# Predation impacts brain allometry and offspring production in female guppies (Poecilia reticulata)

Regina Vega-Trejo, David Mitchell, Catarina Vila-Pouca, Alexander Kotrschal

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## To cite this version:

Regina Vega-Trejo, David Mitchell, Catarina Vila-Pouca, Alexander Kotrschal. Predation impacts brain allometry and offspring production in female guppies (Poecilia reticulata). 2021. **hal-04709517**

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¹Predation impacts brain allometry and offspring production in

²female guppies (*Poecilia reticulata*)

3

4Regina Vega-Trejo¹,²*, David J Mitchell¹, Catarina Vila Pouca¹,³, Alexander Kotrschal¹,³

5

6¹Department of Zoology, Stockholm University, Svante Arrhenius väg 18B, 10691,  
7Stockholm, Sweden

8²Department of Zoology, Edward Grey Institute, University of Oxford, Oxford OX1 3SZ, UK

9³Department of Animal Sciences: Behavioural Ecology, Wageningen University & Research,  
106708 WD Wageningen, Netherlands

11

12*corresponding author: reginavegatrejo@gmail.com

13

14Running title: Predation affects female brain allometry

15

16Keywords: life-history, survival, guppy, reproduction, natural selection, phenotypic plasticity

17

18Word count: 5461

19Number of tables: 0

20Number of figures: 3

21Online appendix items: 1
24Survivorship under predation exerts strong selection on reproductive traits as well as on
25brain anatomy of prey. However, how exactly predation and brain evolution are linked has
26not been resolved as current empirical evidence is inconclusive. This may be due to
27predation pressure having different effects across life stages and/or due to confounding
28factors in ecological comparisons of predation pressure. Here, we used adult guppies
29(*Poecilia reticulata*) to experimentally test the impact of a period of strong predation on
30brain anatomy and reproduction of surviving individuals. We compared the survivors to
31control fish, which were exposed to visual and olfactory predator cues but could not be
32predated on, and found that predation impacted the relative size of female brains. This
33effect was dependent on body size as larger female survivors showed relatively larger
34brains, while smaller survivors showed relatively smaller brains when compared to control
35animals. There were no differences in male relative brain size between the treatments, nor
36for any specific relative brain region sizes for either sex. Moreover, survivors produced more
37offspring, but did not show shorter interbrood intervals than controls. Our results
38corroborate the important, yet complex, role of predation as an important factor behind
39variation in brain anatomy.
40**Introduction**

41

42Predation pressure is a key ecological factor in shaping the evolution of morphological,
43physiological, behavioural, and life-history traits (Reznick & Endler 1982; Lima & Dill 1990;
44Heinen-Kay & Langerhans 2013). Predators drive prey trait evolution over generations
45through non-random mortality (natural selection) or elicit changes in morphology,
46behaviour, or decision-making processes within a generation (phenotypic plasticity; Lima &
47Dill 1990; Kondoh 2010). One key trait for which predation has been identified as an
48important evolutionary selective force is vertebrate brain size (Burns & Rodd 2008;
49Kotrschal et al. 2015; van der Bijl et al. 2015; Walsh et al. 2016). This is because individuals
50may differ in their ability to assess predators due to differences in cognitive abilities
51associated with brain size (Striedter 2005; Moller & Erritzoe 2014; Samuk et al. 2018).
52Larger-brained prey could be more effective at avoiding predators given their likely better
53ability to alter their behavioural responses to specific predator encounters (Shultz & Dunbar
542006). Conversely, predicting the likelihood of a predator attack requires gathering and
55processing information, at which individuals with larger brains might be better (Moller &
56Erritzoe 2014; van der Bijl et al. 2015). Correlational studies in birds have shown that species
57with larger brains experience lower rates of adult mortality when compared to smaller
58brained species (Sol et al. 2007). Another link between predation and brain anatomy in birds
59is flight initiation distance. This indicator for assessing and evading predation threat is
60shorter in species with relatively larger brains (Moller & Erritzoe 2014). Potentially, larger-
61brained birds benefit from being able to better assess the risk, reducing the costs associated
62with fleeing too often, while remaining safe (Sol et al. 2005).

