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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SUPPORTING INFORMATION
Additional supporting information may be found online in the Supporting
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