Categorical Traits Research Articles

Utilisation of traditional ecological plant classification systems to explain major dimensions of trait variation in herb layer of East Carpathians forests

Among researchers, there is constant interest in using ecologically similar plant groups to analyse the principles of forest vegetation functioning. However, these groups are more often defined a priori with a certain dose of subjectivity and low repeatability. We expected, based on widely documented, categorical traits, that it is possible to distinguish a more objective, simple, universal plant group set for herb layer – an important component for temperate deciduous forest ecosystems’ functioning. These plant groups would reflect well the variation in key traits (economic, size and reproductive traits) which reflect the foremost dimensions of the ecological variation between herb species. Because this variation is interpreted as adaptation to the environmental conditions, we thus assumed its importance in understanding the principles of vegetation functioning in changing forest habitats. We proposed the plant group classification method based on categorical traits included in traditional ecological plant classification systems. We established that categorical trait-based plant groups align well with key trait-based classified groups of species. Moreover, categorical trait-based plant groups had high explanatory power for variation in key traits. We found that categorical trait-based plant groups align well with two main global axes of trait variation connected with economic and size related traits. Because the proposed categorical traits are very simple to access and available for most plant species, our results indicate that categorical trait-based plant groups may be widely used to explain the principles of forest vegetation functioning, especially in monitoring and explaining changes in vegetation.

Effect of housing system during pregnancy on reproductive parameters of sows

ABSTRACT The aim of this study was to evaluate the reproductive performance of sows in individual stalls (Stall) or group-housed into groups on days 3 to 5 (Pen5) or 38 to 42 (Pen42) after breeding. The reproductive data was collected from the operating system of the farm establishing the average of the weekly performances of the sows that gave birth, for four years, except for the Pen5 system, which was evaluated for three years. Statistical analyses were performed using SAS®, using MIXED (for quantitative traits), NPAR1WAY (for categorical traits) and LOGISTIC (binomial traits) procedures, using sows as a repeated measure. Sows in Stall system had piglets with higher birth weight them sows in the group-housed system (P<0.05), however the piglets born alive, total piglets weaned, average litter weight, and duration of farrowing were lower in this system than in the group-housed (P<0.0001). There was no difference between Pen5 and Stall systems for gestation period and mummified piglets. The Pen42 system had a higher percentage of mummified piglets and a shorter gestation period, when compared Pen5 and Stall systems (P<0.0001), and similar results to the Pen5 system for duration of farrowing, piglets born alive, stillbirths, total piglets weaned, average litter weight and birth weight (P<0.0001).

Using Genome-Wide Predictions to Assess the Phenotypic Variation of a Barley (Hordeum sp.) Gene Bank Collection for Important Agronomic Traits and Passport Information

Genome-wide predictions are a powerful tool for predicting trait performance. Against this backdrop we aimed to evaluate the potential and limitations of genome-wide predictions to inform the barley collection of the Federal ex situ Genebank for Agricultural and Horticultural Crops with phenotypic data on complex traits including flowering time, plant height, thousand grain weight, as well as on growth habit and row type. We used previously published sequence data, providing information on 306,049 high-quality SNPs for 20,454 barley accessions. The prediction abilities of the two unordered categorical traits row type and growth type as well as the quantitative traits flowering time, plant height and thousand grain weight were investigated using different cross validation scenarios. Our results demonstrate that the unordered categorical traits can be predicted with high precision. In this way genome-wide prediction can be routinely deployed to extract information pertinent to the taxonomic status of gene bank accessions. In addition, the three quantitative traits were also predicted with high precision, thereby increasing the amount of information available for genotyped but not phenotyped accessions. Deeply phenotyped core collections, such as the barley 1,000 core set of the IPK Gatersleben, are a promising training population to calibrate genome-wide prediction models. Consequently, genome-wide predictions can substantially contribute to increase the attractiveness of gene bank collections and help evolve gene banks into bio-digital resource centers.