63

64 The relationship between predation and the brain is not straightforward, with 65ecological comparisons showing evolutionary effects varying in magnitude, direction, 66heritability, and with sex (Gonda et al. 2012; Gonda et al. 2013; Kotrschal et al. 2015; Walsh 67et al. 2016; Samuk et al. 2018). For instance, in guppies artificially selected for large and 68small relative brain size (i.e. brain size relative to body size), large-brained females survived 69longer under predation in a semi-natural setting, while no effect was found for males 70(Kotrschal et al. 2015). However, male but not female guppies exposed to cues of predation
71risk in the laboratory or actual predation risk in the wild developed heavier brains (Reddon 72et al. 2018). Predator-prey comparisons across different fish species have also revealed that 73larger brained predators tend to prey on larger-brained prey, but that prey's relative brain 74size is larger than that of the predator (Kondoh 2010).

75

76 On the other hand, large brains may not always be beneficial in a predatory 77environment as high metabolic costs (Niven & Laughlin 2008) can outweigh the cognitive 78benefits of larger brains. Indeed, in Trinidadian killifish (Rivulus hartii), males from sites with 79large piscivores, which predate on adults, have evolved smaller brains when compared with 80fish from sites that lack piscivorous fish (Walsh et al. 2016). In contrast, when comparing 81sites that differ in juvenile predation, there was no association between predation and adult 82brain size (Beston et al. 2017). Moreover, sticklebacks from complex marine environments 83characterized by high levels of predation and lower prey densities have smaller brain size 84than fish from simple pond environments that lack predators (Gonda et al. 2011). Similarly, 85experimental exposure to predators in sticklebacks resulted in smaller relative brain sizes 86when compared to control populations (Samuk et al. 2018). One cause of variation in the 87effect of predation in ecological comparisons may be other environmental factors. For 88instance, in studies of the guppy (Poecilia reticulata), high- and low-predation populations 89are usually separated by waterfalls which larger predatory fish cannot cross. Predation also 90drives population demographics by reducing densities, and by changing intra and 91interpecific competition dynamics (Magurran & Phillip 2001; Reznick et al. 2001; Reznick et 92al. 2012). These factors are likely to affect brain size through energetic trade-offs (Isler & 93van Schaik 2006), and provide an alternate explanation for the higher growth rates and 94reproductive productivity shown on high predation fish (Arendt & Reznick 2005). Hence, 95despite a wealth of data showing correlations between predation and aspects of brain 96anatomy, empirical evidence for a direct effect of predation on the brain is currently lacking.

97

98 We examined how predation impacts brain morphology and reproductive traits, 99while controlling for non-lethal effects of visual and olfactory predation cues. All individuals 100were bred and raised in similar conditions and were sexually mature young adults when 101exposed to a predator for the first time. We focused on the effect of direct removal by 102predators while controlling for potential foraging effects by providing food 'ad libitum',
103allowing us to test the link between survival and brain size driven by direct predation in the
104adult stage. Guppies are livebearing fish that naturally occur in streams where the presence
105and abundance of predators differ, mainly cichlids and killifish (Reznick & Endler 1982), and
106where predation pressure has been shown to correlate with brain anatomical differences
107(Kotrschal et al. 2017c). While we expected predation to impact brain anatomy in our
108experiment, predation likely also impacts the life-history traits of surviving animals. For
109example, killifish from high predation populations allocate more energy to reproduction
110than those from populations that lack predators (Walsh & Reznick 2008). Guppies are a
111classic system for investigating how predation pressure impacts life history traits (Reznick &
112Endler 1982), and it is well established that guppies from high predation sites mature at an
113earlier age, have higher reproductive effort per pregnancy, and have more but smaller
114offspring per brood in high compared to low predation populations (Reznick et al. 1990;
115Reznick et al. 1996). Moreover, larger brain sizes may be negatively associated with
116reproductive effort due to the costs associated with maintaining a large brain (Isler & van
117Schaik 2006). However, which aspects of predation underlie differences in reproductive
118output, and how they may relate to brain size investment, are not well resolved.

