Trait Databases Research Articles

Advancing mycorrhizal trait-based ecology using both pure cultures and community-level traits.

Traits are the intermediate by which species respond to environmental filters and influence ecosystem functions. With the myriad of biogeochemical processes controlled by fungi, the past decade has witnessed a rising interest in applying trait-based approaches, core to the toolkit of plant and animal ecophysiologists, to fungi. One of the first challenges to tackle when working on fungal ecophysiology is to circumscribe the very definition of what we consider a fungal trait. Traits are characteristics/features possessed by an individual that can influence how it interacts with its environment. Here, the individual scale is both important, and problematic. Important because the very goal of comparative ecology is to measure traits on individuals belonging to known species. This allows us to populate trait databases, and syntheses of such databases can reveal key trade-offs and trait syndromes that govern species' life-histories. The scale of the individual is problematic, however, because it is hard to define for soil fungi, and because a rare minority of fungi can be sampled at the individual scale in the environment (e.g., macroscopic sporocarps, ectomycorrhizal root tips, lichen thalli). Beyond this minority, the individual organisms can only be accessed/sampled through establishing fungal cultures, which probably represents one of the main bottlenecks in the development of fungal trait databases. In this issue of Molecular Ecology, Zhang et al.(2022) show how interesting insights in fungal trait-based ecology can be gained by working at the community level.

Lianas have a faster resource acquisition strategy than trees: Below‐ground evidence from root traits, phylogeny and the root economics space

Abstract The competitive advantage of lianas over trees has been widely documented in studies of their leaf functional traits across diverse habitats; however, the relative contribution of root functional traits to the competitive superiority of lianas over trees has not yet been evaluated. The aim of this study was to explore the root functional traits, phylogenetic structure of these traits and root trait dimensions of lianas to clarify why lianas can outperform trees. We sampled 69 liana species from tropical and temperate forests in China and measured nine key functional traits of first‐order roots of each species, including morphological, architectural, anatomical and chemical traits, as well as the percentage of mycorrhizal colonization. Data on these traits were then compared with similar data of 127 tree species from the same biome obtained from the Global Root Traits (GRooT) database and our previous studies. Liana roots had lower construction costs and could acquire resources more rapidly compared with tree roots. Significant differences were observed in most tree root traits between tropical and temperate sites. However, no significant differences were observed in any of the liana root traits between tropical and temperate sites, apart from the root branching ratio. Lianas showed much weaker phylogenetic conservatism in their root traits than trees when species were pooled across sites. Phylogenetic constraint was lower for nearly all root traits of both temperate lianas and trees compared with those of tropical lianas and trees. The root economics space of lianas and trees had two orthogonal dimensions with ‘conservation’ and ‘collaboration’ axes. However, lianas occupied the trait space with higher root nitrogen concentration and greater specific root length, showing ‘fast’ resource acquisition strategy, while trees placed opposite space and exhibited relatively ‘slow’ strategy. Synthesis. The ability of lianas to outcompete trees in harsh environments might be explained by their faster resource acquisition strategy and the lower phylogenetic constraint in root traits. Generally, lianas might play an increasingly important role in the structure and function of forest ecosystems in the future with ongoing habitat fragmentation and climate change.

New Proposal of Epiphytic Bromeliaceae Functional Groups to Include Nebulophytes and Shallow Tanks.

The Bromeliaceae family has been used as a model to study adaptive radiation due to its terrestrial, epilithic, and epiphytic habits with wide morpho-physiological variation. Functional groups described by Pittendrigh in 1948 have been an integral part of ecophysiological studies. In the current study, we revisited the functional groups of epiphytic bromeliads using a 204 species trait database sampled throughout the Americas. Our objective was to define epiphytic functional groups within bromeliads based on unsupervised classification, including species from the dry to the wet end of the Neotropics. We performed a hierarchical cluster analysis with 16 functional traits and a discriminant analysis, to test for the separation between these groups. Herbarium records were used to map species distributions and to analyze the climate and ecosystems inhabited. The clustering supported five groups, C3 tank and CAM tank bromeliads with deep tanks, while the atmospheric group (according to Pittendrigh) was divided into nebulophytes, bromeliads with shallow tanks, and bromeliads with pseudobulbs. The two former groups showed distinct traits related to resource (water) acquisition, such as fog (nebulophytes) and dew (shallow tanks). We discuss how the functional traits relate to the ecosystems inhabited and the relevance of acknowledging the new functional groups.

