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AnimalTraits - a curated animal trait database for body mass, metabolic rate and brain size

Abstract

Trait databases have become important resources for large-scale comparative studies in ecology and evolution. Here we introduce the AnimalTraits database, a curated database of body mass, metabolic rate and brain size, in standardised units, for terrestrial animals. The database has broad taxonomic breadth, including tetrapods, arthropods, molluscs and annelids from almost 2000 species and 1000 genera. All data recorded in the database are sourced from their original empirical publication, and the original metrics and measurements are included with each record. This allows for subsequent data transformations as required. We have included rich metadata to allow users to filter the dataset. The additional R scripts we provide will assist researchers with aggregating standardised observations into species-level trait values. Our goals are to provide this resource without restrictions, to keep the AnimalTraits database current, and to grow the number of relevant traits in the future.

Measurement(s) metabolic rate quantification • body mass • brain size
Technology Type(s) metabolic rate measurement • body mass quantification • brain mass brain volume

Background & Summary

Large, multi-species trait-based comparative approaches have been successfully applied in animal and plant functional ecology, comparative physiology and macroevolution1,2,3,4, and bacterial and archaeal traits5,6. More recently, there have been calls to establish more taxon-specific databases7. Trait databases provide a major boost to this research by concentrating scattered trait data into one central repository. For example, the quantification of functional diversity in 46,000 vascular plants enabled the generation of a global trait space into which plant lineages and plant communities were mapped8. Trait databases also have application to conservation. For example, a trait database of corals was used to better understand the mechanisms associated with coral bleaching9.

The disciplines of animal physiology, ecology and behaviour have a long tradition of collating large volumes of trait data into meta-analyses to test theoretical predictions. For example, comparative methods have been applied to ask questions about insect body size variation2, the relationship between reptile brain size, sociality, and environmental complexity10, the phenological response of animals to climate change11, and variation in metabolic rate across all domains of life12. These databases are usually static and have been amassed with very specific questions in mind. They often include some form of data transformation from the original published data and may incorporate previously published data sets that have also applied various data transformations. These approaches limit the future usefulness of these data compilations because the ability to transform original raw data into alternative metrics carries data integrity risks that are difficult - if not impossible - to detect and correct.

Here, we introduce a curated animal trait database that includes three basic functional traits: body size, metabolic rate, and brain size, for terrestrial animals. Each row in the database is an ‘observation’; one or more trait values measured from a single specimen or group of specimens of the same species. These observations can be aggregated into species-mean trait values using the R script we provide. We have limited our database to these initial traits because they are central to many ecological questions and in order to prioritize exceptionally ‘clean’ data. We intend to continue to expand the number of included traits with time. The distinctive value of this new animal trait database is four-fold:

  1. 1)

    Open access: the data are openly available to researchers without restrictions13;

  2. 2)

    Taxonomic breadth: the database includes a broad taxonomic range of terrestrial animal species including several groups of tetrapods and arthropods, as well as molluscs and annelids;

  3. 3)

    Clean, empirical data: all data are sourced from the original publication that made and reported on the included measurements, and are entered into the database using the original metrics – all subsequent transformations can be applied to these original data, meaning it is eminently reusable by future researchers;

  4. 4)

    Annotation: we have included useful methodological metadata (such as measurement method and parameters) that allow researchers to filter the dataset as needed.

While the AnimalTraits database is relatively small compared to other studies that have amassed data on the same or similar traits, its distinguishing feature is that it contains high quality raw data. Raw data are often no longer available from published databases that might only include species mean values based on unknown sample sizes, often even single datapoints. Moreover, the AnimalTraits database also includes the sample size of means or ranges when those were available from the original papers. This allows the user to exercise ultimate control over data selection.

Methods

Our goal was to generate a reliable and high-quality trait database with ultimate transparency and flexibility, while minimising error prone manual or ad hoc data conversions. For example, some data compilations only report converted data (e.g. watts for metabolic rates), without providing the raw data and the conversion equation. This not only limits the utility of the data, as they cannot be converted back to their original form, but it also prevents any form of quality control associated with converting the data.

Our database compilation process consisted of the following steps:

  1. 1.

    Data selection: identifying sources of trait data from peer reviewed papers.

  2. 2.

    Transcription: manually extracting the data and transcribing them into a comma-separated values (CSV) file (a ‘raw’ data file), retaining the measurement units as published.

  3. 3.

    Standardisation: programmatically reading all raw data files, converting to standard units for each trait, performing data validity checks, and combining into a single CSV file of standardised observations (performed in R, scripts available in auxiliary material).

  4. 4.

    Quality control: performing additional data quality checks (see below) on the standardised observations; correcting any processing errors and excluding problematic data from the database.

To build the trait database, we collected measurements of body mass, brain size and metabolic rate from published, peer-reviewed data sources. Not all three variables had to be reported in the original source to be included in the database. Any units of body mass or weight were acceptable for recording body mass in the raw files. Brain sizes were recorded as either volume or mass. We accepted raw metabolic rates expressed as rate of CO2 production, rate of O2 consumption, or rate of energy transfer, i.e. power measured in watts or joules/sec. Both mass-specific metabolic rate (consumption of energy per gram of body mass per unit of time) and whole-body metabolic rate (consumption of energy for the whole body per unit of time) were recorded from the source data. Mass-specific metabolic rate was converted to whole-body metabolic rate (or vice versa) when the data source provided a value for body mass. We further recorded the method used to measure metabolic rate, e.g. basal or resting metabolic rate (metabolic rate of an inactive, fasting animal in its thermal neutral zone), standard metabolic rate (resting metabolic rate of an ectotherm), or field metabolic rate (average respiration rates of free living animals). In the database (‘metabolic rate- method’ column), we recorded the type of metabolic rate measured as specified by the original researchers.

We created one raw file for each source data publication (Table 1), with all observations transcribed into a predefined set of columns (raw data columns are described in the Template.xslx spreadsheet in the auxiliary material). Each row contained a single trait measurement. Each measured entity (i.e. an animal or a group of animals measured together) was assigned an object identifier that was unique within the raw file. This meant that when multiple traits were measured for a single entity (such as both body mass and metabolic rate), those measurements shared the same object identifier. To minimise transcription or unit conversion errors, values were transcribed into the raw file as originally reported in the source document, along with the reported units. When a paper described multiple treatment groups, we collected data from the control or the ‘least manipulated’ group. We also recorded the temperature at which metabolic rate was recorded and the applicable respiratory quotient (if reported).

Table 1 Summary of the traits contained in the Animal Trait Database and the primary source for the data.

Whenever possible, we collected traits measured from a single individual; however, we also allowed mean values with sample sizes or a range of values to be specified as ‘min – max’ (together with a sample size). During standardisation, ranges were reduced to their midpoints, although the minimum and maximum values were also standardised and recorded in the database. In the current release of the database, two data sources (49 observations) specified a range for body mass, and no other traits were specified as range. If a user prefers not to use range reduction to midpoint for an application, such rows can be manually filtered from the database before use by selecting non-empty minimum or maximum values. Measurement units allowed optional additional information within round brackets, e.g. ‘(CO2) ml’ or ‘(O2) l’ for metabolic rate measured as either millilitres of CO2 produced or litres of O2 consumed, respectively.

Standardisation

The standardisation step consisted of compiling R scripts14 that read the raw data CSV files, performed various checks, transformed the values into standard units, then wrote the result to a single CSV file of standardised observations. We included the following checks: trait type was ‘body mass’, ‘metabolic rate’, ‘mass-specific metabolic rate’ or ‘brain size’; units were known and interpretable (detail below); and scientific names were defined by the R package taxize15. In addition, we checked the binomial names against several databases (see auxiliary material) and corrected any flagged spelling errors. We updated any binomial name changes that we were aware of and encourage readers to contact us with further updates.

The automated conversion process was implemented to avoid a class of errors potentially introduced by manual conversion of values during data entry. Preserving the source units makes it simple to double-check for transcription errors by comparing the transcribed raw data files with the source data. Base units were converted using the R packages units16 and udunits217. Some traits required additional, non-standard unit conversion handling. Units sometimes contained a numeric factor (prefixed by ‘x’), which was multiplied with the trait value (e.g. ‘x6.4e-5 mm3’) during the standardisation step.

We converted raw units of body mass to kilograms during the standardisation process. Mass and volume measures of brain sizes were standardised to mass in kilograms. While users can apply their own statistics to convert brain volume to mass, we included this step as an additional service to users applying published conversion metrics with an assumed density of 1.036 g/mL e.g.18,19. This conversion factor is based on gravity measurements of fresh vertebrate brain tissue.

All metabolic rates were converted to watts. To achieve this, CO2 production was first converted to the equivalent consumption of O2. This conversion was only possible when the respiratory quotient (q) was specified in the original data source and recorded in the raw CSV file. Conversion of CO2 production to O2 consumption used the equation

$${O}_{2}=C{O}_{2}/q$$
(1)

Rate of O2 consumption was converted to watts by multiplying by a conversion factor of 20 J/ml12. Non-endothermic metabolic rates, q, measured at a temperature other than 25 °C were transformed to their equivalent at 25 °C, q25, with the equation

$${{\rm{q}}}_{25}={\rm{q}}\times {Q}_{10}^{(25-T)/1{0}^{\circ }C}$$
(2)

where Q10 is the temperature coefficient; the factor by which the metabolic rate changes for each change of 10 temperature units. We used Q10 = 2.21 or 2.44 for amphibians and reptiles respectively, and 2 for all other non-endothermic taxa (which were arachnids, insects, crustaceans and myriapods)12. Q10 values can be updated in light of more specific values becoming available in future. The standardisation parameters follow Makarieva et al.12, however they can be modified and the database recompiled by users wishing to use different parameters or output units (see Usage Notes).

Both mass-specific and whole-body metabolic rate were handled by the standardisation process. Mass-specific metabolic rate was converted to whole-body metabolic rate (and vice versa) if the observation also included a value for body mass.

Data Records

As we grow this database, new versions will be released along with any corrections.

