A general theory for temperature dependence in biology

Unifying functional and population ecology to test the adaptive value of traits

Plant strategies are phenotypes shaped by natural selection that enable populations to persist in a given environment. Plant strategy theory is essential for understanding the assembly of plant communities, predicting plant responses to climate change, and enhancing the restoration of our degrading biosphere. However, models of plant strategies vary widely and have tended to emphasize either functional traits or life-history traits at the expense of integrating both into a general framework to improve our ecological and evolutionary understanding of plant form and function. Advancing our understanding of plant strategies will require investment in two complementary research agendas that together will unify functional ecology and population ecology. First, we must determine what is phenotypically possible by quantifying the dimensionality of plant traits. This step requires dense taxonomic sampling of traits on species representing the broad diversity of phylogenetic clades, environmental gradients, and geographical regions found across Earth. It is important that we continue to sample traits locally and share data globally to fill biased gaps in trait databases. Second, we must test the power of traits for explaining species distributions, demographic rates, and population growth rates across gradients of resource limitation, disturbance regimes, temperature, vegetation density, and frequencies of other strategies. This step requires thoughtful, theory-driven empiricism. Reciprocal transplant experiments beyond the native range and synthetic demographic modelling are the most powerful methods to determine how trait-by-environment interactions influence fitness. Moving beyond easy-to-measure traits and evaluating the traits that are under the strongest ecological selection within different environmental contexts will improve our understanding of plant adaptations. Plant strategy theory is poised to (i) unpack the multiple dimensions of productivity and disturbance gradients and differentiate adaptations to climate and resource limitation from adaptations to disturbance, (ii) distinguish between the fundamental and realized niches of phenotypes, and (iii) articulate the distinctions and relationships between functional traits and life-history traits.

Soil temperature and moisture as key controls of phosphorus export in mountain watersheds

Oligotrophic mountain lakes act as sensitive indicators of landscape-scale changes in mountain regions due to their low nutrient concentration and remote, relatively undisturbed watersheds. Recent research shows that phosphorus (P) concentrations are increasing in mountain lakes around the world, creating more mesotrophic states and altering lake ecosystem structure and function. The relative importance of atmospheric deposition and climate-driven changes to local biogeochemistry in driving these shifts is not well established. In this study, we test whether increasing temperatures in watershed soils may be contributing to the observed increases in mountain lake P loading. Specifically, we test whether higher soil temperatures increase P mobilization from mountain soils by accelerating the rate of geochemical weathering and soil organic matter decomposition. We used paired soil incubation (lab) and soil transplant (field) experiments with mountain soils from around the western United States to test the effects of warming on rain-leachable P concentration, soil P mobilization, and soil respiration. Our results show that while higher temperature can increase soil P mobilization, low soil moisture can limit the effects of warming in some situations. Soils with lower bulk densities, higher pH, lower aluminum oxide contents, and lower ratios of carbon to nitrogen had much higher rain-leachable P concentration across all sites and experimental treatments. Together, these results suggest that mountain watersheds with high-P soils and relatively high soil moisture could have the largest increases in P mobilization with warming. Consequently, lakes and streams in such watersheds could become especially susceptible to soil-driven eutrophication as temperatures rise.

High temperature delays and low temperature accelerates evolution of a new protein phenotype

Since the origin of life, temperatures on earth have fluctuated both on short and long time scales. How such changes affect the rate at which Darwinian evolution can bring forth new phenotypes remains unclear. On the one hand, high temperature may accelerate phenotypic evolution because it accelerates most biological processes. On the other hand, it may slow phenotypic evolution, because proteins are usually less stable at high temperatures and therefore less evolvable. Here, to test these hypotheses experimentally, we evolved a green fluorescent protein in E. coli towards the new phenotype of yellow fluorescence at different temperatures. Yellow fluorescence evolved most slowly at high temperature and most rapidly at low temperature, in contradiction to the first hypothesis. Using high-throughput population sequencing, protein engineering, and biochemical assays, we determined that this is due to the protein-destabilizing effect of neofunctionalizing mutations. Destabilization is highly detrimental at high temperature, where neofunctionalizing mutations cannot be tolerated. Their detrimental effects can be mitigated through excess stability at low temperature, leading to accelerated adaptive evolution. By modifying protein folding stability, temperature alters the accessibility of mutational paths towards high-fitness genotypes. Our observations have broad implications for our understanding of how temperature changes affect evolutionary adaptations and innovations.

