100 resultados para Nutritional Ecology


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Engagement with globalisation is growing in the field of youth transitions from out of home care. This includes cross national exchange of research, policy and practise, regional advocacy networking and global policy development. Furthering this emerging international child welfare perspective requires extending it to countries in the developing world and building conceptual frameworks which encompass a social ecology of care leaving, including its global dimension, the latter needs to address not only the needs, expectations and rights of care leavers but also the theories of change underpinning service design and delivery. Such a model is presented combining resilience and social capital as personal assets situated within a social ecology of support. To illustrate how this provides a means to help engage with the experience of countries where there appears to be very little information available on care leaving, a small scale South African initiative is considered. SA-YES is a youth mentoring project for young people leaving a variety of out of home placements. Planned as a three-year pilot, initial results are encouraging but require more rigorous evaluation focusing on program process and outcomes, quality of interpersonal relationships and synchronisation with cultural expectations and policy environment.

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Microbial ecology is currently undergoing a revolution, with repercussions spreading throughout microbiology, ecology and ecosystem science. The rapid accumulation of molecular data is uncovering vast diversity, abundant uncultivated microbial groups and novel microbial functions. This accumulation of data requires the application of theory to provide organization, structure, mechanistic insight and, ultimately, predictive power that is of practical value, but the application of theory in microbial ecology is currently very limited. Here we argue that the full potential of the ongoing revolution will not be realized if research is not directed and driven by theory, and that the generality of established ecological theory must be tested using microbial systems.

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I draw attention to the need for ecologists to take spatial structure into account more seriously in hypothesis testing. If spatial autocorrelation is ignored, as it usually is, then analyses of ecological patterns in terms of environmental factors can produce very misleading results. This is demonstrated using synthetic but realistic spatial patterns with known spatial properties which are subjected to classical correlation and multiple regression analyses. Correlation between an autocorrelated response variable and each of a set of explanatory variables is strongly biased in favour of those explanatory variables that are highly autocorrelated - the expected magnitude of the correlation coefficient increases with autocorrelation even if the spatial patterns are completely independent. Similarly, multiple regression analysis finds highly autocorrelated explanatory variables "significant" much more frequently than it should. The chances of mistakenly identifying a "significant" slope across an autocorrelated pattern is very high if classical regression is used. Consequently, under these circumstances strongly autocorrelated environmental factors reported in the literature as associated with ecological patterns may not actually be significant. It is likely that these factors wrongly described as important constitute a red-shifted subset of the set of potential explanations, and that more spatially discontinuous factors (those with bluer spectra) are actually relatively more important than their present status suggests. There is much that ecologists can do to improve on this situation. I discuss various approaches to the problem of spatial autocorrelation from the literature and present a randomisation test for the association of two spatial patterns which has advantages over currently available methods.

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The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.

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Spatial analysis was used to explore the distribution of individual species in an ectomycorrhizal (ECM) fungal community to address: whether mycorrhizas of individual ECM fungal species were patchily distributed, and at what scale; and what the causes of this patchiness might be. Ectomycorrhizas were extracted from spatially explicit samples of the surface organic horizons of a pine plantation. The number of mycorrhizas of each ECM fungal species was recorded using morphotyping combined with internal transcribed spacer (ITS) sequencing. Semivariograms, kriging and cluster analyses were used to determine both the extent and scale of spatial autocorrelation in species abundances, potential interactions between species, and change over time. The mycorrhizas of some, but not all, ECM fungal species were patchily distributed and the size of patches differed between species. The relative abundance of individual ECM fungal species and the position of patches of ectomycorrhizas changed between years. Spatial and temporal analysis revealed a dynamic ECM fungal community with many interspecific interactions taking place, despite the homogeneity of the host community. The spatial pattern of mycorrhizas was influenced by the underlying distribution of fine roots, but local root density was in turn influenced by the presence of specific fungal species.

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Lakes in Arctic and subarctic regions display extreme levels of seasonal variation in light, temperature and ice cover. Comparatively little is known regarding the effects of such seasonal variation on the diet and resource use of fish species inhabiting these systems. Variation in the diet of European whitefish Coregonus lavaretus (L.) during periods of ice cover in this region is often regarded as 'common knowledge'; however, this aspect of the species' ecology has not been examined empirically. Here, we outline the differences in invertebrate community structure, fish activity, and resource use of monomorphic whitefish populations between summer (August-September) and winter (February-March) in three subarctic lakes in Finnish Lapland. Benthic macroinvertebrate densities did not exhibit measurable differences between summer and winter. Zooplankton diversity and abundance, and activity levels of all fish species (measured as catch per unit effort) were lower in winter. The summer diet of C. lavaretus was typical of a generalist utilising a variety of prey sources. In winter, its dietary niche was significantly reduced, and the diet was dominated by chironomid larvae in all study sites. Pelagic productivity decreases during winter, and fish species inhabiting these systems are therefore restricted to feeding on benthic prey. Sampling time has strong effect on our understanding of resource utilisation by whitefish in subarctic lakes and should be taken into account in future studies of these systems. © 2012 John Wiley & Sons A/S.

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Although widespread, the ecology of the whiskered bat, Myotis mystacinus in Europe remains poorly understood. Ireland is positioned at the most western extreme of this species' range. To ascertain the ecology of M. mystacinus at its geographic range extreme, the roosting behaviour, home range and habitat use of females in a maternity roost in Ireland was investigated by radio-tracking. M. mystacinus were active in a diversity of habitats: namely, mixed woodland, riparian vegetation, arable land and rough grassland. However, only mixed woodland and riparian habitats were selected as core foraging areas. This is in contrast to a previous study from Britain where only pasture was utilised but is in agreement with data from Slovakia, where woodland was also selected, whilst riparian areas were also utilised by this species in Germany. A high degree of overlap in the foraging areas of individuals was observed. A total of seven roosts were utilised by tracked bats and roost switching behaviour was observed. We discuss our contrasting results in respect to range limitations, regional variability in landscape structure and the composition of bat communities. The present results have implications for the conservation of M. mystacinus within Ireland and other parts of its range, highlighting the need for range wide ecological studies. Regional variability in the ecology of bats related to landscape factors is an important consideration for bat conservation and therefore must be incorporated into future management plans. (C) 2012 Deutsche Gesellschaft fur Saugetierkunde. Published by Elsevier GmbH. All rights reserved.