Antiquity and fundamental processes of the antler cycle in Cervidae (Mammalia)

The origins of the regenerative nature of antlers, being branched and deciduous apophyseal appendages of frontal bones of cervid artiodactyls, have long been associated with permanent evolutionary precursors. In this study, we provide novel insight into growth modes of evolutionary early antlers. We analysed a total of 34 early antlers affiliated to ten species, including the oldest known, dating from the early and middle Miocene (approx. 18 to 12 million years old) of Europe. Our findings provide empirical data from the fossil record to demonstrate that growth patterns and a regular cycle of necrosis, abscission and regeneration are consistent with data from modern antlers. The diverse histological analyses indicate that primary processes and mechanisms of the modern antler cycle were not gradually acquired during evolution, but were fundamental from the earliest record of antler evolution and, hence, explanations why deer shed antlers have to be rooted in basic histogenetic mechanisms. The previous interpretation that proximal circular protuberances, burrs, are the categorical traits for ephemerality is refuted.

Towards a more balanced combination of multiple traits when computing functional differences between species

Abstract Functional trait differences between species are key drivers of community assembly and ecosystem functioning. Quantifying these differences routinely requires using approaches like the Gower distance to combine various types of traits into a multi‐trait dissimilarity. Without special care, the Gower distance can however produce a multi‐trait dissimilarity with a disproportional contribution of certain traits, particularly categorical traits and bundle of correlated traits reflecting similar ecological functions. These effects persist even after applying multivariate analyses traditionally used to reduce trait dimensionality. We propose the ‘gawdis’ R function, and corresponding package, to produce multi‐trait dissimilarity with more uniform contributions of different traits, including fuzzy coded ones. The approach is based on minimizing the differences in the correlation between the dissimilarity of each trait, or groups of traits, and the multi‐trait dissimilarity. This is done using either an analytical or a numerical solution, both available in the function. Properly taking into account the contribution of multiple traits into multi‐trait dissimilarity is key for interpreting the ecological effects of complex species differences. The gawdis r package in CRAN can be further applied to improve equitability in distance‐based measures in other field of research, such as social sciences or marketing surveys, which routinely analyse mixed type data.

Genome-enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods.

This study aimed to assess the predictive ability of different machine learning (ML) methods for genomic prediction of reproductive traits in Nellore cattle. The studied traits were age at first calving (AFC), scrotal circumference (SC), early pregnancy (EP) and stayability (STAY). The numbers of genotyped animals and SNP markers available were 2342 and 321419 (AFC), 4671 and 309486 (SC), 2681 and 319619 (STAY) and 3356 and 319108 (EP). Predictive ability of support vector regression (SVR), Bayesian regularized artificial neural network (BRANN) and random forest (RF) were compared with results obtained using parametric models (genomic best linear unbiased predictor, GBLUP, and Bayesian least absolute shrinkage and selection operator, BLASSO). A 5-fold cross-validation strategy was performed and the average prediction accuracy (ACC) and mean squared errors (MSE) were computed. The ACC was defined as the linear correlation between predicted and observed breeding values for categorical traits (EP and STAY) and as the correlation between predicted and observed adjusted phenotypes divided by the square root of the estimated heritability for continuous traits (AFC and SC). The average ACC varied from low to moderate depending on the trait and model under consideration, ranging between 0.56 and 0.63 (AFC), 0.27 and 0.36 (SC), 0.57 and 0.67 (EP), and 0.52 and 0.62 (STAY). SVR provided slightly better accuracies than the parametric models for all traits, increasing the prediction accuracy for AFC to around 6.3 and 4.8% compared with GBLUP and BLASSO respectively. Likewise, there was an increase of 8.3% for SC, 4.5% for EP and 4.8% for STAY, comparing SVR with both GBLUP and BLASSO. In contrast, the RF and BRANN did not present competitive predictive ability compared with the parametric models. The results indicate that SVR is a suitable method for genome-enabled prediction of reproductive traits in Nellore cattle. Further, the optimal kernel bandwidth parameter in the SVR model was trait-dependent, thus, a fine-tuning for this hyper-parameter in the training phase is crucial.

