Trait Databases Research Articles

Herb hydraulics: Variation and correlation for traits governing drought tolerance and efficiency of water transport

Hydraulic traits dictate plant response to drought, thus enabling better understanding of community dynamics under global climate change. Despite being intensively documented in woody species, herbaceous species (graminoids and forbs) are largely understudied, hence the distribution and correlation of hydraulic traits in herbaceous species remains unclear. Here, we collected key hydraulic traits for 436 herbaceous species from published literature, including leaf hydraulic conductivity (Kleaf), water potential inducing 50 % loss of hydraulic conductivity (P50), stomatal closure (Pclose) and turgor loss (Ptlp). Trait variation of herbs was analyzed and contrasted with angiosperm woody species within the existing global hydraulic traits database, as well as between different growth forms within herbs. Furthermore, hydraulic traits coordination was also assessed for herbaceous species. We found that herbs showed overall more negative Pclose but less negative Ptlp compared with angiosperm woody species, while P50 did not differ between functional types, regardless of the organ (leaf and stem). In addition, correlations were found between Kleaf and P50 of leaf (P50leaf), as well as between Pclose, P50leaf and Kleaf. Within herbs, graminoids generally exhibited more negative P50 and Ptlp, but lower Kleaf, relative to forbs. Within herbs, no clear pattern regarding hydraulic traits-climate relationship was found. Our analysis provided insights into herb hydraulic, and highlighted the knowledge gaps need to be filled regarding the response of herbs to drought.

Response trait diversity and species asynchrony underlie the diversity-stability relationship in Romanian bird communities.

Biodiversity-stability relationships have frequently been studied in ecology, with the recent integration of traits to explain community stability over time. Classical theory underlying the biodiversity-stability relationship posits that different species' responses to the environment should stabilise community-level properties (e.g. biomass or abundance) through compensatory dynamics. However, functional response traits, which aim to predict how species respond to environmental change, are still rarely integrated into studies of ecological stability. Such traits should mechanistically drive community stability, both in terms of community abundance (functional variability) and composition (compositional variability). In turn, whether and how functional or compositional stability scales to affect temporal variation in functional effect traits (a proxy for ecosystem functioning) remains largely unknown, but is key to consistent ecosystem functioning under environmental change. Here, we explore the diversity-stability relationship in bird communities using annual survey data across 98 sites in central Romania, in combination with global trait databases and structural equation models. We show that higher response trait diversity promotes compositional variability directly, and functional variability indirectly via species asynchrony. In turn, functional variability impacts the temporal stability of effect trait diversity. Multiple facets of diversity and community stability differ between natural forests and agricultural or human-dominated survey sites, and the relationship between response diversity and functional variability is mediated by land cover. Further integration of response-and-effect trait frameworks into studies of community stability will enhance understanding of the drivers of biodiversity change, allowing targeted conservation decision-making with a focus on stable ecosystem functioning in the face of global environmental change.

GIFTdb: a useful gene database for plant fruit traits improving.

Fruit traits are critical determinants of plant fitness, resource diversity, productive and quality. Gene regulatory networks in plants play an essential role in determining fruit traits, such as fruit size, yield, firmness, aroma and other important features. Many research studies have focused on elucidating the associated signaling pathways and gene interaction mechanism to better utilize gene resources for regulating fruit traits. However, the availability of specific database of genes related to fruit traits for use by the plant research community remains limited. To address this limitation, we developed the Gene Improvements for Fruit Trait Database (GIFTdb, http://giftdb.agroda.cn). GIFTdb contains 35 365 genes, including 896 derived from the FR database 1.0, 305 derived from 30 882 articles from 2014 to 2021, 236 derived from the Universal Protein Resource (UniProt) database, and 33 928 identified through homology analysis. The database supports several aided analysis tools, including signal transduction pathways, gene ontology terms, protein-protein interactions, DNAWorks, Basic Local Alignment Search Tool (BLAST), and Protein Subcellular Localization Prediction (WoLF PSORT). To provide information about genes currently unsupported in GIFTdb, potential fruit trait-related genes can be searched based on homology with the supported genes. GIFTdb can provide valuable assistance in determining the function of fruit trait-related genes, such as MYB306-like, by conducting a straightforward search. We believe that GIFTdb will be a valuable resource for researchers working on gene function annotation and molecular breeding to improve fruit traits.