119

120 We predicted that fish surviving predation events would reproduce faster and have
121more offspring, in line with previous life-history evidence in guppies (Reznick & Endler
1221982). We also predicted survivors would have a larger relative brain size, and more
123specifically larger structures related to perception or learning (in particular telencephalon
124and optic tectum), than fish from the control treatment. This is because the telencephalon is
125associated with spatial learning and memory in fish (Broglio et al. 2003), which could
126increase the accuracy or speed of decisions. Similarly, elelctrical stimulation in the optic
127tectum elicits coordinated body movements and motor patterns (Broglio et al. 2003), that
128would allow individuals to have a better response to avoid predators. Both brain regions
129have been shown to be positively associated with predator pressure in the wild (Kotrschal et
130al. 2017b).

131

132Methods

133
134We examined the effect of direct predation on relative brain size, as well as on reproductive
135traits (number of offspring and interbrood interval), by comparing fish that were exposed to
136visual and olfactory cues but could not be predated (control treatment) with fish that
137survived exposure to a predator (predation treatment).

138

139 We used laboratory descendants of Trinidadian guppies originated from large high
140predation populations, but that have not been exposed to predators for 16 years. We set up
141110 breeding pairs, from which individuals for three replicates were produced, and we
142additionally included 100 fry from the stock population. Fry were kept in 4L tanks until their
143sex could be identified (females by their gravid spot, and males by the presence of a
144modified anal fin called a gonopodium). Mature individuals were kept in single-sex 50L tanks
145until the start of the experiment. For each replicate, a total of 200 mature individuals of
146each sex were used; 180 individuals were randomly selected for the predation treatment
147and 32 individuals for the control treatment, and we conducted three replicates per sex.

148

149 The experimental tank was 120×110×70 cm, filled with 220L of water, with a
150bottom layer of multicoloured limestone gravel (3-8 mm grain size) with which we crafted
151areas of different depths, so that the water depth ranged from 5-17 cm (Fig. 1). The shallow
152area provided a refuge for the guppies where the predator could not hunt. One cichlid
153(*Chrenicicla alta*) was placed at the deepest area of the tank and provided a clay pipe as a
154shelter (Fig. 1). The cichlids used were acquired through the aquarium trade and fed with
155live guppies prior to the experiment. Note that this is a sister species to *C. frenata*, the
156guppy's natural predator. Control fish (16 individuals per tank) were held in two 11L
157transparent tanks which were located at each side of the experimental tank. We installed
158two Eheim filter pumps (60L × h⁻¹ per pump) outside the 11L tanks and directed the water
159flow into each of these 11L tanks to provide olfactory cues for the control fish. Thus, control
160fish had visual exposure to the cichlid, to the behaviour and density of guppies in the full
161tank, and were exposed to the same water. This setup had the potential limitation that
162control fish were in a more constrained area, which *may* affect their growth and
163development. However, we prioritised standardising the visual and olfactory cues of
164predation which are known to have strong developmental effects on guppies (Torres-
165Dowdall *et al.* 2012; Ghalambor *et al.* 2015), including on their relative brain size (Reddon
166et al. 2018). Thus we effectively controlled for these effects to better focus on selective
167survival.

168

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169

170

171Figure 1. Set up of the experimental tank (view from above). Fish from the predation
172treatment were allowed to swim freely in the tank (N=180), whereas control fish were
173placed in 11L transparent tanks (N=16 each, shown in dashed squares) to provide visual
174cues, with a filter pump that allowed water to get into the tank to provide olfactory cues.
175Water flow from the pumps is indicated with arrows. A predatory cichlid was placed at the
176deepest area with a clay pipe for shelter. Different shades of blue represent different
177depths.

178

179 During the first two days of the experiment, we placed a mesh enclosure around the 180cichlid so guppies could escape easily, acclimatise, and learn about the position and 181potential danger of the predator. This mesh was removed on the third day. We visually 182monitored the amount of fish in the tanks daily. When the number of surviving fish seemed 183to have reached our target (15% of the group, ~ 30 individuals), they were captured with a 184net to be counted. If more than the desired number of survivors was counted, they were 185returned to the tank. Due to logistical constraints, the final percentage of survivors varied 186from 13 to 23% between replicates. The number of weeks fish were in the treatment varied
187from 3 to 7 weeks for males, and from 11 to 14 weeks for females. See Supplementary
188material Section 1 for details. Because one predator showed signs of stress (hiding and very
189little feeding), it was replaced with another cichlid after 28 days. Fish were kept at 24°C
190under a 12:12 light:dark cycle and fed flake food daily and freshly hatched brine shrimp at
191least three times per week.

