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Volume 5 •2017 10.1093/conphys/cox010
Research article
Effects of ambient oxygen and size-selective
mortality on growth and maturation in guppies
Beatriz Diaz Pauli
1,†,‡
, Jeppe Kolding
1,2
, Geetha Jeyakanth
1
and Mikko Heino
1,3,4,
*
1
Department of Biology, University of Bergen and Hjort Centre for Marine Ecosystem Dynamics, Bergen, Norway
2
IUCN Commission of Ecosystem Management, Fisheries Expert Group (IUCN-CEM-FEG), Gland, Switzerland
3
Institute of Marine Research, Bergen, Norway
4
Evolution and Ecology Program, International Institute for Applied Systems Analysis, Laxenburg, Austria
*Corresponding author: Department of Biology, University of Bergen and Hjort Centre for Marine Ecosystem Dynamics, Bergen, Norway.
Tel: +47 55 588137. Email: Mikko.Heino@uib.no; beatriz.diaz-pauli@uib.no
Growth, onset of maturity and investment in reproduction are key traits for understanding variation in life-history strat-
egies. Many environmental factors affect variation in these traits, but for fish, hypoxia and size-dependent mortality have
become increasingly important because of human activities, such as increased nutrient enrichment (eutrophication), cli-
mate warming and selective fishing. Here, we study experimentally the effect of oxygen availability on maturation and
growth in guppies (Poecilia reticulata) from two different selected lines, one subjected to positive and the other negative
size-dependent fishing. This is the first study to assess the effects of both reduced ambient oxygen and size-dependent
mortality in fish. We show that reduced ambient oxygen led to stunting, early maturation and high reproductive invest-
ment. Likewise, lineages that had been exposed to high mortality of larger-sized individuals displayed earlier maturation
at smaller size, greater investment in reproduction and faster growth. These life-history changes were particularly evident
for males. The widely reported trends towards earlier maturation in wild fish populations are often interpreted as resulting
from size-selective fishing. Our results highlight that reduced ambient oxygen, which has received little experimental inves-
tigation to date, can lead to similar phenotypic changes. Thus, changes in ambient oxygen levels can be a confounding fac-
tor that occurs in parallel with fishing, complicating the causal interpretation of changes in life-history traits. We believe
that better disentangling of the effects of these two extrinsic factors, which increasingly affect many freshwater and marine
ecosystems, is important for making more informed management decisions.
Key words: Eutrophication, fishing selection, hypoxia, life history, Poecilia reticulata, water management
Editor: Steven Cooke
Received 24 October 2016; Revised 12 January 2017; Editorial Decision 20 January 2017; accepted 6 February 2017
Cite as: Diaz Pauli B, Kolding J, Jeyakanth G, Heino M (2017) Effects of ambient oxygen and size-selective mortality on growth and maturation
in guppies. Conserv Physiol 5(1): cox010; doi:10.1093/conphys/cox010.
†
Department of Biosciences, Centre for Ecological and Evolutionary Syntheses (CEES), University of Oslo, Oslo, Norway
‡
Inst. d’Ecologie et des Sciences de l’Environnement –Paris (iEES-Paris), Sorbonne Universités/UPMC Univ Paris 06/CNRS/INRA/IRD/Paris Diderot
Univ Paris 07/UPEC/, Paris, France
..............................................................................................................................................................
1
© The Author 2017. Published by Oxford University Press and the Society for Experimental Biology.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/
by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Introduction
Maturation determines the beginning of the reproductive
part of an individual’s life cycle and is costly in terms of
survival and energy. The age and size at which an individ-
ual matures are therefore key life-history traits. Growth
determines the relationship between age and size, with the
latter also being a key determinant of survival and fecund-
ity. Thus, studying the effects of different extrinsic factors
on growth and maturity is important for understanding the
variation in life-history strategies (Roff, 1992;Stearns,
1992,2000).
Many different environmental factors, such as food avail-
ability, temperature, oxygen and presence of predators,
affect the acquisition and allocation of resources to growth,
maturation and reproduction (Berner and Blanckenhorn,
2007;Enberg et al., 2012). Two factors affecting life-history
traits are of particular interest in fishes, namely oxygen and
size-dependent mortality. Oxygen is one of the most critical
physical constraints for aquatic animals (Ross, 2000;Pauly,
2010): water is a dense, viscous medium that contains little
oxygen in comparison to air; only small quantities of oxy-
gen can be dissolved, and respiratory areas do not grow as
fast as body weight (Pauly, 1981,2010). Oxygen demand is
proportional to the rate of metabolism and increases with,
e.g. body size and stress. Low-oxygen conditions occur nat-
urally in many closed water bodies and in the oxygen min-
imum zones of the World Ocean, but oxygen depletion is
also becoming increasingly prevalent in freshwater and mar-
ine ecosystems because of increasing eutrophication and
temperature (Diaz and Rosenberg, 2008;Doney et al.,
2012;Jenny et al., 2016). Importantly, temperature plays a
dual role: increasing temperature reduces the solubility of
oxygen, while in ectotherms, it also increases the metabolic
demand for oxygen (Pörtner and Knust, 2007;Holt and
Jørgensen, 2015).
Similar to oxygen depletion, size-dependent mortality
occurs naturally but can be influenced by human activities.
Size-dependent natural mortality is driven by the presence of
predators that commonly prey more heavily on smaller size
classes, i.e. it is negatively size selective (Lorenzen, 1996;
Sogard, 1997;Gislason et al.,2010). In contrast, fishing most
often targets large fish (i.e. it is positively size selective).
