Modelling and analysis of recruitment distributions

Recruitment data for 18 marine fish stocks are smoothed using 10 parametric families of probability distributions. Comparative fit of the 10 families is assessed by means of the maximized log-likelihood. Results indicate that the gamma distribution provides an overall good fit in the right-hand tail of the data, but that some adjustment to the gamma distribution is called for in the left-hand tail. Weight functions and weighted distributions are suggested as one means of achieving the needed adjustment.     

Transport of Pollutant in Open Channel with Short Waves

This study examines the effect of short period water waves on the longitudinal mixing of pollutants in open channel flow. These waves create orbital motions and therefore increase the magnitude of the dispersion coefficient. Experiments are conducted for non-wavy and wavy flow. The values of the longitudinal dispersion coefficients are determined by applying the method of least squares to the measured solute concentrations at various time intervals. For non-wavy flow, the measured values of longitudinal dispersion coefficient match closely with those computed from the empirical equation given by Seo [1]. For wavy flow, a new factor called the wave parameter (a/TU _*, a=wave amplitude, T=wave period, U _*=shear velocity) is found important and a nonlinear multiple regression analysis is used to derive a new expression for the wave induced longitudinal dispersion coefficient (WILDC). An uncertainty analysis is conducted as per IS Code 5168 and the confidence interval is determined. Linear water wave theory is applied to modify the existing expression of the longitudinal dispersion coefficient of Seo [1] by including the effect of short waves. A mathematical model for WILDC is then developed. Comparative study between wavy and non-wavy flow cases has been conducted. The results clearly show an increase in the magnitude of longitudinal dispersion coefficient in the presence of waves.     

PULSE,progressive upper level set scan statistic for geospatial hotspot detection

This paper presents a scan statistic, progressive upper level set (PULSE) scan statistic, for geospatial hotspot detection and its software implementation. Like ULS, the PULSE scan statistic is based on the arbitrarily shaped scan window and can be adapted for a network setting. PULSE is a refinement of the upper level set (ULS) scan statistic. Like some other likelihood based scanning devices, the ULS scan statistic identifies maximum likelihood estimate (MLE) zones that tend to be ‘stringy’ and sprawling. Its search path increases possibility of inclusion of extraneous cells in its MLE zones and, to a smaller extent, of exclusion of cells that belong to a true hotspot from its MLE zone. The PULSE scan statistic achieves improvement over the ULS scan statistic in two ways. First, it begins its search for a most likely zone with a large population of candidate zones obtained by modifying the ULS tree structure and continues its search using a genetic algorithm. Secondly, to reduce chances of generating an MLE that is excessively stringy and that includes extraneous cells in the MLE zone, PULSE uses cardinality and compactness of zones along with their likelihoods as the fitness function in the genetic algorithm and uses several pertinent criteria including evenness of intra-zone cellular response ratios to determine the MLE zone. To reduce computation, Gumbel distribution of extreme values is used to determine the p-value of the MLE zone. Better results come at the cost of increased processing time. An evaluative performance study is presented.     

Next-generation sequencing in the biodiversity conservation of endangered medicinal plants

Environmental Science and Pollution Research - Medicinal plants have been used as traditional herbal medicines in the treatment of various types of diseases. However, the increased demand for these...     

Detection and delineation of critical areas using echelons and spatial scan statistics with synoptic cellular data

Geographical surveillance for hotspot detection and delineation has become an important area of investigation both in geospatial ecosystem health and in geospatial public health. In order to find critical areas based on synoptic cellular data, geospatial ecosystem health investigations apply recently discovered echelon tools. In order to find elevated rate areas based on synoptic cellular data, geospatial public health investigations apply recently discovered spatial scan statistic tools. The purpose of this paper is to conceptualize a joint role for these together in the spirit of a cross-disciplinary cross-fertilization to accomplish more effective and efficient geographical surveillance for hotspot detection and delineation, and early warning system.     

Environmental fate of chlorantraniliprole residues on cauliflower using QuEChERS technique

Chlorantraniliprole, an anthranilic diamide insecticide with novel mode of action is found effective against several lepidopteran as well as coleopteran, dipteran, and hemipteran pests. The present studies were carried out to study the dissipation pattern of chlorantraniliprole on cauliflower and to suggest suitable waiting period for the safety of consumers. Quick, easy, cheap, effective, rugged, and safe method was used for the extraction and cleanup of samples and the residues of chlorantraniliprole were estimated using high-performance liquid chromatograph (HPLC) and confirmed by liquid chromatograph–mass spectrometer and high-performance thin layer chromatograph. Following three applications of chlorantraniliprole (Coragen 18.5 SC) at recommended dose (9.25 g a.i.?ha^?1) and double the recommended dose (18.50 g a.i.?ha^?1), the average initial deposits of chlorantraniliprole were observed to be 0.18 and 0.29 mg kg^?1, respectively. These deposits were found to be less than the maximum residue limit of 2.0 mg kg^?1 prescribed by the Codex Alimentarius Commission. These residues dissipated below the limit of quantification of 0.10 mg kg^?1 after 3 and 5 days at recommended and double the recommended dosages, respectively. The half-life value (T _1/2) of chlorantraniliprole was worked out to be 1.36 days following its application at recommended dosages. Hence, the use of this pesticide at recommended dosages does not seem to pose any risk, and a waiting period of 1 day is suggested for safe consumption of cauliflower curds.     

Biodiversity protection funding preference: a case study of hotspot geoinformatics and digital governance for the Map of Italian Nature in the presence of multiple indicators of ecological value,ecological sensitivity and anthropic pressure for the Oltrepò Pavese and Ligurian-Emilian Apennine study area in Italy

The environmental decision-maker is aware of the increasing difficulties in finding sufficient financial resources for nature conservation. So he must focus his attention on ecological situations that more than the others merit considering and defending because of elevated value but also because of risk for their intrinsic characteristics and for human pressure acting on them. Usually an ecological scientist focuses his attention on the natural patches of the landscape, analyzing their peculiar ecological traits forgetting that, even if we want to protect some environmental critical situations, this can be done only moving to the administrative partition of the territory since the central and local environmental stakeholders have primary interest in providing funds to those involved in those critical situations. The present work shows a methodological approach, consisting of a set of statistical and geoinformational tools, considering both ecological and socio-demographical indicators. The goal is not simply to give some general guidelines for environmental policies to the involved stakeholders but focuses more on finding out which administrative local partitions in a study area are more worthy to receive urgently the priority funds for biodiversity protection to face critical environmental situations often due to a combination of intrinsic ecological parameters and external human pressure ones. Obtaining results that cover 5% of the Communes involved in the area seems to be a realistic result that a decision-maker can support and fund. Methodologically and geospatial data analytically, the investigation offers interesting challenges for surveillance geoinformatics of hotspot detection and prioritization, because of the presence of multiple hotspots and multiple sets of multiple indicators.