Predictions of response to temperature are contingent on model choice and data quality

No universal mathematical model for thermal performance curves across traits and taxonomic groups

In ectotherms, the performance of physiological, ecological and life-history traits universally increases with temperature to a maximum before decreasing again. Identifying the most appropriate thermal performance model for a specific trait type has broad applications, from metabolic modelling at the cellular level to forecasting the effects of climate change on population, ecosystem and disease transmission dynamics. To date, numerous mathematical models have been designed, but a thorough comparison among them is lacking. In particular, we do not know if certain models consistently outperform others and how factors such as sampling resolution and trait or organismal identity influence model performance. To fill this knowledge gap, we compile 2,739 thermal performance datasets from diverse traits and taxa, to which we fit a comprehensive set of 83 existing mathematical models. We detect remarkable variation in model performance that is not primarily driven by sampling resolution, trait type, or taxonomic information. Our results reveal a surprising lack of well-defined scenarios in which certain models are more appropriate than others. To aid researchers in selecting the appropriate set of models for any given dataset or research objective, we derive a classification of the 83 models based on the average similarity of their fits.

Pushing the limits: expanding the temperature tolerance of a coral photosymbiont through differing selection regimes

Coral thermal bleaching resilience can be improved by enhancing photosymbiont thermal tolerance via experimental evolution. While successful for some strains, selection under stable temperatures was ineffective at increasing the thermal threshold of an already thermo-tolerant photosymbiont (Durusdinium trenchii). Corals from environments with fluctuating temperatures tend to have comparatively high heat tolerance. Therefore, we investigated whether exposure to temperature oscillations can raise the upper thermal limit of D. trenchii. We exposed a D. trenchii strain to stable and fluctuating temperature profiles, which varied in oscillation frequency. After 2.1 yr (54-73 generations), we characterised the adaptive responses under the various experimental evolution treatments by constructing thermal performance curves of growth from 21 to 31°C for the heat-evolved and wild-type lineages. Additionally, the accumulation of extracellular reactive oxygen species, photophysiology, photosynthesis and respiration rates were assessed under increasing temperatures. Of the fluctuating temperature profiles investigated, selection under the most frequent oscillations (diurnal) induced the greatest widening of D. trenchii's thermal niche. Continuous selection under elevated temperatures induced the only increase in thermal optimum and a degree of generalism. Our findings demonstrate how differing levels of thermal homogeneity during selection drive unique adaptive responses to heat in a coral photosymbiont.

Model-driven insights into the effects of temperature on metabolism

Temperature affects cellular processes at different spatiotemporal scales, and identifying the genetic and molecular mechanisms underlying temperature responses paves the way to develop approaches for mitigating the effects of future climate scenarios. A systems view of the effects of temperature on cellular physiology can be obtained by focusing on metabolism since: (i) its functions depend on transcription and translation and (ii) its outcomes support organisms' development, growth, and reproduction. Here we provide a systematic review of modelling efforts directed at investigating temperature effects on properties of single biochemical reactions, system-level traits, metabolic subsystems, and whole-cell metabolism across different prokaryotes and eukaryotes. We compare and contrast computational approaches and theories that facilitate modelling of temperature effects on key properties of enzymes and their consideration in constraint-based as well as kinetic models of metabolism. In addition, we provide a summary of insights from computational approaches, facilitating integration of omics data from temperature-modulated experiments with models of metabolic networks, and review the resulting biotechnological applications. Lastly, we provide a perspective on how different types of metabolic modelling can profit from developments in machine learning and models of different cellular layers to improve model-driven insights into the effects of temperature relevant for biotechnological applications.

Thermal trait variation may buffer Southern Ocean phytoplankton from anthropogenic warming

Despite the potential of standing genetic variation to rescue communities and shape future adaptation to climate change, high levels of uncertainty are associated with intraspecific trait variation in marine phytoplankton. Recent model intercomparisons have pointed to an urgent need to reduce uncertainty in the projected responses of marine ecosystems to climate change, including Southern Ocean (SO) surface waters, which are among the most rapidly warming habitats on Earth. Because SO phytoplankton growth responses to warming sea surface temperature (SST) are poorly constrained, we developed a high-throughput growth assay to simultaneously examine inter- and intra-specific thermal trait variation in a group of 43 taxonomically diverse and biogeochemically important SO phytoplankton called diatoms. We found significant differential growth performance among species across thermal traits, including optimum and maximum tolerated growth temperatures. Within species, coefficients of variation ranged from 3% to 48% among strains for those same key thermal traits. Using SO SST projections for 2100, we predicted biogeographic ranges that differed by up to 97% between the least and most tolerant strains for each species, illustrating the role that strain-specific differences in temperature response can play in shaping predictions of future phytoplankton biogeography. Our findings revealed the presence and scale of thermal trait variation in SO phytoplankton and suggest these communities may already harbour the thermal trait diversity required to withstand projected 21st-century SST change in the SO even under severe climate forcing scenarios.

