Real versus Artificial Variation in the Thermal Sensitivity of Biological Traits

Metabolic plasticity drives mismatches in physiological traits between prey and predator

Metabolic rate, the rate of energy use, underpins key ecological traits of organisms, from development and locomotion to interaction rates between individuals. In a warming world, the temperature-dependence of metabolic rate is anticipated to shift predator-prey dynamics. Yet, there is little real-world evidence on the effects of warming on trophic interactions. We measured the respiration rates of aquatic larvae of three insect species from populations experiencing a natural temperature gradient in a large-scale mesocosm experiment. Using a mechanistic model we predicted the effects of warming on these taxa's predator-prey interaction rates. We found that species-specific differences in metabolic plasticity lead to mismatches in the temperature-dependence of their relative velocities, resulting in altered predator-prey interaction rates. This study underscores the role of metabolic plasticity at the species level in modifying trophic interactions and proposes a mechanistic modelling approach that allows an efficient, high-throughput estimation of climate change threats across species pairs.

Hotter is not (always) better: Embracing unimodal scaling of biological rates with temperature

Rate-temperature scaling relationships have fascinated biologists for nearly two centuries and are increasingly important in our era of global climate change. These relationships are hypothesized to originate from the temperature-dependent kinetics of rate-limiting biochemical reactions of metabolism. Several prominent theories have formalized this hypothesis using the Arrhenius model, which characterizes a monotonic temperature dependence using an activation energy E. However, the ubiquitous unimodal nature of biological temperature responses presents important theoretical, methodological, and conceptual challenges that restrict the promise for insight, prediction, and progress. Here we review the development of key hypotheses and methods for the temperature-scaling of biological rates. Using simulations, we examine the constraints of monotonic models, illustrating their sensitivity to data nuances such as temperature range and noise, and their tendency to yield variable and underestimated E, with critical consequences for climate change predictions. We also evaluate the behaviour of two prominent unimodal models when applied to incomplete and noisy datasets. We conclude with recommendations for resolving these challenges in future research, and advocate for a shift to unimodal models that better characterize the full range of biological temperature responses.

Fast Assimilation-Temperature Response: a FAsTeR method for measuring the temperature dependence of leaf-level photosynthesis

We present the Fast Assimilation-Temperature Response (FAsTeR) method, a new method for measuring plant assimilation-temperature (AT) response that reduces measurement time and increases data density compared with conventional methods. The FAsTeR method subjects plant leaves to a linearly increasing temperature ramp while taking rapid, nonequilibrium measurements of gas exchange variables. Two postprocessing steps are employed to correct measured assimilation rates for nonequilibrium effects and sensor calibration drift. Results obtained with the new method are compared with those from two conventional stepwise methods. Our new method accurately reproduces results obtained from conventional methods, reduces measurement time by a factor of c. 3.3 (from c. 90 to 27 min), and increases data density by a factor of c. 55 (from c. 10 to c. 550 observations). Simulation results demonstrate that increased data density substantially improves confidence in parameter estimates and drastically reduces the influence of noise. By improving measurement speed and data density, the FAsTeR method enables users to ask fundamentally new kinds of ecological and physiological questions, expediting data collection in short-field campaigns, and improving the representativeness of data across species in the literature.

Thermal sensitivity of black corals (Antipatharia: Hexacorallia): Comparisons between sympatric species from a thermally fluctuating site in Madagascar and between allopatric congenerics

This study investigated factors shaping the thermal sensitivity in antipatharians, a taxon whose members form dense aggregations in all oceans, harbouring a high biodiversity. First, we tested the thermal responses of five sympatric species (Antipathes grandis, Cupressopathes abies, Stichopathes cf. maldivensis, Cirrhipathes anguina and Cirrhipathes cf. spiralis) from the Great Reef of Toliara (Madagascar), using an acute ramping methodology. We then compared the thermal performance curves (TPCs) for oxygen consumption of these five species. Results indicated that phylogeny alone does not explain differences in thermal sensitivity (Antipathidae vs. Myriopathidae). On the contrary, morphology (branched vs. unbranched) appeared as a key factor, with unbranched species (S. cf. maldivensis, C. anguina, C. cf. spiralis) being more tolerant to thermal stress than branched ones (A. grandis and C. abies). Several hypothesis could explain these variations in thermal tolerance across morphology, such as tissue thickness, surface/volume ratio or mass-transfer efficiency. Secondly, we compared the TPC of Stichopathes from Madagascar with those previously obtained in congenerics from the Canary Islands and French Polynesia. This revealed a higher thermal tolerance in the two former than in the latter. It is proposed that it is linked to higher annual temperature variability (but not daily variability) in these two sites compared to French Polynesia. It is concluded that thermal sensitivity in antipatharians is linked to their morphology influencing their physiology and to their thermal history. Phylogeny at the family level plays a less important role in explaining differences in thermal sensitivity in antipatharians.

Local thermal adaptation and local temperature regimes drive the performance of a parasitic helminth under climate change: The case of Marshallagia marshalli from wild ungulates

Across a species' range, populations are exposed to their local thermal environments, which on an evolutionary scale, may cause adaptative differences among populations. Helminths often have broad geographic ranges and temperature-sensitive life stages but little is known about whether and how local thermal adaptation can influence their response to climate change. We studied the thermal responses of the free-living stages of Marshallagia marshalli, a parasitic nematode of wild ungulates, along a latitudinal gradient. We first determine its distribution in wild sheep species in North America. Then we cultured M. marshalli eggs from different locations at temperatures from 5 to 38°C. We fit performance curves based on the metabolic theory of ecology to determine whether development and mortality showed evidence of local thermal adaptation. We used parameter estimates in life-cycle-based host-parasite models to understand how local thermal responses may influence parasite performance under general and location-specific climate-change projections. We found that M. marshalli has a wide latitudinal and host range, infecting wild sheep species from New Mexico to Yukon. Increases in mortality and development time at higher temperatures were most evident for isolates from northern locations. Accounting for location-specific parasite parameters primarily influenced the magnitude of climate change parasite performance, while accounting for location-specific climates primarily influenced the phenology of parasite performance. Despite differences in development and mortality among M. marshalli populations, when using site-specific climate change projections, there was a similar magnitude of impact on the relative performance of M. marshalli among populations. Climate change is predicted to decrease the expected lifetime reproductive output of M. marshalli in all populations while delaying its seasonal peak by approximately 1 month. Our research suggests that accurate projections of the impacts of climate change on broadly distributed species need to consider local adaptations of organisms together with local temperature profiles and climate projections.

