Roles of multi-level temperature-adaptive responses and microhabitat variation in establishing distributions of intertidal species

In the face of climate change, organisms can adaptively respond to the changing thermal environment using behavioral, physiological and evolutionary approaches (Harley et al., 2006; Somero, 2011, 2012; Somero et al., 2017; Dong et al., 2022a). A quantitative understanding of the thermal responses of organisms is vital for evaluating and forecasting species distributional shifts in response to climate change (Sunday et al., 2012; Deutsch et al., 2015; Pinsky et al., 2019; Pörtner, 2021). Incorporating physiological, molecular and genetic traits into a species distribution model (SDM; see Glossary) can allow the development of a multi-scale, mechanistic SDM that enables a better forecast of future species' distributions and biodiversity (see Box 1; Somero, 2005; Lima et al., 2016; Crickenberger and Wethey, 2018; Dahlke et al., 2020; Liao et al., 2021a; Boardman et al., 2022; Dong et al., 2022b; White et al., 2022). However, a lack of adequate consideration of physiological variation within and among species can greatly lower the predictive power of these models (Helmuth et al., 2005; Bernardo et al., 2007; Osovitz and Hofmann, 2007).

It has long been appreciated that adaptive physiological variation is critical in establishing the environmental relationships of organisms across different spatial and temporal scales (Prosser, 1955; Spicer and Gaston, 1999; Chown, 2001; Chown et al., 2002). As studies have become more mechanistic and reductionist in focus, it has become increasingly clear that adaptive variation is found at all levels of biological organization and entails combinations of genetically based adaptive variation (e.g. in protein amino acid sequence) and phenotypic variation arising from acclimatization (see Glossary; Somero et al., 2017; Dong et al., 2022a). This adaptive variation thus must be examined at multiple hierarchical levels, including changes within a single individual, intrapopulation variation, interpopulation variation and interspecific differences (Fig. 1). Studies of adaptive physiological variation must take into account the influence of phylogeny (Garland and Adolph, 1994) to allow adaptations to be clearly delineated from differences arising strictly from phylogenetic relationships. One means of unambiguously identifying adaptive variation is a comparative examination of congeneric species that have evolved in different environments (Somero et al., 2017). In summary, because of the existence of temperature-adaptive variations of traits at all levels of biological organization and the importance of characterizing the thermal sensitivities of these traits for understanding how sensitive the species is to the current environment and predicted future changes (Chown et al., 2002; Deutsch et al., 2008; Sunday et al., 2014), a core issue is to clarify spatiotemporal patterns of adaptive variation and integrate them into models for predicting and evaluating species distribution ranges.

To develop realistic predictive models, a key component of variation is that found among individuals of a single species owing to genetic variation or different states of acclimatization. However, in many studies, the thermal tolerance limit for a given species is taken to have a species-specific uniform value. As mentioned above, however, thermal performance usually shows high variation among geographically separated populations of a species (Angilletta, 2009; Sgrò et al., 2010). Similarly, recent studies have shown that populations/subpopulations that inhabit different microhabitats – which often are only centimeters or meters apart yet present divergent microclimates – exhibit adaptively different thermal limits (Sinclair, 2001; Seabra et al., 2011; Sunday et al., 2014; Jimenez et al., 2015; Miller et al., 2015; Dong et al., 2017; Moisez et al., 2020). Thus, the scale of environmental variation is a critical variable in governing distribution patterns at a local level. Furthermore, in the context of temporal scales, seasonal acclimatization is another important source of physiological variation, and the relatively higher thermal limit during hot seasons can boost thermal tolerance in the face of high temperatures (Gunderson and Stillman, 2015; Seebacher et al., 2015; Winterová et al., 2020; Dong et al., 2022a). Heat/cold hardening (see Glossary) as a rapid response following sublethal exposure to extreme thermal stress can also change thermal tolerance limits in the short term (Bowler, 2005; Loeschcke and Hoffmann, 2007; Phillips et al., 2015; Moyen et al., 2020; Zhang et al., 2021). Thus, successful development of predictive models must recognize that the thermal limit is not a specific value for a species. Rather, individuals may exhibit wide variations in thermal optima and tolerance limits across space and time; this variation may provide important potential for coping with environmental change.

