Discussion
Our work adds new evidence to the increasing bulk of papers reporting that individuals sharing a common environment can exhibit consistent differences in resource-utilization niche (Bolnick et al. 2003), challenging the traditional idea that individuals within a population are all ecologically equivalent (Colwell et al. 1971). More importantly, while the vast majority of cases of individual specialization document realized individual specialization (sensu Bolnick et al. , 2003a), our experimental demonstration that individuals exposed to similar conditions may differ in food preferences provides a more mechanistic understanding for the existence of niche variation among individuals.
The existence of individual specialization in feral pigeons was first suggested by Giraldeau and Lefebvre (1985). These authors analysed the crop contents of individuals baited with a mixture of seeds, and noticed a strong degree of individual variation in the seeds consumed. Our common garden experiments using individuals from two ecologically distinct populations not only support their finding, but also suggest that specializations reflect consistent differences among individuals in food preferences. Our analyses further reveal that individual specialization was not associated with age, sex or morphological traits like body size and beak morphology. Instead, individuals seemed to use different optimization criteria in their choice of foods, some favouring compounds that provide fast energy while others prefer compounds with higher energy but more difficult to break down.
Resource specialization was only consistent over short time spans (days) but did not last for longer periods (one year). Short-term consistencies are expected if preferences are driven by the physiological state of individuals. Although individuals used different optimization criteria in resource-choice, we did not find evidence that individuals in worse body condition consumed larger amounts of food or foods that provided more rapid energy. Animals may improve foraging efficiency by developing searching images for a few food types (Pietrewicz & Kamil 1979), yet this also does not seem a likely explanation for specialization because in our assays food types were provided in separated patches.
Given the low stability of food preferences, it is unsurprising that we found little evidence for additive genetic effects. Our estimations of the heritable component of food preferences were always low, even when they may include maternal effects. Our analyses neither indicated that preferences were linked to heritable state variables, such as body size and beak morphology. The alternative that preferences were learned from their parents also seem unlikely. First, individuals born in captivity were raised under similar conditions, and hence their early food experiences were similar. Second, the cross-fostering experiment showed a low effect of the common rearing environment on food preferences, suggesting that diet was little influenced by vertical transmission of information from the parents.
The fact that food preferences were little constrained by genetic architecture and/or learning was reflected in their plastic nature. Preferences of individuals did not only change after one year in captivity, but also tended to converge toward similar resources. These adjustments did not seem to reflect adaptive plasticity, as suggests the low heritability of individuals’ responsiveness between the short and long-term assays. However, a role for learning is suggested in the tendency of individuals to converge over time toward a diet richer in calories and proteins. If niche shifts were driven by random processes, we would not expect this convergence.
Regardless of the cause, the finding that food preferences are highly plastic is important because it challenges a major mechanism that may generate and maintain niche specialization within a population. In our study, plastic adjustments of food preferences led to a substantial decrease in the degree of food specialization within the population, either as a result of an expansion of the niche of individuals or a reduction of population niche breadth. Still, the finding that variation in food preferences may easily emerge among individuals subject to similar conditions is relevant because initial decisions regarding what to eat may largely shape the future diet in the wild. Early preferences in the use of certain foods can give rise to different experiences that may reinforce (if positive) the initial preferences (Tinker et al. 2009). Given that foraging proficiency often increases with experience (i.e., learning), initial differences in food preferences among individuals may limit the use of alternative foods that require to learn new foraging skills (Partridge & Green 1987). Variation in resource preferences may also be maintained by emotional responses, like the aversion to explore and incorporate novel foods once the individual reaches maturity (Greenberg & Mettke-hofmann 2001).
We suggest that the above effects may not have been detected in our experiments for two main reasons. First, our food-choice assays were designed to measure preferences, and hence were little demanding in terms of other foraging components like searching, identifying and handling foods. This may have reduced the costs of shifting among food resources. Second, the exposure of individuals to the same stimuli for long periods may have favoured the convergence toward similar food preferences in captivity. Experiments in rodents have for instance shown that individuals raised under stable food conditions are more selective in food choice than those raised under fluctuating food conditions (Gray 1981).
Simultaneous choices between different types of exactly the same amount of food must hardly occur in nature. Rather, resource supplies are likely to vary in time and space, exposing individuals to different experiences and uncertainties regarding food. Moreover, the need of searching, identifying, and handling foods makes it unlikely that individuals are able to exploit all food types efficiently (Price 1987), particularly when this requires advanced cognition (Tinker et al.2009). The costs of acquiring resource information may also force individuals to make decisions based on the perceived rather than actual perceptions of risk (Blumstein 2006; Lamanna & Martin 2016). Under these circumstances, the retention of initial resource preferences through learning trade-offs and neophobic responses is more plausible. In sea otters (Enhydra lutris ), resource specialization driven by reduced food availability is not associated with morphological or genetic differences between individuals, but it appears to reflect limitations in their capacity to learn the skills needed to efficiently exploit different preys (Tinker et al. 2009). 
Although both laboratory and field studies may provide important insight into the origin and maintenance of resource specialization, each of these approaches is limited in scope.  Resource preferences are easier to study in common garden experiments. However, the conditions individuals find in captivity may largely differ from those they encounter in nature. Thus, the integration of laboratory and field studies may largely broaden our understanding of the role of resource preferences in shaping resource specialization within animal populations.
Acknowledgments. We thank Louis Lefebvre for past discussions about pigeon’s behaviour, and Domingo Rodriguez Teijeiro and the staff of Pedro Pons for allowing us to conduct the experiments within their facilities. This project was funded by grants from the Spanish Government CGL2013-47448-P and CGL2017-90033-P. OL and CGL were supported, respectively, by FPI (BES2008-007095) and AGAUR (FI-DGR 2009) grants.
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