192

193Reproductive traits

194

195Once a replicate for each sex was completed, a male and a female from the same treatment
196(control or predation) were paired up to produce fry. Individuals were placed in a 4L tank
197with a mesh in the front to allow fry to shelter. Tanks were then checked daily (or every
198other day due to logistical constraints) and the number of fry and date of birth was noted.
199Fish were allowed to breed between 15 and 24 weeks. Note that the variation on time
200allowed to breed depended on the number of fry produced, as a minimum number of
201offspring were needed for another experiment. After breeding, fish were euthanised with an
202overdose of benzocaine and fixed with 4% formalin in buffered phosphate buffer saline
203(PBS) solution.

204

205Body size and brain measurements

206

207To test for differences in body size between treatments, photographs of fish were taken
208before and after the predation event by placing 30 fish at a time in a 4L tank with 2cm of
209water and photographed from above with a Nikon DSLR camera. Images were then
210measured using Image J software (Abramoff *et al.* 2004) to obtain individual's standard
211length (from the tip of the snout to the end of the caudal peduncle).

212

213 To test for differences in relative brain size and relative brain regions, 12 individuals
214from each sex, replicate, and treatment group (N=144) were randomly selected and their
215standard length was measured to the nearest 0.01 mm using a digital calliper. Fish were
216then placed under a dissection microscope (Leica MZFLIII) and brains dissected and stored in
217PBS. To quantify brain region volumes, brains were photographed from the dorsal, ventral,
218left, and right side under the dissection microscope with an attached digital camera (Leica
219DFC 490) and then weighed to the nearest 0.01 mg (VWR SM-425i-C precision scale). The 220length, width, and height of the olfactory bulbs, telencephalon, optic tectum, hypothalamus, 221cerebellum, and dorsal medulla were then measured using Image J following (Kotrschal et 222al. 2012). See Supplementary material Section 7.2.1 for details. The volume of each of the

223brain regions was estimated using: $V=(L \times W \times H)\frac{\pi}{6}$. All body size and brain

224measurements were taken blind to treatment.

225

226Statistical analyses

227

228We first tested whether the likelihood of producing offspring varied between survivor fish 229from the predation treatment and control fish using a generalised linear model (GLM, 230binomial distribution) using *lme4* (Bates *et al.* 2015), with treatment and replicate as 231predictors. We then evaluated whether the number of offspring differed between 232treatments using a GLM (Poisson distribution) for both the first brood and when including all 233broods. We tested the first brood separately as we expected an immediate response after 234fish had been exposed to the predator (or its cues for the control fish). To test whether 235interbrood interval differed between the treatments we ran two linear models with the 236same predictors as above. We ran one for the time to produce the first brood, and another 237one for interbrood interval for fish that had more than one brood. Note that for interbrood 238interval we present models where time between broods was log transformed as this 239improved normality. When we tested the likelihood of producing offspring across all broods, 240the number of broods was also added as a predictor, where a maximum of four was 241included as pairs that produced more than four were very unlikely.

242

243 To test whether body size before and after the predation event differed between 244treatments we calculated the standardised mean difference for each group (SMD, Hedges & 245Olkin 1985), which is the difference in body size between the time fish started the 246experiment and when they finished the experiment. Note that fish were not individually 247marked, and that sample sizes were the same in the control treatment before and after the 248experiment but different in the predation treatment as at the end of the experiment we 249could only measure survivors. SMDs for each observation with their associated variances
250were used as dependant variables in a random meta-regression model using the *metaphor*
251package (Viechtbauer 2010). We included treatment and replicate as fixed effects, and
252observation ID as a random effect. We ran these models separately for males and females as
253sex differences in guppies are considerable.

254

255 To test whether female reproductive success was associated with body size, we used
256a subsample of 72 females and evaluated whether the number of offspring differed
257between treatments using a GLM (Poisson distribution), with body size (log-transfomed),
258treatment, replicate, and total number of broods as predictors. We note that because
259individuals were not individually marked when fish went into the treatment, the body size
260measurements were obtained when dissecting the females for brain measurements.

