Measuring and comparing constraints to improved biosecurity amongst GB farmers, veterinarians and the auxiliary industries

Constraints to the introduction of enhanced biosecurity systems are rarely considered in sufficient detail when population medicine specialists initiate new control schemes. The main objective of our research was to investigate and compare the different attitudes constraining improvement in biosecurity for cattle and sheep farmers, practising veterinary surgeons and the auxiliary industries in Great Britain (GB). This study was carried out utilizing farmer focus groups, a questionnaire survey of veterinary practitioners and a telephone survey of auxiliary industry representatives. It appears that farmers and veterinarians have their own relatively clear definitions for biosecurity in relation to some major diseases threatening GB agriculture. Overall, farmers believe that other stakeholders, such as the government, should make a greater contribution towards biosecurity within GB. Conversely, veterinary practitioners saw their clients' ability or willingness to invest in biosecurity measures as a major constraint. Veterinary practitioners also felt that there was need for additional proof of efficacy and/or the potential economic benefits of proposed farm biosecurity practices better demonstrated. Auxiliary industries, in general, were not certain of their role in biosecurity although study participants highlighted zoonoses as part of the issue and offered that most of the constraints operated at farm level. (C) 2008 Elsevier B.V. All rights reserved.

Measuring and comparing constraints to improved biosecurity amongst GB farmers, veterinarians and the auxiliary industries

Constraints to the introduction of enhanced biosecurity systems are rarely considered in sufficient detail when population medicine specialists initiate new control schemes. The main objective of our research was to investigate and compare the different attitudes constraining improvement in biosecurity for cattle and sheep farmers, practising veterinary surgeons and the auxiliary industries in Great Britain (GB). This study was carried out utilizing farmer focus groups, a questionnaire survey of veterinary practitioners and a telephone survey of auxiliary industry representatives. It appears that farmers and veterinarians have their own relatively clear definitions for biosecurity in relation to some major diseases threatening GB agriculture. Overall, farmers believe that other stakeholders, such as the government, should make a greater contribution towards biosecurity within GB. Conversely, veterinary practitioners saw their clients' ability or willingness to invest in biosecurity measures as a major constraint. Veterinary practitioners also felt that there was need for additional proof of efficacy and/or the potential economic benefits of proposed farm biosecurity practices better demonstrated. Auxiliary industries, in general, were not certain of their role in biosecurity although study participants highlighted zoonoses as part of the issue and offered that most of the constraints operated at farm level. (C) 2008 Elsevier B.V. All rights reserved.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.