Using a space-for-time approach to select the best biodiversity-based indicators to assess the effects of aridity on Mediterranean drylands

Abstract Mediterranean drylands are particularly vulnerable to predicted increases in aridity which are expected to have negative consequences for biodiversity. To understand the effects of climate change on ecosystems, a framework for the selection of indicators based on the essential biodiversity variables (EBV) was proposed. In this framework, a functional approach has been suggested because functional traits have shown to be sensitive to small-scale environmental changes. Additionally, functional traits are also associated with ecosystem-limiting processes. In this context, we used ants as ecological indicators, as they are functionally important and respond in a measurable way to environmental changes. We identify which biodiversity-based indicators (e.g., taxonomic, single-trait and multi-trait indices) help track changes in Mediterranean drylands; for this, we used a space-for-time substitution climatic gradient in the western Mediterranean. Ants were sampled along an aridity gradient and identified to species level. Four continuous and seven categorical traits were measured or retrieved from literature. Continuous traits included Weber’s length, which is indicative for body length, head length, eye length and femur length; categorical traits were diet, behavioral dominance, daily activity, nest preference, mound presence, worker polymorphism and foraging strategy. We calculated taxonomic, functional structure and single- and multi-trait functional diversity indices and correlated them with aridity. We found that ant taxonomic and multi-trait functional diversity were maintained along the aridity gradient. Despite maintenance of species and functional diversity along the gradient, ant functional structure responded to aridity with increases in mean trait values of Weber’s length, eye length and femur length in the drier part of the gradient. Under wetter conditions, we found the highest proportion of ants with a seed-based diet, reflecting a potential increase in resource quantity. We observed a change in foraging strategy from group to individual as aridity increased. In conclusion, with a space-for-time substitution climatic gradient, this study shows the potential role of aridity as an environmental driver of ant trait values. These results highlight the value of ants and functional traits as indicators to track the effects of climate change on ecosystems. Finally, this study represents a starting point to monitor important species traits in the context of EBV and to use them as indicators to track the effects of aridity on Mediterranean dryland ecosystems.

Mediterranean nekton traits: distribution, relationships and significance for marine ecology monitoring and management.

Biological traits are increasingly used in order to study aspects of ecology as they are related to the organisms’ fitness. Here we analyze a dataset of 23 traits regarding the life cycle, distribution, ecology and behavior of 235 nektonic species of the Mediterranean Sea in order to evaluate the distribution of traits, identify rare ones, detect relationships between trait pairs and identify species functional groups. Trait relationships were tested using correlation and non-linear regression for continuous traits, parametric and non-parametric inference tests for pairs of continuous-categorical traits and cooccurrence testing for categorical traits. The findings have significant implications concerning the potential effects of climate change (e.g., through the relationships of the trait of optimal temperature), fisheries or habitat loss (from the relationships of traits related to tolerance ranges). Furthermore, some unexpected relationships are documented, like the inversely proportional relationship between longevity and age at maturity as a percentage of life span. Associations between functional traits show affinities derived from phylogenetic constraints or life strategies; however, relationships among functional and ecological traits can indicate the potential environmental filtering that acts on functional traits. In total, 18 functional groups were identified by Hill-Smith ordination and hierarchical clustering and were characterized by their dominant traits. For the assessment of the results, we first evaluate the importance of each trait at the level of population, community, ecosystem and landscape and then propose the traits that should be monitored for the regulation and resilience of ecosystem functioning and the management of the marine ecosystems.

Reef fish functional composition and metrics reveal spatial differences in three protected islands in the Eastern Pacific

Reef fish assemblages in the Eastern Pacific (EP) represent an interesting system to understand how areas with lower diversity respond to multiple factors and their effect on ecosystem functions and services. Among the multiple approaches that have emerged, the evaluation of functional metrics provides an initial comprehension of these relationships. In this context, to better understand reef fish variability in the EP, we evaluated spatial differences in ecological metrics, the composition of fish assemblages, and their relationship with habitat structure in coral communities at 3 islands in Mexico (Marietas, Isabel, and Cleofas). To include a functional approach, we created a functional entity (FE) matrix using species abundance and 6 categorical functional traits; specifically, we calculated ecological metrics that reflect the representation or under-representation of species in the functions or FEs (redundancy and vulnerability) and the rarity in FEs and species and their relationship with habitat structure. Overall, most of the fish FEs in the EP were represented by 1 species (i.e. high vulnerability and low functional redundancy). Despite the low redundancy recorded in the islands, reef fish performed multiple key functions; however, many functions remained rare. Furthermore, both metrics and fish composition showed high variability among sites and islands, but this variability was only partially explained by a few variables of habitat structure (i.e. rugosity). These results, in combination with the unique characteristics of coral communities in the EP, highlight the need to identify the drivers of fish assemblages and their effect on the ecosystem processes and services in order to implement unique management strategies for each island.