261

262 To test for differences in relative brain size and relative brain regions between
263treatments, we log-transformed body size (mm), brain weight (mg), and brain region volume
264(mm³) before the analyses. These analyses were fitted separately for males and females as
265treatment duration (the time in the predator tank) varied between the sexes (est males = -
26651, se= 10.970, F = 21.615, p = 0.009), and the highly pronounced sexual dimorphisms make
267sex comparisons not too meaningful.

268

269 To test for differences in relative brain size, we ran a linear model for brain weight,
270with the predictors of treatment, body size, replicate, and all two-way interactions. Log-
271body size was fitted as a covariate to account for allometry and focus on treatment
272differences in *relative* brain size. We checked whether replicate interacted with treatments
273or allometries, but as these were not parameters of biological interest we removed non-
274significant interactions from the model (all p>0.2).

275

276 To test for an effect of predation treatment on relative brain region volumes, we
277fitted a multivariate linear model for each sex with the predictors of treatment, brain
278weight, replicate, and all two-way interactions. All interactions in this model were non-
279significant and uninformative for our research question and therefore removed (all p>0.9).
280We also ran univariate models for each brain region (details for those models and results
281are available in the Supplementary Material). All statistical analyses were performed in R
282v.3.6.1 (R Development Core Team 2012) and model terms were tested for significance
283using the ANOVA function in the car package (Fox & Weisberg 2011) specifying Type III Wald
284chi-square tests. The model results and code are available in the Supplementary Material –
285https://osf.io/42cpt/?view_only=540a73672a594597b51d9345d9fe1a1.

286

## 287 Results

288

289 *Effects on reproductive traits*

290

291 Surviving fish from the predation treatment were more likely to breed than control fish
292 (97% vs 90%, est = 1.288, se= 0.686, $\chi^2$ = 4.072, p = 0.044), which was consistent across the
293 three replicates (Anova replicate: $\chi^2$ = 0.708, p = 0.702). Across all broods, survivors
294 produced more offspring than controls (est predation treatment = 0.123, se= 0.055, $\chi^2$ =
295 55.018, p = 0.025), with a non-significant tendency to vary between replicates ($\chi^2$ = 5.863, p =
296 0.053). The number of offspring also differed between broods ($\chi^2$ = 36.322, p < 0.001), with
297 an increasing number of offspring in broods two and three. This tendency of survivors
298 producing more fry appeared consistent when considering the first brood only, albeit non-
299 significant likely due to lower power (est predation treatment = 0.128, se= 0.067, $\chi^2$ = 3.645,
300 p = 0.056). The number of offspring differed between replicates ($\chi^2$ = 22.002, p < 0.001). The
301 time to produce a first brood and the interbrood interval when considering all broods did
302 not differ between treatments ($\chi^2$ = 0.158, p = 0.691; $\chi^2$ = 3.695, p = 0.054, respectively).
303 However, these varied between replicates ($\chi^2$ = 14.547, p < 0.001; $\chi^2$ = 23.399, p < 0.001,
304 respectively). Interbrood interval differed between broods ($\chi^2$ = 308.610, p < 0.001), with fish
305 producing broods more frequently with time.

306

307 *Effects on body size*

308

309 We found sex-dependent effects of predation on body size. In females, body size differed
310 between treatments, with surviving females being larger than control females (est = 1.322,
311 s.e. = 0.505, Z = 2.619 p = 0.008; Fig. 2a; Suppl. 5.2.2 & 5.2.3). The magnitude of this
312difference in body size varied between replicates (est replicate 2 = 1.094, s.e. = 0.602, Z = 3131.817, p = 0.069; est replicate 3 = 2.673, s.e. = 0.625, Z = 4.277, p < 0.001).

314In males, body size between survivors and controls did not differ (est = 0.303, s.e. = 0.187, Z = 315= 1.622, p = 0.105; Fig. 2b; Suppl. 5.2.2 & 5.2.4), nor was it affected by replicate (Suppl. 3165.2.4).

317

<figure><img src="image_4.png" /></figure>

318

319

320**Figure 2.** Raw data for mean body size ± SD for a) females and b) males for control (open symbols) and predation (filled symbols) treatment fish. Three replicates were measured for control and predation fish before (T₀) and after (T₁) the predation event. Each replicate is shown with a different symbol.

