Assessing post-industrial land cover change at the Pine Point Mine,NWT, Canada using multi-temporal Landsat analysis and landscape metrics

This study investigates land cover change near the abandoned Pine Point Mine in Canada’s Northwest Territories. Industrial mineral development transforms local environments, and the effects of such disturbances are often long-lasting, particularly in subarctic, boreal environments where vegetation conversion can take decades. Located in the Boreal Plains Ecozone, the Pine Point Mine was an extensive open pit operation that underwent little reclamation when it shut down in 1988. We apply remote sensing and landscape ecology methods to quantify land cover change in the 20 years following the mine’s closure. Using a time series of near-anniversary Landsat images, we performed a supervised classification to differentiate seven land cover classes. We used raster algebra and landscape metrics to track changes in land cover composition and configuration in the 20 years since the mine shut down. We compared our results with a site in Wood Buffalo National Park that was never subjected to extensive anthropogenic disturbance. This space-for-time substitution provided an analog for how the ecosystem in the Pine Point region might have developed in the absence of industrial mineral development. We found that the dense conifer class was dominant in the park and exhibited larger and more contiguous patches than at the mine site. Bare land at the mine site showed little conversion through time. While the combination of raster algebra and landscape metrics allowed us to track broad changes in land cover composition and configuration, improved access to affordable, high-resolution imagery is necessary to effectively monitor land cover dynamics at abandoned mines.     

Variability in the phytoplankton community of Kavaratti reef ecosystem (northern Indian Ocean) during peak and waning periods of El Niño 2016

El Niño, an interannual climate event characterized by elevated oceanic temperature, is a prime threat for coral reef ecosystems worldwide, owing to their thermal threshold sensitivity. Phytoplankton plays a crucial role in the sustenance of reef trophodynamics. The cell size of the phytoplankton forms the “master morphological trait” with implications for growth, resource acquisition, and adaptability to nutrients. In the context of a strong El Niño prediction for 2015–2016, the present study was undertaken to evaluate the variations in the size-structured phytoplankton of Kavaratti reef waters, a major coral atoll along the southeast coast of India. The present study witnessed a remarkable change in the physicochemical environment of the reef water and massive coral bleaching with the progression of El Niño 2015–2016 from its peak to waning phase. The fluctuations observed in sea surface temperature, pH, and nutrient concentration of the reef water with the El Niño progression resulted in a remarkable shift in phytoplankton size structure, abundance, and community composition of the reef waters. Though low nutrient concentration of the waning phase resulted in lower phytoplankton biomass and abundance, the diazotroph Trichodesmium erythraeum predominated the reef waters, owing to its capability of the atmospheric nitrogen fixation and dissolved organic phosphate utilization.     

Fluctuating asymmetry rather than oxidative stress in <Emphasis Type="Italic">Bufo raddei</Emphasis> can be an accurate indicator of environmental pollution induced by heavy metals

Oxidative stress (OS) and fluctuating asymmetry (FA) as risk markers for environmental stress are widely used to predict changes in the health and fitness of many animals exposed to pollutants. However, from the perspective of protecting declining amphibians, it remains to be verified which one would be a reliable indicator for amphibians exposed to long-term heavy metal pollution under natural conditions. In this study, the OS and FA of Bufo raddei exposed to natural heavy metal pollution were analyzed to determine which marker is more accurate for indicating heavy metal-induced stress. Three years of data were collected during the breeding season of B. raddei from Baiyin (BY), which has been mainly contaminated with Cu, Zn, Pb, and Cd compounds for a long period, and from Liujiaxia (LJX), which is a relatively unpolluted area. Unexpectedly, although significant accumulation of the four heavy metals was found in the kidney and liver of B. raddei from BY, the levels of superoxide dismutase, glutathione peroxidase, and malondialdehyde in these two organs were found to be irregular, with low repeatability in both BY and LJX. However, significant differences in the levels of FA were observed in B. raddei populations from these two areas over the past 3 years (P < 0.01). The degrees of FA in B. raddei populations from BY and LJX were assessed as degree 4 and 1, respectively. In short, this study suggested that FA was a more reliable and effective indicator than OS to monitor and predict long-term environmental stress on anuran amphibians.     

Metal concentrations in American oyster <Emphasis Type="Italic">Crassotrea virginica</Emphasis> and adjacent sediments from harvestable and non-harvestable sites in the Southeastern USA

Human population growth in coastal areas continues to threaten estuarine ecosystems and resources. Populations of Crassostrea virginica have declined across the USA due to water quality degradation, disease pressure, alteration of habitat, and other changes related to anthropogenic impacts. Metals that may be present in estuarine habitats can bioaccumulate in oysters, with potential consequences to the health of oysters and humans consumers. This study (1) evaluated the occurrence and relationships of metal concentrations in oyster tissue versus estuarine sediments, (2) examined oyster tissue concentrations in relation to state water quality designations, and (3) evaluated the potential risk for humans from oyster consumption related to metal concentrations from harvestable waters. Results indicated metal concentrations in sediments and oysters along coastal South Carolina remain low compared to other areas and that concentrations in oyster tissue and adjacent sediments were not highly correlated with each other. However, high concentrations of some metals occurred in oysters sampled from areas designated as Approved for Harvesting. This is important because most harvest area designation systems rely on regular bacterial monitoring when evaluating the safety of consumption. Others safety measurements may be necessary as part of routine monitoring.     

