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Understanding the factors affecting thermal tolerance is crucial for predicting the impact climate change will have on ectotherms. However, the role developmental plasticity plays in allowing populations to cope with thermal extremes is poorly understood. Here, we meta-analyse how thermal tolerance is initially and persistently impacted by early (embryonic and juvenile) thermal environments by using data from 150 experimental studies on 138 ectothermic species. Thermal tolerance only increased by 0.13°C per 1°C change in developmental temperature and substantial variation in plasticity (~36%) was the result of shared evolutionary history and species ecology. Aquatic ectotherms were more than three times as plastic as terrestrial ectotherms. Notably, embryos expressed weaker but more heterogenous plasticity than older life stages, with numerous responses appearing as non-adaptive. While developmental temperatures did not have persistent effects on thermal tolerance overall, persistent effects were vastly under-studied, and their direction and magnitude varied with ontogeny. Embryonic stages may represent a critical window of vulnerability to changing environments and we urge researchers to consider early life stages when assessing the climate vulnerability of ectotherms. Overall, our synthesis suggests that developmental changes in thermal tolerance rarely reach levels of perfect compensation and may provide limited benefit in changing environments.

Meta-analysis is a powerful tool used to generate quantitatively informed answers to pressing global challenges. By distilling data from broad sets of research designs and study systems into standardised effect sizes, meta-analyses provide physiologists with opportunities to estimate overall effect sizes and understand the drivers of effect variability. Despite this ambition, research designs in the field of comparative physiology can appear, at the outset, as being vastly different to each other because of ‘nuisance heterogeneity’ (e.g. different temperatures or treatment dosages used across studies). Methodological differences across studies have led many to believe that meta-analysis is an exercise in comparing ‘apples with oranges’. Here, we dispel this myth by showing how standardised effect sizes can be used in conjunction with multilevel meta-regression models to both account for the factors driving differences across studies and make them more comparable. We assess the prevalence of nuisance heterogeneity in the comparative physiology literature – showing it is common and often not accounted for in analyses. We then formalise effect size measures (e.g. the temperature coefficient, Q10) that provide comparative physiologists with a means to remove nuisance heterogeneity without the need to resort to more complex statistical models that may be harder to interpret. We also describe more general approaches that can be applied to a variety of different contexts to derive new effect sizes and sampling variances, opening up new possibilities for quantitative synthesis. By using effect sizes that account for components of effect heterogeneity, in combination with existing meta-analytic models, comparative physiologists can explore exciting new questions while making results from large-scale data sets more accessible, comparable and widely interpretable.

Comparative analyses require researchers to not only ensure data quality, but also to make prudent and justifiable assumptions about data comparability. A failure to do so can lead to unreliable conclusions. As a case in point, we comment on a study that estimated the vulnerability of the world’s fish species to climate change using comparison between life stages (Dahlke et al. 2020, Science 369: 65-70). We highlight concerns with the data quality and argue that the metrics used to investigate ontogenetic differences in thermal tolerance were incomparable and confounded. Therefore, we provide caution when interpreting their results in the light of climate vulnerability. We suggest potential remedies and recommend thermal tolerance metrics that may be comparable across life stages. We also encourage the creation of guidelines to design, report, and assess comparative analyses to increase their reliability and reproducibility.