Splay fault branching from the Hikurangi subduction shear zone: Implications for slow slip and fluid flow

Pre-stack depth migration data across the Hikurangi margin, East Coast of the North Island, New Zealand, are used to derive subducting slab geometry, upper crustal structure and seismic velocities resolved to ∼14 km depth. We investigate the potential relationship between the crustal architecture, fluid migration and short-term geodetically determined slow-slip events. The subduction interface is a shallow dipping thrust at < 7 km depth near the trench and steps down to 14 km depth along an ∼18 km long ramp, beneath Porangahau Ridge. This apparent bend in the décollement is associated with splay fault branching and coincides with a zone of maximum slip (90 mm) inferred on the subduction interface during slow slip events in June and July 2011. A low-velocity zone beneath the plate interface, up-dip of the plate interface ramp, is interpreted as fluid-rich overpressured sediments capped with a low permeability condensed layer of chalk and interbedded mudstones. Fluid rich sediments have been imbricated by splay faults in a region that coincides with the step down in the décollement from the top of subducting sediments to the oceanic crust and contribute to spatial variation in frictional properties of the plate interface that may promote slow slip behavior in the region. Further, transient fluid migration along splay faults at Porangahau Ridge may signify stress changes during slow slip

Predicting the habitat expansion of the invasive roach Rutilus rutilus (Actinopterygii, Cyprinidae), in Great Britain

The roach is influential ecologically and has a preference for water temperatures >12°C. In this study, we attempted to predict its habitat expansion in response to global warming, hypothesing its increase in Great Britain. Historical data for air temperature over different time scales (annual, seasonal, monthly and daily) and for the presence of roach in Great Britain were used to create four Ecological Niche Models. Mean seasonal air temperature (EncRoach-S) was the best predictor. Using EncRoach-S, two future climate scenarios were tested: a sensitivity test (i.e. incrementally increasing temperature values by 1°C), and using air temperature data from UKCIP 11-member ensemble of climate change projections for 2031–2040, 2061–2070 and 2091–2100. Both approaches predicted an increase in habitat suitability in Great Britain with rising air temperatures but the extent of change differed for England, Wales and Scotland. In England, the rate of expansion was initially slow but rapidly increased mid-century leading to 88% coverage by the century end. In Wales, there was a greater increase by the century end and a similar trend in Scotland. This study supports the conjecture that a rise in air temperature over the next few decades will lead to an increase in potential roach habitat

Common plants as indicators of habitat suitability for rare plants; quantifying the strength of the association between threatened plants and their neighbours

Rare plants are vulnerable to environmental change but easy to over-look during survey. Methods are therefore needed that can provide early warnings of population change and identify potentially suitable vegetation that could support new or previously overlooked populations. We developed an indicator species approach based on quantifying the association between rare plants across their British ecological range and their suite of more common neighbours. We combined quadrat data, targeted on six example species selected from the Botanical Society of Britain and Ireland's Threatened Plant Project (TPP), with representative survey data from across Britain. Bayes Theorem was then used to calculate the probability that the rare species would occur given the presence of an associated species that occurred at least once with the rare species in the TPP quadrats. These values can be interpreted as indicators of habitat suitability rather than expectations of species presence. Probability values for each neighbour species are calculated separately and are therefore unaffected by biased recording of other species. The method can still be applied if only a subset of species is recorded, for example, where weaker botanists record a pre-selected subset of more easily identifiable neighbour species. Disadvantages are that the method is constrained by the availability of quadrats currently targeted on rare species and results are influenced by any recording biases associated with existing quadrat data

Technical note: A bootstrapped LOESS regression approach for comparing soil depth profiles

Understanding the consequences of different land uses for the soil system is important to make better informed decisions based on sustainability. The ability to assess change in soil properties, throughout the soil profile, is a critical step in this process. We present an approach to examine differences in soil depth profiles between land uses using bootstrapped LOESS regressions (BLRs). This non-parametric approach is data-driven, unconstrained by distributional model parameters and provides the ability to determine significant effects of land use at specific locations down a soil profile. We demonstrate an example of the BLR approach using data from a study examining the impacts of bioenergy land use change on soil organic carbon (SOC). While this straightforward non-parametric approach may be most useful in comparing SOC profiles between land uses, it can be applied to any soil property which has been measured at satisfactory resolution down the soil profile. It is hoped that further studies of land use and land management, based on new or existing data, can make use of this approach to examine differences in soil profiles

Operationalising a metric of nitrogen impacts on biodiversity for the UK response to a data request from the Coordination Centre for Effects