Fishing pressure has increased since the middle of the past
century, mainly targeting large individuals and higher trophic
levels (Pauly et al., 2002;Kolding et al.,2016). Importantly,
reduced oxygen levels and increased size-selective fishing co-
occur in many aquatic ecosystems, for instance in Lake
Victoria (Kolding et al., 2008b), on the Swedish west coast
(Kattegat and Skagerrak; Cardinale and Svedäng, 2004)and
in the northern Benguela system (Utne-Palm et al., 2010).
Reduced oxygen and overexploitation cause reduced abun-
dance and recruitment in demersal fish (Diaz and Rosenberg,
2008). Low oxygen saturation in water is a proximate factor
driving reduced asymptotic maximal size, because the limited
oxygen available is allocated to maintenance rather than som-
atic growth (Pauly, 1981,2010;van Dam and Pauly, 1995;
Chabot and Claireaux, 2008). Little is known about the effect
of hypoxia on reproduction, but extreme levels of hypoxia
canimpairit(
Wu et al.,2003;Landry et al.,2007;Chabot
and Claireaux, 2008). However, it is predicted that at moder-
ate levels of hypoxia, stunting is caused by earlier maturation
and increased reproductive investment at early ages (Kolding,
1993;Kolding et al., 2008a). However, similar changes in
maturation and post-maturation growth are expected from
evolutionary change caused by fisheries-induced selection
(Heino et al.,2015).
Despite the fact that a low oxygen level and fishing may
co-occur and drive similar changes in life-history traits, little
effort has been made to study their joint effect (Kolding
et al., 2008b). Studying the combined effect of several factors
is crucial to gain a better understanding and inform manage-
ment and conservation plans of natural resources and fish
populations in particular (Jackson et al., 2016). For instance,
Kolding et al. (2008b) concluded that low oxygen, rather
than overfishing, was the most important threat for Nile
perch (Lates niloticus) in lake Victoria. Likewise, the reduc-
tion in individual size and maturation observed in Nile perch
(Mkumbo and Marshall, 2015) and Dagaa (Rastrineobola
argentea;Sharpe et al., 2012) in Lake Victoria could be dri-
ven by hypoxia. Crucially, mitigating actions depend on the
driver. If reduced oxygen is the culprit, then changing the
environment is needed (Rabalais et al., 2007) and, in the best
case, the management response is rapid (Beutel and Horne,
1999). In contrast, if dwarfing reflects evolutionary adapta-
tion to fishing, then the fishing pattern needs to be changed,
and even in the best case the response is likely to be slow
(Law, 2000;Heino et al., 2015).
Here, we test how oxygen level affects maturation sche-
dules and growth in fish populations exposed to different
size-selective mortality regimes. We expect that both low
oxygen and exposure to positive size-selective fishing result
in earlier maturation and reduced growth. This is the first
study jointly to assess the effects of reduced ambient oxygen
and size-dependent mortality in fish. Thus, little is known
about the relative importance of these factors in driving
changes in key life-history traits. For this purpose, we used
populations of guppies (Poecilia reticulata) in laboratory
conditions. This model species was also used to demonstrate
von Bertalanffy’s theory of growth von Bertalanffy (1938),
to study the effect of fishing on population dynamics
(Silliman and Gutsell, 1958) and to assess the effect of preda-
tory size-selective mortality on life-history traits (Reznick
and Ghalambor, 2005). Moreover, similar laboratory experi-
ments have been shown to be useful to inform conservation
and management plans (see, e.g. Stockwell and Weeks,
1999;Conover and Munch, 2002;Reznick and Ghalambor,
2005;Diaz Pauli and Heino, 2014).
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Research article Conservation Physiology •Volume 5 2017
Materials and methods
We used guppies from a life-history experiment designed to
study evolutionary consequences of size-selective fishing. The
test fish were first-generation (F1) offspring from six replicate
laboratory populations that had experienced size-selective
mortality for 3.1 years (approximately four generations).
These populations represent two treatments, with three repli-
cates each, as follows: (i) positive size-selected line, in which
large individuals [>16 mm standard length (SL)] were
removed from the population every sixth week; and (ii) nega-
tive-size selected line, in which individuals smaller than 16mm
were removed at equal intervals.
Twenty females per population were housed together in 10
litre tanks and feed ad libitum with newly hatched Artemia
salina in the morning and fish flakes (tetraMin, Tetra) in the
afternoon. Tanks were checked twice a day for newborns,
which were collected and immediately transferred to 2litre
individual isolation aquaria, where they were randomly
assigned to one of two oxygen treatments: (i) high oxygen,
with 95 ±5% oxygen saturation, corresponding to ~7.9 ±0.4
mg l
−1
;or(ii)lowoxygen,with64%±6% oxygen saturation
(5.3 ±0.5 mg l
−1
). All tanks were covered with a tightly fitting
piece of Styrofoam over the whole water surface. The cover
prevented surface breathing and minimized gas exchange with
the atmosphere. In the high-oxygen treatment, high oxygen
saturation was maintained with an air stone. This resulted in
a2×2 full factorial experiment, with oxygen level and inher-
ited background (past size-selective mortality) as the treat-
ments. Ten males and 10 females from each of the six
populations were assigned to each oxygen treatment, resulting
in a total of n=240 fish (1:1 sex ratio).
