When organisms respond behaviorally to a stimulus, they exhibit plasticity, but some individuals respond to the same stimulus consistently differently than others, thereby also exhibiting personality ...differences. Parent house sparrows express individual differences in how often they feed offspring and how that feeding rate changes with nestling age. Mean feeding rate and its slope with respect to nestling age were positively correlated at median nestling ages but not at hatching, indicating that individuality is primarily in plasticity. Individual differences could arise because of (1) interactions between environmental variables, (2) differences in underlying state or “quality,” or (3) differences in the ability to update cues of changing nestling demand. Individual slopes were modestly repeatable across breeding attempts, hinting at the likely action of additional environmental variables, but only brood size was important. I also found few correlates suggesting quality differences. I used short-term brood size manipulations at two nestling ages to test divergent predictions between the three hypotheses. The pattern of correlations between response to the manipulation and individual slope did not fit any single hypothesis. Patterns of sparrow parental care reveal that personality and plasticity are not cleanly separable, and their biology is likely intertwined. New thinking may be needed about the factors parents use in decisions about care and the relevant fitness consequences.
ABSTRACT
Phenotypes vary hierarchically among taxa and populations, among genotypes within populations, among individuals within genotypes, and also within individuals for repeatedly expressed, ...labile phenotypic traits. This hierarchy produces some fundamental challenges to clearly defining biological phenomena and constructing a consistent explanatory framework. We use a heuristic statistical model to explore two consequences of this hierarchy. First, although the variation existing among individuals within populations has long been of interest to evolutionary biologists, within‐individual variation has been much less emphasized. Within‐individual variance occurs when labile phenotypes (behaviour, physiology, and sometimes morphology) exhibit phenotypic plasticity or deviate from a norm‐of‐reaction within the same individual. A statistical partitioning of phenotypic variance leads us to explore an array of ideas about residual within‐individual variation. We use this approach to draw attention to additional processes that may influence within‐individual phenotypic variance, including interactions among environmental factors, ecological effects on the fitness consequences of plasticity, and various types of adaptive variance. Second, our framework for investigating variation in phenotypic variance reveals that interactions between levels of the hierarchy form the preconditions for the evolution of all types of plasticity, and we extend this idea to the residual level within individuals, where both adaptive plasticity in residuals and canalization‐like processes (stability) can evolve. With the statistical tools now available to examine heterogeneous residual variance, an array of novel questions linking phenotype to environment can be usefully addressed.
Linear mixed‐effects models are powerful tools for analysing complex datasets with repeated or clustered observations, a common data structure in ecology and evolution. Mixed‐effects models involve ...complex fitting procedures and make several assumptions, in particular about the distribution of residual and random effects. Violations of these assumptions are common in real datasets, yet it is not always clear how much these violations matter to accurate and unbiased estimation.
Here we address the consequences of violations in distributional assumptions and the impact of missing random effect components on model estimates. In particular, we evaluate the effects of skewed, bimodal and heteroscedastic random effect and residual variances, of missing random effect terms and of correlated fixed effect predictors. We focus on bias and prediction error on estimates of fixed and random effects.
Model estimates were usually robust to violations of assumptions, with the exception of slight upward biases in estimates of random effect variance if the generating distribution was bimodal but was modelled by Gaussian error distributions. Further, estimates for (random effect) components that violated distributional assumptions became less precise but remained unbiased. However, this particular problem did not affect other parameters of the model. The same pattern was found for strongly correlated fixed effects, which led to imprecise, but unbiased estimates, with uncertainty estimates reflecting imprecision.
Unmodelled sources of random effect variance had predictable effects on variance component estimates. The pattern is best viewed as a cascade of hierarchical grouping factors. Variances trickle down the hierarchy such that missing higher‐level random effect variances pool at lower levels and missing lower‐level and crossed random effect variances manifest as residual variance.
Overall, our results show remarkable robustness of mixed‐effects models that should allow researchers to use mixed‐effects models even if the distributional assumptions are objectively violated. However, this does not free researchers from careful evaluation of the model. Estimates that are based on data that show clear violations of key assumptions should be treated with caution because individual datasets might give highly imprecise estimates, even if they will be unbiased on average across datasets.