Landscape resistance index aiming at functional forest connectivity

Resistance models may quantify the ability of the landscape to impede species' movement and represent suitable habitats. Moreover, the performance of resistance models parameterized by land-use/land cover attributes evidence that the integrity of the environments subject to urban sprawl is poorly understood. In this sense, the study assumed we could identify the forest functional connectivity in a landscape considering the disparity in the landscape mosaic. In this context, we sought to develop a landscape resistance index through structural equation modeling (SEM), supported by the criteria of heat emission, biomass, and anthropogenic barriers, obtained by remote sensing, called observed variables. The landscape studied in the Green Belt Biosphere Reserve of São Paulo has significant remnants of the Atlantic Forest, a biodiversity hotspot. However, our results indicated criteria variability in the landscape modeled through the SEM, obtaining a significant adjustment of the landscape resistance index, with comparative fit index (CFI) of 1.00 and root mean square error of approximation (RMSEA) of 0.00. The index reflects the resistance levels of the land use/land cover, expressed by the class interval, ranging from 0% (1.73) to 100% (493.88), with the highest values associated with the anthropized uses and forest isolation. Thus, our index based on environmental attributes reflects the structure of functional forest connectivity and offers a framework to design forest corridors across landscapes.

Thermal dependence of Daphnia life history reveals asymmetries between key vital rates

Temperature variation affects virtually every aspect of ectotherms' ecological performance, such as their foraging rate, reproduction, and survival. Although these changes influence what happens at higher levels of organizations, such as populations and communities, qualitative changes in dynamics usually require some degree of asymmetry between key vital rates, i.e. that different vital rates, such as growth, development, fecundity and mortality rates, respond differently to temperature. In order to identify possible asymmetries among vital rates and/or life stages, we characterized the thermal response of individuals a clone of Daphnia sinensis, drawn from a high-mountain environment in Taiwan, and examined the temperature dependence of growth, maturation, reproduction, and mortality rates, as well as fitness measures (r and R₀) at eight temperatures. Daphnia sinensis was able to maintain reproductive success over a broad range of temperatures, much wider than the one experienced in its environment. However, negative effects of temperature were perceptible at temperatures much lower than the highest one at which they can achieve reproductive success. Adult mortality greatly increased for temperatures above 23 °C, and other vital rates started to decelerate, resulting in a large drop in lifetime reproductive success. This finding implies that D. sinensis may be able to persist over a wide range of temperatures, but also that it may become more sensitive to the detrimental effect of species interactions at increased temperatures. Different vital rates responded relatively similarly at low temperatures, but the degree of asymmetry among these rates was much more pronounced at higher temperatures. In particular, rates associated with adult performance decelerated more strongly than juveniles' rates. These findings indicate that elevated temperatures affect the balance between juvenile and adult performance, which is known to have a crucial role in Daphnia population dynamics. We discuss the implications of these results for the dynamics of structured populations.

Latent functional diversity may accelerate microbial community responses to temperature fluctuations

How complex microbial communities respond to climatic fluctuations remains an open question. Due to their relatively short generation times and high functional diversity, microbial populations harbor great potential to respond as a community through a combination of strain-level phenotypic plasticity, adaptation, and species sorting. However, the relative importance of these mechanisms remains unclear. We conducted a laboratory experiment to investigate the degree to which bacterial communities can respond to changes in environmental temperature through a combination of phenotypic plasticity and species sorting alone. We grew replicate soil communities from a single location at six temperatures between 4°C and 50°C. We found that phylogenetically and functionally distinct communities emerge at each of these temperatures, with K-strategist taxa favored under cooler conditions and r-strategist taxa under warmer conditions. We show that this dynamic emergence of distinct communities across a wide range of temperatures (in essence, community-level adaptation) is driven by the resuscitation of latent functional diversity: the parent community harbors multiple strains pre-adapted to different temperatures that are able to ‘switch on’ at their preferred temperature without immigration or adaptation. Our findings suggest that microbial community function in nature is likely to respond rapidly to climatic temperature fluctuations through shifts in species composition by resuscitation of latent functional diversity.

Catalytic efficiency of soil enzymes explains temperature sensitivity: Insights from physiological theory

Soil enzymes are crucial for carbon and nutrient cycling and are highly sensitive to warming. Biochemical reaction rates increase with temperature according to the Arrhenius law, but changes in microbial physiology may partially counteract this warming-induced acceleration that leads enzymatic rates to deviate from Arrhenius law. Here, we attempt to reconcile disparate views on the enzyme responses to warming based on the Arrhenius law and physiological theory by enzyme catalytic efficiency. In this study, we tested the kinetic parameters of five key enzymes of C, N, and P cycling to warming (from 0 to 40 °C) in cropland soils originating from 5 different temperate zones. The soils were incubated for one month at 0, 10, 20, 30, and 40 °C (±0.5 °C) with 60% water holding capacity (WHC). The kinetic parameters were calculated and measured at a range of 4-methyumbelliferone (MUB)-substrate concentrations. We found that catalytic efficiency (V_max/K_m) of individual enzymes ranged from 0.05 to 27 s^-1 between 0 and 40 °C. Maximum reaction rate (V_max) increased with warming, while V_max/K_m of most enzymes remained stable by warming at low temperatures (up to 10 °C), and it raised from 20 to 40 °C. Most enzymes had lower substrate affinities (K_m) and increased their efficiency with warming. Consistent with studies considering Arrhenius law solely, the temperature sensitivity (Q₁₀) of V_max decreased with warming. However, the Q₁₀ of V_max/K_m displayed a lower value in the cold but a higher value in warmer temperature, which confirmed microbial adaptation based on physiological theory, consequently encouraging its linking with the Arrhenius law. Therefore, Arrhenius linked with physiological theory could correct explanation of enzyme activities by warming. Considering the microbial adaptation to temperature, the present predicted warming-induced acceleration of soil organic matter decomposition might be overestimated in cold and underestimated in warm environments.

Optimum growth temperature declines with body size within fish species

According to the temperature-size rule, warming of aquatic ecosystems is generally predicted to increase individual growth rates but reduce asymptotic body sizes of ectotherms. However, we lack a comprehensive understanding of how growth and key processes affecting it, such as consumption and metabolism, depend on both temperature and body mass within species. This limits our ability to inform growth models, link experimental data to observed growth patterns, and advance mechanistic food web models. To examine the combined effects of body size and temperature on individual growth, as well as the link between maximum consumption, metabolism, and body growth, we conducted a systematic review and compiled experimental data on fishes from 52 studies that combined body mass and temperature treatments. By fitting hierarchical models accounting for variation between species, we estimated how maximum consumption and metabolic rate scale jointly with temperature and body mass within species. We found that whole-organism maximum consumption increases more slowly with body mass than metabolism, and is unimodal over the full temperature range, which leads to the prediction that optimum growth temperatures decline with body size. Using an independent dataset, we confirmed this negative relationship between optimum growth temperature and body size. Small individuals of a given population may, therefore, exhibit increased growth with initial warming, whereas larger conspecifics could be the first to experience negative impacts of warming on growth. These findings help advance mechanistic models of individual growth and food web dynamics and improve our understanding of how climate warming affects the growth and size structure of aquatic ectotherms.