Defensive spines are associated with large geographic range but not diversification in spiny ants (Hymenoptera: Formicidae: Polyrhachis)

AbstractSeveral prominent evolutionary theories propose mechanisms whereby the evolution of a defensive trait or suite of traits causes significant shifts in species diversification rate and niche evolution. We investigate the role of cuticular spines, a highly variable morphological defensive trait in the hyperdiverse ant genus Polyrhachis, on species diversification and geographic range size. Informed by key innovation theory and the escape‐and‐radiate hypothesis, we predicted that clades with longer spines would exhibit elevated rates of diversification and larger range sizes compared to clades with shorter spines. To address these predictions, we estimated phylogenetic relationships with a phylogenomic approach utilizing ultraconserved elements and compiled morphological and biogeographic trait databases. In contrast to the first prediction, we found no association between diversification rate and any trait (spine length, body size and range size), with the sole exception of a positive association between range size and diversification in one of three trait‐based diversification analyses. However, we recovered a positive phylogenetic correlation between spine length and geographic range size, suggesting that spines promote expanded geographic range. Notably, these results were consistent across analyses using different phylogenetic inference approaches and spine trait measurement schemes. This study provides a rare investigation of the role of a defensive trait on geographic range size, and ultimately supports the hypothesis that defensive spines are a factor in increased range size in Polyrhachis ants. Furthermore, the lack of support for an association between spines and diversification, which contrasts with previous work demonstrating a positive association between spines and diversification rate, is intriguing and warrants further study.

The prediction accuracies of linear-type traits in Czech Holstein cattle when using ssGBLUP or wssGBLUP.

The aim of this study was to assess the contribution of the weighted single-step genomic best linear unbiased prediction (wssGBLUP) method compared to the single-step genomic best linear unbiased prediction (ssGBLUP) method for genomic evaluation of 25 linear-type traits in the Czech Holstein cattle population. The nationwide database of linear-type traits with 6,99,681 records combined with deregressed proofs from Interbull (MACE method) was used as the input data. Genomic breeding values (GEBVs) were predicted based on these phenotypes using ssGBLUP and wssGBLUP methods using the BLUPF90 software. The bull validation test was employed which was based on comparing GEBVs of young bulls (N = 334) with no progeny in 2016. A minimum of 50 daughters with their own performance in 2020 was chosen to verify the contribution to the GEBV prediction, GEBV reliability, validation reliabilities (R2), and regression coefficients (b1). The results showed that the differences between the two methods were negligible. The low benefit of wssGBLUP may be due to the inclusion of a small number of SNPs; therefore, most predictions rely on polygenic relationships between animals. Nevertheless, the benefits of wssGBLUP analysis should be assessed with respect to specific population structures and given traits.

Macrophysiology for decision‐making

AbstractIn an 1854 lecture, TH Huxley suggested that physiology should be measured by its contribution to science, its practical worth and the extent to which it should be made a branch of education. Since macrophysiology, or the investigation of variation in physiological traits over large geographical and temporal scales and the ecological implications of this variation, is well‐established and approaching its third decade, these questions are posed for it here. The field is, of course, much older, but, over the last two decades, has contributed substantially to fundamental eco‐evolutionary research and to understanding the conservation consequences of physiological variation at regional and global scales. Its greatest successes have been in understanding variation in thermal and metabolic responses of animals and plants to variable environments and the significance thereof in the context of the climate crisis. By contrast, much less progress has been made in understanding the regulation of water in the context of currently changing environments and projections of further impacts associated with ongoing global change. The development of new datasets of physiological traits across broad spatial scales has been a slower enterprise than the further compilation of trait databases from extant data. Surprising insights have emerged from genomics‐based microbial macrophysiology, an approach which has much potential to span all of life's variety. The findings of macrophysiological investigations have been taken up within policy reports and/or implementation actions, such as those of the IPCC and the Antarctic Treaty System, that have resulted in benefits to society and to the environment. Yet, as is the case with other areas of research, much remains to be done to develop further strategies to counteract the anti‐science attitudes that are now so prevalent globally.