Test fish were maintained in individual isolation at a con-
stant temperature of 25 ±0.5°C and under a 12 h–12 h light–
dark regime. During the first 2 weeks, each fish was fed daily
38 ±6µl of 3% solution of living filtered Artemia salina.At2
weeks of age, this was increased to 76 µlday
−1
,andat4weeks
of age it was increased to 114 µl, which was maintained until
the fish reached maturation and the experiment was terminated.
Fish were anaesthetized in a 0.3 g l
−1
solution of meta-
caine, measured for SL and weight, and assessed for matur-
ation weekly. Non-invasive assessment of maturation is
reliable only in males; this is achieved by following the devel-
opment of the gonopodium (modified anal fin used in insem-
ination). Initiation of maturation is indicated by the increase
from nine to ten segments in the third ray of the anal fin,
while complete maturation is marked by the growth of the
fleshy hood over the tip of the gonopodium and the number
of segments in the third ray being >27 (Turner, 1941;
Reznick, 1990). Gonopodium development is correlated
with the development of the gonadotrophic zone in the ade-
nohypophysis and the maturation of the testis (Kallman and
Schreibman, 1973;Schreibman and Kallman, 1977;Greven,
2011). The initiation of maturation stage is correlated with
initial enlargement of the testis and proliferation of sperma-
gonia and, possibly, spermatocytes (van den Hurk, 1974;
Koya et al., 2003). At the completion stage, there are several
layers of spermagonial cysts, sperm cells and developed tes-
ticular ducts with enzyme activity, and spermatozeugmata
(sperm bundles) are present (Schreibman et al., 1982;Koya
et al., 2003). We consider the initiation of maturation to be
a good representation of male maturation ‘decision’in guppies;
it is the time when they commit to maturation, reflecting more
accurately the factors that affect maturation than the final mat-
uration stage (Tobin et al., 2010;Harney et al., 2012;Diaz
Pauli and Heino, 2013). Therefore, in the present study we
assessed the effect of oxygen and size selection on the initiation
of maturation, from now on referred to as maturation. Female
maturation cannot be assessed non-invasively; therefore, from
female fish we obtained only growth data, from which we later
estimated maturation (see next subsection). Females were kept
in the experiment until 2 weeks after a male from the same
brood reached the last stage of maturation.
Statistical analysis
Growth
All analyses were performed in R (version 3.2.4; RCore
Team, 2016). To assess treatment effects on individual growth,
we used the biphasic growth model of Boukal et al. (2014),
which is derived from the model by Quince et al. (2008),
within the ‘nlme’R package (version 3.1–125; Pinheiro et al.,
2016). The model provides a mechanistic description of som-
atic growth pre- and post-maturation, based on the principles
of allometry and energy allocation. Surplus energy acquisition
rate, which is equal to maximal potential somatic growth, is
related to somatic weight, W, by the coefficient cand the allo-
metric exponent β, as follows:
=()
β
W
tcW
d
d1
Assuming that juveniles allocate surplus energy only to
growth (reproductive investment r
a
=0), the juvenile growth
curve for weight at age ais as follows:
=+(−β) ()
−β
−β
WWc a12
a0
1
1
The post-maturation (adult) growth curve takes into
account reproductive investment (r) for mature individuals,
i.e. for a≥a
mat
:
=(+)+
−(− )
()
−−β −β −β −−β
WRWHba
RHb
RR
11,
3
aaa aa
0
11mat
1
mat mat
1
where H=c(1 −β)b
−(1−β)
,R=1/[1 +(1 −β)r], and W
0
is
weight at birth.
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Conservation Physiology •Volume 5 2017 Research article
Growth curves were estimated for males and females separ-
ately. Weight at birth was affected neither by sex (F
213,1
=
1.68, P=0.19) nor by size-selection treatment (F
4.3,1
=0.07,
P=0.79) according to a linear mixed-effect model with popu-
lation as random factor. These linear mixed models were per-
formed with lme4 R package (version 1.1–11; Bates et al.,
2015). P-values and degrees of freedom were obtained with
the R package ‘lmerTest’(version 2.0–29; Kuznetsova et al.,
2015). Therefore, weight at birth W
0
=0.007 g was used for
both males and females. In males, age at maturation (a
mat
)was
included in the model as a known individual-specific variable
(age at which initiation of maturation occurs), but in females it
was estimated as a model parameter. Reproductive investment
(r) and the coefficient in the allometric growth rate–weight
relationship (c) were estimated for both males and females,
whereas the allometric exponent in the growth rate–weight
relationship (β) was estimated for males but kept constant for
females as β=0.8 because simultaneous estimation of βand
a
mat
was not possible. Initial exploration of our data showed
that β=0.8 was the most appropriate value for our data, and
similar values have been suggested by Boukal et al. (2014).
The parameters were estimated with a non-linear mixed-
effect model in the R package ‘nlme’(Pinheiro et al., 2016),
with fish identity (ID) as random factor for rand cfor both
males and females. Including fish ID as random factor for β
and a
mat
for males and females, respectively, did not improve
the models [for males the change in the Akaike information cri-
terion (ΔAIC) =6.1, likelihood ratio statistic =0.09, P=0.99;
and for females, ΔAIC =6.0, likelihood ratio statistic =0.0002,
P=1]. Oxygen, size-selection line and their interaction were
tested as fixed effects on r,cand βfor males and r,cand a
mat
for females. The model that yielded the lowest AIC was con-
sidered the best approximating model, i.e. the model that best
described the data. We also discuss models that differ from the
best ranked-model with AIC values >2(Δ
i=
AIC
i
−AIC
best
),
as these are considered essentially as good as the best model
(Burnham and Anderson, 1998). We also calculated the prob-
abilities of a model being the best model, referred to as Akaike
weights (w
i
). Notice that the approach chosen here does not
involve significance testing of the model parameters.
