Taxa Research Articles

Transposable element diversity and activity patterns in neotropical salamanders.

Transposable elements (TEs) compose a substantial proportion of the largest eukaryotic genomes. TE diversity has been hypothesized to be negatively correlated with genome size, yet empirical demonstrations of such a relationship in a phylogenetic context are largely lacking. Furthermore, the most abundant type of TEs in genomes varies across groups, and it is not clear if there are patterns of TE activity consistent with genome size among different taxa with large genome sizes. We use low-coverage sequencing of 16 species of Neotropical salamanders, which vary approximately seven-fold in genome size, to estimate TE relative abundance and diversity for each species. We also compare divergence of copies of each TE superfamily to estimate patterns of TE activity in each species. We find a negative relationship between TE diversity and genome size, which is consistent with the hypothesis that either competition among TEs or reduced selection against ectopic recombination may result in lower diversity in the largest genomes. We also find divergent activity patterns in the largest vs. the smallest genomes, suggesting that the history of TE activity may explain differences in genome size. Our results suggest that both TE diversity and relative abundance may be predictable, at least within taxonomic groups.

Influence of vegetable knowledge in preschooler’s vegetable consumption: Veggies4myHeart project

Abstract Background Vegetable consumption among children is below recommended. Food rejection, especially vegetables, is common in preschool-aged children. Impoverished food knowledge is associated with this rejection. The Veggies4myHeart project aims to promote vegetable consumption and knowledge among preschoolers’. This study assesses the project’s effectiveness in increasing vegetable knowledge and consumption and whether increased knowledge influences vegetable consumption. Methods Veggies4myHeart is a prospective longitudinal study with children 2-6 years old attending preschools. Two preschools participated in a five-week intervention in the 2023/24 academic year. A distinctive pedagogical tool was tested in each preschool: a storybook and a digital game. Knowledge and vegetable consumption were assessed before and after the intervention. Knowledge was evaluated through a questionnaire with taxonomic categorization. Consumption was assessed by recording the portions of eight vegetables (carrot, lettuce, red cabbage, cucumber, tomato, onion, beetroot, and red bell pepper). Wilcoxon test was applied to compare vegetable knowledge and consumption before and after the intervention. Spearman’s correlation was used to examine the association between knowledge and vegetable consumption before and after the intervention. Results 98 children (55.1% female, mean age 4.15 ± 0.868 years) participated. Statistically significant increases in both knowledge and total vegetable consumption were observed post-intervention in both preschools (p < 0.001). A moderate correlation of 0.412 (p = 0.013) in the storybook group post-intervention suggests that increased knowledge may contribute to increased vegetable consumption. Conclusions This study demonstrates the potential of the Veggies4myHeart project as an effective strategy to promote knowledge about vegetables among preschool children, highlighting the critical role of educational interventions in promoting healthier dietary patterns. Key messages • To increase vegetable knowledge may lead to higher consumption in preschool children. • Veggies4myHeart demonstrated its effectiveness as an educational project for preschool children.

Veggies4myHeart – educational project to promote vegetable knowledge and consumption in preschoolers

Abstract Vegetable consumption among children is below recommended. Given the critical role of vegetable consumption in health promotion, it is essential to identify effective strategies to promote this intake. The Veggies4myHeart project aims to increase vegetable knowledge and consumption in preschool children through nutrition education strategies (NES). Veggies4myHeart is a prospective longitudinal study with children aged 2 to 6 years who attend preschools in the Leiria district. A questionnaire was applied to the parents to characterize the sample. NES were used: children’s story, digital game, vegetable-themed sticker booklet and the food wheel. The intervention consisted of 5 food education sessions, each focusing on one selected vegetable (lettuce, carrot, red cabbage, cucumber, and tomato). Sessions to assess knowledge and consumption of vegetables were held pre-and post-intervention. Knowledge was evaluated through a taxonomic categorization questionnaire. Consumption was assessed by recording the number of portions of each vegetable consumed. Wilcoxon test was used to compare pre-and post-intervention vegetable knowledge and consumption. ANOVA test was used to compare NES. Between 2018 and 2024, 649 children (52,5% female, mean age 4,36 ± 0,942) from 17 preschools participated. After the intervention, there was a statistically significant increase in vegetable knowledge (p < 0,001) and a statistically significant increase in the consumption of vegetables (p < 0,001). There are statistically significant differences between NES, with the digital game having greater vegetable knowledge (p < 0,001) and consumption (p < 0,001) than the others. The Veggies4myHeart project effectively increased vegetable knowledge and consumption in preschoolers. It is essential to continue the intervention to promote consumption and familiarity with vegetables, as well as the involvement of parents and preschool teachers, due to their prominent role as models for acquiring healthy eating habits. Key messages • The NES used proved useful, contributing to increased knowledge and consumption of vegetables. • The Veggies4myHeart project is an asset for preschool-aged children to become familiar with vegetables.