Dissipative scaling of development and aging in multicellular organisms

Evolution, self-replication and ontogenesis are highly dynamic, irreversible and self-organizing processes dissipating energy. While progress has been made to decipher the role of thermodynamics in cellular fission, it is not yet clear how entropic balances shape organism growth and aging. This paper derives a general dissipation theory for the life history of organisms. It implies a self-regulated energy dissipation facilitating exponential growth within a hierarchical and entropy lowering self-organization. The theory predicts ceilings in energy expenditures imposed by geometric constrains, which promote thermal optimality during development, and a dissipative scaling across organisms consistent with ecological scaling laws combining isometric and allometric terms. The theory also illustrates how growing organisms can tolerate damage through continuous extension and production of new dissipative structures low in entropy. However, when organisms reduce their rate of cell division and reach a steady adult state, they become thermodynamically unstable, increase internal entropy by accumulating damage, and age.

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.

Theory and classification of mass extinction causation

Theory regarding the causation of mass extinctions is in need of systematization, which is the focus of this contribution. Every mass extinction has both an ultimate cause, i.e. the trigger that leads to various climato-environmental changes, and one or more proximate cause(s), i.e. the specific climato-environmental changes that result in elevated biotic mortality. With regard to ultimate causes, strong cases can be made that bolide (i.e. meteor) impacts, large igneous province (LIP) eruptions and bioevolutionary events have each triggered one or more of the Phanerozoic Big Five mass extinctions, and that tectono-oceanic changes have triggered some second-order extinction events. Apart from bolide impacts, other astronomical triggers (e.g. solar flares, gamma bursts and supernova explosions) remain entirely in the realm of speculation. With regard to proximate mechanisms, most extinctions are related to either carbon-release or carbon-burial processes, the former being associated with climatic warming, ocean acidification, reduced marine productivity and lower carbonate δ13C values, and the latter with climatic cooling, increased marine productivity and higher carbonate δ13C values. Environmental parameters such as marine redox conditions and terrestrial weathering intensity do not show consistent relationships with carbon-cycle changes. In this context, mass extinction causation can be usefully classified using a matrix of ultimate and proximate factors. Among the Big Five mass extinctions, the end-Cretaceous biocrisis is an example of a bolide-triggered carbon-release event, the end-Permian and end-Triassic biocrises are examples of LIP-triggered carbon-release events, and the Late Ordovician and Late Devonian biocrises are examples of bioevolution-triggered carbon-burial events. Whereas the bolide-impact and LIP-eruption mechanisms appear to invariably cause carbon release, bioevolutionary triggers can result in variable carbon-cycle changes, e.g. carbon burial during the Late Ordovician and Late Devonian events, carbon release associated with modern anthropogenic climate warming, and little to no carbon-cycle impact due to certain types of ecosystem change (e.g. the advent of the first predators around the end-Ediacaran; the appearance of Paleolithic human hunters in Australasia and the Americas). Broadly speaking, studies of mass extinction causation have suffered from insufficiently critical thinking-an impartial survey of the extant evidence shows that (i) hypotheses of a common ultimate cause (e.g. bolide impacts or LIP eruptions) for all Big Five mass extinctions are suspect given manifest differences in patterns of environmental and biotic change among them; (ii) the Late Ordovician and Late Devonian events were associated with carbon burial and long-term climatic cooling, i.e. changes that are inconsistent with a bolide-impact or LIP-eruption mechanism; and (iii) claims of periodicity in Phanerozoic mass extinctions depended critically on the now-disproven idea that they shared a common extrinsic trigger (i.e. bolide impacts).

