Scaling up experimental trawl impact results to fishery management scales - a modelling approach for a '"hot time"

Abstract

Numerous studies have quantified trawl impacts at small scales. However, effective management of trawl impacts requires synthesis of experimental results (biomass depletion per tow and subsequent recovery) and application at fishery scales - realistically, this is achievable only in a modelling framework. We present a method for scaling up experimental results for management applications that incorporates a benthic biomass model having exponential trawl depletion and logistic recovery. Ultra-fine trawl-track data, supported by simulations, show that realistic trawling can be represented by a negative-binomial stochastic process, with intensity governed by large-scale effort and aggregation by a tunable parameter. Two mechanisms of the process are considered: aggregations in space (hot spots) and aggregations in time (hot times), which yields a logistic differential equation for the large-scale biomass over time. The model shows that scaling from fine scale to fishery scale depends on the degree of aggregation of fishing, with increasing aggregation lowering depletion rates at fishery scales. This model is a fundamental step in enabling assessment of large-scale implications and evaluating alternative management strategies.