Fish assemblages respond to forest cover in small Amazonian basins     

《Limnologica》2020

The removal of native forest affects stream characteristics, processes, and organisms at the local scale. We compared the structure of fish assemblages between microbasins impacted by deforestation and those in pristine condition in the Amazonian Machado River basin, Brazil. Fish were collected with seine and dip nets along an 80-m stretch of 28 streams. At each site, we recorded physical, chemical, and land-water ecotone variables. We collected 6,586 specimens of 109 species, being 39 and 18 of them exclusively of forested and deforested streams, respectively. Non-significant differences were found for abundance and species richness between forested and deforested streams. A total of four main trophic groups were identified. Carnivores were more abundant in forested streams, whereas herbivores, omnivores and detritivores species were the most abundant in deforested streams. The deforested streams showed higher abundance and richness of algae and periphyton consumers, while forested streams presented higher abundance and richness of invertebrate consumers. Forested streams presented longer foodchains, higher occurrence and abundance of species that have more specialized habits and are intolerant to degraded environments, whereas generalist and tolerant species predominated in deforested streams. We conclude that species composition in Amazonian streams predictably responds to the degree of forest cover.  相似文献   

Quantifying groundwater sensitivity and resilience over peninsular India     

Nikhil Kumar  Jhilam Sinha  Chandra A. Madramootoo  Manish Kumar Goyal 《水文研究》2020,34(26):5327-5339

Groundwater in India plays an important role to support livelihoods and maintain ecosystems and the present rate of depletion of groundwater resources poses a serious threat to water security. Yet, the sensitivity of the hydrological processes governing groundwater recharge to climate variability remains unclear in the region. Here we assess the groundwater sensitivity (precipitation–recharge relationship) and its potential resilience towards climatic variability over peninsular India using a conceptual water balance model and a convex model, respectively in 54 catchments over peninsular India. Based on the model performance using a comprehensive approach (Nash Sutcliffe Efficiency [NSE], bias and variability), 24 out of 54 catchments are selected for assessment of groundwater sensitivity and its resilience. Further, a systematic approach is used to understand the changes in resilience on a temporal scale based upon the convex model and principle of critical slowing down theory. The results of the study indicate that the catchments with higher mean groundwater sensitivity (GWS) encompass high variability in GWS over the period (1988–2011), thus indicating the associated vulnerability towards hydroclimatic disturbances. Moreover, it was found that the catchments pertaining to a lower magnitude of mean resilience index incorporates a high variability in resilience index over the period (1993–2007), clearly illustrating the inherent vulnerability of these catchments. The resilience of groundwater towards climatic variability and hydroclimatic disturbances that is revealed by groundwater sensitivity is essential to understand the future impacts of changing climate on groundwater and can further facilitate effective adaptation strategies.  相似文献   

Update and spatial extension of strategic forest inventories using time series remote sensing and modeling     

《International Journal of Applied Earth Observation and Geoinformation》2020

Up-to-date forest inventory information relating the characteristics of managed and natural forests is fundamental to sustainable forest management and required to inform conservation of biodiversity and assess climate change impacts and mitigation opportunities. Strategic forest inventories are difficult to compile over large areas and are often quickly outdated or spatially incomplete as a function of their long production cycle. As a consequence, automated approaches supported by remotely sensed data are increasingly sought to provide exhaustive spatial coverage for a set of core attributes in a timely fashion. The objective of this study was to demonstrate the integration of current remotely-sensed data products and pre-existing jurisdictional inventory data to map four forest attributes of interest (stand age, dominant species, site index, and stem density) for a 55 Mha study region in British Columbia, Canada. First, via image segmentation, spectrally homogenous objects were derived from Landsat surface-reflectance pixel composites. Second, a suite of Landsat-based predictors (e.g., spectral indices, disturbance history, and forest structure) and ancillary variables (e.g., geographic, topographic, and climatic) were derived for these units and used to develop predictive models of target attributes. For the often difficult classification of dominant species, two modelling approaches were compared: (a) a global Random Forests model calibrated with training samples collected over the entire study area, and (b) an ensemble of local models, each calibrated with spatially constrained local samples. Accuracy assessment based upon independent validation samples revealed that the ensemble of local models was more accurate and efficient for species classification, achieving an overall accuracy of 72% for the species which dominate 80% of the forested areas in the province. Results indicated that site index had the highest agreement between predicted and reference (R² = 0.74, %RMSE = 23.1%), followed by stand age (R² = 0.62, %RMSE = 35.6%), and stem density (R² = 0.33, %RMSE = 65.2%). Inventory attributes mapped at the image-derived unit level captured much finer details than traditional polygon-based inventory, yet can be readily reassembled into these larger units for strategic forest planning purposes. Based upon this work, we conclude that in a multi-source forest monitoring program, spatially localized and detailed characterizations enabled by time series of Landsat observations in conjunction with ancillary data can be used to support strategic inventory activities over large areas.  相似文献   

