941 resultados para golden mussel


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Department of Marine Biology, Microbiology and Biochemistry, Cochin University of Science and Technology

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School of Environmental Studies, Cochin University of Science and Technology

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In this thesis certain important aspects of heavy metal toxicity have been worked out. Recent studies have clearly shown that when experimental media contained more than one heavy metals, such metals could conspicuously influence the toxic reaction of the animals both in terms of quantity and nature. The experimental results available on individual metal toxicity show that, in majority of such results, unrealistically high concentrations of dissolved metals are involved. A remarkable number of factors have been shown to influence metal toxicity such as various environmental factors particularly temperature and salinity, the condition of the organism and the ability of some of the marine organisms to adapt to metallic contamination. Further, some of the more sensitive functions like embryonic and larval development, growth and fecundity, oxygen utilization and the function of various enzymes are found to be demonstrably sensitive in the presence of heavy metals. However, some of the above functions could be compensated for by adaptive process. If it is assumed that the presence of a single metal in higher concentrations could affect the life function of marine animals, more than one metal in the experimental media should manifest such effects in a greater scale. Commonly known as synergism or more than additivity, majority of heavy metals bring about synergistic reaction .The work presented in this thesis comprises lethal and sublethal toxicities of different salt forms of copper and silver on the brown mussel Perna indica. during the present investigation sublethal concentrations of copper and silver in their dent effects on survival, oxygen consumption, filtration, accumulation and depuration on Perna indica. The results are presented under different sections to make the presentation meaningful .

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Industrialisation affects air, water, and soil. Industrial effluents which enter the aquatic environment either by direct disposal or through run off, affect living organisms at morphological and physiological levels. In any living tissue toxic materials exert their effects first at molecular and biochemical levels (Robbins and Angell, 1976). Most of the industrial effluents contain elevated concentrations of organic and inorganic chemicals capable of eliciting stimulatory or inhibitory effects on the metabolism of aquatic organisms. Heavy metals form an important group of environmental pollutants. Effects of pollution on the aquatic environment by heavy metals have received considerable attention in recent years due to their toxicity even at very low levels, persistence in the environment, and chances of getting biomagnified. A pollutant that does not affect a particular process under normal unstressed condition may affect the ability of the animal to adjust to changing environmental conditions which ultimately decrease its chances of survival (Thurberg et al., 1973

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We compared habitat features of Golden-winged Warbler (Vermivora chrysoptera) territories in the presence and absence of the Blue-winged Warbler (V. cyanoptera) on reclaimed coal mines in southeastern Kentucky, USA. Our objective was to determine whether there are species specific differences in habitat that can be manipulated to encourage population persistence of the Golden-winged Warbler. When compared with Blue-winged Warblers, Golden-winged Warblers established territories at higher elevations and with greater percentages of grass and canopy cover. Mean territory size (minimum convex polygon) was 1.3 ha (se = 0.1) for Golden-winged Warbler in absence of Blue-winged Warbler, 1.7 ha (se = 0.3) for Golden-winged Warbler coexisting with Blue-winged Warbler, and 2.1 ha (se = 0.3) for Blue-winged Warbler. Territory overlap occurred within and between species (18 of n = 73 territories, 24.7%). All Golden-winged and Blue-winged Warblers established territories that included an edge between reclaimed mine land and mature forest, as opposed to establishing territories in open grassland/shrubland habitat. The mean distance territories extended from a forest edge was 28.0 m (se = 3.8) for Golden-winged Warbler in absence of Blue-winged Warbler, 44.7 m (se = 5.7) for Golden-winged Warbler coexisting with Blue-winged Warbler, and 33.1 m (se = 6.1) for Blue-winged Warbler. Neither territory size nor distances to forest edges differed significantly between Golden-winged Warbler in presence or absence of Blue-winged Warbler. According to Monte Carlo analyses, orchardgrass (Dactylis glomerata), green ash (Fraxinus pennsylvanica) seedlings and saplings, and black locust (Robinia pseudoacacia) saplings were indicative of sites with only Golden-winged Warblers. Sericea lespedeza, goldenrod (Solidago spp.), clematis vine (Clematis spp.), and blackberry (Rubus spp.) were indicative of sites where both species occurred. Our findings complement recent genetic studies and add another factor for examining Golden-winged Warbler population decline. Further, information from our study will aid land managers in manipulating habitat for the Golden-winged Warbler.

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Conservation planning requires identifying pertinent habitat factors and locating geographic locations where land management may improve habitat conditions for high priority species. I derived habitat models and mapped predicted abundance for the Golden-winged Warbler (Vermivora chrysoptera), a species of high conservation concern, using bird counts, environmental variables, and hierarchical models applied at multiple spatial scales. My aim was to understand habitat associations at multiple spatial scales and create a predictive abundance map for purposes of conservation planning for the Golden-winged Warbler. My models indicated a substantial influence of landscape conditions, including strong positive associations with total forest composition within the landscape. However, many of the associations I observed were counter to reported associations at finer spatial extents; for instance, I found Golden-winged Warblers negatively associated with several measures of edge habitat. No single spatial scale dominated, indicating that this species is responding to factors at multiple spatial scales. I found Golden-winged Warbler abundance was negatively related with Blue-winged Warbler (Vermivora cyanoptera) abundance. I also observed a north-south spatial trend suggestive of a regional climate effect that was not previously noted for this species. The map of predicted abundance indicated a large area of concentrated abundance in west-central Wisconsin, with smaller areas of high abundance along the northern periphery of the Prairie Hardwood Transition. This map of predicted abundance compared favorably with independent evaluation data sets and can thus be used to inform regional planning efforts devoted to conserving this species.

