Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment.

Growth and production of Pacific ocean perch (Sebastes alutus) in nursery habitats of the Gulf of Alaska

Nursery areas for juvenile fishes are often important for determining recruitment in marine populations by providing habitats that can maximize growth and thereby minimize mortality. Pacific ocean perch (POP, Sebastes alutus) have an extended juvenile period where they inhabit rocky nursery habitats. We examined POP nursery areas to link growth potential to recruitment. Juvenile POP were captured from nursery areas in 2004 and 2008, and estimated growth rates ranged from −0.19 to 0.60 g day−1 based on differences in size between June and August. Predicted growth rates from a bioenergetics model ranged from 0.05 to 0.49 g day−1 and were not significantly different than observed. Substrate preferences and the distribution of their preferred habitats were utilized to predict the extent of juvenile POP nursery habitat in the Gulf of Alaska. Based on densities of fish observed on underwater video transects and the spatial extent of nursery areas, we predicted 278 and 290 million juvenile POP were produced in 2004 and 2008. Growth potential for juvenile POP was reconstructed using the bioenergetics model, spring zooplankton bloom timing and duration and bottom water temperature for 1982–2008. When a single outlying recruitment year in 1986 was removed, growth potential experienced by juvenile POP in nursery areas was significantly correlated to the recruitment time-series from the stock assessment, explaining ∼30% of the variability. This research highlights the potential to predict recruitment using habitat-based methods and provides a potential mechanism for explaining some of the POP recruitment variability observed for this population.

Validation of the detection of Pseudo-nitzschia spp. using specific RNA probes tested in a microarray format: Calibration of signal based on variability of RNA content with environmental conditions.

Harmful algal blooms (HAB) occur worldwide and cause health problems and economic damage to fisheries and tourism. Monitoring for toxic algae is therefore essential but is based primarily on light microscopy, which is time consuming and can be limited by insufficient morphological characters such that more time is needed to examine critical features with electron microscopy. Monitoring with molecular tools is done in only a few places world-wide. EU FP7 MIDTAL (Microarray Detection of Toxic Algae) used SSU and LSU rRNA genes as targets on microarrays to identify toxic species. In order to comply with current monitoring requirements to report cell numbers as the relevant threshold measurement to trigger closure of fisheries, it was necessary to calibrate our microarray to convert the hybridisation signal obtained to cell numbers. Calibration curves for two species of Pseudo-nitzschia for use with the MIDTAL microarray are presented to obtain cell numbers following hybridisation. It complements work presented by Barra et al. (2012b. Environ. Sci. Pollut. Res. doi: 10.1007/s11356-012-1330-1v) for two other Pseudo-nitzschia spp., Dittami and Edvardsen (2012a. J. Phycol. 48, 1050) for Pseudochatonella, Blanco et al. (2013. Harmful Algae 24, 80) for Heterosigma, McCoy et al. (2013. FEMS. doi: 10.1111/1574-6941.12277) for Prymnesium spp., Karlodinium veneficum, and cf. Chatonella spp. and Taylor et al. (2014. Harmful Algae, in press) for Alexandrium.