From fish stocks to fishers and consumers: eco-viability in the Australian Southern and Eastern Scalefish and Shark Fishery 

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Management procedures

The management procedure module is used to set and allocate TACs. At the end of each year, the EU TAC for the following year is calculated so that the stock is harvested under a fishing mortality Ftarget according to the procedure described in Appendix A.2. Hereafter, the term management strategy will refer to the specification of fishing mortality targets (and associated catch limitations) for the regulated stocks. The French quota Qs,t is derived from the EU TAC according to the relative stability principle: Qs,t = TACshrs × TACs,t, (2.13) with TACshrs the French share of the EU TAC of stock s. The national quota is then allocated to producer organisations (POs), and in turn to individual harvesters following an allocation key Qshrs provided as an input 2 Qi,s,t = Qshri,s × Qs,t.

Eco-viability framework

Identifying appropriate acceptability constraints is a determinant step in the operationalization of the viability approach. It consists in:
1. Identifying the elements which determine the persistence of the system, i.e which variables are constrained;
2. Defining the acceptability threshold for the identified variables;
3. And identifying tolerance levels regarding the frequency with which these thresholds should be met in stochastic systems (Thébaud et al., 2014). For this study we conditioned the viability of the fishing activity on the maintenance of its production factors. First, as any activity based on the exploitation of a natural resource, fishing can only persist if the resource, here the fish stocks, is present. In this regard, the spawning biomass of the stocks should not fall below a limit threshold Blim, under which recruitment is likely to be impaired (ICES, 2015a).

Eco-viability under uncertainty

Precautionary management requires articulating the acceptability constraints with possible uncertainties on the modelled processes. In our model, stochasticity applies to the recruitment of the dynamic species. De Lara and Doyen (2008) and De Lara et al. (2015) presented how uncertainties could be addressed in the viability framework, thanks to the concept of stochastic viability which is interpreted as maximizing the probability of respecting acceptability constraints. We estimated this probability through a Monte-Carlo simulation approach, which consists in running a number nrep of replicates for which the value of the uncertain factor(s) is drawn in a probability distribution.

Model’s dimensions and calibration

To select the fleets to model, we considered the four key demersal stocks under EU TAC management in the Bay of Biscay (northern stock of European hake, Bay of Biscay stock of common sole, Bay of Biscay stock of Norway lobster, and anglerfish in the Bay of Biscay and Celtic Sea). Modelled vessels were the French vessels contributing significantly to the landings of at least one of the four key stocks (in order to ensure that > 95% of the landings of each stock was accounted for by the model). In addition, we identified fleets depending economically on a stock as those for which more than 30% of the gross value of landings was made up of landings of this stock. Vessels that were economically dependent on one of the stocks were also included in the model, even if their contribution to landings was limited. In total, 710 vessels were identified and allocated to fleets adapted from the European Data Collection Framework typology of fishing fleets (EU, 2008), to account for regional specificities. The fleets were further divided into length categories to define segments sharing the same cost structures. Each vessel was modelled individually, but results were aggregated at the segment level by averaging economic indicators across all vessels in the segment, in order to represent regional differences in the structure of fishing activities from North to South of the Bay. Fishing activity of the vessels was described through 13 metiers referenced in Appendix – Table B.3.

Management strategies

In order for the results to be displayed in two dimensions, we restricted our analysis to the joint management of two species, chosen for their historic importance in the Bay of Biscay demersal fishery, namely European hake and common sole. We recognize that it is a simplification of current management in the Bay of Biscay since many other stocks are actually under TAC regulation in the region. However, this stylized application has been beneficial both in terms of development and presentation of the approach as outputs were easily tractable and conveyable, and trade-offs between different objectives being made transparent. In the remainder of the paper, a management strategy St will refer to a couple of target fishing mortalities Ftarg for the 2 stocks under TAC management in the model, namely hake and sole, associated with TAC recommendations. Let FtargSOL be an element of ISOLand FtargHKE an element of IHKE, then St is an element of ISOL × IHKE. For simulation purposes this 2D space was discretized in a grid of 20×20 which amounts to 400 simulated strategies. Based on preliminary analyses, the results presented here correspond to ISOL = IHKE = [0.1; 0.8].

Table of contents :