At the time of publication, the animal traits database contained over 3500 observations from over 200 data sources. The almost 2000 terrestrial species in the database came from over 1000 genera, 350 families, 90 orders and four phyla (Chordata, Arthropoda, Annelida, Mollusca). For the majority of species in the database, we transcribed body mass data (>1700 species) and brain size data (>1400 species), with both traits recorded for over 1200 species (Table 1). The database contains metabolic rate data for over 600 species. Body mass measurements span 10 orders of magnitude (Fig. 1), while metabolic rates and brain sizes both span 8 orders of magnitude (Fig. 1). Details of trait data are summarised in Table 1 along with the primary sources, which should be referenced wherever possible.

Fig. 1
figure 1

Overview of the ranges of trait values in the database at time of publication. Each point represents a single observation of (a) body mass and metabolic rate, and (b) body mass and brain size. To orient the reader, some taxa with outstanding trait values are labelled in the graph. The differing allometries of endotherms and ectotherms are apparent for both metabolic rate and brain size. Axes are log-scaled.

The database is under a CC0 1.0 licence with unrestricted use. It consists of a single CSV file (docs/observations.csv in the online auxiliary material on Zenodo20 (also under a CCO 1.0 licence) or accessible from the website https://animaltraits.org) The database columns are described in the online file docs/column-documentation.csv. We also provide an Excel spreadsheet that contains both the database content and the column descriptions as separate worksheets (docs/observations.xlsx online or downloadable from the website). The auxiliary material includes all raw CSV data files (located within the data/raw folder) and the R scripts used to compile and standardise the raw data into the final database (located within the R folder), as well as the source for the website (in the docs folder). Text files named README.md in most folders describe the auxiliary material in greater detail.

The database contains one row per observation. It includes columns that describe the specimen taxa, sex (when specified), sample size, full data source reference and optional comments. Each trait has columns for the standardised trait value and units, the original trait value and units, and the (standardised) minimum and maximum values for ranges. Additional columns include the temperature at which metabolic rate was recorded and the respiratory quotient used to convert from CO2 production to the equivalent O2 consumption. Metadata columns for metabolic rate apply to both metabolic rate and mass-specific metabolic rate. The columns are fully documented in the auxiliary material.

We provide R scripts to assist with aggregating standardised observations into species-level trait values (see below, Code Availability). We provide a script rather than a standard species-traits data set, in order to provide flexibility to customise the aggregation as needed. In this way, researchers have full control over both the records to be combined and the way in which they are combined. For example, a researcher might choose to exclude body mass observations recorded as a range, and aggregate males and females separately.

Technical Validation

We included only peer reviewed data sources that reported original observations (thus not from reviews, meta-analyses or existing databases or data compilations) on terrestrial animals identified to genus or species. Data sources that were difficult to interpret, or from which raw data measurements could not be extracted, were excluded. We used reviews and meta-analyses to identify suitable papers from which we extracted the original data.

Our unit conversion scripts detected and reported an error for several types of data entry issues, including when the conversion script was unable to convert the units, which most likely indicates a data entry error. Furthermore, invalid, incomplete or problematic data generated warnings, including unknown taxa or metabolic rate specified as CO2 production with no respiratory quotient. Additional quality check steps involved plotting results and checking for outliers.

Whenever a problem was reported by the standardisation or quality check steps, we first checked if it was caused by a transcription error by comparing the raw file to the source data. If so, we fixed the raw file. Otherwise, we checked if the problem resulted from a failure of the standardisation step (i.e., a programming error). If it did, we fixed the standardisation scripts, otherwise we checked if an error was apparent in the source paper, such as incorrect units or a misplaced decimal place. If we found an apparent error in the source data or the observation could not be standardised, we excluded either the entire data source or else the problematic observations. Otherwise, we retained the paper and data.

Usage Notes

This database can be used to address a number of current biological questions including how metabolic rate and brain size scale to body size in broad taxonomic groups. More focused questions can be addressed by combining it with additional species-specific data such as behaviour, distribution or range limits, life history tactics or pace of life, or phylogenetic and genomic data. Advanced users are able to use the supplied R scripts to compile and standardise the database using different standardisation parameters or output units; see the online file R/README.md for more details. Finally, as we have included metadata on the methods for obtaining metabolic rate and brain size, the impact of method bias on rate and size estimate can be explored. The database is available in the auxiliary material20, and it can be download as either a UTF-8 encoded CSV file or a Microsoft Excel spreadsheet file from https://animaltraits.org.

Access

The static version of the dataset described here is available via Zenodo20 under a CC0 1.0 licence, which allows for the unrestricted use of the dataset. We kindly ask that users of the database cite this descriptor and the original sources cited within this descriptor.

Code availability

The observations database, all raw CSV files and the R scripts used to standardise and check the observations, as well as a sample script to aggregate the observations database into a species-trait data set are available in the auxiliary material20. The auxiliary material also contains README.txt files that describe the structure and usage of the data and scripts. The auxiliary material is managed as a GitHub repository (https://github.com/animaltraits/animaltraits.github.io). GitHub is also used to build and serve the website.

References

  1. Westoby, M. & Wright, I. J. Land-plant ecology on the basis of functional traits. Trends Ecol. Evol. 21, 261–268 (2006).

    Article  Google Scholar 

  2. Chown, S. L. & Gaston, K. J. Body size variation in insects: a macroecological perspective. Biol. Rev. Camb. Philos. Soc. 85, 139–169 (2010).

    Article  Google Scholar 

  3. Parr, C. L. et al. GlobalAnts: a new database on the geography of ant traits (Hymenoptera: Formicidae). Insect Conserv. Divers. 10, 5–20 (2017).

    Article  Google Scholar 

  4. Wolff, J. O., Wierucka, K., Uhl, G. & Herberstein, M. E. Building behavior does not drive rates of phenotypic evolution in spiders. Proceedings of the National Academy of Sciences 118, e2102693118 (2021).

    CAS  Article  Google Scholar 

  5. Le Boulch, M., Déhais, P., Combes, S. & Pascal, G. The MACADAM database: a MetAboliC pAthways DAtabase for Microbial taxonomic groups for mining potential metabolic capacities of archaeal and bacterial taxonomic groups. Database 2019 (2019).

  6. Madin, J. S. et al. A synthesis of bacterial and archaeal phenotypic trait data. Scientific Data 7, 170 (2020).

    CAS  Article  Google Scholar 

  7. Lowe, E. C., Wolff, J. O. & Aceves-Aparicio, A. Towards establishment of a centralized spider traits database. The Journal of Arachnology (2020).

  8. Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).

    ADS  Article  Google Scholar 

  9. Mizerek, T. L., Baird, A. H. & Madin, J. S. Species traits as indicators of coral bleaching. Coral Reefs 37, 791–800 (2018).

    ADS  Article  Google Scholar 

  10. De Meester, G. & Huyghe, K. & Van Damme, R. Brain size, ecology and sociality: a reptilian perspective. Biol. J. Linn. Soc. Lond. 126, 381–391 (2019).

    Article  Google Scholar 

  11. Cohen, J. M., Lajeunesse, M. J. & Rohr, J. R. A global synthesis of animal phenological responses to climate change. Nat. Clim. Chang. 8, 224–228 (2018).

    ADS  Article  Google Scholar 

  12. Makarieva, A. M. et al. Mean mass-specific metabolic rates are strikingly similar across life’s major domains: Evidence for life’s metabolic optimum. Proceedings of the National Academy of Sciences 105, 16994 (2008).

    ADS  CAS  Article  Google Scholar 

  13. Gallagher, R. V. et al. Open Science principles for accelerating trait-based science across the Tree of Life. Nat Ecol Evol 4, 294–303 (2020).

    Article  Google Scholar 

  14. R Core Team. A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. (2020).

  15. Chamberlain, S. A. & Szöcs, E. taxize: taxonomic search and retrieval in R [version 2; peer review: 3 approved]. F1000Res. 2, (2013).

  16. Pebesma, E., Mailund, T. & Hiebert, J. Measurement Units in R. R J. 8, 486–494 (2016).

    Article  Google Scholar 

  17. Hiebert, J. udunits-2 bindings for R. (2016).

  18. Iwaniuk, A. N. & Nelson, J. E. Can endocranial volume be used as an estimate of brain size in birds? Canadian Journal of Zoology-Revue Canadienne De Zoologie 80, 16–23 (2002).

    Article  Google Scholar 

  19. Taylor, G. M., Nol, E. & Boire, D. Brain regions and encephalization in anurans: adaptation or stability? Brain Behav. Evol. 45, 96–109, https://doi.org/10.1159/000113543 (1995).

    CAS  Article  PubMed  Google Scholar 

  20. McLean, D. J. AnimalTraits (v1.0.7). Zenodo. https://doi.org/10.5281/zenodo.6468938 (2022).

  21. Christian, K. & Conley, K. Activity and Resting Metabolism of Varanid Lizards Compared With Typical Lizards. Aust. J. Zool. 42, 185–193, https://doi.org/10.1071/ZO9940185 (1994).

    Article  Google Scholar 

  22. Hadley, N. F., Ahearn, G. A. & Howarth, F. G. Water and metabolic relations of cave-adapted and epigean lycosid spiders in Hawaii. J. Arachnol., 215–222 (1981).

  23. Wang, L. C., Jones, D. L., MacArthur, R. A. & Fuller, W. A. Adaptation to cold: energy metabolism in an atypical lagomorph, the arctic hare (Lepus arcticus). Can. J. Zool. 51, 841–846, https://doi.org/10.1139/z73-125 (1973).

    CAS  Article  PubMed  Google Scholar 

  24. Nevo, E. & Shkolnik, A. Adaptive metabolic variation of chromosome forms in mole rats, Spalax. Experientia 30, 724–726, https://doi.org/10.1007/bf01924150 (1974).

    CAS  Article  PubMed  Google Scholar 

  25. Haim, A. Adaptive variations in heat production within Gerbils (genus Gerbillus) from different habitats. Oecologia 61, 49–52, https://doi.org/10.1007/bf00379087 (1984).

    ADS  CAS  Article  PubMed  Google Scholar 

  26. Kamel, S. & Gatten, R. E. J. Aerobic and Anaerobic Activity Metabolism of Limbless and Fossorial Reptiles. Physiol. Zool. 56, 419–429, https://doi.org/10.1086/physzool.56.3.30152607 (1983).

