Irene Mantzouni:
Meta-analysis of carrying capacity and abundance-area relationships in marine fish species

Date: 26-04-2010    Supervisor: Henrik Gislason and Brian R. MacKenzie

Knowledge on the carrying capacity and the abundance-area relationships of fish is critical to evaluate the impacts of exploitation and climate on the sustainability and also the recovery potential of the populations. Of particular interest is climate change, inducing major consequences for population dynamics and life histories of marine biota as it progresses in the 21st century. In the present PhD project, a variety of meta-analytic methods was employed to statistically combine data across the north Atlantic distributions of 3 commercially and ecologically important species; cod (Gadus morhua), herring (Clupea harengus) and haddock (Melanogrammus aeglefinus), in order to identify the effects of temperature, habitat size and life-history on their productivity patterns.

The first objective was to investigate how production and survival indices of cod recruitment (i.e. the number of new fish produced by spawners in a given year which subsequently grow and survive to become vulnerable to fishing gear) have reacted to temperature fluctuations, and in particular to extremes of temperature, throughout the north Atlantic. Meta-analytical methods based on effect sizes were employed to compare recruitment productivity during exceptionally warm or cold spawning seasons, and detect large scale patterns. Temperature was found to induce geographically explicit effects on cod recruitment; impacts differed depending on whether populations are located in the upper (negative effects) or in the lower (positive effects) thermal range. The probability of successful year-classes in populations living in warm areas is on average 34% higher in cold compared with warm seasons, whereas opposite patterns exist for populations living in cold areas.

The effects of thermally extreme time periods were investigated also across the north Atlantic distribution of haddock. The major motivations were first, to provide an evaluation of potential thermal effects on haddock recruitment productivity across its distribution, since the species is relatively less investigated on this regard compared to cod. In addition, remarkable differences are recently observed between the productivities of the two species, with haddock showing signs of recovery and many cod stocks remaining at low levels, although the two gadoids exhibit similarities in terms of life-history and historic dynamics. Thus, the second main aim was to investigate whether the two species differ in the sensitivity of recruitment success to temperature and to compare biogeographic patterns between the two gadoids across their common distribution. The productivity levels of haddock were found significantly associated with temperature, but substantial differences in the patterns were identified between stocks located in the upper and lower thermal range. In the latter, strong year-classes occurred mainly during warmer seasons and vice versa. For stocks located in the warmer waters, however, no significant patterns were obtained, suggesting that increased temperature is not yet a limiting factor for haddock. Conversely, most of the sympatric cod stocks are negatively affected by extremely warm seasons.

Having identified the dependence of cod recruitment productivity on temperature variability, the next step was to develop hierarchical, Bayesian stock-recruitment (SR) models incorporating also thermal effects. SR models are of particular importance in fisheries, since stock status evaluation and recovery policies in fisheries management rely largely on reference points derived from their parameters. Thus, the approach can provide valuable insights on the environmental impacts on key population parameters, which is required for an ecosystem approach to cod management, particularly under ocean-warming scenarios. The commonly used SR models, Ricker and Beverton-Holt, were extended by applying hierarchical methods, mixed-effects models and Bayesian inference, to incorporate the influence of ecosystem factors, mainly temperature and habitat size, on model parameters representing cod maximum reproductive rate and carrying capacity. The pattern of temperature effects on cod productivity at the species level were identified and SR model parameters were estimated with increased precision. Temperature impacts vary geographically, being positive in areas where temperatures are below 5oC, and negative for higher temperatures. Using the relationship derived, it was possible to predict expected changes in population-specific reproductive rates and carrying capacities resulting from temperature increases. Further, carrying capacity covaries with available habitat size, explaining at least half its variability across stocks.

Subsequently, similar approaches were applied also to N Atlantic herring. Using hierarchical, meta-analytic methods the dependence of recruitment and carrying capacity in 14 populations throughout the north Atlantic on spawning season temperature and habitat size was investigated. Temperature impacts varied geographically: recruitment increased until temperature reached ~7°C but then declined at warmer temperatures. Carrying capacity was significantly related to available spawning habitat size, providing support for the “larval retention” hypothesis. These patterns improve our understanding of environmental impacts on key population parameters, which is required for an ecosystem approach to cod management, particularly under ocean-warming scenarios.