10.5061/DRYAD.4B8GTHT8J
Mobley, Kenyon
0000-0003-2843-6407
University of Helsinki
Granroth-Wilding, Hanna
0000-0002-4052-3821
University of Helsinki
Ellmen, Mikko
University of Turku
Orell, Panu
Natural Resources Institute Finland
Erkinaro, Jaakko
0000-0002-7843-0364
Natural Resources Institute Finland
Primmer, Craig
University of Helsinki
Time spent in distinct life-history stages has sex-specific effects on
reproductive fitness in wild Atlantic salmon
Dryad
dataset
2020
parentage analysis
Salmo salar
seaage at maturity
Atlantlantic salmon
reproductive fitness
genotype
maturation
Holocene
Reproductive success
Fitness trade-off
life-history
Reproductive success
European Research Council
https://ror.org/0472cxd90
742312
Academy of Finland
https://ror.org/05k73zm37
307593
Academy of Finland
https://ror.org/05k73zm37
302873
Academy of Finland
https://ror.org/05k73zm37
284941
2020-02-26T00:00:00Z
2020-02-26T00:00:00Z
en
https://doi.org/10.5061/dryad.3ss2t53
https://doi.org/10.1126/sciadv.aav1112
https://doi.org/10.1111/mec.15390
251191 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
In species with complex life cycles, life history theory predicts that
fitness is affected by conditions encountered in previous life history
stages. Here, we use a four-year pedigree to investigate if time spent in
two distinct life history stages has sex-specific reproductive fitness
consequences in anadromous Atlantic salmon (Salmo salar). We determined
the amount of years spent in fresh water as juveniles (freshwater age, FW,
measured in years), and years spent in the marine environment as adults
(sea age, SW, measured in sea winters) on 264 sexually mature adults
collected on a river spawning ground. We then estimated reproductive
fitness as the number of offspring (reproductive success) and the number
of mates (mating success) using genetic parentage analysis (>5000
offspring). Sea age is significantly and positively correlated with
reproductive and mating success of both sexes whereby older and larger
individuals gained the highest reproductive fitness benefits (females:
62.2% increase in offspring/SW and 34.8% increase in mate number/SW;
males: 201.9% offspring/SW and 60.3% mates/SW). Younger freshwater age was
significantly related to older sea age and thus increased reproductive
fitness, but only among females (females: -33.9% offspring/FW and -32.4%
mates/FW). This result implies that females can obtain higher reproductive
fitness by transitioning to the marine environment earlier. In contrast,
male mating and reproductive success was unaffected by freshwater age and
more males returned at a younger age than females despite the reproductive
fitness advantage of later sea age maturation. Our results show that the
timing of transitions between juvenile and adult phases has a sex-specific
consequence on female reproductive fitness, demonstrating a life-history
trade-off between maturation and reproduction in wild Atlantic salmon.
Anadromous adults were sampled in September-October 2011-2014 at the lower
Utsjoki spawning grounds at the mouth of the Utsjoki tributary of the Teno
River in northern Finland (69°54'28.37''N,
27°2'47.52''E, see Mobley et al. (2019) for further details
on sampling location). Adults were weighed, and total length was recorded.
Condition was calculated as the residual from a linear model of weight
predicted by length for each sex and spawning cohort (Mobley et al., 2019;
Patterson, 1992). Scales were collected for age analysis and a small piece
of anal fin was collected for genetic analysis prior to release near the
site of capture. Juveniles were sampled by electrofishing shallow areas in
the region of the spawning grounds 10 to 11 months later, which is two to
three months after they are expected to have emerged from the nests in the
stream bed gravel (Mobley et al., 2019). Genetic samples were collected
from all juveniles by collecting a small piece of adipose and/or anal
fins, after which they were immediately returned to the river (Mobley et
al., 2019). Four parent-offspring cohorts were sampled in this manner
between 2011 and 2015. Age determination Freshwater age, defined as the
number of years spent in freshwater prior to migrating to sea, and sea
age, defined as the number of years an individual overwintered at sea
before returning to spawn, was determined for adults captured on the
spawning ground using scale growth readings as outlined in Aykanat et al.