    Article  Google Scholar 

  27. Gatten, R. E. Jr. Aerobic metabolism in snapping turtles, Chelydra serpentina, after thermal acclimation. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 61, 325–337, https://doi.org/10.1016/0300-9629(78)90116-0 (1978).

    Article  Google Scholar 

  28. Coelho, J. R. & Moore, A. J. Allometry of resting metabolic rate in cockroaches. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 94, 587–590, https://doi.org/10.1016/0300-9629(89)90598-7 (1989).

    CAS  Article  Google Scholar 

  29. Lighton, J. & Garrigan, D. Ant breathing: testing regulation and mechanism hypotheses with hypoxia. J. Exp. Biol. 198, 1613–1620 (1995).

    CAS  Article  Google Scholar 

  30. Pettit, T. N., Ellis, H. I. & Whittow, G. C. Basal metabolic rate in tropical seabirds. The Auk 102, 172–174, https://doi.org/10.2307/4086838 (1985).

    Article  Google Scholar 

  31. Bozinovic, F. & Contreras, L. C. Basal rate of metabolism and temperature regulation of two desert herbivorous octodontid rodents: Octomys mimax and Tympanoctomys barrerae. Oecologia 84, 567–570, https://doi.org/10.1007/bf00328175 (1990).

    ADS  Article  PubMed  Google Scholar 

  32. Morrison, P. & Middleton, E. H. Body temperature and metabolism in the pigmy marmoset. Folia Primatol. 6, 70–82, https://doi.org/10.1159/000155068 (1967).

    CAS  Article  Google Scholar 

  33. Bartholomew, G. A. & Casey, T. M. Body temperature and oxygen consumption during rest and activity in relation to body size in some tropical beetles. J. Therm. Biol. 2, 173–176, https://doi.org/10.1016/0306-4565(77)90026-2 (1977).

    Article  Google Scholar 

  34. Cortés, A., Báez, C., Rosenmann, M. & Pino, C. Body temperature, activity cycle and metabolic rate in a small nocturnal Chilean lizard, Garthia gaudichaudi (Sauria: Gekkonidae). Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 109, 967–973, https://doi.org/10.1016/0300-9629(94)90245-3 (1994).

    Article  Google Scholar 

  35. Leitner, P. & Nelson, J. E. Body temperature, oxygen consumption and heart rate in the Australian false vampire bat, Macroderma gigas. Comp. Biochem. Physiol. 21, 65–74, https://doi.org/10.1016/0010-406X(67)90115-6 (1967).

    CAS  Article  PubMed  Google Scholar 

  36. Whittow, G. C., Gould, E. & Rand, D. Body temperature, oxygen consumption, and evaporative water loss in a primitive insectivore, the moon rat, Echinosorex gymnurus. J. Mammal. 58, 233–235, https://doi.org/10.2307/1379582 (1977).

    CAS  Article  PubMed  Google Scholar 

  37. Weathers, W. W., Koenig, W. D. & Stanback, M. T. Breeding energetics and thermal ecology of the acorn woodpecker in central coastal California. Condor, 341–359, https://doi.org/10.2307/1368232 (1990).

  38. Shelton, T. G. & Appel, A. G. Carbon dioxide release in Coptotermes formosanus Shiraki and Reticulitermes flavipes (Kollar): effects of caste, mass, and movement. J. Insect Physiol. 47, 213–224, https://doi.org/10.1016/S0022-1910(00)00111-6 (2001).

    CAS  Article  PubMed  Google Scholar 

  39. Bradley, T. J., Brethorst, L., Robinson, S. & Hetz, S. Changes in the Rate of CO2 Release following Feeding in the Insect Rhodnius prolixus. Physiol. Biochem. Zool. 76, 302–309, https://doi.org/10.1086/367953 (2003).

    Article  PubMed  Google Scholar 

  40. Herreid, C. F. & Full, R. J. Cockroaches on a treadmill: aerobic running. J. Insect Physiol. 30, 395–403, https://doi.org/10.1016/0022-1910(84)90097-0 (1984).

    Article  Google Scholar 

  41. Arends, A. & McNab, B. K. The comparative energetics of ‘caviomorph’ rodents. Comp. Biochem. Physiol. A: Mol. Integr. Physiol. 130, 105–122, https://doi.org/10.1016/S1095-6433(01)00371-3 (2001).

    CAS  Article  Google Scholar 

  42. McNab, B. K. The comparative energetics of rigid endothermy: the Arvicolidae. J. Zool. 227, 585–606, https://doi.org/10.1111/j.1469-7998.1992.tb04417.x (1992).

    Article  Google Scholar 

  43. Bozinovic, F. & Rosenmann, M. Comparative energetics of South American cricetid rodents. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 91, 195–202, https://doi.org/10.1016/0300-9629(88)91616-7 (1988).

    CAS  Article  Google Scholar 

  44. Haim, A. & Skinner, J. D. A comparative study of metabolic rates and thermoregulation of two African antelopes, the steenbok Raphicerus campestris and the blue duiker Cephalophus monticola. J. Therm. Biol. 16, 145–148, https://doi.org/10.1016/0306-4565(91)90036-2 (1991).

    Article  Google Scholar 

  45. Else, P. L. & Hulbert, A. J. Comparison of the “mammal machine” and the “reptile machine”: energy production. Am. J. Physiol. Regul. Integr. Comp. Physiol. 240, R3–R9, https://doi.org/10.1152/ajpregu.1981.240.1.R3 (1981).

    CAS  Article  Google Scholar 

  46. Duncan, F. D. & Crewe, R. M. A comparison of the energetics of foraging of three species of Leptogenys (Hymenoptera, Formicidae). Physiol. Entomol. 18, 372–378, https://doi.org/10.1111/j.1365-3032.1993.tb00610.x (1993).

    Article  Google Scholar 

  47. Kurta, A. & Ferkin, M. The correlation between demography and metabolic rate: a test using the beach vole (Microtus breweri) and the meadow vole (Microtus pennsylvanicus). Oecologia 87, 102–105, https://doi.org/10.1007/bf00323786 (1991).

    ADS  Article  PubMed  Google Scholar 

  48. Chown, S. L. & Holter, P. Discontinuous gas exchange cycles in Aphodius fossor (Scarabaeidae): a test of hypotheses concerning origins and mechanisms. J. Exp. Biol. 203, 397–403, https://doi.org/10.1242/jeb.203.2.397 (2000).

    CAS  Article  PubMed  Google Scholar 

  49. Duncan, F. D. & Byrne, M. J. Discontinuous gas exchange in dung beetles: patterns and ecological implications. Oecologia 122, 452–458, https://doi.org/10.1007/s004420050966 (2000).

    ADS  CAS  Article  PubMed  Google Scholar 

  50. Rezende, E. L., Silva-Durán, I., Novoa, F. F. & Rosenmann, M. Does thermal history affect metabolic plasticity?: a study in three Phyllotis species along an altitudinal gradient. J. Therm. Biol. 26, 103–108, https://doi.org/10.1016/S0306-4565(00)00029-2 (2001).

    Article  PubMed  Google Scholar 

  51. Chown, S. L., Scholtz, C. H., Klok, C. J., Joubert, F. J. & Coles, K. S. Ecophysiology, range contraction and survival of a geographically restricted African dung beetle (Coleoptera: Scarabaeidae). Funct. Ecol. 9, 30–39, https://doi.org/10.2307/2390087 (1995).

    Article  Google Scholar 

  52. Rübsamen, U., Hume, I. D. & Rübsamen, K. Effect of ambient temperature on autonomic thermoregulation and activity patterns in the rufous rat-kangaroo (Aepyprymnus rufescens: Marsupialia). J. Comp. Physiol. 153, 175–179, https://doi.org/10.1007/bf00689621 (1983).

    Article  Google Scholar 

  53. Lewis, L. C., Mutchmor, J. A. & Lynch, R. E. Effect of Perezia pyraustae on oxygen consumption by the European corn borer, Ostrinia nubilalis. J. Insect Physiol. 17, 2457–2468, https://doi.org/10.1016/0022-1910(71)90093-X (1971).

    Article  Google Scholar 

  54. Louw, G., Young, B. & Bligh, J. Effect of thyroxine and noradrenaline on thermoregulation, cardiac rate and oxygen consumption in the monitor lizard Varanus albigularis albigularis. J. Therm. Biol. 1, 189–193, https://doi.org/10.1016/0306-4565(76)90013-9 (1976).

    CAS  Article  Google Scholar 

  55. Full, R. J., Zuccarello, D. A. & Tullis, A. Effect of variation in form on the cost of terrestrial locomotion. J. Exp. Biol. 150, 233–246 (1990).

    CAS  Article  Google Scholar 

  56. Bennett, A. F., Dawson, W. R. & Bartholomew, G. A. Effects of activity and temperature on aerobic and anaerobic metabolism in the Galapagos marine iguana. J. Comp. Physiol. 100, 317–329, https://doi.org/10.1007/bf00691052 (1975).

    CAS  Article  Google Scholar 

  57. Thompson, G. G. & Withers, P. C. Effects of body mass and temperature on standard metabolic rates for two Australian varanid lizards (Varanus gouldii and V. panoptes). Copeia, 343–350, https://doi.org/10.2307/1446195 (1992).

  58. Hack, M. A. The effects of mass and age on standard metabolic rate in house crickets. Physiol. Entomol. 22, 325–331, https://doi.org/10.1111/j.1365-3032.1997.tb01176.x (1997).

    ADS  Article  Google Scholar 

  59. Gatten, R. E. Jr. Effects of temperature and activity on aerobic and anaerobic metabolism and heart rate in the turtles Pseudemys scripta and Terrapene ornata. Comp. Biochem. Physiol., A: Mol. Integr. Physiol, https://doi.org/10.1016/0300-9629(74)90606-9 (1974).

  60. Gleeson, T. T. The effects of training and captivity on the metabolic capacity of the lizard Sceloporus occidentalis. J. Comp. Physiol. 129, 123–128, https://doi.org/10.1007/bf00798176 (1979).

