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1.
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   
2.
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 Strategic forest inventories are difficult to compile over large areas and are often quickly outdated or spatially incomplete as a function of their long production cycle.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   
3.
Simulating land use/cover change (LUCC) and determining its transition rules have been a focus of research for several decades. Previous studies used ordinary logistic regression (OLR) to determine transition rules in cellular automata (CA) modeling of LUCC, which often neglected the spatially non-stationary relationships between driving factors and land use/cover categories. We use an integrated geographically weighted logistic regression (GWLR) CA-Markov method to simulate LUCC from 2001–2011 over 29 towns in the Connecticut River Basin. Results are compared with those obtained from the OLR-CA-Markov method, and the sensitivity of LUCC simulated by the GWLR-CA-Markov method to the spatial non-stationarity-based suitability map is investigated. Analysis of residuals indicates better goodness of fit in model calibration for geographically weighted regression (GWR) than OLR. Coefficients of driving factors indicate that GWLR outperforms OLR in depicting the local suitability of land use/cover categories. Kappa statistics of the simulated maps indicate high agreement with observed land use/cover for both OLR-CA-Markov and GWLR-CA-Markov methods. Similarity in simulation accuracy between the methods suggests that the sensitivity of simulated LUCC to suitability inputs is low with respect to spatial non-stationarity. Therefore, this study provides critical insight on the role of spatial non-stationarity throughout the process of LUCC simulation.  相似文献   
4.
Riparian land use is a key driver of stream ecosystem processes but its effects on water quality are still a matter of debate when proposing measures to improve freshwater quality. The aim of this study was to examine the influence of riparian land use on stream habitat and water chemistry, and to assess in what extent stream habitat also affects water quality. To that end, we selected eight reaches in the Ave River basin (northwestern Portugal) and compared longitudinal variations in water chemistry and stream habitat between reaches with different land use (urban, agricultural and natural), and between reaches with natural riparian areas and different habitats. Stream habitat was assessed using the Fluvial Functional Index, the HABSCORE, and the Riparian Forest Quality Index. Longitudinal variations in water chemistry were determined measuring differences in concentrations of ammonium, nitrate, phosphate and oxygen, and conductivity, pH and temperature between the downstream and the upstream ends of each reach. Nitrate concentration tended to decrease along reaches with more natural riparian areas and to increase along reaches with more urban and agricultural land uses. Longitudinal variations in water chemistry also differed between reaches with natural riparian areas, suggesting that water quality also depends on stream habitat. Moreover, longitudinal variation in water chemistry was proven a simple, useful and low-cost approach to assess the influence of land cover and stream habitat on water quality. Overall results demonstrated that both riparian land use and stream habitat influence water quality and that riparian forests are essential to reduce nutrient export to downstream ecosystems.  相似文献   
5.
The emergence of high-resolution land cover data has created the opportunity to assess the accuracy of impervious cover (IC) provided by the National Land Cover Database (NLCD). We assessed the accuracy of the 900 m2 NLCD2011 %IC for 18 metropolitan areas throughout the conterminous United States using reference data from 1 m2 land cover data developed as part of the United States Environmental Protection Agency’s EnviroAtlas project. Agreement was assessed from two perspectives: 1) sensitivity to the size of the assessment unit used for the comparison, and 2) utility of NLCD %IC to serve as a proxy for high-resolution IC. The former perspective was considered because statistical relationships can be sensitive to assessment unit size and shape, and the latter perspective was considered because high resolution (reference) %IC data are not available nationwide. The utility of NLCD %IC as a proxy for the high resolution data was assessed for seven lattice (square) cell sizes ranging from 1 ha to 200 ha using four EnviroAtlas IC indicators: 1) %IC per 100 ha (1 km2); 2) %IC by Census block group; 3) %IC within a 15 m (radius) of the riparian zone, and; 4) %IC within a 50 m (radius) of the riparian zone. Agreement was quantified as per assessment unit deviation (NLCD %IC – reference %IC) and summarized as Mean Absolute Deviation (MAD) and Mean Deviation (MD) both within and across the 18 metropolitan areas. Ordinary least squares (OLS) regression (y = reference %IC and x = NLCD %IC) was also used to evaluate the quality of the NLCD %IC data. MAD was ≤ 5% for six of the seven lattice cell sizes. MAD was also ≤ 5% for Census block groups > 100 ha and for both riparian units. These results suggest that uncertainty attributable to the measurement of %IC was no greater than the uncertainty related to the effect of IC on aquatic resources that have been derived from studies of aquatic condition (e.g., benthic fauna) over a range of %IC. Overall, agreement was variable from one metropolitan area to the next. Agreement improved as assessment unit size increased and declined as the level of urbanization (NLCD %IC) increased. NLCD %IC tended to underestimate reference %IC overall, but NLCD %IC was sometimes greater than reference %IC in urbanized settings.  相似文献   
6.