Intertidal species provide an excellent study system for investigating physiological variation and its importance for establishing distribution patterns. Living at the interface between the land and the ocean, and thus able to function in both water and air, intertidal species occupy habitats along most global coastlines (Thompson et al., 2002; Thyrring and Peck, 2021), and frequently suffer intense thermal stress across multiple spatial and temporal scales (Helmuth et al., 2002; Wethey et al., 2011a; Lima and Wethey, 2012). For many years, physiologists and ecologists have studied how intertidal species physiologically adapt to this frequently changing and extremely stressful environment (Allee, 1923; Bullock, 1955; Southward, 1958; Newell, 1969; Wolcott, 1973), and more recent studies have revealed the roles of this adaptive change at all levels of biological organization (e.g. Somero et al., 2017). Increasingly, combined data from these multi-level analyses are used to predict the impact of climate change, especially global warming and heat waves, on species' distributions (Mislan et al., 2009; Sorte et al., 2010).

In this Review, I address three issues that are vital for understanding – and predicting – the impacts of climate change on the distributions of intertidal species. First, I characterize adaptive responses to thermal stress at multiple levels of biological organization – including physiological, biochemical and molecular (mRNA) systems – to identify traits that may be especially important for setting thermal optima and tolerance limits. One sub-theme in this analysis concerns the amount of molecular variation that is needed to adaptively modify a biochemical or physiological trait. Second, I briefly summarize the physiological variation of intertidal molluscs at different hierarchical levels (i.e. species, population, individual) to understand the ‘raw material’ that may be available for effecting adaptive responses at different spatial (e.g. microhabitat) and temporal scales. Third, I consider how genetic polymorphisms that influence temperature-sensitive traits contribute to setting temporal and spatial variation in thermal responses and population abundance, notably at the previously underappreciated microhabitat scale. In this Review, most examples are drawn from studies performed along China's coasts, where intertidal ecology is relatively less studied compared with coastal regions in Europe and North America. Much of this analysis is based on work from our laboratory, where multi-level analyses on species from highly stressful habitats have been a primary focus.

Thermal stress can affect numerous physiological and cellular processes and biological structures (Somero et al., 2017; Dong et al., 2022a), including energy metabolism (Dong and Zhang, 2016), the heat shock response (Tomanek and Somero, 1999), macromolecular turnover (Kültz, 2020), gene transcription and proteome composition (Connor and Gracey, 2011; Drake et al., 2017; Clark et al., 2018; Collins et al., 2023). Thus, thermal perturbations and the adaptive responses organisms make to these stresses play a vital role in determining ecological fitness (Wethey et al., 2011b; Sinclair et al., 2016). One way in which whole-organism thermal optima and tolerance limits have been examined is using the optimum (T_opt) and critical (CT_max) temperatures (see Glossary), which are calculated using thermal performance curves (TPCs; Angilletta, 2009; Huey and Kingsolver, 1989). TPCs have been used to depict changes in fitness-related traits (e.g. feeding rate, growth rate, metabolic rate and reproduction) under different thermal conditions (Huey and Stevenson, 1979; Huey and Kingsolver, 1989; Sunday et al., 2019). However, care must be taken in employing the conventional TPC, which has the form of a left-skewed curve, because not all species or physiological processes may respond to changes in temperature according to this pattern (McMahon and Russell-Hunter, 1977; Marshall and McQuaid, 2011; Sinclair et al., 2016; Hui et al., 2020). A few intertidal species, especially high intertidal snails, display temperature-insensitive responses of oxygen consumption and heart performance (Q₁₀ values near 1.0; see Glossary) to temperature increases over a wide range of temperatures, which results in energy saving (i.e. metabolic depression; see Glossary) under stress (Marshall and McQuaid, 2011). Thus, for such species, a TPC that incorporates metabolic depression must be developed to describe and predict the effects of changing temperatures.

With this in mind, Liao et al. (2021a) developed a quantitative method for depicting TPCs that incorporate the phenomenon of metabolic depression; this model utilizes a cardiac performance dataset for 26 species of intertidal molluscs. Because of the role of the heart in supplying oxygen and nutrients and removing waste products, changes in cardiac performance are an important physiological response to environmental changes. Heart rate has commonly been used as an indicator of thermal optima and limits to evaluate thermal performance in intertidal molluscs (Pickens, 1965; Widdows, 1973), including snails (Stenseng et al., 2005; Marshall et al., 2010), limpets (Dong and Williams, 2011; Bjelde and Todgham, 2013), mussels (Moyen et al., 2019, 2022), scallops (Xing et al., 2016) and abalones (Chen et al., 2020).

