4 resultados para Multivariate generalized t -distribution

em Universidad de Alicante


Relevância:

30.00% 30.00%

Publicador:

Resumo:

Changes in benthic community structure are strongly related to environmental factors, and we need to determine how these natural changes occur in order to interpret the possible changes associated with anthropogenic impacts. The aim of this survey was to characterize and classify the polychaete assemblages inhabiting unpolluted soft bottoms in the Spanish Mediterranean in relation to environmental factors. Thirteen localities were sampled at depths between 9 and 31 m, from 2004 to 2006. Multivariate techniques showed that the structure of polychaete assemblages detected in 2004 was consistent over time and correlations between polychaetes and environmental factors were detected. The study area comprises four kinds of communities mainly characterized by polychaete assemblages, sediment types, and depth.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

The interaction of both natural conditions and anthropogenic environmental impacts can lead to different soft-bottom macrobenthic distribution patterns. Soft-bottom macrobenthic community was analysed at different taxonomic scales in order to evaluate whether diverse subset of organisms respond to the variability of the environmental pressures (natural and human induced) showing or not similar distribution patterns. Therefore, this long-term survey had been focused on a heterogeneous area, where both anthropogenic and natural stress may affect the community. Three perpendicular transects to the coast were established and stations at 4, 10 and 15 m depths were sampled at each transect twice a year (summer- winter) from 2004 to 2009. Non-parametric multivariate techniques were used to analyse soft-bottom macrobenthic community distribution and its relation to the environmental factors. Similar distribution patterns between investigated taxonomic levels were detected and they were mainly related to depth.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.