Declarations
Statement on co-authorship
Abstract
Acknowledgements
Scientific production
1 General introduction 
1.1 Addressing the modern concept of sustainability
1.1.1 Definition and normative foundations
1.1.2 Sustainability in a context of uncertainties
1.1.3 Viability theory to address the sustainability of renewable resource extraction
1.2 Sustainability in fisheries management: the Ecosystem Approach to Fisheries and science in support to its implementation
1.2.1 Ecosystem Approach to Fisheries: the incarnation of sustainability in fisheries management
1.2.2 Development of integrated models to operationalize the Ecosystem Approach to Fisheries
1.2.3 Eco-viability modelling for holistic sustainability assessments of fisheries
1.3 Managing mixed fisheries
1.3.1 Limitations of single-species approaches for the management of mixed fisheries
1.3.2 Specific management arrangements in mixed fisheries
1.3.3 Scientific advice for mixed fisheries: some current approaches and limitations
1.4 Thesis objectives
1.5 Context of the PhD
1.6 Case studies
1.6.1 Bay of Biscay French demersal fishery (BoB)
1.6.2 Australian Southern and Eastern Scalefish and Shark Fishery (SESSF)
1.7 Structure of the thesis
2 Providing integrated total catch advice for the management of mixed fisheries with an eco-viability approach 
2.1 Introduction
2.2 The Bay of Biscay mixed demersal fishery
2.3 Bio-economic simulation model
2.3.1 Operating model
2.3.2 Management procedures
2.4 Eco-viability evaluation
2.4.1 Eco-viability framework
2.4.2 Eco-viability under uncertainty
2.5 Model’s dimensions and calibration
2.6 Management strategies
2.7 Results
2.7.1 The joint production problem
2.7.2 Biological viability
2.7.3 Fleets’ viability
2.7.4 From target reference points on fishing mortality to TAC advice
2.8 Discussion
2.8.1 Towards operational eco-viable TAC advice for mixed fisheries
2.8.2 Its application to the Bay of Biscay demersal mixed fishery .
2.8.3 Limitations and perspectives
2.8.4 Articulation with current ICES mixed fisheries advice .
3 Modelling quota uptake in multi-species fisheries managed with ITQs 
3.1 Introduction
3.2 Equilibrium of multispecies ITQ markets
3.2.1 The model
3.2.2 Market equilibrium
3.3 The convergence towards ITQ market equilibrium
3.3.1 The tâtonnement algorithm
3.3.2 Implementation considerations
3.3.3 Numerical application to the Australian Southern and Eastern Scalefish and Shark Fishery
3.4 Discussion
3.4.1 Fishing incentives under perfectly competitive ITQ markets
3.4.2 Observations from multi-species ITQ markets
3.4.3 Perspectives for process-based simulation models of multi-species ITQ markets
3.5 Conclusion
4 Flexibility of joint production in mixed fisheries and implications for management 
4.1 Introduction
4.2 The Australian Southern and Eastern Scalefish and Shark Fishery (SESSF)
4.3 Methods
4.3.1 IAM bio-economic model
4.3.2 Model calibration
4.3.3 Exploring flexibility in joint productions
4.4 Results
4.4.1 Flexibility in joint productions
4.4.2 Socio-economic performance
4.5 Discussion
4.6 Conclusion
5 From fish stocks to fishers and consumers: eco-viability in the Australian Southern and Eastern Scalefish and Shark Fishery 
5.1 Introduction
5.2 The Australian Southern and Eastern Scalefish and Shark Fishery (SESSF)
5.3 Methods
5.3.1 IAM bio-economic model
5.3.2 Eco-viability framework
5.3.3 Simulation plan
5.4 Results
5.4.1 Operating domain accounting for market dynamics
5.4.2 Eco-viability analysis
5.4.3 Trade-offs within the eco-viable space
5.5 Discussion
5.5.1 Definition of sustainability thresholds
5.5.2 From sustainability to trade-offs
5.5.3 Market dynamics in multispecies fisheries: what is the addedvalue for management advice?
5.6 Conclusion
6 General discussion 
6.1 Key results of the thesis
6.2 The representation of mixed fisheries dynamics in the models used to support tactical decision-making in mixed fisheries
6.2.1 Modelling the biological dynamics of mixed fisheries
6.2.2 Modelling fishing activity
6.2.3 Modelling ITQ markets in multi-species fisheries
6.2.4 Modelling fish price dynamics
6.3 Integrating biological, economic and social considerations in the advisory process
6.3.1 Assessing eco-viability
6.3.2 Highlighting trade-offs
6.3.3 Contributions of the approach to advisory procedures in both European and Australian federal contexts
6.4 Perspectives
6.4.1 Modelling human behaviour under uncertainty
6.4.2 Tackling the curse of dimensionality
6.4.3 Better accounting of ecological dimensions of EBFM
6.4.4 Beyond eco-viability
Appendices
A Detailed description of the IAM model 
A.1 Biological module
A.2 Harvest Control Rule module
A.3 ITQ market module
A.4 Short-term behaviour module
A.5 Catch module
A.6 Fish market module
A.7 Economic module
B Calibration of the model IAM for the Bay of Biscay demersal mixed fishery 
B.1 Biological module
B.2 Fishing activity and catch module
B.3 Economic module
C Calibration of the model IAM for the Australian Southern and Eastern Scalefish and Shark Fishery 
C.1 Biological module
C.2 Fishing activity and catch module
C.3 ITQ market module
C.4 Fish price module
C.5 Economic module
D Metier and fleet definition in the Australian Southern and Eastern Scalefish and Shark Fishery 
D.1 Material and Methods
D.1.1 Data
D.1.2 Definition of metiers
D.1.3 Definition of fleets
D.2 Results
D.2.1 Metiers
D.2.2 Fleets
E Example of stochastic trajectories and associated viability probabilities
F Influence of remuneration system on crew surplus 
G Résumé long 
G.1 Introduction générale
G.1.1 Durabilité des activités humaines et théorie de la viabilité
G.1.2 Une gestion durable des pêches: l’approche écosystémique des pêches et la science en appui à sa mise en oeuvre
G.1.3 La gestion des pêcheries mixtes
G.1.4 Objectifs de la thèse
G.1.5 Cas d’étude
G.2 Chapitre 2
G.3 Chapitre 3
G.4 Chapitre 4
G.5 Chapitre 5
G.6 Discussion générale
G.6.1 La représentation des dynamiques de pêcherie mixte dans les modèles d’appui à la décision TAC
G.6.2 L’intégration des dimensions biologiques, économiques et sociales de la durabilité dans le développement d’avis TAC
G.6.3 Perspectives
G.6.4 La modélisation du comportement humain sous incertitudes
G.6.5 Le défi de la dimensionnalité
G.6.6 Une meilleure prise en compte des dimensions écologiques de l’AEP210
G.6.7 Au-delà de l’éco-viabilité
List of acronyms
Bibliography 

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