Maturation
Maturation in males is described by the probabilistic matur-
ation reaction norm (PMRN; Heino et al.,2002), estimated
with generalized linear mixed models with binomial error dis-
tribution using the lme4 package in R (version 1.1–11; Bates
et al., 2015). Fish ID nested within population was included as
a random factor, whereas age, weight, oxygen, size-selection
line and all their first-order interactions were included as fixed
effects. As for the growth models, we used the AIC to select
the final model. The logistic curve for the probability of matur-
ation is given by the following equation:
()~ + + + + +… ()pc cacwcocs clogit , 4
n01 2 3 4
where logit(p)=log
e
[p/(1 −p)] is the link function, c
0
is the
intercept, and c
1
to c
n
are the regression parameters of the
model for the different explanatory variables (age a,weightw,
oxygen o, size-selection line s, interactions, etc.). To facilitate
the interpretation of the model coefficients, weight and age
were standardized to zero mean and unity standard deviation
(SD). In males, mean age was
¯
x
±SD =87.6 ±27 days, and
mean weight was
¯
x
±SD =0.055 ±0.012 g. The PMRN mid-
points (i.e. the estimated age-specific weight at which the prob-
ability of maturing is 50%; also referred as W
p50
)wereusedto
illustrate the estimated reaction norms and are roots of equa-
tion (4) for weight w.
For females, maturation cannot be assessed non-invasively,
and age at maturation (a
mat
) was estimated from the biphasic
growth model. This implies a definition of maturation that is
purely energetic and corresponds to the (assumed) abrupt start
of allocating a significant proportion of energy to reproduc-
tion; it is not possible to link this definition to male matur-
ation based on different criteria.
Results
Males
Growth in males showed high inter-individual variability
(Fig. 1a). Nevertheless, growth models suggested significant
effects of both oxygen treatment and parental size-selection
line (Fig. 1b and Table 1). No single model was superior, but
all highest-ranking models were broadly similar and suggested
significant effects of oxygen and/or size selection on all para-
meters (Table 1). The model that explained the data best (M1)
included effects of oxygen and size selection on reproductive
investment (r) and on the coefficient cin the growth rate–
weight relationship, whereastherewasaneffectofsize-
selection line only on the allometric exponent βof the growth
rate–weight relationship (Table 1). This model was superior to
the model that did not include any treatment effect (M0;
ΔAIC =25.99, likelihood ratio test statistic =35.99, P<0.001).
Males under low ambient oxygen from each selection line
reached lower predicted weights at age 210 days than their
counterparts with high ambient oxygen (Fig. 1b and Table 1),
but their size-specific maximal potential growth rate was higher
(growth rate theoretically attained in the absence of reproduc-
tion; Fig. 2a). Likewise, males that were descended from the
positive size-selection lines reached higher predicted weights at
age 210 days (Fig. 1b) and presented a higher size-specificmax-
imal potential growth rate than those descended from the nega-
tive size-selection lines (Fig. 2a). Results are similar for the
other models with high probability for explaining our data
(M2–M4); these models also showed the effect of our treat-
ments on the growth parameters, particularly with an effect of
size-selection line on allometric growth and oxygen in repro-
ductive investment (Table 1). Only one model (M3) included
an interaction effect between oxygen and size selection, suggest-
ing that the effect of oxygen on reproductive investment (r)was
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Research article Conservation Physiology •Volume 5 2017
reversed for the negatively compared with positively size-
selected lines (Table 1).
In high-oxygen conditions, males from the lines exposed
to negative size-selective mortality matured at 0.065 ±
0.010 g (mean ±SD) and 111 ±25 days old, whereas those
from positive size-selective mortality matured at 0.060 ±
0.008 g and 97 ±23 days (Fig. 3). In the presence of low
oxygen availability, males matured at 0.048 ±0.008 g and
75 ±19 days old and at 0.044 ±0.007 g and 66 ±12 days
old for negative and positive size-selection, respectively.
Thus, both low oxygen and positive size-selective mortality
resulted in earlier maturation at smaller size, but the effect of
oxygen was larger than that of size-selective mortality.
Mean age and size at maturation are also influenced by
growth. Maturation tendency can be expressed independently
from growth by calculating age- and size-dependent matur-
ation probabilities, i.e. PMRNs. Nearly horizontal PMRNs
(Fig. 3) show that maturation is primarily determined by
size, with only a weak, positive effect of age. The size
(weight) at 50% maturation probability at a given age was
significantly smaller in low-oxygen conditions and for posi-
tive size-selection lines (Fig. 3). The oxygen availability had
the strongest effect, with the odds of maturation in the pres-
ence of low oxygen ~61 times higher than in high-oxygen
conditions [estimate ±SE =4.11 ±0.9 in log(odds),
z=4.68, d.f. =1, P<0.001]. This is in line with the results
obtained from analysis of growth curves showing that
males in the presence of low oxygen also invested more in
reproduction (higher r) than those reared in high oxygen.
Descending from the positive size-selection line had a
weaker positive effect, increasing the odds of maturation
compared with negative size-selection by a factor of 3.1
[estimate ±SE =1.12 ±0.5 in log(odds), z=2.33, d.f. =1,
P=0.02].
