Trait Databases Research Articles

Traits.build: A data model, workflow and R package for building harmonised ecological trait databases

Trait databases have proliferated over the past decades, facilitating research on the ecology, evolution, and conservation of taxa across the Tree of Life. Typically, teams of independent researchers build these databases, and each must develop their own workflow and output structure. This divests research hours from downstream tasks such as trait-based analysis and interpretation and the resultant datasets are often difficult to integrate due to disparate database structures. Here we introduce the {traits.build} R-package, which offers a generalised workflow for building trait databases. {traits.build} contains bespoke functions for propagating metadata files, extensive tutorials, and sample configuration files, allowing researchers to efficiently build a new trait database using open source tools. In addition, the {traits.build} output structure is fully documented by a data model, ensuring the meaning of each variable and semantic relationship between variables is transparent and consistent. The data standard links to terms in previously published data standards, drawing strongly on DarwinCore and the Ecological Trait-data Standard, but also includes the ability to fully map location and context properties absent from these vocabularies. It is the first published database-building workflow that adheres to the Extensible Observation Ontology. Simultaneously developing a generalised workflow and publishing a data standard for the workflow provides {traits.build} users a straightforward pathway to build a new trait database that achieves the FAIR principles. The meaning of all variables in a {traits.build} database are already documented, allowing further integration with either other {traits.build} databases or indeed any other database with a documented data model. This follows the vision of the Open Traits Network to build trait databases whose data can be easily integrated for further analysis.

AVOTREX: A Global Dataset of Extinct Birds and Their Traits

ABSTRACTMotivationHuman activities have been reshaping the natural world for tens of thousands of years, leading to the extinction of hundreds of bird species. Past research has provided evidence of extinction selectivity towards certain groups of species, but trait information is lacking for the majority of clades, especially for prehistoric extinctions identified only through subfossil remains. This incomplete knowledge potentially obscures the structure of natural communities, undermining our ability to infer changes in biodiversity across space and time, including trends in functional and phylogenetic diversity. Biases in currently available trait data also limit our ability to identify drivers and processes of extinction. Here we present AVOTREX, an open‐access database of species traits for all birds known to have gone extinct in the last 130,000 years. This database provides detailed morphological information for 610 extinct species, along with a pipeline to build phylogenetic trees that include these extinct species.Main Types of Variables ContainedFor each extinct bird species, we provide information on the taxonomy, geographic location, and period of extinction. We also present data on island endemicity, flight ability, and body mass, as well as standard measurements of external (matching the AVONET database of extant birds) and skeletal morphology from museum specimens where available. To ensure comprehensive morphological data coverage, we estimate all missing morphological measurements using a data imputation technique based on machine learning. Finally, we provide an R package to graft all extinct species onto a global phylogeny of extant species (BirdTree).Spatial Location and GrainGlobal.Time Period and GrainAll known globally extinct bird species from 130,000 years ago up until 2024.Major Taxa and Level of MeasurementBirds (Class Aves), species level.Software FormatSpreadsheets (.csv) stored in Dryad.

Combining citizen science data and literature to build a traits dataset of Taiwan’s birds

Trait-based methodologies are gaining traction in the field of ecology, providing deeper insights into ecosystem structure and functions. To this end, trait databases tailored to specific taxonomic groups have become foundational. In Taiwan, the collaborative efforts of avian researchers and dedicated citizen scientists have led to the compilation of a vast array of data. This includes web-sourced images from social media, spatial distribution records from eBird, and morphological metrics from banded birds and specimens. Enriched by peer-reviewed literature, we have meticulously assembled a comprehensive trait dataset encompassing 454 bird species across 73 families. This dataset covers a wide range of traits, including foraging ecology, morphological characteristics, territorial behaviors, breeding attributes, and the roles of bird species in ecosystem regulation. As an invaluable resource, this dataset lays the foundation for in-depth exploration of functional diversity, trait-based community ecology, ecosystem function, and critical insights needed to shape conservation strategies.