Searching for Principles of Microbial Ecology Across Levels of Biological Organization

Microbial communities play pivotal roles in ecosystems across different scales, from global elemental cycles to household food fermentations. These complex assemblies comprise hundreds or thousands of microbial species whose abundances vary over time and space. Unraveling the principles that guide their dynamics at different levels of biological organization, from individual species, their interactions, to complex microbial communities, is a major challenge. To what extent are these different levels of organization governed by separate principles, and how can we connect these levels to develop predictive models for the dynamics and function of microbial communities? Here, we will discuss recent advances that point towards principles of microbial communities, rooted in various disciplines from physics, biochemistry, and dynamical systems. By considering the marine carbon cycle as a concrete example, we demonstrate how the integration of levels of biological organization can offer deeper insights into the impact of increasing temperatures, such as those associated with climate change, on ecosystem-scale processes. We argue that by focusing on principles that transcend specific microbiomes, we can pave the way for a comprehensive understanding of microbial community dynamics and the development of predictive models for diverse ecosystems.

Toxicokinetic-Toxicodynamic Model to Assess Thermal Stress

Temperature is a crucial environmental factor affecting the distribution and performance of ectothermic organisms. This study introduces a new temperature damage model to interpret their thermal stress. Inspired by the ecotoxicological damage model in the General Unified Threshold model for Survival (GUTS) framework, the temperature damage model assumes that damage depends on the balance between temperature-dependent accumulation and constant repair. Mortality due to temperature stress is driven by the damage level exceeding a threshold. Model calibration showed a good agreement with the measured survival of Gammarus pulex exposed to different constant temperatures. Further, model simulations, including constant temperatures, daily temperature fluctuations, and heatwaves, demonstrated the model's ability to predict temperature effects for various environmental scenarios. With this, the present study contributes to the mechanistic understanding of temperature as a single stressor while facilitating the incorporation of temperature as an additional stressor alongside chemicals in mechanistic multistressor effect models.

DLTKcat: deep learning-based prediction of temperature-dependent enzyme turnover rates

The enzyme turnover rate, ${k}_{cat}$, quantifies enzyme kinetics by indicating the maximum efficiency of enzyme catalysis. Despite its importance, ${k}_{cat}$ values remain scarce in databases for most organisms, primarily because of the cost of experimental measurements. To predict ${k}_{cat}$ and account for its strong temperature dependence, DLTKcat was developed in this study and demonstrated superior performance (log10-scale root mean squared error = 0.88, R-squared = 0.66) than previously published models. Through two case studies, DLTKcat showed its ability to predict the effects of protein sequence mutations and temperature changes on ${k}_{cat}$ values. Although its quantitative accuracy is not high enough yet to model the responses of cellular metabolism to temperature changes, DLTKcat has the potential to eventually become a computational tool to describe the temperature dependence of biological systems.

Temperature sensitivity and temperature response across development in the Drosophila larva

The surrounding thermal environment is highly important for the survival and fitness of animals, and as a result most exhibit behavioral and neural responses to temperature changes. We study signals generated by thermosensory neurons in Drosophila larvae and also the physical and sensory effects of temperature variation on locomotion and navigation. In particular we characterize how sensory neuronal and behavioral responses to temperature variation both change across the development of the larva. Looking at a wide range of non-nociceptive isotropic thermal environments, we characterize the dependence of speed, turning rate, and other behavioral components on temperature, distinguishing the physical effects of temperature from behavior changes based on sensory processing. We also characterize the strategies larvae use to modulate individual behavioral components to produce directed navigation along thermal gradients, and how these strategies change during physical development. Simulations based on modified random walks show where thermotaxis in each developmental stage fits into the larger context of possible navigation strategies. We also investigate cool sensing neurons in the larva's dorsal organ ganglion, characterizing neural response to sine-wave modulation of temperature while performing single-cell-resolution 3D imaging. We determine the sensitivity of these neurons, which produce signals in response to extremely small temperature changes. Combining thermotaxis results with neurophysiology data, we observe, across development, sensitivity to temperature change as low as a few thousandths of a °C per second, or a few hundredths of a °C in absolute temperature change.

