Early Life Stress Strengthens Trait Covariance: A Plastic Response That Results in Reduced Flexibility

Merrill, Loren; Grindstaff, Jennifer L.

doi:10.1086/699839

Cited by 19 publications

(28 citation statements)

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“…There are some indications that early-life stress may increase the correlations between and within traits (i.e. repeatability) (Briffa, 2013;Burton, Killen, Armstrong, & Metcalfe, 2011;Guenther, Groothuis, Krüger, & Goerlich-Jansson, 2018;Han & Dingemanse, 2017;Jenkins, 2011;Merrill & Grindstaff, 2018;Royauté, Greenlee, Baldwin, & Dochtermann, 2015). Irreversible plasticity generally acts in early life, during (pre-or early post-natal) developmental sensitive periods (Mousseau & Fox, 1998).…”

Section: Current Evidence For H2mentioning

confidence: 99%

“…Across vertebrate taxa, there is strong evidence that glucocorticoid hormones mediate environmental stressors through pleiotropic effects on multiple neurological, physiological and behavioural traits (reviewed in Hau, Casagrande, Ouyang, & Baugh, 2016). Experimental work indicates potential for glucocorticoids to alter associations between life history, physiological and behavioural traits (Guenther et al, 2018;Merrill & Grindstaff, 2018). Glucocorticoids may be particularly meaningful in responding to changes in energy demands as they help adjust energy balance according to current needs by coordinating responses to regular but also to acute, unpredictable circumstances (Sapolsky, Romero, & Munck, 2000;Wingfield, 2013).…”

Section: Current Evidence For H3mentioning

confidence: 99%

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Environmental effects on the covariation among pace‐of‐life traits

et al. 2020

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Pace-of-life syndromes (POLSs) are suites of life-history, physiological and behavioral traits that arise due to trade-offs between allocation to current and future reproduction. Traits generally show covariation that can arise from genetic and environmental influences on phenotypes and constrain the independent evolution of traits, resulting in fitness consequences and impacts on population dynamics. The notion that correlations among traits may vary among populations along environmental gradients suggests an important role for the environment in shaping and maintaining POLS. However, no synthesis has been attempted of the myriad ways in which environmental factors should influence POLS. Here, we formulate a series of hypotheses targeting the critical interfaces of the environment and life history-behaviour associations across different organisms. We discuss the hypotheses in light of findings from a systematic review of studies that measured changes in the association between behavior and life-history traits as a function of environmental conditions. The review revealed that POLS is often shaped by environmental variation, where harshness of the environment in early life has the most consistent effects on POLS. However, only partial or no effects of environmental variation were found in a number of studies, which may result from the highly variable study systems, traits, and environments studied. We highlight promising directions arising from the available studies and identify knowledge gaps that, if unaddressed, will impede progress in the field.

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Section: Current Evidence For H2mentioning

confidence: 99%

Section: Current Evidence For H3mentioning

confidence: 99%

Environmental effects on the covariation among pace‐of‐life traits

et al. 2020

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show abstract

“…There are some indications that early-life stress may increase the correlations between and within traits (i.e. repeatability) (Briffa, 2013;Burton, Killen, Armstrong, & Metcalfe, 2011;Guenther, Groothuis, Krüger, & Goerlich-Jansson, 2018;Han & Dingemanse, 2017;Jenkins, 2011;Merrill & Grindstaff, 2018;Reid, Armstrong, & Metcalfe, 2011;Royauté, Greenlee, Baldwin, & Dochtermann, 2015). Irreversible plasticity generally acts in early life, during (pre-or early postnatal) developmental sensitive periods (Mousseau & Fox, 1998).…”