The effects of phylogeny, habitat and host characteristics on the thermal sensitivity of helminth development

Helminth parasites are part of almost every ecosystem, with more than 300 000 species worldwide. Helminth infection dynamics are expected to be altered by climate change, but predicting future changes is difficult owing to lacking thermal sensitivity data for greater than 99.9% of helminth species. Here, we compiled the largest dataset to date on helminth temperature sensitivities and used the Metabolic Theory of Ecology to estimate activation energies (AEs) for parasite developmental rates. The median AE for 129 thermal performance curves was 0.67, similar to non-parasitic animals. Although exceptions existed, related species tended to have similar thermal sensitivities, suggesting some helminth taxa are inherently more affected by rising temperatures than others. Developmental rates were more temperature-sensitive for species from colder habitats than those from warmer habitats, and more temperature sensitive for species in terrestrial than aquatic habitats. AEs did not depend on whether helminth life stages were free-living or within hosts, whether the species infected plants or animals, or whether the species had an endotherm host in its life cycle. The phylogenetic conservatism of AE may facilitate predicting how temperature change affects the development of helminth species for which empirical data are lacking or difficult to obtain.

Increasing temperature weakens the positive effect of genetic diversity on population growth

Genetic diversity and temperature increases associated with global climate change are known to independently influence population growth and extinction risk. Whether increasing temperature may influence the effect of genetic diversity on population growth, however, is not known. We address this issue in the model protist system Tetrahymena thermophila. We test the hypothesis that at temperatures closer to the species' thermal optimum (i.e., the temperature at which population growth is maximal, or T opt), genetic diversity should have a weaker effect on population growth compared to temperatures away from the thermal optimum. To do so, we grew populations of T. thermophila with varying levels of genetic diversity at increasingly warmer temperatures and quantified their intrinsic population growth rate, r. We found that genetic diversity increases population growth at cooler temperatures, but that as temperature increases, this effect weakens. We also show that a combination of changes in the amount of expressed genetic diversity (G) in r, plastic changes in population growth across temperatures (E), and strong G × E interactions underlie this temperature effect. Our results uncover important but largely overlooked temperature effects that have implications for the management of small populations with depauperate genetic stocks in an increasingly warming world.

Refocusing multiple stressor research around the targets and scales of ecological impacts

Ecological communities face a variety of environmental and anthropogenic stressors acting simultaneously. Stressor impacts can combine additively or can interact, causing synergistic or antagonistic effects. Our knowledge of when and how interactions arise is limited, as most models and experiments only consider the effect of a small number of non-interacting stressors at one or few scales of ecological organization. This is concerning because it could lead to significant underestimations or overestimations of threats to biodiversity. Furthermore, stressors have been largely classified by their source rather than by the mechanisms and ecological scales at which they act (the target). Here, we argue, first, that a more nuanced classification of stressors by target and ecological scale can generate valuable new insights and hypotheses about stressor interactions. Second, that the predictability of multiple stressor effects, and consistent patterns in their impacts, can be evaluated by examining the distribution of stressor effects across targets and ecological scales. Third, that a variety of existing mechanistic and statistical modelling tools can play an important role in our framework and advance multiple stressor research.

Theory of temperature-dependent consumer-resource interactions

Changes in temperature affect consumer-resource interactions, which underpin the functioning of ecosystems. However, existing studies report contrasting predictions regarding the impacts of warming on biological rates and community dynamics. To improve prediction accuracy and comparability, we develop an approach that combines sensitivity analysis and aggregate parameters. The former determines which biological parameters impact the community most strongly. The use of aggregate parameters (i.e., maximal energetic efficiency, ρ, and interaction strength, κ), that combine multiple biological parameters, increases explanatory power and reduces the complexity of theoretical analyses. We illustrate the approach using empirically derived thermal dependence curves of biological rates and applying it to consumer-resource biomass ratio and community stability. Based on our analyses, we generate four predictions: (1) resource growth rate regulates biomass distributions at mild temperatures, (2) interaction strength alone determines the thermal boundaries of the community, (3) warming destabilises dynamics at low and mild temperatures only and (4) interactions strength must decrease faster than maximal energetic efficiency for warming to stabilise dynamics. We argue for the potential benefits of directly working with the aggregate parameters to increase the accuracy of predictions on warming impacts on food webs and promote cross-system comparisons.

Systematic variation in the temperature dependence of bacterial carbon use efficiency

Carbon use efficiency (CUE) is a key characteristic of microbial physiology and underlies community-level responses to changing environments. Yet, we currently lack general empirical insights into variation in microbial CUE at the level of individual taxa. Here, through experiments with 29 strains of environmentally isolated bacteria, we find that bacterial CUE typically responds either positively to temperature, or has no discernible response, within biologically meaningful temperature ranges. Using a global data synthesis, we show that these results are generalisable across most culturable groups of bacteria. This variation in the thermal responses of bacterial CUE is taxonomically structured, and stems from the fact that relative to respiration rates, bacterial population growth rates typically respond more strongly to temperature, and are also subject to weaker evolutionary constraints. Our results provide new insights into microbial physiology, and a basis for more accurately modelling the effects of thermal fluctuations on complex microbial communities.

Temperature adaptation of soil microbial respiration in alpine, boreal and tropical soils: An application of the square root (Ratkowsky) model

Warming is expected to stimulate soil microbial respiration triggering a positive soil carbon-climate feedback loop while a consensus remains elusive regarding the magnitude of this feedback. This is partly due to our limited understanding of the temperature-adaptive response of soil microbial respiration, especially over broad climatic scales. We used the square root (Ratkowsky) model to calculate the minimum temperature for soil microbial respiration (T_min , which describes the temperature adaptation of soil microbial respiration) of 298 soil samples from alpine grasslands on the Tibetan Plateau and forest ecosystems across China with a mean annual temperature (MAT) range from -6°C to +25°C. The instantaneous soil microbial respiration was determined between 4°C and 28°C. The square root model could well fit the temperature effect on soil microbial respiration for each individual soil, with R² higher than 0.98 for all soils. T_min ranged from -8.1°C to -0.1°C and increased linearly with increasing MAT (R²  = 0.68). MAT dominantly regulated T_min variation when accounting simultaneously for multiple other drivers (mean annual precipitation, soil pH and carbon quality); an independent experiment showed that carbon availability had no significant effect on T_min . Using the relationship between T_min and MAT, soil microbial respiration after an increased MAT could be estimated, resulting in a relative increase in respiration with decreasing MAT. Thus, soil microbial respiration responses are adapted to long-term temperature differences in MAT. We suggest that T_min  = -5 + 0.2 × MAT, that is, every 1°C rise in MAT is estimated to increase T_min of respiration by approximately 0.2°C, could be used as a first approximation to incorporate temperature adaptation of soil microbial respiration in model predictions. Our results can be used to predict future changes in the response of soil microbial respiration to temperature over different levels of warming and across broad geographic scales with different MAT.