For many molluscs, the typical cardiac thermal response is initially an increase in heart rate up to a critical temperature followed by a sharp decrease in heart rate (Fig. 2A). Two traits based on cardiac thermal performance – the Arrhenius breakpoint temperature (ABT; see Glossary) and the flatline temperature (FLT; see Glossary) – are commonly measured. The ABT can be regarded as the sublethal thermal limit (see Glossary) to cardiac performance, and the FLT can be regarded as the lethal thermal limit (Stenseng et al., 2005). Importantly, in the context of developing realistic analyses and models of thermal responses, cardiac performance in snails and mussels can be modified through acclimatization (Stenseng et al., 2005) and even through short-term exposure (e.g. 1 week) to heat stress (Moyen et al., 2020).

The model developed by Liao et al. (2021a) allows the calculation of the physiological thermal performance limits as gauged by the temperature at which heart rate is decreased to 50% of the maximal rate (T_1/2H; Fig. 2B). This analysis accounts for not only the metabolic depression of cardiac performance of intertidal species, but also for the high inter-individual variability in the shape of cardiac TPCs. This multi-scale (from individual to population to species) mechanistic understanding that incorporates metabolic depression and inter-individual variability in thermal response has enabled better evaluation and prediction of species' distributions compared with the traditional method that ignores the impacts of metabolic depression and physiological variation.

The striking adaptive variation noted at the physiological (organ) level in the analysis of cardiac function is also found at the biochemical and molecular levels. In fact, as I show below, similar patterns of temperature-adaptive variation in traits are found across all levels of biological organization.

The structures and functions of macromolecules are highly sensitive to changes in temperature and exhibit significant patterns of temperature adaptation. For example, the conformational flexibility of orthologous proteins (see Glossary) of species that evolved in different thermal environments exhibits temperature-related adaptation in both structural stability and function (Dalhus et al., 2002; Somero et al., 2017). Usually, orthologs of cold-adapted species exhibit higher intrinsic activity and greater flexibility than orthologs of warm-adapted species (Fields et al., 2015). The level of flexibility is important to protein function: proteins must be stable enough to have the right geometry for binding their substrates, but they also must be flexible enough to allow changes in conformation to complete the catalytic cycle (Somero et al., 2017; Somero, 2022). As an example, I here consider the cytosolic paralog of malate dehydrogenase (cMDH) (EC 1.1.1.37). This enzyme catalyzes the interconversion of malate and oxaloacetate, thus playing an essential role in many metabolic pathways (e.g. tricarboxylic acid cycle, glyoxylate bypass, amino acid synthesis, gluconeogenesis). cMDH is a well-characterized enzyme that has served as an important tool for understanding the relationship between thermal biochemical adaptation and species distribution (Goward and Nicholls, 1994; Fields et al., 2006; Dong and Somero, 2009). Below, I examine several properties of cMDH that provide insights into the thermal relationships that are the central focus of this Review.

To investigate the mechanisms by which orthologous proteins adapt to the thermal environment, both in vitro methods (enzyme kinetic experiments and thermal stability analyses) and in silico molecular dynamic simulation (MDS; see Glossary) have been applied to study the structural and functional properties of cMDH orthologs of five genera of marine molluscs adapted to a ∼60°C range of temperatures. MDS analysis reveals global as well as local adaptation in structural flexibility. The root mean square deviation (RMSD) of main-chain atoms is a quantitative index of backbone atom movements and, thereby, of global protein flexibility. Among orthologs, the effects of temperature on movement of the protein backbone throughout the enzyme (i.e. ΔRMSD, the difference in RMSD values between simulation temperatures of 42 and 15°C) were linearly related to the lethal temperature (LT₅₀) and the rate of thermal denaturation of cMDH (Fig. 3A,B; Liao et al., 2017; Dong et al., 2018; Liao et al., 2019).