324

325Linking body size and reproductive traits

326

327Bigger females had more offspring (body size est= 1.397 s.e. = 0.478, χ² = 8.572, p = 0.003; 328Suppl. 6), although there was no difference in the allometry between the treatments (est= 3290.067, s.e. = 0.058, χ² = 1.343, p = 0.246; Suppl. 6). The total number of offspring produced
330differered between replicates ($\chi^2$ = 12.418, p = 0.002), but in the same direction across 331replicates. As expected, females having more broods had more offspring (est= 0.523, s.e. = 3320.039, $\chi^2$ = 247.5556, p < 0.001; Suppl. 6).

333

334Effects on relative brain size

335

336In females, we found that predation impacted the allometry between brain weight and body size, with surviving females having relatively larger brains than controls at large body sizes. 337and relatively smaller brains at smaller body sizes (treatment × body size est = 0.825, s.e. = 3390.260, $F_{1,66}$= 19.051, p = 0.002; Fig. 3a). Note that at smaller to intermediate sizes, the 340difference between surviving females and controls was not as large (Fig. 3a). These results 341varied between replicates ($F_{2,66}$ = 17.378, p < 0.001). In males, we found no difference in the 342allometry between brain weight and body size between treatment groups (treatment × 343body size est = 0.328, s.e. = 0.327, $F_{1,66}$= 1.006, p = 0.319; Fig. 3b). Additionally, overall 344relative brain size was similar between treatments (treatment est = -0.871, s.e. = 0.902, 345$F_{1,66}$ = 0.933, p = 0.338; Suppl. Section7). We observed a body size effect on relative brain 346independent of treatment; larger males had relative bigger brains (body size est = 0.807, s.e. 347= 0.239, $F_{1,66}$= 11.429, p = 0.001; Suppl. Section7). These results varied between replicates 348($F_{2,66}$ = 3.672, p = 0.031), but note there was no replicate by treatment interaction.

349

350Effects on relative brain region size

351

352The multivariate analyses of brain region volumes (olfactory bulb, telencephalon, optic 353tectum, hypothalamus, cerebellum, and dorsal medulla) for females and for males after 354accounting for the allometries associated with brain weight (females: $F_{6,62}$ = 25.030, p < 3550.001; males: $F_{6,62}$ = 13.449, p < 0.001) revealed no effect of treatment on relative brain 356region volumes for either sex (females: $F_{6,62}$ = 0.479, p = 0.821; males: $F_{6,62}$ = 1.130, p = 3570.356). Univariate models of each brain region supported the lack of differences and are 358available at the Suppl. Section 7.

359
<figure><img src="image_5.png" /><figcaption>362**Figure 3.** Differences in brain size between the control (grey circles) and predation (purple triangles) treatments for a) females and b) males. Model predictions are plotted as the best fit line.</figcaption></figure>

366**Discussion**

367
368We compared fish that survived a predation event (survivors) to fish that were exposed to 369olfactory and visual predator cues only (controls), and found that survivors were more likely 370to reproduce and had overall more offspring in an equal number of broods than controls.
371Importantly, survivor females were bigger and showed a body-size-dependent difference in 372brain size compared to controls. There were no such differences in males associated with 373the treatments; and in both sexes, relative brain region volumes were similar between the 374two treatment groups. Our study provides experimental evidence on the impacts of direct 375predation on brain size and reproductive output.
377 We assessed brain anatomy in adult guppies exposed to strong predation and in 378control fish where visual and olfactory cues were provided, in an effort to account for 379phenotypic plasticity to test for an effect of selection. Given the nature of the experiment, 380several weeks passed between the predation event and the assessment of body size and 381brain anatomy, and so we cannot fully disentangle the effects of natural selection and 382phenotypic plasticity. Did non-random predation according to female brain and body size 383lead to our results, or did the period of actual predation threat trigger alternative 384developmental pathways? The literature provides evidence for both those mechanisms. For 385instance, life history traits, growth, and brain anatomy have all been shown to respond 386rapidly to natural selection (Roff 1992; Stearns 1992; de Winter & Oxnard 2001), and adult 387guppies show plasticity in all three traits (Reznick 1990; Reznick & Yang 1993; Burns & Rodd 3882008). More importantly, plasticity and evolution/natural selection may not necessarily work 389in the same direction. Plasticity for instance could lead to lower somatic growth on body 390size, while the natural selection could increase somatic growth. Evidence suggests however, 391that at least for brain size in guppies, both plasticity and natural selection seem to be in the 392same direction (Reddon et al. 2018). Partitioning evolutionary from plastic effects was not 393the aim of this study. Yet, the strength of our approach is that it revealed, independently of 394ecological confounding factors present in the wild, how life history decisions and brain 395anatomy 'depend' on an episode of predation. Moreover, this event occurred during 396adulthood, be it via non-random predation or divergent development. In the following we 397offer several non-mutually exclusive explanations for our results, including the apparent lack 398of response in male traits.