Microbiome associated to an H2-emitting zone in the São Francisco basin Brazil

BackgroundDihydrogen (H₂) natural gas is a clean and renewable energy source of significant interest in the transition to sustainable energy. Unlike conventional petroleum-based fuels, H₂ releases only water vapor upon combustion, making it a promising alternative for reducing carbon footprints in the future. However, the microbial impact on H₂ dynamics in H2-emitting zones remains unclear, as does the origin of H2 — whether it is produced at greater depths or within shallow soil layers. In the São Francisco Basin, soil hydrogen concentrations of approximately 200 ppm were identified in barren ground depressions. In this study, we investigated the microbiome associated with this area using the 16S rRNA gene sequencing, with a focus on metabolic processes related to H₂ consumption and production. Soil samples were collected from two monitored (< 1 m) depths – 10 cm and 1 m – in the emission zone, which is predominantly covered with pasture vegetation, and from an adjacent area with medium and small trees.ResultsOur findings suggest that the H2-emitting zone significantly influences the composition and function of the microbiome, with Bacillus emerging as the dominant genus. In contrast to typical Cerrado soil, we observed a higher prevalence of Actinobacteriota (∼ 40%) and Firmicutes (∼ 20%). Additionally, we identified an abundance of sporulating bacteria and taxonomic groups previously described as H2-oxidizing bacteria.ConclusionsThe H2-emitting zone in the São Francisco Basin presents a unique opportunity to deepen our understanding of the impact of H₂ on microbial communities. This study is the first to characterize a natural H2-associated bacterial community in Cerrado soil using a culture-independent approach.

An Inconvenient Truth: A Comprehensive Examination of the Added Value (or Lack Thereof) of Leadership Measures

AbstractThe leadership literature encompasses a bewildering array of leadership styles, with most studies focussing on the nature and consequences of a single leadership style in isolation. This isolationist approach has led researchers to mostly ignore the similarities between supposedly different leadership styles, and few studies have examined these overlaps empirically. To understand the extent of this problem, we use bifactor exploratory structural equation modelling to examine whether 12 dominant leadership measures capture shared variance and whether any variance unique to a particular style is related to theoretically and empirically established covariates. Moreover, we explore what the shared variance of these leadership measures may represent. Across seven samples, five countries, multiple organizational contexts, and 4000 respondents, the 12 leadership measures shared significant amounts of variance and did not systematically capture unique leadership‐related variance. Further analyses indicated this shared variance mainly represented the affective quality of the leader–follower relationship. The results reveal an inconvenient truth for leadership researchers who wish to differentiate styles, as the styles have much more in common than differences. Contrasting with previous recommendations to refine styles, we argue that a taxonomic leadership behaviour categories approach to leadership research is the most parsimonious way forward.

Towards a Taxonomy Machine: A Training Set of 5.6 Million Arthropod Images

The taxonomic identification of organisms from images is an active research area within the machine learning community. Current algorithms are very effective for object recognition and discrimination, but they require extensive training datasets to generate reliable assignments. This study releases 5.6 million images with representatives from 10 arthropod classes and 26 insect orders. All images were taken using a Keyence VHX-7000 Digital Microscope system with an automatic stage to permit high-resolution (4K) microphotography. Providing phenotypic data for 324,000 species derived from 48 countries, this release represents, by far, the largest dataset of standardized arthropod images. As such, this dataset is well suited for testing the efficacy of machine learning algorithms for identifying specimens into higher taxonomic categories.

