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Increased brain size has been associated with greater sensitivity to environmental context, but this flexibility is potentially costly as sampling the environment is time and energy consuming and may even increase the risk of predation. However, these potential trade-offs remain virtually unexplored in natural populations. We hypothesized that large brain size is 1 beneficial under challenging conditions and allows better matching of antipredator responses to the actual threat by predators and 2 associated with thorough risk assessment, which can be costly under benign conditions.
To test these hypotheses, we examined the relationship between relative head volume, reproductive decisions, and fitness components in female common eiders Somateria mollissima under variable predation risk and breeding phenologies. This species is ideal for this purpose because of highly variable predation pressure and a distinct seasonal decline in reproductive success.
The results were consistent with our hypotheses. Second, large-headed females, but not small-headed ones, took a shorter time to form antipredator brood-rearing coalitions in more dangerous years. Thus, predation risk and annual phenology may exert temporally fluctuating selection on relative head size, maintaining intraspecific variation in cognitive ability.
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Information is a crucial currency in animal decision making because it provides an insurance against the uncertainty inherent to natural systems, allowing individuals to respond flexibly to changing conditions Dall et al. It is therefore puzzling why individuals commonly vary in how flexibly they respond to environmental cues Sih and Del Guidice ; Mathot and Dall However, responding flexibly to changing environmental conditions is not cost-free.
Acquiring information typically improves the accuracy of decisions Abbott and Sherratt , but it also takes time away from other fitness-related activities such as foraging or reproduction and may also expose organisms to increased risk of predation Trimmer et al.
However, these potential trade-offs remain poorly understood in natural populations, reflecting the lack of studies investigating the fitness consequences of individual differences in cognitive abilities in the wild Thornton and Lukas ; Morand-Ferron et al. A large brain relative to body size allows animals to process, integrate, and store more information about their environment, which may facilitate more flexible behavioral responses to environmental stimuli Clutton-Brock and Harvey ; Lefebvre et al.
However, in addition to the neural costs of evolving a larger brain Laughlin et al. Empirical evidence suggests that such speed—accuracy trade-offs in decision making are relevant in contexts involving relatively complex cognitive tasks, such as predator—prey interactions Burns and Rodd ; Ings and Chittka and nest-site selection Franks et al.
Individuals with relatively small brains may not possess the necessary cognitive capacity to gain as much from additional sampling Sih and Del Guidice , and so they may be inclined to place more emphasis on short-term gains such as limiting the costs of time expenditure Trimmer et al. One way to speed up the decision process is to form inflexible routines and hence to pay less attention to changes in the environment Sih and Del Guidice Although fast decision making may result in less accurate decisions, this strategy may be favored in benign or stable environments Sih and Del Guidice , where excessive sensitivity to external stimuli may compromise foraging or reproductive opportunities Chittka et al.
Conversely, because harsh or challenging conditions may tip the balance in favor of decision accuracy over speed, cognitive ability, and hence increased relative brain size, may be selected for in severe or challenging environments e. However, the fitness consequences of intraspecific brain size variation have not yet been assessed in wild populations subject to natural variation in environmental harshness. This is because, on the one hand, the potential benefits of accurately assessing predation risk can be very high.
For example, nest predation explains a large part of the variation in avian reproductive success Ricklefs Hence, temporally fluctuating selection could promote the maintenance of variation in relative brain size.
Here, we heed recent calls for exploring individual variation in cognitive performance under natural conditions Cole et al. The common eider is long lived, indicating that it can gain great potential benefits from information acquisition see Deaner et al.
After hatching of their brood, brood-tending females in this facultatively social species with uniparental female care arrive at sea and engage in intense social interactions. The purpose of these interactions is to decide whether and with whom to cooperate to rear young. Coalition formation is primarily driven by the need to minimize predation risk Jaatinen et al.
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We formulated 2 hypotheses based on the above considerations: 1 large-brained individuals may be better at assessing predation risk Kotrschal et al. To test these hypotheses, we used 5 years of data on nest success and timing of breeding of known female common eiders and the time it took them to form enduring brood-rearing coalitions under variable predation risk. The common eider is ideal for this purpose because antipredator adaptations are likely to be at a high premium.
