COS 166-1 - Age-dependent interactions of two related species

Thursday, August 10, 2017: 1:30 PM
D138, Oregon Convention Center
Edwige Bellier1, Øystein Langangen2, Jan Ohlberger3, Nils Christian Stenseth2 and Joel Durant2, (1)Department of Arctic and Marine Biology, UiT The Arctic University of Norway, Tromsø, Norway, (2)Department of Biosciences, Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway, (3)School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA
Background/Question/Methods

Species exist as part of complex food webs, which can make species interactions difficult to identify. Knowing how species interact is important for better appreciating potentially unintended consequences of single-species management. Considering the different life-history stages of the interacting species might facilitate our ability to identify interactions. We developed life-cycle models for the population dynamics of two marine fishes, Atlantic haddock (Melanogrammus aeglefinus) and cod (Gadus morhua). We dynamically coupled these two models to include predation of cod on early life-stages juvenile and young (immature) haddock and predation of haddock on pelagic cod larvae. Both predation from cod on early life-stages and predation from haddock on cod larvae might affect natural mortalities of both species. The models include information from scientific surveys and commercial harvest since 1980 up until today. Model parameters are estimated using a state-space framework, which accounts for observation errors and stochasticity in the population dynamics. We quantified the contribution of environmental stochasticity and density-dependent processes to the variation of age-classes abundances

Results/Conclusions

Natural mortalities of haddock shows strong interannual fluctuations and decreasing strength of density-dependence with increasing age. Cod predation significantly affected the survival of the youngest age classes of haddock. Considering age-dependent interactions is crucial for highlighting key species interactions, better understanding the consequences of single species management and generate realistic scenarios under climate change.