Global root trait underrepresentation in Paleotropical communities: a qualitative analysis

Many ecosystem processes revolve around plant roots and the rhizosphere, but root trait knowledge has generally lagged behind aboveground plant traits from leaves and stems. In particular, root trait representation of Paleotropical species and tropical communities in modern trait databases remains poor, constraining our understanding of belowground processes in these regions. Therefore, we sought to examine the current state of root trait representation and associated topics in the Paleotropics to identify gaps and biases in the existing literature. Using an exhaustive literature scan, we compiled a list of publications that contained various belowground trait information. Subsequently, we utilized a statistical topic modeling method to analyze abstracts of publications in order to identify topics studied alongside root trait documentation. Finally, we consolidated trends in root trait coverage and topics across five geographical regions and four time periods to illustrate shifts in literature and knowledge of ecological processes revolving around roots. Root trait representation was heavily biased toward root biomass but other aspects of root systems such as physiology, architecture and anatomical traits remain underrepresented. We categorized 23 unique topics around root trait literature across eight categories: ecosystem productivity and biomass stocks, plant functional traits, resource availability, ecosystem processes and dynamics, mycorrhizal colonization, edaphic processes, seedling experiments, and global change and variation. Traits and topic coverage were unequally distributed across the Paletropics and exhibited a notable shift in focus from resource limitation and mycorrhizae research to root trait variation at large spatial and temporal scales over the last 50 years of root trait literature. Given these trends and the heterogenous effects global change exerts on the tropics at a regional scale, we provided several recommendations to facilitate inter-study comparisons of traits to advance the field’s understanding of belowground ecosystem processes in pantropical communities.

A workflow to create trait databases from collections of textual taxonomic descriptions

There is a wealth of information about the characteristics (traits) of organisms within collections of taxonomic descriptions of plants and animals called a ‘Flora’ or ‘Fauna’ of a region. However, such knowledge is usually encoded as text paragraphs, and is thus unavailable for immediate analysis. In order to make use of the knowledge embedded in taxon descriptions, text must be organised into standardised, queryable datasets. Despite the recent development of natural language processing (NPL) tools to analyse taxonomic descriptions to extract trait values, the complexity and specificity of these methods currently limits broad application. Accessible and flexible methods for extracting traits across large numbers of taxonomic descriptions are therefore needed. Here we present such an R-based workflow, which can be adapted for use on any organismal group using a language familiar to researchers in the biological sciences. We document a way to (1) assemble tens of thousands of taxonomic descriptions into a standardised format, (2) split the taxon descriptions into different topics, (3) extract trait values as defined by the user, and (4) assign traits described at the genus and family level to lower level taxa to maximise trait coverage. As a case study, we apply the workflow to a collection of taxonomic descriptions drawn from Australia's state and national floras and describe useful techniques for creating workflows and thereby research-grade trait datasets. Using this method, we were able to extract 615,812 trait values from 38 different plant traits. Trait data collated using this method are freely available as part of the AusTraits trait database and have already contributed to analyses in several scientific publications.

Rasgos‐CL: A functional trait database of Chilean woody plants

AbstractMotivationDue to language and networking barriers, global initiatives to compile trait data often fail to integrate data from sources in non‐English languages or scientists that largely speak and write in non‐English languages. To illustrate the potential for regional databases to fill gaps in trait data, and how such databases may fill critical gaps in global biodiversity databases, we built the Rasgos‐CL Database. Rasgos‐CL provides a comprehensive set of plant traits for the woody flora of Chile by mobilizing and standardizing unstructured data largely from the Spanish‐language literature. We quantified the gains in trait coverage compared to global trait databases and identified phylogenetic and geographic biases of trait data gaps.Main Types of Variables ContainedRasgos‐CL contains 25,174 trait records, including 2 continuous and 21 categorical traits for 662 woody species.Spatial Location and GrainNational coverage, with species that occur across all ecosystems in continental Chile.Time Period and GrainData were extracted from sources published between 1833 and 2023.Major Taxa and Level of MeasurementRasgos‐CL includes trait data aggregated at the species level for 662 tree and shrub species, and also provides trait records from individual data sources.Software FormatRasgos‐CL includes four csv files. A GitHub repository contains the csv files.