Overcoming challenges to access ecological function: a marine soft-bottom perspective

Ecosystem functioning studies have gained prominence due to concerns about the decline of species. In marine sediments, benthic invertebrates perform important ecological functions. However, the challenges within the field of functional ecology are sparsely discussed. Our aim was to systematize the problems and suggest pathways forward. To achieve this, we review recent articles on functional ecology on marine sediments and identified two main issues. First, the absence of a clear definition of terms. Second, in terms of applicability, we observed a mismatch between the scales of functioning and traits, incomplete information on trait databases, inappropriate selection of traits, subjective measures of traits, overlooked trait variability and data analyses without the link between the taxonomy and the traits associated with functions. We propose some pathways to overcome the challenges, such as (i) reasoning of the concept of function, process and trait, (ii) increasing experiments to measure functions, (iii) clarification of the relationship between traits and functions, (iv) clear procedure for assigning trait scores, (v) experiments for understanding trait variability and function performance, and (vi) analyses that consider the sets of traits of each taxon. Overcoming these challenges will allow us to advance research and fill gaps in knowledge of ecosystem functioning.

Modelling soil prokaryotic traits across environments with the trait sequence database ampliconTraits and the R package MicEnvMod

We present a comprehensive, customizable workflow for inferring prokaryotic phenotypic traits from marker gene sequences and modelling the relationships between these traits and environmental factors, thus overcoming the limited ecological interpretability of marker gene sequencing data. We created the trait sequence database ampliconTraits, constructed by cross-mapping species from a phenotypic trait database to the SILVA sequence database and formatted to enable seamless classification of environmental sequences using the SINAPS algorithm. The R package MicEnvMod enables modelling of trait – environment relationships, combining the strengths of different model types and integrating an approach to evaluate the models' predictive performance in a single framework. Traits could be accurately predicted even for sequences with low sequence identity (80 %) with the reference sequences, indicating that our approach is suitable to classify a wide range of environmental sequences. Validating our approach in a large trans-continental soil dataset, we showed that trait distributions were robust to classification settings such as the bootstrap cutoff for classification and the number of discrete intervals for continuous traits. Using functions from MicEnvMod, we revealed precipitation seasonality and land cover as the most important predictors of genome size. We found Pearson correlation coefficients between observed and predicted values up to 0.70 using repeated split sampling cross validation, corroborating the predictive ability of our models beyond the training data. Predicting genome size across the Iberian Peninsula, we found the largest genomes in the northern part. Potential limitations of our trait inference approach include dependence on the phylogenetic conservation of traits and limited database coverage of environmental prokaryotes. Overall, our approach enables robust inference of ecologically interpretable traits combined with environmental modelling allowing to harness traits as bioindicators of soil ecosystem functioning.

Change in functional trait diversity mediates the effects of nutrient addition on grassland stability

Abstract Nutrient enrichment impacts grassland plant diversity such as species richness, functional trait composition and diversity, but whether and how these changes affect ecosystem stability in the face of increasing climate extremes remains largely unknown. We quantified the direct and diversity‐mediated effects of nutrient addition (by nitrogen, phosphorus, and potassium) on the stability of above‐ground biomass production in 10 long‐term grassland experimental sites. We measured five facets of stability as the temporal invariability, resistance during and recovery after extreme dry and wet growing seasons. Leaf traits (leaf carbon, nitrogen, phosphorus, potassium, and specific leaf area) were measured under ambient and nutrient addition conditions in the field and were used to construct the leaf economic spectrum (LES). We calculated functional trait composition and diversity of LES and of single leaf traits. We quantified the contribution of intraspecific trait shifts and species replacement to change in functional trait composition as responses to nutrient addition and its implications for ecosystem stability. Nutrient addition decreased functional trait diversity and drove grassland communities to the faster end of the LES primarily through intraspecific trait shifts, suggesting that intraspecific trait shifts should be included for accurately predicting ecosystem stability. Moreover, the change in functional trait diversity of the LES in turn influenced different facets of stability. That said, these diversity‐mediated effects were overall weak and/or overwhelmed by the direct effects of nutrient addition on stability. As a result, nutrient addition did not strongly impact any of the stability facets. These results were generally consistent using individual leaf traits but the dominant pathways differed. Importantly, major influencing pathways differed using average trait values extracted from global trait databases (e.g. TRY). Synthesis. Investigating changes in multiple facets of plant diversity and their impacts on multidimensional stability under global changes such as nutrient enrichment can improve our understanding of the processes and mechanisms maintaining ecosystem stability.