Reliability analysis of fish traits reveals discrepancies among databases

Abstract Trait‐based approaches are commonly used in ecology to understand the relationship between biodiversity and ecosystem functioning, environmental filtering or biotic responses to anthropogenic perturbations. However, little is known about the reliability of assigned traits and the consistency of trait information among different databases currently in use. Using 99 native and alien Iberian inland fish species, we investigated a total of 27 biological and ecological traits for their consistency among 19 different databases and identified less reliable traits, that is, traits with high disagreement among databases. Specifically, we used generalised linear models and inter‐rater reliability statistics (Krippendorff's α) to test for differences in trait values among databases. We also identified well‐studied versus data‐deficient traits and species. Our results show notable discrepancies and low reliability for several biological and ecological traits such as microhabitat preference, omnivory, invertivory, rheophily, and limnophily. Least reliable traits were mainly categorical (rather than continuous) and established by expert judgment and without a clear definition or a common methodology. Interestingly, categorical traits such as rheophily or limnophily, which showed significantly lower reliability, concurrently showed higher data availability and use than continuously scaled traits. Such uncertainties in trait assignments could affect bioassessment and other ecological analyses. Species with smaller distributional ranges and those that have been described more recently, presented lower coverage and data availability in trait databases. We encourage further standardisation of fish trait measurement protocols to help improve the robust application of bioassessment indices and trait‐based approaches.

Estimation of heritabilities of disease resistance to Edwardsiella tarda and genetic correlations between resistance and growth traits in Chinese tongue sole (Cynoglossus semilaevis)

Chinese tongue sole (Cynoglossus semilaevis) is an important marine flatfish which is widely cultured in coastal areas in China. Infectious bacterial diseases such as Edwardsiella tarda imposed serious threats to this species. A potential strategy to prevent this disease is to select resistance strains. The aim of the present work was to estimate the genetic variation of disease resistance to E. tarda and to evaluate the genetic correlations between resistance traits and growth traits. Three types of models were fitted by using different trait definitions (binary, continuous and categorical). After a 9-day challenge test, the overall survival was 75.4% (ranging from 6.4% to 100% in families), and at test day 6, the overall survival was 50.7%. We set test day 6 and 9 as cut-off point times respectively. The heritabilities of survival traits were ranging from 0.10 to 0.36. Considerably higher heritability values were obtained at day 6 than at day 9, regardless of which model or trait definition used (except Trait 2 in LIN). The genetic correlations between disease resistance traits and growth traits (i.e. body weight and total length) were low and not significant from zero (−0.12–0.24). There is a substantial re-ranking of families when defined resistance as categorical and continuous traits compared to binary trait. These results confirm the existence of genetic variation for resistance against E. tarda and weak genetic correlations indicate that joint genetic improvement of E. tarda resistance and growth is scarcely available.

Addressing score comparability in diagnostic classification models: an observed-score equating and linking approach

The purpose of this study is to revamp and examine the observed-score approach for equating scores under diagnostic classification models (DCMs). The observed-score approach was adapted to accommodate the categorical latent traits and scores, a unique property of DCMs. Three simulation studies, each corresponding to a data collection design, were conducted to evaluate the amount of equating error and the improvement in score comparability with the observed-score approach. Findings indicate that (a) DCM scores are robust to form differences when high-quality items are used, and (b) the observed-score approach shows promise for yielding a small amount of equating error and increasing classification accuracy under small sample size conditions.

