IMIS | Flanders Marine Institute

Flanders Marine Institute

Platform for marine research


Publications | Institutes | Persons | Datasets | Projects | Maps
[ report an error in this record ]basket (0): add | show Printer-friendly version

Modelling the effect of ecosystem change on spawning per recruit of Baltic herring
Rahikainen, M.; Kuikka, S.; Parmanne, R. (2003). Modelling the effect of ecosystem change on spawning per recruit of Baltic herring. ICES J. Mar. Sci./J. Cons. int. Explor. Mer 60: 94-109
In: ICES Journal of Marine Science. Academic Press: London. ISSN 1054-3139, more
Peer reviewed article  

Available in  Authors 


Authors  Top 
  • Rahikainen, M.
  • Kuikka, S.
  • Parmanne, R.

    A plea for linking assessment and management to the broader ecosystem state has been made several times in the fisheries literature. The need for ecosystem considerations is obvious for Baltic herring stock which has experienced large fluctuations in growth and natural mortality rate. Biological reference points, based on stock-recruitment data, have gained importance under precautionary approach and the need for more restrictive management. An alternative method for establishing thresholds for recruitment overfishing is spawning per recruit analysis. Within this context, understanding the effects of highly variable natural mortality and growth rate on fishing mortality reference point is of interest. We used Monte Carlo simulations to investigate variation in spawning per recruit caused by varying stock attributes. Causal biological response to changing environmental conditions was created by adjusting the correlation between growth, maturity, and natural mortality. The correlation of the input variables was controlled under three models, assuming future conditions were (1) as experienced recently (empirical model), (2) random, and (3) depending upon causal linkages in the biological key processes (ecological model). The overall uncertainty was large in all models. Biological reference point (F30%SPR) was uncertain due to problem of defining maximum spawning per recruit and due to variation in input variables in SPR analysis. The concept of Fx%SPR was judged to be ambiguous. The use of causal ecological knowledge reduced uncertainty of the reference point only to a limited extent. However, relying only to the observed data appeared to be the riskiest approach.

All data in IMIS is subject to the VLIZ privacy policy Top | Authors