Phenotypic plasticity is a ubiquitous and necessary adaptation of organisms to variable environments, but most environments have multiple dimensions that vary. Many studies have documented plasticity ...of a trait with respect to variation in multiple environmental factors. Such multidimensional phenotypic plasticity (MDPP) exists at all levels of organismal organization, from the whole organism to within cells. This complexity in plasticity cannot be explained solely by scaling up ideas from models of unidimensional plasticity. MDPP generates new questions about the mechanism and function of plasticity and its role in speciation and population persistence. Here we review empirical and theoretical approaches to plasticity in response to multidimensional environments and we outline new opportunities along with some difficulties facing future research.
Many studies of plasticity reveal the flexibility of a trait to more than one environmental factor; these often interact to affect trait expression nonadditively.
Integration of multiple cues can underlie both simultaneous and sequential multidimensional plasticity. Such mechanisms do not require a nervous system, can involve complex molecular pathways, and may integrate across levels of organismal organization, with one factor affecting the whole organism and others producing mitigating effects locally.
Theory on multidimensional phenotypic plasticity (MDPP) reveals its potential impact but does not yet address the full fitness consequences of plasticity in response to multiple factors or the array of possible interactive effects.
MDPP has not been considered in models of plasticity and speciation, yet it may alter both the nature of speciation and the process of adaptation to rapid environmental change.
Lifetime genetic monogamy, by increasing sibling relatedness, has been proposed as an important causal factor in the evolution of altruism. Monogamy, however, could influence the subsequent evolution ...of cooperation in other ways. We present several alternative, non-mutually exclusive, evolutionary processes that could explain the correlated evolution of monogamy and cooperation. Our analysis of these possibilities reveals that many ecological or social factors can affect all three variables of Hamilton's Rule simultaneously, thus calling for a more holistic, systems-level approach to studying the evolution of social traits. This perspective reveals novel dimensions to coevolutionary relationships and provides solutions for assigning causality in complex cases of correlated social trait evolution, such as the sequential evolution of monogamy and cooperation.
Monogamy and cooperation tend to correlate in evolutionary time. Although traditionally attributed to increased sibling relatedness, a variety of factors could cause this correlation.
Monogamy and cooperation are favored by the same selective pressures and could be indirectly linked in certain environments.
Adaptations resulting from antecedent monogamy could create selective pressure for the subsequent evolution of cooperation. Ancestral adaptations to social monogamy could also provide variation in social traits that could be co-opted for cooperative traits, further contributing to the monogamy–cooperation correlation.
Coevolutionary dynamics between mating systems and social systems could yield correlations among terms in Hamilton's Rule, complicating the assignment of causality to any one term in the evolution of cooperation.
A holistic, systems-level approach is essential for understanding the correlated evolution of complicated behavioral traits, such as monogamy and cooperation.
Evolutionary path analyses should yield tractable methodological solutions for testing causality in complex evolutionary relationships such as that between monogamy and cooperation.
The conditions an organism experiences during development can modify how they plastically respond to short-term changes in their environment later in life. This can be adaptive because the optimal ...average trait value and the optimal plastic change in trait value in response to the environment may differ across different environments. For example, early developmental temperatures can adaptively modify how reptiles, fish and invertebrates metabolically respond to temperature. However, whether individuals within populations respond differently (a prerequisite to adaptive evolution), and whether this occurs in birds, which are only ectothermic for part of their life cycle, is not known. We experimentally tested these possibilities by artificially incubating the embryos of Pekin ducks (Anas platyrhynchos domesticus) at constant or variable temperatures. We measured their consequent heart rate reaction norms to short-term changes in egg temperature and tracked their growth. Contrary to expectations, the early thermal environment did not modify heart rate reaction norms, but regardless, these reaction norms differed among individuals. Embryos with higher average heart rates were smaller upon hatching, but heart rate reaction norms did not predict subsequent growth. Our data also suggests that the thermal environment may affect both the variance in heart rate reaction norms and their covariance with growth. Thus, individual avian embryos can vary in their plasticity to temperature, and in contrast to fully ectothermic taxa, the early thermal environment does not explain this variance. Because among-individual variation is one precondition to adaptive evolution, the factors that do contribute to such variability may be important.