Citizen science plant observations encode global trait patterns.

Global maps of plant functional traits are essential for studying the dynamics of the terrestrial biosphere, yet the spatial distribution of trait measurements remains sparse. With the increasing popularity of species identification apps, citizen scientists contribute to growing vegetation data collections. The question emerges whether such opportunistic citizen science data can help map plant functional traits globally. Here we show that we can map global trait patterns by complementing vascular plant observations from the global citizen science project iNaturalist with measurements from the plant trait database TRY. We evaluate these maps using sPlotOpen, a global collection of vegetation plot data. Our results show high correlations between the iNaturalist- and sPlotOpen-based maps of up to 0.69 (r) and higher correlations than to previously published trait maps. As citizen science data collections continue to grow, we can expect them to play a significant role in further improving maps of plant functional traits.

Postglacial species arrival and diversity buildup of northern ecosystems took millennia.

What drives ecosystem buildup, diversity, and stability? We assess species arrival and ecosystem changes across 16 millennia by combining regional-scale plant sedimentary ancient DNA from Fennoscandia with near-complete DNA and trait databases. We show that postglacial arrival time varies within and between plant growth forms. Further, arrival times were mainly predicted by adaptation to temperature, disturbance, and light. Major break points in ecological trait diversity were seen between 13.9 and 10.8 calibrated thousand years before the present (cal ka BP), as well as break point in functional diversity at 12.0 cal ka BP, shifting from a state of ecosystem buildup to a state where most habitat types and biotic ecosystem components were in place. Trait and functional diversity stabilized around 8 cal ka BP, after which both remained stable, although changes in climate took place and species inflow continued. Our ecosystem reconstruction indicates a millennial-scale time phase of formation to reach stable and resilient levels of diversity and functioning.

Avoiding growing pains in reproductive trait databases: the curse of dimensionality

AbstractAimReproductive output features prominently in many trait databases, but the metrics describing it vary and are often untethered to temporal and volumetric dimensions (e.g., fecundity per bout). The use of such ambiguous reproductive measures to make broad‐scale comparisons across taxonomic groups will be meaningful only if they show a 1:1 relationship with a reproductive measure that explicitly includes both a volumetric and a temporal component (i.e., reproductive mass per year). We sought to map the prevalence of ambiguous and explicit reproductive measures across taxa and to explore their relationships with one another to determine the cross‐compatibility and utility of reproductive metrics in trait databases.LocationGlobal.Time period1990–2021.Major taxa studiedWe searched for reproductive measures across all Metazoa and identified 19,785 vertebrate species (Chordata), and 440 invertebrate species (Arthropoda, Cnidaria or Mollusca).MethodsWe included 37 databases, from which we summarized the commonality of reproductive metrics across taxonomic groups. We also quantified scaling relationships between ambiguous reproductive traits (fecundity per bout, fecundity per year and reproductive mass per bout) and an explicit measure (reproductive mass per year) to assess their cross‐compatibility.ResultsMost species were missing at least one temporal or volumetric dimension of reproductive output, such that reproductive mass per year could be reconstructed for only 4,786 vertebrate species. Ambiguous reproductive measures were poor predictors of reproductive mass per year; in no instance did these measures scale at 1:1.Main conclusionsAmbiguous measures systematically misestimate reproductive mass per year. Until more data are collected, we suggest that researchers should use the clade‐specific scaling relationships provided here to convert ambiguous reproductive measures to reproductive mass per year.

Drought has inconsistent effects on seed trait composition despite their strong association with ecosystem drought sensitivity