黄土山区煤层群分层开采地表位移规律分析     

沈宇恒 《北京测绘》2020,(4):490-494

为了研究黄土山区地形对煤层群开采地表位移的影响,以榆林某矿为地质原型,利用数值软件模拟地表为近水平、正坡、负坡、凸面和凹面五种地形条件下煤层群开采。结果表明:黄土山区地形的变化,对煤层群开采顶板垂直应力影响不明显,对地表位移影响较大;单向坡开采,斜坡滑移引起的下沉量在坡顶与开采沉陷量形成“叠加”,在坡底形成“抵消”;在组合坡中,煤层群开采地表位移量相差很大,说明在变坡点附近地表位移较为复杂。  相似文献   

近59 a锡林河流域潜在蒸散发及地表干湿状况变化趋势分析          下载免费PDF全文

张璐  朱仲元  张圣微  王慧敏  王飞  席小康 《干旱区地理》2020,43(4):997-1003

利用1960—2018年锡林河流域周边13个气象站的逐日气象资料,采用世界粮农组织（Food and Agriculture Organization of the United Nations,FAO）推荐的Penman-Monteith公式计算各气象站多年潜在蒸散发量及相对湿润度指数。通过利用主成分分析、相关分析和偏相关分析,探讨了锡林河流域潜在蒸散发、地表干湿状况多年变化规律;分析了影响潜在蒸散发的主要气象因子及各气象要素间的相互作用;着重讨论了锡林河流域潜在蒸散发的周期变化及其与相对湿润度指数、各气象要素的相互作用。结果表明：流域近59 a潜在蒸散发整体呈现增长趋势,且上升趋势显著,存在显著增加—减小交替的多尺度时频变化特征和多主周期变化规律;各气象要素中潜在蒸散发对温度的响应较大,平均风速次之;平均相对湿度受到潜在蒸散发的影响较大,降水次之。整个流域环境有不显著的变湿润趋势。  相似文献   

贵州夜郎湖表层水体地球化学昼夜变化及其影响因素     

王家录  任娟  王勇  李维杰  娄昭  陈佳 《热带地理》2020,40(2):335-345

为探究岩溶水库水文地球化学行为过程,对贵州普定夜郎湖表层水体进行了为期3 d的高分辨率昼夜监测。结果表明：1）多变的天气和水文条件叠加导致水体离子指标昼夜变化不显著,规律性较差。而水温、DO、pH值、SpC、SIc、pCO₂等常规理化指标受水温变化和生物作用表现出明显的昼夜波动。2）利用亨利常数和主成分分析,得到温度变化、生物作用、人类活动、水库的蓄水与放水对夜郎湖水库水文地球化学特征变化的贡献率分别为21.66%、17.28%、14.08%和10.22%,说明作用于水库水文地球化学行为的因子具有多元性。3）δ ¹⁸O表现出与DO一致的波动趋势,即白天上升,晚上下降,反映在短时间尺度上,氢氧稳定同位素变化受控于生物过程（主要是呼吸作用过程）;而对比水库水体和大气降水的d-excess（d值）发现,水库水体的d值（8.21‰）显著偏低于当地大气降水的d值（9.64‰）,说明在长时间尺度上,主要受蒸发效应引起的不平衡分馏影响。  相似文献   

