From performance curves to performance surfaces: Interactive effects of temperature and oxygen availability on aerobic and anaerobic performance in the common wall lizard

Accurately predicting the responses of organisms to novel or changing environments requires the development of ecologically-appropriate experimental methodology and process-based models. For ectotherms, thermal performance curves (TPCs) have provided a useful framework to describe how organismal performance is dependent on temperature. However, this approach often lacks a mechanistic underpinning, which limits our ability to use TPCs predictively. Furthermore, thermal dependence varies across traits, and performance is also limited by additional abiotic factors, such as oxygen availability. We test a central prediction of our recent Hierarchical Mechanisms of Thermal Limitation (HMTL) Hypothesis which proposes that natural hypoxia exposure will reduce maximal performance and cause the TPC for whole-organism performance to become more symmetrical. We quantified TPCs for two traits often used as fitness proxies, sprint speed and aerobic scope, in lizards under conditions of normoxia and high-elevation hypoxia. In line with the predictions of HMTL, anaerobically fuelled sprint speed was unaffected by acute hypoxia while the TPC for aerobic scope became shorter and more symmetrical. This change in TPC shape resulted from both the maximum aerobic scope and the optimal temperature for aerobic scope being reduced in hypoxia as predicted. Following these results, we present a mathematical framework, which we call Temperature–Oxygen Performance Surfaces, to quantify the interactive effects of temperature and oxygen on whole-organism performance in line with the HMTL hypothesis. This framework is transferrable across traits and levels of organization to allow predictions for how ectotherms will respond to novel combinations of temperature and other abiotic factors, providing a useful tool in a time of rapidly changing environmental conditions.info:eu-repo/semantics/publishedVersio

General conclusion to the special issue Moving forward on individual heterogeneity

International audienc

Transform-limited photons from a coherent tin-vacancy spin in diamond

Solid-state quantum emitters that couple coherent optical transitions to long-lived spin qubits are essential for quantum networks. Here we report on the spin and optical properties of individual tin-vacancy (SnV) centers in diamond nanostructures. Through cryogenic magneto-optical and spin spectroscopy, we verify the inversion-symmetric electronic structure of the SnV, identify spin-conserving and spin-flipping transitions, characterize transition linewidths, measure electron spin lifetimes and evaluate the spin dephasing time. We find that the optical transitions are consistent with the radiative lifetime limit even in nanofabricated structures. The spin lifetime is phononlimited with an exponential temperature scaling leading to $T_1$ $>$ 10 ms, and the coherence time, $T_2$ reaches the nuclear spin-bath limit upon cooling to 2.9 K. These spin properties exceed those of other inversion-symmetric color centers for which similar values require millikelvin temperatures. With a combination of coherent optical transitions and long spin coherence without dilution refrigeration, the SnV is a promising candidate for feasable and scalable quantum networking applications

Analyzing Stress as a Multivariate Phenotype

The stress phenotype is multivariate. Recent advances have broadened our understanding beyond characterizing the stress response in a single dimension. Simultaneously, the toolbox available to ecophysiologists has expanded greatly in recent years, allowing the measurement of multiple biomarkers from an individual at a single point in time. Yet these advances—in our conceptual understanding and available methodologies—have not yet been combined in a unifying multivariate statistical framework. Here, we offer a brief review of the multivariate stress phenotype and describe a general statistical approach for analysis using nonparametric multivariate analysis of variance with residual randomization in permutation procedures (RRPP) implemented using the “RRPP” package in R. We also provide an example illustrating the novel insights that can be gained from a holistic multivariate approach to stress and provide a tutorial for how we analyzed these data, including annotated R code and a guide to interpretation of outputs (Online Appendix 1). We hope that this statistical methodology will provide a quantitative framework facilitating the unification of our theoretical understanding and empirical observations into a quantitative, multivariate theory of stress

Data from: Among-individual heterogeneity in maternal behaviour and physiology affects reproductive allocation and offspring life-history traits in the garter snake Thamnophis elegans

Accumulating evidence suggests that within-individual plasticity of behavioural and physiological traits is limited, resulting in stable among-individual differences in these aspects of the phenotype. Furthermore, these traits often covary within individuals, resulting in a continuum of correlated phenotypic variation among individuals within populations and species. This heterogeneity, in turn, affects individual fitness and can have cross-generational effects. Patterns of trait covariation, among-individual differences, and subsequent fitness consequences have long been recognized in reptiles. Here, we provide a test of patterns of among-individual heterogeneity in behaviour and physiology and subsequent effects on reproduction and offspring fitness in the garter snake Thamnophis elegans. We find that measures of activity levels vary among individuals and are consistent within individuals in reproductive female snakes, indicating stable behavioural phenotypes. Blood hormone and glucose concentrations are not as stable within individuals, indicating that these traits do not describe consistent physiological phenotypes. Nonetheless, the major axes of variation in maternal traits describe behavioural and physiological phenotypes that interact to predict offspring body condition and mass at birth. This differential allocation of energy to offspring, in turn, strongly influences subsequent offspring growth and survival. This pattern suggests the potential for strong selection on phenotypes defined by behaviour-physiology interactions