Bioinformatics tools in predictive ecology: Applications to fisheries

This article is made available throught the Brunel Open Access Publishing Fund - Copygith @ 2012 Tucker et al.There has been a huge effort in the advancement of analytical techniques for molecular biological data over the past decade. This has led to many novel algorithms that are specialized to deal with data associated with biological phenomena, such as gene expression and protein interactions. In contrast, ecological data analysis has remained focused to some degree on off-the-shelf statistical techniques though this is starting to change with the adoption of state-of-the-art methods, where few assumptions can be made about the data and a more explorative approach is required, for example, through the use of Bayesian networks. In this paper, some novel bioinformatics tools for microarray data are discussed along with their ‘crossover potential’ with an application to fisheries data. In particular, a focus is made on the development of models that identify functionally equivalent species in different fish communities with the aim of predicting functional collapse

Aboveground Herbivory Shapes the Biomass Distribution and Flux of Soil Invertebrates

Contains fulltext : 72659.pdf ( ) (Open Access)Background Living soil invertebrates provide a universal currency for quality that integrates physical and chemical variables with biogeography as the invertebrates reflect their habitat and most ecological changes occurring therein. The specific goal was the identification of “reference” states for soil sustainability and ecosystem functioning in grazed vs. ungrazed sites. Methodology/Principal Findings Bacterial cells were counted by fluorescent staining and combined direct microscopy and automatic image analysis; invertebrates (nematodes, mites, insects, oligochaetes) were sampled and their body size measured individually to allow allometric scaling. Numerical allometry analyses food webs by a direct comparison of weight averages of components and thus might characterize the detrital soil food webs of our 135 sites regardless of taxonomy. Sharp differences in the frequency distributions are shown. Overall higher biomasses of invertebrates occur in grasslands, and all larger soil organisms differed remarkably. Conclusions/Significance Strong statistical evidence supports a hypothesis explaining from an allometric perspective how the faunal biomass distribution and the energetic flux are affected by livestock, nutrient availability and land use. Our aim is to propose faunal biomass flux and biomass distribution as quantitative descriptors of soil community composition and function, and to illustrate the application of these allometric indicators to soil systems.7 p

Estimating high resolution trawl fishing effort from satellite-based vessel monitoring system data

High resolution estimates of trawling effort are needed to underpin studies of trawling impacts on species, habitats, and ecosystem processes, and to monitor responses to area closure and other management actions. Satellite-based vessel monitoring systems (VMS) were designed for fishery control and enforcement, but they provide potentially valuable source information on spatial and temporal patterns of trawling activity at multiple scales. Based on an analysis of VMS data for UK beam trawlers in the North Sea, a method is described for identifying trawling activity and estimating fishing intensity based on the minimum and maximum potential spatial extent of trawling effort from VMS data. The optimal method for identifying trawling and steaming behaviour combined speed and directionality rules and correctly identified trawling and steaming in 99% and 95% of cases, respectively. Using speed- and directionality-filtered VMS data, trawling effort can be reported as area impacted per unit time per unit area at a range of grid scales from 1 km to 100 km (10 000 km2). Trawling effort is accurately represented at a grid cell resolution of 3 km or less