Modeling honey yield, defensive and swarming behaviors of Italian honey bees (Apis mellifera ligustica) using linear-threshold approaches

BackgroundGenetic improvement of honey bees is more difficult compared to other livestock, due to the very different reproductive behavior. Estimation of breeding values requires specific adjustment and the use of sires in the pedigree is only possible when mating of queens and drones is strictly controlled. In the breeding program of the National Registry for Italian Queen Breeders and Bee Producers the paternal contribution is mostly unknown. As stronger modeling may compensate for the lack of pedigree information, we tested two models that differed in the way the direct and maternal effects were considered. The two models were tested using 4003 records for honey yield, defensive and swarming behaviors of Italian honey bee queens produced between 2002 and 2014. The first model accounted for the direct genetic effect of worker bees and the genetic maternal effect of the queen, whereas model 2 considered the direct genetic effect of the queen without maternal effect. The analyses were performed by linear (honey production) and threshold (defensive and swarming behavior) single-trait models; estimated genetic correlations among traits were obtained by a three-trait linear-threshold model.ResultsFor all traits, the highest predictability (correlation between breeding values estimated with and without performance records) was obtained with model 2, where direct genetic effect of queens was considered. With this model, heritability estimates were 0.26 for honey yield, 0.36 for defensive behavior, and 0.34 for swarming behavior. Multi-trait estimation resulted in similar or higher heritability estimates for all traits. A low, positive genetic correlation (0.19) was found between honey yield and defensive behavior, whereas the genetic correlation between honey yield and swarming behavior was moderate (0.41). A strong, positive genetic correlation was found between defensive and swarming behaviors (0.62). Predictability for multi-trait evaluations was higher for honey yield (0.46) and defensive behavior (0.30) but almost identical for swarming behavior (0.45) compared to corresponding single-trait predictability.ConclusionsMulti-trait evaluation using a model that accounts for the direct genetic effect of queen was the best approach for breeding value estimation of Italian honey bees. The results suggest a new direction for selection of linear and categorical traits in breeding programs where drone origin is unknown.

ARE LICHEN GROWTH FORM CATEGORIES SUPPORTED BY CONTINUOUS FUNCTIONAL TRAITS: WATER-HOLDING CAPACITY AND SPECIFIC THALLUS MASS?

The focus of community ecology has shifted from the description of taxonomic composition towards an understanding of community assembly based on species’ ‘functional traits’. The functional trait approach is well developed for vascular plants, utilising variability of continuous phenotypic characters that affect ecological fitness, such as specific leaf area, tissue nitrogen concentration or seed mass, to explain community structure. In contrast, community assembly studies for poikilohydric cryptogamic plants and fungi, such as lichens, remain focused on broad categorical traits such as growth form difference: fruticose, foliose or crustose. This study examined intra- and interspecific variability for two highly promising continuous phenotypic measurements that affect lichen physiology and ecological fitness: water-holding capacity (WHC) and specific thallus mass (STM). Values for WHC and STM were compared within and among species, and within and among key macrolichen growth forms (fruticose and green-algal and cyanolichen foliose species), asking whether these widely used categories adequately differentiate the continuous variables (WHC and STM). We show large intra- and interspecific variability that does not map satisfactorily onto growth form categories, and on this basis provide recommendations and caveats in the future use of lichen functional traits.

Molecular and Phenotypic Diversity of Traditional European Plum (Prunus domestica L.) Germplasm of Southern Italy

The European plum (Prunus domestica L.) is a worldwide distributed tree species. Italy has an ample number of traditional varieties, but many are neglected and at risk of extinction. This germplasm is still cultivated in rural areas in spite of the EU-28 crisis of the stone fruit sector. Traditional European plum varieties remain poorly characterized, strongly limiting their promotion in local markets, use for farm diversification, and exploitation for local gastronomic products. In this study, we carried out an investigation of the morphological and genetic diversity present in an ex-situ collection of 29 traditional varieties of P. domestica of the Campania region (Southern Italy). The combination of five continuous and five categorical fruit traits allowed us to phenotypically distinguish all the varieties. Similarly, the Simple Sequence Repeats (SSRs) employed (five genomic and five deriving from Expressed Sequence Tags) identified a unique molecular profile for each variety. Moreover, the data indicated that the phenotypic and molecular investigations provided different clustering, suggesting that the two analyses sampled different sources of diversity. The number and the distribution of the scored phenotypes as well as the indices of genetic diversity imply the presence of a wide-ranging variation, which may sustain the development of high-value, niche market products. Our work provided evidence that the implementation of measures for a combination of ex-situ and on-farm conservation of traditional European plum varieties should be preferred to avoid the loss of an ample diversity.

