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Record W2091446623 · doi:10.1111/1365-2435.12048

The ecology of stress: a marriage of disciplines

2013· article· en· W2091446623 on OpenAlex
Rudy Boonstra

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFunctional Ecology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsBiologyEcologyOrganismLife historyResource (disambiguation)Evolutionary biologyEnvironmental stressVertebrateLife history theoryStressorReproductionGeneGeneticsNeuroscience

Abstract

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Life is difficult. (M.S. Peck, The Road Less Travelled, 1978) The above-mentioned truism applies not only to humans, but also to all other organisms. In vertebrates, a key response to life's difficulties is the activation of the stress axis. The study of this axis is one of the best windows we have to ‘see’ under the surface of the animal into the functional mechanisms it uses to cope. The major reason for this is that the key circulating steroid hormones of the stress axis – glucocorticoids – influence the expression of c. 10% of the genome and its targets include genes controlling metabolism, growth, repair, reproduction and the management of resource allocation (Le et al. 2005). However, the axis plays a role not just during life's difficulties but all the time, mediating the relationship of the organism to its environment. At the individual level, the stress axis plays a key role in allowing animals to respond to change and challenge in the face of both environmental certainty and uncertainty. At the species level, the stress axis plays a central role in evolutionary adaptations to particular ecological pressures, such that an understanding of the differences among species is essential to understanding life-history adaptations (Boonstra et al. 2007). The stress axis is part of the neuroendocrine system, a major pathway that integrates environmental change and through which life-history decisions – to reproduce, to grow, or to put energy into storage – are implemented (Ricklefs & Wikelski 2002). Ecology is the scientific study of the interactions that determine the distribution and abundance of organisms (Krebs 2009). The ecology of stress is a part of the functional underpinnings of ecology and plays a fundamental role in our understanding of the study of a species' distribution and abundance. The study of the ecology of stress overlaps with each of the major areas of biology (Fig. 1), but our progress in elucidating the connections between stress and these other areas is uneven. The objective of this special feature is to assess where we are with respect to this progress: to review our state of knowledge of the mechanisms, impact and implications of the ecology of stress in vertebrates at the individual, population and community levels with a view to assessing what we know, what we do not, what the key questions are and how to answer them. The underlying foundation of these review papers is a physiological one, but the threads of behaviour, evolution and genetics occur throughout. The 10 review papers in this special feature focus on a stress axis of vertebrates – the limbic system (dentate gyrus and hippocampus) combined with the hypothalamic–pituitary–interrenal axis in fish, amphibians and reptiles, and the hypothalamic–pituitary–adrenal cortex axis in birds and mammals. What are not covered are the other aspects of the stress response, including the sympathetic nervous response (causing the adrenal medulla to release catecholamines – epinephrine and norepinephrine – into general circulation) and all the other hormones, neurotransmitters, opioid peptides, cytokines and brain functions (Sapolsky, Romero & Munck 2000). Although these may be important, they have largely not been studied in wild vertebrates. This special feature focuses only on the stress axis in vertebrates, not because only they experience stress (clearly invertebrates also experience and respond to it – for example see reviews by Preisser, Bolnick & Benard 2005 and Hawlena & Schmitz 2010), but because the various vertebrate taxa share similar hormonal mechanisms to cope with stress. There are four broad themes covered in this special feature. The first theme, examined by Boonstra (2013), leads off by examining the contribution of the biomedical research to our understanding of the role of stress in wild vertebrates, particularly chronic stress. The sheer volume, detail and sophistication of the research by the biomedical community into stress in humans and our research surrogates – laboratory rodents and primates – have provided exquisite detail of how the stress axis functions in this context. However, is this evidence and the conclusions drawn from it transferable to animals in nature? It may be and here we are thus invoking the uniformity of nature assumption: if we understand how the stress axis functions within the confines of the laboratory, we can then understand how it functions in nature. Some aspects of these laboratory findings are indeed broadly transferable. In common laboratory species, about 90–95% of blood glucocorticoids are bound to a carrier protein called corticosteroid-binding globulin and thus not free and not biologically active. Desantis et al. (2013) found that the vast majority of vertebrates follow this 90% rule. However, Boonstra argues that the conclusions derived from the biomedical community of pathology and maladaptation resulting from chronic stress are not transferable to wild animals. The latter have long evolutionary history of adaptation to natural stressors with some species not being chronically stressed by the same factors that chronically stress other species. What is not discussed, but is implied, is the question of why humans (who also suffer from the effects of chronic stress, but in addition, also show its pathological consequences) are fundamentally different from other vertebrates. Recent papers explore the nature of these differences, especially the profound differences in cognition between humans and other vertebrates (Burkart, Hrdy & van Schaik 2009; Muehlenbein & Flinn 2011). The second theme examined is how we should quantify stress in natural populations. Breuner, Delehanty & Boonstra (2013) come to the conclusion that the vast majority of studies that have collected blood samples have relied on an incomplete metric of stress. Most studies have only measured total glucocorticoid levels and have ignored the measurement of corticosteroid-binding globulin, which would allow the calculation of free glucocorticoid levels. Although research over 30 years ago already pointed to the need to measure free levels, there was always an element of uncertainty. Breuner et al. conclude that recent research unequivocally supports the conclusion that it is only the free levels that are biologically active and thus relevant. This conclusion is supported by the assessment of Crespi et al. (2013) and indirectly by the phylogenetic analysis of Desantis et al. (2013). The uncomfortable question that occurs next is: what are we to make of the vast number of studies that have not measured free glucocorticoid? One can make the simplifying assumption that total and free glucocorticoid levels are tightly correlated, such that we can ignore the issue. However, in some studies, this is not the case, and thus, the assumption needs to be tested on a case-by-case basis. The Breuner et al. paper also review nine other downstream measures of stress that deepen our understanding of how wild animals cope with stressors, some of which are not difficult to measure. Few wildlife studies go beyond simply quantifying glucocorticoid levels. This limitation, however, is also often found in