Integrated Analysis of Metabolites and Microorganisms Reveals the Anthracnose Resistance Benefits from Cyanidin Mediated by Proteobacteria in Tea Plants

Anthocyanins, key quality components of tea, act as an important bridge between plants and the environment due to their function on protecting plants from biotic and abiotic irritants. This study aimed to assess the interactions between anthocyanins metabolism and the environment. Purple (P) and green (G) leaves with different anthocyanin contents were inoculated with tea plant anthracnose. High-throughput metabolomics and 16S microbial diversity sequencing methods were used to screen the anthocyanin fractions of tea plant leaves responsive to anthracnose. The interconnections between metabolites and the resistance of phyllosphere microorganisms to fungal pathogens were then analyzed. The results showed that leaves with high anthocyanin content (0.14% of diseased area ratio) were less impacted by anthracnose infestation than leaves with low anthocyanin (3.12%). The cyanidin content decreased after infection in purple leaves (PR) and increased in green leaves (GR). The relative abundance of Cyanobacteria was suppressed by the significant enrichment of Proteobacteria after anthracnose infection in green leaves. However, there were no significant differences between these two groups of microorganisms in purple leaves. Collinear network analysis revealed a strong correlation between Cyanobacteria and Dihydrosorbinol and between Proteobacteria and cyanidin metabolites. Among them, OTU456 (Bosea) was identified as the key taxonomic group of bacterial communities in the green-infected leaf network. In summary, the anthracnose resistance benefits from cyanidin mediated by proteobacteria in tea plants. These results deepen our understanding of the regulation of secondary metabolism in tea plants and the formation of plant resistance.

Effects of tillage intensity and pesticide treated seeds on epigeal arthropod communities and weed seed predation in a maize-soybean rotation

Tillage practices and the use of pesticide seed treatments (PST) both have the potential to influence epigeal arthropod communities and the ecosystem services they provide, yet few studies have examined both factors in conjunction. A three-year field study (2017–2019) was conducted to assess the independent and interactive effects of tillage and pesticide seed treatments on epigeal arthropod communities and weed seed predation in a long-term row crop tillage intensity experiment located in southeastern New Hampshire, USA. Throughout the study, maize and soybean were planted in rotation with and without pesticide seed treatments (seed coatings containing a mixture of systemic and contact fungicides and neonicotinoid insecticides) under three tillage systems (full-, strip-, and no-till) in a randomized complete block design with four replications. Epigeal arthropod communities were sampled with pitfall traps from September to October 2018–2019 and weed seed predation was assessed over the same period each year from 2017–2019. A total of 1669 individual arthropods, representing 47 taxonomic groups, were observed over the course of the study. In 2018, epigeal arthropod communities differed based only on pesticide seed treatment. The opposite response was observed in 2019, as epigeal arthropod communities differed based only on tillage. Activity densities of Pterostichus melanarius (Illiger) were higher in the strip-till compared to full-till treatment in 2018. Annual levels of post-dispersal weed seed predation by invertebrates (% total seeds removed) varied based on tillage treatment in 2017 and 2019, but not in 2018, and ranged from as low as 6.1 % to as much as 27.2 % depending on year and treatment. These data provide evidence that both pesticide seed treatments and tillage systems can influence the communities of epigeal arthropods that inhabit annual row crop agroecosystems relatively late in the growing season, when the majority of pesticide residues have likely dissipated, and that the weed seed predation services provided by members of this community can be strongly negatively impacted by intensive tillage.

Host and habitat shape ectoparasite diversity on Mastomys natalensis and Mastomys coucha (Muridae).

Mastomys natalensis and M. coucha are commensal rodent species endemic to Africa. A recent taxonomic revision within Mastomys leaves the parasite–host list of M. natalensis questionable and that of M. coucha incomplete. The current study aimed to develop a better understanding of the ectoparasite diversity associated with the 2 distinct but closely related rodent species and to explore the influence of host and habitat type on ectoparasite infestations. Between 2014 and 2020, 590 rodents were trapped in 3 habitat types (village, agriculture and natural) across a wildlife-human/domestic animal interface. In total 48 epifaunistic species (45 ectoparasitic and 3 predatory) represented by 29 genera from 4 taxonomic groups (fleas, lice, mites and ticks) were recorded. Only 50% of the epifauna were shared between the 2 rodent species, with mites the most speciose taxon in both host species. The abundance of epifaunistic individuals, and also those of mites and fleas, were significantly higher on male M. natalensis, while ticks were significantly higher on reproductively active M. natalensis. For both rodent species, infestations by most epifaunistic taxa (on M. natalensis) and some taxa (on M. coucha) were significantly lower in the village as opposed to the less disturbed agricultural and natural habitat types. The study highlights the importance of host life history, even in closely related rodent species, in shaping parasite profiles and a loss of parasite diversity in more extreme anthropogenic habitats.