Patterns of thermal adaptation in a globally distributed plant pathogen: Local diversity and plasticity reveal two-tier dynamics

Plant pathogen populations inhabit patchy environments with contrasting, variable thermal conditions. We investigated the diversity of thermal responses in populations sampled over contrasting spatiotemporal scales, to improve our understanding of their dynamics of adaptation to local conditions. Samples of natural populations of the wheat pathogen Zymoseptoria tritici were collected from sites within the Euro-Mediterranean region subject to a broad range of climatic conditions. We tested for local adaptation, by accounting for the diversity of responses at the individual and population levels on the basis of key thermal performance curve parameters and "thermotype" (groups of individuals with similar thermal responses) composition. The characterization of phenotypic responses and genotypic structure revealed the following: (i) a high degree of individual plasticity and variation in sensitivity to temperature conditions across spatiotemporal scales and populations; and (ii) geographic variation in thermal response among populations, with major alterations due to seasonal patterns over the wheat-growing season. The seasonal shifts in functional composition suggest that populations are locally structured by selection, contributing to adaptation patterns. Further studies combining selection experiments and modeling are required to determine how functional group selection drives population dynamics and adaptive potential in response to thermal heterogeneity.

Variation in thermal performance curves for oxygen consumption and loss of critical behaviors in co-occurring species indicate the potential for ecosystem stability under ocean warming

Species-level differences in responses to environmental factors may increase a community's ability to retain key functions under environmental change. We compared the oxygen consumption rates and maintenance of critical behaviors for three co-occurring intertidal gastropod species over a temperature range of 30 °C. Each species exhibited a distinct thermal performance curve (TPC) for oxygen consumption. The TPC of Lunella granulata was horizontally shifted to be significantly warmer than that of Chlorostoma argyrostoma. Monodonta labio's TPC was vertically shifted compared to the other two species, reflecting greater oxygen consumption overall. L. granulata and M. labio maintained critical behaviors at temperatures 3-5 °C warmer than C. argyrostoma. These differences in the thermal tolerances of similar, co-occurring species provide space for the insurance effect of biodiversity to occur. Understanding the degree to which co-occurring species respond differently to increased temperature may help us predict community resistance in the face of climate change.

Phytoplankton mortality in a changing thermal seascape

Predicting spatiotemporal distributions of phytoplankton biomass and community composition heavily relies on experimental studies that document how environmental conditions influence population growth rates. In unicellular phytoplankton, the net population growth rate is the difference between the cell division rate and the death rate. Along with predation and disease, phytoplankton mortality arises from abiotic stress. Although the effect of temperature on the net population growth rate is well understood, studies examining thermally induced death rates in phytoplankton are scarce. We investigated how cell division and death rates of the diatom Phaeodactylum tricornutum varied within its thermal tolerance limits (thermal niche), and at temperatures just above its upper thermal tolerance limit. We show that death rates were largely independent of temperature when P. tricornutum was grown within its thermal niche, but increased significantly at temperatures that approached or exceeded its upper thermal tolerance limit. Furthermore, the sensitivity of mortality increased with the duration of exposure to heat stress and was affected by the pre-acclimation temperature. Heat waves can be expected to significantly affect phytoplankton mortality episodically. The increasing frequency of heat waves accompanying global warming can be expected to drive changes in phytoplankton community structure due to interspecific variability of thermal niches with potential implications for food web dynamics and biogeochemical cycles.