(2015). Freshwater age could not be determined on 25 individuals (3
females, 22 males) using scale data. Sea age could not be determined for
16 adults > 1SW (1 female, 15 males) using scale data and was
therefore extrapolated based on calculated distributions of weight of
known sea age individuals (see Mobley et al., 2019, Supplementary
Materials, Table S4). However, freshwater age was not extrapolated based
on weight due to the poor relationship between weight and freshwater age
(see Results). Therefore, these individuals were excluded from statistical
analyses. Repeat spawners that were spawning for a second time were also
determined using scale data. Thirteen individuals (6 females, 7 males)
were identified as repeat spawners by scale aging analysis. The mean sea
age of repeat spawning females was 3.2 ± 0.4 SE (range 2-4 SW) and all
repeat spawning males had spent one year at sea before the first spawning
migration and another year at sea before returning to spawning for the
second time (i.e., all male repeat spawners were 2 SW). Parentage analysis
Molecular parentage analysis was conducted according to Mobley et al.
(2019). Briefly, all adults and juveniles were genotyped using 13
microsatellite loci previously used for parentage analyses in this species
(Aykanat et al., 2014). Pedigrees were constructed for each
parent-offspring cohort separately using the package MasterBayes V2.55
(Hadfield, Richardson & Burke, 2006) in the R programming
environment (R Core Team, 2018). Genotyping error rate was calculated as
per Mobley et al. (2019). The distribution of unsampled population sizes
(mothers and fathers separate) were given a prior mean of twice the
sampled population size, following Aykanat et al. (2014), with a variance
calculated as 1.5 – 0.25 * sampled population size, which encompassed
likely parameter space. The pedigree was run for 30,000 iterations after a
burn-in of 5,000. We then extracted the mode of the posterior distribution
of pedigrees, and removed assignments with a likelihood of less than 90%.
Offspring assigned to a known parent were either confidently (>90%
likelihood) assigned to two sampled adults, or one parent confidently
assigned to a sampled adult and the other confidently assigned to an
unsampled adult. In this manner, an offspring that contributed to our
reproductive fitness measures were either assigned to both a sampled sire
and a sampled dam, or to either a sampled sire or a dam and an unsampled
adult (Mobley et al., 2019). Reproductive fitness estimates Reproductive
success was quantified as the number of offspring assigned to an adult,
following parentage assignment of all offspring. Mating success was
estimated as the number of unique mates per individual identified within
our sample by parentage analysis (Mobley et al., 2019). Citations Aykanat
T., Johnston S. E., Cotter D., Cross T. F., Poole R., Prodőhl P. A.,
...Primmer C. R. (2014) Molecular pedigree reconstruction and estimation
of evolutionary parameters in a wild Atlantic salmon river system with
incomplete sampling: a power analysis. BMC Evolutionary Biology 14, 68.
doi: 10.1186/1471-2148-14-68 Aykanat T., Johnston S. E., Orell P., Niemelä
E., Erkinaro J., Primmer C. R. (2015) Low but significant genetic
differentiation underlies biologically meaningful phenotypic divergence in
a large Atlantic salmon population. Molecular Ecology 24, 5158-5174. doi:
10.1111/mec.13383 Hadfield J. D., Richardson D. S., Burke T. (2006)
Towards unbiased parentage assignment: combining genetic, behavioural and
spatial data in a Bayesian framework. Molecular Ecology 15, 3715-3730.
doi: 10.1111/j.1365-294X.2006.03050.x Mobley K. B., Granroth-Wilding H.,
Ellmen M., Vaha J.-P., Aykanat T., Johnston S. E., ...Primmer C. R. (2019)
Home ground advantage: local Atlantic salmon have higher reproductive
fitness than dispersers in the wild. Science Advances 5, eaav1112. doi:
10.1126/sciadv.aav1112 Patterson K. R. (1992) An improved method for
studying the condition of fish, with an example using Pacific sardine
Savdinops sagax (Jenyns). Journal of Fish Biology 40, 821-831. doi: 0022-1
112/92/060821 R Core Team (2018) R: A language and environment for
statistical computing. R Foundation for Statistical Computing, Vienna,
Austria.
UtsAdults.csv This file contains all phenotypic and reproductive fitness
data for each individual adult salmon sampled at the lower Utsjoki study
site over four cohort years (2011-2015). ID corresponds to ID in DRYAD
submission: 10.5061/dryad.3ss2t53. UtsParentageAssignments.csv This file
contains the output of the pedigree fit, i.e. parentage assignments, for
all sampled offspring sampled at the lower Utsjoki study site over four
cohort years (2011-2015). ID corresponds to ID in DRYAD submission:
10.5061/dryad.3ss2t53. Utsreadme.txt Describes the data and abbeviations
in the above datasets.