    CAS  Article  Google Scholar 

  61. Bartholomew, G. A. & Lighton, J. R. Endothermy and energy metabolism of a giant tropical fly, Pantophthalmus tabaninus thunberg. J. Comp. Physiol., B 156, 461–467, https://doi.org/10.1007/bf00691031 (1986).

    Article  Google Scholar 

  62. Bailey, W. J., Withers, P. C., Endersby, M. & Gaull, K. The energetic costs of calling in the bushcrisket Requena verticalis (Orthoptera: Tettigoniidae: Listroscelidinae). J. Exp. Biol. 178, 21–37 (1993).

    Article  Google Scholar 

  63. Kotiaho, J. S. et al. Energetic costs of size and sexual signalling in a wolf spider. Proc. R. Soc. B: Biol. Sci. 265, 2203–2209, https://doi.org/10.1098/rspb.1998.0560 (1998).

    Article  Google Scholar 

  64. Chaplin, S. B. The energetic significance of huddling behavior in common bushtits (Psaltriparus minimus). The Auk, 424-430 (1982).

  65. Seymour, R. S., Withers, P. C. & Weathers, W. W. Energetics of burrowing, running, and free-living in the Namib Desert golden mole (Eremitalpa namibensis). J. Zool. 244, 107–117 (1998).

    Article  Google Scholar 

  66. Herreid, C. F., Full, R. J. & Prawel, D. A. Energetics of Cockroach Locomotion. J. Exp. Biol. 94, 189–202 (1981).

    Article  Google Scholar 

  67. Bartholomew, G. A., Lighton, J. R. & Louw, G. N. Energetics of locomotion and patterns of respiration in tenebrionid beetles from the Namib Desert. J. Comp. Physiol., B 155, 155–162, https://doi.org/10.1007/bf00685208 (1985).

    Article  Google Scholar 

  68. Lighton, J. R. B. & Gillespie, R. G. The energetics of mimicry: the cost of pedestrian transport in a formicine ant and its mimic, a clubionid spider. Physiol. Entomol. 14, 173–177, https://doi.org/10.1111/j.1365-3032.1989.tb00949.x (1989).

    Article  Google Scholar 

  69. Marhold, S. & Nagel, A. The energetics of the common mole rat Cryptomys, a subterranean eusocial rodent from Zambia. J. Comp. Physiol., B 164, 636–645, https://doi.org/10.1007/bf00389805 (1995).

    CAS  Article  Google Scholar 

  70. Pauls, R. W. Energetics of the red squirrel: a laboratory study of the effects of temperature, seasonal acclimatization, use of the nest and exercise. J. Therm. Biol. 6, 79–86, https://doi.org/10.1016/0306-4565(81)90057-7 (1981).

    ADS  Article  Google Scholar 

  71. Brush, A. H. Energetics, temperature regulation and circulation in resting, active and defeathered California quail, Lophortyx californicus. Comp. Biochem. Physiol. 15, 399–421, https://doi.org/10.1016/0010-406X(65)90141-6 (1965).

    Article  Google Scholar 

  72. Bailey, C. G. & Riegert, P. W. Energy dynamics of Encoptolophus sordidus costalis (Scudder) (Orthoptera: Acrididae) in a grassland ecosystem. Can. J. Zool. 51, 91–100, https://doi.org/10.1139/z73-014 (1973).

    Article  Google Scholar 

  73. Prinzinger, R., Lübben, I. & Schuchmann, K.-L. Energy metabolism and body temperature in 13 sunbird species (Nectariniidae). Comp. Biochem. Physiol. A: Mol. Integr. Physiol. 92, 393–402, https://doi.org/10.1016/0300-9629(89)90581-1 (1989).

    Article  Google Scholar 

  74. Baudinette, R. V. Energy metabolism and evaporative water loss in the California ground squirrel. J. Comp. Physiol. 81, 57–72, https://doi.org/10.1007/bf00693550 (1972).

    Article  Google Scholar 

  75. May, M. L. Energy metabolism of dragonflies (Odonata: Anisoptera) at rest and during endothermic warm-up. J. Exp. Biol. 83, 79–94 (1979).

    Article  Google Scholar 

  76. Baudinette, R. V., Churchill, S. K., Christian, K. A., Nelson, J. E. & Hudson, P. J. Energy, water balance and the roost microenvironment in three Australian cave-dwelling bats (Microchiroptera). J. Comp. Physiol., B 170, 439–446, https://doi.org/10.1007/s003600000121 (2000).

    CAS  Article  Google Scholar 

  77. Withers, P. C. Energy, Water, and Solute Balance of the Ostrich Struthio camelus. Physiol. Zool. 56, 568–579, https://doi.org/10.1086/physzool.56.4.30155880 (1983).

    Article  Google Scholar 

  78. Hadley, N. F., Quinlan, M. C. & Kennedy, M. L. Evaporative Cooling in the Desert Cicada: Thermal Efficiency and Water/Metabolic Costs. J. Exp. Biol. 159, 269–283, https://doi.org/10.1242/jeb.159.1.269 (1991).

    Article  Google Scholar 

  79. Dunson, W. A. & Bramham, C. R. Evaporative Water Loss and Oxygen Consumption of Three Small Lizards from the Florida Keys: Sphaerodactylus cinereus, S. notatus, and Anolis sagrei. Physiol. Zool. 54, 253–259, https://doi.org/10.1086/physzool.54.2.30155827 (1981).

    Article  Google Scholar 

  80. Wunder, B. A. Evaporative water loss from birds: effects of artificial radiation. Comp. Biochem. Physiol. 63, 493–494, https://doi.org/10.1016/0300-9629(79)90180-4 (1979).

    Article  Google Scholar 

  81. Maclean, G. S. Factors influencing the composition of respiratory gases in mammal burrows. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 69, 373–380, https://doi.org/10.1016/0300-9629(81)92992-3 (1981).

    Article  Google Scholar 

  82. Campbell, K. L., McIntyre, I. W. & MacArthur, R. A. Fasting metabolism and thermoregulatory competence of the star-nosed mole, Condylura cristata (Talpidae: Condylurinae). Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 123, 293–298, https://doi.org/10.1016/S1095-6433(99)00065-3 (1999).

    CAS  Article  Google Scholar 

  83. Weathers, W. W., Paton, D. C. & Seymour, R. S. Field Metabolic Rate and Water Flux of Nectarivorous Honeyeaters. Aust. J. Zool. 44, 445–460, https://doi.org/10.1071/ZO9960445 (1996).

    Article  Google Scholar 

  84. Fewell, J. H., Harrison, J. F., Lighton, J. R. B. & Breed, M. D. Foraging energetics of the ant, Paraponera clavata. Oecologia 105, 419–427, https://doi.org/10.1007/bf00330003 (1996).

    ADS  Article  PubMed  Google Scholar 

  85. Greenstone, M. H. & Bennett, A. F. Foraging strategy and metabolic rate in spiders. Ecology 61, 1255–1259, https://doi.org/10.2307/1936843 (1980).

    Article  Google Scholar 

  86. Schmitz, A. Functional morphology of the respiratory organs in the cellar spider Pholcus phalangioides (Arachnida, Araneae, Pholcidae). J. Comp. Physiol., B 185, 637–646, https://doi.org/10.1007/s00360-015-0914-8 (2015).

    CAS  Article  Google Scholar 

  87. Marder, J. & Bernstein, R. Heat balance of the partridge Alectoris chukar exposed to moderate, high and extreme thermal stress. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 74, 149–154, https://doi.org/10.1016/0300-9629(83)90726-0 (1983).

    CAS  Article  Google Scholar 

  88. Lovegrove, B. G., Raman, J. & Perrin, M. R. Heterothermy in elephant shrews, Elephantulus spp. (Macroscelidea): daily torpor or hibernation? J. Comp. Physiol., B 171, 1–10, https://doi.org/10.1007/s003600000139 (2001).

    CAS  Article  Google Scholar 

  89. Zari, T. The influence of body mass and temperature on the standard metabolic rate of the herbivorous desert lizard, Uromastyx microlepis. J. Therm. Biol. 16, 129–133, https://doi.org/10.1016/0306-4565(91)90033-X (1991).

    Article  Google Scholar 

  90. Jensen, T. F. & Nielsen, M. G. The influence of body size and temperature on worker ant respiration. Nat. Jutl. 18, 21–25 (1975).

    Google Scholar 

  91. McNab, B. K. The Influence of Body Size on the Energetics and Distribution of Fossorial and Burrowing Mammals. Ecology 60, 1010–1021, https://doi.org/10.2307/1936869 (1979).

    Article  Google Scholar 

  92. Shillington, C. Inter-sexual differences in resting metabolic rates in the Texas tarantula, Aphonopelma anax. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 142, 439–445, https://doi.org/10.1016/j.cbpa.2005.09.010 (2005).

    CAS  Article  Google Scholar 

  93. Nespolo, R. F., Lardies, M. A. & Bozinovic, F. Intrapopulational variation in the standard metabolic rate of insects: repeatability, thermal dependence and sensitivity (Q10) of oxygen consumption in a cricket. J. Exp. Biol. 206, 4309–4315, https://doi.org/10.1242/jeb.00687 (2003).

    CAS  Article  PubMed  Google Scholar 

  94. Hailey, A. & Davies, P. M. C. Lifestyle, latitude and activity metabolism of natricine snakes. J. Zool. 209, 461–476, https://doi.org/10.1111/j.1469-7998.1986.tb03604.x (1986).

    Article  Google Scholar 

  95. Richter, T. A., Webb, P. I. & Skinner, J. D. Limits to the distribution of the southern African ice rat (Otomys sloggetti): thermal physiology or competitive exclusion? Funct. Ecol. 11, 240–246, https://doi.org/10.1046/j.1365-2435.1997.00078.x (1997).

    Article  Google Scholar 

  96. Putnam, R. W. & Murphy, R. W. Low metabolic rate in a nocturnal desert lizard, Anarbylus switaki Murphy (Sauria: Gekkonidae). Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 71, 119–123 (1982).

