An evaluation of a biophysical model for predicting avian thermoregulation in the heat.

Survival and reproduction of endotherms depend on their ability to balance energy and water exchange with their environment, avoiding lethal deficits and maximising gains for growth and reproduction. At high environmental temperatures, diurnal endotherms maintain body temperature (Tb) below lethal limits via physiological and behavioural adjustments. Accurate models of these processes are crucial for predicting effects of climate variability on avifauna. We evaluated the performance of a biophysical model (NicheMapR) for predicting evaporative water loss (EWL), resting metabolic rate (RMR) and Tb at environmental temperatures approaching or exceeding normothermic Tb for three arid-zone birds: southern yellow-billed hornbill (Tockus leucomelas), southern pied babbler (Turdoides bicolor) and southern fiscal (Lanius collaris). We simulated metabolic chamber conditions and compared model outputs with thermal physiology data collected at air temperatures (Tair) between 10 and 50°C. Additionally, we determined the minimum data needed to accurately model diurnal birds' thermoregulatory responses to Tair using sensitivity analyses. Predicted EWL, metabolic rate and Tb corresponded tightly with observed values across Tair, with only minor discrepancies for EWL in two species at Tair≈35°C. Importantly, the model captured responses at Tair=30-40°C, a range spanning threshold values for sublethal fitness costs associated with sustained hot weather in arid-zone birds. Our findings confirm how taxon-specific parameters together with biologically relevant morphological data can accurately model avian thermoregulatory responses to heat. Biophysical models can be used as a non-invasive way to predict species' sensitivity to climate, accounting for organismal (e.g. physiology) and environmental factors (e.g. microclimates).

Comment on "Metabolic scaling is the product of life-history optimization".

The model used by White et al. (1) to explore life-history optimization of metabolic scaling has limited ability to capture observed combinations of growth and reproduction, including those of the domestic chicken. The analyses and interpretations may change substantially with realistic parameters. The model's biological and thermodynamic realism needs further exploration and justification before being applied to life-history optimization studies.

Long-term biogeographical processes dominate patterns of genetic diversity in a wingless grasshopper despite substantial recent habitat fragmentation.

Low-vagility species may hold strong genetic signatures of past biogeographical processes but are also vulnerable to habitat loss. Flightless grasshoppers of the morabine group were once widespread in southeastern Australia, including Tasmania, but are becoming restricted to remnant patches of vegetation, with local ranges impacted by agriculture and development as well as management. Habitat fragmentation can generate genetically differentiated "island" populations with low genetic variation. However, following revegetation, populations could be re-established, and gene flow increased. Here we characterize single nucleotide polymorphism-based genetic variation in a widespread chromosomal race of the morabine Vandiemenella viatica (race 19) to investigate the genetic health of remnant populations and to provide guidelines for restoration efforts. We update the distribution of this race to new sites in Victoria and Tasmania, and show that V. viatica populations from northern Tasmania and eastern Victoria have reduced genetic variation compared to other mainland populations. In contrast, there was no effect of habitat fragment size on genetic variation. Tasmanian V. viatica populations fell into two groups, one connected genetically to eastern Victoria and the other connected to southwestern Victoria. Mainland populations showed isolation by distance. These patterns are consistent with expectations from past biogeographical processes rather than local recent population fragmentation and emphasize the importance of small local reserves in preserving genetic variation. The study highlights how genomic analyses can combine information on genetic variability and population structure to identify biogeographical patterns within a species, which in turn can inform decisions on potential source populations for translocations.

Global patterns of climate change impacts on desert bird communities.

The world's warm deserts are predicted to experience disproportionately large temperature increases due to climate change, yet the impacts on global desert biodiversity remain poorly understood. Because species in warm deserts live close to their physiological limits, additional warming may induce local extinctions. Here, we combine climate change projections with biophysical models and species distributions to predict physiological impacts of climate change on desert birds globally. Our results show heterogeneous impacts between and within warm deserts. Moreover, spatial patterns of physiological impacts do not simply mirror air temperature changes. Climate change refugia, defined as warm desert areas with high avian diversity and low predicted physiological impacts, are predicted to persist in varying extents in different desert realms. Only a small proportion (<20%) of refugia fall within existing protected areas. Our analysis highlights the need to increase protection of refugial areas within the world's warm deserts to protect species from climate change.