Using both site-directed mutagenesis and in silico mutagenesis, the relationship between enzyme thermal stability and amino acid usage was revealed using cMDH orthologs from marine molluscs native to diverse thermal environments, from Antarctica (−1.9°C) to the South China coast (∼55°C; Liao et al., 2019). The amino acid usage in different regions of the enzyme (surface, intermediate depth and protein core) had a close relationship with the adaptation temperature, illustrating that those regions of the protein surface lying outside of the catalytic site can be important for the evolutionary adaptation of enzymes. Importantly for considerations of how species may evolve to cope with climate change, adaptive variation in cMDH function and structure can result from only a single amino acid change in this 330-residue protein. For example, a single amino acid substitution of a serine at site 291 in the ortholog of cMDH of warm-adapted Lottia austrodigitalis for the glycine found in its cold-adapted congener, L. digitalis, leads to formation of three additional hydrogen bonds that increase the stability of the warm-adapted protein. The higher structural stability of the ortholog of L. austrodigitalis is closely related to the distribution expansion of the southern species in the last decades (Dong and Somero, 2009).

Similar to what has been discovered with the orthologs of proteins, the trade-off between stability and lability of the secondary structure of messenger RNA (mRNA) is also affected by adaptation to environmental temperature. The secondary structures of mRNAs are important in governing several vital mRNA functions, including the rate of elongation, RNA turnover and binding of small RNAs (Dana and Tuller, 2012; Mortimer et al., 2014). Thus, like proteins, mRNAs should maintain appropriate marginal stability for conformational changes that occur at normal body temperature.

In order to investigate the effects of temperature on RNA stability among species, in silico methods have been applied to determine secondary structures and estimate changes in free energy of folding (ΔG_fold) (see Glossary) for orthologous mRNAs of cMDH in 25 marine molluscs with adaptation temperatures spanning an almost 60°C range (Liao et al., 2021b). The differences in ΔG_fold among different mRNA orthologs are related to the differences in the numbers and classes of secondary structure elements (Mathews et al., 1999). The change in ΔG_fold that occurs during the formation of the ensemble of mRNA secondary structures is negative for all orthologs and the absolute value of ΔG_fold increases with adaptation temperature, reflecting increasingly stable secondary structures of mRNA in warm-adapted species (Fig. 3C). As predicted, ΔG_fold significantly correlates with the rate of thermal denaturation of cMDH, which is used as an index of adaptation temperature. The changes in ΔG_fold values are probably caused by a significant increase in synonymous guanine and cytosine substitutions in the mRNA with increasing temperature.

These findings imply that the stability of the secondary structure of mRNA is another important trait underlying thermal adaptation of species. As in the case of proteins, relatively few changes in composition may allow adaptive adjustment of mRNA stability, a finding that is relevant to developing predictions about the potential of species to evolve resistance to rising temperatures. Although it clearly is premature to attempt to predict evolutionary rates based on requirements for changes in amino acid and nucleotide sequence, future examination of proteins and RNAs may assist in clarifying whether adaptive evolution can ‘keep up’ with rising stresses from climate change.

The fitness-related variation in traits of intertidal species commonly exhibits evolved differences among species (e.g. Wolcott, 1973; Compton et al., 2007; Sorte et al., 2018). For intertidal molluscs, physiological variation occurs over both large spatial scales (e.g. latitudinal; Somero, 2005; Kuo and Sanford, 2009; Sorte et al., 2011; Logan et al., 2012; Dong et al., 2015, 2017; Sunday et al., 2019) and small spatial scales (e.g. microhabitat; Dowd et al., 2015; Jimenez et al., 2015; Brahim and Marshall, 2020; Li et al., 2021). Thus, it is important to map the micro-scale physiological landscape across space and time, rather than relying on large-scale averages of temperature and means of thermal limits in a species (Dong et al., 2017; Bates et al., 2018). To illustrate this point, physiological variation of intertidal species at different spatio-temporal scales is discussed below, along with the implications for species distribution patterns.

Geographical patterns of thermal tolerance have been extensively studied in intertidal species across their distribution ranges (e.g. Kuo and Sanford, 2009, Sunday et al., 2019). Species often comprise multiple locally adapted populations with different thermal tolerance limits (Thyrring et al., 2015). Kuo and Sanford (2009) analyzed the upper thermal limits of the intertidal snail Nucella canaliculata from seven sites along the northeastern Pacific coast. Importantly, all these snails were reared through two generations under common garden conditions to remove the potential influence of acclimatization. The authors found that the difference in the upper thermal limit between these populations was likely to be genetically driven, and local temperature conditions played important roles as selective forces.

