A combination of hydrodynamical and statistical modeling reveals non-stationary climate effects on fish larvae distributions

• Published in: Proceedings of the Royal Society B: Biological Sciences
• Main Authors: Hidalgo, Manuel, Gusdal, Yvonne, Dingsør, Gjert Endre, Hjermann, D.Ø., Ottersen, Geir, Stige, Leif Christian, Melsom, Arne, Stenseth, Nils Christian
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2012
• Subjects: Centro Oceanográfico de Baleares; ocean advection; Pesquerías; particle-tracking models; spatially explicit analyses; fish larvae distribution; spawning distribution; ecological climate effects; Barents Sea; Lofoten; North Atlantic; North Atlantic oscillation
• Online Access: http://hdl.handle.net/10508/8467; http://hdl.handle.net/10261/323843; https://doi.org/10.1098/rspb.2011.0750

Biological processes and physical oceanography are often integrated in numerical modelling of marine fish larvae, but rarely in statistical analyses of spatio-temporal observation data. Here, we examine the relative contribution of inter-annual variability in spawner distribution, advection by ocean currents, hydrography and climate in modifying observed distribution patterns of cod larvae in the Lofoten–Barents Sea. By integrating predictions from a particle-tracking model into a spatially explicit statistical analysis, the effects of advection and the timing and locations of spawning are accounted for. The analysis also includes other environmental factors: temperature, salinity, a convergence index and a climate threshold determined by the North Atlantic Oscillation (NAO). We found that the spatial pattern of larvae changed over the two climate periods, being more upstream in low NAO years. We also demonstrate that spawning distribution and ocean circulation are the main factors shaping this distribution, while temperature effects are different between climate periods, probably due to a different spatial overlap of the fish larvae and their prey, and the consequent effect on the spatial pattern of larval survival. Our new methodological approach combines numerical and statistical modelling to draw robust inferences from observed distributions and will be of general interest for studies of many marine fish species.