A. W. Leach

Spatial patterns of sterile Mediterranean fruit fly dispersal

The success of the sterile insect technique (SIT) for the control of the Mediterranean fruit fly or medfly, Ceratitis capitata (Wiedemann) (Diptera: Tephritidae), depends largely on the ability of sterile flies to spread in the target area and compete with the wild males for wild females. Our objectives in the present study were three‐fold: (1) to evaluate the dispersal ability of sterile male medflies and compare their spatial dispersion patterns with that of wild males, (2) to evaluate how different release methods affect subsequent spatial dispersal, and (3) to determine whether manipulating the pre‐release diet of sterile males affects their dispersal. To achieve these objectives, we conducted three experiments in the field where we quantified and analyzed the spatial and temporal dispersal patterns of sterile medflies and the dispersion of resident wild males. Overall, ca. 5% of the released sterile flies were recaptured 100 m from the release point, and ca. 2% were recaptured 200 m from the release point. The released flies rarely survived longer than 5–7 days. We repeatedly found that the spatial dispersion patterns of sterile males significantly correlated with those of wild males. Release methods strongly affected subsequent fly dispersal in the field as significantly more flies were recaptured following a scattered release vs. a central one. Finally, we show that enriching sterile fly pre‐release diet with protein did not affect subsequent dispersal in the field. We conclude that sterile males are able to match the dispersion patterns of wild males, an outcome that is highly important for SIT success. Large releases from central points distant from each other may leave many areas uncovered. Accordingly, scattered releases, repeated twice a week, will provide better coverage of all available aggregations sites. The spatial performance of protein‐fed males suggests that pre‐release diet amendments may be used without detriment as a sexual stimulant in SIT programs.

Modelling Moniliophthora roreri in Costa Rica

Abstract A model of the field dynamics of Moniliophthora roreri, its management and economics was developed to evaluate net returns of various management strategies to farmers in Central America. The model is primarily based on the cropping patterns and economics of cocoa production in Costa Rica. With minimal inputs the model can be adapted to simulate the crop phenology and economics in any country, where the disease causes significant economic loss. The model is a time-based deterministic spreadsheet model that simulates the production and management of one hectare of cocoa at weekly intervals over a user-selected two-year period. The model demonstrates the need for frequent stripping of infected pods to prevent sporulating pods accumulating in the field, under a broad range of economic scenarios. The model allows the user to evaluate potential extension advice in terms of user-definable “real world” variables including: frequency of harvesting and stripping of infected pods; losses of ripe unharvested pods to rodents; ability to identify infected pods; international cocoa prices; farm-gate prices and premiums; and labour costs and requirements.

Eliciting and Combining Decision Criteria Using a Limited Palette of Utility Functions and Uncertainty Distributions: Illustrated by Application to Pest Risk Analysis.

Utility functions in the form of tables or matrices have often been used to combine discretely rated decision-making criteria. Matrix elements are usually specified individually, so no one rule or principle can be easily stated for the utility function as a whole. A series of five matrices are presented that aggregate criteria two at a time using simple rules that express a varying degree of constraint of the lower rating over the higher. A further nine possible matrices were obtained by using a different rule either side of the main axis of the matrix to describe situations where the criteria have a differential influence on the outcome. Uncertainties in the criteria are represented by three alternative frequency distributions from which the assessors select the most appropriate. The output of the utility function is a distribution of rating frequencies that is dependent on the distributions of the input criteria. In pest risk analysis (PRA), seven of these utility functions were required to mimic the logic by which assessors for the European and Mediterranean Plant Protection Organization arrive at an overall rating of pest risk. The framework enables the development of PRAs that are consistent and easy to understand, criticize, compare, and change. When tested in workshops, PRA practitioners thought that the approach accorded with both the logic and the level of resolution that they used in the risk assessments.

Pesticide environmental accounting: a decision-making tool estimating external costs of pesticides

In cost-benefit analyses of pesticide use an area-based measure of both costs and benefits is needed for spatial analysis of net benefits. The pesticide environmental accounting (PEA) tool provides a monetary estimate of environmental and health impacts per hectare-application of pesticide (Leach and Mumford 2008). The model combines the Environmental Impact Quotient method (rating human health and eco-toxicological behaviour of specific pesticides) with absolute estimates of external pesticide costs in the UK, USA and Germany. The model converts external costs of a pesticide to other countries using GDP per capita and % GDP from agriculture. For many countries, resources are not available for intensive assessments of external pesticide costs. Economic and policy applications include rationalising pesticide choice, estimating impacts of pesticide reduction policies or calculating benefits from technologies that replace pesticides [sterile insect technique (SIT) or biological pesticides such as Metarhizium]. PEA is a logical integration of diverse data and approaches. The assumptions provide transparency and consistency but at the cost of specificity and precision, a reasonable trade-off for a method that provides both comparative estimates of pesticide impacts and area-based assessments of absolute impacts. The method has been applied to cost-benefit analyses of SIT in fruit flies (two species) and pesticide choice in Desert Locust (DL) campaigns in Africa. An example of external cost calculations for sugar beet herbicides in Europe is presented. There are also planned uses in public health mosquito control.