Knowledge Base on Species Life Traits: A Spanish/French Plinian Core implementation use case

The French “Traits” working group was created in 2021 to support the development of the national knowledge base on species life traits managed by the PatriNat department*1, to identify and implement a suitable standard for managing and sharing species life traits (including interactions) at the national, then international, level. Its core members are part of several PatriNat teams (Species Knowledge, Dissemination & Mediation, Coordination of Information Systems), as well as other French research units*2 working on the topic of traits and ontologies. The Plinian Core (Plinian Core Task Group 2021) was first discussed in 2004 and its development began in 2005–2006 when the first version was deployed as a collaboration between InBIO*3 (Costa Rica) and GBIF Spain*4. It reuses and extends the Darwin Core vocabulary (Wieczorek et al. 2012, Darwin Core Maintenance Interest Group 2014) to describe different aspects of biological species information, that is, all kinds of properties or traits related to taxa, including biological and non-biological species traits. The Plinian Core was discussed with Dr Pando (convener of the TDWG Plinian Core Task Group*5) during one of the Traits working group meetings, and was found to be relevant to the French species life traits database (currently in development). The Traits working group future works will be following the example of the Plinian Core-based EIDOS database*6 (Spanish Ministry for the Ecological Transition), which allows for detailed species pages with distinct information sections (e.g., interactions, taxonomy, legal status, conservation). This collaboration resulted in a Capacity Enhancement Support Programme project submission (GBIF 2023) between French and Spanish partners, allowing for the consolidation of both the infrastructure and the sharing process of species life traits for taxa found on all French territories, as well as European Union territories. Additionally, this is an opportunity to provide information to GBIF (Global Biodiversity Information Facility) through a new update of the TAXREF (Gargominy 2022) national checklist, one of the core constituents of the GBIF Backbone Taxonomy (GBIF 2022). Species life traits and interactions will be added thanks to the new Plinian Core extension implemented on the GBIF Integrated Publishing Toolkit (IPT),*7 and an Atlas of Living Australia’s architecture BIE (Biodiversity Information Explorer) module*8 developed by Costa Rica in the context of a Capacity Enhancement Support Programme (CESP) project carried out with SIBBR*9 (GBIF Brasil).

Diversity of Platyhelminthes Proseriata in Western Mediterranean sandy beaches: a database of species occurrences and traits

Diversity of Platyhelminthes Proseriata in Western Mediterranean sandy beaches: a database of species occurrences and traits

Combination of observational and functional trait-based approaches in developing a polyculture design tool

ABSTRACT Models of species composition in diversified cropping systems utilize mostly functional trait-based or observation-based approaches. We argue that a combination of these two approaches makes polyculture design tools more robust. We assessed quantity, quality, and complementarity of information from multiple sources for designing diversified cropping systems with vegetables and spice crops for cold temperate climate. Trait and observational data were integrated from: (i) two grower-oriented and one academic crop database, (ii) a survey of farmers practicing community-supported agriculture, and (iii) a systematic literature review on the use of spice crops in vegetable farming. Survey results reveal that the farmers were capable of achieving medium to good levels of their main goals, but failed to reach desired multifunctionality with their polycultures, which can be potentially improved with computational tools. None of the analyzed data sources provided a comprehensive dataset for all target crops and functional traits. However, source combination allowed for design from known crop companions (farmers survey and grower-oriented databases), to addressing specific pest problems (literature review), and increasing functional complementarity and facilitation by trait matching (academic and grower-oriented trait databases). Integrating information from different sources increased the number of crop combination options but also planning and management complexity.