CASCADE: Dataset of extant coccolithophore size, carbon content and global distribution

Coccolithophores are marine calcifying phytoplankton important to the carbon cycle and a model organism for studying diversity. Here, we present CASCADE (Coccolithophore Abundance, Size, Carbon And Distribution Estimates), a new global dataset for 139 extant coccolithophore taxonomic units. CASCADE includes a trait database (size and cellular organic and inorganic carbon contents) and taxonomic-unit-specific global spatiotemporal distributions (Latitude/Longitude/Depth/Month/Year) of coccolithophore abundance and organic and inorganic carbon stocks. CASCADE covers all ocean basins over the upper 275 meters, spans the years 1964-2019 and includes 33,119 gridded taxonomic-unit-specific abundance observations. Within CASCADE, we characterise the underlying uncertainties due to measurement errors by propagating error estimates between the different studies. This error propagation pipeline is statistically robust and could be applied to other plankton groups. CASCADE can contribute to (observational or modelling) studies that focus on coccolithophore distribution and diversity and the impacts of anthropogenic pressures on historical populations. Additionally, our new taxonomic-unit-specific cellular carbon content estimates provide essential conversions to quantify the role of coccolithophores on ecosystem functioning and global biogeochemistry.

Datasets of traits of zodariid spiders (Araneae: Zodariidae)

Species traits are essential for inferences on ecology and the evolution of organisms. Spiders are the most abundant and diversified terrestrial predators, playing an important role in a range of ecosystem services. Here, I present datasetse on all traits of zodariid spiders, which are known to be free-living ground-dwellers occurring on all continents (except Antarctica) with the highest species diversity in Australia. I collated the data from published resources. The datasets includes nearly 100 000 trait records on all (90) genera and almost all species (1249) of the family. The majority of the 88 traits collected are morphometric, followed by those relating to ecology, reproduction, and physiology. Morphometric traits were available for the majority of species. Other trait classes were only available for some species. I provide a standardized classification of selected categorical traits (habitat, microhabitat, retreat type, circadian activity, prey, primary defensive, and predators). This is the first complete database of traits of a whole spider family, which is available through the World Spider Trait database.

Phenotypic variation in 1,100 provenances of Picea abies measured over 50 years on 33 German trial sites

We present a database of Norway spruce phenotypic traits measured over a period of 51 years in provenance trials planted across western Germany. These trials are part of the ‘Inventory Provenance Test 1964/68 with Norway spruce’ (IPTNS) that tested a total of 1,100 provenances collected across Europe, both from the species natural and artificial range. Phenotypic traits (first height, later diameter at breast height, survival) were recorded at 33 trial sites of 100 provenances, each a subsample from the entire collection area that represents an approximately comparable climate space. The dataset contains 424,781 records of the same 65,518 trees ranging from age 7 to 51. Overall, it captures the considerable genetic and phenotypic intraspecific variation present in Norway spruce and should be of interest to various fields including quantitative genetics, ecology, biogeography and the adaptive management of forests.