Although coastlines are generally defined by clear latitudinal gradients, geographical patterns of biotic and abiotic factors usually exhibit mosaics that do not strictly conform to latitudinal gradients, in part because of differences in the timing of the tidal cycle at different latitudes (Helmuth et al., 2006; Gilman et al., 2006). The upper thermal limits of intertidal species also show non-linear relationships with latitudinal gradients and are consistent with the existence of local mosaics of environmental factors (Dwane et al., 2022). For example, the upper thermal limits (as indicated by ABT and FLT of cardiac performance) of three intertidal snail species – Littoraria sinensis, Littorina brevicula and Nerita yoldii – inhabiting mid-latitude locations are higher than those at other, less thermally stressful locations along the Chinese coast (Dong et al., 2017). Because of the high summer air temperature at mid-latitude sites and the timing of low tides during midday, these local populations face more serious thermal stress than those at other latitudes.

Small-scale spatial variation in temperature is an important attribute of many habitats, especially in the intertidal zone where high landscape heterogeneity and highly dynamic environmental conditions are common (Gilman et al., 2006; Helmuth et al., 2006; Denny et al., 2011; Jimenez et al., 2015; Miller and Dowd, 2017; Choi et al., 2019; Sun et al., 2022). The accumulated effect of small-scale ecological processes owing to heterogeneous environments can affect the distribution and abundance of animals occupying different microhabitats (De Frenne et al., 2013; Potter et al., 2013). As an example of the sort of ecological process that might be involved here, specimens of the mussel Mytilus californianus inhabiting a wave-sheltered, ‘protected’, warm microhabitat gape more widely and remain open for longer periods during high tide than their counterparts from a wave-splashed, ‘exposed’, cool microhabitat (Miller and Dowd, 2017).

In intertidal systems, thermal environments are tidal height- and microhabitat-specific. This complex thermal landscape integrates with physiological tolerance limits, setting abundance and zonation (see Glossary) (Stickle et al., 2017). For example, in the face of different thermal environments among microhabitats, the mussel Mytilisepta virgata inhabiting sun-exposed microhabitats frequently encounters lethal thermal stress (Han et al., 2020) and shows a higher upper lethal temperature compared with those in shaded microhabitats; the relatively benign shaded microhabitats serve as refugia, allowing individuals to survive extreme thermal stress (Li et al., 2021). These findings offer a compelling argument for including microhabitat variation in studies designed to predict the effects of climate change. They also illustrate the importance of adaptive behavioral responses that allow an individual to protect its physiological systems from lethal thermal stress.

Small-scale thermal variations at low temperatures can also affect the physiological performance of intertidal species. Reid and Harley (2021) found that the microclimate in sheltered microhabitats is warmer than that of the surrounding exposed areas during winter low tides in a temperate rocky shore. Individuals of the snail Littorina scutulata from the sheltered microhabitats exhibit different behavior performances (e.g. self-righting) and recover more quickly from cold shock compared with those from the exposed areas. These results further confirm that the sheltered microhabitats can act as refugia against extreme thermal stresses both in winter and in summer. Sun et al. (2023) studied the metabolomic responses of the limpet Cellana toreuma living in tidal pools or on the surrounding emergent rock, and found that purine metabolism, energy metabolism, osmoregulation and cellular stress responses exhibited coordinated diurnal changes in the limpet in winter. Microhabitat differences were also discovered. This work shows that metabolic responses that are associated with the cellular stress response and energy metabolism are highly induced in individuals on the emergent rock microhabitat compared with those in the nearby tidal pools.

Acclimatization and hardening can alter the physiological performance of intertidal species during their lifetimes (Bowler, 2005; Thyrring et al., 2017; Moyen et al., 2020). For example, in the Antarctic intertidal zone, the limpet Nacella concinna exhibits seasonal variations in oxygen consumption and nitrogen excretion. Summer-acclimatized limpets have significantly higher rates for both processes relative to winter specimens (Obermüller et al., 2011). Additionally, experiments on a subtropical intertidal mollusc have shown pronounced variations in cardiac function across multiple temporal scales: the ABTs and FLTs of the mussel M. virgata in the cold season are significantly lower than in the warm season (Li et al., 2021), implying that there is acclimatization to the natural thermal environment.