399

400 The body size difference in survivor and control females that we found can be 401explained by size-selective predation if the pike cichlid preferentially preyed on smaller 402females. Although 'high predation' guppies are typically smaller in body size than 'low 403predation' fish (Reznick et al. 2001; Reddon et al. 2018), this effect is likely due to the strong 404selection for maturing early and at smaller size in risky habitats rather than due to size- 405selective predation (Reznick 1990; Reznick et al. 1996). In fact, the relationship between 406body size and predation seems complex. For instance, males guppies from high predation 407sites in the wild are smaller than those from low predation sites, but such differences are 408not apparent for female body size (Reddon et al. 2018). Yet, males exposed to predation risk
409cues in the laboratory during development were bigger than those exposed to control cues, 410with female body size showing no response (Reddon et al. 2018). In another study, a 411comparison of a laboratory-born generation of guppies from high and low predation 412localities showed that females from high-predation sites grew faster than those from low- 413predation sites (Arendt & Reznick 2005). While *Crenicichla cichlids* often prefer larger prey 414(Johansson et al. 2004), predation across prey sizes by cichlids, rather than selective 415predation on large guppies has also been described (Mattingly & Butler 1994). Moreover, 416other predators present in wild populations target smaller size classes (Rodd & Reznick 4171997). In our case, smaller females may have been easier to catch than larger ones by the 418cichlid, since body size is a key factor influencing swimming parameters (Rubio-Gracia et al. 4192020), and in our study females were virgin and so were not compromised by swimming 420performance (Banet et al. 2016). This hypothesis may also explain why in our study males 421were predated faster than females. Cichlids would have required more (small) males than 422(large) females to reach saturation (as seen by Mattingly & Butler 1994), thus explaining the 423increased consumption rate of males. The lack of body size differences in males between 424the treatments may be explained by the fact that male guppies show almost determinate 425growth with little additional growth after maturation, while females continue to grow 426substantially during adulthood (Constantz 1989; Arendt & Reznick 2005). Due to the large 427number of animals necessary for this experiment, breeding all animals took several months. 428This means that, while all animals were adults, they were between four and seven months 429old. This produced a larger range in female compared to male body size and hence a 430stronger potential to detect size-selective mortality. Alternatively, in a scenario relying on 431phenotypic plasticity, survivor females may have simply grown faster during the time in the 432predation treatment tank. This could be due to the fact that controls and survivors, although 433designed to only differ in the potential for physical contact between guppies and pike 434cichlid, also differed in the space they could utilize. Controls were restricted to smaller tanks 435within the predator tanks whereas survivors could use the larger tank. As growth in fish can 436depend on tank size (Espmark et al. 2017), this may have contributed to our results. While 437the lacking body size difference in males may indicate such a scenario is unlikely, the near- 438determinate male growth explained above may render this counter-argument invalid. It is 439hence evident that dedicated growth experiments in the set up used here, but without a
440predator, are needed to conclusively clarify the mechanism by which females that survive
441predation are larger than controls.