Comparing Energetics and Physiological Trait Patterns of North American Birds to Support Ecological Risk Assessment

The environmental risk assessment (ERA) of plant protection products (PPPs) is commonly conducted for a number of standard laboratory species, though its scope includes all species, especially those that are vulnerable or endangered. This begs the question of how the eco-physiological and life history traits of those data-rich species compare to those of less documented species. This paper investigates the utility of a database of such traits, the Add-my-Pet collection of Dynamic Energy Budget theory, for the ERA of North American birds. We identified 72 bird species in the collection that have a federal listing status or are otherwise of interest for the ERA of PPPs and compared their eco-physiological and life history traits in relation to body size, feeding guild, and taxonomic identity to those of 446 terrestrial Holarctic birds, as well as those of standard lab species, notably the northern bobwhite, mallard, and zebra finch. The properties of standard lab species generally align with those of a similar taxonomy and size, with the notable exception of the relatively high reproductive capacity of the northern bobwhite and mallard due to the unique properties of laboratory study data. In addition, taxonomy appears to be a better predictor of eco-physiological traits than feeding guild. We conclude that, to identify representative species for the ERA of PPPs, more traits need to be included, such as those directly linked to the likelihood of exposure and those related to reproductive behavior.

A phylogeny-informed characterisation of global tetrapod traits addresses data gaps and biases.

Tetrapods (amphibians, reptiles, birds, and mammals) are model systems for global biodiversity science, but continuing data gaps, limited data standardisation, and ongoing flux in taxonomic nomenclature constrain integrative research on this group and potentially cause biased inference. We combined and harmonised taxonomic, spatial, phylogenetic, and attribute data with phylogeny-based multiple imputation to provide a comprehensive data resource (TetrapodTraits 1.0.0) that includes values, predictions, and sources for body size, activity time, micro- and macrohabitat, ecosystem, threat status, biogeography, insularity, environmental preferences, and human influence, for all 33,281 tetrapod species covered in recent fully sampled phylogenies. We assess gaps and biases across taxa and space, finding that shared data missing in attribute values increased with taxon-level completeness and richness across clades. Prediction of missing attribute values using multiple imputation revealed substantial changes in estimated macroecological patterns. These results highlight biases incurred by nonrandom missingness and strategies to best address them. While there is an obvious need for further data collection and updates, our phylogeny-informed database of tetrapod traits can support a more comprehensive representation of tetrapod species and their attributes in ecology, evolution, and conservation research.

Ecological drivers of taxonomic, functional, and phylogenetic diversity of bryophytes in an oceanic island.

Montane oceanic islands possess unique geographic and ecological attributes, rendering them valuable for assessing patterns and drivers of alpha and beta taxonomic, functional, and phylogenetic diversity along elevational gradients. Such comparisons of diversity facets can provide insights into the mechanisms governing community assembly on islands. Herein, we aimed to characterize taxonomic, functional, and phylogenetic bryophyte diversity on Madeira Island within and across areas at varying elevations. We also assessed how these diversity facets for the alpha and beta components relate to ecological and anthropogenic factors. We estimated and compared alpha and beta taxonomic, functional, and phylogenetic diversity using 80 plots of 0.5 m × 0.5 m across the whole elevational gradient of the island. We compiled trait databases and supplemented them with our own observations. Phylogenetic information was sourced from the Moss and Liverwort Tree of Life. To assess the impact of ecological and anthropogenic factors on the three facets, we applied linear mixed-effects models and generalized dissimilarity models to alpha- and beta-diversity matrices, respectively. All facets of diversity exhibited strong correlations within both mosses and liverworts, indicating a substantial congruence when alpha and beta are analyzed separately. The bryophyte groups categorized by the growth form demonstrated contrasting patterns, aligning with their distinctive ecological requirements. While a mid-elevation peak emerged as a common pattern across the three facets of alpha diversity, beta diversity often displayed the opposite trend. Although the relative influence of environmental factors varied depending on the diversity facet and bryophyte grouping considered, we found that alpha and beta diversity of bryophytes are more influenced by climatic factors and the predominant type of vegetation than by anthropogenic factors. In the current context of global change, these results should be interpreted with caution, but they point to the resilience of bryophytes to survive in relatively well-preserved natural microhabitats within anthropogenic landscapes. In this study on Madeira Island, we investigated patterns and drivers of alpha and beta taxonomic, functional, and phylogenetic diversity along elevational gradients. We found that alpha and beta diversity of bryophytes are more strongly influenced by climatic factors and the predominant type of vegetation than by anthropogenic factors.