The effect of oxygen availability on maturation was strong
also in comparison to the effect of growth. An increase in
weight by 1 SD (0.012 g) corresponded to an increase in odds
of maturing by a factor of 11.0 [estimate ±SE =2.41 ±0.5
in log(odds), z=5.12, d.f. =1, P<0.001]. Age influenced
maturation only through its interaction with weight; the effect
was weak but significant [odds ratio =0.59 for 1 SD increase
in weight and age, estimate ±SE =−0.53 ±0.1 in log(odds),
z=−3.75, d.f. =1, P<0.001], which resulted in a decreas-
ing PMRN for older ages (Fig. 3).
Females
As with males, inter-individual variability in female growth
was high but contained significant effects related to oxygen
availability and parental size-selection line (Fig. 4a). The
best-ranked model (F1) showed an effect of oxygen level,
selection line and their interaction on age at maturation, and
an effect of oxygen and size selection on reproductive invest-
ment and on the growth coefficient (Table 2). Females reared
in low-oxygen conditions showed lower predicted weight at
age 190 days relative to females reared in high-oxygen condi-
tions (Fig. 4b). Similar to the males, this was probably a
result of a higher investment in reproduction and earlier age
at maturation (Table 2), rather than size-specific maximal
potential growth rate that was higher in low oxygen
(Fig. 2b). Although females from the positive size-selection
0.00
0.05
0.10
0.15
Age (days)
Weight (g)
(a)
Positive and high O2
Positive and low O2
Negative and high O2
Negative and low O2
0 10 30 50 70 90 110 130 150 170 190 210 0 10 30 50 70 90 110 130 150 170 190 210
0.00
0.05
0.10
0.15
Age (days)
Weight (g)
(b)
Positive and high O2
Positive and low O2
Negative and high O2
Negative and low O2
Figure 1: Growth trajectories for males from raw data (a) and biphasic growth model estimates (b). In (a), symbol type represents the size-
selection treatment and colour the oxygen treatment. Filled symbols depict the observations when initiation of maturation was scored. In (b),
colour represents oxygen treatments, respectively, and line type refers to size-selection line. Growth curves are based on the best-ranked
model (M1), and growth parameter values are given in Table 1.
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Conservation Physiology •Volume 5 2017 Research article
line reached a higher predicted weight at 190 days (Fig. 4b),
their size-specific maximal potential growth rate was lower
than that of females in negative size-selection lines (Fig. 2b
and Table 2). Females from positive size-selection lines
presented lower reproductive investment and older age at
maturation (Table 2) relative to females from negative
size-selection lines. The model showing these treatment
effects (F1) was superior to the null model considering no
treatment effects (F0; ΔAIC =48.11, likelihood ratio test stat-
istic =62.10, P<0.001). Similar results were obtained with
the second-ranked model (F2; Table 2). Both best-ranked
models suggest an interaction effect between oxygen and size
selection, either for age at maturation (F1) or for reproductive
investment (F2; Table 2).
Age at maturation for females could not be observed dir-
ectly, but the estimates from the growth model showed a pat-
tern similar to the one obtained for males (Table 2). Mean
age at maturation was lower in low-oxygen conditions com-
pared with high-oxygen conditions. However, females from
lines with negative size-selective mortality had a lower age at
maturation than those from lines with positive size-selective
mortality. The highest mean age at maturation was for
females in high-oxygen conditions for females from lines
with positive size-selective mortality (65 days). These esti-
mates are lower than the observations for males (treatment-
specific mean 66–111 days), but the estimates are not directly
comparable because they are based on different ways of
defining and estimating maturation.
Discussion
The oxygen saturation in the ambient water and prior
ancestral exposure to size-selective mortality affected mat-
uration, growth and reproductive investment in similar
ways. A reduced ambient oxygen led to stunting, early mat-
uration and high reproductive investment. Fish exposed to
high mortality of larger-sized individuals displayed earlier
maturation at smaller size, greater investment in reproduc-
tion and faster growth. These results were clearer for male
guppies than for females.
Table 1: Male biphasic growth model estimates for reproductive investment, r, growth coefficient, c, and allometric exponent, β
Model
Effects Support Parameter estimates
Δ
i
w
i
Treatment rc(g
1−β
day
−1
)β
M1 r~ size selection +O
2
c~ size selection +O
2
β~ size selection
0 0.28 High O
2
and negative size selection 0.0006 0.0009 0.16
High O
2
and positive size selection 0.0009 0.0013 0.25
Low O
2
and negative size selection 0.0025 0.0010 0.16
Low O
2
and positive size selection 0.0028 0.0014 0.25
M2 r~O
2
c ~ size selection
β~ size selection +O
2
0.07 0.27 High O
2
and negative size selection 0.0007 0.0009 0.17
High O
2
and positive size selection 0.0007 0.0013 0.25
Low O
2
and negative size selection 0.0023 0.0009 0.14
Low O
2
and positive size selection 0.0023 0.0013 0.22
M3 r~ size selection * O
2
c ~ size selection +O
2
β~ size selection
0.11 0.26 High O
2
and negative size selection 0.0002 0.0009 0.16
High O
2
and positive size selection 0.0014 0.0013 0.24
Low O
2
and negative size selection 0.0029 0.0010 0.16
Low O
2
and positive size selection 0.0020 0.0014 0.24
M4 r~O
2
c~ size selection +O
2
β~ size selection
0.81 0.19 High O
2
and negative size selection 0.0007 0.0009 0.16
High O
2
and positive size selection 0.0007 0.0013 0.24
Low O
2
and negative size selection 0.0026 0.0010 0.16
Low O
2
and positive size selection 0.0026 0.0014 0.24
M0 r~1
c~1
β~1
25.99 0.00 n.a. 0.0013 0.001 0.18
Support for a particular model is given by the change in the Akaike information criterion (AIC) relative to the model with the lowest AIC (Δ
i
), and by the Akaike
weights (w
i
). All models follow equations (2) and (3) but differ in which of the parameters (if any) are affected by the treatment(s) as well as the presence of treat-
ment interactions (denoted with ‘*’in the model formulae). Results are shown for the four best-ranked non-linear mixed-effect models (M1–M4; the model with the
lowest AIC and all models for which Δ
i
<2) as well as for the null model (M0) without any effects of experimental treatments (formula ‘~1’means that the param-
eter is unaffected by the treatments). n.a. means "not applicable".
