53 resultados para Terrestrial and Aquatic Ecology


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In a recent letter, Thomsen & Wernberg (2015) rean-alyzed data compiled for our recent paper (Lyonset al., 2014). In that paper, we examined the effectsof macroalgal blooms and macroalgal mats on sevenimportant measures of community structure and eco-system functioning and explored several ecologicaland methodological factors that might explain someof the variation in the observed effects. Thomsen &Wernberg (2015) re-analyzed two small subsets of the data, focusing on experimental studies examining effects of blooms/mats on invertebrate abundance.Their analyses revealed two interesting patterns.First, they showed that macroalgal blooms reducedthe abundance of communities that Thomsen andWernberg categorized as ‘mainly infauna’, whileincreasing the abundance of communities categorized as ‘mainly epifauna’. Second, they showed that theimpacts of macroalgal blooms on ‘mainly infauna’communities increased with algal density in experiments that included multiple levels of algal density.These findings, as well as the conclusions that Thomsen & Wernberg (2015) draw from them, are largely consistent with our own expectations and interpretations. However, we also feel that some caution is required when interpreting the results of their analyses.

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Abstract: The UK Government funded, GB Non-Native Species Information Portal (GBNNSIP) collects and collates data on non-native species in Great Britain making information available online. Resources include a comprehensive register of non-native species and detailed fact sheets for a sub-set, significant to humans or the environment. Reporting of species records are linked to risk analyses, rapid responses and horizon scanning to support the early recognition of threats (Figure 12). The portal has improved flow of new and existing distributional data to the National Biodiversity Network (NBN) to generate distribution maps for the portal. The project is led by the Biological Records Centre and the Marine Biological Association is responsible for marine non-native species within this scheme. The INTERREG IV funded project Marinexus has included professional research and citizen science work, which has fed directly into the portal. The portal outputs and the work of Marinexus have a range of marine governance applications, including supporting work towards MSFD compliance.

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1.There are tens of thousands of species of phytoplankton found throughout the tree of life. Despite this diversity, phytoplankton are often aggregated into a few functional groups according to metabolic traits or biogeochemical role. We investigate the extent to which phytoplankton species dynamics are neutral within functional groups. 2.Seasonal dynamics in many regions of the ocean are known to affect phytoplankton at the functional group level leading to largely predictable patterns of seasonal succession. It is much more difficult to make general statements about the dynamics of individual species. 3.We use a 7 year time-series at station L4 in the Western English Channel with 57 diatom and 17 dinoflagellate species enumerated weekly to test if the abundance of diatom and dinoflagellate species vary randomly within their functional group envelope or if each species is driven uniquely by external factors. 4.We show that the total biomass of the diatom and dinoflagellate functional groups is well predicted by irradiance and temperature and quantify trait values governing the growth rate of both functional groups. The biomass dynamics of the functional groups are not neutral and each has their own distinct responses to environmental forcing. Compared to dinoflagellates, diatoms have faster growth rates, and grow faster under lower irradiance, cooler temperatures, and higher nutrient conditions. 5.The biomass of most species vary randomly within their functional group biomass envelope, most of the time. As a consequence, modelers will find it difficult to predict the biomass of most individual species. Our analysis supports the approach of using a single set of traits for a functional group and suggests that it should be possible to determine these traits from natural communities.

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The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.

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Sublittoral macrobenthic communities in the Skomer Marine Nature Reserve (SMNR), Pembrokeshire, Wales, were sampled at 10 stations in 1993, 1996, 1998, 2003, 2007 and 2009 using a Day grab and a 0.5 mm mesh. The time series is analysed using Similarities Profiles (SIMPROF) tests and associated methods. Q-mode analysis using clustering with Type 1 SIMPROF addresses multivariate structure among samples, showing that there is clear structure associated with differences among years. Inverse (r-mode) analysis using Type 2 SIMPROF decisively rejects a hypothesis that species are not associated with each other. Clustering of the variables (species) with Type 3 SIMPROF identifies groups of species which covary coherently through the time-series. The time-series is characterised by a dramatic decline in abundances and diversity between the 1993 and 1996 surveys. By 1998 there had been a shift in community composition from the 1993 situation, with different species dominating. Communities had recovered in terms of abundance and species richness, but different species dominated the community. No single factor could be identified which unequivocally explained the dramatic changes observed in the SMNR. Possible causes were the effects of dispersed oil and dispersants from the Sea Empress oil spill in February 1996 and the cessation of dredge-spoil disposal off St Anne’s Head in 1995, but the most likely cause was severe weather. With many species, and a demonstrable recovery from an impact, communities within the SMNR appear to be diverse and resilient. If attributable to natural storms, the changes observed here indicate that natural variability may be much more important than is generally taken into account in the design of monitoring programmes.

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Statutory monitoring of the fauna of the ‘mudflats and sandflats not covered by seawater at low tide’ biotope complex on St Martin’s Flats, a part of the Isles of Scilly Complex Special Area of Conservation, was undertaken in 2000, 2004 and 2009. The targets set by Natural England for “characteristic biotopes” were that “composite species, abundance and diversity should not deviate significantly from an established baseline, subject to natural change”. The three specified biotopes could not be distinguished, and instead three assemblages were subjectively defined based on sediment surface features. There were statistically significant natural changes in diversity and species composition between years, especially in the association initially characterized by the razor-clam Ensis, and possible reasons for this are discussed. It is suggested that setting fixed local limits on natural variability is almost always impractical. Two possible approaches to distinguishing between natural and anthropogenic changes are suggested; a change in ecological condition as indicated by AMBI scores, and a significant change in average taxonomic distinctness (Δ+) compared with expectation. The determination of species biomasses as well as abundances might also open more possibilities for assessment. The practice of setting objectives for a marine SAC feature that include the range and number of biotopes cannot be supported, in view the difficulty in ascribing assemblages to recognised biotopes. A more realistic definition of species assemblages might best be gained from examination of the species that consistently make a substantial contribution to the Bray Curtis similarity among samples collected from specific sites.