Juvenile life history diversity is associated with lifetime individual heterogeneity in a migratory fish

Abstract

Differences in the life history pathways (LHPs) of juvenile animals are often associated with differences in demographic rates in later life stages. For migratory animals, different LHPs often result in animals from the same population occupying distinct habitats subjected to different environmental drivers.Understanding how demographic rates differ among animals expressing different LHPs may reveal fitness trade-offs that drive the expression of alternative LHPs and enable better prediction of population dynamics in a changing environment. To understand how demographic outcomes and their relationships with environmental variables differ among animals with different LHPs, we analyzed a long-term (2006-2021) mark-recapture dataset for Chinook salmon (Oncorhynchus tshawytscha) from the Wenatchee River, Washington, USA. Distinct LHPs represented in this population include either remaining in the natal stream until emigrating to the ocean as a 1-year-old (natal-reach rearing) or emigrating from the natal stream and rearing in downstream habitats for several months before completing the emigration to the ocean as a 1-year-old (downstream rearing). We found that downstream-rearing fish emigrated to the ocean 19 days earlier on average and returned as adults from the ocean at higher rates. We detected a positive correlation between rate of return from the ocean by downstream-rearing fish and coastal upwelling in their spring of outmigration, whereas for natal-reach-rearing fish we detected a positive correlation with sea surface temperature during their first marine summer. Different responses to environmental variability should lead to asynchrony in adult abundance among juvenile LHPs. A higher proportion of downstream-rearing fish returned at younger ages compared with natal-reach-rearing fish, which contributed to variability in age at reproduction and greater mixing across generations. Our results demonstrate how diversity in juvenile LHPs is associated with heterogeneity in demographic rates during subsequent life stages, which can in turn affect variance in aggregate population abundance and response to environmental change.

Lunar rhythms and their carry-over effects may shape environmental sex determination in a coral reef fish

“…carry-over effects) appear to be a common feature of marine organisms with complex life cycles [61][62][63][64][65][66][67]. Several studies from other systems have documented sex-dependent carry-over effects [60,68,69], and certainly many instances of environmental sex determination [3,4] constitute a form of carry-over effect. Here, we suggest that (1) important carry-over effects may shape post-settlement survival and maturation patterns of the sixbar wrasse, and (2) these carry-over effects may be mediated by the moon, which drives a predictable dynamic of risk and reward in the pelagic rearing environment of many larval fishes and invertebrates [19,22,29].…”

Incorporating life history diversity in an integrated population model to inform viability analysis

“…Modeling of survival and adult return rates was informed by Sorel et al (2023a) and is detailed in Supplementary material B. The abundance of juvenile smolts (2-year olds) passing Bonneville Dam, Smolts h,y,s , in year y from stream s that had expressed LHP h was the product of the number of emigrants and their survival rates φ r h,y,s over three intervals, r, between emigration from natal streams and passing Bonneville Dam, Smolts h,y,s = Juv h,y,s…”

“…During the first survival interval, we fit unique survival rate intercepts for each LHP in each stream, synchronous random effects of year that were common to all LHPs and stream, and asynchronous random effects that were unique to LHPs but common across streams (Sorel et al 2023a, Supplementary material B). In the first survival interval, we included effects of winter air temperature on the survival of downstreamrearing LHPs (Sorel et al 2023a).…”

“…During the first survival interval, we fit unique survival rate intercepts for each LHP in each stream, synchronous random effects of year that were common to all LHPs and stream, and asynchronous random effects that were unique to LHPs but common across streams (Sorel et al 2023a, Supplementary material B). In the first survival interval, we included effects of winter air temperature on the survival of downstreamrearing LHPs (Sorel et al 2023a). In the second and third survival intervals, we assumed that the three downstreamrearing LHPs from each natal stream had the same survival rates, which were allowed to differ from the natal-reachrearing LHP in each stream.…”

“…The multistate model likelihood for each PIT-tagged fish released from a rotary screw trap was calculated with the forward algorithm (McClintock et al 2020; see Zucchini et al 2016), while accounting for imperfect detection. Details of the observation model for the multistate model are included in Supplementary material B and Sorel et al (2023a). We did not have data to directly inform the survival of spr.0 emigrants, because they were almost all too small to be tagged (<60 mm) upon emigration.…”