    Article  Google Scholar 

  97. Lighton, J. R. B. & Fielden, L. J. Mass Scaling of Standard Metabolism in Ticks: A Valid Case of Low Metabolic Rates in Sit-and-Wait Strategists. Physiol. Zool. 68, 43–62, https://doi.org/10.1086/physzool.68.1.30163917 (1995).

    Article  Google Scholar 

  98. Jones, D. L. & Wang, L. C.-H. Metabolic and cardiovascular adaptations in the western chipmunks, genus Eutamias. J. Comp. Physiol. 105, 219–231, https://doi.org/10.1007/bf00691124 (1976).

    Article  Google Scholar 

  99. Casey, T. M., Withers, P. C. & Casey, K. K. Metabolic and respiratory responses of arctic mammals to ambient temperature during the summer. Comp. Biochem. Physiol. A: Mol. Integr. Physiol. 64, 331–341, https://doi.org/10.1016/0300-9629(79)90452-3 (1979).

    Article  Google Scholar 

  100. Grant, G. S. & Whittow, G. C. Metabolic cost of incubation in the Laysan albatross and Bonin petrel. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 74, 77–82, https://doi.org/10.1016/0300-9629(83)90715-6 (1983).

    CAS  Article  Google Scholar 

  101. Bennett, A. F. & Gleeson, T. T. Metabolic expenditure and the cost of foraging in the lizard Cnemidophorus murinus. Copeia, 573-577, https://doi.org/10.2307/1443864 (1979).

  102. Withers, P. C., Thompson, G. G. & Seymour, R. S. Metabolic physiology of the north-western marsupial mole. Notoryctes caurinus (Marsupialia: Notoryctidae). Aust. J. Zool. 48, 241–258, https://doi.org/10.1071/ZO99073 (2000).

    Article  Google Scholar 

  103. Thurling, D. J. Metabolic rate and life stage of the mites Tetranychus cinnabarinus boisd. (Prostigmata) and Phytoseiulus persimilis A-H. (Mesostigmata). Oecologia 46, 391–396, https://doi.org/10.1007/BF00346269 (1980).

    ADS  CAS  Article  PubMed  Google Scholar 

  104. Vleck, C. M. & Vleck, D. Metabolic rate in five tropical bird species. Condor 81, 89–91, https://doi.org/10.2307/1367864 (1979).

    Article  Google Scholar 

  105. Terblanche, J. S., Jaco Klok, C., Marais, E. & Chown, S. L. Metabolic rate in the whip-spider, Damon annulatipes (Arachnida: Amblypygi). J. Insect Physiol. 50, 637-645, j.jinsphys.2004.04.010 (2004).

  106. Boyce, A. J., Mouton, J. C., Lloyd, P., Wolf, B. O. & Martin, T. E. Metabolic rate is negatively linked to adult survival but does not explain latitudinal differences in songbirds. Ecol. Lett. 23, 642–652, https://doi.org/10.1111/ele.13464 (2020).

    Article  PubMed  Google Scholar 

  107. Worthen, G. L. & Kilgore, D. L. Metabolic rate of pine marten in relation to air temperature. J. Mammal. 62, 624–628, https://doi.org/10.2307/1380410 (1981).

    Article  Google Scholar 

  108. Hails, C. J. The metabolic rate of tropical birds. Condor, 61–65, https://doi.org/10.2307/1367889 (1983).

  109. Terblanche, J. S., Klok, C. J. & Chown, S. L. Metabolic rate variation in Glossina pallidipes (Diptera: Glossinidae): gender, ageing and repeatability. J. Insect Physiol. 50, 419–428, https://doi.org/10.1016/j.jinsphys.2004.02.009 (2004).

    CAS  Article  PubMed  Google Scholar 

  110. Schmitz, A. Metabolic rates during rest and activity in differently tracheated spiders (Arachnida, Araneae): Pardosa lugubris (Lycosidae) and Marpissa muscosa (Salticidae). J. Comp. Physiol., B 174, 519–526, https://doi.org/10.1007/s00360-004-0440-6 (2004).

    CAS  Article  Google Scholar 

  111. Anderson, J. F. Metabolic rates of resting salticid and thomisid spiders. J. Arachnol. 129–134 (1996).

  112. Adams, N. J. & Brown, C. R. Metabolic rates of sub-Antarctic Procellariiformes: a comparative study. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 77, 169–173, https://doi.org/10.1016/0300-9629(84)90030-6 (1984).

    Article  Google Scholar 

  113. Morrison, P. & Ryser, F. A. Metabolism and body temperature in a small hibernator, the meadow jumping mouse, Zapus hudsonius. J. Cell. Compar. Physl. 60, 169–180, https://doi.org/10.1002/jcp.1030600206 (1962).

    CAS  Article  Google Scholar 

  114. Bieńkowski, P. & Marszałek, U. Metabolism and energy budget in the snow vole. Acta Theriol. 19, 55–67 (1974).

    Article  Google Scholar 

  115. Lardies, M. A., Catalán, T. P. & Bozinovic, F. Metabolism and life-history correlates in a lowland and highland population of a terrestrial isopod. Can. J. Zool. 82, 677–687, https://doi.org/10.1139/z04-033 (2004).

    Article  Google Scholar 

  116. Król, E. Metabolism and thermoregulation in the eastern hedgehog Erinaceus concolor. J. Comp. Physiol., B 164, 503–507, https://doi.org/10.1007/bf00714589 (1994).

    Article  Google Scholar 

  117. Hennemann, W. W., Thompson, S. D. & Konecny, M. J. Metabolism of Crab-Eating Foxes, Cerdocyon thous: Ecological Influences on the Energetics of Canids. Physiol. Zool. 56, 319–324, https://doi.org/10.1086/physzool.56.3.30152596 (1983).

    Article  Google Scholar 

  118. Lovegrove, B. G. The metabolism of social subterranean rodents: adaptation to aridity. Oecologia 69, 551–555, https://doi.org/10.1007/bf00410361 (1986).

    ADS  CAS  Article  PubMed  Google Scholar 

  119. Prinzinger, R. & Hänssler, I. Metabolism-weight relationship in some small nonpasserine birds. Experientia 36, 1299–1300, https://doi.org/10.1007/bf01969600 (1980).

    Article  Google Scholar 

  120. Hill, R. W. Metabolism, thermal conductance, and body temperature in one of the largest species of Peromyscus, P. pirrensis. J. Therm. Biol. 1, 109–112, https://doi.org/10.1016/0306-4565(76)90029-2 (1976).

    Article  Google Scholar 

  121. Saarela, S. & Hissa, R. Metabolism, thermogenesis and daily rhythm of body temperature in the wood lemming, Myopus schisticolor. J. Comp. Physiol., B 163, 546–555, https://doi.org/10.1007/bf00302113 (1993).

    CAS  Article  Google Scholar 

  122. MacMillen, R. E. Nonconformance of standard metabolic rate with body mass in Hawaiian Honeycreepers. Oecologia 49, 340–343, https://doi.org/10.1007/bf00347595 (1981).

    ADS  CAS  Article  PubMed  Google Scholar 

  123. Krog, H. & Monson, M. Notes on the metabolism of a mountain goat. Am. J. Physiol. 178, 515–516 (1954).

    CAS  Article  Google Scholar 

  124. Du Toit, J. T., Jarvis, J. U. M. & Louw, G. N. Nutrition and burrowing energetics of the Cape mole-rat Georychus capensis. Oecologia 66, 81–87, https://doi.org/10.1007/bf00378556 (1985).

    ADS  Article  PubMed  Google Scholar 

  125. Farrell, D. J. & Wood, A. J. The nutrition of the female mink (Mustela vison). I. The metabolic rate of the mink. Can. J. Zool. 46, 41–45, https://doi.org/10.1139/z68-008 (1968).

    Article  Google Scholar 

  126. Hennemann, W. W. & Konecny, M. J. Oxygen consumption in large spotted genets, Genetta tigrina. J. Mammal. 61, 747–750, https://doi.org/10.2307/1380332 (1980).

    Article  Google Scholar 

  127. May, M. L., Pearson, D. L. & Casey, T. M. Oxygen consumption of active and inactive adult tiger beetles. Physiol. Entomol. 11, 171–179, https://doi.org/10.1111/j.1365-3032.1986.tb00403.x (1986).

    Article  Google Scholar 

  128. Bartholomew, G. A. & Casey, T. M. Oxygen Consumption of Moths During Rest, Pre-Flight Warm-Up, and Flight In Relation to Body Size and Wing Morphology. J. Exp. Biol. 76, 11–25 (1978).

    Article  Google Scholar 

  129. MacMillen, R. E., Whittow, G. C., Christopher, E. A. & Ebisu, R. J. Oxygen consumption, evaporative water loss, and body temperature in the sooty tern. The Auk, 72–79 (1977).

  130. Francis, C. & Brooks, G. R. Oxygen consumption, rate of heart beat and ventilatory rate in parietalectomized lizards, Sceloporus occidentalis. Comp. Biochem. Physiol. 35, 463–469, https://doi.org/10.1016/0010-406X(70)90609-2 (1970).

    Article  Google Scholar 

  131. Tucker, V. A. Oxygen consumption, thermal conductance, and torpor in the California pocket mouse Perognathus californicus. J. Cell. Physiol. 65, 393–403, https://doi.org/10.1002/jcp.1030650313 (1965).

    CAS  Article  PubMed  Google Scholar 

  132. McNab, B. K. Physiological convergence amongst ant-eating and termite-eating mammals. J. Zool. 203, 485–510, https://doi.org/10.1111/j.1469-7998.1984.tb02345.x (1984).

    Article  Google Scholar 

  133. Genoud, M., Bonaccorso, F. J. & Anends, A. Rate of metabolism and temperature regulation in two small tropical insectivorous bats (Peropteryx macrotis and Natalus tumidirostris). Comp. Biochem. Physiol. A: Mol. Integr. Physiol. 97, 229–234, https://doi.org/10.1016/0300-9629(90)90177-T (1990).

    Article  Google Scholar 

  134. Genoud, M. & Ruedi, M. Rate of metabolism, temperature regulations, and evaporative water loss in the lesser gymnure Hylomys suillus (Insectivora, Mammalia). J. Zool. 240, 309–316, https://doi.org/10.1111/j.1469-7998.1996.tb05287.x (1996).

