Daniel W. A. Noble

The ability to detect prey is crucial for survival in many animals. However, prey detection is a cognitive process that can be influenced by early life conditions such as prenatal stress or temperature. Mitochondrial function is likely to underlie these effects because cognitive abilities are energetically demanding (i.e. dependent on efficient metabolic function) and because metabolic‐derived oxidative stress and oxidative damage can impair cognitive function. Yet, whether prenatal stress and thermal environments affect prey detection, and whether mitochondrial function mediates such effects, remains poorly understood. Here, we investigated the links between prenatal environments, mitochondrial function and prey detection in the delicate skink ( Lampropholis delicata ). We manipulated egg corticosterone (CORT) levels—a key stress hormone in reptiles—and incubation temperature and assessed the ability of lizards to detect chemical and visual prey stimuli. Then, using flow cytometry, we measured metabolic function, oxidative stress and oxidative damage in the olfactory bulbs and optic tecta, two brain regions involved in sensory processing. While metabolic function and oxidative stress remained robust to early life conditions, CORT and temperature interacted to influence oxidative damage. Particularly, CORT decreased DNA damage in the olfactory bulbs of cold‐incubated lizards but had no effect on hot‐incubated lizards. In both brain regions, lipid peroxidation was lower in CORT‐treated lizards incubated at high temperatures compared to CORT‐treated cold‐incubated lizards, but no other between‐treatment differences were detected. Additionally, CORT‐treated lizards responded faster when presented with chemical cues but not visual stimuli. We did not find any relationship between mitochondrial function and prey detection. Our findings suggest that prenatal conditions have lasting effects on DNA damage and prey detection, but prey detection appears decoupled from mitochondrial function in L. delicata . Read the free Plain Language Summary for this article on the Journal blog.

Meta‐analyses in ecology and evolution sometimes target the magnitude of differences between groups rather than their direction, for example, when the question concerns deviation from a biological optimum or divergence from a reference state. A common practice is to convert signed effects into magnitudes by taking absolute values, but this can induce upward distortion and non‐normal sampling distributions under standard meta‐analytic models. Here we introduce lnM, a log‐ratio effect size for the magnitude of difference between two groups, defined from one‐way ANOVA components. lnM is asymptotically normal, supports standard multilevel meta‐analysis and meta‐regression and applies to both ratio‐ and interval‐scale traits. Using theory, simulations and worked examples, we show when delta‐method and single‐fit bootstrap estimators perform well, and how lnM can be used to assess publication bias.

Increasing resource demand, desire to sequester atmospheric carbon, and conservation goals are driving a need for forests to be managed more effectively in the face of numerous challenges. One such challenge is damage perpetrated by browsing mammals, which can cause substantial financial and ecological impacts. Current practices focus on lethal control measures for mitigating mammal browsing damage, however stakeholder pressure is calling for a transition to non‐lethal alternatives. Little is known about the relative efficacy of different non‐lethal control methods for mitigating browsing damage by mammals other than deer. Using a multilevel meta‐analytical framework across 1,908 effect sizes, we investigate the relative efficacy and longevity of different non‐lethal control methods implemented against a broad suite of browsing mammals across different spatial scales. We found that tree guards, repellents and exclusion fencing all significantly reduce mammal browsing damage and retain their effect for long periods. There was, however, substantial variation in efficacy within individual control strategies highlighting the importance to forest managers of selecting the correct method from within the broad strategies we identified. We then discuss other factors to consider when implementing non‐lethal mammal browsing control so that forest managers are well informed when implementing a control strategy.

Quantity discrimination affects a range of behaviours essential for fitness, including social interactions, navigation, and foraging and is widespread across animal taxa. However, in reptiles, evidence for this ability — particularly for small number contrasts — remains limited and mixed. Early-life conditions, such as hormonal exposure and temperature, can also shape brain development and cognitive performance, potentially affecting numerical abilities. Here, we tested the ability of the common garden skink ( Lampropholis guichenoti ) to discriminate between quantities and the effects of elevated prenatal glucocorticoids and incubation temperature on quantity discrimination and decision-making. We assessed quantity discrimination using a spontaneous choice test with food as a stimulus. We subjected lizards to five two-choice tests differing in the number of items (1 VS 4, 1 VS 3, 2 VS 4, 2 VS 3, 3 VS 4) while controlling for total length and area. Contrary to our predictions, lizards did not show clear preferences toward the larger items, providing no evidence of spontaneous quantity discrimination in L. guichenoti . Furthermore, prenatal conditions did not influence latency to make a choice, also a proxy for decision-making. Despite these results, further investigation of quantity discrimination in live-prey-feeding reptiles and the impact of early conditions on other taxa remains an important area of research.

A maximum-likelihood implementation of the thermal-load-sensitivity framework for thermal death-time modelling introduced by Noble, Arnold and Pottier in the 'bayesTLS' package, providing the frequentist counterpart to that Bayesian workflow. The modelling idea and the four-parameter logistic parameterisation are theirs; 'freqTLS' contributes a 'Template Model Builder' ('TMB') likelihood whose midpoint is written directly in terms of critical thermal maximum ('CTmax') and thermal sensitivity (z) so both headline quantities are estimable, and reports uncertainty through a unified trio of frequentist intervals – Wald (delta), profile-likelihood, and bootstrap – for binomial and beta-binomial survival counts and beta-distributed proportions. Column and formula interfaces support fixed and grouped designs plus limited independent random intercepts; prediction includes survival curves and deterministic heat-injury scenarios. Equivalence claims are restricted to the matched relative-threshold, constant-shape 'bayesTLS' configuration.