New Earth observation missions and technologies are delivering large amounts of data. Processing this data requires developing and evaluating novel dimensionality reduction approaches to identify the most informative features for classification and regression tasks. Here we present an exhaustive evaluation of Guided Regularized Random Forest (GRRF), a feature selection method based on Random Forest. GRRF does not require fixing a priori the number of features to be selected or setting a threshold of the feature importance. Moreover, the use of regularization ensures that features selected by GRRF are non-redundant and representative. Our experiments based on various kinds of remote sensing images, show that GRRF selected features provides similar results to those obtained when using all the available features. However, the comparison between GRRF and standard random forest features shows substantial differences: in classification, the mean overall accuracy increases by almost 6% and, in regression, the decrease in RMSE almost reaches 2%. These results demonstrate the potential of GRRF for remote sensing image classification and regression. Especially in the context of increasingly large geodatabases that challenge the application of traditional methods.  相似文献   
7.
为了掌握快速路瓶颈路段异质交通流的演变规律,以缓解交通拥堵,本文以快速路上匝道瓶颈路段为研究对象,构建了考虑安全距离的改进NaSch上匝道模型,利用数值仿真,对不同场景交通流演化过程进行系统性研究。仿真结果显示:在不同条件下,异质交通流中自动驾驶车辆比例的增加对瓶颈路段交通运营状态影响结果各异。在自由流阶段,自动驾驶车辆比例的增加对快速路瓶颈路段运营通行能力的增加无显著影响,自动驾驶车辆比例取0.9时,瓶颈路段运营通行能力反而降低了2.48%;在交通拥堵状态下,当异质交通流中自动驾驶车辆比例达到0.7及以上时,才有助于交通拥堵的消散,且其临界值随交通拥堵状态程度的提高而增大;当交通密度达到100 veh/km以上时,自动驾驶车辆比例的增加无法实质性改善瓶颈路段交通拥堵状态。研究结果可为异质交通流环境下的快速路上匝道瓶颈路段的治堵策略提供理论依据。  相似文献   
8.
石睿  张锡贵 《贵州地质》2020,37(3):266-272
针对现有烟包上包机存在的占地面积过大,易发生掉包以及移动困难等问题,设计了一种基于可编程逻辑控制器(PLC)控制的新型烟包上包机。该设备采用提升链条为输送装置,可以对烟包进行垂直运输,从而减小占地面积;以托盘作为烟包输送的载体,可以使烟包在上包过程中放置平稳,减小掉包的可能性。利用SolidWorks软件完成整机机械结构的三维建模,采用PLC控制系统来控制烟包上包机的上包作业流程。与传统的烟包上包机相比,该新型烟包上包机具有占地面积小,上包作业过程运行平稳,操作简单轻便等优点,可适应多种工作场所。  相似文献   
9.
The Lower Mississippi Alluvial Valley (LMAV) was home to about ten million hectare bottomland hardwood (BLH) forests in the Southern U.S. It experienced over 80 % area loss of the BLH forests in the past centuries and large-scale afforestation in recent decades. Due to the lack of a high-resolution cropland dataset, impacts of land use change (LUC) on the LMAV ecosystem services have not been fully understood. In this study, we developed a novel framework by integrating the machine learning algorithm, county-level agricultural census, and satellite-based cropland products to reconstruct the LMAV cropland distribution during 1850–2018 at a 30-m resolution. Results showed that the LMAV cropland area increased from 0.78 × 104 km2 in 1850 to 6.64 × 104 km2 in 1980 and then decreased to 6.16 × 104 km2 in 2018. Cropland expansion rate was the largest in the 1960s (749 km2 yr−1) but decreased rapidly thereafter, whereas cropland abandonment rate increased substantially in recent decades with the largest rate of 514 km2 yr−1 in the 2010s. Our dataset has three notable features: (1) the depiction of fine spatial details, (2) the integration of the county-level census, and (3) the inclusion of a machine-learning algorithm trained by satellite-based land cover product. Most importantly, our dataset well captured the continuous increasing trend in cropland area from 1930–1960, which was misrepresented by other cropland datasets reconstructed from the state-level census. Our dataset would be important to accurately evaluate the impacts of historical deforestation and recent afforestation efforts on regional ecosystem services, attribute the observed hydrological changes to anthropogenic and natural driving factors, and investigate how the socioeconomic factors control regional LUC pattern. Our framework and dataset are crucial to developing managerial and policy strategies for conserving natural resources and enhancing ecosystem services in the LMAV.  相似文献   
10.
万伟  唐新功  黄清华 《地球物理学报》2019,62(12):4846-4859
陆地可控源电磁法的观测资料可依据频段范围近似地划分为近区场、中间区场及远区场,但采用测量相互正交电、磁分量,并计算视电阻率的资料处理方式只适用于远区场数据.为更有效地利用陆地可控源电磁法不同区间场的观测资料,本文结合三维数值模拟技术并采用电场分量直接进行反演的策略,对不同区间电场的响应特征与探测效果进行了分析.数值模拟结果表明:近区电场的异常响应最明显,异常响应不随频率发生显著变化,但纵向分辨能力差;远区电场异常响应随频率发生显著变化,其探测深度取决于频率的高低;中间区场较为复杂,地表电场异常响应的等值线中心并不是位于异常体中心正上方,而是在沿场传播方向上向异常体与围岩的分界面处偏移,并且发现中间区场资料的加入会影响反演结果的准确性.综合合成数据和野外实测资料的反演结果,发现结合近区场和远区场资料而舍弃中间区场资料的反演效果更佳,这为陆地可控源电磁法资料的反演解释提供了一种有效途径.  相似文献   
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