Mechanistic forecasts of species responses to climate change: The promise of biophysical ecology.

A core challenge in global change biology is to predict how species will respond to future environmental change and to manage these responses. To make such predictions and management actions robust to novel futures, we need to accurately characterize how organisms experience their environments and the biological mechanisms by which they respond. All organisms are thermodynamically connected to their environments through the exchange of heat and water at fine spatial and temporal scales and this exchange can be captured with biophysical models. Although mechanistic models based on biophysical ecology have a long history of development and application, their use in global change biology remains limited despite their enormous promise and increasingly accessible software. We contend that greater understanding and training in the theory and methods of biophysical ecology is vital to expand their application. Our review shows how biophysical models can be implemented to understand and predict climate change impacts on species' behavior, phenology, survival, distribution, and abundance. It also illustrates the types of outputs that can be generated, and the data inputs required for different implementations. Examples range from simple calculations of body temperature at a particular site and time, to more complex analyses of species' distribution limits based on projected energy and water balances, accounting for behavior and phenology. We outline challenges that currently limit the widespread application of biophysical models relating to data availability, training, and the lack of common software ecosystems. We also discuss progress and future developments that could allow these models to be applied to many species across large spatial extents and timeframes. Finally, we highlight how biophysical models are uniquely suited to solve global change biology problems that involve predicting and interpreting responses to environmental variability and extremes, multiple or shifting constraints, and novel abiotic or biotic environments.

Parthenogenesis without costs in a grasshopper with hybrid origins.

The rarity of parthenogenetic species is typically attributed to the reduced genetic variability that accompanies the absence of sex, yet natural parthenogens can be surprisingly successful. Ecological success is often proposed to derive from hybridization through enhanced genetic diversity from repetitive origins or enhanced phenotypic breadth from heterosis. Here, we tested and rejected both hypotheses in a classic parthenogen, the diploid grasshopper Warramaba virgo. Genetic data revealed a single hybrid mating origin at least 0.25 million years ago, and comparative analyses of 14 physiological and life history traits showed no evidence for altered fitness relative to its sexual progenitors. Our findings imply that the rarity of parthenogenesis is due to constraints on origin rather than to rapid extinction.

An endangered flightless grasshopper with strong genetic structure maintains population genetic variation despite extensive habitat loss.

Conservation research is dominated by vertebrate examples but the shorter generation times and high local population sizes of invertebrates may lead to very different management strategies, particularly for species with low movement rates. Here we investigate the genetic structure of an endangered flightless grasshopper, Keyacris scurra, which was used in classical evolutionary studies in the 1960s. It had a wide distribution across New South Wales (NSW) and Victoria in pre-European times but has now become threatened because of land clearing for agriculture and other activities. We revisited remnant sites of K. scurra, with populations now restricted to only one area in Victoria and a few small patches in NSW and the Australian Capital Territory (ACT). Using DArtseq to generate SNP markers as well as mtDNA sequence data, we show that the remaining Victorian populations in an isolated valley are genetically distinct from the NSW populations and that all populations tend to be genetically unique, with large F ST values up to 0.8 being detected for the SNP datasets. We also find that, with one notable exception, the NSW/ACT populations separate genetically into previously described chromosomal races (2n = 15 vs. 2n = 17). Isolation by distance was detected across both the SNP and mtDNA datasets, and there was substantial differentiation within chromosomal races. Genetic diversity as measured by heterozygosity was not correlated with the size of remaining habitat where the populations were found, with high variation present in some remnant cemetery sites. However, inbreeding correlated negatively with estimated habitat size at 25-500 m patch radius. These findings emphasize the importance of small habitat areas in conserving genetic variation in such species with low mobility, and they highlight populations suitable for future translocation efforts.

A general model of the thermal constraints on the world's most destructive locust, Schistocerca gregaria.