Extreme heat events are becoming more frequent, intense and prolonged, making it urgent to predict how heat intensity and exposure duration combine to threaten organisms. Thermal death time (TDT) and thermal load sensitivity (TLS) models provide this link, but conventional two-stage analyses often discard uncertainty, mishandle censored or overdispersed data and limit inference. Here, we show how the four-parameter log-logistic model can recover TDT/TLS quantities, including thermal tolerance ( CT _max ), sensitivity ( z ), critical temperature ( T _crit ), heat injury and survival, from one model. Simulations show the joint model reproduces classical estimates when two-stage assumptions hold and is more reliable when they fail. We introduce these workflows as Bayesian and frequentist R packages. Case studies across plant and animal taxa demonstrate this modelling framework can estimate group contrasts and predict survival from realistic field temperature-time series. This framework provides more robust inference and flexible tools for predicting organismal responses to extreme heat events.

The environmental conditions organisms experience during early development can have powerful and sustained effects on morphology, physiology, behaviour, and performance. Such developmental effects can influence reproductive success, survival, and life‐history strategies and can be transmitted across generations (i.e. trans and intergenerational effects). In this way, developmental effects can be powerful drivers of evolutionary change. Given the developmental environment affects a range of phenotypic traits, it has been proposed that physiological responses to developmental conditions are modulated through cellular mechanisms that are shared across cell and tissue types, such as mitochondrial function. Mitochondrial respiratory function is highly sensitive to environmental conditions and exposure to adverse conditions during development can have sustained effects on different aspects of aerobic respiration in mitochondria. However, it is currently unknown if these effects are widespread across taxonomic groups and which components of mitochondrial respiratory function are most likely to be affected by the environment during development. We compiled data from 86 studies to examine the effects of developmental stressors (nutritional imbalance, glucocorticoid hormone exposure, parental care deprivation, and psychological disturbance) on mitochondrial respiratory function using meta‐analysis. We sought to uncover whether there are general effects of developmental stressors on different aspects of mitochondrial respiratory function (antioxidants, metabolic capacity, oxidative damage, oxidative stress, and aerobic respiration). We tested how the type of developmental stressor, together with timing of exposure (prenatal versus postnatal), and sex and taxon of the test subjects influenced the magnitude, direction, and duration of effects on mitochondrial respiratory function. Finally, we tested which aspects of mitochondrial respiratory function were most impacted by developmental stressors. We found that exposure to glucocorticoids, parental care deprivation, and psychological disturbances during development generally decreased mitochondrial respiratory function. Generally, these developmental stressors increased the production of reactive oxygen species and oxidative damage and reduced aerobic respiration, metabolic capacity, and antioxidant levels. Nutritional imbalances during development (including both restricted and excessive nutrition) had a slight negative effect on mitochondrial respiratory function, but this effect may be influenced by publication bias. Overall, our results show that exposure to stressors during development negatively affects mitochondrial respiratory function, suggesting that changes in cellular metabolism may link developmental stressors to variation in whole animal traits and individual fitness.

Maternal stress and the developmental environment jointly affect offspring fitness and phenotype during early life. Mothers transmit stress to offspring through the deposition of hormones and energy into developing embryos, who are themselves subject to environmental stressors. A species’ life-history strategy (e.g. size and number of eggs) may further buffer or exacerbate the effects of developmental stress on offspring. We experimentally tested the joint effects of stress hormones (exogenous corticosterone applied directly to eggs) and the developmental environment (incubation temperature) on the hatching success and size of two lizards (Lampropholis delicata and Lampropholis guichenoti) that differ in maternal investment strategy. Hatching success was reduced by corticosterone exposure, but only in L. delicata, which produces clutches of more numerous but smaller eggs than L. guichenoti. Hatchling size in both species, however, was reduced by corticosterone exposure, incubation at high temperatures or both. In both species, maternal investment (egg size) was the best predictor of hatching success and hatchling size, regardless of treatment. Our findings suggest that, both within species and between species, greater maternal investment buffers offspring from maternal and developmental stress effects on early-life fitness (survival) but does not prevent their effects on fitness-associated phenotypes (hatchling size).

A defining feature of climate change is the increasing frequency, intensity, and severity of extreme weather events. Among them, extreme heat is recognized as a critical driver of ecological and evolutionary change. Intense heat episodes can exceed physiological limits, alter animal movement, restructure geographic ranges, and increase extinction risk more than gradual changes to mean temperatures. Yet links between extreme heat events and organismal biology remain limited, in part because definitions and metrics are not standardized, and user-friendly workflows and guides are lacking for many biologists. We present a methodological roadmap, with reproducible code, for integrating extreme heat into studies of behavior, physiology, biophysical ecology, species distribution models (SDMs), and population dynamics. First, we provide standardized computational approaches to define and quantify extreme heat. Second, we fit species distribution models for California quail ( Callipepla californica ) that include an extreme heat metric and showcase improved predictions of habitat suitability, particularly at range edges. Third, we compute biophysical simulations to quantify exposure to thermal stress in Sleepy lizards ( Tiliqua rugosa ) across distinct macro- and microclimates. Finally, accounting for temporal autocorrelation in temperature profiles in population simulation models, we show that clustered heat extremes—missed by averages—can increase the risk of population collapse. As extreme heat events become more common, incorporating their dynamics is essential for understanding ecological and evolutionary change, designing experiments across species’ geographic ranges, and supporting conservation in a rapidly warming world. Together, these case studies illustrate a reproducible, organism-informed roadmap to integrate extreme heat into predictions of ecological impacts and inference across levels of biological organization under ongoing climate change.