Monday, August 3, 2009 - 4:40 PM

OOS 2-10: Predicting the fate of stocked fish: Modelling individual dispersal, and mortality to optimise the management of vulnerable species

Julien Cucherousset1, Richard Stillman1, Jean-Marc Roussel2, Jean-Marc Paillisson3, J Robert Britton1, and Rodolphe E Gozlan1. (1) Bournemouth University, (2) INRA Institut National de la Recherche Agronomique, (3) Universite de Rennes 1

Background/Question/Methods

The release in the wild of captive-raised animals (stocking) is a common tool used for the conservation of vulnerable species and the enhancement of exploited stocks, but conservationists require practical guidance to optimize its cost-effectiveness. A good example comes from freshwater fisheries as many rely on regular stocking of juveniles to sustain the subsequent catches of adults. Determining the individual patterns of mortality (e.g. predation, food resource shortage) and dispersal in the stocked fishes is crucial in evaluating stocking, but remains largely unknown. This is technically challenging, as small-bodied individuals cannot be monitored with conventional tools, and virtually no data exist on their fate after release. Existing habitat models rarely consider the ecological processes underlying species distribution (e.g. optimal habitat choice), and do not predict the movement, and survival of individuals. To have confidence in model predictions, they must operate on basic principles that still apply in new environmental conditions and under different stocking scenarios. Using individual-based models (IBMs) as a tool to provide a reliable basis for prediction, and northern pike (Esox lucius) as a model species, the study aims to: i) parameterize an IBM based on optimal foraging and game theories to determine the fate of stocked juveniles; ii) test these predictions using the results from an innovative field survey using PIT telemetry (individual tagging, and monitoring) and repeated stable isotope analyses (SIA); and iii) using outputs from the IBM, predict how individual fish will respond to different environmental conditions and stocking scenarios to define an optimised design.  

Results/Conclusions

We found that the IBM could accurately predict the observed growth, mortality, and dispersal of juveniles. Specifically, we measured size-dependant dispersal and low survival (19.3% of the 192 PIT-tagged individuals). Based on PIT telemetry, we estimated that 59 individuals were predated by birds, and 68 suffered from another source of size-dependent mortality although SIA revealed this was not significantly caused by cannibalism. A selective use of the deepest areas was also observed and predicted. Using different environmental conditions and stocking scenarios, the IBM predicted the influence of the characteristics of released juveniles, release locations, stocking density, and timing on fish survival rates. The combined use of innovative field techniques with an IBM provides new insights into the management of vulnerable species and reveals the transferability of IBMs to other model species to provide realistic information for managers to optimise their stocking strategies.