁地表PM₁₀释放浓度，探讨其主要影响因素。针对戈壁区砾石、砂砾、砂质和砂土4种路面类型，应用TSI粉尘仪多次重复观测车辆碾压产生的PM₁₀浓度，进而阐明碾压次数、车速和地表水分等因素对起尘浓度的影响。结果表明：4种路面的平均起尘浓度依次为5.339、9.089、16.944、50.251 mg·m^-3，是自然状态下的5~50倍；起尘浓度随碾压次数增多而增大，其中砂土路情况下的增长最显著；随土层厚度的增大呈现出幂函数的增长趋势；降雨后路面起尘浓度显著减小，且降雨量会影响降雨后起尘浓度的变化趋势。最后提出了针对性的建议和措施以减弱车辆碾压导致的戈壁地表起尘。  相似文献