Extra-pair paternity (EPP) is extremely variable among species of birds,
both in its frequency and in the behavioral events that produce it. A flood of
field studies and comparative analyses has ...stimulated an array of novel ideas,
but the results are limited in several ways. The prevailing view is that EPP is
largely the product of a female strategy. We evaluate what is known about the
behavioral events leading to EPP and find the justification for this view to be
weak. Conflict theory (derived from selection theory) predicts that adaptations
in all the players involved will influence the outcome of mating interactions,
producing complex and often highly variable patterns of behavior and levels of
EPP. Data support some of these predictions, but alternative hypotheses abound.
Tests of predictions from conflict theory will require better information on
how males and females encounter one another, behave once they have met, and
influence fertilization once insemination has occurred.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, INZLJ, IZUM, KILJ, NMLJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK, ZRSKP
The mechanisms that contribute to variation in lifetime reproductive success are not well understood. One possibility is that telomeres, conserved DNA sequences at chromosome ends that often shorten ...with age and stress exposures, may reflect differences in vital processes or influence fitness. Telomere length often predicts longevity, but longevity is only one component of fitness and little is known about how lifetime reproductive success is related to telomere dynamics in wild populations. We examined the relationships between telomere length beginning in early life, telomere loss into adulthood and lifetime reproductive success in free-living house sparrows (
). We found that females, but not males, with longer telomeres during early life had higher lifetime reproductive success, owing to associations with longevity and not reproduction per year or attempt. Telomeres decreased with age in both sexes, but telomere loss was not associated with lifetime reproductive success. In this species, telomeres may reflect differences in quality or condition rather than the pace of life, but only in females. Sexually discordant selection on telomeres is expected to influence the stability and maintenance of within population variation in telomere dynamics and suggests that any role telomeres play in mediating life-history trade-offs may be sex specific.
ABSTRACT
Learning is a familiar process to most people, but it currently lacks a fully developed theoretical position within evolutionary biology. Learning (memory and forgetting) involves ...adjustments in behaviour in response to cumulative sequences of prior experiences or exposures to environmental cues. We therefore suggest that all forms of learning (and some similar biological phenomena in development, aging, acquired immunity and acclimation) can usefully be viewed as special cases of phenotypic plasticity, and formally modelled by expanding the concept of reaction norms to include additional environmental dimensions quantifying sequences of cumulative experience (learning) and the time delays between events (forgetting). Memory therefore represents just one of a number of different internal neurological, physiological, hormonal and anatomical ‘states’ that mediate the carry‐over effects of cumulative environmental experiences on phenotypes across different time periods. The mathematical and graphical conceptualisation of learning as plasticity within a reaction norm framework can easily accommodate a range of different ecological scenarios, closely linking statistical estimates with biological processes. Learning and non‐learning plasticity interact whenever cumulative prior experience causes a modification in the reaction norm (a) elevation mean phenotype, (b) slope responsiveness, (c) environmental estimate error informational memory and/or (d) phenotypic precision skill acquisition. Innovation and learning new contingencies in novel (laboratory) environments can also be accommodated within this approach. A common reaction norm approach should thus encourage productive cross‐fertilisation of ideas between traditional studies of learning and phenotypic plasticity. As an example, we model the evolution of plasticity with and without learning under different levels of environmental estimation error to show how learning works as a specific adaptation promoting phenotypic plasticity in temporally autocorrelated environments. Our reaction norm framework for learning and analogous biological processes provides a conceptual and mathematical structure aimed at usefully stimulating future theoretical and empirical investigations into the evolution of plasticity across a wider range of ecological contexts, while providing new interdisciplinary connections regarding learning mechanisms.
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