Development and Testing of 2D Finite Difference Model in Open Channels

This study develops a depth-averaged two-dimensional (2D) numerical model using a finite difference method (FDM) on a staggered grid. The governing equations were solved using the Marker and Cell method that was developed at the Los Alamos laboratories by Harlow and Welch in 1965. In the paper, an explicit FDM was used to solve the governing equations. A first-order approximation was used for the temporal derivative. Second-order central difference approximations were used for space discretization. The time step is limited by the Courant–Friedrichs–Lewy (CFL) condition. The time step used in this study depends on the grid spacing and velocity components in the x- and y-directions. The study is divided into two steps: the first step is to develop a depth-averaged 2D numerical model to simulate the flow process. The second constructs a module to calculate the bed load transport and simulate the river morphology in the areas that have steep slopes, torrents, and mountain rivers. Developed model was applied to the artificial channel and a flood event in the Asungjun River section of the mountainous Yangyang Namdae River (South Korea). General simulation results showed that the developed model was in good agreement with the observed data.     

Principal response curves technique for the analysis of multivariate biomonitoring time series

Although chemical and biological monitoring is often used to evaluate the quality of surface waters for regulatory purposes and/or to evaluate environmental status and trends, the resulting biological and chemical data sets are large and difficult to evaluate. Multivariate techniques have long been used to analyse complex data sets. This paper discusses the methods currently in use and introduces the principal response curves method, which overcomes the problem of cluttered graphical results representation that is a great drawback of most conventional methods. To illustrate this, two example data sets are analysed using two ordination techniques, principal component analysis and principal response curves. Whereas PCA results in a difficult-to-interpret diagram, principal response curves related methods are able to show changes in community composition in a diagram that is easy to read. The principal response curves method is used to show trends over time with an internal reference (overall mean or reference year) or external reference (e.g. preferred water quality or reference site). Advantages and disadvantages of both methods are discussed and illustrated.     

Biomonitoring of heavy metals (Cd,Hg, and Pb) and metalloid (As) with the Portuguese common buzzard (Buteo buteo)

The accumulation of heavy metals in the environment may have a wide range of health effects on animals and humans. Thus, in this study, the concentrations of arsenic (As), cadmium (Cd), lead (Pb), and mercury (Hg) in the blood and tissues (liver and kidney) of Portuguese common buzzards (Buteo buteo) were determined by inductively coupled plasma-mass spectrometer (ICP-MS) in order to monitor environmental pollution to these elements. In general, Hg and As were the elements which appeared in the highest and lowest concentrations, respectively. A highest percentage of non-detected concentration was found for blood Cd (94.6 %) but, in turn, it was the only metal that was detected in all kidney samples. The kidney was the analyzed sample which showed the highest concentrations of each element evaluated. Statistically, significant differences among blood, liver, and kidney samples were observed for As and Cd (P?相似文献   

Building low-carbon and disaster-resilient communities: integrating climate mitigation and adaptation into the assessment of self-help housing design

Housing is not only one of the major sources of carbon dioxide (CO₂) emissions, but it has been increasingly vulnerable to climate-induced disasters, particularly those sheltering the urban poor. Both mitigation and adaptation measures are therefore required for the design and construction of low-income housing to encourage low carbon development and improve resilience to disasters. As self-help housing—the common type of housing for the urban poor in developing countries—is usually built by ordinary people with participatory approach, it is crucial to develop a low-carbon and disaster-resilient assessment tool for assisting them in making informed decisions during planning process. The objective of this article is to propose a new approach for developing a low-carbon and disaster-resilient assessment tool for self-help housing (LoDAT-SH) by combining opinions from experts and community residents to assign weights, identify indicators, and establish benchmarks with the aim to develop a simple, relevant, and practical tool for non-expert users like self-help residents. The application of the proposed methodology to a case study of a developing country, Thailand, shows the ability of LoDAT-SH, which contains 45 indicators in the four categories of low carbon development, disaster resilience, community participation, and financial consideration, in enabling self-help residents to assess the performance of their housing design, identify potential measures to create a low-carbon and disaster-resilient housing, and prioritize such actions. To support the creation of a low-carbon and disaster-resilient housing as the mitigation and adaptation strategy for urban development at the global level, the study suggests that the methodology of LoDAT-SH should be replicated to develop a more comprehensive assessment tool applicable for the use in self-help housing design in other developing countries, which will house about 900 million of the urban poor by 2020.     

Thermotolerant coliform loadings to coastal areas of Santa Catarina (Brazil) evidence the effect of growing urbanisation and insufficient provision of sewerage infrastructure

Thermotolerant coliform (TC) loadings were quantified for 49 catchments draining into the North and South Bays of Santa Catarina (SC, southeastern Brazil), an area known for its tourism and aquaculture. TC loadings were calculated based on flow measurements taken in 26 rivers. TC concentrations ere quantified based on surface water samples collected at 49 catchment outlets in 2012 and 2013. Median TC loads ranged from 3.7 × 10³ to 6.8 × 10⁸ MPN s^?1. TC loadings in the catchments increased in proportion to increases in resident human population, population density and percentage of urbanised area. Catchments with more than 60% of area covered by wastewater collection and treatment systems had higher TC loads per person than catchments with less than 25%. Based on the study catchments, these results indicate that current sewerage infrastructure is ineffective in reducing contamination of faecal origin to surface waters. These findings have important implications for the management of microbiological health hazards in bathing, recreational and shellfish aquaculture waters in the North and South Bays of Santa Catarina Island.