From the perspective of a breeding female, avoidance of predation on eggs cannot be distinguished from avoidance of predation on themselves, and therefore qualitative differences between adaptations against these forms of predation are unlikely. Female common eiders were captured by hand nets predominantly during the end of incubation to minimize nest desertion Bolduc and Guillemette The time spent on each island during a bout of female capture was also held to a minimum to decrease disturbance.
On capture, the females were weighed to the nearest 5g , measured for structural size length of the radius—ulna to the nearest 1mm and head size width, breadth, and height to the nearest 0. As a proxy for brain size, we used head volume, that is, the product of the head measurements to the nearest 0. The repeatability of head volume was calculated using a linear mixed model LMM and extracting the intraclass correlation coefficient using female identity as a random effect Wolak et al.
This repeatability, 0.
This allowed us to extend the available data set to —, from which we had data on breeding biology but lacked head volume measurements. Thus, we are confident that we obtained representative measurements of individual head volume, regardless of whether it was measured in the same year s as the breeding biology data or in the 2 years after collecting these data. We used mean head volumes for birds for which repeated measures were available. Nests were visited at the estimated time of hatching in order to measure tarsus length to the nearest 0.
Determining hatching success was straightforward even in cases when the brood had already left the nest. This was done by regressing the log-transformed projected weight at hatching against the log-transformed radius—ulna length and using the standardized residuals as a condition index data from all years were pooled to obtain a global index. The projected weight at hatching was obtained by subtracting the expected weight loss by calculating the expected number of days before hatching, based on incubation stage from the body weight measured at capture.
The median hatch date was calculated based on all trapped females that successfully hatched a brood in each year.
We quantified annual predation risk as the number of killed females found per censused nest during the incubation period Jaatinen et al. The annual predation index PI ranged from 3. Using this proxy for quantifying predation risk is justified because females and not the young make partner choice decisions; these decisions are made soon on arrival at sea, and female predation mortality during incubation demonstrably carries over to affect female grouping decisions made after incubation is completed Jaatinen et al.
These features make this index particularly promising for revealing how cognitive processes are related to predation risk.
Active predation was the primary cause of mortality of females. Thus, postmortem examination of carcasses in the field often revealed typical signs of predation e. Almost invariably, we also found a destroyed nest in the immediate vicinity of the carcass, indicating that predation occurred while the female was actively incubating. Annual distributions of mean head volume of common eider females losing their nest to predation expected under random predation susceptibility with respect to head volume iterations.
The vertical dashed lines illustrate the actual observed mean head volumes of females with depredated nests. In panels a—e , the values next to the lines represent, from the top: annual PI see Materials and Methods for details , observed mean head volume of females with depredated nests, 1-tailed P value see Materials and Methods , and annual median hatch date.
In panel f , the values next to the line represent, from the top: average head volume of females with depredated nests in —, and 1-tailed P value.
We conducted permutation tests to assess head volume— and structural size—specific susceptibility to nest depredation. The latter permutation test was done to ensure that any observed patterns in head volume—specific susceptibility to nest depredation could be attributed to differences in head volume per se rather than to differences in structural size radius—ulna length. In these year-specific tests, the annual number of observed nest depredation events was randomly assigned to females regardless of head volume and radius—ulna length.
By repeating this procedure times, we obtained simulated annual null distributions of average head volumes and radius—ulna lengths of females representing random nest depredation with respect to head volume and structural size, respectively. We then compared these expected distributions with the observed average head volumes and radius—ulna lengths of females whose nests were actually depredated in each year.
A 1-tailed P value was obtained as the proportion of the null distribution that is at least as extreme on either tail than the observed value.
For example, a value of 0. The hypothesis of head size—specific responsiveness to predation risk was tested using a LMM, where the time taken to form an enduring brood-rearing coalition was explained by head volume, annual PI, female group size, breeding experience, body condition, the availability of potential coalition partners, and their 2-way interactions. The model was fitted using maximum likelihood, and female identity was used as a random effect to correct for potential pseudoreplication arising from repeated observations of the same females in different years.