Antibiotics Shift the Temperature Response Curve of Escherichia coli Growth

Temperature variation-through time and across climatic gradients-affects individuals, populations, and communities. Yet how the thermal response of biological systems is altered by environmental stressors is poorly understood. Here, we quantify two key features-optimal temperature and temperature breadth-to investigate how temperature responses vary in the presence of antibiotics. We use high-throughput screening to measure growth of Escherichia coli under single and pairwise combinations of 12 antibiotics across seven temperatures that range from 22°C to 46°C. We find that antibiotic stress often results in considerable changes in the optimal temperature for growth and a narrower temperature breadth. The direction of the optimal temperature shifts can be explained by the similarities between antibiotic-induced and temperature-induced damage to the physiology of the bacterium. We also find that the effects of pairs of stressors in the temperature response can often be explained by just one antibiotic out of the pair. Our study has implications for a general understanding of how ecological systems adapt and evolve to environmental changes. IMPORTANCE The growth of living organisms varies with temperature. This dependence is described by a temperature response curve that is described by an optimal temperature where growth is maximized and a temperature range (termed breadth) across which the organism can grow. Because an organism's temperature response evolves or acclimates to its environment, it is often assumed to change over only evolutionary or developmental timescales. Counter to this, we show here that antibiotics can quickly (over hours) change the optimal growth temperature and temperature breadth for the bacterium Escherichia coli. Moreover, our results suggest a shared-damage hypothesis: when an antibiotic damages similar cellular components as hot (or cold) temperatures do, this shared damage will combine and compound to more greatly reduce growth when that antibiotic is administered at hot (or cold) temperatures. This hypothesis could potentially also explain how temperature responses are modified by stressors other than antibiotics.

Projected expansion of Trichodesmium's geographical distribution and increase in growth potential in response to climate change

Estimates of marine N₂ fixation range from 52 to 73 Tg N/year, of which we calculate up to 84% is from Trichodesmium based on previous measurements of nifH gene abundance and our new model of Trichodesmium growth. Here, we assess the likely effects of four major climate change-related abiotic factors on the spatiotemporal distribution and growth potential of Trichodesmium for the last glacial maximum (LGM), the present (2006-2015) and the end of this century (2100) by mapping our model of Trichodesmium growth onto inferred global surface ocean fields of pCO₂ , temperature, light and Fe. We conclude that growth rate was severely limited by low pCO₂ at the LGM, that current pCO₂ levels do not significantly limit Trichodesmium growth and thus, the potential for enhanced growth from future increases in CO₂ is small. We also found that the area of the ocean where sea surface temperatures (SST) are within Trichodesmium's thermal niche increased by 32% from the LGM to present, but further increases in SST due to continued global warming will reduce this area by 9%. However, the range reduction at the equator is likely to be offset by enhanced growth associated with expansion of regions with optimal or near optimal Fe and light availability. Between now and 2100, the ocean area of optimal SST and irradiance is projected to increase by 7%, and the ocean area of optimal SST, irradiance and iron is projected to increase by 173%. Given the major contribution of this keystone species to annual N₂ fixation and thus pelagic ecology, biogeochemistry and CO₂ sequestration, the projected increase in the geographical range for optimal growth could provide a negative feedback to increasing atmospheric CO₂ concentrations.

High predictability of direct competition between marine diatoms under different temperatures and nutrient states

The distribution of marine phytoplankton will shift alongside changes in marine environments, leading to altered species frequencies and community composition. An understanding of the response of mixed populations to abiotic changes is required to adequately predict how environmental change may affect the future composition of phytoplankton communities. This study investigated the growth and competitive ability of two marine diatoms, Phaeodactylum tricornutum and Thalassiosira pseudonana, along a temperature gradient (9-35°C) spanning the thermal niches of both species under both high-nitrogen nutrient-replete and low-nitrogen nutrient-limited conditions. Across this temperature gradient, the competitive outcome under both nutrient conditions at any assay temperature, and the critical temperature at which competitive advantage shifted from one species to the other, was well predicted by the temperature dependencies of the growth rates of the two species measured in monocultures. The temperature at which the competitive advantage switched from P. tricornutum to T. pseudonana increased from 18.8°C under replete conditions to 25.3°C under nutrient-limited conditions. Thus, P. tricornutum was a better competitor over a wider temperature range in a low N environment. Being able to determine the competitive outcomes from physiological responses of single species to environmental changes has the potential to significantly improve the predictive power of phytoplankton spatial distribution and community composition models.

