Fisheries scientists habitually consider uncertainty in parameter values, but often neglect uncertainty about model structure, an issue of increasing importance as ecosystem models are devised to support the move to an ecosystem approach to fisheries (EAF). This paper sets out pragmatic approaches with which to account for uncertainties in model structure and we review current ways of dealing with this issue in fisheries and other disciplines. All involve considering a set of alternative models representing different structural assumptions, but differ in how those models are used. The models can be asked to identify bounds on possible outcomes, find management actions that will perform adequately irrespective of the true model, find management actions that best achieve one or more objectives given weights assigned to each model, or formalize hypotheses for evaluation through experimentation. Data availability is likely to limit the use of approaches that involve weighting alternative models in an ecosystem setting, and the cost of experimentation is likely to limit its use. Practical implementation of an EAF should therefore be based on management approaches that acknowledge the uncertainty inherent in model predictions and are robust to it. Model results must be presented in ways that represent the risks and trade‐offs associated with alternative actions and the degree of uncertainty in predictions. This presentation should not disguise the fact that, in many cases, estimates of model uncertainty may be based on subjective criteria. The problem of model uncertainty is far from unique to fisheries, and a dialogue among fisheries modellers and modellers from other scientific communities will therefore be helpful. 相似文献
We conducted a study on 81 initially bulk-milk ELISA negative dairy herds taken from a random sample of Dutch dairy herds to evaluate variation in bulk-milk S/P ratios and to study reasons for bulk-milk conversion. These herds were repeatedly (3-month intervals) tested between April 2004 and August 2005 and serostatus of all animals had previously been established as negative (N), low-positive (LP) or high-positive (HP). Of these herds, herd- and test-related factors associated with variation in sample over positive (S/P) ratios were analysed using a multivariable linear-mixed model with ‘herd’ as random effect. In addition, changes of animal serostatus in converting herds were described. S/P ratios were calculated as the optical density of the bulk-milk sample minus the optical density of the negative serum control divided by the difference in optical density between the positive and negative serum control.
Sixteen bulk-milk conversions in 12 dairy herds were seen with few indications of serological conversion in lactating cattle except for one herd in which recrudescence of infection appeared likely in nine cows. The effect of HP serostatus on bulk-milk S/P ratio was 2–3 times stronger compared with LP serostatus. In addition, bulk-milk S/P-ratio increased when the proportion of HP animals between 1 and 60 days in milk increased and decreased when the average milk-production level of the herd increased. Besides these herd-related factors, the use of different ELISA-testkits between test rounds had a significant effect on the S/P-ratio in bulk-milk samples. 相似文献