442

443 The brains of female guppies were affected by the predation treatment. This
444resembles results from a previous study where a large-scale survival experiment under
445semi-natural conditions showed that relative brain size determined survival in females, but
446not in males (Kotrschal et al. 2015). However, the results we report here deviate from this
447previous study and from our predictions as we did not find a clear effect of predation on
448relative brain size. Instead, predation changed the slope of the regression between female
449brain and body size, which resulted in relatively smaller brains in small survivors but
450relatively larger brains in large survivors, compared to controls. This was unexpected but
451interesting, as it suggests that brain-size derived cognitive advantages (e.g. Kotrschal et al.
4522013; Benson-Amram et al. 2016; Buechel et al. 2016) may be size-dependent under
453predation pressure. Relatively larger brains might indeed provide cognitive advantages if
454indeed a relatively larger brain helps to avoid getting eaten (Moller & Erritzoe 2014), but
455may also be costly to maintain. Thus, differential selection of predators (e.g. Johansson et
456al. 2004), or different escape strategies used by small and large fish may be causing the
457allometric effects we found. Such body size-dependent effect of predation on brain size has
458been shown in male killifish when comparing high predation sites versus sites with no
459predators (Dunlap et al. 2019), but seems absent in other studies relating predation
460pressure to brain size (Walsh et al. 2016; Reddon et al. 2018; Mitchell et al. 2020). This may
461be due to a mix of differently-sized predators in the wild, either across predatory species or
462from changes with age/size of gape-size limited predators like Crenicichla.

463

464 Variation in specific brain regions may play a fundamental role in how animals
465respond to their environment, and indeed it has been shown that changes in specific brain
466regions can be associated with predation risk (Joyce & Brown 2020). Despite predicting
467differences between treatments on specific brain regions such as the telencephalon and
468optic tectum as they are associated with learning and motor functions (Broglio et al. 2003),
469we found no such effect. There is indeed contradictory evidence on the link between
470predation and brain size (Gonda et al. 2009; Kotrschal et al. 2015; Walsh et al. 2016; Beston
471et al. 2017). Indirect ecological consequences such as density, or food availability were not
472expected to influence our results, and these have likely contributed to both negative and
473positive results in previous studies, highlighting the multiple mechanisms by which
474predation may shape the brain and its regions' size.

475

476 We found a higher likelihood to reproduce and higher reproductive output of 477surviving females compared to controls. Our results support, at least partially, an increased 478reproductive effort under high predation pressure. This may be a direct consequence of the 479body size differences in females of those groups, as body size is a strong predictor of 480reproductive output in fish (Lim et al. 2014). However, high mortality rates in guppy 481localities predated by the pike cichlid have been associated with a higher investment in 482reproduction (Reznick 1990; Reznick et al. 1996). It is possible that we did not find more 483differences in reproductive effort between treatments because the risk of predation was no 484longer present when fish were allowed to breed. This is because the costs of behaviours 485related to acquiring a mate, conspicuous displays, or the costs of gravid females having 486lower agility (Magnhagen 1991) were removed when fish were moved to the breeding 487tanks. Interestingly, larger surviving females had bigger brains, and although we cannot 488disentangle fully male and female contribution to reproductive effort, it seems like large 489females with larger brains do not exhibit a larger brain investment at the cost of 490reproductive effort.

491

492 Predation may lead to differences in brain size across species (Moller & Erritzoe 4932014), and even to a large degree of variation among similar populations on the same 494species (Burns & Rodd 2008; Walsh et al. 2016; Kotrschal et al. 2017a). Here we show that 495predation impacts brain size likely through direct lethal effects, and uncover a sex- and 496body-size dependent effect. Our results highlight the need to explore the complex effect of 497predation on brain evolution further, and ultimately incorporate cognitive assays to 498understand whether individuals evolve larger brains and better learning capacities to avoid 499predators.

500

501**Acknowledgments**

502
503We thank Eduardo Nila Espinosa and Jérémy Lefèvre for help with animal husbandry.

504

505**Funding**

506

507This research was funded by the Swedish Research Council (2017-04957 to A.K.). C.V.P was

508supported by a Carl Tryggers Stiftelse Postdoctoral stipend (CTS18:205 to A.K.).

509

510**Conflicts of interest**

511

512We declare we have no conflict of interest.

513

514**Ethics approval**

515

516This research was approved by the Stockholm Ethical Board (Dnr: 11627-2019).

517

518**Availability of data and code**

519

520Data and code are available at https://osf.io/42cpt/?

521view_only=540a73672a594597b51d9345d9fe1a1.

522

523**Authors' contributions**

524

525R.V-T and A.K conceived the study, R.V-T collected the data aided by D.J.M and C.V.P. R.V-T

526analysed the data and wrote the first version of the manuscript. All authors provided

527feedback on earlier versions of the manuscript.

528

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