There is growing interest in studying hormones beyond single 'snapshot' measurements, as recognition that individual variation in the endocrine response to environmental change may underlie many rapid, coordinated phenotypic changes. Repeated measures of hormone levels in individuals provide additional insight into individual variation in endocrine flexibility - that is, how individuals modulate hormone levels in response to the environment. The ability to quickly and appropriately modify phenotype is predicted to be favored by selection, especially in unpredictable environments. The need for repeated samples from individuals can make empirical studies of endocrine flexibility logistically challenging, but methods based in mathematical modeling can provide insights that circumvent these challenges. Our Review introduces and defines endocrine flexibility, reviews existing studies, makes suggestions for future empirical work, and recommends mathematical modeling approaches to complement empirical work and significantly advance our understanding. Mathematical modeling is not yet widely employed in endocrinology, but can be used to identify innovative areas for future research and generate novel predictions for empirical testing.

/pdf/integrating-theoretical-and-empirical-approaches-for-a-5mo3wnbw.pdf

Integrating theoretical and empirical approaches for a robust understanding of endocrine flexibility.

Hormones are highly responsive internal signals that help organisms adjust their phenotype to fluctuations in environmental and internal conditions. Our knowledge of the causes and consequences of variations in circulating hormone concentrations has improved greatly in the past. However, this knowledge comes from population-level studies which generally tend to make the flawed assumption that all individuals respond in the same way to environmental changes. Here, we advocate that we can vastly expand our understanding of the ecology and evolution of hormonal traits once we acknowledge the existence of individual differences by quantifying hormonal plasticity at the individual level, where selection acts. In this review, we use glucocorticoid hormones as examples of highly plastic endocrine traits that interact intimately with energy metabolism but also with other organismal traits like behavior and physiology. First, we highlight the insights gained by repeatedly assessing an individual's glucocorticoid concentrations along a gradient of environmental or internal conditions using a 'reaction norm approach'. This study design should be followed by a hierarchical statistical partitioning of the total endocrine variance into the among-individual component (individual differences in average hormone concentrations, i.e. in the intercept of the reaction norm) and the residual (within-individual) component. The latter is ideally further partitioned by estimating more precisely the hormonal plasticity (i.e. the slope of the reaction norm), which allows to test whether individuals differ in the degree of hormonal change along the gradient. Second, we critically review the published evidence for glucocorticoid variation, focusing mostly on among- and within-individual levels, finding only a good handful of studies that used repeated-measures designs and random regression statistics to investigate glucocorticoid plasticity. These studies indicate that individuals can differ in both the intercept and the slope of their glucocorticoid reaction norm to a known gradient. Third, we suggest rewarding avenues for future work on hormonal reaction norms, for example to uncover potential costs and trade-offs associated with glucocorticoid plasticity or to test whether glucocorticoid plasticity varies when an individual's reaction norm is repeatedly assessed along the same gradient, whether reaction norms in glucocorticoids covary with those in other traits like behavior and fitness (generating multivariate plasticity) or to quantify glucocorticoid reaction norms along multiple external and internal gradients that act simultaneously (leading to multidimensional plasticity). Throughout this review we emphasize the power that reaction norm approaches offer for resolving unanswered questions in ecological and evolutionary endocrinology.

https://academic.oup.com/icb/advance-article-pdf/doi/10.1093/icb/icab196/41357072/icab196.pdf

Quantifying Glucocorticoid Plasticity Using Reaction Norm Approaches: There Still is So Much to Discover!