All terrestrial ectotherms are constrained to some degree by their thermal environment and the extent to which they can behaviorally buffer variable thermal conditions. New biophysical modeling methods (NicheMapR) allow the calculation of the body temperature of thermoregulating animals anywhere in the world from first principles, but require detailed observational data for parameterization and testing. Here we describe the thermoregulatory biology of marching bands of the desert locust, Schistocerca gregaria, in the Sahara Desert of Mauritania where extreme heat and strong diurnal fluctuations are a major constraint on activity and physiological processes. Using a thermal infrared camera in the field, we showed that gregarious nymphs altered the microhabitats they used, as well as postural thermoregulatory behaviors, to maintain relatively high body temperature (nearly 40°C). Field and laboratory experiments demonstrated that the preferred body temperature accelerated digestive rates. Migratory bands frequently left foraging sites with full guts before consuming all vegetation and moved to another habitat before emptying their foregut. Thus, the repertoire for behavioral thermoregulation in the desert locust strongly facilitates foraging and digestion rates, which may accelerate developmental rates and increase survival. We used our data to successfully parameterize a general biophysical model of thermoregulatory behavior that could capture hourly body temperature and activity at our remote site using globally available environmental forcing data. This modeling approach provides a stronger basis for forecasting thermal constraints on locust outbreaks under current and future climates.

Three questions about the eco-physiology of overwintering underground.

In cold environments ectotherms can be dormant underground for long periods. In 1941 Cowles proposed an ecological trade-off involving the depth at which ectotherms overwintered: on warm days, only shallow reptiles could detect warming soils and become active; but on cold days, they risked freezing. Cowles discovered that most reptiles at a desert site overwintered at shallow depths. To extend his study, we compiled hourly soil temperatures (5 depths, 90 sites, continental USA) and physiological data, and simulated consequences of overwintering at fixed depths. In warm localities shallow ectotherms have lowest energy costs and largest reserves in spring, but in cold localities, they risk freezing. Ectotherms shifting hourly to the coldest depth potentially reduce energy expenses, but paradoxically sometimes have higher expenses than those at fixed depths. Biophysical simulations for a desert site predict that shallow ectotherms have increased opportunities for mid-winter activity but need to move deep to digest captured food. Our simulations generate testable predictions to eco-physiological questions but rely on physiological responses to acute cold rather than to natural cooling profiles. Furthermore, natural-history data to test most predictions do not exist. Thus, our simulation approach uncovers knowledge gaps and suggests research agendas for studying ectotherms overwintering underground.

What is the status of metabolic theory one century after Pütter invented the von Bertalanffy growth curve?

Metabolic theory aims to tackle ecological and evolutionary problems by explicitly including physical principles of energy and mass exchange, thereby increasing generality and deductive power. Individual growth models (IGMs) are the fundamental basis of metabolic theory because they represent the organisational level at which energy and mass exchange processes are most tightly integrated and from which scaling patterns emerge. Unfortunately, IGMs remain a topic of great confusion and controversy about the origins of the ideas, their domain and breadth of application, their logical consistency and whether they can sufficiently capture reality. It is now 100 years since the first theoretical model of individual growth was put forward by Pütter. His insights were deep, but his model ended up being attributed to von Bertalanffy and his ideas largely forgotten. Here I review Pütter's ideas and trace their influence on existing theoretical models for growth and other aspects of metabolism, including those of von Bertalanffy, the Dynamic Energy Budget (DEB) theory, the Gill-Oxygen Limitation Theory (GOLT) and the Ontogenetic Growth Model (OGM). I show that the von Bertalanffy and GOLT models are minor modifications of Pütter's original model. I then synthesise, compare and critique the ideas of the two most-developed theories, DEB theory and the OGM, in relation to Pütter's original ideas. I formulate the Pütter, DEB and OGM models in the same structure and with the same notation to illustrate the major similarities and differences among them. I trace the confusion and controversy regarding these theories to the notions of anabolism, catabolism, assimilation and maintenance, the connections to respiration rate, and the number of parameters and state variables their models require. The OGM model has significant inconsistencies that stem from the interpretation of growth as the difference between anabolism and maintenance, and these issues seriously challenge its ability to incorporate development, reproduction and assimilation. The DEB theory is a direct extension of Pütter's ideas but with growth being the difference between assimilation and maintenance rather than anabolism and catabolism. The DEB theory makes the dynamics of Pütter's 'nutritive material' explicit as well as extending the scheme to include reproduction and development. I discuss how these three major theories for individual growth have been used to explain 'macrometabolic' patterns including the scaling of respiration, the temperature-size rule (first modelled by Pütter), and the connection to life history. Future research on the connections between theory and data in these macrometabolic topics have the greatest potential to advance the status of metabolic theory and its value for pure and applied problems in ecology and evolution.