Shift of bacterial and fungal communities upon soil amelioration is driven by carbon degradability of organic amendments

The structural response of bacterial and fungal soil communities to four carbon-rich organic amendments of increasing recalcitrance was investigated. Wheat straw, green compost, a mixed product based on biogas residues, and a fermented biochar were applied to a sandy agricultural soil of low organic carbon content. After laboratory incubation for 6 months, the community structure was investigated via DNA sequencing. All amendments caused changes in the communities of bacteria and fungi, but to different extents, with the communities exposed to more recalcitrant amendments showing the least variation compared to the non-amended soil. Changes in species composition as well as their relative abundances were observed. While the straw had a pronounced effect on bacteria (e.g., the highest number of indicator species), effects of the composted, fermented, or pyrolyzed materials were minor. Hierarchical clustering showed that the fungal communities were more different from each other than the bacterial ones with the straw-soil being most different and the biochar-soil least different from the non-amended soil. While the abundant fungal species in biochar-soil and non-amended soil were very alike, especially rare fungal species shifted upon addition of biochar. An indicator species analysis identified specific taxonomic groups which were triggered by the different organic materials. We conclude that bacterial and fungal communities strongly change upon input of degradable carbon (straw), while fungi in particular respond to the application of processed organic materials. With this study, we report the consequences of applying organic materials for the microbial community in one soil. We provide these data for meta-analyses that are required to unravel all relevant interactions across different soils, organic materials, and time. This will allow to better understand and predict the effects of organic soil amelioration measures on soil microorganisms.

The 2024 IPD-MHC database update: a comprehensive resource for major histocompatibility complex studies.

The IPD-MHC Database project (http://www.ebi.ac.uk/ipd/mhc/) serves as a comprehensive and expertly curated repository for major histocompatibility complex (MHC) sequences from non-human species, providing the necessary infrastructure and tools to study the function and evolution of this highly polymorphic genomic region. In its latest version, the IPD-MHC database has expanded both in content and in the tools for data visualization and comparison. The database now hosts over 18 000 MHC alleles from 125 species, organized into eleven taxonomic groups, all manually curated and named by the Comparative MHC Nomenclature Committee. A cetacean section has recently been included, offering researchers valuable data to study the immune system of whales, dolphins, and porpoises, as well establishing the official nomenclature platform for the Cetacea Leukocyte Antigens (CeLA). In response to user demand and reflecting broader trends in bioinformatics and immunogenetics, IPD-MHC now includes the predicted tertiary structure of over 8000 alleles and allows comparison and visualisation of allele variation within and between species at single residue resolution. These latest developments maintain the critically important link between official nomenclature of curated alleles and the ability to analyse this complex polymorphism using the most up to date methods within a single repository.

LukProt: A database of eukaryotic predicted proteins designed for investigations of animal origins.

The origins and early evolution of animals is a subject with many outstanding questions. One problem faced by researchers trying to answer them is the absence of a comprehensive database with sequences from non-bilaterians. Publicly available data is plentiful but scattered and often not associated with proper metadata. A new database presented in this paper, LukProt, is an attempt at solving this issue. The database contains protein sequences obtained mostly from genomic, transcriptomic and metagenomic studies and is an extension of EukProt (Richter et al., 2022, Peer Community Journal, 2, e56). LukProt adopts the EukProt naming conventions and includes data from 216 additional animals. The database is associated with a taxonomic grouping (taxogroup) scheme suitable for studying early animal evolution. Minor updates to the database will contain species additions or metadata corrections and major updates will synchronize LukProt to each new version of EukProt and releases are permanently stored on Zenodo (https://doi.org/10.5281/zenodo.7089120). A BLAST server to search the database is available at https://lukprot.hirszfeld.pl/. Users are invited to participate in maintaining and correcting LukProt. As it can be searched without downloading locally, the database can be a convenient resource not only for evolutionary biologists, but for the broader scientific community as well.

