Livestock host composition rather than land use or climate explains spatial patterns in bluetongue disease in South India.

Culicoides-borne arboviruses of livestock impair animal health, livestock production and livelihoods worldwide. As these arboviruses are multi-host, multi-vector systems, predictions to improve targeting of disease control measures require frameworks that quantify the relative impacts of multiple abiotic and biotic factors on disease patterns. We develop such a framework to predict long term (1992-2009) average patterns in bluetongue (BT), caused by bluetongue virus (BTV), in sheep in southern India, where annual BT outbreaks constrain the livelihoods and production of small-holder farmers. In Bayesian spatial general linear mixed models, host factors outperformed landscape and climate factors as predictors of disease patterns, with more BT outbreaks occurring on average in districts with higher densities of susceptible sheep breeds and buffalo. Since buffalo are resistant to clinical signs of BT, this finding suggests they are a source of infection for sympatric susceptible sheep populations. Sero-monitoring is required to understand the role of buffalo in maintaining BTV transmission and whether they must be included in vaccination programs to protect sheep adequately. Landscape factors, namely the coverage of post-flooding, irrigated and rain-fed croplands, had weak positive effects on outbreaks. The intimate links between livestock host, vector composition and agricultural practices in India require further investigation at the landscape scale.

Long-term increases in soil carbon due to ecosystem fertilization by atmospheric nitrogen deposition demonstrated by regional-scale modelling and observations.

Fertilization of nitrogen (N)-limited ecosystems by anthropogenic atmospheric nitrogen deposition (Ndep) may promote CO2 removal from the atmosphere, thereby buffering human effects on global radiative forcing. We used the biogeochemical ecosystem model N14CP, which considers interactions among C (carbon), N and P (phosphorus), driven by a new reconstruction of historical Ndep, to assess the responses of soil organic carbon (SOC) stocks in British semi-natural landscapes to anthropogenic change. We calculate that increased net primary production due to Ndep has enhanced detrital inputs of C to soils, causing an average increase of 1.2 kgCm-2 (c. 10%) in soil SOC over the period 1750-2010. The simulation results are consistent with observed changes in topsoil SOC concentration in the late 20th Century, derived from sample-resample measurements at nearly 2000 field sites. More than half (57%) of the additional topsoil SOC is predicted to have a short turnover time (c. 20 years), and will therefore be sensitive to future changes in Ndep. The results are the first to validate model predictions of Ndep effects against observations of SOC at a regional field scale. They demonstrate the importance of long-term macronutrient interactions and the transitory nature of soil responses in the terrestrial C cycle.

Nitrogen deposition effects on plant species diversity; threshold loads from field data.

National-scale plant species richness data for Great Britain in 1998 were related to modelled contemporary N deposition (N(dep)) using a broken stick median regression, to estimate thresholds above which N(dep) definitely has had an effect. The thresholds (kg N ha⁻¹ a⁻¹) are 7.9 for acid grassland 14.9 for bogs, 23.6 for calcareous grassland, 7.8 for deciduous woodland and 8.8 for heath. The woodland and heath thresholds are not significantly greater than the lowest N(dep), which implies that species loss may occur over the whole range of contemporary N(dep). This also applies to acid grassland if it is assumed that N(dep) has substituted for previous N fixation. The thresholds for bog and calcareous grassland are both significantly above the lowest N(dep). The thresholds are lower than the mid-range empirical Critical Loads for acid grassland, deciduous woodland and heath, higher for bogs, and approximately equal for calcareous grassland.

Indices of stress in three-spined sticklebacks Gasterosteus aculeatus in relation to extreme weather events and exposure to wastewater effluent.

Whole-body concentrations of cortisol and glucose were measured in three-spined sticklebacks Gasterosteus aculeatus from two rivers (Rivers Ray and Ock) in southern England during a 30 month period in order to assess effects on the stress axis of (1) remediation of a wastewater treatment works (WWTW) effluent (River Ray) and (2) episodic changes in flow rate arising from periods of high rainfall (Rivers Ray and Ock). The postcapture concentrations of cortisol and glucose in fish from both rivers did not exhibit a seasonal periodicity but did show significant between-sample, between-site and between-river variation, superimposed upon a consistent downward trend for each analyte during the monitoring period. Corticosteroid and glucose concentrations following capture were inversely linked with a progressive increase in condition of the fish during this period. Site-dependent trends possibly related to exposure to the WWTW effluent were detected for both analytes in fish from the River Ray. For fish in the River Ray, a significant proportion of variation in both corticosteroid and glucose concentrations, additional to the downward trend with time, was accounted for by temporal proximity of the sample to exceptional flow events arising from episodes of high rainfall and high turbidity. This relationship was not statistically significant for fish from the River Ock. These data suggest that the responsiveness of the stress axis in free-living G. aculeatus may be altered by exposure to WWTW effluent and by exposure to physical changes in the aquatic environment such as those arising from extreme weather events. The magnitude of these effects may be increased by exposure to both stressors concurrently.

Inference for clustered inhomogeneous spatial point processes.

SUMMARY: We propose a method to test for significant differences in the levels of clustering between two spatial point processes (cases and controls) while taking into account differences in their first-order intensities. The key advance on earlier methods is that the controls are not assumed to be a Poisson process. Inference and diagnostics are based around the inhomogeneous K-function with confidence envelopes obtained from either resampling events in a nonparametric bootstrap approach, or simulating new events as in a parametric bootstrap. Methods developed are demonstrated using the locations of adult and juvenile trees in a tropical forest. A simulation study briefly examines the accuracy and power of the inferential procedures.

Line transect methods for plant surveys.

Interest in surveys for monitoring plant abundance is increasing, due in part to the need to quantify the rate of loss of biodiversity. Line transect sampling offers an efficient way to monitor many species. However, the method does not work well in some circumstances, for example on small survey plots, when the plant species has a strongly aggregated distribution, or when plants that are on the line are not easily detected. We develop a crossed design, together with methods that exploit the additional information from such a design, to address these problems. The methods are illustrated using data on a colony of cowslips.