Section: H3: Life Stagementioning

confidence: 99%

Environmental effects on the covariation among pace-of-life traits

Hämäläinen¹,

Guenther²,

Patrick³

et al. 2019

Preprint

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A range of life-history strategies along a slow-fast continuum emerge due to trade-offs between allocation to current and future reproduction. Pace-of-life syndromes (POLS) are suites of correlated life-history, physiological and behavioral traits that arise due to these trade-offs. The notion that correlations among traits may vary between populations of the same species or along environmental gradients suggests an important role for the environment in shaping and maintaining POLS. Understanding how environmental conditions influence POLS is important for understanding evolutionary change as covariation between traits may constrain their independent evolution. Here, we formulate a series of hypotheses on how environmental conditions influence POLS, with specific focus on the integration of behavior with life-history traits. We make predictions on the interactions among defining features of the environment (harshness, predictability) and type of organism (taxonomy, endothermy, life stage). We review the empirical support for each hypothesis from studies that measured changes in the association between behavior and life-history traits as a function of environmental conditions. Environmental factors were frequently found to influence the covariance of behavioral traits with life history but the effects were not broadly generalizable across study systems. Evidence of environmental harshness and the significance of early life environment suggest these as important determinants of POLS, but environmental predictability and differences between taxa are, in essence, unstudied. We identify knowledge gaps and highlight promising directions arising from current studies.

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“…Hence, when the same genetic mechanisms or physiological pathways affect traits in different life stages, there is the potential that trait variation becomes constrained between life stages, despite developmental boundaries to prevent covariances and promote decoupling (Schluter et al 1991;Phillips 1998;De Block and Stoks 2005;Marshall and Morgan 2011;Aguirre et al 2014). Developmental environments can also impose constraints between life stages through legacy effects, whereby exposure to particular environmental conditions early in life canalises development later in life, reducing the phenotypic space an individual could occupy (Pechenik 2006;Allen and Marshall 2010;Merrill and Grindstaff 2018).…”

Section: Complex Life Cycles and Their Consequences On Marine Evolutionmentioning

confidence: 99%

“…A less well studied aspect of marine complex life cycles is the pattern of covariance in life history traits, which is important because it determines the distribution of traits at the population level (Merrill and Grindstaff 2018). Furthermore, given heritable (Aguirre et al 2014) and environmental (Hamilton et al 2008;Shima et al 2015) components of early life history trait variation, studies of temporal patterns in trait covariances can shed light on the underlying stability of genetic or environmental factors contributing towards life history phenotype distributions.…”

Section: Complex Life Cycles and Their Consequences On Marine Evolutionmentioning

confidence: 99%

Dimensions of genotypic and phenotypic divergence in marine metapopulations: space, time, and ontogeny

Thia¹

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The tussle between selection and gene flow has considerable implications for evolution. As directly opposing counterparts, divergent selection should drive differentiation among subpopulations, whilst gene flow homogenises subpopulations. The balance between these two forces determines the evolutionary trajectories within and among subpopulations. However, many different outcomes can manifest, contingent on eco-evolutionary conditions, which makes predicting the product of selection-gene flow interactions challenging. Two particularly intriguing considerations are adaptive evolution amidst high gene flow and variability in selection-gene flow interactions. Under strong gene flow, considerable selection is required to overcome homogenisation. Successful adaptation is predicted to produce genotype-phenotype-environment associations. However, phenotypic plasticity might be favoured under high gene flow because it facilitates phenotype-environment matching when there is appreciable likelihood for genotype-environment mismatches. Species with extensive dispersal therefore represent interesting systems to investigate the conditions that local adaptation emerges, and contributions of directly heritable and plastic components to phenotypes, amidst homogenising gene flow. Additionally, factors affecting the pattern of selection and gene flow are not static, and selection-gene flow interactions are potentially variable across different scales. Spatial and temporal variation might exist in both these forces. Moreover, dispersal might be limited to specific life stages, or selection may not be consistent across an individual's lifetime. Collectively, the ecological dimensions of space, time, and ontogeny have potentially complex ways of structuring genotypic and phenotypic variation within and among subpopulations. Understanding when, where, and how this variation is structured can elucidate the effect of selection-gene flow interactions on biodiversity and genotype-phenotype-environment associations in natural settings. Marine species are extremely useful for studying how space, time, and ontogeny structure V Publications included in this thesis CHAPTER 2-Thia JA, Riginos C, Liggins L, Figueira WF, McGuigan K (2018) Larval traits show temporally consistent constraints, but are decoupled from postsettlement juvenile growth, in an intertidal fish.

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Early Life Stress Strengthens Trait Covariance: A Plastic Response That Results in Reduced Flexibility

Cited by 19 publications

References 70 publications

Environmental effects on the covariation among pace‐of‐life traits

Environmental effects on the covariation among pace‐of‐life traits

Environmental effects on the covariation among pace-of-life traits

Dimensions of genotypic and phenotypic divergence in marine metapopulations: space, time, and ontogeny

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