Permanent Genetic Resources added to Molecular Ecology Resources Database 1 May 2009-31 July 2009

This article documents the addition of 512 microsatellite marker loci and nine pairs of Single Nucleotide Polymorphism (SNP) sequencing primers to the Molecular Ecology Resources Database. Loci were developed for the following species: Alcippe morrisonia morrisonia, Bashania fangiana, Bashania fargesii, Chaetodon vagabundus, Colletes floralis, Coluber constrictor flaviventris, Coptotermes gestroi, Crotophaga major, Cyprinella lutrensis, Danaus plexippus, Fagus grandifolia, Falco tinnunculus, Fletcherimyia fletcheri, Hydrilla verticillata, Laterallus jamaicensis coturniculus, Leavenworthia alabamica, Marmosops incanus, Miichthys miiuy, Nasua nasua, Noturus exilis, Odontesthes bonariensis, Quadrula fragosa, Pinctada maxima, Pseudaletia separata, Pseudoperonospora cubensis, Podocarpus elatus, Portunus trituberculatus, Rhagoletis cerasi, Rhinella schneideri, Sarracenia alata, Skeletonema marinoi, Sminthurus viridis, Syngnathus abaster, Uroteuthis (Photololigo) chinensis, Verticillium dahliae, Wasmannia auropunctata, and Zygochlamys patagonica. These loci were cross-tested on the following species: Chaetodon baronessa, Falco columbarius, Falco eleonorae, Falco naumanni, Falco peregrinus, Falco subbuteo, Didelphis aurita, Gracilinanus microtarsus, Marmosops paulensis, Monodelphis Americana, Odontesthes hatcheri, Podocarpus grayi, Podocarpus lawrencei, Podocarpus smithii, Portunus pelagicus, Syngnathus acus, Syngnathus typhle,Uroteuthis (Photololigo) edulis, Uroteuthis (Photololigo) duvauceli and Verticillium albo-atrum. This article also documents the addition of nine sequencing primer pairs and sixteen allele specific primers or probes for Oncorhynchus mykiss and Oncorhynchus tshawytscha; these primers and assays were cross-tested in both species.

Sequentially assembled food webs and extremum principles in ecosystem ecology

Successional changes during sequential assembly of food webs were examined. This was carried out by numerical methods, drawing one species at a time from a species pool and obtaining the permanent (persistent) community emerging at each step. Interactions among species were based on some simple rules about body sizes of consumers and their prey, and community dynamics were described in terms of flows of biomass density.

Habitat effects on the spatial ecology of the European badger (Meles meles)

This study investigates how habitat variation affects sett density, the number of animals per social group and group territory size in the badger (Meles meles). Identical methods were applied in three habitat types: lowland parkland with mixed woodland, pastoral farmland and upland rough pasture with moorland, representing areas of presumed good, medium and poor badger habitat, respectively. Contiguous main setts were identified and bait-marking was used to estimate territory size. Group size was estimated by direct enumeration. Variation in sett density, group size and territory size supported the hypothesis that badger group and territory size are influenced by habitat type. This was further supported by analyses of data from other studies in the British Isles. The implications for badger spatial ecology, badger survey techniques and the badger's role in the epidemiology of TB are discussed.

Constructing a global understanding of the social ecology of leaving out of home care

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.

Towards a better understanding of the nature and contribution of the interflow to catchment dynamics.

A detailed understanding of flow and contaminant transfer along each of the key hydrological pathways within a catchment is critical for designing and implementing cost effective Programmes of Measures under the Water
Framework Directive.
The Contaminant Movement along Pathways Project (’The Pathways Project’) is an Irish, EPA STRIVE funded, large multi-disciplinary project which is focussed on understanding and modelling flow and attenuation along each of these pathways for the purposes of developing a catchment management tool. The tool will be used by EPA and RBD catchment managers to assess and manage the impacts of diffuse contamination on stream aquatic ecology. Four main contaminants of interest — nitrogen, phosphorus, sediment and pathogens — are being
investigated in four instrumented test catchments. In addition to the usual hydrological and water chemistry/quality parameters typically captured in catchment studies, field measurements at the test catchments include ecological
sampling, sediment dynamics, soil moisture dynamics, and groundwater levels and chemistry/quality, both during and between significant rainfall events. Spatial and temporal sampling of waters directly from the pathways of
interest is also being carried out.
Sixty-five percent of Ireland is underlain by poorly productive aquifers. In these hydrogeological settings, the main pathways delivering flow to streams are overland flow, interflow and shallow bedrock flow. Little is
known about the interflow pathway and its relative importance in delivery of flow and contaminants to the streams. Interflow can occur in both the topsoil and subsoil, and may include unsaturated matrix flow, bypass or macropore
flow, saturated flow in locally perched water tables and artificial field drainage.
Results to date from the test catchment experiments show that artificial field drains play an important role in the delivery of interflow to these streams, during and between rainfall events when antecedent conditions are
favourable. Hydrochemical mixing models, using silica and SAC254 (the absorbance of UV light at a wavelength of 254 nm which is a proxy for dissolved organic matter) as tracers, show that drain flow is an important end
member contributing to the stream and that proportionally, its contribution is relatively high.
Results from the study also demonstrate that waters originating from one pathway often mix with the waters from another, and are subsequently delivered to the stream at rates, and with chemical/quality characteristics,
that are not typical of either pathway. For example, pre-event shallow groundwater not far from the catchment divide comes up to the surface as rejected recharge during rainfall events and is rapidly delivered to the stream
via overland flow and/or artificial land drainage, bringing with it higher nitrate than would often be expected from a quickflow pathway contribution. This is contrary to the assumption often made in catchment studies that the
deeper hydrological pathways have slower response times in stream hydrographs during a rainfall event, and it emphasizes that it is critical to have a strong three-dimensional conceptual model as the basis for the interpretation
of catchment data.

Quantifying contributions of domestic wastewater treatment systems to nutrient fluxes in stream headwaters

Effective implementation of the Water Framework Directive requires a reappraisal of conventional approaches to water quality monitoring. Quantifying the impact of domestic wastewater treatment systems (DWWTS) in Irish catchments is further complicated by high levels of natural heterogeneity. This paper presents a numerical model that couples attenuation to flow along different hydrological pathways contributing to river discharge; this permits estimation of the impact of DWWTS to overall nutrient fluxes under a range of geological conditions. Preliminary results suggest high levels of attenuation experienced
before DWWTS effluent reaches bedrock play a significant role in reducing its ecological impact on aquatic receptors. Conversely, low levels of attenuation in systems discharging directly to surface water may affect water quality more significantly, particularly during prolonged dry periods in areas underlain by low productivity aquifers (>60% of Ireland), where dilution capacity is limited.

Essay - The role of ecological theory in microbial ecology

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.

Red-shifts and red herrings in geographical ecology

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.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

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.