10.5061/DRYAD.79CNP5HTJ
Petrik, Colleen
0000-0003-3253-0455
Texas A&M University
González Taboada, Fernando
Princeton University
Stock, Charles
Geophysical Fluid Dynamics Laboratory
Sarmiento, Jorge
Princeton University
An updated life history scheme for marine fishes predicts recruitment
variability and sensitivity to exploitation
Dryad
dataset
2020
fishing
life history
maturation rate
Rockfish
Nippon Foundation
https://ror.org/05wszs827
Nereus Program
2021-12-23T00:00:00Z
2021-12-23T00:00:00Z
en
89345 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Aim: Patterns of population renewal in marine fishes are often irregular
and lead to volatile fluctuations in abundance that challenge management
and conservation efforts. Here, we examine the relationship between life
history strategies and recruitment variability in exploited marine fish
species using a macroecological approach. Location: Global ocean. Time
period: 1950-2018. Major taxa studied: Bony and cartilaginous fish.
Methods: Based on trait data for 244 marine fish species, we objectively
extend the established Equilibrium-Periodic-Opportunistic (E-P-O) life
history classification scheme to include two additional emergent life
history strategies: “Bet-hedgers” (B) and Salmonic (S) strategists. B
strategists include Rockfishes and other species inhabiting patchy benthic
habitats with life histories that blend characteristics of E and P
species; they combine very long lifespans with elevated investments in
both parental care and fecundity. S strategists are comprised of mostly
salmonids that share life history characteristics with E and O species:
elevated investments in parental care reminiscent of E strategists, but
with reduced fecundity and short lifespans characteristic of O species. We
analyzed how the E-B-P-O-S life history classification mapped onto
patterns of recruitment variability observed in population time series
data (n = 156 species). Results: Generalized linear models suggest that
life history strategy explains a modest, yet significant amount of
recruitment variability across species. Greater predictive power arose
after controlling for increased recruitment variance associated with
variable fishing pressure, with O strategists showing the strongest
sensitivity. B strategists were similarly susceptible to exploitation as P
stocks, but their longer times to maturity make them particularly
vulnerable to overfishing. Main conclusions: A broader recognition of the
distinct ecology of Salmonic and Bet-hedger groups is important when
studying life history strategies in marine fish. More generally, our
results stress the importance of considering life history strategies for
understanding patterns of recruitment variability across fish stocks.
Life history trait data were collected from FishBase (Froese &
Pauly 2000; accessed Sep 24 2019) on a stock-specific basis for 244
exploited marine fish species. FishBase was accessed using the package
rfishbase (version 3.0.4; Boettiger et al. 2015) for the software R
(version 4.0.3; R Development Core Team, 2016). All life history traits
were the mean (if numeric) or most frequent (if categorical) value
reported for each stock of each species. "tmax" is the maximum
time to maturity in years. "Fecundity" is the logarithmic mean
of minimum and maximum fecundity. "PCI" is the Parental Care
Index that weighted quantitative and categorical data on the mode of
fertilization, Balon’s (1990) reproductive guilds, the presence/absence of
any kind of parental care, and the duration of the gestation period.
Missing values of maturity and fecundity for a small fraction of stocks
(6% and 19% respectively) were imputed using closely related traits
belonging to that stock and traits from other stocks using additive
regression and bootstrapping techniques implemented with the aregImpute
function in the Hmisc package (Harrell et al., 2017) of the software R.
Separate imputations were performed on the taxonomic groups:
Elasmobranchii, Scorpaeniformes, and non-Scorpaeniform teleosts. Time
series of recruitment (R), spawning stock biomass (SSB), fishing rate (F),
and exploitation rate (ER) were retrieved from the RAM Legacy Stock
Assessment Data (RAM SAD) version 4.44 assessment data only
(http://ramlegacy.org). Data gathered prior to 1950, stocks with less than
10 years of data, and stocks with an unknown assessment method were
excluded. Exploitation rate was used to estimate the fishing rate for
stocks where it was missing using the Baranov equation. Variance in the
recruitment time series was calculated as normalized recruitment
deviations from expectations based on (1) a simple density dependent
survival model (R/SSB), (2) a normal compensation (Beverton-Holt) model,
and (3) an over compensation (Ricker) model. RAM SAD stocks were matched
to FishBase stocks using information on regional location from both
databases. If a RAM SAD stock was not represented by one FishBase stock,
then the mean of one or more FishBase stocks were used. These means are
indicated with fractional FishBaseStockCodes.