    Article  Google Scholar 

  135. Ricklefs, R. E. & Matthew, K. K. Rates of oxygen consumption in four species of seabird at Palmer Station, Antarctic peninsula. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 74, 885–888, https://doi.org/10.1016/0300-9629(83)90363-8 (1983).

    CAS  Article  Google Scholar 

  136. Lasiewski, R. C. & Dawson, W. R. A Re-Examination of the Relation between Standard Metabolic Rate and Body Weight in Birds. Condor 69, 13–23, https://doi.org/10.2307/1366368 (1967).

    Article  Google Scholar 

  137. Goldstein, R. B. Relation of metabolism to ambient temperature in the Verdin. Condor 76, 116–119, https://doi.org/10.2307/1365995 (1974).

    Article  Google Scholar 

  138. Mispagel, M. E. Relation of oxygen consumption to size and temperature in desert arthropods. Ecol. Entomol. 6, 423–431, https://doi.org/10.1111/j.1365-2311.1981.tb00634.x (1981).

    Article  Google Scholar 

  139. Bryant, D. M., Hails, C. J. & Tatner, P. Reproductive energetics of two tropical bird species. The Auk, 25–37 (1984).

  140. Holter, P. Resource utilization and local coexistence in a guild of scarabaeid dung beetles (Aphodius spp.). Oikos 39, 213–227, https://doi.org/10.2307/3544488 (1982).

    Article  Google Scholar 

  141. Goldstein, D. L. & Nagy, K. A. Resource Utilization by Desert Quail: Time and Energy, Food and Water. Ecology 66, 378–387, https://doi.org/10.2307/1940387 (1985).

    Article  Google Scholar 

  142. Louw, G. N., Nicolson, S. W. & Seely, M. K. Respiration beneath desert sand: carbon dioxide diffusion and respiratory patterns in a tenebrionid beetle. J. Exp. Biol. 120, 443–446 (1986).

    Article  Google Scholar 

  143. Anderson, J. F. & Prestwich, K. N. Respiratory Gas Exchange in Spiders. Physiol. Zool. 55, 72–90, https://doi.org/10.1086/physzool.55.1.30158445 (1982).

    Article  Google Scholar 

  144. Meyer, E. & Phillipson, J. Respiratory metabolism of the isopod Trichoniscus pusillus provisorius. Oikos, 69–74, https://doi.org/10.2307/3544200 (1983).

  145. Duncan, F. D. & Dickman, C. R. Respiratory patterns and metabolism in tenebrionid and carabid beetles from the Simpson Desert, Australia. Oecologia 129, 509–517, https://doi.org/10.1007/s004420100772 (2001).

    ADS  Article  PubMed  Google Scholar 

  146. Nielsen, M. G. Respiratory rates of ants from different climatic areas. J. Insect Physiol. 32, 125–131, https://doi.org/10.1016/0022-1910(86)90131-9 (1986).

    Article  Google Scholar 

  147. Calder, W. A. III & Dawson, T. J. Resting metabolic rates of ratite birds: the kiwis and the emu. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 60, 479–481 (1978).

    Article  Google Scholar 

  148. Kawamoto, T. H., Machado, Fd. A., Kaneto, G. E. & Japyassu, H. F. Resting metabolic rates of two orbweb spiders: A first approach to evolutionary success of ecribellate spiders. J. Insect Physiol. 57, 427–432, https://doi.org/10.1016/j.jinsphys.2011.01.001 (2011).

    CAS  Article  PubMed  Google Scholar 

  149. Lehmann, F. O., Dickinson, M. H. & Staunton, J. The scaling of carbon dioxide release and respiratory water loss in flying fruit flies (Drosophila spp.). J. Exp. Biol. 203, 1613–1624 (2000).

    CAS  Article  Google Scholar 

  150. Chown, S. L. et al. Scaling of insect metabolic rate is inconsistent with the nutrient supply network model. Funct. Ecol. 21, 282–290, https://doi.org/10.1111/j.1365-2435.2007.01245.x (2007).

    Article  Google Scholar 

  151. Bartholomew, G. A. & Lighton, J. R. B. Short Communication: Ventilation and Oxygen Consumption During Rest and Locomotion in a Tropical Cockroach, Blaberus Giganteus. J. Exp. Biol. 118, 449–454 (1985).

    Article  Google Scholar 

  152. Stahel, C. D., Megirian, D. & Nicol, S. C. Sleep and metabolic rate in the little penguin, Eudyptula minor. J. Comp. Physiol., B 154, 487–494, https://doi.org/10.1007/bf02515153 (1984).

    Article  Google Scholar 

  153. Lighton, J. R. Slow Discontinuous Ventilation in the Namib Dune-sea Ant Camponotus Detritus (Hymenoptera, Formicidae). J. Exp. Biol. 151, 71–82 (1990).

    Article  Google Scholar 

  154. Bech, C., Chappell, M. A., Astheimer, L. B., Londoño, G. A. & Buttemer, W. A. A ‘slow pace of life’ in Australian old-endemic passerine birds is not accompanied by low basal metabolic rates. J. Comp. Physiol., B 186, 503–512, https://doi.org/10.1007/s00360-016-0964-6 (2016).

    CAS  Article  Google Scholar 

  155. Young, S. R. & Block, W. Some factors affecting metabolic rate in an Antarctic mite. Oikos, 178–185, https://doi.org/10.2307/3544180 (1980).

  156. Wang, L. C.-H. & Hudson, J. W. Some physiological aspects of temperature regulation in the normothermic and torpid hispid pocket mouse, Perognathus hispidus. Comp. Biochem. Physiol. 32, 275–293, https://doi.org/10.1016/0010-406X(70)90941-2 (1970).

    CAS  Article  PubMed  Google Scholar 

  157. Bedford, G. S. & Christian, K. A. Standard metabolic rate and preferred body temperatures in some Australian pythons. Aust. J. Zool. 46, 317–328, https://doi.org/10.1071/ZO98019 (1999).

    Article  Google Scholar 

  158. Vogt, J. T. & Appel, A. G. Standard metabolic rate of the fire ant, Solenopsis invicta Buren: effects of temperature, mass, and caste. J. Insect Physiol. 45, 655–666, https://doi.org/10.1016/S0022-1910(99)00036-0 (1999).

    CAS  Article  PubMed  Google Scholar 

  159. Thompson, G., Heger, N., Heger, T. & Withers, P. Standard metabolic rate of the largest Australian lizard, Varanus giganteus. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 111, 603–608, https://doi.org/10.1016/0300-9629(95)00055-C (1995).

    Article  Google Scholar 

  160. Vitali, S. D., Withers, P. C. & Richardson, K. C. Standard metabolic rates of three nectarivorous meliphagid passerine birds. Aust. J. Zool. 47, 385–391, https://doi.org/10.1071/ZO99023 (1999).

    Article  Google Scholar 

  161. Dawson, T. J., Grant, T. R. & Fanning, D. Standard Metabolism of Monotremes and the Evolution of Homeothermy. Aust. J. Zool. 27, 511–515, https://doi.org/10.1071/ZO9790511 (1979).

    Article  Google Scholar 

  162. Al-Sadoon, M. K. & Abdo, N. M. Temperature effects on oxygen consumption of two nocturnal geckos, Ptyodactylus hasselquistii (Donndorff) and Bunopus tuberculatus (Blanford) (Reptilia: Gekkonidae) in Saudi Arabia. J. Comp. Physiol., B 159, 1–4, https://doi.org/10.1007/bf00692676 (1989).

    ADS  Article  Google Scholar 

  163. Roxburgh, L. & Perrin, M. R. Temperature regulation and activity pattern of the round-eared elephant shrew Macroscelides proboscideus. J. Therm. Biol. 19, 13–20, https://doi.org/10.1016/0306-4565(94)90004-3 (1994).

    Article  Google Scholar 

  164. Wang, L. C.-H. & Hudson, J. W. Temperature regulation in normothermic and hibernating eastern chipmunk, Tamias striatus. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 38, 59–90, https://doi.org/10.1016/0300-9629(71)90098-3 (1971).

    CAS  Article  Google Scholar 

  165. Rfinking, L. N., Kilgore, D. L. Jr, Fairbanks, E. S. & Hamilton, J. D. Temperature regulation in normothermic black-tailed prairie dogs, Cynomys ludovicianus. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 57, 161–165, https://doi.org/10.1016/0300-9629(77)90368-1 (1977).

    Article  Google Scholar 

  166. Chew, R. M., Lindberg, R. G. & Hayden, P. Temperature regulation in the little pocket mouse, Perognathus longimembris. Comp. Biochem. Physiol. 21, 487–505, https://doi.org/10.1016/0010-406X(67)90447-1 (1967).

    CAS  Article  PubMed  Google Scholar 

  167. Ebisu, R. J. & Whittow, G. C. Temperature regulation in the small Indian mongoose (Herpestes auropunctatus). Comp. Biochem. Physiol. A: Mol. Integr. Physiol. 54, 309–313, https://doi.org/10.1016/S0300-9629(76)80117-X (1976).

    CAS  Article  Google Scholar 

  168. Whittow, G. C., Scammell, C. A., Leong, M. & Rand, D. Temperature regulation in the smallest ungulate, the lesser mouse deer (Tragulus javanicus). Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 56, 23–26, https://doi.org/10.1016/0300-9629(77)90436-4 (1977).

    CAS  Article  Google Scholar 

  169. Fusari, M. H. Temperature responses of standard, aerobic metabolism by the California legless lizard, Anniella pulchra. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 77, 97–101, https://doi.org/10.1016/0300-9629(84)90018-5 (1984).

    CAS  Article  Google Scholar 

  170. Dawson, T. J. & Fanning, F. D. Thermal and energetic problems of semiaquatic mammals: a study of the Australian water rat, including comparisons with the platypus. Physiol. Zool. 54, 285–296 (1981).