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.

Holopelagic Sargassum aggregations provide warmer microhabitats for associated fauna

Drifting aggregations of Sargassum algae provide critical habitat for endemic, endangered, and commercially important species. They may also provide favorable microclimates for associated fauna. To quantify thermal characteristics of holopelagic Sargassum aggregations, we evaluated thermal profiles of 50 aggregations in situ in the Sargasso Sea. Sea surface temperature (SST) in the center of aggregations was significantly higher than in nearby open water, and SST differential was independent of aggregation volume, area, and thickness. SST differential between aggregation edge and open water was smaller than those between aggregation center and aggregation edge and between aggregation center and open water. Water temperature was significantly higher inside and below aggregations compared to open water but did not vary inside aggregations with depth. Holopelagic Sargassum aggregations provide warmer microhabitats for associated fauna, which may benefit marine ectotherms, though temperature differentials were narrow (up to 0.7 °C) over the range of aggregation sizes we encountered (area 0.01-15 m2). We propose a hypothetical curve describing variation in SST differential with Sargassum aggregation size as a prediction for future studies to evaluate across temporal and geographic ranges. Our study provides a foundation for investigating the importance of thermal microhabitats in holopelagic Sargassum ecosystems.

Toward a cohesive understanding of ecological complexity

Ecological systems are quintessentially complex systems. Understanding and being able to predict phenomena typical of complex systems is, therefore, critical to progress in ecology and conservation amidst escalating global environmental change. However, myriad definitions of complexity and excessive reliance on conventional scientific approaches hamper conceptual advances and synthesis. Ecological complexity may be better understood by following the solid theoretical basis of complex system science (CSS). We review features of ecological systems described within CSS and conduct bibliometric and text mining analyses to characterize articles that refer to ecological complexity. Our analyses demonstrate that the study of complexity in ecology is a highly heterogeneous, global endeavor that is only weakly related to CSS. Current research trends are typically organized around basic theory, scaling, and macroecology. We leverage our review and the generalities identified in our analyses to suggest a more coherent and cohesive way forward in the study of complexity in ecology.

A conceptual framework for the dynamic modeling of time-resolved phenotypes for sets of genotype-environment-management combinations: a model library

Introduction

Dynamic crop growth models are an important tool to predict complex traits, like crop yield, for modern and future genotypes in their current and evolving environments, as those occurring under climate change. Phenotypic traits are the result of interactions between genetic, environmental, and management factors, and dynamic models are designed to generate the interactions producing phenotypic changes over the growing season. Crop phenotype data are becoming increasingly available at various levels of granularity, both spatially (landscape) and temporally (longitudinal, time-series) from proximal and remote sensing technologies.

Methods

Here we propose four phenomenological process models of limited complexity based on differential equations for a coarse description of focal crop traits and environmental conditions during the growing season. Each of these models defines interactions between environmental drivers and crop growth (logistic growth, with implicit growth restriction, or explicit restriction by irradiance, temperature, or water availability) as a minimal set of constraints without resorting to strongly mechanistic interpretations of the parameters. Differences between individual genotypes are conceptualized as differences in crop growth parameter values.

Results

We demonstrate the utility of such low-complexity models with few parameters by fitting them to longitudinal datasets from the simulation platform APSIM-Wheat involving in silico biomass development of 199 genotypes and data of environmental variables over the course of the growing season at four Australian locations over 31 years. While each of the four models fits well to particular combinations of genotype and trial, none of them provides the best fit across the full set of genotypes by trials because different environmental drivers will limit crop growth in different trials and genotypes in any specific trial will not necessarily experience the same environmental limitation.