Thermal mismatches in biological rates determine trophic control and biomass distribution under warming

Temperature has numerous effects on the structure and dynamics of ecological communities. Yet, there is no general trend or consensus on the magnitude and directions of these effects. To fill this gap, we propose a mechanistic framework based on key biological rates that predicts how temperature influences biomass distribution and trophic control in food webs. We show that these predictions arise from thermal mismatches between biological rates and across trophic levels. We couple our theory with experimental data for a wide range of species and find that warming should lead to top-heavier terrestrial food chains and stronger top-down control in aquatic environments. We then derive predictions for the effects of temperature on herbivory and validate them with data on stream grazers. Our study provides a mechanistic explanation of thermal effects on consumer-resource systems which is crucial to better understand the biogeography and the consequences of global warming on trophic dynamics.

Adaptive evolution shapes the present-day distribution of the thermal sensitivity of population growth rate

Developing a thorough understanding of how ectotherm physiology adapts to different thermal environments is of crucial importance, especially in the face of global climate change. A key aspect of an organism's thermal performance curve (TPC)-the relationship between fitness-related trait performance and temperature-is its thermal sensitivity, i.e., the rate at which trait values increase with temperature within its typically experienced thermal range. For a given trait, the distribution of thermal sensitivities across species, often quantified as "activation energy" values, is typically right-skewed. Currently, the mechanisms that generate this distribution are unclear, with considerable debate about the role of thermodynamic constraints versus adaptive evolution. Here, using a phylogenetic comparative approach, we study the evolution of the thermal sensitivity of population growth rate across phytoplankton (Cyanobacteria and eukaryotic microalgae) and prokaryotes (bacteria and archaea), 2 microbial groups that play a major role in the global carbon cycle. We find that thermal sensitivity across these groups is moderately phylogenetically heritable, and that its distribution is shaped by repeated evolutionary convergence throughout its parameter space. More precisely, we detect bursts of adaptive evolution in thermal sensitivity, increasing the amount of overlap among its distributions in different clades. We obtain qualitatively similar results from evolutionary analyses of the thermal sensitivities of 2 physiological rates underlying growth rate: net photosynthesis and respiration of plants. Furthermore, we find that these episodes of evolutionary convergence are consistent with 2 opposing forces: decrease in thermal sensitivity due to environmental fluctuations and increase due to adaptation to stable environments. Overall, our results indicate that adaptation can lead to large and relatively rapid shifts in thermal sensitivity, especially in microbes for which rapid evolution can occur at short timescales. Thus, more attention needs to be paid to elucidating the implications of rapid evolution in organismal thermal sensitivity for ecosystem functioning.

Warming can alter host behavior in a similar manner to infection with behavior-manipulating parasites

Parasites are ecologically ubiquitous and, by modifying the physiology and behavior of their host organisms, act as key regulators of the dynamics and stability of ecosystems. It is, however, as yet unclear how parasitic relationships will act to moderate or accelerate the ecological impacts of global climate change. Here, we explore experimentally how the effects of parasites on both the physiology and behavior of their hosts can be moderated by warming, utilising a well-established aquatic host-parasite model system-the ecologically important amphipod Gammarus duebeni and its acanthocephalan parasite Polymorphus minutus. We show that, while only warming affected measured components of host physiology, parasite infection and warming both supressed predator-avoidance behavior of the host independently, yet in a similar manner. Six degrees of warming altered geotactic behaviors to the same extent as infection with behavior-manipulating parasites. These results indicate a novel mechanism by which parasites impact their ecosystems that could be critical to predicting the ecological impacts of warming. Our findings highlight the need for holistic knowledge of interaction networks, incorporating multiple interaction types and behaviors, to predict the effects of both warming and parasitism on the dynamics and stability of ecosystems.

Embracing a new paradigm for temperature sensitivity of soil microbes

The temperature sensitivity of soil processes is of major interest, especially in light of climate change. Originally formulated to explain the temperature dependence of chemical reactions, the Arrhenius equation, and related Q₁₀ temperature coefficient, has a long history of application to soil biological processes. However, empirical data indicate that Q₁₀ and Arrhenius model are often poor metrics of temperature sensitivity in soils. In this opinion piece, we aim to (a) review alternative approaches for characterizing temperature sensitivity, focusing on macromolecular rate theory (MMRT); (b) provide strategies and tools for implementing a new temperature sensitivity framework; (c) develop thermal adaptation hypotheses for the MMRT framework; and (d) explore new questions and opportunities stemming from this paradigm shift. Microbial ecologists should consider developing and adopting MMRT as the basis for predicting biological rates as a function of temperature. Improved understanding of temperature sensitivity in soils is particularly pertinent as microbial response to temperature has a large impact on global climate feedbacks.

Introducing a Stabilizer Formulation for Allergenic Mold Extracts

Background

Sensitization to common mold allergens is one of the major causes of allergic rhinitis and asthma. Therefore, there is a critical need for standard sensitivity tests including skin prick tests to improve the stability of fungi extracts in traditional allergenic formulations. To address this concern, the present study aimed to develop a formulation to preserve allergenic activity of mold extracts.

Methods

48 stabilizer formulations were designed and monitored for allergenic activity during a 40-days incubation period at 37 °C using an ELISA. Specifically, the IgE reactivity of allergenic A. alternata extracts were examined. After establishing the most effective stabilizer formulation, we evaluated whether it could protect the allergenic activity of Alt a1, A. fumigatus, and C. herbarum using an IgE inhibition ELISA after 40 days at 37 °C.

Results

We demonstrated that the most effective stabilizer formulation was a glycerol-based extract containing Arg and Glu. This formulation had an equal ratio of sucrose, sorbitol and protein and was able to preserve more than 95% of allergenic A. alternata extract activity during a 40-days incubation period at 37 °C.

Conclusion

The present study reveals a novel formulation that is an efficient stabilizer of allergenic mold extract activity and has practical applications in mold skin prick tests, ELISAs, immunotherapies, and RAST.