Future winters present a complex energetic landscape of decreased costs and reduced risk for a freeze-tolerant amphibian, the Wood Frog (Lithobates sylvaticus).

Winter climate warming is rapidly leading to changes in snow depth and soil temperatures across mid- and high-latitude ecosystems, with important implications for survival and distribution of species that overwinter beneath the snow. Amphibians are a particularly vulnerable group to winter climate change because of the tight coupling between their body temperature and metabolic rate. Here, we used a mechanistic microclimate model coupled to an animal biophysics model to predict the spatially explicit effects of future climate change on the wintering energetics of a freeze-tolerant amphibian, the Wood Frog (Lithobates sylvaticus), across its distributional range in the eastern United States. Our below-the-snow microclimate simulations were driven by dynamically downscaled climate projections from a regional climate model coupled to a one-dimensional model of the Laurentian Great Lakes. We found that warming soil temperatures and decreasing winter length have opposing effects on Wood Frog winter energy requirements, leading to geographically heterogeneous implications for Wood Frogs. While energy expenditures and peak body ice content were predicted to decline in Wood Frogs across most of our study region, we identified an area of heightened energetic risk in the northwestern part of the Great Lakes region where energy requirements were predicted to increase. Because Wood Frogs rely on body stores acquired in fall to fuel winter survival and spring breeding, increased winter energy requirements have the potential to impact local survival and reproduction. Given the geographically variable and intertwined drivers of future under-snow conditions (e.g., declining snow depths, rising air temperatures, shortening winters), spatially explicit assessments of species energetics and risk will be important to understanding the vulnerability of subnivium-adapted species.

Tracheal branching in ants is area-decreasing, violating a central assumption of network transport models.

The structure of tubular transport networks is thought to underlie much of biological regularity, from individuals to ecosystems. A core assumption of transport network models is either area-preserving or area-increasing branching, such that the summed cross-sectional area of all child branches is equal to or greater than the cross-sectional area of their respective parent branch. For insects, the most diverse group of animals, the assumption of area-preserving branching of tracheae is, however, based on measurements of a single individual and an assumption of gas exchange by diffusion. Here we show that ants exhibit neither area-preserving nor area-increasing branching in their abdominal tracheal systems. We find for 20 species of ants that the sum of child tracheal cross-sectional areas is typically less than that of the parent branch (area-decreasing). The radius, rather than the area, of the parent branch is conserved across the sum of child branches. Interpretation of the tracheal system as one optimized for the release of carbon dioxide, while readily catering to oxygen demand, explains the branching pattern. Our results, together with widespread demonstration that gas exchange in insects includes, and is often dominated by, convection, indicate that for generality, network transport models must include consideration of systems with different architectures.

The resilience of coastal marshes to hurricanes: The potential impact of excess nutrients.