Discussion

A combination of low-complexity phenomenological models covering a small set of major limiting environmental factors may be a useful forecasting tool for crop growth under genotypic and environmental variation.

Energetic costs increase with faster heating in an aquatic ectotherm

The thermal sensitivity of metabolism is widely studied due to its perceived importance for organismal fitness and resilience to future climate change. Almost all such studies estimate metabolism at a variety of constant temperatures, with very little work exploring how metabolism varies during temperature change. However, temperature in nature is rarely static, so our existing understanding from experiments may not reflect how temperature influences metabolism in natural systems. Using closed-chamber respirometry, we estimated the aerobic metabolic rate of an aquatic ectotherm, the Atlantic ditch shrimp Palaemonetes varians, under varying thermal conditions. We continuously measured oxygen consumption of shrimp during heating, cooling and constant temperatures, starting trials at a range of acclimation temperatures and exposing shrimp to a variety of rates of temperature change. In a broad sense, cumulative oxygen consumption estimated from static temperature exposures corresponded to estimates derived from ramping experiments. However, further analyses showed that oxygen consumption increases for both faster heating and faster cooling, with rapid heating driving higher metabolic rates than if shrimp were warmed slowly. These results suggest a systematic influence of heating rate on the thermal sensitivity of metabolism. With influential concepts such as the metabolic theory of ecology founded in data from constant temperature experiments, our results encourage further exploration of how variable temperature impacts organism energetics, and to test the generality of our findings across species. This is especially important given climate forecasts of heat waves that are characterised by both increased temperatures and faster rates of change.

Scaling of biological rates with body size as a backbone in the assembly of metacommunity biodiversity

The dispersal-body mass association has been highlighted as a main determinant of biodiversity patterns in metacommunities. However, less attention has been devoted to other well-recognized determinants of metacommunity diversity: the scaling in density and regional richness with body size. Among active dispersers, the increase in movement with body size may enhance local richness and decrease β-diversity. Nevertheless, the reduction of population size and regional richness with body mass may determine a negative diversity-body size association. Consequently, metacommunity assembly probably emerges from a balance between the effect of these scalings. We formalize this hypothesis by relating the exponents of size-scaling rules with simulated trends in α-, β- and γ-diversity with body size. Our results highlight that the diversity-body size relationship in metacommunities may be driven by the combined effect of different scaling rules. Given their ubiquity in most terrestrial and aquatic biotas, these scaling rules may represent the basic determinants-backbone-of biodiversity, over which other mechanisms operate determining metacommunity assembly. Further studies are needed, aimed at explaining biodiversity patterns from functional relationships between biological rates and body size, as well as their association with environmental conditions and species interactions.

Variation in Temperature Dependences across Europe Reveals the Climate Sensitivity of Soil Microbial Decomposers

Temperature is a major determinant of biological process rates, and microorganisms are key regulators of ecosystem carbon (C) dynamics. Temperature controls microbial rates of decomposition, and thus warming can stimulate C loss, creating positive feedback to climate change. If trait distributions that define temperature relationships of microbial communities can adapt to altered temperatures, they could modulate the strength of this feedback, but if this occurs remains unclear. In this study, we sampled soils from a latitudinal climate gradient across Europe. We established the temperature relationships of microbial growth and respiration rates and used these to investigate if and with what strength the community trait distributions for temperature were adapted to their local environment. Additionally, we sequenced bacterial and fungal amplicons to link the variance in community composition to changes in temperature traits. We found that microbial temperature trait distributions varied systematically with climate, suggesting that an increase in mean annual temperature (MAT) of 1°C will result in warm-shifted microbial temperature trait distributions equivalent to an increase in temperature minimum (T_min) of 0.20°C for bacterial growth, 0.07°C for fungal growth, and 0.10°C for respiration. The temperature traits for bacterial growth were thus more responsive to warming than those for respiration and fungal growth. The microbial community composition also varied with temperature, enabling the interlinkage of taxonomic information with microbial temperature traits. Our work shows that the adaptation of microbial temperature trait distributions to a warming climate will affect the C-climate feedback, emphasizing the need to represent this to capture the microbial feedback to climate change. IMPORTANCE One of the largest uncertainties of global warming is if the microbial decomposer feedback will strengthen or weaken soil C-climate feedback. Despite decades of research effort, the strength of this feedback to warming remains unknown. We here present evidence that microbial temperature relationships vary systematically with environmental temperatures along a climate gradient and use this information to forecast how microbial temperature traits will create feedback between the soil C cycle and climate warming. We show that the current use of a universal temperature sensitivity is insufficient to represent the microbial feedback to climate change and provide new estimates to replace this flawed assumption in Earth system models. We also demonstrate that temperature relationships for rates of microbial growth and respiration are differentially affected by warming, with stronger responses to warming for microbial growth (soil C formation) than for respiration (C loss from soil to atmosphere), which will affect the atmosphere-land C balance.