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In recent years, the eastern foothills of the Rocky Mountains in northeastern British Columbia have received interest as a site of industrial wind energy development but, simultaneously, have been the subject of concern about wind development coinciding with a known migratory corridor of Golden Eagles (Aquila chrysaetos). We tracked and quantified eagle flights that crossed or followed ridgelines slated for one such wind development. We found that hourly passage rates during fall migration peaked at midday and increased by 17% with each 1 km/h increase in wind speed and by 11% with each 1°C increase in temperature. The propensity to cross the ridge tops where turbines would be situated differed between age classes, with juvenile eagles almost twice as likely to traverse the ridge-top area as adults or subadults. During fall migration, Golden Eagles were more likely to cross ridges at turbine heights (risk zone, < 150 m above ground) under headwinds or tailwinds, but this likelihood decreased with increasing temperature. Conversely, during spring migration, eagles were more likely to move within the ridge-top area under eastern crosswinds. Identifying Golden Eagle flight routes and altitudes with respect to major weather systems and local topography in the Rockies may help identify scenarios in which the potential for collisions is greatest at this and other installations.

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Population models are essential components of large-scale conservation and management plans for the federally endangered Golden-cheeked Warbler (Setophaga chrysoparia; hereafter GCWA). However, existing models are based on vital rate estimates calculated using relatively small data sets that are now more than a decade old. We estimated more current, precise adult and juvenile apparent survival (Φ) probabilities and their associated variances for male GCWAs. In addition to providing estimates for use in population modeling, we tested hypotheses about spatial and temporal variation in Φ. We assessed whether a linear trend in Φ or a change in the overall mean Φ corresponded to an observed increase in GCWA abundance during 1992-2000 and if Φ varied among study plots. To accomplish these objectives, we analyzed long-term GCWA capture-resight data from 1992 through 2011, collected across seven study plots on the Fort Hood Military Reservation using a Cormack-Jolly-Seber model structure within program MARK. We also estimated Φ process and sampling variances using a variance-components approach. Our results did not provide evidence of site-specific variation in adult Φ on the installation. Because of a lack of data, we could not assess whether juvenile Φ varied spatially. We did not detect a strong temporal association between GCWA abundance and Φ. Mean estimates of Φ for adult and juvenile male GCWAs for all years analyzed were 0.47 with a process variance of 0.0120 and a sampling variance of 0.0113 and 0.28 with a process variance of 0.0076 and a sampling variance of 0.0149, respectively. Although juvenile Φ did not differ greatly from previous estimates, our adult Φ estimate suggests previous GCWA population models were overly optimistic with respect to adult survival. These updated Φ probabilities and their associated variances will be incorporated into new population models to assist with GCWA conservation decision making.

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The Golden-winged Warbler (Vermivora chrysoptera) is currently being considered for protected status under the U.S. Endangered Species Act. The creation of breeding habitat in the Appalachian Mountains is considered a conservation priority for this songbird, which is dependent on extensively forested landscapes with adequate availability of young forest. We modeled abundance of Golden-winged Warbler males in regenerating harvested forest stands that were 0-17 years postharvest at both mid-Appalachian and northeast Pennsylvania regional scales using stand and within-stand characteristics of 222 regenerating stands, 2010-2011. Variables that were most influential at the mid-Appalachian scale were different than those in the northeast region. Across the mid-Appalachian ecoregion, the proportion of young forest cover, i.e., shrub/scrub cover, within 1 km of regenerating stands best explained abundance of Golden-winged Warblers. Golden-winged Warbler response was best explained by a concave quadratic relationship in which abundance was highest with 5-15% land in young forest cover. We also found evidence that the amount of herbaceous cover, i.e., the amount of grasses and forbs, within a regenerating stand positively influenced abundance of Golden-winged Warblers. In northeastern Pennsylvania, where young forest cover is found in high proportions, the distance to the nearest regenerating stand best explained variation in abundance of Golden-winged Warblers. Abundance of Golden-winged Warblers was <1 male per survey when another regenerating stand was >1500 m away. When modeling within-stand features in the northeast region, many of the models were closely ranked, indicating that multiple variables likely explained Golden-winged Warbler response to within-stand conditions. Based on our findings, we have proposed several management guidelines for land managers interested in creating breeding habitat for Golden-winged Warblers using commercial timber operations. For example, we recommend when managing for Golden-winged Warblers in the central Appalachian Mountains that managers should strive for 15% young forest in a heavily forested landscape (>70% forest cover) and cluster stands within 1-2 km of other young forest habitats.

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Among shrubland- and young forest-nesting bird species in North America, Golden-winged Warblers (Vermivora chrysoptera) are one of the most rapidly declining partly because of limited nesting habitat. Creation and management of high quality vegetation communities used for nesting are needed to reduce declines. Thus, we examined whether common characteristics could be managed across much of the Golden-winged Warbler’s breeding range to increase daily survival rate (DSR) of nests. We monitored 388 nests on 62 sites throughout Minnesota, Wisconsin, New York, North Carolina, Pennsylvania, Tennessee, and West Virginia. We evaluated competing DSR models in spatial-temporal (dominant vegetation type, population segment, state, and year), intraseasonal (nest stage and time-within-season), and vegetation model suites. The best-supported DSR models among the three model suites suggested potential associations between daily survival rate of nests and state, time-within-season, percent grass and Rubus cover within 1 m of the nest, and distance to later successional forest edge. Overall, grass cover (negative association with DSR above 50%) and Rubus cover (DSR lowest at about 30%) within 1 m of the nest and distance to later successional forest edge (negative association with DSR) may represent common management targets across our states for increasing Golden-winged Warbler DSR, particularly in the Appalachian Mountains population segment. Context-specific adjustments to management strategies, such as in wetlands or areas of overlap with Blue-winged Warblers (Vermivora cyanoptera), may be necessary to increase DSR for Golden-winged Warblers.

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