..............................................................................................................................................................
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Research article Conservation Physiology •Volume 5 2017
Oxygen
Exposure to low oxygen saturation resulted in a smaller size
at age and higher investment in reproduction relative to
exposure to normoxic conditions, as expected if reduced
oxygen supply triggers the shift from somatic growth to mat-
uration (Pauly, 1984;Kolding, 1993;Kolding et al., 2008a).
Both males and females also matured at an earlier age and
smaller size when reared in low-oxygen relative to high-
oxygen conditions. The low-oxygen treatment was not severe
enough to hamper fish maturation as observed in some other
studies (e.g. Wu et al., 2003;Landry et al., 2007;Chabot
and Claireaux, 2008).
Low oxygen resulted in faster juvenile size-specific max-
imal growth rate. Iles (1973) predicted such an increase in
the juvenile growth rate of wild tilapia owing to low oxygen
availability, although his prediction might be a result of lack
of standardization of the growth rates. In any case, it should
be noticed that a reduction in growth rate associated with
low oxygen levels is detectable only after maturation (Pauly,
1981;van Dam and Pauly, 1995). Other studies of adult
growth in guppies did see a decrease in growth rate owing to
oxygen limitation (Weber and Kramer, 1983). The lack of
decrease in growth rate in our experiment was not attribut-
able to surface respiration, because our experimental set-up
prevented it. Aquatic surface respiration is initiated in
(a) (b)
Positive and high O2
Positive and low O2
Negative and high O2
Negative and low O2
4e−04
5e−04
6e−04
7e−04
8e−04
Weight (g)
Growth rate (g day−1)
0.00 0.02 0.04 0.06 0.08 0.10 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14
0.0000
0.0005
0.0010
0.0015
0.0020
0.0025
0.0030
Weight (g)
Growth rate (g day−1)
Figure 2: Maximal potential size-specific growth rates for males (a) and females (b) in high (black lines) and low (grey lines) oxygen treatments
and that belonged to the positive size-selection lines (dashed lines) or the negative size-selection lines (dotted lines). Growth rates are based in
males (a) on the allometric exponent βand the coefficient cin the growth rate–weight relationship estimated with the best-ranked model (M1,
Table 1), whereas in females (b), growth rates are based on the allometric coefficient cin the growth rate–weight relationship estimated with
the best-ranked model (F1) and the exponent βhad the value of 0.8 for all treatments (Table 2). Realized growth rates are lower when energy
is allocated to reproduction; the predicted growth curves in Figs 1b and 4b account for this, for males and females, respectively.
Positive and high O2
Positive and low O2
Negative and high O2
Negative and low O2
40 60 80 100 120 140 160
0.00
0.02
0.04
0.06
0.08
Age (days)
Weight (g)
Figure 3: Weight- and age-based probabilistic maturation reaction
norms for males represented by the midpoints (weight with 50%
maturation probability, W
p50
) in conditions of high (black line) and
low (grey line) oxygen and for positive (dashed line) and negative
(dotted line) size-selected lines. Black and grey triangles (negative
size-selection line) and inverted triangles (positive size-selection line)
represent the observed weights (in grams) and ages (in days) at
maturation for high and low oxygen, respectively.
..............................................................................................................................................................
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Conservation Physiology •Volume 5 2017 Research article
guppies at ~30% oxygen saturation (Kramer and Mehegan,
1981); hence, even if it had been allowed in our study, it
might not have been important. Thus, our modest reduction
in oxygen availability led to a slightly faster juvenile growth
rate and triggered earlier maturation and increased repro-
ductive allocation, which resulted in stunting in both males
and females, despite higher maximal potential growth rates.
Size-selective mortality
Positive size-selective mortality implies a higher mortality risk
for large individuals relative to small individuals. In the pre-
sent study, the size limit for culling was set at 16 mm SL,
slightly less than normal guppy maturation length (Magurran,
2005). Positive size-dependent mortality favours fast life-
0.00
0.05
0.10
0.15
Age (days)
Weight (g)
0 20 40 60 80 100 120 140 160 180 200 0 20 40 60
80
100 120 140 160 180
0.00
0.05
0.10
0.15
Age (days)
Weight (g)
Positive and high O2
Positive and low O2
Negative and high O2
Negative and low O2
Positive and high O2
Positive and low O2
Negative and high O2
Negative and low O2
(a) (b)
Figure 4: Growth trajectories for females from raw data (a) and biphasic growth model estimates (b). In (a), inverted triangles represent the
positive size-selected line and upright triangles the negative size-selected line, while black refers to high oxygen and grey to low oxygen. In (b),
black and grey lines represent high- and low-oxygen treatments, respectively; and dashed lines refer to females that belonged to the positive
size-selection line whereas dotted lines refer to the negative size-selection line. Growth curves are based on the best-ranked model (F1), and
growth parameter values are given in Table 2.