Mark-recapture estimation of mortality and migration rates for sea trout (Salmo trutta) in the northern Baltic sea

&NA; Knowledge of current fishing mortality rates is an important prerequisite for formulating management plans for the recovery of threatened stocks. We present a method for estimating migration and fishing mortality rates for anadromous fishes that combines tag return data from commercial and recreational fisheries with expert opinion in a Bayesian framework. By integrating diverse sources of information and allowing for missing data, this approach may be particularly applicable in data‐limited situations. Wild populations of anadromous sea trout (Salmo trutta) in the northern Baltic Sea have undergone severe declines, with the loss of many populations. The contribution of fisheries to this decline has not been quantified, but is thought to be significant. We apply the Bayesian mark‐recapture model to two reared sea trout stocks from the Finnish Isojoki and Lestijoki Rivers. Over the study period (1987‐2012), the total harvest rate was estimated to average 0.82 y‐1 for the Isojoki River stock and 0.74 y‐1 for the Lestijoki River stock. Recreational gillnet fishing at sea was estimated to be the most important source of fishing mortality for both stocks, particularly during the 1980s and 1990s. Our results indicate a high probability of unsustainable levels of fishing mortality for both stocks, and illustrate the importance of considering the effect of recreational fisheries on fish population dynamics.

Bayesian Networks to Compare Pest Control Interventions on Commodities Along Agricultural Production Chains.

The production of an agricultural commodity involves a sequence of processes: planting/growing, harvesting, sorting/grading, postharvest treatment, packing, and exporting. A Bayesian network has been developed to represent the level of potential infestation of an agricultural commodity by a specified pest along an agricultural production chain. It reflects the dependency of this infestation on the predicted level of pest challenge, the anticipated susceptibility of the commodity to the pest, the level of impact from pest control measures as designed, and any variation from that due to uncertainty in measure efficacy. The objective of this Bayesian network is to facilitate agreement between national governments of the exporters and importers on a set of phytosanitary measures to meet specific phytosanitary measure requirements to achieve target levels of protection against regulated pests. The model can be used to compare the performance of different combinations of measures under different scenarios of pest challenge, making use of available measure performance data. A case study is presented using a model developed for a fruit fly pest on dragon fruit in Vietnam; the model parameters and results are illustrative and do not imply a particular level of fruit fly infestation of these exports; rather, they provide the most likely, alternative, or worst-case scenarios of the impact of measures. As a means to facilitate agreement for trade, the model provides a framework to support communication between exporters and importers about any differences in perceptions of the risk reduction achieved by pest control measures deployed during the commodity production chain.

Integrating Crop Bioterrorism Hazards into Pest Risk Assessment Tools

Risks from intentional releases of organisms to agriculture, the food chain or the environment must be assessed to ensure proportionate planning, just as accidental releases from trade or natural spread must be predicted so that management can be organised. Pest risk assessment methods are well established for trade related introductions and it is efficient to build on these and adapt available risk assessment components from agricultural and environmental assessment tools. Some additional risk considerations, particularly related to the motivation, capacity and intended impact of a perpetrator should be included, and some key elements of trade related assessments, such as the volume of trade, may be irrelevant for intentional targeted releases. Risk levels from the various causes and impacts should be comparable to allow authorities to direct responses appropriately. Preventative actions, for both intentional and unintentional introductions, are particularly important. For intentional release this puts emphasis on motivation, capacity and sources. A scenario based approach to assessing intentional release risks is taken to develop a pest risk assessment tool that can cover the range of levels of potential activity. A risk assessment framework is illustrated and a range of example scenarios is described.

Decision Tool for Assessing the Likelihood of an Intentional Foodborne Illness Outbreak

Outbreaks of foodborne illnesses are frequent, but intentional cases are rare. Authorities dealing with suspected intentional foodborne illness outbreaks need a decision support tool to help distinguish accidental or natural outbreaks from intentional cases. Two broad discrimination models are available that cover biological warfare agents but these are not fully relevant to the scale and nature of intentional foodborne illness outbreaks. Two new models are proposed, one involving a scoring system, evaluated on total points, and another based on a Bayesian Network. The Bayesian Network model is more complex, but deals with uncertainty explicitly. The two proposed models are demonstrated by assessing four known outbreaks, two intentional and two accidental.