中印对尼泊尔地缘影响力的演变分析     

张良兵  骆华松  洪菊花  陆好健 《世界地理研究》2020,29(1):43-51

尼泊尔在地理位置上处于中国和印度包围之中，由于历史原因，其经济、政治、军事等长期受到制约。随着中国“一带一路”倡议的推进和中印近年来领土和国际政治问题的冲突与分歧，尼泊尔正在成为中印新的角力场。本文首先通过构建地缘影响力模型进行演变格局分析与趋势预测，并加入世界环境和区域环境两方面影响因素，运用定性与定量分析结合的方法，预测中、尼、印三国未来战略行动方向。综合以上分析发现：1）2000年—2016年，中国对尼泊尔地缘影响力较于印度对于尼泊尔地缘影响力上升趋势明显，预计在2022年至2023年中、印对尼泊尔地缘影响力达到平衡。2）硬实力是中国对尼泊尔地缘影响力上升的关键因素；软实力和交流互动力是未来中国增强在尼泊尔地缘影响力的发展因素；地理环境是中国对尼泊尔地缘影响力发展的制约因素。3）未来中国将继续实施积极性合作战略，印度形成对中国遏制性防范战略，尼泊尔维持被动性中印平衡战略。  相似文献   

基于EEMD和ARIMA的海温预测模型研究          下载免费PDF全文

张莹  谭艳春  彭发定  廖杏杰  余昱昕 《海洋学研究》2019,37(1):9-14

类型丰富、时空分辨率高的海洋探测数据,为信号分解和机器学习算法的应用提供了可能。本文针对如何建立有效的海温预测模型这一问题,使用高时空分辨率的海表温度(SST)融合产品,引入信号处理领域的集合经验模态分解(EEMD)和机器学习领域的自回归积分滑动平均模型(ARIMA)。首先利用最适于分解自然信号的EEMD方法,将海温数据分解成多个确定频率的序列;再利用ARIMA分别对各个频率的序列进行预测,最后将各个序列的预测结果进行组合。该方法在丰富数据的支撑下,比以往直接使用海温数据所建立的预测模型精度更高,为更好地进行海温预测提供了新方法。  相似文献   

多点液压式波浪能海水淡化系统建模与仿真   总被引：1，自引：1，他引：0  

胡缘  杨绍辉  何宏舟  陈沪  郑松根  张迪 《海洋工程》2019,37(1):134-141

为缓解淡水资源短缺及化石能源过度使用问题,提出多点液压式波浪能海水淡化系统,该系统主要由采能装置、液压传递系统与反渗透膜海水淡化设备组成。系统的采能装置采用振荡浮子式,可将波浪能转换为浮子振荡从而被液压系统吸收达到采集波浪能的目的。为了提高液压式波浪能海水淡化系统的采能效率及淡水率,利用AMEsim软件对液压传递系统进行建模与仿真,分析了蓄能器、浮子个数及波高对液压传递系统输出响应的影响。结果表明:蓄能器能够使液压马达的输出响应更加稳定;当浮子的数量增加时,液压系统达到稳定的运行状态所需的时间更短,从而有利于提高系统的效率;波高在2 m左右时,本系统的产水量达到最大。  相似文献   

利用GLAS激光测高数据评估DSM产品质量及精度优化   总被引：2，自引：0，他引：2  

胡柳茹  唐新明  李国元  付冬暇  窦显辉  赵世湖 《测绘通报》2019,(11):39-43

提出了一种利用卫星激光测高数据直接优化提升数字表面模型（DSM）产品精度的方法。选取境外中亚地区的资源三号DSM开展试验，通过采用多准则约束方法提取激光高程控制点，分别利用偏度、中值、线性、二次多项式等进行DSM误差修正，发现4种模型均能有效消除DSM系统误差，其中基于二次多项式的方法更适用于平地和丘陵地貌，线性模型更适用于高山地貌。试验验证了采用卫星激光测高数据优化境外DSM技术流程的可行性，最终可提高DSM的绝对高程精度。  相似文献