Developing stock-recruitment models (WP 2)

The overall aim of WP2 is to improve the understanding of processes determining variability in recruitment. Specifically, the main patterns of recruitment variability over time will be identified, and the importance of spatial structuring, variations in reproductive potential, and processes in the early life-history will be evaluated. Finally, the consequences of these processes for the provision of appropriate management advice will be assessed.  

The partners involved in WP2 have a long history of in research and modelling of stock and recruitment relationships. Therefore, within the consortium, there is considerable knowledge on the problems of recruitment processes in fishes covering a large range of seas and oceans, both locally (European waters) and over the planet.  

Within task 2.1, the project will identify the main causes of variation in recruitment patterns between stocks.  Initially, a meta-analysis of a wide variety of stocks will be used to examine the relationship between recruitment and stock-size, resilience to changes in stock size (compensatory vs depensatory dynamics) and whether recruitment variability increases when age structure of the stock is reduced. In addition, directional shifts in relationships between stock size and recruitment will be investigated to reveal changes in stock productivity. Subsequently, changes during periods where fishing pressure was exceedingly low (e.g. during periods of conflict) or environmental conditions were know to differ from the recent past will be analysed utilising time series lengthened beyond the standard stock-assessment period. These analyses will provide indications of the stability of any relationships between stock and recruitment (i.e. non-stationarity). 

Within task 2.2, the project will identify stock sub-structure. Stock sub-structure has important implications for both recruitment variability and potential stock recovery. Current knowledge is limited as to whether sub-stock differences potentially reflect local adaptations and hence could be reflected in genetic sub-stock differences, and how such genetic differences affect recruitment variability and the distribution of individuals in time and space. The project will assess relationships between genomic differences and environmental parameters among spatially explicit spawning components. Further, the relative contributions to both egg production and survivors of population sub-components under differing climatic conditions will be identified based upon hydrographic drift models and analysis of observations of early-life stages.  

With task 2.3, we will identify variability in the production of spawning products. The assumption that spawning stock biomass (SSB) is an acceptable proxy for the stock reproductive potential (SRP) is increasingly challenged. Therefore using SSB to manage fish stocks instead of a more accurate index of SRP may give a false perception of the stock’s productivity, result in the definition of inaccurate reference points and finally, in providing biased diagnostics of the state of the stock. Based on existing data, we will examine factors such as age structure, sex structure, fecundity at age, maternal effects, spatial structure, maturity ogives, growth and adult mortalities which contribute to SRP variability. We will then investigate whether estimates of SRP improve our understanding of the relationship between stock size and recruitment.  

Within task 2.4, we will identify key processes from spawning to recruitment that contribute to recruitment variability. Critical life-history stages where year class strength is determined will be identified and the role of the physical environment on survival during these key stages will be investigated based upon the analysis of observations of early-life stages using hydrographic drift models. The role of the biological environment (e.g. prey availability) will be inferred by linking the physical conditions experienced by early life-stages with their daily growth rates inferred from otolith microstructure analysis. The role of local adaptations on survival will be inferred from the application of the genomic techniques from Task 2.3. Linking this task to field studies performed as a part of an IMR internal project will provide insight into early life history processes.  

Within task 2.5, we will apply the results of tasks 2.1-2.4 to provide improved stock recruitment relationships and examine the consequences for indicators of sustainable exploitation. The recruitment variability caused by stock sub-structure, variable production of spawning products and post-fertilisation processes will be identified. The improved understanding of recruitment variability (in the form of both equations and drivers) will provide input to task 2.6. Historical variation in recruitment success we will then be reinterpreted based on SRP indices and the corresponding reference points will be compared to conventional reference points (e.g. SSB). Management strategy evaluations (MSEs) will be employed to examine the implications of stock sub-structure, variable production of spawning products, and post-fertilisation processes.  

Within task 2.6, the project will include the improved stock-recruitment relationships in the improved multispecies prediction models constructed under WP1. In order to gain a general overview of the dynamics of the resulting models in different ecosystems, a Schaeffer model will be fitted to all the multispecies models. This will provide a simple model suitable for use in the economics modelling in WP4 as well as a tool to compare and contrast the dynamics of multispecies models.

 

 

http://www.defineit.dk/Project_structure/Workpackage2
16 DECEMBER 2018