Phytoplankton thermal responses adapt in the absence of hard thermodynamic constraints

To better predict how populations and communities respond to climatic temperature variation, it is necessary to understand how the shape of the response of fitness-related rates to temperature evolves (the thermal performance curve). Currently, there is disagreement about the extent to which the evolution of thermal performance curves is constrained. One school of thought has argued for the prevalence of thermodynamic constraints through enzyme kinetics, whereas another argues that adaptation can-at least partly-overcome such constraints. To shed further light on this debate, we perform a phylogenetic meta-analysis of the thermal performance curves of growth rate of phytoplankton-a globally important functional group-controlling for environmental effects (habitat type and thermal regime). We find that thermodynamic constraints have a minor influence on the shape of the curve. In particular, we detect a very weak increase of maximum performance with the temperature at which the curve peaks, suggesting a weak "hotter-is-better" constraint. Also, instead of a constant thermal sensitivity of growth across species, as might be expected from strong constraints, we find that all aspects of the thermal performance curve evolve along the phylogeny. Our results suggest that phytoplankton thermal performance curves adapt to thermal environments largely in the absence of hard thermodynamic constraints.

Interactive effects of warming and microplastics on metabolism but not feeding rates of a key freshwater detritivore

Microplastics are an emerging pollutant of high concern, with their prevalence in the environment linked to adverse impacts on aquatic organisms. However, our knowledge of these impacts on freshwater species is rudimentary, and there is almost no research directly testing how these effects can change under ongoing and future climate warming. Given the potential for multiple stressors to interact in nature, research on the combined impacts of microplastics and environmental temperature requires urgent attention. Thus, we experimentally manipulated environmentally realistic concentrations of microplastics and temperature to partition their independent and combined impacts on metabolic and feeding rates of a model freshwater detritivore. There was a significant increase in metabolic and feeding rates with increasing body mass and temperature, in line with metabolic and foraging theory. Experimental warming altered the effect of microplastics on metabolic rate, which increased with microplastic concentration at the lowest temperature, but decreased at the higher temperatures. The microplastics had no effect on the amount of litter consumed by the detritivores, therefore, did not result in altered feeding rates. These results show that the metabolism of important freshwater detritivores could be altered by short-term exposure to microplastics, with greater inhibition of metabolic rates at higher temperatures. The consequences of these metabolic changes may take longer to manifest than the duration of our experiments, requiring further investigation. Our results suggest little short-term impact of microplastics on litter breakdown by gammarid amphipods and highlight the importance of environmental context for a better understanding of microplastic pollution in freshwater ecosystems.

Community-level respiration of prokaryotic microbes may rise with global warming

Understanding how the metabolic rates of prokaryotes respond to temperature is fundamental to our understanding of how ecosystem functioning will be altered by climate change, as these micro-organisms are major contributors to global carbon efflux. Ecological metabolic theory suggests that species living at higher temperatures evolve higher growth rates than those in cooler niches due to thermodynamic constraints. Here, using a global prokaryotic dataset, we find that maximal growth rate at thermal optimum increases with temperature for mesophiles (temperature optima [Formula: see text]C), but not thermophiles ([Formula: see text]C). Furthermore, short-term (within-day) thermal responses of prokaryotic metabolic rates are typically more sensitive to warming than those of eukaryotes. Because climatic warming will mostly impact ecosystems in the mesophilic temperature range, we conclude that as microbial communities adapt to higher temperatures, their metabolic rates and therefore, biomass-specific CO[Formula: see text] production, will inevitably rise. Using a mathematical model, we illustrate the potential global impacts of these findings.

Habitat, latitude and body mass influence the temperature dependence of metabolic rate

The sensitivity of metabolic rate to temperature constrains the climate in which ectotherms can function, yet the temperature dependence of metabolic rate may evolve in response to biotic and abiotic factors. We compiled a dataset on the temperature dependence of metabolic rate for heterotrophic ectotherms from studies that show a peak in metabolic rate at an optimal temperature (i.e. that describe the thermal performance curve for metabolic rate). We found that peak metabolic rates were lower in aquatic than terrestrial habitats and increased with body mass, latitude and the optimal temperature. In addition, the optimal temperature decreased with latitude. These results support competing hypotheses about metabolic rate adaptation, with hotter being better in the tropics but colder being better towards the poles. Moreover, our results suggest that the temperature dependence of metabolic rate is more complex than previously suggested.

Thermal performance across levels of biological organization

Thermal performance curves are widely used to describe how ambient temperature impacts different attributes of ectothermic organisms, from protein function to life-history traits, and to predict the potential effects of global warming on ecological systems. Nonetheless, from an analytical standpoint, they remain primarily heuristic and few attempts have been made to develop a formal framework to characterize these curves and disentangle which factors contribute to their variation. Here we employ a nonlinear regression approach to assess if they vary systematically in shape depending on the performance proxy of choice. We compare curves at contrasting levels of organization, namely photosynthetic rates in plants ( n = 43), running speeds in lizards ( n = 51) and intrinsic rates of population increase in insects ( n = 47), and show with discriminant analyses that differences lie in a single dimension accounting for 99.1% of the variation, resulting in 75.8% of classification accuracy. Differences revolve primarily around the thermal range for elevated performance (greater than or equal to 50% of maximum performance), which is broader for photosynthetic rates (median of 26.4°C), intermediate for running speeds (19.5°C) and narrower for intrinsic rates of increase (12.5°C). We contend, confounding taxonomic factors aside, that these differences reflect contrasting levels of biological organization, and hypothesize that the thermal range for elevated performance should decrease at higher organization levels. In this scenario, instantaneous or short-term measures of performance may grossly overestimate the thermal safety margins for population growth and reproduction. Taken together, our analyses suggest that descriptors of the curve are highly correlated and respond in tandem, potentially resulting in systematic variation in shape across organization levels. Future studies should take into consideration this potential bias, address if it constitutes a general pattern and, if so, explain why and how it emerges. This article is part of the theme issue 'Physiological diversity, biodiversity patterns and global climate change: testing key hypotheses involving temperature and oxygen'.

Morphology-based differences in the thermal response of freshwater phytoplankton

The thermal response of maximum growth rate in morphology-based functional groups (MBFG) of freshwater phytoplankton is analysed. Contrasting an exponential Boltzmann-Arrhenius with a unimodal model, three main features were evaluated: (i) the activation energy of the rise (E_r), (ii) the presence of a break in the thermal response and (iii) the activation energy of the fall (E_f). The whole dataset (N = 563) showed an exponential increase (E_r ∼ 0.5), a break around 24°C and no temperature dependence after the breakpoint (E_f = 0). Contrasting thermal responses among MBFG were found. All groups showed positive activation energy (E_r > 0), four showed no evidence of decline in growth rate (temperature range = 0-35°C) and two presented a breakpoint followed by a sharp decrease in growth rate. Our results evidenced systematic differences between MBFG in the thermal response and a coherent response significantly related to morphological traits other than size (i.e. within MBFG). These results provide relevant information for water quality modelling and climate change predictions.

