Environmental drivers of aquatic macrophyte communities in southern tropical African rivers:Zambia as a case study

The first-ever extensive macrophyte survey of Zambian rivers and associated floodplain waterbodies, conducted during 2006–2012, collected 271 samples from 228 sites, mainly located in five freshwater ecoregions of the world primarily represented in Zambia. The results supported the hypothesis that variation in macrophyte community structure (measured as species composition and diversity) in southern tropical African river systems, using Zambia as a case study area, is driven primarily by geographical variation in water physico-chemical conditions. In total, 335 macrophyte taxa were recorded, and a chronological cumulative species records curve for the dataset showed no sign of asymptoting: clearly many additional macrophyte species remain to be found in Zambian rivers. Emergent macrophytes were predominant (236 taxa), together with 26 floating and 73 submerged taxa. Several species were rare in a regional or international context, including two IUCN Red Data List species: Aponogeton rehmanii and Nymphaea divaricata. Ordination and classification analysis of the data found little evidence for temporal change in vegetation, at repeatedly-sampled sites, but strong evidence for the existence of seven groups of samples from geographically-varied study sites. These supported differing sets of vegetation (with eight species assemblages present in the sample-groups) and showed substantial inter-group differences in both macrophyte alpha-diversity, and geographically-varying physico-chemical parameters. The evidence suggested that the main environmental drivers of macrophyte community composition and diversity were altitude, stream order, shade, pH, alkalinity, NO3-N, and underwater light availability, while PO4-P showed slightly lower, but still significant variation between sample-groups

Niche-breadth of freshwater macrophytes occurring in tropical southern African rivers predicts species global latitudinal range

The study tested the hypothesis that measurement, using multivariate Principal Components Analy-sis (PCA), of the niche-breadth of river macrophyte species in southern tropical Africa, may predicttheir larger-scale biogeographical range. Two measures of niche-breadth were calculated for 44 riverinemacrophyte species, from 20 families commonly occurring in Zambia, using an approach based on PCAordination with 16 bio-physico-chemical input variables. These included altitude, stream order, streamflow, pH, conductivity and soluble reactive phosphate concentration (SRP). In the absence of additionalchemical water quality data for Zambian rivers, invertebrate-based measures of general water qualitywere also used. These were benthic macroinvertebrate Average Score per Taxon (ASPT), and individualabundance of nine macroinvertebrate families with differing water quality tolerance, indicated by theirSensitivity Weightings within the Zambian Invertebrate Scoring System (ZISS). Macrophyte large-scalelatitudinal range was derived from world geopositional records held by online databases, and additionalrecords held by the authors. The two niche-breadth metrics divided the species into narrow-niche andintermediate/broad-niche categories, showing significant variation (from one or both of correlation andANOVA test outcomes) in altitude, stream flow, conductivity, SRP, pH and ASPT, but not stream order.Macrophyte alpha-diversity (as a measure of number of individual niches co-existing per habitat) showedno significant relationship with individual species niche-breadth. Narrow-niche species included a higherproportion of Afrotropical endemics than did species with broader niche size. There were significant pre-dictive relationships between macrophyte niche-breadth and latitudinal range of the target species atglobal and Afrotropical scales, but not for the Neotropics.Fil: Kennedy, Michael. University Of Aberdeen; Reino UnidoFil: Lang, Pauline. University of Glasgow; Reino UnidoFil: Tapia Grimaldo, Julissa. University of Glasgow; Reino UnidoFil: Varandas Martins, Sara. University of Glasgow; Reino UnidoFil: Bruce, Alannah. University of Glasgow; Reino UnidoFil: Moore, Isabel. University of Glasgow; Reino UnidoFil: Taubert, Rebeca. University of Glasgow; Reino UnidoFil: Macleod-Nolan, Chantal. University of Glasgow; Reino UnidoFil: McWaters, Stephanie. University of Glasgow; Reino UnidoFil: Briggs, John. University of Glasgow; Reino UnidoFil: Lowe, Steve. University of Glasgow; Reino UnidoFil: Saili, Kochelani. University Of Zambia;Fil: SICHINGABULA, Henry. University Of Zambia;Fil: Dallas, Helen. Nelson Mandela Metropolitan University, Sudafrica; SudáfricaFil: Morrison, Sean. University of Glasgow; Reino UnidoFil: Franceschini, Maria Celeste. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Centro de Ecología Aplicada del Litoral. Universidad Nacional del Nordeste. Centro de Ecología Aplicada del Litoral; ArgentinaFil: Willems, Frank. The Kasanka Trust; ZambiaFil: Bottino, Flavia. Universidad Federal de San Carlos; BrasilFil: MURPHY Kevin. University of Glasgow; Reino Unid

Lean manufacturing model for the reduction of production times and reduction of the returns of defective items in textile industry

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.Textile garment industries must be readily aware of the system’s current situation, respond quickly to changes in style to process orders on time, and manage an appropriate method of work to avoid production delays. In addition, the textile sector plays an important role because it presents a significant weight in the world economy. Likewise, this sector is considered influential when defining an international business agreement. Therefore, adequate management is required in the sector. Otherwise, it will generate a competitive disadvantage because the Peruvian industry is approaching an export recession. This paper proposes using the lean manufacturing methodology to reduce production times. The project is validated through a simulation of the current and proposed processes with the application of lean thinking tools to reduce waste (manufacturing process times)