Calculating Nitrogen Uptake Rates in Forests: Which Components Can Be Omitted, Simplified, or Taken from Trait Databases and Which Must Be Measured In Situ?

Calculating Nitrogen Uptake Rates in Forests: Which Components Can Be Omitted, Simplified, or Taken from Trait Databases and Which Must Be Measured In Situ?

A morphological traits dataset of Heteroptera sampled in biodiversity priority areas of Southwest China

Functional traits reveal the adaptive strategies of species to their environment, and are relevant to the formation of communities, the function of ecosystems, and the mechanisms underlying biodiversity. However, trait databases have not been established for most biological taxa, especially for insects, which encompass a vast number of species. This study measured the morphological traits of 307 species of Heteroptera insects collected in 2019 from the “Xishuangbanna Priority Conservation Area” in Southwest China using sweep netting and light trapping methods. This study provides a dataset for 307 Heteroptera species, comprising 34 morphometric measurements and 17 morphological traits. The dataset contains information on species sex, abundance, and the average, maximum, and minimum values of traits. This dataset facilitates an enhanced understanding of the functional traits and ecological associations of Heteroptera insects and offers opportunities for exploring a more diverse range of research topics.

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

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

Shifts in evolutionary lability underlie independent gains and losses of root-nodule symbiosis in a single clade of plants

Root nodule symbiosis (RNS) is a complex trait that enables plants to access atmospheric nitrogen converted into usable forms through a mutualistic relationship with soil bacteria. Pinpointing the evolutionary origins of RNS is critical for understanding its genetic basis, but building this evolutionary context is complicated by data limitations and the intermittent presence of RNS in a single clade of ca. 30,000 species of flowering plants, i.e., the nitrogen-fixing clade (NFC). We developed the most extensive de novo phylogeny for the NFC and an RNS trait database to reconstruct the evolution of RNS. Our analysis identifies evolutionary rate heterogeneity associated with a two-step process: An ancestral precursor state transitioned to a more labile state from which RNS was rapidly gained at multiple points in the NFC. We illustrate how a two-step process could explain multiple independent gains and losses of RNS, contrary to recent hypotheses suggesting one gain and numerous losses, and suggest a broader phylogenetic and genetic scope may be required for genome-phenome mapping.

The AusTraits plant dictionary

Traits with intuitive names, a clear scope and explicit description are essential for all trait databases. The lack of unified, comprehensive, and machine-readable plant trait definitions limits the utility of trait databases, including reanalysis of data from a single database, or analyses that integrate data across multiple databases. Both can only occur if researchers are confident the trait concepts are consistent within and across sources. Here we describe the AusTraits Plant Dictionary (APD), a new data source of terms that extends the trait definitions included in a recent trait database, AusTraits. The development process of the APD included three steps: review and formalisation of the scope of each trait and the accompanying trait description; addition of trait metadata; and publication in both human and machine-readable forms. Trait definitions include keywords, references, and links to related trait concepts in other databases, enabling integration of AusTraits with other sources. The APD will both improve the usability of AusTraits and foster the integration of trait data across global and regional plant trait databases.