Heat/cold hardening following a sub-lethal thermal exposure can alter thermal limits rapidly. This is important in allowing intertidal species to persist in their thermally variable environment, where they suffer from frequent extreme thermal stress (Dunphy et al., 2018; Moyen et al., 2020). The California mussel M. californianus can acquire enhanced thermal tolerance after a short bout of sublethal heat stress (2 h at 30 or 35°C) and maintain the elevated tolerance for up to 3 weeks. The ‘rapid gain and slow loss’ model is an adaptation to the frequently changing thermal environment on the shore and allows the mussel to survive unpredictable heat events (Moyen et al., 2020). Given that hardening and acclimatization occur over different time scales, they can work together to affect thermal limits. For example, in the razor clam (Sinonovacula constricta), which is found in mudflat habitats, heat hardening induces different strengths of physiological plasticity during different seasons; a stronger heat hardening response occurs in warm seasons (Zhang et al., 2021).

The predictability of the thermal stress is a critical factor in defining the upper thermal limits of intertidal species (Helmuth et al., 2011; Drake et al., 2017; Wang et al., 2020a). Temporal autocorrelation analyses (see Glossary) of the body temperatures of intertidal species show that the predictability of extreme temperatures is lowest at the hottest sites (Helmuth et al., 2011; Dong et al., 2017). Repeated aerial exposure can increase upper thermal limits for the limpet L. digitalis in unpredictable fluctuating environments (Drake et al., 2017), implying that the thermal physiological responses under the ‘natural’ conditions may differ from those observed under experimental conditions. This highlights the importance of investigating the predictability of thermal environments and its impacts on physiological responses, which will have knock-on effects on distribution and abundance (Wang et al., 2020a,b).

The importance of existing genetic variation (and its interaction with physiological variation; see Glossary) in coping with fluctuating temperatures is becoming increasingly apparent. Realistic assessments of the impacts of global warming on population dynamics and distribution ranges are likely to require an integrated analysis of the roles of standing genetic variation and physiological responses (Bridle et al., 2010; Foden et al., 2018; Han et al., 2020; Boardman et al., 2022). Predicting the success of biological invasions is one example of how important combined genetic and physiological studies can be. In many previous studies of biological invasions, individuals or populations have been regarded as genetically and/or physiologically uniform across the species distribution range (e.g. Cronin et al., 2015). However, in a study of the European green crab, Carcinus maenas, Tepolt and Palumbi (2015) found that newly established invasive populations are genetically different from the native populations. Moreover, cardiac thermal responses show significant variation among populations, which may stem from a combination of genetic differences and acclimatization effects (Tepolt and Somero, 2014). During species range shifts, natural selection or genetic drift (see Glossary) can alter the mean phenotype, thus affecting initial population settlement and subsequent establishment (Whitney and Gabler, 2008; Hu and Dong, 2022). Therefore, it is important to consider genetic information and evolutionary potential when evaluating and predicting species distributions (Razgour, 2015; Dong et al., 2022b).

Genetic structures of natural populations are highly variable across multiple spatiotemporal scales. For example, the genetic diversity and structure of the black mussel (M. virgatus) differ significantly across different seasons on a subtropical shore in China (Han et al., 2020). For this species, inter-individual variation in thermal tolerance correlates significantly with genetic differences at some specific gene loci, and heterozygotes have higher thermal tolerances than homozygotes (Han et al., 2020). The observed seasonal changes in genotype frequency suggest that these loci are under balancing selection (see Glossary). The ability of thermally resistant heterozygotes to survive in sun-exposed microhabitats acts to balance the loss of homozygotes during summer and enables the persistence of genetic polymorphisms (Han et al., 2020). Population persistence of the mussel is also facilitated by the micro-scale variation in temperature, which provides refugia from thermal stress. Adaptive synonymous mutations can also affect the upper thermal limits of the black mussels by adjusting gene expression profiles (Tan et al., 2023).

These results emphasize several important points. First, reliance on average values for species' thermal responses and habitat temperature masks important sources of biological and microhabitat variation. Second, genetic heterogeneity may be crucial in establishing a population's ability to persist in a habitat, and this genetic variation may play different roles across time (e.g. seasons) and space (e.g. microhabitat heterogeneity). These observations thus highlight the importance of incorporating variations in habitat, physiology and genetics into analyses of the causal relationships that govern species distributions.

In the face of climate change and large-scale alterations in land use, the biogeographic patterns of intertidal species along the Chinese coast are experiencing dramatic changes. For example, some southern species are moving northward across former biogeographic barriers; consequently, a new biogeographic pattern is emerging (Dong et al., 2016; Wang et al., 2020b; Hu and Dong, 2021). The high diversity of intertidal communities and the northward shift of intertidal species along the coast of China make the intertidal flora and fauna of this region an excellent model system for evaluating and predicting the impacts of climate change and land-use change on species distributions.