Phenotypic plasticity in locomotor performance of a monophyletic group of weevils accords with the warmer is better hypothesis

Ectotherms may respond to variable environmental conditions by altering their phenotypes. Phenotypic plasticity was initially thought to be beneficial to an organism's physiological fitness. Several alternative hypotheses, have, however, been proposed with growing empirical support. In this study, we test the full suite of hypotheses by investigating acclimation responses of locomotor performance for nine populations of five species of sub-Antarctic weevils, using static and fluctuating temperatures. Species showed typical locomotion thermal performance curves with temperature of the maximum speed (Topt) ranging between 22.3±1.7°C (mean±s.e.) and 31.1±0.7°C. For most species Topt was not affected by acclimation. For maximum speed (Umax), significant, positive effects of acclimation were found for all species except a supralittoral one. Individuals acclimated to 0°C showed much lower values than the other two acclimation treatments (15°C and fluctuating 0-15°C). Performance breadth (the index of the breadth of the curve, Tbr) typically showed little response to acclimation. None of the traits of the supralittoral species were affected by acclimation treatment. Responses to stable and fluctuating temperature treatments were similar. Our findings also revealed that the mean estimated activation energy 0.40±0.015 eV (mean±s.e.) was lower than for other herbivores, the category to which these weevils belong, suggesting that some form of compensation in the rate-temperature relationship may be evident. Thus, we typically found support for the warmer is better hypothesis for acclimation of locomotor performance, though some compensation is evident.

Metabolic Theory and the Temperature-Size Rule Explain the Temperature Dependence of Population Carrying Capacity

The temperature dependence of highly conserved subcellular metabolic systems affects ecological patterns and processes across scales, from organisms to ecosystems. Population density at carrying capacity plays an important role in evolutionary processes, biodiversity, and ecosystem function, yet how it varies with temperature-dependent metabolism remains unclear. Though the exponential effect of temperature on intrinsic population growth rate, r, is well known, we still lack clear evidence that population density at carrying capacity, K, declines with increasing per capita metabolic rate, as predicted by the metabolic theory of ecology (MTE). We experimentally tested whether temperature effects on photosynthesis propagate directly to population carrying capacity in a model species, the mobile phytoplankton Tetraselmis tetrahele. After maintaining populations at a fixed resource supply and fixed temperatures for 43 days, we found that carrying capacity declined with increasing temperature. This decline was predicted quantitatively when models included temperature-dependent metabolic rates and temperature-associated body-size shifts. Our results demonstrate that warming reduces carrying capacity and that temperature effects on body size and metabolic rate interact to determine how temperature affects population dynamics. These findings bolster efforts to relate metabolic temperature dependence to population and ecosystem patterns via MTE.

A meta-analysis of temperature sensitivity as a microbial trait

Traits-based approaches in microbial ecology provide a valuable way to abstract organismal interaction with the environment and to generate hypotheses about community function. Using macromolecular rate theory (MMRT), we recently identified that temperature sensitivity can be characterized as a distinct microbial trait. As temperature is fundamental in controlling biological reactions, variation in temperature sensitivity across communities, organisms, and processes has the potential to vastly improve understanding of microbial response to climate change. These microbial temperature sensitivity traits include the heat capacity ( ΔCP‡ ), temperature optimum (T_opt ), and point of maximum temperature sensitivity (TS_max ), each of which provide unique insights about organismal response to changes in temperature. In this meta-analysis, we analyzed the distribution of these temperature sensitivity traits from bacteria, fungi, and mixed communities across a variety of biological systems (e.g., soils, oceans, foods, wastewater treatment plants) in order to identify commonalities in temperature responses across these diverse organisms and reaction rates. Our analysis of temperature sensitivity traits from over 350 temperature response curves reveals a wide distribution of temperature sensitivity traits, with T_opt and TS_max well within biological relevant temperatures. We find that traits vary significantly depending on organism type, microbial diversity, source environment, and biological process, with higher temperature sensitivity found in fungi than bacteria and in less diverse systems. Carbon dioxide production was found to be less temperature sensitive than denitrification, suggesting that changes in temperature will have a potentially larger impact on nitrogen-related processes. As climate changes, these results have important implications for basic understanding of the temperature sensitivity of biological reactions and for ecological understanding of species' trait distributions, as well as for improved treatment of temperature sensitivity in models.

Role of carbon allocation efficiency in the temperature dependence of autotroph growth rates

Relating the temperature dependence of photosynthetic biomass production to underlying metabolic rates in autotrophs is crucial for predicting the effects of climatic temperature fluctuations on the carbon balance of ecosystems. We present a mathematical model that links thermal performance curves (TPCs) of photosynthesis, respiration, and carbon allocation efficiency to the exponential growth rate of a population of photosynthetic autotroph cells. Using experiments with the green alga, Chlorella vulgaris, we apply the model to show that the temperature dependence of carbon allocation efficiency is key to understanding responses of growth rates to warming at both ecological and longer-term evolutionary timescales. Finally, we assemble a dataset of multiple terrestrial and aquatic autotroph species to show that the effects of temperature-dependent carbon allocation efficiency on potential growth rate TPCs are expected to be consistent across taxa. In particular, both the thermal sensitivity and the optimal temperature of growth rates are expected to change significantly due to temperature dependence of carbon allocation efficiency alone. Our study provides a foundation for understanding how the temperature dependence of carbon allocation determines how population growth rates respond to temperature.

Reaction and diffusion thermodynamics explain optimal temperatures of biochemical reactions

Ubiquitous declines in biochemical reaction rates above optimal temperatures (Topt) are normally attributed to enzyme state changes, but such mechanisms appear inadequate to explain pervasive Topt well below enzyme deactivation temperatures (Tden). Here, a meta-analysis of 92 experimental studies shows that product formation responds twice as strongly to increased temperature than diffusion or transport. This response difference has multiple consequences for biochemical reactions, such as potential shifts in the factors limiting reactions as temperature increases and reaction-diffusion dynamics that predict potential product inhibition and limitation of the reaction by entropy production at temperatures below Tden. Maximizing entropy production by the reaction predicts Topt that depend on enzyme concentration and efficiency as well as reaction favorability, which are patterns not predicted by mechanisms of enzyme state change. However, these predictions are strongly supported by patterns in a meta-analysis of 121 enzyme kinetic studies. Consequently, reaction-diffusion thermodynamics and entropy production may constrain organism performance at higher temperatures, yielding temperature optima of life that may depend on reaction characteristics and environmental features rather than just enzyme state changes.