Table 2: Female biphasic growth model estimates for reproductive investment, r, growth coefficient, c, and age at maturation, a
mat
Model
Effects Support Parameter estimates
Δ
i
w
i
Treatment rc(g
1−β
day
−1
)a
mat
(days)
F1 r~ size selection +O
2
c~ size selection +O
2
a
mat
~ size selection * O
2
0 0.48 High O
2
and negative size selection 0.011 0.013 53.7
High O
2
and positive size selection 0.009 0.012 65.2
Low O
2
and negative size selection 0.014 0.014 53.6
Low O
2
and positive size selection 0.012 0.013 62.8
F2 r~ size selection * O
2
c~O
2
a
mat
~ size selection +O
2
0.95 0.30 High O
2
and negative size selection 0.010 0.012 54.4
High O
2
and positive size selection 0.009 0.012 63.7
Low O
2
and negative size selection 0.012 0.013 53.5
Low O
2
and positive size selection 0.014 0.013 62.9
F0 r~1
c~1
a
mat
~1
48.11 0.00 n.a. 0.011 0.013 60.6
Results are shown for the two best-ranked non-linear mixed-effect models [F1–F2, i.e. the model with the lowest Akaike information criterion (AIC) and the only other model
for which Δ
i
<2] as well as for the null model (F0) without any effectsof experimental treatments. See Table 1for further explanation. n.a. means "not applicable".
..............................................................................................................................................................
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Research article Conservation Physiology •Volume 5 2017
history strategies involving early maturation, high investment
in reproduction and, in many cases, a faster growth rate
before maturation (Charlesworth, 1994;Law, 2000;Réale
et al.,2010
;Enberg et al.,2012).
Our results are in agreement with these expectations, par-
ticularly in the case of male guppies. Males descending from
lines exposed to positive size-selective mortality had a higher
probability of maturing at a given age and size, which led to
maturation at a smaller size and younger age compared with
males from the lines subjected to negative size selection.
Males also had a higher investment in reproduction. Our esti-
mates are comparable with earlier studies on guppies and
other poeciliids for reproductive investment (Baatrup and
Junge, 2001;Schlupp et al.,2006) and size and age at matur-
ation (Reznick and Bryga, 1987;Magurran, 2005); it should
be noticed that most studies considered completion of matur-
ation, rather than initiation of maturation (but see Diaz Pauli
and Heino, 2013). Similar directional changes in maturation
and reproductive investment have been observed in several
exploited fish populations (Heino et al.,2015) and in other
selection experiments (van Wijk et al.,2013;Uusi-Heikkilä
et al.,2015
).
Males presented faster maximal potential and realized
growth rates in lines exposed to positive size-dependent mor-
tality. Studies on the effect of (positive) size-selective fishing
mortality have often concluded that growth rates decreased
rather than increased, but in most cases such reduction was
a secondary effect from increased allocation to reproduction
(reviewed by Enberg et al., 2012;Heino et al., 2015) and
applies to post-maturation growth. This contrasts with the
simplistic expectation that killing large fish should always
favour smaller fish and thus slower growth. Although this
expectation is largely warranted for adult fish, expectations
for juvenile growth are less straightforward (Enberg et al.,
2012). Dunlop et al. (2009) concluded that one key factor
that determines whether positively size-selective fishing
favours an increased or decreased juvenile growth rate is the
size limit at which the harvesting takes place. When the min-
imal size is set smaller than the size at maturation, as in our
experiment, juvenile growth is expected to accelerate to
reach maturation earlier in life (Dunlop et al., 2009).
Positive size selection also led to faster juvenile growth rate
in zebrafish (Danio rerio;Uusi-Heikkilä et al., 2015).
Males from the lines exposed to positive size-selective
mortality had larger predicted size at age 210 days (the max-
imal age in the experiment). This occurred because of their
high maximal potential growth rate and despite their earlier
maturation and higher investment in reproduction. This
result is contrary to theoretical expectations (Heino et al.,
2015) and other experimental studies (Walsh et al., 2006;
van Wijk et al., 2013;Uusi-Heikkilä et al., 2015). A possible
explanation is that because we killed our fish soon after mat-
uration, we have little information on how their realized
growth and reproductive allocation would have developed
through their adulthood, which was estimated in former
studies (Walsh et al., 2006;van Wijk et al., 2013;Heino
et al., 2015;Uusi-Heikkilä et al., 2015). The ultimate size at
adulthood is affected by the maximal potential somatic
growth rate as well as the continued investment in reproduc-
tion in this iteroparous species and might have resulted in
smaller individuals later in life in positive size-selected lines.
Our estimates of realized growth rate are similar to those of
Auer et al. (2010). The values of βestimated from our model
are in the lower range of the great variation in the values of
the allometric exponent β(Killen et al., 2010;Boukal et al.,
2014), which is associated with determinate/indeterminate
growth. Male poeciliids are typically considered to have
determinate growth, although they do not completely cease
growth after maturation (Snelson, 1982). Nevertheless,
because fish were killed well before reaching their maximal
sizes, our estimates of βmight be downward biased. In prac-
tice, the estimations of βand reproductive investment (r) are
confounded, and the truncated adult lifespan might have
aggravated this problem.
Whether the differences between size-selected lines represent
evolutionary (i.e. genetic) change is ambiguous, as our experi-
mental set-up only controlled for environmental differences
among the fish subjected to the oxygen treatments, but not
those of their parents. It is generally accepted that lines should
be maintained for at least two generations in common gar-
den conditions to be able to discern genetic changes clearly
using phenotypic data (Reznick and Ghalambor, 2005). The
differences could therefore represent parental effects, genetic
differences or (perhaps most likely) a combination of both.