Trait-based analysis of the human skin microbiome

BackgroundThe past decade of microbiome research has concentrated on cataloging the diversity of taxa in different environments. The next decade is poised to focus on microbial traits and function. Most existing methods for doing this perform pathway analysis using reference databases. This has both benefits and drawbacks. Function can go undetected if reference databases are coarse-grained or incomplete. Likewise, detection of a pathway does not guarantee expression of the associated function. Finally, function cannot be connected to specific microbial constituents, making it difficult to ascertain the types of organisms exhibiting particular traits—something that is important for understanding microbial success in specific environments. A complementary approach to pathway analysis is to use the wealth of microbial trait information collected over years of lab-based, culture experiments.MethodsHere, we use journal articles and Bergey’s Manual of Systematic Bacteriology to develop a trait-based database for 971 human skin bacterial taxa. We then use this database to examine functional traits that are over/underrepresented among skin taxa. Specifically, we focus on three trait classes—binary, categorical, and quantitative—and compare trait values among skin taxa and microbial taxa more broadly. We compare binary traits using a Chi-square test, categorical traits using randomization trials, and quantitative traits using a nonparametric relative effects test based on global rankings using Tukey contrasts.ResultsWe find a number of traits that are over/underrepresented within the human skin microbiome. For example, spore formation, acid phosphatase, alkaline phosphatase, pigment production, catalase, and oxidase are all less common among skin taxa. As well, skin bacteria are less likely to be aerobic, favoring, instead, a facultative strategy. They are also less likely to exhibit gliding motility, less likely to be spirillum or rod-shaped, and less likely to grow in chains. Finally, skin bacteria have more difficulty at high pH, prefer warmer temperatures, and are much less resilient to hypotonic conditions.ConclusionsOur analysis shows how an approach that relies on information from culture experiments can both support findings from pathway analysis, and also generate new insights into the structuring principles of microbial communities.

Quantitative Trait Loci Controlling Lodging Resistance and other Important Agronomic Traits in Dry Field Peas

ABSTRACTTo discover the quantitative trait loci (QTLs) influencing lodging resistance and other agronomic traits in pea (Pisum sativum L.), a recombinant inbred line (RIL) population was created from a cross between the variety Delta and a breeding line from a complex cross. The RIL population was grown for five site years, and phenotypic data were collected for 13 quantitative traits and seven categorical traits. Genotypic data were derived from single nucleotide polymorphism (SNP), simple sequence repeat (SSR), and cleaved amplified polymorphic sequence (CAPS) markers. A layered QTL analysis identified seven specific regions where QTLs for these traits colocated. Mendel's height gene (Le) and the semi‐leafless mutation (Af) together accounted for the majority of the variation in lodging in the pea RIL population. All of the seven regions influenced stem thickness characteristics, but not all regions were associated with lodging. The regions near the high response to photoperiod (Hr) gene, and Mendel's flower color locus (A) putatively influenced yield. Both the region near Hr and a region on upper Linkage Group (LG) I were very important for seed size. Since data were collected on 13 different traits, pleiotropic effects could also be studied, giving a unique multi‐trait insight into the effects of these QTLs.