Abstract Seeds provide the basis of genetic diversity in perennial grassland communities and their traits may influence ecosystem resistance to extreme drought. However, we know little about how drought effects the community functional composition of seed traits and the corresponding implications for ecosystem resistance to drought. We experimentally removed 66% of growing season precipitation for 4 years across five arid and semi‐arid grasslands in northern China and assessed how this multi‐year drought impacted community‐weighted means (CWMs) of seed traits, seed trait functional diversity and above‐ground net primary productivity (ANPP). Experimental drought had limited effects on CWM traits and the few effects that did occur varied by site and year. For three separate sites, and in different years, drought reduced seed length and phosphorus content but increased both seed and seed‐coat thickness. Additionally, drought led to increased seed functional evenness, divergence, dispersion and richness, but only in some sites, and mostly in later years following cumulative effects of water limitation. However, we observed a strong negative relationship between drought‐induced reductions in ANPP and CWMs of seed‐coat thickness, indicating that a high abundance of dominant species with thick seeds may increase ecosystem resistance to drought. Seed trait functional diversity was not significantly predictive of ANPP, providing little evidence for a diversity effect. Our results suggest that monitoring community composition with a focus on seed traits may provide a valuable indicator of ecosystem resistance to future droughts despite inconsistent responses of seed trait composition overall. This highlights the importance of developing a comprehensive seed and reproductive traits database for arid and semi‐arid grassland biomes. Read the free Plain Language Summary for this article on the Journal blog.

Sharkipedia: a curated open access database of shark and ray life history traits and abundance time-series

A curated database of shark and ray biological data is increasingly necessary both to support fisheries management and conservation efforts, and to test the generality of hypotheses of vertebrate macroecology and macroevolution. Sharks and rays are one of the most charismatic, evolutionary distinct, and threatened lineages of vertebrates, comprising around 1,250 species. To accelerate shark and ray conservation and science, we developed Sharkipedia as a curated open-source database and research initiative to make all published biological traits and population trends accessible to everyone. Sharkipedia hosts information on 58 life history traits from 274 sources, for 170 species, from 39 families, and 12 orders related to length (n = 9 traits), age (8), growth (12), reproduction (19), demography (5), and allometric relationships (5), as well as 871 population time-series from 202 species. Sharkipedia relies on the backbone taxonomy of the IUCN Red List and the bibliography of Shark-References. Sharkipedia has profound potential to support the rapidly growing data demands of fisheries management, international trade regulation as well as anchoring vertebrate macroecology and macroevolution.

Microclimate relationships of intraspecific trait variation in sub‐Arctic plants

Within‐species trait variation is a substantial part of plant functional diversity. However, this intraspecific trait variation (ITV) is rarely investigated in relation to a key characteristic of the Arctic and alpine ecosystems: fine‐scale microclimatic heterogeneity. Here, we quantified the influence of microclimate (soil moisture, snow and local temperatures) on plant functional traits, specifically on ITV. We focused on six widespread northern latitude vascular plant species, and measured four traits: plant height, leaf area, leaf dry matter content (LDMC) and specific leaf area (SLA). We related ITV to field and remotely sensed microclimate data from 150 study plots within six study grids. The grids were located within a 76‐m altitudinal belt in three environments: the tundra, tundra–forest ecotone and mountain birch forest in Kilpisjärvi, northwestern Finland. We compared the range of trait values between this local trait dataset (n = 5493) and global trait databases (n = 10 383). We found that information in the local dataset covers a relatively large portion of the trait ranges in global databases. The proportion varies among traits and species; the largest portion was 74% for variation in leaf area of Vaccinium uliginosum, and the lowest was 19% for LDMC of Betula nana. We found that ITV in height was mostly related to local temperatures, whereas SLA and LDMC were more related to soil moisture and snow conditions. However, species showed contrasting relationships with the microclimate drivers. We conclude that microclimate profoundly shapes ITV in northern latitude plants and that even a very compact geographic area can contain a large amount of ITV. The influence of the microclimatic conditions varies among functional traits and species, which indicates that plastic response or adaptive potential of the species to climate change may also vary across species, but that necessary variation may often be present within local plant populations.

Ecological Predictors of Zoonotic Vector Status Among Dermacentor Ticks (Acari: Ixodidae): A Trait-Based Approach.