Hormones are highly responsive internal signals that help organisms adjust their phenotype to fluctuations in environmental and internal conditions. Our knowledge of the causes and consequences of variation in circulating hormone concentrations has improved greatly in the past. However, this knowledge often comes from population-level studies, which generally tend to make the flawed assumption that all individuals respond in the same way to environmental changes. Here, we advocate that we can vastly expand our understanding of the ecology and evolution of hormonal traits once we acknowledge the existence of individual differences by quantifying hormonal plasticity at the individual level, where selection acts. In this review, we use glucocorticoid (GC) hormones as examples of highly plastic endocrine traits that interact intimately with energy metabolism but also with other organismal traits like behavior and physiology. First, we highlight the insights gained by repeatedly assessing an individual's GC concentrations along a gradient of environmental or internal conditions using a "reaction norm approach." This study design should be followed by a hierarchical statistical partitioning of the total endocrine variance into the among-individual component (individual differences in average hormone concentrations, i.e., in the intercept of the reaction norm) and the residual (within-individual) component. The latter is ideally further partitioned by estimating more precisely hormonal plasticity (i.e., the slope of the reaction norm), which allows to test whether individuals differ in the degree of hormonal change along the gradient. Second, we critically review the published evidence for GC variation, focusing mostly on among- and within-individual levels, finding only a good handful of studies that used repeated-measures designs and random regression statistics to investigate GC plasticity. These studies indicate that individuals can differ in both the intercept and the slope of their GC reaction norm to a known gradient. Third, we suggest rewarding avenues for future work on hormonal reaction norms, for example to uncover potential costs and trade-offs associated with GC plasticity, to test whether GC plasticity varies when an individual's reaction norm is repeatedly assessed along the same gradient, whether reaction norms in GCs covary with those in other traits like behavior and fitness (generating multivariate plasticity), or to quantify GC reaction norms along multiple external and internal gradients that act simultaneously (leading to multidimensional plasticity). Throughout this review, we emphasize the power that reaction norm approaches offer for resolving unanswered questions in ecological and evolutionary endocrinology. 

Glucocorticoids in a warming world: Do they help birds to cope with high environmental temperatures?

The vertebrate stress response comprises a suite of behavioural and physiological traits that must be functionally integrated to ensure organisms cope adaptively with acute stressors. Natural selection should favour functional integration, leading to a prediction of genetic integration of these traits. Despite the implications of such genetic integration for our understanding of human and animal health, as well as evolutionary responses to natural and anthropogenic stressors, formal quantitative genetic tests of this prediction are lacking. Here, we demonstrate that acute stress response components in Trinidadian guppies are both heritable and integrated on the major axis of genetic covariation. This integration could either facilitate or constrain evolutionary responses to selection, depending upon the alignment of selection with this axis. Such integration also suggests artificial selection on the genetically correlated behavioural responses to stress could offer a viable non-invasive route to the improvement of health and welfare in captive animal populations. 

Genetic integration of behavioural and endocrine components of the stress response

Metabolic rate is a key ecological variable that quantifies the energy expenditure needed to fuel almost all biological processes in an organism. Metabolic rates are typically measured at the whole-organism level (woMR) with protocols that can elicit stress responses due to handling and confinement, potentially biasing resulting data. Improved, non-stressful methodology would be especially valuable for measures of field metabolic rate, which quantifies the energy expenditure of free-living individuals. Recently, techniques to measure cellular metabolic rate (cMR) in mitochondria of blood cells have become available, suggesting that blood-based cMR can be a proxy of organismal aerobic performance. Aerobic metabolism actually takes place in the mitochondria. Quantifying cMR from blood samples offers several advantages such as direct estimates of metabolism and minimized disturbance of individuals. To our knowledge, the hypothesis that blood-based cMR correlates with woMR has not yet been directly tested. We measured cMR in red blood cells of captive great tits (Parus major), first during their morning activity period and second after subjecting them to a 2.5 h day-time respirometry protocol to quantify woMR. We predicted cMR to decrease as individuals transitioned from an active to a resting state. In the two blood samples we also assessed circulating corticosterone concentrations to determine the perceived disturbance of individuals. From respirometry traces we extracted initial and final woMR measures to test for a predicted positive correlation with cMR measures, while accounting for corticosterone concentrations. Indeed, cMR declined from the first to the second measurement. Furthermore, woMR and cMR were positively related in individuals that had relatively low corticosterone concentrations and displayed little locomotor activity throughout respirometry. By contrast, woMR and cMR covaried negatively in birds that increased corticosterone concentrations and activity levels substantially. Our results show that red blood cell cMR represents a proxy for woMR when birds do not display signs of stress, i.e., either before increases in hormonal or behavioral parameters have occurred or after they have abated. This method represents a valuable tool for obtaining metabolic data repeatedly and in free-living individuals. Our findings also highlight the importance of accounting for individual stress responses when measuring metabolic rate at any level.

/pdf/inferring-whole-organism-metabolic-rate-from-red-blood-cells-qfpqn6zg0h.pdf

Kasja Malkoc

Papers

Inferring Whole-Organism Metabolic Rate From Red Blood Cells in Birds.

Quantifying Glucocorticoid Plasticity Using Reaction Norm Approaches: There Still is So Much to Discover!