NZTD - The New Zealand Trait Database for shallow-water marine benthic invertebrates

Macrobenthic traits, for example feeding mode, life history, morphology, are increasingly used for determining responses of macrobenthic fauna to environmental change and influences on ecosystem functioning. Yet, trait information is scarce or non-existent in several parts of the world, such as New Zealand. This deficit makes collecting trait data a difficult and time-consuming task, limiting its potential use in trait-based assessments. Here, we present the New Zealand Trait Database (NZTD) for marine benthic invertebrates, the first comprehensive assessment of macrobenthic traits in New Zealand. The NZTD provides trait information for more than 700 macrobenthic taxa, categorised by 18 traits and 77 trait modalities. The NZTD includes five freely downloadable datasets, (1) the macrobenthic trait dataset, with outcomes from a fuzzy coding procedure, (2) the trait source information, (3) the references by taxa, (4) the full references list, and (5) the full taxa list used in the NZTD. Establishing the NZTD closes the trait knowledge gap in New Zealand and facilitates future research applying trait-based approaches to New Zealand’s coastal macrofauna.

SAviTraits 1.0: Seasonally varying dietary attributes for birds

AbstractMotivationTrait‐based studies remain limited by the quality and scope of the underlying trait data available. Most of the existing trait databases treat species traits as fixed across time, with any potential temporal variation in the measured traits being unavailable. This is despite the fact that many species are well known to show plasticity in their trait characteristics over the course of the year. This data paper describes a compilation of species‐specific dietary preferences and their known intra‐annual variation for over 10,000 of the world's extant bird species (SAviTraits 1.0). Information on dietary preferences was obtained from the Cornell Lab of Ornithology Birds of the World (BOW) online database. Textual descriptions of species' dietary preferences were translated into semi‐quantitative information denoting the proportion of dietary categories utilized by each species. Temporal variation in dietary attributes was captured at a monthly temporal resolution. We describe the methods for data discovery and translation and present tools for summarizing the annual variability of avian dietary preferences. Altogether, we were able to document a seasonal variability in dietary attributes for a total of 1031 species (ca. 10%). For the remaining species, the dietary attributes were either temporally stationary or the information on temporal variability of the diet was not available.Main Types of Variable ContainedTemporally‐varying dietary traits for birds.Spatial Location and GrainN/A.Time Period and GrainVariation in diet was captured at a monthly temporal resolution.Major Taxa and Level of MeasurementBirds, species level.Software Format.csv/.rds

Size-Pattern and Larval-Length–Mass Relationships for the Most Common Chironomid Taxa in the Deep Subalpine Lake Maggiore

For the first time, the size spectra of 28 chironomid genera/species are reported for the most common chironomid taxa in the deep subalpine Lake Maggiore (northwestern Italy). Species-specific length–mass regression models were developed to predict the dry masses of the larval stages of Cladotanytarsus sp., Cryptochironomus sp., Polypedilum bicrenatum, P. nubeculosum, and Stictochironomus pictulus. The predicted dry-mass values differed by less than 20% from the measured values, suggesting that these original equations will be important in chironomid production studies. Regressions at the subfamily level were also developed for case identification at the genus or species level, which is difficult to obtain. The chironomid weights were determined directly and a dry/wet-weight-conversion ratio was estimated. The results were consistent with previously reported results. The relationships between the dry masses and the body lengths were compared with published data for different types of lake all over the world. We found that regression models for other freshwater environments somehow differed from those in Lake Maggiore, albeit slightly. The combination of diversity-based and trait-based approaches improves our knowledge about chironomids and our understanding of the effects of global environmental changes on freshwater biota. This first collection of trait data on summer–autumn chironomid assemblages in a temperate subalpine lake is a valuable contribution to the European trait database. The taxonomic diversity and abundance of chironomids were uploaded for open access on the GBIF platform.