A portable and low-cost optical device for pigment-based taxonomic classification of microalgae using machine learning

The proliferation of certain phytoplankton species may lead to harmful algal blooms (HABs) that can affect living resources and human health. Therefore, an accurate identification of phytoplankton populations is essential for the sustainable management of some activities relevant for the blue economy, such as aquaculture, being also relevant for environmental monitoring and marine research purposes. Microalgae taxonomic discrimination, based on their pigment composition, is a versatile and promising technique to detect and identify potential HABs. In this work, a portable and low-cost device for taxonomic identification of microalgae, based on the pigment composition of 16 species belonging to 6 different phyla, was developed. It uses the fluorescence intensity signal emitted by each species at three wavelengths (575 nm, 680 nm and 730 nm) when excited at five wavelengths (405 nm, 450 nm, 500 nm, 520 nm and 623 nm) to create a fluorescence signature for each species. Furthermore, several machine learning classifiers were studied using this fluorescence signature as features to train and classify each species according to their respective taxonomic group. The Extreme Gradient Boosting (XGBoost) classifier was able to correctly predict microalgae monocultures with 97 % accuracy at the phylum level and 92 % accuracy at the order level. The obtained results confirm the potential of this technique for fast, accurate and low-cost identification of microalgae.

Influence of Storage Methods on the Vitality and Growth Rate of Macrofungi

The work contains a comparative analysis of methods for storing pure cultures of macrofungi. The study used 20 species of macrofungi from various taxonomic and ecological-trophic groups. Storage was carried out using five methods: serial subculturing, storage under a layer of distilled water and three cryopreservation protocols: a protocol using blocks of agar medium, a “perlite protocol” and a “grain protocol”. For the selected cryostorage methods, various cryoprotective compounds (glycerol, trehalose) were used. Radial growth rate was used as a criterion for the state of crops. The values of the radial growth rate obtained immediately after isolation of the pure culture were chosen as the control. It has been shown that the most favorable for preserving the physiological activity of cultures are the storage method under a layer of distilled water, “perlite” and “grain” cryopreservation protocols.

The Neotropical Biodiversity Mapping Initiative: Transforming Venezuelan biodiversity monitoring and capacity building

Tropical Latin America is home to an enormous share of the world's biodiversity. Despite its immense natural wealth, the region faces a significant deficit of reliable biodiversity data and lacks the local capacity necessary to collect such data. The Neotropical Biodiversity Mapping Initiative (NeoMaps or NeoMapas) is a long-term biodiversity monitoring program. NeoMaps has not only addressed these gaps in biodiversity data in one of the megadiverse tropical countries, Venezuela, but has also emerged as a model for efficiently surveying biodiversity while strengthening the local capacity needed to conduct these surveys. After three nationwide systematic surveys and international field courses in 2006, 2009, and 2010, NeoMaps assembled an invertebrate collection and biodiversity database with over 170,000 records of occurrence and abundance for birds, dung beetles, and butterflies. NeoMaps activities lead to direct outcomes by reducing biodiversity knowledge gaps for three taxonomic groups and training more than 60 conservationists from Venezuela, Colombia, Mexico, Peru, Bolivia, Brazil, Uruguay, and Spain. NeoMaps had a broader impact on national capacity building programs, and made important contributions for improving, sharing and applying national biodiversity knowledge.

Application of the MENTOR model to advance One Health by promoting bat conservation and reducing zoonotic spillover risk

For few taxonomic groups do conservation efforts have such a disproportionate impact on biodiversity and human well-being as they do with bats. Bats face significant conservation challenges that affect their long-term viability, inhibit their ecosystem functions and services, and increase zoonotic spillover risks. Protecting bat populations and their habitats ultimately reduces these conservation threats, helps prevent pandemics, and supports essential ecosystem services. MENTOR-Bat is a fellowship program focused on strengthening technical research, and leadership capacity in the Global South to promote healthy environments where bats and humans can coexist with reduced risks of pathogen transmission. Co-designed by the United States Fish and Wildlife Service (USFWS) and Bat Conservation International (BCI), MENTOR-Bat mirrors the One Health framework by featuring a transdisciplinary team of three mentors and nine fellows from Cameroon, Colombia, and Indonesia. Fellows and mentors receive academic and field-based training on bat ecology and conservation, One Health, human dimensions of conservation, behavior change, strategic communications, international policy, adaptive management, project planning, conservation leadership, and public health. Fellows will then design and implement team pilot projects to advance One Health and bat conservation in their respective countries. Program evaluation of MENTOR-Bat is based on Kirkpatrick’s Hierarchy and focuses on measuring the development of established One Health core competences. By incorporating One Health and conservation within its activities, MENTOR-Bat can become a valuable programmatic template for transdisciplinary programming advancing evidence-based strategies for improving the well-being of bats, humans, and the environment.

