/ In this paper we develop a conceptual framework for selectingstressor data and analyzing their relationship to geographic patterns ofspecies richness at large spatial scales. Aspects of climate and topography,which are not stressors per se, have been most strongly linked withgeographic patterns of species richness at large spatial scales (e.g.,continental to global scales). The adverse impact of stressors (e.g., habitatloss, pollution) on species has been demonstrated primarily on much smallerspatial scales. To date, there has been a lack of conceptual developmenton how to use stressor data to study geographic patterns of speciesrichness at large spatial scales.The framework we developed includes four components: (1) clarification of theterms stress and stressor and categorization of factors affecting speciesrichness into three groups-anthropogenic stressors, natural stressors, andnatural covariates; (2) synthesis of the existing hypotheses for explaininggeographic patterns of species richness to identify the scales over whichstressors and natural covariates influence species richness and to providesupporting evidence for these relationships through review of previousstudies; (3) identification of three criteria for selection of stressor andcovariate data sets: (a) inclusion of data sets from each of the threecategories identified in item 1, (b) inclusion of data sets representingdifferent aspects of each category, and (c) to the extent possible, analysisof data quality; and (4) identification of two approaches for examiningscale-dependent relationships among stressors, covariates, and patterns ofspecies richness-scaling-up and regression-tree analyses.Based on this framework, we propose 10 data sets as a minimum data base forexamining the effects of stressors and covariates on species richness atlarge spatial scales. These data sets include land cover, roads, wetlands(numbers and loss), exotic species, livestock grazing, surface water pH,pesticide application, climate (and weather), topography, and streams.KEY WORDS: Anthropogenic impacts; Biodiversity; Environmental gradients;Geographic information systems; Hierarchy 相似文献
The technique of DGT (diffusive gradients in thin films) using three diffusive gel thicknesses was applied to estimate the mobility and bioavailability of heavy metals in sediments and porewater of Lake Taihu, China. The DGT results showed significantly positive correlations between Co, Pb, Cd and Mn, and Ni and Fe concentrations in porewater. Cu and Zn showed a significantly negative correlation with Mn, due to Cu combination with carbonates and Zn derived from agricultural pollution, respectively. The rank order of average concentrations of Co, Ni and Cd at each station was DGT1.92 > DGT0.78 > DGT0.39, suggesting stronger resupply from sediments to porewater when using thicker diffusive gels. Comparing centrifugation and DGT measurements, Co, Ni and Cd are highly labile; Mn and Fe are moderately labile; and Cu, Zn and Pb are slightly labile. The variations of AVS concentrations in sediment cores indicate that metal sulfides in deeper layers are easily diffused into surface sediments. 相似文献
The technique of DGT (diffusive gradients in thin films) using three diffusive gel thicknesses was applied to estimate the mobility and bioavailability of heavy metals in sediments and porewater of Lake Taihu, China. The DGT results showed significantly positive correlations between Co, Pb, Cd and Mn, and Ni and Fe concentrations in porewater. Cu and Zn showed a significantly negative correlation with Mn, due to Cu combination with carbonates and Zn derived from agricultural pollution, respectively. The rank order of average concentrations of Co, Ni and Cd at each station was DGT1.92 > DGT0.78 > DGT0.39, suggesting stronger resupply from sediments to porewater when using thicker diffusive gels. Comparing centrifugation and DGT measurements, Co, Ni and Cd are highly labile; Mn and Fe are moderately labile; and Cu, Zn and Pb are slightly labile. The variations of AVS concentrations in sediment cores indicate that metal sulfides in deeper layers are easily diffused into surface sediments. 相似文献
The condition of 25 stream sites in the Yakima River Basin, Washington, were assessed by the U.S. Geological Survey's National Water-Quality Assessment Program. Multimetric condition indices were developed and used to rank sites on the basis of physical, chemical, and biological characteristics. These indices showed that sites in the Cascades and Eastern Cascades ecoregions were largely unimpaired. In contrast, all but two sites in the Columbia Basin ecoregion were impaired, some severely. Agriculture (nutrients and pesticides) was the primary factor associated with impairment and all impaired sites were characterized by multiple indicators of impairment. All indices of biological condition (fish, invertebrates, and algae) declined as agricultural intensity increased. The response exhibited by invertebrates and algae suggested a threshold response with conditions declining precipitously at relatively low levels of agricultural intensity and little response at moderate to high levels of agricultural intensity. This pattern of response suggests that the success of mitigation will vary depending upon where on the response curve the mitigation is undertaken. Because the form of the community condition response is critical to effective water-quality management, the National Water-Quality Assessment Program is conducting studies to examine the response of biota to gradients of land-use intensity and the relevance of these responses to water-quality management. These land-use gradient pilot studies will be conducted in several urban areas starting in 1999. 相似文献
The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC)
for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions
has become the search for the best classification that optimally trades off classification complexity for class homogeneity.
