Testing spatial heterogeneity with stock assessment models

This paper describes a methodology that combines meta-population theory and stock assessment models to gain insights about spatial heterogeneity of the meta-population in an operational time frame. The methodology was tested with stochastic simulations for different degrees of connectivity between sub-populations and applied to two case studies, North Sea cod (\emph{Gadus morua}) and Northeast Atlantic sardine (\emph{Sardina pilchardus}). Considering that the biological components of a population can be partitioned into discrete spatial units, we extended this idea into a property of additivity of sub-population abundances. If the additivity results hold true for putative sub-populations, then the sub-populations are isolated spatial components of the meta-population and assessment results based on sub-populations will provide information to develop and monitor the implementation of finer scale/local management. The simulation study confirmed that when sub-populations are independent and not too heterogeneous with regards to productivity, the sum of stock assessment model estimates of sub-populations' SSB is similar to the SSB estimates of the meta-population. It also showed that a strong diffusion process can be detected and that the stronger the connection between SSB and recruitment, the better the diffusion process will be detected. On the other hand it showed that weak to moderate diffusion processes are not easy to identify and large differences between sub-populations productivities may be confounded with weak diffusion processes. The application to North Sea cod and Atlantic sardine exemplified how much insight can be gained. For the North Sea cod there is a large amount of information that advocates the existence of sub-populations and our results support such claim. In relation to sardine not so much information exists, nevertheless the results obtained were sufficiently robust to support the regional analysis.

GAMITO JARDIM José Ernesto;  EERO Margit;  SILVA A.;  ULRICH Clara;  PAWLOWSKI Lionel;  HOLMES Steven;  IBAIBARRIAGA Leire;  DE OLIVEIRA José;  RIVEIRO Isabel;  ALZORRIZ GAMIZ Nekane;  CITORES Leire;  SCOTT Finlay;  URIARTE Andres;  CARRERA Pablo;  DUHAMEL Erwan;  MOSQUEIRA SANCHEZ Iago; 

2018-12-18

PUBLIC LIBRARY SCIENCE

JRC106742

1932-6203 (online),   

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0190791,    https://publications.jrc.ec.europa.eu/repository/handle/JRC106742,   

10.1371/journal.pone.0190791 (online),