FUN Azores: a FUNctional trait database for the meio-, macro-, and megafauna from the Azores Marine Park (Mid-Atlantic Ridge)

Trait-based approaches that complement taxonomy-based studies have increased in popularity among the scientific community over the last decades. The collection of biological and ecological characteristics of species (i.e., traits) provides insight into species and ecosystem vulnerability to environmental and anthropogenic changes, as well as ecosystem functioning. Here, we present the FUN Azores trait database, describe our approach, evaluate its scope, compare it to other marine trait databases, and explore the spatial distribution of its traits with “functional maps.” While most of the available trait databases to date contain essential information to understand the functional diversity of a taxonomic or functional group, our ecosystem-based approach provides a comprehensive assessment of diverse fauna (i.e., meio-, macro-, and megafauna) from benthic and pelagic environments in the Azores Marine Park; including ridges, seamounts, hydrothermal vents, and the overlying water column. We used a collaborative approach involving 30 researchers with different expertise to develop the FUN Azores database, which contains compiled data on 14 traits representing morphological, behavioral, and life history characteristics for 1,210 species across 10 phyla. The “functional maps” show a distinct distribution of the two most common size classes, suggesting different communities with different functionalities. The following traits had the best scoring coverage (i.e., >95% of the species scored): maximum body size, body form, skeleton material, feeding structure, motility, environmental position, substratum affinity, distribution, and depth range; while traits related to species behavior (e.g., sociability or aggregation tendencies) and life history (e.g., developmental mechanism) had lower scoring coverage, highlighting the need for further research to fill these knowledge gaps. We found a larger number of species in the benthic compared to the pelagic environment and differing species composition between areas within the Azores Marine Park resulting from varying biodiversity, ecosystem types, sampling effort, and methodologies used. The FUN Azores database will foster and facilitate trait-based approaches in the area, develop a framework for expansion of cross-ecosystem and cross-taxa trait databases elsewhere, and improve our ecological understanding of the Azores Marine Park and its conservation requirements.

Leaf trait responses to global change factors in terrestrial ecosystems

Global change influences plant growth by affecting plant morphology and physiology. However, the effects of global change factors vary based on the climate gradient. Here, we established a global database of leaf traits from 192 experiments on elevated CO2 concentrations (eCO2), drought, N deposition, and warming. The results showed that the leaf mass per area (LMA) significantly increased under eCO2 and drought conditions but decreased with N deposition, whereas eCO2 levels and drought conditions reduced stomatal conductance and increased and decreased photosynthetic rates, respectively. Leaf dark respiration (Rd) increased in response to global change, excluding N deposition. Leaf N concentrations declined with eCO2 but increased with N deposition. Leaf area increased with eCO2, N deposition, and warming but decreased with drought. Leaf thickness increased with eCO2 but decreased with warming. eCO2 and N deposition enhanced plant water-use efficiency (WUE), eCO2 and warming increased photosynthetic N-use efficiency (PNUE), while N fertilization reduced PNUE significantly. eCO2 produced a positive relationship between WUE and PNUE, which were limited under drought but increased in areas with high humidity and high temperature. Trade-offs were observed between WUE and PNUE under drought, N deposition, and warming. These findings suggest that the effects of global change factors on plants can be altered by complex environmental changes; moreover, diverse plant water and nutrient strategy responses can be interpreted against the background of their functional traits.

AlgaeTraits: a trait database for (European) seaweeds

Abstract. The analysis of biological and ecological traits has a long history in evolutionary and ecological research. However, trait data are often scattered and standardised terminology that transcends taxonomic and biogeographical context are generally missing. As part of the development of a global trait database of marine species, we collated trait information for European seaweeds and structured the data within the standardised framework of the World Register of Marine Species (WoRMS). We collected 45 175 trait records for 21 biologically and ecologically relevant traits of seaweeds. This resulted in a trait database for 1745 European seaweed species of which more than half (56 %) of the records were documented at the species level, while the remaining 44 % were documented at a higher taxonomic level and subsequently inherited at lower levels. The trait database for European seaweeds will serve as a foundation for future research on diversity and evolution of seaweeds and their responses to global changes. The data will contribute to developing detailed trait-based ecosystem models and will be an important tool to inform marine conservation policies. The data are publicly accessible through the AlgaeTraits portal, https://doi.org/10.14284/574 (AlgaeTraits, 2022).