Evaluating the kinetic basis of plant growth from organs to ecosystems

Contents Summary 37 I. Introduction 37 II. Predictions for metabolic kinetics 38 III. Kinetics of net photosynthesis 38 IV. Kinetics of plant growth 40 V. Hypotheses for higher-level kinetic decoupling 41 VI. Conclusions 42 Acknowledgements 42 References 42 SUMMARY: Understanding how temperature influences the scaling of physiological rates through levels of biological organization is critical for predicting plant responses to climate. Metabolic theory predicts that many rates increase exponentially with temperature following an activation energy (E) of 0.32 eV for photosynthesis. Here, I evaluate this prediction for net photosynthesis and organ, individual, and ecosystem growth. Observed E for photosynthesis varied widely but was not statistically different from predictions, while E for organs was greater than predicted, and E for individuals and ecosystems only weakly characterized temperature responses. I review several hypotheses that may underlie these results. Understanding how multiple rate-limiting processes coalesce into a single E that characterizes metabolic responses to temperature, and how to best estimate E from unimodal data, remain important challenges.

The thermal dependence of carbon stable isotope incorporation and trophic discrimination in the domestic cricket, Acheta domesticus

Stable isotopes are valuable tools in physiological and ecological research, as they can be used to estimate diet, habitat use, and resource allocation. However, in most cases a priori knowledge of two key properties of stable isotopes is required, namely their rate of incorporation into the body (incorporation rate) and the change of isotope values between consumers and resources that arises during incorporation of the isotopes into the consumer's tissues (trophic discrimination). Previous studies have quantified these properties across species and tissue types, but little is known about how they vary with temperature, a key driver of many biological rates and times. Here, we explored for the first time how temperature affects both carbon incorporation rate and trophic discrimination via growth rates, using the domestic cricket, Acheta domesticus. We raised crickets at 16 °C, 21 °C, and 26 °C and showed that temperature increased carbon isotope incorporation rate, which was driven by both an increased growth rate and catabolism at higher temperatures. Trophic discrimination of carbon isotopes decreased at higher temperatures, which we attributed to either lower activation energies needed to synthesize non-essential amino acids at higher temperatures or the increased utilization of available resources of consumers at higher temperatures. Our results demonstrate that temperature is a key driver of both carbon isotope incorporation rate and trophic discrimination, via mechanisms that likely persist across all ectotherms. Experiments to determine incorporation rates and trophic discrimination factors in ectotherms must include temperature as a major factor, and natural variation in temperature might have significant effects on these isotopic properties that then can affect inferences made from isotope values.

Metabolic traits predict the effects of warming on phytoplankton competition

Understanding how changes in temperature affect interspecific competition is critical for predicting changes in ecological communities with global warming. Here, we develop a theoretical model that links interspecific differences in the temperature dependence of resource acquisition and growth to the outcome of pairwise competition in phytoplankton. We parameterised our model with these metabolic traits derived from six species of freshwater phytoplankton and tested its ability to predict the outcome of competition in all pairwise combinations of the species in a factorial experiment, manipulating temperature and nutrient availability. The model correctly predicted the outcome of competition in 72% of the pairwise experiments, with competitive advantage determined by difference in thermal sensitivity of growth rates of the two species. These results demonstrate that metabolic traits play a key role in determining how changes in temperature influence interspecific competition and lay the foundation for mechanistically predicting the effects of warming in complex, multi‐species communities.

Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits

There is currently unprecedented interest in quantifying variation in thermal physiology among organisms, especially in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a rate, across individuals or species, at a common temperature (temperature normalisation). An increasingly popular model for fitting thermal performance curves to data-the Sharpe-Schoolfield equation-can yield strongly inflated estimates of temperature-normalised rate values. These deviations occur whenever a key thermodynamic assumption of the model is violated, i.e., when the enzyme governing the performance of the rate is not fully functional at the chosen reference temperature. Using data on 1,758 thermal performance curves across a wide range of species, we identify the conditions that exacerbate this inflation. We then demonstrate that these biases can compromise tests to detect metabolic cold adaptation, which requires comparison of fitness or rate performance of different species or genotypes at some fixed low temperature. Finally, we suggest alternative methods for obtaining unbiased estimates of temperature-normalised rate values for meta-analyses of thermal performance across species in climate change impact studies.

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.

Conceptualizing ecosystem tipping points within a physiological framework

Connecting the nonlinear and often counterintuitive physiological effects of multiple environmental drivers to the emergent impacts on ecosystems is a fundamental challenge. Unfortunately, the disconnect between the way "stressors" (e.g., warming) is considered in organismal (physiological) and ecological (community) contexts continues to hamper progress. Environmental drivers typically elicit biphasic physiological responses, where performance declines at levels above and below some optimum. It is also well understood that species exhibit highly variable response surfaces to these changes so that the optimum level of any environmental driver can vary among interacting species. Thus, species interactions are unlikely to go unaltered under environmental change. However, while these nonlinear, species-specific physiological relationships between environment and performance appear to be general, rarely are they incorporated into predictions of ecological tipping points. Instead, most ecosystem-level studies focus on varying levels of "stress" and frequently assume that any deviation from "normal" environmental conditions has similar effects, albeit with different magnitudes, on all of the species within a community. We consider a framework that realigns the positive and negative physiological effects of changes in climatic and nonclimatic drivers with indirect ecological responses. Using a series of simple models based on direct physiological responses to temperature and ocean pCO 2, we explore how variation in environment-performance relationships among primary producers and consumers translates into community-level effects via trophic interactions. These models show that even in the absence of direct mortality, mismatched responses resulting from often subtle changes in the physical environment can lead to substantial ecosystem-level change.