Applications of structural equation modeling in plant functional trait research

1.Plant functional traits, which encompass morphological, physiological, and ecological characteristics, are key to plant adaptation, growth, and development. In recent years, the structural equation model (SEM) has gained widespread use as a powerful statistical tool for studying plant functional traits and conducting research in this field. Its ability to distinguish between direct and indirect effects makes the SEM a robust method for investigating the complex relationships among environment components, traits and ecosystem functions. 2.Here, we review and discuss four commonly used SEMs: (1) the covariance-based structural equation model, (2) the piecewise structural equation model, (3) the Bayesian structural equation model, and (4) the partial least squares structural equation model. We also explore their applications in three typical ecosystems—forest, grassland, and wetland ecosystems—and investigate these forms of SEM in the context of their use in trait-ecosystem function research. 3.Our specific objectives were to: (i) compare the advantages and disadvantages of these four types of SEMs; (ii) analyze the current state of research on SEM applications in plant functional traits across diverse ecosystems; and (iii) highlight new approaches and potential research areas for the future application of SEM in plant functional traits. 4.In this paper, several key findings were obtained: (i) the selection of SEM type is influenced by the different spatial scales of the study. (ii) latent and composite variables were less commonly utilized in recent SEM studies. (iii) while SEMs have proven effective in distinguishing between direct and indirect effects to unravel the complex relationships among multiple variables, indirect effects deserve more attention in general studies. We propose that future applications of SEMs in plant functional traits should incorporate a broader spectrum of traits as well as the trade-offs between them. Larger and more diverse databases of plant functional traits would help make SEM analyses more accurate across different scales.

Exotic plant species with longer seed bank longevity and lower seed dry mass are more likely to be invasive in China

Abstract Globalization of social and economic activities has led to the large-scale redistribution of plant species. It is still unclear how the traits aid the successful invasion of alien species. Here, we downloaded global plant trait data from the TRY-Plant Trait Database and classified alien species in China into four groups: high, medium, need attention and harmless according to their distribution and degree of harm to local plant communities based on existed studies. The relationship between plant functional traits and invasion level was clarified, and we established a prediction model based on plant functional traits and taxonomy. The results showed that species with smaller seeds, smaller individuals, lower special leaf area and longer seed bank longevity (SL) are more likely to be an invasive species after introduction to foreign ecosystems. In summary, exotic species with longer SL and lower seed dry mass are more likely to be invasive in China. We also trained two predictive models to check if we can predict a species’ invasion. Combining the two models together, statistically, we could predict if a species is invasive from its traits and taxonomy with a 91.84% accuracy. This model could help local governments, managers and stakeholders to evaluate shall we introduce some plant species in China.

ZooTraits: An R shiny app for exploring animal trait data for ecological and evolutionary research.

Animal trait data are scattered across several datasets, making it challenging to compile and compare trait information across different groups. For plants, the TRY database has been an unwavering success for those ecologists interested in addressing how plant traits influence a wide variety of processes and patterns, but the same is not true for most animal taxonomic groups. Here, we introduce ZooTraits, a Shiny app designed to help users explore and obtain animal trait data for research in ecology and evolution. ZooTraits was developed to tackle the challenge of finding in a single site information of multiple trait datasets and facilitating access to traits by providing an easy-to-use, open-source platform. This app combines datasets centralized in the Open Trait Network, raw data from the AnimalTraits database, and trait information for animals compiled by Gonçalves-Souza etal. (2023, Ecology and Evolution 13, e10016). Importantly, the ZooTraits app can be accessed freely and provides a user-friendly interface through three functionalities that will allow users to easily visualize, compare, download, and upload trait data across the animal tree of life-ExploreTrait, FeedTrait, and GetTrait. By using ExploreTrait and GetTrait, users can explore, compare, and extract 3954 trait records from 23,394 species centralized in the Open Traits Network, and trait data for ~2000 species from the AnimalTraits database. The app summarizes trait information for numerous taxonomic groups within the Animal Kingdom, encompassing data from diverse aquatic and terrestrial ecosystems and various geographic regions worldwide. Moreover, ZooTraits enables researchers to upload trait information, serving as a hub for a continually expanding global trait database. By promoting the centralization of trait datasets and offering a platform for data sharing, ZooTraits is facilitating advancements in trait-based ecological and evolutionary studies. We hope that other trait databases will evolve to mirror the approach we have outlined here.