Functional trait trade-offs define plant population stability across different biomes.

Ecological theory posits that temporal stability patterns in plant populations are associated with differences in species' ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, especially across different biomes. We compiled a worldwide collection of long-term permanent vegetation records (greater than 7000 plots from 78 datasets) from a large range of habitats which we combined with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits. We found that populations with greater leaf dry matter content and seed mass were more stable over time. Despite the variability explained by these traits being low, their effect was consistent across different datasets. Other traits played a significant, albeit weaker, role in species stability, and the inclusion of multi-variate axes or phylogeny did not substantially modify nor improve predictions. These results provide empirical evidence and highlight the relevance of specific ecological trade-offs, i.e. in different resource-use and dispersal strategies, for plant populations stability across multiple biomes. Further research is, however, necessary to integrate and evaluate the role of other specific traits, often not available in databases, and intraspecific trait variability in modulating species stability.

Towards a trait‐based framework for marine macroalgae: Using categorical data to explore the nature of emergent functional groups

Abstract While trait‐based approaches have been effectively leveraged by plant ecologists to advance our understanding of community responses to major global challenges, such as climate change and invasive species, the study of marine macroalgae is still mired in a functional group (FG) framework developed in the 1980s. In this paper, we used predominantly categorical data for 18 macroalgal traits that were accessible in public databases and/or the literature to explore their usefulness in a trait‐based framework for marine macroalgae. Species were clustered into emergent, data‐driven groups using a Gower dissimilarity matrix, then a k‐medoid clustering approach called partitioning around the medoids. We identified 14 emergent groups (EGs) that captured a spectrum of strategies used by different macroalgal species. However, significant ‘gaps’ in trait space may identify evolutionary constraints to algal adaptive strategies. Multivariate analysis showed how the 18 traits created trait space and drove the clustering. A spectrum of strategies and the influence of multiple traits imply that algal strategies are likely governed by complex multivariate, not bivariate, trade‐offs. Finally, we found that our EGs appeared to reflect multivariate trade‐offs and diverse ecological strategies more than the traditional FG model for macroalgae. We tested the usefulness of our EGs by comparing real‐world spatial distributions of species across habitats with known strong environmental filters to their area occupied in trait space. We found significant separation in trait space and divergent occupancy patterns across global distributions, attachment substrates and elevational zones. These results support the use of categorical data accessible in the literature as a useful step towards developing trait‐based ecology for marine macroalgae. Synthesis. Our findings indicate that readily accessible categorical traits produce emergent FGs that reflect environmental filtering and therefore demonstrate the power of trait‐based approaches over the current FG framework. Furthermore, we posit that categorical traits are a valuable and potentially complementary addition to a newly developing database of continuous traits because they encompass a broader, more globally accessible set of traits.

Frugivoria: A trait database for birds and mammals exhibiting frugivory across contiguous Neotropical moist forests