Nevertheless, the phenotypic changes were in agreement
with the predictions from life-history theory.
Estimates for reproductive investment, growth rate and age
at maturation in females are comparable with values obtained
in other studies (Magurran, 2005;Auer et al., 2010;Rocha
et al., 2011). Still, as maturation in females could not be deter-
mined visually, the study of life-history changes in them was
not as thorough as with males. Exposure to positive size-
selective mortality led to estimated maturation at older rather
than younger ages, and to a lower investment in reproduction.
This is opposite to what was observed in males in the present
study and earlier selection experiments (Walsh et al., 2006;
Uusi-Heikkilä et al., 2015). However, these results refer to age
at maturation inferred with the growth model and which might
be inaccurate, rather than to directly observed maturation, as
with males. In addition, females in the positive size-selected
line presented lower maximal potential size-specificgrowth
rates, but higher realized growth, contrary to what was
observed in males. The estimation of maximal growth rate was
based on only one parameter (c, the coefficient in the growth
rate–weight relationship), while the allometric exponent βwas
kept constant. For males, it was the allometric exponent βthat
showed the strongest effect of size-selection line and the param-
eter that affected growth rate the most. If the growth model
for females is performed to estimate βby keeping cconstant at
..............................................................................................................................................................
9
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Conservation Physiology •Volume 5 2017 Research article
0.01 g
1−β
day
−1
, the results remain very similar (results not
shown). Nevertheless, the differences between positively and
negatively size-selected lines were smaller for females than for
males, despite being significant in all cases.
Interplay of effects on life-history traits and
implications
Manipulation of the oxygen level resulted in bigger changes
in reproductive investment and maturation compared with
manipulation of size-selective mortality in parental genera-
tions. Positive culling led to an estimated increase in repro-
ductive investment of 33% relative to negative culling (in
high-oxygen conditions), whereas low oxygen led to an
increase of >100% relative to high oxygen. Similar results
were obtained for age and size at maturation; the odds of
maturing were 60 times higher in the presence of low oxygen
compared with high oxygen, but only three times higher for
positive lines compared with negative lines.
However, direct comparison of the importance or strength
of these two different drivers is difficult for two reasons. First,
the two treatments are conceptually very different; the oxygen
treatment was affecting the ambient environment of the very
same fish that we observed during the experiment, whereas the
size-selective mortality treatment represented conditions that
the parental generations of the test fish had experienced over
the course of 3 years (approximately four generations). The
actual treatment levels are in both cases somewhat arbitrary
(i.e. the specific oxygen saturation level and the duration and
intensity of past size selection). Second, the mechanisms
through which the treatments affect life histories are different.
Oxygen is a strong proximate driver of phenotypic change in
maturation and growth, triggering direct plastic responses
(Pauly, 1984;Kolding et al.,2008a), whereas the effect of size-
selective mortality on life histories occurs through both genetic
change (evolution) and phenotypic plasticity, including inter-
generational plasticity (parental effects). Although hypoxia
could also lead to evolutionary changes in life history (Riesch
et al., 2010), this was not considered in our experiment that
followed only a single generation of fish.
Our results do not suggest strong interactions between
ambient oxygen and prior size selection in controlled labora-
tory conditions; that is, that the effects of oxygen level would
depend on adaptations to contrasting size-selectivity regimes.
For males, only one of the four top-ranking growth models
included an interaction between size selection and oxygen
(affecting a single parameter), whereas for females, both top-
ranking models contained a single interaction each. These
findings provide some evidence for the oxygen-depletion-
induced increase in reproductive investment being stronger
in the lines that had been subjected to negative size-selective
mortality. Most effects, however, were simply additive.
We believe it is essential to consider both proximate and
ultimate factors to gain a better understanding of life-history
variation and how populations evolve under the influence of
these factors. Hypoxia and size-dependent mortality, including
that induced by fishing, not only co-occur, but can also drive
similar life-history changes. Thus, investigation of the interplay
of fishing- and hypoxia-induced changes is necessary to make
ecosystem-based predictions on the sustainability of the fishery
(Kolding et al., 2008b). To our knowledge, this is the first
study to look at the combined effect of oxygen and size-
dependent mortality on life-history traits. Despite being an
experimental study, our results illustrate the risks of trying to
infer the process from patterns. This is a well-known problem,
much discussed in the context of using observational field data
to study life-history changes in exploited fish populations (e.g.
Dieckmann and Heino, 2007;Kraak, 2007;Browman et al.,
2008;Jørgensen et al.,2008;Kuparinen and Merilä, 2008).
The potential role of low oxygen levels in driving phenotypic
change, however, has until now been overlooked (e.g. Sharpe
et al.,2012
). We encourage the performance of further studies
to link these factors to changes in life-history, behavioural and
physiological traits, and that the confounding effect of oxygen
should be considered along with other environmental factors
when studying the effects of size-selective fishing in exploited
populations.
Acknowledgements
We want to thank Diep Mach Ellertsen for help with the
maintenance of the fish, Heikki Savolainen for technical help
in the laboratory and Daniel Pauly for comments on the
manuscript. This experiment was carried out with the
approval of the Norwegian Animal Research Authority
(Forsøksdyrutvalget, Id. 5562).
Funding
This work was supported by the Research Council of
Norway (project 214189/F20), the Bergen Research
Foundation, and the University of Bergen fund for Open
Access.
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