    Article  Google Scholar 

  171. Campbell, K. L. & Hochachka, P. W. Thermal biology and metabolism of the American shrew-mole, Neurotrichus gibbsii. J. Mammal. 81, 578-585, 10.1644/1545-1542(2000)081<0578:TBAMOT>2.0.CO;2 (2000).

  172. Hosken, D. J. Thermal Biology and Metabolism of the Greater Long-eared Bat. Nyctophilus major (Chiroptera:Vespertilionidae). Aust. J. Zool. 45, 145–156, https://doi.org/10.1071/ZO96043 (1997).

    Article  Google Scholar 

  173. Duxbury, K. J. & Perrin, M. Thermal biology and water turnover rate in the Cape gerbil, Tatera afra (Gerbillidae). J. Therm. Biol. 17, 199–208, https://doi.org/10.1016/0306-4565(92)90056-L (1992).

    Article  Google Scholar 

  174. Downs, C. T. & Perrin, M. R. The thermal biology of the white-tailed rat Mystromys albicaudatus, a cricetine relic in southern temperate African grassland. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 110, 65–69, https://doi.org/10.1016/0300-9629(94)00147-L (1995).

    CAS  Article  Google Scholar 

  175. Downs, C. T. & Perrin, M. R. The thermal biology of three southern African elephant-shrews. J. Therm. Biol. 20, 445–450, https://doi.org/10.1016/0306-4565(95)00003-F (1995).

    Article  Google Scholar 

  176. Maloiy, G. M. O., Kamau, J. M. Z., Shkolnik, A., Meir, M. & Arieli, R. Thermoregulation and metabolism in a small desert carnivore: the Fennec fox (Fennecus zerda)(Mammalia). J. Zool. 198, 279–291, https://doi.org/10.1111/j.1469-7998.1982.tb02076.x (1982).

    Article  Google Scholar 

  177. Maskrey, M. & Hoppe, P. P. Thermoregulation and oxygen consumption in Kirk’s dik-dik (Madoqua kirkii) at ambient temperatures of 10–45 °C. Comp. Biochem. Physiol. A: Mol. Integr. Physiol. 62, 827–830, https://doi.org/10.1016/0300-9629(79)90010-0 (1979).

    Article  Google Scholar 

  178. Kamau, J. M., Johansen, K. & Maloiy, G. Thermoregulation and standard metabolism of the slender mongoose (Herpestes sanguineus). Physiol. Zool. 52, 594–602 (1979).

    Article  Google Scholar 

  179. Knight, M. H. Thermoregulation in the largest African cricetid, the giant rat Cricetomys gambianus. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 89, 705–708, https://doi.org/10.1016/0300-9629(88)90856-0 (1988).

    CAS  Article  Google Scholar 

  180. Bennett, N. C., Aguilar, G. H., Jarvis, J. U. M. & Faulkes, C. G. Thermoregulation in three species of Afrotropical subterranean mole-rats (Rodentia: Bathyergidae) from Zambia and Angola and scaling within the genus Cryptomys. Oecologia 97, 222–227, https://doi.org/10.1007/bf00323153 (1994).

    ADS  CAS  Article  PubMed  Google Scholar 

  181. Casey, T. M. & Casey, K. K. Thermoregulation of Arctic Weasels. Physiol. Zool. 52, 153–164, https://doi.org/10.1086/physzool.52.2.30152560 (1979).

    Article  Google Scholar 

  182. Layne, J. N. & Dolan, P. G. Thermoregulation, metabolism, and water economy in the golden mouse (Ochrotomys nuttalli). Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 52, 153–163, https://doi.org/10.1016/S0300-9629(75)80146-0 (1975).

    CAS  Article  Google Scholar 

  183. Roberts, J. R. & Baudinette, R. V. Thermoregulation, Oxygen Consumption and Water Turnover in Stubble Quail, Coturnix pectoralis, and King Quail, Coturnix chinensis. Aust. J. Zool. 34, 25–33, https://doi.org/10.1071/ZO9860025 (1986).

    Article  Google Scholar 

  184. du Plessis, A., Erasmus, T. & Kerley, G. I. Thermoregulatory patterns of two sympatric rodents: Otomys unisulcatus and Parotomys brantsii. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 94, 215–220, https://doi.org/10.1016/0300-9629(89)90538-0 (1989).

    Article  Google Scholar 

  185. Bradley, W. & Yousef, M. Thermoregulatory responses in the plains pocket gopher, Geomys bursarius. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 52, 35–38, https://doi.org/10.1016/S0300-9629(75)80122-8 (1975).

    CAS  Article  Google Scholar 

  186. Drent, R. H. & Stonehouse, B. Thermoregulatory responses of the Peruvian penguin, Spheniscus humboldti. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 40, 689–710, https://doi.org/10.1016/0300-9629(71)90254-4 (1971).

    CAS  Article  Google Scholar 

  187. El-Nouty, F. D., Yousef, M. K., Magdub, A. B. & Johnson, H. D. Thyroid hormones and metabolic rate in burros, Equus asinus, and llamas, Lama glama: effects of environmental temperature. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 60, 235–237, https://doi.org/10.1016/0300-9629(78)90238-4 (1978).

    Article  Google Scholar 

  188. Krüger, K., Prinzinger, R. & Schuchmann, K.-L. Torpor and metabolism in hummingbirds. Comp. Biochem. Physiol. A: Mol. Integr. Physiol. 73, 679–689 (1982).

    Google Scholar 

  189. Bartholomew, G. A. & Barnhart, M. C. Tracheal Gases, Respiratory Gas Exchange, Body Temperature and Flight in Some Tropical Cicadas. J. Exp. Biol. 111, 131–144 (1984).

    Article  Google Scholar 

  190. Zachariassen, K. E., Andersen, J., Maloiy, G. M. & Kamau, J. M. Transpiratory water loss and metabolism of beetles from arid areas in East Africa. Comp. Biochem. Physiol., A: Mol. Integr. Physiol. 86, 403–408, https://doi.org/10.1016/0300-9629(87)90515-9 (1987).

    Article  Google Scholar 

  191. Bucher, T. L. Ventilation and oxygen consumption in Amazona viridigenalis. J. Comp. Physiol., B 155, 269–276, https://doi.org/10.1007/bf00687467 (1985).

    ADS  Article  Google Scholar 

  192. Bickler, P. E. & Anderson, R. A. Ventilation, Gas Exchange, and Aerobic Scope in a Small Monitor Lizard, Varanus gilleni. Physiol. Zool. 59, 76–83, https://doi.org/10.1086/physzool.59.1.30156093 (1986).

    Article  Google Scholar 

  193. Seid, M. A., Castillo, A. & Wcislo, W. T. The allometry of brain miniaturization in ants. Brain Behav. Evol. 77, 5–13, https://doi.org/10.1159/000322530 (2011).

    Article  PubMed  Google Scholar 

  194. Quesada, R. et al. The allometry of CNS size and consequences of miniaturization in orb-weaving and cleptoparasitic spiders. Arthropod Struct. Dev. 40, 521–529, https://doi.org/10.1016/j.asd.2011.07.002 (2011).

    Article  PubMed  Google Scholar 

  195. Mares, S., Ash, L. & Gronenberg, W. Brain allometry in bumblebee and honey bee workers. Brain Behav. Evol. 66, 50–61, https://doi.org/10.1159/000085047 (2005).

    Article  PubMed  Google Scholar 

  196. Mlikovsky, J. Brain size and forearmen magnum area in crows and allies (Aves: Corvidae). Acta Soc. Zool. Bohem. 67, 203–211 (2003).

    Google Scholar 

  197. Mlikovsky, J. Brain size in birds: 4. Passeriformes. Acta Soc. Zool. Bohem. 54, 27–37 (1990).

    Google Scholar 

  198. Bronson, R. T. Brain weight-body weight relationships in 12 species of nonhuman primates. Am. J. Phys. Anthropol. 56, 77–81, https://doi.org/10.1002/ajpa.1330560109 (1981).

    Article  Google Scholar 

  199. Guay, P., Weston, M., Symonds, M. & Glover, H. Brains and bravery: Little evidence of a relationship between brain size and flightiness in shorebirds. Austral Ecol. 38, 516–522, https://doi.org/10.1111/j.1442-9993.2012.02441.x (2013).

    Article  Google Scholar 

  200. Boddy, A. M. et al. Comparative analysis of encephalization in mammals reveals relaxed constraints on anthropoid primate and cetacean brain scaling. J. Evol. Biol. 25, 981–994, https://doi.org/10.1111/j.1420-9101.2012.02491.x (2012).

    CAS  Article  PubMed  Google Scholar 

  201. Stankowich, T. & Romero, A. N. The correlated evolution of antipredator defences and brain size in mammals. Proc. R. Soc. B: Biol. Sci. 284, https://doi.org/10.1098/rspb.2016.1857 (2017).

  202. Sheehan, Z. B. V., Kamhi, J. F., Seid, M. A. & Narendra, A. Differential investment in brain regions for a diurnal and nocturnal lifestyle in Australian Myrmecia ants. J. Comp. Neurol. 0, https://doi.org/10.1002/cne.24617.

  203. Bauchot, R. & Stephan, H. Données nouvelles sur l’encéphalisation des insectivores et des prosimiens. Mammalia 30, 160–196, https://doi.org/10.1515/mamm.1966.30.1.160 (1966).

    Article  Google Scholar 

  204. Rosenzweig, M. & Bennett, E. L. Effects of differential environments on brain weights and enzyme activities in gerbils, rats, and mice. Dev. Psychobiol. 2, 87–95, https://doi.org/10.1002/dev.420020208 (1969).

    CAS  Article  PubMed  Google Scholar 

  205. Pirlot, P. & Stephan, H. Encephalization in Chiroptera. Can. J. Zool. 48, 433–444, https://doi.org/10.1139/z70-075 (1970).

    Article  Google Scholar 

  206. Ashwell, K. W. S. Encephalization of Australian and New Guinean marsupials. Brain Behav. Evol. 71, 181–199, https://doi.org/10.1159/000114406 (2008).

    CAS  Article  PubMed  Google Scholar 

  207. Hoops, D. et al. Evidence for concerted and mosaic brain evolution in dragon lizards. Brain Behav. Evol. 90, 211–223, https://doi.org/10.1159/000478738 (2017).