Avian influenza virus prevalence in marine birds is dependent on ocean temperatures

Waterfowl and shorebirds are the primary hosts of influenza A virus (IAV), however, in most surveillance efforts, large populations of birds are not routinely examined; specifically marine ducks and other birds that reside predominately on or near the ocean. We conducted a long-term study sampling sea ducks and gulls in coastal Maine for IAV and found a virus prevalence (1.7%) much lower than is typically found in freshwater duck populations. We found wide year-to-year variation in virus detection in sea ducks and that the ocean water temperature was an important factor affecting IAV prevalence. In particular, the ocean temperature that occurred 11 d prior to collecting virus positive samples was important while water temperature measured concurrently with host sampling had no explanatory power for viral detection. We also experimentally showed that IAV is relatively unstable in sea water at temperatures typically found during our sampling. This represents the first report of virus prevalence and actual environmental data that help explain the variation in marine IAV transmission dynamics.

Phenotyping Thermal Responses of Yeasts and Yeast-like Microorganisms at the Individual and Population Levels: Proof-of-Concept, Development and Application of an Experimental Framework to a Plant Pathogen

Deciphering the responses of microbial populations to spatiotemporal changes in their thermal environment is instrumental in improving our understanding of their eco-evolutionary dynamics. Recent studies have shown that current phenotyping protocols do not adequately address all dimensions of phenotype expression. Therefore, these methods can give biased assessments of sensitivity to temperature, leading to misunderstandings concerning the ecological processes underlying thermal plasticity. We describe here a new robust and versatile experimental framework for the accurate investigation of thermal performance and phenotypic diversity in yeasts and yeast-like microorganisms, at the individual and population levels. In addition to proof-of-concept, the application of this framework to the fungal wheat pathogen Zymoseptoria tritici resulted in detailed characterisations for this yeast-like microorganism of (i) the patterns of temperature-dependent changes in performance for four fitness traits; (ii) the consistency in thermal sensitivity rankings of strains between in planta and in vitro growth assessments; (iii) significant interindividual variation in thermal responses, with four principal thermotypes detected in a sample of 66 strains; and (iv) the ecological consequences of this diversity for population-level processes through pairwise competition experiments highlighting temperature-dependent outcomes. These findings extend our knowledge and ability to quantify and categorise the phenotypic heterogeneity of thermal responses. As such, they lay the foundations for further studies elucidating local adaptation patterns and the effects of temperature variations on eco-evolutionary and epidemiological processes.

Picoeukaryotes of the Micromonas genus: sentinels of a warming ocean

Photosynthetic picoeukaryotesx in the genus Micromonas show among the widest latitudinal distributions on Earth, experiencing large thermal gradients from poles to tropics. Micromonas comprises at least four different species often found in sympatry. While such ubiquity might suggest a wide thermal niche, the temperature response of the different strains is still unexplored, leaving many questions as for their ecological success over such diverse ecosystems. Using combined experiments and theory, we characterize the thermal response of eleven Micromonas strains belonging to four species. We demonstrate that the variety of specific responses to temperature in the Micromonas genus makes this environmental factor an ideal marker to describe its global distribution and diversity. We then propose a diversity model for the genus Micromonas, which proves to be representative of the whole phytoplankton diversity. This prominent primary producer is therefore a sentinel organism of phytoplankton diversity at the global scale. We use the diversity within Micromonas to anticipate the potential impact of global warming on oceanic phytoplankton. We develop a dynamic, adaptive model and run forecast simulations, exploring a range of adaptation time scales, to probe the likely responses to climate change. Results stress how biodiversity erosion depends on the ability of organisms to adapt rapidly to temperature increase.

Predictions of response to temperature are contingent on model choice and data quality

The equations used to account for the temperature dependence of biological processes, including growth and metabolic rates, are the foundations of our predictions of how global biogeochemistry and biogeography change in response to global climate change. We review and test the use of 12 equations used to model the temperature dependence of biological processes across the full range of their temperature response, including supra- and suboptimal temperatures. We focus on fitting these equations to thermal response curves for phytoplankton growth but also tested the equations on a variety of traits across a wide diversity of organisms. We found that many of the surveyed equations have comparable abilities to fit data and equally high requirements for data quality (number of test temperatures and range of response captured) but lead to different estimates of cardinal temperatures and of the biological rates at these temperatures. When these rate estimates are used for biogeographic predictions, differences between the estimates of even the best-fitting models can exceed the global biological change predicted for a decade of global warming. As a result, studies of the biological response to global changes in temperature must make careful consideration of model selection and of the quality of the data used for parametrizing these models.