Abiotic selection of microbial genome size in the global ocean

Strong purifying selection is considered a major evolutionary force behind small microbial genomes in the resource-poor photic ocean. However, very little is currently known about how the size of prokaryotic genomes evolves in the global ocean and whether patterns reflect shifts in resource availability in the epipelagic and relatively stable deep-sea environmental conditions. Using 364 marine microbial metagenomes, we investigate how the average genome size of uncultured planktonic prokaryotes varies across the tropical and polar oceans to the hadal realm. We find that genome size is highest in the perennially cold polar ocean, reflecting elongation of coding genes and gene dosage effects due to duplications in the interior ocean microbiome. Moreover, the rate of change in genome size due to temperature is 16-fold higher than with depth up to 200 m. Our results demonstrate how environmental factors can influence marine microbial genome size selection and ecological strategies of the microbiome.

Speed it up: How temperature drives toxicokinetics of organic contaminants in freshwater amphipods

The acceleration of global climate change draws increasing attention towards interactive effects of temperature and organic contaminants. Many studies reported a higher sensitivity of aquatic invertebrates towards contaminant exposure with increasing or fluctuating temperatures. The hypothesis of this study was that the higher sensitivity of invertebrates is associated with the changes of toxicokinetic processes that determine internal concentrations of contaminants and consequently toxic effects. Therefore, the influence of temperature on toxicokinetic processes and the underlying mechanisms were studied in two key amphipod species (Gammarus pulex and Hyalella azteca). Bioconcentration experiments were carried out at four different temperatures with a mixture of 12 exposure relevant polar organic contaminants. Tissue and medium samples were taken in regular intervals and analysed by online solid-phase extraction liquid chromatography high-resolution tandem mass spectrometry. Subsequently, toxicokinetic rates were modelled and analysed in dependence of the exposure temperature using the Arrhenius equation. An exponential relationship between toxicokinetic rates versus temperature was observed and could be well depicted by applying the Arrhenius equation. Due to a similar Arrhenius temperature of uptake and elimination rates, the bioconcentration factors of the contaminants were generally constant across the temperature range. Furthermore, the Arrhenius temperature of the toxicokinetic rates and respiration was mostly similar. However, in some cases (citalopram, cyprodinil), the bioconcentration factor appeared to be temperature dependent, which could potentially be explained by the influence of temperature on active uptake mechanisms or biotransformation. The observed temperature effects on toxicokinetics may be particularly relevant in non-equilibrated systems, such as exposure peaks in summer as exemplified by the exposure modelling of a field measured pesticide peak where the internal concentrations increased by up to fourfold along the temperature gradient. The results provide novel insights into the mechanisms of chemical uptake, biotransformation and elimination in different climate scenarios and can improve environmental risk assessment.