AbstractMotivationBiodiversity in many areas is rapidly declining because of global change. As such, there is an urgent need for new tools and strategies to help identify, monitor and conserve biodiversity hotspots. This is especially true for frugivores, species consuming fruit, because of their important role in seed dispersal and maintenance of forest structure and health. One way to identify these areas is by quantifying functional diversity, which measures the unique roles of species within a community and is valuable for conservation because of its relationship with ecosystem functioning. Unfortunately, the functional trait information required for these studies can be sparse for certain taxa and specific traits and difficult to harmonize across disparate data sources, especially in biodiversity hotspots. To help fill this need, we compiled Frugivoria, a trait database containing ecological, life‐history, morphological and geographical traits for mammals and birds exhibiting frugivory. Frugivoria encompasses species in contiguous moist montane forests and adjacent moist lowland forests of Central and South America—the latter specifically focusing on the Andean states. Compared with existing trait databases, Frugivoria harmonizes existing trait databases, adds new traits, extends traits originally only available for mammals to birds also and fills gaps in trait categories from other databases. Furthermore, we create a cross‐taxa subset of shared traits to aid in analysis of mammals and birds. In total, Frugivoria adds 8662 new trait values for mammals and 14,999 for birds and includes a total of 45,216 trait entries with only 11.37% being imputed. Frugivoria also contains an open workflow that harmonizes trait and taxonomic data from disparate sources and enables users to analyse traits in space. As such, this open‐access database, which aligns with FAIR data principles, fills a major knowledge gap, enabling more comprehensive trait‐based studies of species in this ecologically important region.Main Types of Variable ContainedEcological, life‐history, morphological and geographical traits.Spatial Location and GrainNeotropical countries (Mexico, Guatemala, Costa Rica, Panama, El Salvador, Belize, Nicaragua, Ecuador, Colombia, Peru, Bolivia, Argentina, Venezuela and Chile) with contiguous montane regions.Time Period and GrainIUCN spatial data: obtained February 2023, spanning range maps collated from 1998 to 2022. IUCN species data: obtained June 2019–September 2022. Newly included traits: span 1924 to 2023.Major Taxa and Level of MeasurementClasses Mammalia and Aves; 40,074 species‐level traits; 5142 imputed traits for 1733 species (mammals: 582; birds: 1147) and 16 sub‐species (mammals).Software Format.csv; R.

Human land use is comparable to climate as a driver of global plant occurrence and abundance across life forms

AbstractAimHistorically, climate has been a dominant driver of global vegetation patterns. Recently, ecological understanding has been updated to acknowledge the influence of human land use (the dominant driver of biodiversity change) in shaping global vegetation patterns. We test whether Raunkiær's life form, a plant classification system designed to reflect climatic drivers, affects how plants respond to both land use and climate.LocationForty‐one countries across six continents.Time period1990 to 2013.Major taxa studiedTerrestrial plants.MethodsCombining data from the biodiversity and land use database PREDICTS, and plant trait databases TRY and BIEN, we use generalized linear mixed models with weighted effects coding to test whether Raunkiær's life form affects plant response to land use and climate in over 4800 species at over 300 sites globally.ResultsWe provide evidence that human land use is comparable to climate in influencing life form occurrence and that land use produces divergent outcomes across life forms.Main conclusionsCombined with climatic suitability, land use acts as a filter contracting the realized niche of trees and expanding the realized niche of disturbance‐tolerant species. Our results highlight the fundamental role of human activity in shaping species' distribution.

MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales

Abstract. Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity, which requires moving away from broadly defined functional types. Different approaches have been adopted in the last years to incorporate a trait-based perspective into modeling exercises. A common parametrization strategy involves using trait data to represent functional variation between individuals while discarding taxonomic identity. However, this strategy ignores the phylogenetic signal of trait variation and cannot be employed when predictions for specific taxa are needed, such as in applications to inform forest management planning. An alternative strategy involves adapting the taxonomic resolution of model entities to that of the data source employed for large-scale initialization and estimating functional parameters from available plant trait databases, adopting diverse solutions for missing data and non-observable parameters. Here we report the advantages and limitations of this second strategy according to our experience in the development of MEDFATE (version 2.9.3), a novel cohort-based and trait-enabled model of forest dynamics, for its application over a region in the western Mediterranean Basin. First, 217 taxonomic entities were defined according to woody species codes of the Spanish National Forest Inventory. While forest inventory records were used to obtain some empirical parameter estimates, a large proportion of physiological, morphological, and anatomical parameters were matched to measured plant traits, with estimates extracted from multiple databases and averaged at the required taxonomic level. Estimates for non-observable key parameters were obtained using meta-modeling and calibration exercises. Missing values were addressed using imputation procedures based on trait covariation, taxonomic averages or both. The model properly simulated observed historical changes in basal area, with a performance similar to an empirical model trained for the same region. While strong efforts are still required to parameterize trait-enabled models for multiple taxa, and to incorporate intra-specific trait variability, estimation procedures such as those presented here can be progressively refined, transferred to other regions or models and iterated following data source changes by employing automated workflows. We advocate for the adoption of trait-enabled and population-structured models for regional-level projections of forest function and dynamics.