Increasing incidence of tick-borne human diseases and geographic range expansion of tick vectors elevates the importance of research on characteristics of tick species that transmit pathogens. Despite their global distribution and role as vectors of pathogens such as Rickettsia spp., ticks in the genus Dermacentor Koch, 1844 (Acari: Ixodidae) have recently received less attention than ticks in the genus Ixodes Latreille, 1795 (Acari: Ixodidae). To address this knowledge gap, we compiled an extensive database of Dermacentor tick traits, including morphological characteristics, host range, and geographic distribution. Zoonotic vector status was determined by compiling information about zoonotic pathogens found in Dermacentor species derived from primary literature and data repositories. We trained a machine learning algorithm on this data set to assess which traits were the most important predictors of zoonotic vector status. Our model successfully classified vector species with ~84% accuracy (mean AUC) and identified two additional Dermacentor species as potential zoonotic vectors. Our results suggest that Dermacentor species that are most likely to be zoonotic vectors are broad ranging, both in terms of the range of hosts they infest and the range of ecoregions across which they are found, and also tend to have large hypostomes and be small-bodied as immature ticks. Beyond the patterns we observed, high spatial and species-level resolution of this new, synthetic dataset has the potential to support future analyses of public health relevance, including species distribution modeling and predictive analytics, to draw attention to emerging or newly identified Dermacentor species that warrant closer monitoring for zoonotic pathogens.

Succession of protistan functional traits is influenced by bloom timing

Surface ocean eukaryotic phytoplankton biogeography can be determined as chlorophyll-a using remote sensing techniques yet evaluating its community composition remains limited. Given our ability to track site-specific chlorophyll-a concentration, we tested which factors influenced protistan functional trait distribution, and whether the distributions can be inferred from bloom succession. Here we surveyed the Labrador Sea during spring over three consecutive years, sequenced 18S data over 15 stations and collected satellite-derived chlorophyll-a concentration from March to July for each year. We evaluated changes in distribution of taxonomic composition as well as the functional traits of protistan size, trophic strategy (defined as phototrophy, phagotrophy, and mixotrophy as capable of both), motility and dimethylsulfoxide or dimethylsulfoniopropionate production by building a functional trait database after an extensive literature review. More variability in the biogeography of protistan functional traits was explained across water masses, and among years than taxonomic composition and patterns in trait variability were more apparent when site-specific timing of peak chlorophyll-a was considered. We found that reconstructing bloom phenology using days before peak (DBP) chlorophyll explained a significant amount of variability in functional trait community structure that was previously attributed to water masses or years, suggesting that spatial and interannual variations can be explained by the sampling moment during succession. Approximately 30 days prior to peak, mixotrophy as a trophic strategy was replaced by phototrophic protists of typically larger size classes. Our work suggests DBP influences protistan community trait succession that could inform biogeochemical models, and likely acts a proxy for the onset of stratification.

The Australian National Species List steps up for biodiversity conservation

The Australian National Species List (AuNSL) will bring together authoritative national taxonomies and supporting nomenclatural data for flora, fauna, fungi and algae. These data enable biodiversity infrastructures, such as the Atlas of Living Australia, to store information about taxa against a standard, permanently resolvable taxonomy, and to create linkages between them. The Biodiversity Data Repository (BDR) is a new Australian government infrastructure supporting environmental assessments under Australia's Environment Protection and Biodiversity Conservation Act. The BDR will bring together biodiversity data assets from a range of sources and enable decision making to be based on a more holistic view of taxa in Australia. To achieve its objectives, the BDR requires the ability to align disparate taxonomies to a national standard. To support the BDR we have restructured and consolidated the constituent datasets of the AuNSL and added a GraphQL interface from which we can provide machine access to the full suite of taxonomic and nomenclatural entities in the data and the linkages between them. Currently we provide a simple name check service for aligning supplied names with the standard AuNSL taxonomy and a full taxonomic backbone extract as a SKOS concept scheme expressed in JSON-LD. We are working towards an expanded set of taxonomic and nomenclatural services and a more generalised and complete graph of the AuNSL taxonomy, which can serve an increasing number of initiatives including the Australian Traits database (AusTraits), the Australian National DNA Library, and sensitive species data exchange mechanisms.

