Sustainable (biological) control of sea lice in Norwegian Atlantic salmon farms: a system dynamics approach

Transcription

1 Sustainable (biological) control of sea lice in Norwegian Atlantic salmon farms: a system dynamics approach Kanar Hamza and Karl M. Rich, University of New England IIFET 7-11 July 2014 Brisbane, Australia

2 Why sea lice is a problem? Norway is a leading global producer of farmed Atlantic salmon, producing nearly 50% of global production (Hamza, Rich and Wheat (forthcoming, 2014)). It is estimated to cost the salmon industry between billion NOK each year. The Norwegian Research Council spent nearly 50 million NOK on sea lice research between Norwegian Research Council (2010)

3 A need for an integrated model (further expansion) There is a need to develop a more integrated approach to the epidemiology and economics of disease that better represents and captures existing feedback mechanisms that can influence the success of disease control interventions and their costeffectiveness (Hamza, Rich and Wheat (forthcoming, 2014)).

4 Goal We motivate a generic framework that can be used more broadly in analyzing the impacts of alternative aquatic disease control strategies. We then provide some illustrative results of applying this model in the context of sea lice (lepeophtheirus Salmonis) control strategies in the farmed salmon industry in Norway as a proof-of-concept. Introduction of biological control of sea lice to the original model. (Hamza, Rich and Wheat (forthcoming, 2014)).

5 Research questions Can sea wrasse provide a more effective control of sea lice in Norwegian salmon farms? A. How much does it cost? B. Is wrasse treatment more effective in terms of lice control and costs than chemical treatments (in-feed and bath)?

6 Overview of Model Structure (Hamza, Rich and Wheat (forthcoming, 2014)).

7 Expansion In this project, we expand the work of Hamza, Rich, and Wheat (forthcoming, 2014) to model the impact of biological control on sea lice on salmon farms. We also add value to the modeling work done on the effectiveness of sea wrasse to control sea lice by Groner, Cox, Gettinby, and Revie (2013).

8 Simulation scenarios Simulation 1: Baseline Simulation 2 Simulation 3 Simulation 1: Baseline Simulation 2 Day Treatment Day Treatment Day Treatment Day Treatment Day Treatment Sea wrasse (the whole 78 In-feed 78 In-feed 1 production cycle) 78 In-feed 78 In-feed 126 In-feed 126 In-feed 365 In-feed 126 In-feed 126 In-feed 377 Bath 320 In-feed 377 Bath 320 In-feed 397 In-feed 370 In-feed 397 In-feed 370 In-feed I 464 Bath 444 Bath 464 Bath 444 Bath Groner, Cox, Gettinby and Revie (2013) Hamza, Rich and Wheat (forthcoming, 2014); Hamza and Aunsmo (2013) biological control

9 Lice/Fish Simulation results 5. Mobile stage lice Data Simulation 1 Simulation 2 Simulation Days Simulations 1 & 2 results are from Hamza, Rich and Wheat (forthcoming, 2014)

10 Simulation results 2.5 Adult female lice 2 Lice/Fish Data Simulation 1 Simulation 2 Simulation Days Simulations 1 & 2 results are from Hamza, Rich and Wheat (forthcoming, 2014)

11 Kg Simulation results 6.0 Fish weight Data Simulation 1 Simulation 2 Simulation Days Simulations 1 & 2 results are from Hamza, Rich and Wheat (forthcoming, 2014)

12 NOK Simulation results Treatment costs Simulation 1 Simulation 2 Simulation Days Simulations 1 & 2 results are from Hamza, Rich and Wheat (forthcoming, 2014)

13 NOK/kg Simulation results Treatment costs per kg of fish Simulation 1 - total cost Simulation 1- treatment cost Simulation 1 - biological cost Simulation 2 - total cost Simulation 2 - treatment cost Simulation 2 - biological cost Simulatio 3 - total cost Simulation 3 - treatment cost Simulation 3 - biological cost 0. Simulation 1 Simulation 2 Simulation 3 Simulations 1 & 2 results are from Hamza and Aunsmo (2013)

14 Conclusions Our previous study showed the timing and type of treatment could make lice control strategies more efficient (Hamza, Rich and Wheat (forthcoming, 2014)). The current study shows that biological control of lice is even more efficient in controlling lice in terms of: 1. Costs 2. Lice level per fish 3. Significant reduction of dependency on chemical treatments (80% less use of chemicals) - reduction of environmental externality associated with chemicals

15 More insights The effectiveness of wrasse to control lice depends on: 1. Wrasse to salmon ratio (density)? 2. Wrasse feeding (eating lice) efficacy? Optimization depends on what to optimize: 1. Lowest possible lice level. 2. 0% use of chemical treatments. 3. Lowest cost. 4. Highest lice consumption rate (wrasse feeding optimization).

16 Thank you..