GIFT – A Global Inventory of Floras and Traits for macroecology and biogeography

AbstractAimTo understand how functional traits and evolutionary history shape the geographic distribution of plant life on Earth, we need to integrate high‐quality and global‐scale distribution data with functional and phylogenetic information. Large‐scale distribution data for plants are, however, often restricted to either certain taxonomic groups or geographic regions. Range maps only exist for a small subset of all plant species and digitally available point‐occurrence information is biased both geographically and taxonomically. Floras and checklists represent an alternative, yet rarely used potential source of information. They contain highly curated information about the species composition of a clearly defined area, and together virtually cover the entire global land surface. Here, we report on our recent efforts to mobilize this information for macroecological and biogeographical analyses in the GIFT database, the Global Inventory of Floras and Traits.LocationGlobal.TaxonLand plants (Embryophyta).MethodsGIFT integrates plant distributions from regional Floras and checklists with functional traits, phylogenetic information, and region‐level geographic, environmental and socio‐economic data. It contains information about the floristic status (native, endemic, alien and naturalized) and takes advantage of the wealth of trait information in the regional Floras, complemented by data from global trait databases.ResultsGIFT 1.0 holds species lists for 2,893 regions across the whole globe including ~315,000 taxonomically standardized species names (i.e. c. 80% of all known land plant species) and ~3 million species‐by‐region occurrences. Based on a hierarchical and taxonomical derivation scheme, GIFT contains information for 83 functional traits and more than 2.3 million trait‐by‐species combinations and achieves unprecedented coverage in categorical traits such as woodiness (~233,000 spp.) or growth form (~213,000 spp.).Main conclusionsHere, we present the structure, content and automated workflows of GIFT and a corresponding web‐interface (http://gift.uni-goettingen.de) as proof of concept for the feasibility and potential of mobilizing aggregated biodiversity data for global macroecological and biogeographical research.

Beyond guilds: the promise of continuous traits for mammalian functional diversity

Studies on mammalian community ecology and biogeography are increasingly using functional diversity to advance our understanding of how diversity is maintained and how it varies across space and over time. Functional diversity quantifies the range and prevalence of species traits in an assemblage and provides a means of linking patterns of diversity to the ecological processes that generate them. Measuring the most appropriate and informative traits is critically important, yet the variety of traits applied to mammalian systems has been relatively limited and most are categorical rather than continuous. As a result, finer variation among species is often overlooked, which may obscure more detailed and accurate conclusions, particularly for studies on smaller species pools. We seek to improve the quality of trait information for mammals by investigating the value of three continuous ecomorphological traits: the relative medullary thickness of the kidney (an indicator of urine concentrating ability) as a metric of habitat moisture requirements, hair density as a measure of temperature limitations, and an integrated suite of cranial and dental measurements as an indicator of dietary specialization. We measured these traits for the small mammal assemblage of the Great Basin ecoregion using fluid-preserved and skeletal specimens housed in natural history collections and accounted for phylogenetic and allometric relationships. Kidney morphology, hair density, and craniodental morphology each exhibited phylogenetic signal and revealed ecologically meaningful variation that is overlooked by associated categorical traits. The greater resolution of these continuous trait data will facilitate more refined assessments of functional diversity and improve efforts to test ecological theories or track responses to environmental change.

Spatial Congruence or Mismatch Between Phylogenetic and Functional Structure of Seed Plants Along a Tropical Elevational Gradient: Different Traits Have Different Patterns

Compared with species richness, few studies have investigated the patterns and the relationship of phylogenetic and functional structure along elevation gradients. Here, we used general additive models (GAM) to determine the trends of species richness (SR), phylogenetic and functional diversity (PD and FD), phylogenetic structure (NRI), and functional structure (NFRI) of seed plants along the elevation gradient in a tropical mountain of Africa. We measured growth form, fruit type, maximum height, and maximum leaf size of each species, calculated the phylogenetic signal of each trait, and tested the Pearson correlation coefficients between NRI and NFRI of each trait. Our results showed that SR, PD, and FD decrease gradually along the elevation gradient. NRI exhibited a fluctuating pattern along the elevation gradient, while NFRI of the four functional traits showed noticeably different patterns. We concluded that the relationship between phylogenetic and functional structure in different functional traits could be congruent or mismatch along the elevation gradient. Compared with relatively conservative categorical traits (e.g., growth form and fruit type), continuous traits (e.g., height and leaf size) have a random or convergent evolutionary pattern; therefore, they could be more easily affected by the environment and possibly have higher phenotypic plasticity.