IKNOW: A platform for knowledge graph construction for biodiversity

Nowadays, more and more biodiversity datasets containing observational and experimental data are collected and produced by different projects. In order to answer the fundamental questions of biodiversity research, these data need to be integrated for joint analyses. However, to date, too often, these data remain isolated in silos. Both in academia and industry, Knowledge Graphs (KGs) are widely regarded as a promising approach to overcome issues of data silos and lack of common understanding of data (Fensel and Şimşek 2020). KGs are graph-structured knowledge bases that store factual information in the form of structured relationships between entities, like “tree_species has_trait average_SLA” or “nutans is_observed_in SCH_Location" (Hogan et al. 2021). In our context, entities could be, e.g., abstract concepts like a kingdom, a species, or a trait, or a concrete specimen of a species. Example relationships could be "co-occurs" or, "possesses-trait". KGs for biodiversity have been proposed by Page 2019 and have also been the topic at prior TDWG conferences *1 (Page 2021). However, to date, uptake of this concept in the community has been rather slow (Sachs et al. 2019). We argue that this is at least partially due to the high effort and expertise required in developing and managing such KGs. Therefore, in our ongoing project, iKNOW (Babalou et al. 2021), we aim to provide a toolbox for reproducible KG creation. While iKNOW is still in an early stage, we aim to make this platform open-source and freely available to the biodiversity community. Thus, it can significantly contribute to making biodiversity data widely available, easily discoverable, and integratable. For now, we focus on tabular datasets resulting from biodiversity observation or sampling events or experiments. Given such a dataset, iKNOW will support its transformation into (subject, predicate, object) triples in the RDF standard (Resource Description Framework). Every uploaded dataset will be considered as a subgraph of the main KG in iKNOW. If required, data can be cleaned. After that, the entities and relationships among them should be extracted. For that, a user will be able select one of the existing semi-automatic tools available on our platform (e.g., JenTab (Abdelmageed and Schindler 2020)). The entities in this step can be linked to respective global identifiers in Wikidata, GBIF, the Global Biodiversity Information Facility, or any other user-selected knowledge resource. In the next step, (subject, predicate, object) triples based on the extracted information from the previous steps will be created. After these processes, the generated sub-KG can be used directly. However, one can take further steps such as: Triple Augmentation (generate new triples and extra relations to ease KG completion), Schema Refinement (refine the schema, e.g., via logical reasoning for the KG completion and correctness), Quality Checking (check the quality of the generated sub-KG), and Query Building (create customized SPARQL queries for the generated KG). iKNOW will include a wide range of functionalities for creating, accessing, querying, visualizing, updating, reproducing, and tracking the provenance of KGs. The reproducibility of such a creation is essential to strengthening the establishment of open science practices in the biodiversity domain. Thus, all information regarding the user-selected tools with parameters and settings, along with the initial dataset and intermediate results, will be saved in every step of our platform. With the help of this, users can redo the previous steps. Moreover, this enables us to track the provenance of the created KG. The iKNOW project is a joint effort by computer scientists and domain experts from the German Centre for Integrative Biodiversity Research (iDiv). As a showcase, we aim to create a KG of plant-related data sources at iDiv. These include, among others: TRY (the plant trait database) (Kattge and DÍaz 2011), sPlot (the database about global patterns of taxonomic, functional, and phylogenetic diversity) (Bruelheide and Dengler 2019), and PhenObs (the dataset of the global network of botanical gardens monitoring the impacts of climate change on the phenology of herbaceous plant species) (Nordt and Hensen 2021), LCVP, the Leipzig Catalogue of Vascular Plants, (Freiberg and Winter 2020), and many others. The resulting KG will serve as a discovery tool for biodiversity data and provide a robust infrastructure for managing biodiversity knowledge. From the biodiversity research perspective, iKNOW will contribute to creating a dataset following the Linked Open Data principles by interlinking to cross-domain and specific-domain KGs. From the computer science perspective, iKNOW will contribute to developing tools for dynamic, low-effort creation of reproducible knowledge graphs.