In this study, three techniques are investigated for their ability to find the best classification of the physical environments
of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network,
and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally
trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free
because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that
there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity
acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract
parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure
and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing
Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information
upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive
classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure
of the landscape and to use this knowledge to select the best ELC at the required scale of analysis. 相似文献
The speciation of titrated copper in a dissolved tannic acid (TA) solution with an initial concentration of 4 mmol organic carbon (OC)/l was investigated in a nine-step titration experiment (Cu/OC molar ratio = 0.0030–0.0567). We differentiated between soluble and insoluble Cu species by 0.45 μm filtration. Measurements with a copper ion selective electrode (ISE) and diffusive gradients in thin films (DGT) were conducted to quantify unbound Cu(II) cations (‘free’ Cu) and labile soluble Cu complexes. For the DGT measurements, we used an APA hydrogel and a Chelex 100 chelating resin (Na form). Insoluble organic Cu complexes (>0.45 μm) was the dominant Cu species for Cu/OC = 0.0030–0.0567 with a maximum fraction of 0.96 of total Cu. At Cu/OC > 0.0100, Cu-catalysed degradation of aggregate structures resulted in a strong increase of free Cu and (labile) soluble Cu complexes with a maximum fraction of 0.28 and 0.32 of total Cu, respectively. Labile (i.e. DGT-detectable) soluble Cu complexes had a relatively high averaged diffusion coefficient (D) in the APA hydrogel (3.50 × 10−6– 5.58 × 10−6 cm2 s−1). 相似文献
• Selective molecularly imprinted polymer (MIP) binding gel was prepared.• MIP-DGT showed excellent uptake performance for antibiotics.• In situ measurement of antibiotics in wastewaters via MIP-DGT was developed.• The MIP-DGT method was robust, reliable, and highly sensitive. Urban wastewater is one of main sources for the introduction of antibiotics into the environment. Monitoring the concentrations of antibiotics in wastewater is necessary for estimating the amount of antibiotics discharged into the environment through urban wastewater treatment systems. In this study, we report a novel diffusive gradient in thin films (DGT) method based on molecularly imprinted polymers (MIPs) for in situ measurement of two typical antibiotics, fluoroquinolones (FQs) and sulfonamides (SAs) in urban wastewater. MIPs show specific adsorption toward their templates and their structural analogs, resulting in the selective uptake of the two target antibiotics during MIP-DGT deployment. The uptake performance of the MIP-DGTs was evaluated in the laboratory and was relatively independent of solution pH (4.0–9.0), ionic strength (1–750 mmol/L), and dissolved organic matter (DOM, 0–20 mg/L). MIP-DGT samplers were tested in the effluent of an urban wastewater treatment plant for field trials, where three SA (sulfamethoxazole, sulfapyridine, and trimethoprim) and one FQ (ofloxacin) antibiotics were detected, with concentrations ranging from 25.50 to 117.58 ng/L, which are consistent with the results measured by grab sampling. The total removal efficiency of the antibiotics was 80.1% by the treatment plant. This study demonstrates that MIP-DGT is an effective tool for in situ monitoring of trace antibiotics in complex urban wastewaters. 相似文献
Objective: The objective of this study is to develop a novel algorithm on a mobile system that can warn drivers about the possibility of a collision with a pedestrian. The constraints of the algorithm are near-real-time detection speed and a good detection rate.
Method: Histogram of gradients (HOG)-based detection is widely used in pedestrian safety applications; however, it has low detection speed for real-time systems. Hence, it has no direct usage for mobile systems. In order to achieve near-real-time detection speed, partial Haar transform predetections are applied to an image before HOG detection. The partial and HOG detections are merged and a score-based confidence level is defined for the final detection phase. In this way, the outcome is prioritized and different warning levels can be issued to warn the driver before a possible pedestrian collision.
Results: The proposed algorithm provides an increase in detection speed (from 46 to 76 fps) and detection rate (from 80 to 91%) with respect to HOG-based pedestrian detection. It also improves confidence of the results by multidetection merging and score assignment to detections.
Conclusions: Performance improvement of the algorithm is compared with respect to state-of-the-art detectors/algorithms. Based on the detection rate and detection speed performance, it can be concluded that the proposed algorithm is suitable to be used for mobile systems to warn drivers about the possibility of collision with a pedestrian. 相似文献