Macromolecular rate theory explains the temperature dependence of membrane conductance kinetics

The factor Q10 is used in neuroscience to adjust reaction rates of voltage-activated membrane conductances to different temperatures and is widely assumed to be constant. By performing an analysis of published data of the reaction rates of sodium, potassium, and calcium membrane conductances, we demonstrate that 1) Q10 is temperature dependent, 2) this relationship is similar across conductances, and 3) there is a strong effect at low temperatures (<15°C). We show that macromolecular rate theory (MMRT) explains this temperature dependency. MMRT predicts the existence of optimal temperatures at which reaction rates decrease as temperature increases, a phenomenon that we also found in the published data sets. We tested the consequences of using MMRT-adjusted reaction rates in the Hodgkin-Huxley model of the squid's giant axon. The MMRT-adjusted model reproduces the temperature dependence of the rising and falling times of the action potential. Furthermore, the model also reproduces these properties for different squid species that live in different climates. In a second example, we compare spiking patterns of biophysical models based on human pyramidal neurons from the Allen Cell Types database at room and physiological temperatures. The original models, calibrated at 34°C, failed to generate realistic spikes at room temperature in more than half of the tested models, while the MMRT produces realistic spiking in all conditions. In another example, we show that using the MMRT correction in hippocampal pyramidal cell models results in 100% differences in voltage responses. Finally, we show that the shape of the Q10 function results in systematic errors in predicting reaction rates. We propose that the optimal temperature could be a thermodynamical barrier to avoid over excitation in neurons. While this study is centered on membrane conductances, our results have important consequences for all biochemical reactions involved in cell signaling.

The sizes of life

Recent research has revealed the diversity and biomass of life across ecosystems, but how that biomass is distributed across body sizes of all living things remains unclear. We compile the present-day global body size-biomass spectra for the terrestrial, marine, and subterranean realms. To achieve this compilation, we pair existing and updated biomass estimates with previously uncatalogued body size ranges across all free-living biological groups. These data show that many biological groups share similar ranges of body sizes, and no single group dominates size ranges where cumulative biomass is highest. We then propagate biomass and size uncertainties and provide statistical descriptions of body size-biomass spectra across and within major habitat realms. Power laws show exponentially decreasing abundance (exponent -0.9±0.02 S.D., R2 = 0.97) and nearly equal biomass (exponent 0.09±0.01, R2 = 0.56) across log size bins, which resemble previous aquatic size spectra results but with greater organismal inclusivity and global coverage. In contrast, a bimodal Gaussian mixture model describes the biomass pattern better (R2 = 0.86) and suggests small (~10-15 g) and large (~107 g) organisms outweigh other sizes by one order magnitude (15 and 65 Gt versus ~1 Gt per log size). The results suggest that the global body size-biomass relationships is bimodal, but substantial one-to-two orders-of-magnitude uncertainty mean that additional data will be needed to clarify whether global-scale universal constraints or local forces shape these patterns.

The methanogen core and pangenome: conservation and variability across biology's growth temperature extremes

Temperature is a key variable in biological processes. However, a complete understanding of biological temperature adaptation is lacking, in part because of the unique constraints among different evolutionary lineages and physiological groups. Here we compared the genomes of cultivated psychrotolerant and thermotolerant methanogens, which are physiologically related and span growth temperatures from -2.5°C to 122°C. Despite being phylogenetically distributed amongst three phyla in the archaea, the genomic core of cultivated methanogens comprises about one-third of a given genome, while the genome fraction shared by any two organisms decreases with increasing phylogenetic distance between them. Increased methanogenic growth temperature is associated with reduced genome size, and thermotolerant organisms-which are distributed across the archaeal tree-have larger core genome fractions, suggesting that genome size is governed by temperature rather than phylogeny. Thermotolerant methanogens are enriched in metal and other transporters, and psychrotolerant methanogens are enriched in proteins related to structure and motility. Observed amino acid compositional differences between temperature groups include proteome charge, polarity and unfolding entropy. Our results suggest that in the methanogens, shared physiology maintains a large, conserved genomic core even across large phylogenetic distances and biology's temperature extremes.