Preface: Functional biogeography in Japanese cedar

Preface: Functional biogeography in Japanese cedar

Using functional traits to identify conservation priorities for the world's crocodylians

AbstractOver half of all crocodylians are threatened with extinction, with many species considered to be functionally extinct throughout their historical ranges. How such losses impact crocodylian functional diversity (FD) and its conservation is poorly understood, but can be investigated using measurable traits. Where such information is unavailable, phylogenetic diversity (PD) has been proposed as an effective strategy to capture FD, but this assumption is not well tested.We constructed a global trait database for 28 extant crocodylians, and quantified their FD, distinctiveness and groupings. Functionally distinctive crocodylians include the most and least evolutionarily distinct species, likely because unusual trait values and combinations can be produced by both evolutionary isolation and evolutionarily recent adaptive radiation. We identified four functional groups of crocodylians, within which species have similar ecological roles. Highly distinctive species, such as the gharial, fit less well into functional groups.We combined functional distinctiveness (FUD) and threat ranking scores to prioritise species for conservation. The metric is termed Ecologically Distinct and Globally Endangered (EcoDGE), and we tested how well it operates to preserve crocodylian FD among extant Crocodylia. Under current extinction scenarios, 32%–38% of crocodylian FD might be lost within 100 years. Losses increase to 48% if all threatened species go extinct, with Asia identified as a hotspot of threatened FD in crocodylians. Highly threatened distinctive species lead this extinction scenario, exacerbated by clusters of species sharing traits linked to high extinction risk. These traits include habitat specialism and lower reproductive investment; in contrast, species that tolerate climate extremes are more resilient.Prioritising at‐risk species based on FUD and threat status appears to be an effective way to conserve present‐day crocodylian diversity. Conservation prioritisation based on the EcoDGE metric performed well to minimise projected losses in FD. Among extant crocodylians, FD losses are projected when high diversity overlaps with high extrinsic threats.We then examined the utility of PD‐based measures as surrogates for FD conservation, to better understand the advantages and drawbacks of such substitutions. A PD‐based measure such as the Evolutionarily Distinct and Globally Endangered metric provided an effective tool to capture FD in our tests.Read the freePlain Language Summaryfor this article on the Journal blog.

Floral and reproductive traits are an independent dimension within the plant economic spectrum of temperate central Europe.

Major dimensions of plant ecological strategies have been widely studied bringing forward the concept of 'economic spectra' of plants. Sexual reproductive traits, 'floral traits', have been largely neglected in this context, despite their strong link to fitness. Here, we aimed at integrating floral traits into the dimensionality of plant form and function so far dominated by vegetative traits. We used principal component analyses and constructed trait networks to assess the correlation structure of leaf, belowground, plant size-related, and floral traits. We studied forbs within two independent datasets; one compiled from central European trait databases and one sampled in the Austrian Alps. Floral traits defined the second dimension of trait variability within both datasets, while plant size determined the first dimension. Floral traits were largely independent from the leaf economic spectrum. Flower size, however, positively scaled with plant size and leaf size. Mating system was the most well-connected trait across modules of plant tissue/organ types. The independence of floral traits was consistent also after accounting for phylogenetic relationships between species. Floral traits explained a unique part of the variation in plant form and function and thus, likely play a distinctive ecological role within the whole plant economic spectrum.

Improving measurements of the falling trajectory and terminal velocity of wind-dispersed seeds.

Seed dispersal by wind is one of the most important dispersal mechanisms in plants. The key seed trait affecting seed dispersal by wind is the effective terminal velocity (hereafter “terminal velocity”, V t ), the maximum falling speed of a seed in still air. Accurate estimates of V t are crucial for predicting intra‐ and interspecific variation in seed dispersal ability. However, existing methods produce biased estimates of V t for slow‐ or fast‐falling seeds, fragile seeds, and seeds with complex falling trajectories. We present a new video‐based method that estimates the falling trajectory and V t of wind‐dispersed seeds. The design involves a mirror that enables a camera to simultaneously record a falling seed from two perspectives. Automated image analysis then determines three‐dimensional seed trajectories at high temporal resolution. To these trajectories, we fit a physical model of free fall with air resistance to estimate V t . We validated this method by comparing the estimated V t of spheres of different diameters and materials to theoretical expectations and by comparing the estimated V t of seeds to measurements in a vertical wind tunnel. V t estimates closely match theoretical expectations for spheres and vertical wind tunnel measurements for seeds. However, our V t estimates for fast‐falling seeds are markedly higher than those in an existing trait database. This discrepancy seems to arise because previous estimates inadequately accounted for seed acceleration. The presented method yields accurate, efficient, and affordable estimates of the three‐dimensional falling trajectory and terminal velocity for a wide range of seed types. The method should thus advance the understanding and prediction of wind‐driven seed dispersal.