As a signatory party to the Convention on Long Range Transboundary Air Pollution (CLRTAP), the UK has been requested to provide biodiversity metrics for use in assessing impacts of atmospheric nitrogen (N) pollution. Models of soil and vegetation responses to N pollution can predict changes in habitat suitability for many plant and lichen species. Metrics are required to relate changes in a set of species to biodiversity targets. In a previous study, the suitability of the habitat for a set of positive indicator-species was found to be the measure, out of potential outputs from models currently applicable to the UK, which was most clearly related to the assessment methods of habitat specialists at the Statutory Nature Conservation Bodies (SNCBs). This report describes the calculation of values for a metric, based on this principle, for a set of example habitats under different N pollution scenarios. The examples are mainly from Natura-2000 sites, and are defined at EUNIS Level 3 (e.g. F4.1 Wet heath). Values for the biodiversity metric were shown to be greater on all sites in the “Background” scenario than in the scenario with greater N and S pollution, illustrating a positive response of biodiversity to reduced pollution. Results of the study were submitted in response to the ‘Call for Data 2012-14’ by the CLTRAP Co-ordination Centre for Effects (CCE), and presented at the 24th CCE Workshop in April 2014. Metrics calculated on a similar basis were also presented by the Netherlands, Switzerland and Denmark. Such metrics indicate biodiversity status more accurately than other types of metric such as Simpson index or similarity to a reference community, so it was decided to adopt habitat-suitability for positive indicator-species as a common basis for a biodiversity metric in this context. Further work is needed to determine the typical range of metric values in different habitats, and threshold values for damage and recovery. Requirements are likely to be specified in detail in the next CCE Call for Data. The current study shows that a biodiversity metric based on habitat-suitability for positive indicator-species is a useful and responsive method for summarising outputs of models of air pollution impacts on ecosystems

Feather corticosterone content in predatory birds in relation to body condition and hepatic metal concentration

This study investigated the feasibility of measuring corticosterone in feathers from cryo-archived raptor specimens, in order to provide a retrospective assessment of the activity of the stress axis in relation to contaminant burden. Feather samples were taken from sparrowhawk Accipiter nisus, kestrel Falco tinnunculus, buzzard Buteo buteo, barn owl Tyto alba, and tawny owl Strix aluco and the variation in feather CORT concentrations with respect to species, age, sex, feather position, and body condition was assessed. In sparrowhawks only, variation in feather CORT content was compared with hepatic metal concentrations. For individuals, CORT concentration (pg mm-1) in adjacent primary flight feathers (P5 and P6), and left and right wing primaries (P5), was statistically indistinguishable. The lowest concentrations of CORT were found in sparrowhawk feathers and CORT concentrations did not vary systematically with age or sex for any species. Significant relationships between feather CORT content and condition were observed in only tawny owl and kestrel. In sparrowhawks, feather CORT concentration was found to be positively related to the hepatic concentrations of five metals (Cd, Mn, Co, Cu, Mo) and the metalloid As. There was also a negative relationship between measures of condition and total hepatic metal concentration in males. The results suggest that some factors affecting CORT uptake by feathers remain to be resolved but feather CORT content from archived specimens has the potential to provide a simple effects biomarker for exposure to environmental contaminants

Spatial controls on dissolved organic carbon in upland waters inferred from a simple statistical model

Dissolved organic carbon (DOC) concentrations in upland surface waters in many northern hemisphere industrialised regions are at their highest in living memory, provoking debate over their ‘‘naturalness’’. Because of the implications for drinking water treatment and supply there is increasing interest in the potential for mitigation through local land management, and for forecasting the likely impact of environmental change. However, the dominant controls on DOC production remain unresolved, hindering the establishment of appropriate reference levels for specific locations. Here we demonstrate that spatial variation in long-term average DOC levels draining upland UK catchments is highly predictable using a simplemultiple logistic regression model comprising variables representing wetland soil cover, rainfall, altitude, catchment sensitivity to acidification and current acid deposition. A negative relationship was observed between DOC concentration and altitude that, for catchments dominated by organo-mineral soils, is plausibly explained by the combined effects of changing net primary production and temperature-dependent decomposition. However, the magnitude of the altitude effect was considerably greater for catchments with a high proportion ofwetland cover, suggesting that additional controls influence these sites such as impeded respiratory loss of carbon in wet soils and/or an increased susceptibility to water level drawdown at lower altitudes. The model suggests (1) that continuing reductions in sulphur deposition on acid sensitive organo-mineral soils, will drive further significant increases in DOC and, (2) given the differences in the magnitude of the observed altitude-DOC relationships, that DOC production from catchments with peatdominated soilsmay bemore sensitive to climate change than those dominated by mineral soils. However, given that mechanisms remain unclear, the latter warrants further investigation

Empirical realised niche models for British coastal plant species

Coastal environments host plant taxa adapted to a wide range of salinity conditions. Salinity, along with other abiotic variables, constrains the distribution of coastal plants in predictable ways, with relatively few taxa adapted to the most saline conditions. However, few attempts have been made to quantify these relationships to create niche models for coastal plants. Quantification of the effects of salinity, and other abiotic variables, on coastal plants is essential to predict the responses of coastal ecosystems to external drivers such as sea level rise. We constructed niche models for 132 coastal plant taxa in Great Britain based on eight abiotic variables. Paired measurements of vegetation composition and abiotic variables are rare in coastal habitats so four of the variables were defined using community mean values for Ellenberg indicators, i.e. scores assigned according to the typical alkalinity, fertility, moisture availability and salinity of sites where a species occurs. The remaining variables were the canopy height, annual precipitation, and maximum and minimum temperatures. Salinity and moisture indicator scores were significant terms in over 80 % of models, suggesting the distributions of most coastal species are at least partly determined by these variables. When the models were used to predict species occurrence against an independent dataset 64 % of models gave moderate to good predictions of species occurrence. This indicates that most models had successfully captured the key determinants of the niche. The models could potentially be applied to predict changes to habitats and species-dependent ecosystem services in response to rising sea levels