Functional relationship between harp seal body condition and available prey in the Barents Sea

Abstract

The Barents Sea ecosystem has undergone substantial ecological fluctuations over the past 40 yr, including large variations in the abundance of capelin Mallotus villosus, herring Clupea harrengus, krill Thysanoessa sp. and Meganyctiphanes norvegica, polar cod Boreo gadus saida, and Atlantic cod Gadus morhua. There is evidence to suggest that harp seals Pagophilus groenlandicus have responded to these changes. The current study analysed the relationships between harp seal body condition, environmental variables and the biomass of major harp seal prey. Harp seal body condition was estimated from samples taken in the southeastern Barents Sea during spring from 1992 to 2011. Body condition of juveniles and adults varied between years, improving from 1992 until 2001 and later deteriorating, with weakest condition in 2011. We investigated covariates that might explain such interannual variation. Significant relationships were found between harp seal blubber thickness and prey abundances. High abundances of capelin, polar cod and Atlantic cod had a negative impact on condition, whereas high abundance of krill had a positive impact. Environmental covariates did not improve the models, probably because these were strongly correlated with prey abundance. We also found a correlation between pup production and blubber thickness, indicating that observed declines in pup production may be associated with decreased body condition of the seals. We further show that competitive interactions in the food web (e.g. competition between harp seals and some of their prey for shared resources, such as krill) may result in unexpected negative predator-prey relationships. This has implications for predator breeding success and population dynamics.

Size‐dependent prey availability affects diet and performance of predatory fish at sea: a case study of Atlantic salmon

“…Similar predator-prey relationships have been shown for other piscivorous predators, with changes in prey quality, abundance, or size distributions affecting their performance ( € Osterblom et al 2006, Øig ard et al 2013, Golet et al 2015. Given that energy intake affects body growth, energy storage, and reproductive success, the link between size-dependent food availability and the performance of salmon in its growth habitat may be of great importance for understanding variation in survival and spawning success of individual salmon, and therefore also for populationlevel performance.…”

Arctic marine mammal population status, sea ice habitat loss, and conservation recommendations for the 21st century

“…Climate change has had widespread ecological impacts on the Arctic (Rosenzweig et al ; Gilg et al ; Post et al ), yet its effects are relatively underreported despite abiotic changes that exceed those in temperate, tropical, and montane biomes (ACIA ). Recent studies provide quantitative evidence of negative impacts of sea ice loss on some ice‐obligate AMMs (Stirling et al ; Regehr et al ; Øigard et al 2010, ; Regehr et al ). However, species‐ and subpopulation‐specific responses to climate change are likely to vary in time and space, as evidenced by delayed or even positive responses to sea ice loss for some AMMs (Moore & Laidre ; Quakenbush et al 2011; Stirling et al 2011; Rode et al ; George et al ).…”

Population Structure and Dynamics

“…For example, an at-sea salmon index was found to be highly correlated with survival rates of resident killer whales in British Columbia (Ford et al 2005), and a host of reproductive parameters vary with body condition, which in turn varies with prey availability. This direct link between food resource availability, pregnancy rates, and recruitment rates has been demonstrated in various pinnipeds, dugongs (Dugong dugon), polar bears, and sea otters, as well as cetaceans (e.g., Krafft et al 2006b;Marsh and Kwan, 2008;Frie et al 2012;Øigård et al 2013;Rode et al 2014;Thometz et al 2014). When sufficient information is known (or can be estimated) regarding reproductive life-history traits in a population, Leslie Matrix, or similar models, can be used to predict population trends.…”