To study the connection between timing of breeding and head size, we constructed a LMM, where hatch date was explained by head volume, breeding experience, body condition, year, and their 2-way interactions. The model was fitted using restricted maximum likelihood, and female identity was used as a random effect to correct for potential pseudoreplication arising from repeated observations of the same females in different years. All analyses were conducted using the software R 3.
The LMMs were reduced by sequential removal of nonsignificant variables, except for radius—ulna length that was always forced into all final models large females are expected to have larger heads. Stepwise backward elimination has been criticized in favor of approaches based on information theory and model averaging Whittingham et al. However, model averaging was not a feasible alternative, due to the need to consider a relatively large number of variables compared to sample size.
The residuals of both LMMs adhered to the assumption of normality. Significant interactions were graphically illustrated using simple slope analysis Aiken and West , by estimating the slope of the independent variable on the dependent variable at high 75th percentile , median, and low 25th percentile levels of the moderator.
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To examine the presence and degree of multicollinearity, we calculated the variance inflation factors VIF for the independent variables in the LMMs as described above. All VIFs were found to be below 1. Our first hypothesis was that large brain size would confer fitness benefits under challenging conditions and allow more accurate adjustment of antipredator responses to the actual level of threat.
Indeed, the permutation tests showed that females with depredated nests had a significantly smaller head volume than expected by chance in , the year with the highest predation rate on females Figure 1b.
Thus, the time taken to form a coalition was reduced among individuals with large heads under high risk of predation, whereas it was prolonged in such individuals under low risk of predation Figure 2.
The time taken to form enduring brood-rearing coalitions is related to head volume, but this effect is modulated by annual predation risk.
Under low risk of predation 25th percentile, solid line L, black dots , larger-headed females take more time to establish enduring coalitions than smaller-headed females.
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Under high risk of predation 75th percentile, dotted line H, open circles , the opposite is true, that is, larger-headed females are faster at forming coalitions, indicating an adaptive antipredator response through the dilution of predation risk offered by the ducklings of coalition partners. Under intermediate predation risk median, dashed line M, gray circles , the time taken to form coalitions is essentially unrelated to female head volume.
Each dot represents 1 female in a given year. Our second hypothesis was that large-brained individuals employ a thorough risk-assessment strategy, which can be costly under benign conditions. Furthermore, the permutation tests showed that females with depredated nests had a significantly larger head volume than expected by chance in , a year characterized by the earliest annual nesting phenology and relatively minor predation pressure on females Figure 1a.
The observed nonrandomness in head size—specific nest predation susceptibility was not a by-product of structural size.
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Thus, the year-specific permutation tests regarding radius—ulna length showed that nest predation was random with respect to radius—ulna length in all years; the corresponding P values ranged from 0.
Thus, nests of large-headed females were less likely to be depredated when predation pressure on females was the highest year ; Figure 1b.
Indeed, the year was notorious for exceptionally high predation pressure on nests and incubating females particularly by mammalian predators Ekroos et al.
The cognitive buffer hypothesis has rarely, if ever, been assessed before at the individual level in natural populations. However, at the population level, a harsher and more unpredictable climate can demonstrably select for improved spatial memory and a larger hippocampus, as shown in black-capped chickadees Poecile atricapilla Roth and Pravosudov Large-headed female common eiders also appeared better informed about predation threats after completing their incubation.
Second, the time it took them to establish partnerships responded more strongly to annual variation in predation risk than that of small-headed females Figure 2.
This latter observation agrees with the hypothesis that increased brain size is associated with more flexible behavior although so far most of the available evidence for the behavioral flexibility hypothesis comes from comparative studies between species Sol et al.
Consistent with our second hypothesis that the potentially greater responsiveness of large-brained individuals to environmental stimuli may incur costs under benign conditions, because of time or energy constraints of sampling and of maintaining the required sensory machinery Wolf et al.
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Although cognitive ability may trade-off with competitive ability Cole and Quinn , female competition is unlikely responsible for the observed delay in nest-site selection. A late onset of breeding can be costly in this species in terms of reduced fecundity Descamps et al.