Results of a 15-year systematic survey of commensal rodents in English dwellings.

Population trends for commensal rodents are the subject of interest and speculation but accurate data are rarely available. Here we report data from a 15-year systematic survey of rats and mice in English dwellings and present national-level estimates of prevalence for 1996-2010. We found evidence for peaks in prevalence of mice inside and rats around dwellings in 2002 and 2008. Models containing twelve variables relating to the dwelling and local area explained some but not all of the variation in prevalence. Older dwellings, those in rural areas, those with litter, drainage faults and pets or other animals outdoors tended to have higher levels of rodent prevalence. Regional differences were found but there were no seasonal trends apart from lower prevalence of mice during summer. Rodent prevalence was generally higher in rented (compared to owner-occupied) dwellings, although apparently not due to reduced tendency to carry out rodent control. The percentage of households having taken some form of action against active rodent problems varied according to prevalence at the national level, and therefore appropriate data on number of rodent control treatments carried out each year could likely act as a useful index of household rodent prevalence.

Evidence for pollinator cost and farming benefits of neonicotinoid seed coatings on oilseed rape.

Chronic exposure to neonicotinoid insecticides has been linked to reduced survival of pollinating insects at both the individual and colony level, but so far only experimentally. Analyses of large-scale datasets to investigate the real-world links between the use of neonicotinoids and pollinator mortality are lacking. Moreover, the impacts of neonicotinoid seed coatings in reducing subsequent applications of foliar insecticide sprays and increasing crop yield are not known, despite the supposed benefits of this practice driving widespread use. Here, we combine large-scale pesticide usage and yield observations from oilseed rape with those detailing honey bee colony losses over an 11 year period, and reveal a correlation between honey bee colony losses and national-scale imidacloprid (a neonicotinoid) usage patterns across England and Wales. We also provide the first evidence that farmers who use neonicotinoid seed coatings reduce the number of subsequent applications of foliar insecticide sprays and may derive an economic return. Our results inform the societal discussion on the pollinator costs and farming benefits of prophylactic neonicotinoid usage on a mass flowering crop.

An improved regulatory sampling method for mapping and representing plant disease from a limited number of samples.

A key challenge for plant pathologists is to develop efficient methods to describe spatial patterns of disease spread accurately from a limited number of samples. Knowledge of disease spread is essential for informing and justifying plant disease management measures. A mechanistic modelling approach is adopted for disease mapping which is based on disease dispersal gradients and consideration of host pattern. The method is extended to provide measures of uncertainty for the estimates of disease at each host location. In addition, improvements have been made to increase computational efficiency by better initialising the disease status of unsampled hosts and speeding up the optimisation process of the model parameters. These improvements facilitate the practical use of the method by providing information on: (a) mechanisms of pathogen dispersal, (b) distance and pattern of disease spread, and (c) prediction of infection probabilities for unsampled hosts. Two data sets of disease observations, Huanglongbing (HLB) of citrus and strawberry powdery mildew, were used to evaluate the performance of the new method for disease mapping. The result showed that our method gave better estimates of precision for unsampled hosts, compared to both the original method and spatial interpolation. This enables decision makers to understand the spatial aspects of disease processes, and thus formulate regulatory actions accordingly to enhance disease control.

Indicator organisms for assessing sanitization during composting of plant wastes.

The potential for using plant pathogens and seeds as indicator organisms for assessing sanitization of plant wastes during composting was tested in bench-scale flask and large-scale systems. Plasmodiophora brassicae was unsuitable due to high temperature tolerance in dry to moist composts, and detection of viable inoculum post-composting using bioassay plants not corresponding with that using TaqMan® PCR, possibly due to preservation of nucleic acids at elevated temperatures. Several other plant pathogens (Sclerotinia sclerotiorum, Microdochium nivale, Phytophthora cinnamomi and Phytophthora nicotianae) were unsuitable due their low temperature tolerance. Fusarium oxysporum f.sp. cepae and f.sp. radicis-lycopersici chlamydospores and tomato seeds were suitable indicators due to their moderate temperature tolerance and ease of viability testing post-composting. Abutilon seeds were more tolerant than tomato seeds of compost temperatures ≥52°C but more prone to degradation at lower temperatures and therefore less suitable as indicators. Relationships between compost temperature during exposures of 2-10 days and subsequent viability of the above chlamydospores or seeds enabled the sanitizing effect of composting processes to be predicted within 2-6 days. Plant waste type (woody or vegetable) had a small but significant effect on the relationship for tomato seeds but not for F. oxysporum chlamydospores.

Modeling of Relationships Between Weather and Septoria tritici Epidemics on Winter Wheat: A Critical Approach.

ABSTRACT Two models for predicting Septoria tritici on winter wheat (cv. Riband) were developed using a program based on an iterative search of correlations between disease severity and weather. Data from four consecutive cropping seasons (1993/94 until 1996/97) at nine sites throughout England were used. A qualitative model predicted the presence or absence of Septoria tritici (at a 5% severity threshold within the top three leaf layers) using winter temperature (January/February) and wind speed to about the first node detectable growth stage. For sites above the disease threshold, a quantitative model predicted severity of Septoria tritici using rainfall during stem elongation. A test statistic was derived to test the validity of the iterative search used to obtain both models. This statistic was used in combination with bootstrap analyses in which the search program was rerun using weather data from previous years, therefore uncorrelated with the disease data, to investigate how likely correlations such as the ones found in our models would have been in the absence of genuine relationships.