    Article  PubMed  Google Scholar 

  208. Pasquet, A., Toscani, C. & Anotaux, M. Influence of aging on brain and web characteristics of an orb web spider. J. Ethol. 36, 85–91, https://doi.org/10.1007/s10164-017-0530-z (2018).

    Article  PubMed  Google Scholar 

  209. Warnke, P. Mitteilung neuer Gehirn-und Körpergewichtsbestimmungen bei Saugern. J. Psychol. Neurol. 13, 355–403 (1908).

    Google Scholar 

  210. Naccarati, S. On the relation between the weight of the internal secretory glands and the body weight and brain weight. Anat. Rec. 24, 254–260, https://doi.org/10.1002/ar.1090240408 (1922).

    Article  Google Scholar 

  211. Crile, G. & Quiring, D. P. A record of the body weight and certain organ and gland weights of 3690 animals. Ohio J. Sci. (1940).

  212. Franklin, D. C., Garnett, S. T., Luck, G. W., Gutierrez-Ibanez, C. & Iwaniuk, A. N. Relative brain size in Australian birds. Emu 114, 160–170, https://doi.org/10.1071/MU13034 (2014).

    Article  Google Scholar 

  213. Hrdlička, A. Weight of the brain and of the internal organs in American monkeys. With data on brain weight in other apes. Am. J. Phys. Anthropol. 8, 201–211, https://doi.org/10.1002/ajpa.1330080207 (1925).

    Article  Google Scholar 

  214. Stöckl, A. L., Ribi, W. A. & Warrant, E. J. Adaptations for nocturnal and diurnal vision in the hawkmoth lamina. J. Comp. Neurol. 524, 160–175, https://doi.org/10.1002/cne.23832 (2016).

    Article  PubMed  Google Scholar 

  215. Napiorkowska, T. & Kobak, J. The allometry of the central nervous system during the postembryonic development of the spider Eratigena atrica. Arthropod Struct. Dev. 46, 805–814, https://doi.org/10.1016/j.asd.2017.08.005 (2017).

    Article  PubMed  Google Scholar 

  216. El Jundi, B., Huetteroth, W., Kurylas, A. E. & Schachtner, J. Anisometric brain dimorphism revisited: Implementation of a volumetric 3D standard brain in Manduca sexta. J. Comp. Neurol. 517, 210–225, https://doi.org/10.1002/cne.22150 (2009).

    Article  PubMed  Google Scholar 

  217. Krieger, J., Sandeman, R. E., Sandeman, D. C., Hansson, B. S. & Harzsch, S. Brain architecture of the largest living land arthropod, the Giant Robber Crab Birgus latro (Crustacea, Anomura, Coenobitidae): evidence for a prominent central olfactory pathway? Front. Zool. 7, 25, https://doi.org/10.1186/1742-9994-7-25 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  218. Powell, B. J. & Leal, M. Brain Organization and Habitat Complexity in Anolis Lizards. Brain Behav. Evol. 84, 8–18, https://doi.org/10.1159/000362197 (2014).

    Article  PubMed  Google Scholar 

  219. Platel, R. in Biology of the Reptilia 10 (eds Gans, C. G., Northcutt, R. G & Ulinski, P. S.) 147–171 (Academic Press, 1979).

  220. Van Der Woude, E., Smid, H. M., Chittka, L. & Huigens, M. E. Breaking Haller’s rule: brain-body size isometry in a minute parasitic wasp. Brain Behav. Evol. 81, 86–92, https://doi.org/10.1159/000345945 (2013).

    Article  PubMed  Google Scholar 

  221. Guay, P.-J. & Iwaniuk, A. N. Captive breeding reduces brain volume in waterfowl (Anseriformes). Condor 110, 276–284, https://doi.org/10.1525/cond.2008.8424 (2008).

    Article  Google Scholar 

  222. Robinson, C. D., Patton, M. S., Andre, B. M. & Johnson, M. A. Convergent evolution of brain morphology and communication modalities in lizards. Current Zoology 61, 281–291, https://doi.org/10.1093/czoolo/61.2.281 (2015).

    Article  Google Scholar 

  223. Kvello, P., Løfaldli, B., Rybak, J., Menzel, R. & Mustaparta, H. Digital, three-dimensional average shaped atlas of the Heliothis virescens brain with integrated gustatory and olfactory neurons. Front. Syst. Neurosci. 3, https://doi.org/10.3389/neuro.06.014.2009 (2009).

  224. Montgomery, S. H. & Merrill, R. M. Divergence in brain composition during the early stages of ecological specialization in Heliconius butterflies. J. Evol. Biol. 30, 571–582, https://doi.org/10.1111/jeb.13027 (2017).

    CAS  Article  PubMed  Google Scholar 

  225. Gordon, D. G., Zelaya, A., Arganda-Carreras, I., Arganda, S. & Traniello, J. F. A. Division of labor and brain evolution in insect societies: Neurobiology of extreme specialization in the turtle ant Cephalotes varians. PLOS ONE 14, e0213618, https://doi.org/10.1371/journal.pone.0213618 (2019).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  226. Rein, K., Zöckler, M., Mader, M. T., Grübel, C. & Heisenberg, M. The Drosophila Standard Brain. Curr. Biol. 12, 227–231, https://doi.org/10.1016/S0960-9822(02)00656-5 (2002).

    CAS  Article  PubMed  Google Scholar 

  227. Shen, J.-M., Li, R.-D. & Gao, F.-Y. Effects of ambient temperature on lipid and fatty acid composition in the oviparous lizards, Phrynocephalus przewalskii. Comp. Biochem. Physiol. B: Biochem. Mol. Biol. 142, 293–301, https://doi.org/10.1016/j.cbpb.2005.07.013 (2005).

    CAS  Article  Google Scholar 

  228. Muscedere, M. L., Gronenberg, W., Moreau, C. S. & Traniello, J. F. A. Investment in higher order central processing regions is not constrained by brain size in social insects. Proc. R. Soc. B: Biol. Sci. 281, https://doi.org/10.1098/rspb.2014.0217 (2014).

  229. Platel, R. L’encéphalisation chez le Tuatara de Nouvelle-Zélande Sphenodon punctatus Gray (Lepidosauria, Sphenodonta). Etude quantifiée des principales subdivisions encéphaliques. J. Hirnforsch. 30, 325–337 (1989).

    CAS  PubMed  Google Scholar 

  230. Makarova, A. A. & Polilov, A. A. Peculiarities of the brain organization and fine structure in small insects related to miniaturization. 1. The smallest Coleoptera (Ptiliidae). Entomol. Rev. 93, 703–713, https://doi.org/10.1134/S0013873813060043 (2013).

    Article  Google Scholar 

  231. Bininda‐Emonds, O. R. P. Pinniped brain sizes. Mar. Mamm. Sci. 16, 469–481 (2000).

    Article  Google Scholar 

  232. Stafstrom, J. A., Michalik, P. & Hebets, E. A. Sensory system plasticity in a visually specialized, nocturnal spider. Sci. Rep. 7, 46627, https://doi.org/10.1038/srep46627 (2017).

    ADS  Article  PubMed  PubMed Central  Google Scholar 

  233. O’Donnell, S., Bulova, S. J., Barrett, M. & Fiocca, K. Size constraints and sensory adaptations affect mosaic brain evolution in paper wasps (Vespidae: Epiponini). Biol. J. Linn. Soc. 123, 302–310, https://doi.org/10.1093/biolinnean/blx150 (2018).

    Article  Google Scholar 

  234. Kamhi, J. F., Gronenberg, W., Robson, S. K. A. & Traniello, J. F. A. Social complexity influences brain investment and neural operation costs in ants. Proc. R. Soc. B: Biol. Sci. 283, 20161949, https://doi.org/10.1098/rspb.2016.1949 (2016).

    Article  Google Scholar 

  235. Kurylas, A. E., Rohlfing, T., Krofczik, S., Jenett, A. & Homberg, U. Standardized atlas of the brain of the desert locust, Schistocerca gregaria. Cell Tissue Res. 333, 125, https://doi.org/10.1007/s00441-008-0620-x (2008).

    Article  PubMed  Google Scholar 

  236. O’Donnell, S. et al. A test of neuroecological predictions using paperwasp caste differences in brain structure (Hymenoptera: Vespidae). Behav. Ecol. Sociobiol. 68, 529–536, https://doi.org/10.1007/s00265-013-1667-6 (2014).

    Article  Google Scholar 

  237. Weltzien, P. & Barth, F. G. Volumetric measurements do not demonstrate that the spider brain “central body” has a special role in web building. J. Morphol. 208, 91–98, https://doi.org/10.1002/jmor.1052080104 (1991).

    Article  PubMed  Google Scholar 

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Acknowledgements

We acknowledge the Wallumattagal clan of the Dharug nation as the traditional custodians of the land on which Macquarie University now stand and that their sovereignty was never ceded. This work was funded by Macquarie University through the Species Spectrum Research Center. We strongly support equity, diversity and inclusion in science. The authors come from different countries (Australia, Austria, United States, South Africa, Bangladesh, Argentina, United Kingdom, Germany, Brazil and India) and represent different career stages (from undergraduate and PhD students, to postdocs, mid-career researchers and Professors). Our author gender balance is biased towards men and at least two authors self-identify as a member of the LGBTQI+community.

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All authors contributed to the conception and development of the original idea. M.E.H., D.J.M., M.K.K., K.S., J.W. collected data from primary sources and curated the data. M.E.H., D.J.M., M.K.K., J.W., A.A., J.S.M., I.W., D.F. designed the database and the workflow. D.J.M. developed the database compilation and standardisation software, J.S.M. developed some of the earlier trialled coding; A.N., M.J.W., M.D.B.E., D.J.M., M.K.K. verified and updated the taxonomy. All authors contributed to the writing and editing of the paper.

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Herberstein, M.E., McLean, D.J., Lowe, E. et al. AnimalTraits - a curated animal trait database for body mass, metabolic rate and brain size. Sci Data 9, 265 (2022). https://doi.org/10.1038/s41597-022-01364-9

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