Evidence for ecological tuning of anuran biofluorescent signals

Although biologists have described biofluorescence in a diversity of taxa, there have been few systematic efforts to document the extent of biofluorescence within a taxonomic group or investigate its general significance. Through a field survey across South America, we discover and document patterns of biofluorescence in tropical amphibians. We more than triple the number of anuran species that have been tested for this trait. We find evidence for ecological tuning (i.e., the specific adaptation of a signal to the environment in which it is received) of the biofluorescent signals. For 56.58% of species tested, the fluorescence excitation peak matches the wavelengths most abundant at twilight, the light environment in which most frogs are active. Additionally, biofluorescence emission spans both wavelengths of low availability in twilight and the peak sensitivity of green-sensitive rods in the anuran eye, likely increasing contrast of this signal for a conspecific receiver. We propose an expanded key for testing the ecological significance of biofluorescence in future studies, providing potential explanations for the other half of fluorescent signals not originally meeting formerly proposed criteria. With evidence of tuning to the ecology and sensory systems of frogs, our results suggest frog biofluorescence is likely functioning in anuran communication.

A new small-sized Calotes Cuvier (Squamata: Agamidae: Draconinae) from the Subansiri river basin, Arunachal Pradesh, India

We describe a new species of small-sized Calotes from mid-elevation (~1270 m asl.), swidden or shifting cultivation areas in the Subansiri river basin, Upper Subansiri District, Arunachal Pradesh, India. Mitochondrial sequence data (ND2) recovers Calotes sinyik sp. nov. as the closely related sister taxon to an unnamed species from Medog, Tibet; the two falling in a broader clade including C. paulus + C. zolaiking and species of the C. emma and C. mystaceus groups. The new species is 7.8% divergent in ND2 sequence data from the unnamed lineage from Medog and deeply divergent (≥ 21.6–28.1%) from other congeners. The new species can easily be distinguished from regional congeners by its small adult body size (maximum snout to vent length of 65 mm) and heterogenous dorsal scales, and from its closest relatives C. paulus and C. zolaiking by having 54 or 55 midbody scale rows and 42 or 43 vertebral scales. It is likely that many more allied species remain to be discovered from Northeast India, which remains poorly surveyed across taxonomic groups.

Decoding Adverse Effects of Organic Contaminants in the Aquatic Environment: A Meta-analysis of Species Sensitivity, Hazard Prediction, and Ecological Risk Assessment.

Aquatic organisms in the environment are frequently exposed to a variety of organic chemicals, while these biological species may show different sensitivities to different chemical groups present in the environment. This study evaluated species sensitivity, hazards, and risks of six classes of organic chemicals in the aquatic environment. None of the taxonomic groups were the most sensitive or tolerant to all chemicals, as one group sensitive to one class of chemicals might possess adaptations to other chemical groups. Polychlorinated biphenyls were generally the most toxic chemical group, followed by polybrominated diphenyl ethers, polycyclic aromatic hydrocarbons, and pharmaceuticals and personal care products, while per- and polyfluoroalkyl substances and phthalate esters were the less toxic chemical groups. The hazard of organic chemicals was closely related to their physicochemical properties, including hydrophobicity and molecular weight. It was shown that 20% of the evaluated chemicals exhibited medium or high ecological risks with the worst-case scenario in the Pearl River Estuary. This novel work represented a comprehensive comparison of chemical hazards and species sensitivity among different classes of organic chemicals, and the reported results herein have provided scientific evidence for ecological risk assessment and water quality management to protect aquatic ecosystems against organic chemicals.

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

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