Thermal Performance Curves and the Metabolic Theory of Ecology-A Practical Guide to Models and Experiments for Parasitologists

Climate change will affect host-parasite dynamics in complex ways. The development of forecast models is necessary for proactive disease management, but past studies have frequently reported thermal performance data in idiosyncratic ways that have limited use for parameterizing thermal host-parasite models. Development of improved forecast models will require strong collaborations between experimental parasitologists and disease modelers. The purpose of this article is to facilitate such collaborations by reviewing practical considerations for describing thermal performance curves of parasite and host performance traits, and using them to predict climate change impacts on host-parasite systems. In the first section, we provide an overview of how thermal performance curves can be embedded in life-cycle-based dynamical models of parasitism, and we outline how such models can capture the net effect of multiple nonlinear temperature dependencies affecting the host-parasite dynamics. We also discuss how macroecological generalities based on the metabolic theory of ecology (MTE) can be used to determine a priori parameter estimates for thermal performance curves to derive null models for data-deficient species, but we note that most of the generalities suggested by MTE remain to be tested for parasites. In the second section, we discuss empirical knowledge gaps for the temperature dependence of parasite and host performance traits, and we outline the types of data that need to be collected to inform MTE-based models for data-deficient species. We specifically emphasize the importance of (1) capturing the entire thermal response of performance traits, including lower and upper temperature thresholds, and (2) experimentally or statistically separating out the thermal responses of different performance traits (e.g., development and mortality) rather than only reporting composite measures (e.g., apparent development). Not adhering to these principles can lead to biased climate change impact predictions. In the third section, we provide a practical guide outlining how experimentalists can contribute to fill data gaps by measuring the temperature dependence of host and parasite performance traits in ways that are systematic, statistically rigorous, and consistent with the requirements of life cycle-based host-parasite models. This guide includes recommendations and practical examples illustrating (1) the use of perturbation analyses to determine experimental priorities, (2) experimental design tips for quantifying thermal response curves, and (3) statistical methods for estimating the parameters of thermal performance curves. Our hope is that this article helps researchers to maximize the value and use of future data collections for both empirical and modelling studies investigating the way in which temperature influences parasitism.

The combined effects of reactant kinetics and enzyme stability explain the temperature dependence of metabolic rates

A mechanistic understanding of the response of metabolic rate to temperature is essential for understanding thermal ecology and metabolic adaptation. Although the Arrhenius equation has been used to describe the effects of temperature on reaction rates and metabolic traits, it does not adequately describe two aspects of the thermal performance curve (TPC) for metabolic rate—that metabolic rate is a unimodal function of temperature often with maximal values in the biologically relevant temperature range and that activation energies are temperature dependent. We show that the temperature dependence of metabolic rate in ectotherms is well described by an enzyme‐assisted Arrhenius (EAAR) model that accounts for the temperature‐dependent contribution of enzymes to decreasing the activation energy required for reactions to occur. The model is mechanistically derived using the thermodynamic rules that govern protein stability. We contrast our model with other unimodal functions that also can be used to describe the temperature dependence of metabolic rate to show how the EAAR model provides an important advance over previous work. We fit the EAAR model to metabolic rate data for a variety of taxa to demonstrate the model's utility in describing metabolic rate TPCs while revealing significant differences in thermodynamic properties across species and acclimation temperatures. Our model advances our ability to understand the metabolic and ecological consequences of increases in the mean and variance of temperature associated with global climate change. In addition, the model suggests avenues by which organisms can acclimate and adapt to changing thermal environments. Furthermore, the parameters in the EAAR model generate links between organismal level performance and underlying molecular processes that can be tested for in future work.

Warming-Induced Changes to Body Size Stabilize Consumer-Resource Dynamics

Both body size and temperature directly influence consumer-resource dynamics. There is also widespread empirical evidence for the temperature-size rule (TSR), which creates a negative relationship between temperature and body size. However, it is not known how the TSR affects community dynamics. Here we integrate temperature- and size-dependent models to include indirect effects of warming, through changes in body size, to answer the question, How does the TSR affect the predicted response of consumer-resource systems to warming? We find that the TSR is expected to maintain consumer-resource biomass ratios and buffer the community from extinctions under warming. While our results are limited to conditions where organisms are below their thermal optimum, they hold under a range of realistic temperature-size responses and are robust to the type of functional response. Our analyses suggest that the widely observed TSR may reduce the impacts of warming on consumer-resource systems.

Temperature Sensitivity as a Microbial Trait Using Parameters from Macromolecular Rate Theory

The activity of soil microbial extracellular enzymes is strongly controlled by temperature, yet the degree to which temperature sensitivity varies by microbe and enzyme type is unclear. Such information would allow soil microbial enzymes to be incorporated in a traits-based framework to improve prediction of ecosystem response to global change. If temperature sensitivity varies for specific soil enzymes, then determining the underlying causes of variation in temperature sensitivity of these enzymes will provide fundamental insights for predicting nutrient dynamics belowground. In this study, we characterized how both microbial taxonomic variation as well as substrate type affects temperature sensitivity. We measured β-glucosidase, leucine aminopeptidase, and phosphatase activities at six temperatures: 4, 11, 25, 35, 45, and 60°C, for seven different soil microbial isolates. To calculate temperature sensitivity, we employed two models, Arrhenius, which predicts an exponential increase in reaction rate with temperature, and Macromolecular Rate Theory (MMRT), which predicts rate to peak and then decline as temperature increases. We found MMRT provided a more accurate fit and allowed for more nuanced interpretation of temperature sensitivity in all of the enzyme × isolate combinations tested. Our results revealed that both the enzyme type and soil isolate type explain variation in parameters associated with temperature sensitivity. Because we found temperature sensitivity to be an inherent and variable property of an enzyme, we argue that it can be incorporated as a microbial functional trait, but only when using the MMRT definition of temperature sensitivity. We show that the Arrhenius metrics of temperature sensitivity are overly sensitive to test conditions, with activation energy changing depending on the temperature range it was calculated within. Thus, we propose the use of the MMRT definition of temperature sensitivity for accurate interpretation of temperature sensitivity of soil microbial enzymes.

The effects of climatic fluctuations and extreme events on running water ecosystems

Most research on the effects of environmental change in freshwaters has focused on incremental changes in average conditions, rather than fluctuations or extreme events such as heatwaves, cold snaps, droughts, floods or wildfires, which may have even more profound consequences. Such events are commonly predicted to increase in frequency, intensity and duration with global climate change, with many systems being exposed to conditions with no recent historical precedent. We propose a mechanistic framework for predicting potential impacts of environmental fluctuations on running-water ecosystems by scaling up effects of fluctuations from individuals to entire ecosystems. This framework requires integration of four key components: effects of the environment on individual metabolism, metabolic and biomechanical constraints on fluctuating species interactions, assembly dynamics of local food webs, and mapping the dynamics of the meta-community onto ecosystem function. We illustrate the framework by developing a mathematical model of environmental fluctuations on dynamically assembling food webs. We highlight (currently limited) empirical evidence for emerging insights and theoretical predictions. For example, widely supported predictions about the effects of environmental fluctuations are: high vulnerability of species with high per capita metabolic demands such as large-bodied ones at the top of food webs; simplification of food web network structure and impaired energetic transfer efficiency; and reduced resilience and top-down relative to bottom-up regulation of food web and ecosystem processes. We conclude by identifying key questions and challenges that need to be addressed to develop more accurate and predictive bio-assessments of the effects of fluctuations, and implications of fluctuations for management practices in an increasingly uncertain world.