Research Technical Report
Towards Ecosystem-based Fishery Management in the California Current System – Predators and the Preyscape: A Workshop
Ainley, D., P. Adams, and J. Jahncke (March 2014)
Unpublished report to the National Fish and Wildlife Foundation. Point Blue Conservation Science, Petaluma, California. Point Blue contribution number 1979.
- Most California Current System (CCS) predators are generalists, very few are krill specialists (e.g. blue whales). Owing to the variability inherent in the CCS, predators must engage in prey switching at both temporal (decadal to seasonal) and spatial (region to local) scales;
- There are foraging hotspots in the CCS, and while their general location may be similar from year to year (e.g., Northern Channel Islands to Point Conception, Gulf of the Farallones-Monterey Bay, Cape Blanco to Heceta Bank, Strait of Juan de Fuca), they are subject to temporal (decadal to seasonal) and spatial (meso- to micro-scale) variability in their relative importance, which contributes to the prey switching behavior of the predators;
- While the classic "forage species" are prevalent in predator diets of the CCS (e.g. anchovy, herring, sardine), juveniles of important federal FMP species (e.g., salmon, rockfish, hake) as well as several invertebrates (krill, market squid, octopus) are equally prevalent;
- Where human and "wild" predators coincide, based on experimental evidence, the human fishers are far more efficient in their prey harvesting activities, putting "wild" predators at a disadvantage;
- Current modeling to assess fish stocks generally takes a single-species approach, which fails to incorporate the importance of the temporal and spatial availability of key prey species; however, incorporating these prey species into stock assessment modeling (or other types) presents its own suite of challenges and cannot be based on reserving some portion of the exploited biomass alone, but rather must also address availability to predators (biomass does not equal availability);
- Undertaking further, complex modeling will require the expensive collection of additional data not currently available.
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