Life stage‐specific, stochastic environmental effects overlay density dependence in an Atlantic salmon population. Issue 1 (22nd August 2018)

• Record Type: Journal Article
• Authors: Honkanen, Hannele M.; Boylan, Patrick; Dodd, Jennifer A.; Adams, Colin E.
• Is Part Of: Ecology of freshwater fish. Volume 28:Issue 1(2019)
• Page Start: 156
• Page End: 166
• Publication Date: 2018-08-22
• Subjects: density independence -- environmental variability -- exploitation -- fisheries -- long‐term data -- population dynamics; Freshwater fishes -- Periodicals; Freshwater fishes -- Ecology -- Periodicals; Fisheries -- Periodicals; 597.092
• DOI: 10.1111/eff.12439
• Languages: English
• ISSNs: 0906-6691

Abstract

Abstract: Atlantic salmon populations appear to fluctuate stochastically through time. It is suspected that both density‐dependent and density‐independent factors cause these fluctuations but the relative importance of each, and the life stages at which they operate, is not well known. In this study, a long‐term data set on Atlantic salmon migrants returning to the Foyle catchment, Ireland, was used to determine the role of density‐dependent and life stage‐specific environmental factors regulating population size. A Ricker density‐dependent model showed that spawning adult population size significantly predicted variation in the resultant filial generation; however, a large amount of variation (ca. 68%) remained unexplained. It was shown that environmental factors were significant in explaining some of the remaining variance and that these influences were linked to specific life stages. Three life stages—spawning and incubation, fry emergence and marine survival—were shown to have significant environmental effects that resulted in changes in the returning cohort strength. It is concluded that these life stage‐specific environmental effects are likely to contribute to the stochastic variation in population size resulting from the application of traditional stock–recruitment models. The identification and quantification of these effects should allow improved model accuracy.