Hurricanes pose an increasing threat to coastal environments as the intensity and severity of hurricanes are predicted to increase under the changing climate. Coastal wetlands are effective nature-based defenses of coastal cities against storms. However, the ecosystems themselves are also susceptible to the impacts of hurricanes, which are highly complex and not fully understood. Here we utilize multi-decadal satellite data archives (Landsat 1984-2014 and MODIS 2005-2015) and long-term coast-wide field-based environmental data (1978-2018) to investigate the impacts of hurricanes Katrina (2005), Gustav (2008), and Isaac (2012) on the coastal marshes in Louisiana, USA, where the hurricanes made landfall. While the hurricanes had immediate impacts on the marshes' biomass and area at an ecosystem scale, general recovery was observed in the next one and two years. We also found that the most severe damage always occurred in the intermediate and brackish marshes of the Breton Sound basin, where the nitrogen concentration in the water was significantly higher compared to areas with less damage (P < 0.01). Because excess nutrient can reduce the marshes' root growth and degrade their root mat, we posit that the long-term nutrient enrichment in the area, which resulted from the diverted Mississippi River water, has increased the marshes' susceptibility to hurricanes. The results highlight the resilience of coastal marsh ecosystems against hurricanes, but also underline the profound synergistic effects of climatic and anthropogenic factors on the sustainability of coastal ecosystems, which have important implications for coastal management under the current climate trend.

Publisher Correction: Open Science principles for accelerating trait-based science across the Tree of Life.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The roles of acclimation and behaviour in buffering climate change impacts along elevational gradients.

The vulnerability of species to climate change is jointly influenced by geographic phenotypic variation, acclimation and behavioural thermoregulation. The importance of interactions between these factors, however, remains poorly understood. We demonstrate how advances in mechanistic niche modelling can be used to integrate and assess the influence of these sources of uncertainty in forecasts of climate change impacts. We explored geographic variation in thermal tolerance (i.e. maximum and minimum thermal limits) and its potential for acclimation in juvenile European common frogs Rana temporaria along elevational gradients. Furthermore, we employed a mechanistic niche model (NicheMapR) to assess the relative contributions of phenotypic variation, acclimation and thermoregulation in determining the impacts of climate change on thermal safety margins and activity windows. Our analyses revealed that high-elevation populations had slightly wider tolerance ranges driven by increases in heat tolerance but lower potential for acclimation. Plausibly, wider thermal fluctuations at high elevations favour more tolerant but less plastic phenotypes, thus reducing the risk of encountering stressful temperatures during unpredictable extreme events. Biophysical models of thermal exposure indicated that observed phenotypic and plastic differences provide limited protection from changing climates. Indeed, the risk of reaching body temperatures beyond the species' thermal tolerance range was similar across elevations. In contrast, the ability to seek cooler retreat sites through behavioural adjustments played an essential role in buffering populations from thermal extremes predicted under climate change. Predicted climate change also altered current activity windows, but high-elevation populations were predicted to remain more temporally constrained than lowland populations. Our results demonstrate that elevational variation in thermal tolerances and acclimation capacity might be insufficient to buffer temperate amphibians from predicted climate change; instead, behavioural thermoregulation may be the only effective mechanism to avoid thermal stress under future climates.

Microclimate modelling of beach sand temperatures reveals high spatial and temporal variation at sea turtle rookeries.

The continual development of ecological models and availability of high-resolution gridded climate surfaces have stimulated studies that link climate variables to functional traits of organisms. A primary constraint of these studies is the ability to reliably predict the microclimate that an organism experiences using macroscale climate inputs. This is particularly important in regions where access to empirical information is limited. Here, we contrast correlative models based on both ambient and sea surface temperatures to mechanistic modelling approaches to predict beach sand temperatures at depths relevant to sea turtle nesting. We show that mechanistic models are congruent with correlative models at predicting sand temperatures. We used these predictions to explore thermal variation across 46 mainland and island beaches that span the geographical range of sea turtle nesting in Western Australia. Using high resolution gridded climate surfaces and site-specific soil reflectance, we predict almost 9 °C variation in average annual temperatures between beaches, and nearly 10 °C variation in average temperatures during turtle nesting seasons. Validation of models demonstrated that predictions were typically within 2 °C of observations and, although most sites had high correlations (r2 > 0.7), predictive capacity varied between sites. An advantage of the mechanistic model demonstrated here is that it can be used to explore the impacts of climate change on sea turtle nesting beach temperatures as, unlike correlative models, it can be forced with novel combinations of environmental variables.

Open Science principles for accelerating trait-based science across the Tree of Life.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.