Identifying trade-offs in fisheries presumes some knowledge about interactions between harvested species, yet there is typically considerable uncertainly about the type and nature of food web interactions. Even relatively simple food webs can embody complicated and unknown interactions.
For example, a seemingly simple predator-prey interaction contains unknowns regarding the shape of the functional response, and also whether size-structured interactions might make prey an important competitor of or predator on the young of predators. I explored the potential biases resulting
from using models that do not account for these interactions using a series of simulations based on naive models that either assume predator-independent functional responses or do not include egg predation. Process models, in which predictions are based on a mechanistic construction of food-web
interactions, were prone to biases when they did not fully or accurately describe the nature of predator-prey interactions. However, inverse models, where parameter estimates are derived from fitting the model to time-series data, had considerably less bias. These results suggest that inverse
modeling methods are generally robust and that the inherent uncertainty in food-web responses to harvesting is not a legitimate rationale for eschewing ecologically based approaches to fisheries management.
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