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Indian Ocean humpback dolphins Sousa plumbea inhabit nearshore waters from South Africa to eastern India. Humpback dolphins are vulnerable to conservation threats due to their naturally small population sizes and use of nearshore habitats, where human activities are highest. We investigated the abundance and residency of this species inhabiting Mossel Bay, South Africa, using photographic mark-recapture. Data were collected during 81 surveys in Mossel Bay between 2011 and 2013. Open population modelling using the POPAN parameterisation produced a ‘super-population’ estimate of 125 individuals (95% CI: 61–260) and within-year estimates of between 33 and 86 individuals (2011: 71 [95% CI: 30–168]; 2012: 33 [15–73], 32 [15–70]; 2013: 46 [20–108]). Although less appropriate, closed capture models were also run for comparison with previous studies in the region and generated similar, but slightly smaller, population estimates within each year. We compared our catalogue with opportunistic data collected from East London, Plettenberg Bay, De Hoop and Gansbaai. The only catalogue matches attained were between Plettenberg Bay (n = 44 identified) and Mossel Bay (n = 67 identified), separated by 140?km. Population exchange was moderate, with nine individuals resighted in multiple years between these two areas. This study supports previous findings of long-range movements for this species and provides a baseline from which to assess future impacts on the population. 相似文献
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N.BRATCHELL 《地理学报(英文版)》1989,(3)
Analysis of multivariate response data by modelling the principal components of the response has beenapplied to two sets of data. In both cases principal components analysis revealed the relationships amongthe response variables and exploited them to simplify the problem of modelling and optimizing themultivariate response. The models and optima obtained from the principal components comparedfavourably with the individual models and simultaneous optima. 相似文献
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David T. Adamson PhD PE Grayson Uhlir BS Sharon R. Rauch BA Tessa Klein BS Anthony S. Danko PhD PE 《Ground Water Monitoring & Remediation》2021,41(3):29-40
1,4-Dioxane is a contaminant of emerging concern, and there is significant uncertainty about how its environmental occurrence in groundwater is being assessed given the various analytical methods available. This study compiled public sampling records from 2000 to 2019 that included >106,000 analyses of 1,4-dioxane from 822 different U.S. sites. The 1,4-dioxane detection frequency in the entire dataset (including all methods) was 45%, and the median detected concentration was 10 μg/L, highlighting the dilute nature of 1,4-dioxane in environmental media and the importance of selecting methods with adequate sensitivity. The annual distribution of samples analyzed by each method type confirmed a shift towards methods designed for semi-volatile compounds (Method 8270 and Method 8270 SIM) that exhibited consistently lower reporting limits (median reporting limit for each year typically ≤1 μg/L). In contrast, the method designed for volatile compounds (Method 8260) exhibited less sensitivity for 1,4-dioxane (median reporting limit per year between 40 and 100 μg/L) and its use declined significantly over time with increasing use of the moderately sensitive Method 8260 SIM in later years. This shift contributed to an increase in the 1,4-dioxane detection frequency over time, with a strong correlation between the annual detection frequency and the median reporting limit. Sites where 1,4-dioxane was analyzed but not detected overwhelmingly used less-sensitive methods that may not have been adequate for the expected concentration levels. Given the sub-μg/L groundwater criteria issued for 1,4-dioxane by some regulatory agencies, more sensitive and accurate methods will be increasingly needed to assess compliance. 相似文献
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Ocean Dynamics - The complicated pattern of the chaotic ocean surface depends strongly on the interaction between wind and waves. An accurate representation of momentum and energy exchange at... 相似文献
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Richard Rago BS Andy Rezendes BS Jay Peters MS Kelly Chatterton BS Arun Kammari MS 《Ground Water Monitoring & Remediation》2021,41(2):27-47
A background indoor air study has been completed which includes the collection of indoor air samples from office buildings and schools. The anonymous study was designed with input from the U.S. Environmental Protection Agency and the Massachusetts Department of Environmental Protection. The sampling was implemented in 2013, 2014, and 2015 and included the collection of 25 school building samples and 61 office building samples. The study generated 14,668 new indoor air background data points, with samples collected from buildings located in 26 cities in 18 states, including Arizona, California, Connecticut, Indiana, Kansas, Maine, Massachusetts, Minnesota, Montana, New Hampshire, New Jersey, New York, Nevada, North Carolina, Ohio, Texas, Utah, and Washington. Indoor air background concentrations of target compound volatile organic compounds (VOCs) ranged from less than the laboratory method reporting limit of 0.044 μg/m3 to concentrations up to 1190 μg/m3, with hydrocarbon ranges from less than the reporting method limit of 10 μg/m3 to concentrations up to 3000 μg/m3. Some VOCs were identified ubiquitously in indoor air background, and some were identified at concentrations which exceeded risk-based regulatory screening levels. These study results provide useful and updated information on indoor air background and air quality in offices and schools and can be used in future regulatory guidance update considerations, for further examination of relationships between these data and residential study data, in human health risk assessments and risk communication, and in planning future studies. 相似文献
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When the number of variables exceeds the number of samples, one method of multivariate discriminationis to use principal components analysis to reduce the dimensionality and then to perform canonicalvariates analysis (PC-CVA). This paper proposes an alternative approach in which discriminant analysisis carried out by a weighted principal component analysis of the group means (DPCA). This method doesnot require prior data reduction and produces discriminant factors that are orthogonal in the original dataspace. The theory and performance of the two methods are compared. Although the individual factors ofDPCA are found to be less discriminating than PC-CVA, the overall discrimination, calculated bymultivariate analysis of variance, and the predictive value, estimated by the leaving-one-out error rate,are broadly comparable. 相似文献
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Given a set of test criteria that determine a quality specification,the question often arises whether anyof the tests are redundant because of intercorrelations.Simple selection of tests on the basis of partialcorrelations with the other tests is rejected on the basis that the random error in the data may be causingspurious correlations.One method is to use cross-validation to define the systematic principal components and examine thecorrelation structure in this reduced space.It is shown that the presence of principal componentsdominated by individual tests(‘variable specific’PCs),which are indicated by cross-validation as beingnon-systematic,must be taken into account.Having defined the dimensionality,a variable reductionmethod based on Procrustes rotation selects subsets of tests that preserve the structure of the samples inmultivariate space.This is an attractive proposition in the context of maintaining a quality controlspecification.It is also shown that the variable reduction technique can be used to aid the identificationof the true dimensionality of the data space.This approach is applied to a number of routine tests carriedout on aviation turbine fuel. 相似文献
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