the biomedical literature. Breuner et al. urge a more holistic approach to quantifying the role of stress in wild vertebrates. The third theme addressed in this special feature regards how the stress axis is affected by the ecological factors – the abiotic and biotic environmental factors – that determine the distribution and abundance of animals. In turn, the stress axis should affect individual fitness and, if the effects are widespread, possibly affect population growth (through reproduction and survival). In ecology texts, biotic factors are typically split into competition and predation. In this special feature, the former of these has been split into two: food, which largely reflects scramble competition, and social factors, which reflects contest competition. The evidence from field studies of these factors acting on the stress axis largely focuses on their impact at the level of the individual, and here, we have a great deal of excellent research. However, longitudinal field studies that are then able assess the long-term consequences of this individual stress on the population processes are more scattered and limited. Wingfield (2013) reviews how individuals cope with abiotic factors, both those that require short-term responses and those that require more permanent solutions. He highlights that there is a dearth of such studies, and urges for more field investigations, particularly as abiotic factors are likely to play an increasing role as the climate changes and we need to know how much phenotypic plasticity is present in populations, and whether this plasticity will permit an adequate response to these changes. Schultner et al. (2013) discuss the role of food limitation and abundance on endogenous energy stores, focusing on a sea-bird species that is not significantly affected by predation. Their study is the first to test how the allostasis conceptual model (McEwen & Wingfield 2003) translates into energy allocation. Clinchy, Sheriff & Zanette (2013) review the impact of predation-induced fear on individuals and populations. Such indirect effects of predators on their prey are extremely widespread and have significant impacts on individuals and on population demography. They identify that what has been missing thus far is how such stress impacts the brain and that there may be commonalities between post-traumatic stress in humans and chronic severe fear in animals in nature. Finally, Creel et al. (2013) review the impact of the social environment, both in species that are nonsocial and interact through territoriality and in those that are social and interact through dominance–subordinate relationships. Creel et al. present convincing evidence in social species that dominance interactions profoundly affect the stress experienced by individuals. The impact of the social environment on population processes has been better studied in the nonsocial territorial species, but remains to be investigated in the social species. Finally, they set the stage for future research by highlighting the gaps in our knowledge, such as linking the social environment to other environmental factors. The fourth theme addressed is how the stress axis plays a role in life-history adaptations, with the first paper focusing on the ecological time frame and the last three on the evolutionary time frame. It is becoming increasingly clear that complexity, not simplicity, characterizes the functioning of the stress axis and related organizational and activational components, both within individuals and among species. The simplifying assumption that the axis is robustly conserved may only be true at the most rudimentary level. This is distressing, given that it implies that we need much greater sophistication and effort to extract general principles from wild animals. Love, McGowan & Sheriff (2013) review the biomedical literature to show how both maternal adversity (affecting both the mother and her in utero and/or postnatal offspring) and life-long individual adversity can program those individuals permanently, having intergenerational and possibly transgenerational consequences on fitness. These changes may be epigenetic, having both individual consequences and, if the stressor affects the majority of individuals, population consequences. Key in their review is the focus not just on the proximate mechanisms of these changes, but whether they have ultimate, adaptive fitness benefits. The final three papers take the long-term, evolutionary view of how the stress axis functions. Crespi et al. (2013) address the question of whether glucocorticoids influence life-history variation. The evidence is suggestive in some areas, but the simple measures are not sufficient to explain all the variation we see. The relationship between glucocorticoids and life-history variation is complex, and Crespi et al. call for a more comprehensive, inclusive assessment of both the stress axis and related components if we are to extract generalities. Desantis et al. (2013) carry out a phylogenetic analysis on only one of the key components of stress axis – the glucocorticoid carrier protein in plasma – corticosteroid-binding globulin. Reassuringly, most vertebrates (except for some of the oldest ones) have this protein and it binds the glucocorticoid as predicted from laboratory animal models. However, at least six extant New World mammal species appear to have none or virtually none, yet function perfectly well. It is not entirely clear what adjustments these species have made to cope with extreme amounts of free glucocorticoids nor how they managed to jump the gulf between their ancestors having this protein and then loosing it. Finally, Jessop, Woodford & Symonds (2013) ask the simple question and obtain a modestly robust answer: can large-scale environmental patterns, such as variation in primary productivity, predict how reptiles and birds respond to a standardized stressor. The answer is yes and, with fine tuning (such as measuring the free glucocorticoid response, rather than the total glucocorticoid response), the explanatory power of these relationships may be useful for predicting the capability of species to respond to climate change. Much species-specific variation remains. However, this is one of the first such studies of which I am aware, and it shows great promise in identifying generalities that permit us insight into life-history patterns. The board sweep of papers included in this special feature summarizes the breadth and depth of research on the ecology of stress in wild vertebrates. It is an extremely vigorous area of research, where we have made significant headway, but these reviews have also identified controversies of methods and interpretation that future work will have to resolve. They identify the key gaps in our knowledge that link the impact of stress on individuals to population and community processes. They also highlight the complexity of the stress response and the species-specific solutions to the problem of existence. Fundamentally, if we are to understand how vertebrates interact with their environment, we must understand how the stress axis functions and its integrative role in adaptation. These papers provide a solid foundation for this understanding. I thank the contributors and reviewers of papers in this special feature, Charles Fox for his criticism in the pursuit of excellence, insight and guidance over this entire endeavour and Liz Baker, Jennifer Meyer and Beulah Devaney for their editorial guidance. I thank Charles Krebs and Alice Kenney producing Fig. 1 for me.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.712
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.201
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it