The snail Nerita yoldii has extended its northward distribution limit by ∼200 km along China's coastline in recent decades (Fig. 4A), and it has established new marginal populations on the artificial structures built at mid-latitude sites along the coastline. Subsequently, a few more species, such as the Kumamoto oyster (Crassostrea sikamea), have also been recorded as extending their distributions northward along China's coast (Hu and Dong, 2022).

During the northward distribution expansion of N. yoldii, a few snails served as founders in the establishment of the new north marginal populations (Fig. 4B). Physiological analyses show that the new marginal populations have divergent responses from the southern native populations (Fig. 4C). Using maximum heart rate as a proxy for physiological differences among populations, the most recently colonized population has the highest maximal heart rate. The values of ABT and FLT are also significantly different among populations, and the new marginal populations have higher upper thermal limits than the southern population. These results shed light on the phylogeographic structure and physiological and molecular responses of the marginal population during the range shift of intertidal species (Wang et al., 2022), and illustrate clearly the complex interplay among habitat variation, on the one hand, and physiological and genetic variation, on the other hand, in determining where a species can survive.

Through the lens of ecological physiology, we can determine physiological responses at the individual level and then use these data to calculate thermal sensitivity at the population and species levels. The addition of high-resolution environmental data on microhabitat variation and extreme temperature events such as heat waves will allow us to map thermal sensitivity more accurately than would be possible using mean values alone. Three considerations are of particular importance in this context.

Firstly, future climates will have more variability and more frequent extreme events, so it is important to evaluate and predict the impacts of extreme events (e.g. heat waves and cold spells) and their predictability on the thermal limits of organisms. To achieve this goal, we need to translate the environmental temperature to body temperature, to allow us to establish global, regional and local body temperature datasets using both model simulations (e.g. heat budget models, Denny, 2016) and in situ measurements (e.g. Helmuth et al., 2016). By using these datasets, we can analyze the trend of warming and the occurrence of heat waves that can directly affect the physiological activity of organisms. Another important application of these datasets is to predict hotspots and refugia at different geographical scales. These hotspots (locations with low thermal resistance and resilience) and refugia (locations with high thermal resistance and resilience) should receive special attention because of their importance for individual survival, population dynamics and community structure.

Secondly, spatial and temporal variations of thermal environments at the microhabitat scale should be considered for evaluating and predicting the impacts of climate change on species distributions. Ecological and physiological studies have shown that intertidal species living in various microhabitats face different levels of thermal stress, and that benign microhabitats (e.g. shaded microhabitats) can act as ‘refugia’ at the microhabitat scale, allowing individuals to cope with thermal stress (Dong et al., 2017; Miller and Dowd, 2017). If we fail to consider spatial and temporal variations of thermal environments, especially the ecological impacts of benign ‘refugia’, we may potentially overestimate the impacts of climate change. Thus, in addition to monitoring and analyzing the changes in large-scale thermal environments, we need to establish datasets on the microhabitat-scale thermal environment.

Thirdly, physiological responses often have high plasticity at different levels of biological organization, from the individual to the population to the species (Dong et al., 2022a). Plasticity has an important temporal element as well. Acclimatization rates may vary across species and processes; hardening responses are especially rapid adjustments that can increase thermal tolerance. Indeed, a clearer delineation of how the changes that occur during acclimatization differ from those induced during hardening should be a priority for physiologists, in order to better characterize the temporal aspects of the response to thermal stress. Indeed, all forms of plasticity can affect the thermal resilience of organisms. Plasticity at all levels of biological organization is thus another issue that needs to be considered to allow us to evaluate and forecast species' distributions in the context of climate change. In order to consider physiological variation across different levels, appropriate statistical models should be developed and applied. For example, kernel density estimation is a method used to study the characteristics of data distribution from the data sample itself (Chen, 2017; Zhang et al., 2023). This type of statistical analysis, in concert with other experimental approaches outlined above, may allow us to establish strong causal linkages between environmental change – notably in temperature – and species distributions and physiological status. These analyses will not only allow mechanistic understanding of species range patterns, but will also provide a basis for predicting the consequences of ongoing global change.

I thank Prof. George Somero and three referees for their constructive suggestions and discussions, and Drs Ming-Ling Liao, Jie Wang, Li-sha Hu and Yue Tan for preparing the figures.