FAIRTraits: An enriched, FAIR-compliant database of plant traits from Mediterranean populations of 240 species.

MotivationThe Tundra Trait Team (TTT) database includes field‐based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade‐offs, trait–environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters.Main types of variable containedThe database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density.Spatial location and grainMeasurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub‐Antarctic Marion Island. More than 99% of observations are georeferenced.Time period and grainAll data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods.Major taxa and level of measurementTrait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species.Software formatcsv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.

Our understanding of plant responses to biotic and abiotic drivers is largely based on above-ground plant traits, with little focus on below-ground traits despite their key role in water and nutrient uptake. Here, we aimed to understand the extent to which above- and below-ground traits are co-ordinated, and how these traits respond to soil moisture gradients and plant intraspecific competition. We chose seedlings of five tropical tree species and grew them in a greenhouse for 16 weeks under a soil moisture gradient [low (drought), medium and high (well-watered) moisture levels] with and without intraspecific competition. At harvest, we measured nine above- and five below-ground traits of all seedlings based on standard protocols. In response to the soil moisture gradient, above-ground traits are found to be consistent with the leaf economics spectrum, whereas below-ground traits are inconsistent with the root economics spectrum. We found high specific leaf area and total leaf area in well-watered conditions, while high leaf dry matter content, leaf thickness and stem dry matter content were observed in drought conditions. However, below-ground traits showed contrasting patterns, with high specific root length but low root branching index in the low water treatment. The correlations between above- and below-ground traits across the soil moisture gradient were variable, i.e. specific leaf area was positively correlated with specific root length, while it was negatively correlated with root average diameter across moisture levels. However, leaf dry matter content was unexpectedly positively correlated with both specific root length and root branching index. Intraspecific competition has influenced both above- and below-ground traits, but interacted with soil moisture to affect only below-ground traits. Consistent with functional equilibrium theory, more biomass was allocated to roots under drought conditions, and to leaves under sufficient soil moisture conditions. Our results indicate that the response of below-ground traits to plant intraspecific competition and soil moisture conditions may not be inferred using above-ground traits, suggesting that multiple resource use axes are needed to understand plant ecological strategies. Lack of consistent leaf-root trait correlations across the soil moisture gradient highlight the multidimensionality of plant trait relationships which needs more exploration.

Abstract. Functional trait databases are emerging as a crucial tool for a wide range of ecological studies, including next-generation vegetation modelling across the world. However, few large-scale studies have been reported on plant traits in the Tibetan Plateau (TP), the cradle of East Asian flora and fauna with specific alpine ecosystems, and no report on plant trait databases could be found. In this work, an extensive dataset of 11 leaf functional traits (TiP-Leaf), mainly for herbs and shrubs and a few trees on the TP, was compiled through field surveys. The TiP-Leaf dataset, which was compiled from 336 sites distributed mainly on the plateau surface and the northern margin of the TP across alpine and temperate vegetation regions and sampled from 2018 to 2021, contained 1692 morphological trait measurements of leaf thickness, leaf fresh weight, leaf dry weight, leaf dry-matter content, leaf water content, leaf area, specific leaf area and leaf mass per area and 1645 chemical element trait measurements of leaf carbon, nitrogen and phosphorus contents. Thus, 468 species that belong to 184 genera and 51 families were obtained and measured. In addition to leaf trait measurements, the geographic coordinates, bioclimate variables, disturbance intensities and vegetation types of each site were also recorded. The dataset could provide solid data support to effectively quantify the modern ecological features of alpine ecosystems, thereby further evaluating the response of alpine ecosystems to climate change and human disturbances and improving the next-generation vegetation model. The dataset, which is available from the National Tibetan Plateau Data Center (TPDC; Jin et al., 2022a; https://doi.org/10.11888/Terre.tpdc.272516), can make a great contribution to the regional and global plant trait databases.

<p>Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants – determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystems properties and derived benefits and detriments to people. Plant trait data thus represent the essential basis for a vast area of research spanning evolutionary biology, community and functional ecology, biodiversity conservation, ecosystem and landscape management and restoration, biogeography to earth system modeling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community. Increasingly the TRY database also supports new frontiers of trait-based research, including identi:cation of data gaps and subsequent mobilization or measurement of new data. To support this development, in this article we take stock of trait data compiled in TRY and analyze emerging patterns of data coverage, representativeness, and gaps. Best species coverage is achieved for categorical traits (stable within species) relevant to determine plant functional types commonly used in global vegetation models. For the trait ‘plant growth form’ complete species coverage is within reach. However, most traits relevant for ecology and vegetation modeling are characterized by intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment: completeness at global scale is impossible and representativeness challenging. Due to the sheer amount of data in the TRY database, machine learning for trait prediction is promising - but does not add new data. We therefore conclude that reducing data gaps and biases by further and more systematic mobilization of trait data and new in-situ trait measurements must continue to be a high priority. This can only be achieved by a community effort in collaboration with other initiatives.</p>

Data quality and documentation are at the core of the FAIR (Findable, Accessible, Interoperable, Reusable) principles (Wilkinson et al. 2016). Regarding biodiversity and more broadly ecology domains, complementary solutions of the well-known data standard (notably through Darwin Core (Wieczorek et al. 2012)) orientation are emerging from the intensive use of EML (Ecological Metadata Language (Michener et al. 1997)) metadata standard. These notably capitalize on using: semantic annotation from EML metadata documents that describe data attributes, and FAIR quality assessment as proposed by DataOne (Data Observation Network for Earth) network. semantic annotation from EML metadata documents that describe data attributes, and FAIR quality assessment as proposed by DataOne (Data Observation Network for Earth) network. Here we propose to present this point of view by orchestrating the production of rich (with attributes description and links with terminological resources terms) EML metadata from raw datafiles and, through the generation of FAIR metrics for direct assessment of FAIRness and creation of data standards like Darwin Core. Using EML, we can describe each data attribute (e.g., name, type, unit) and associate each attribute one to several terms coming from terminological resources. Using the Darwin Core vocabulary as a terminological resource, we can thus associate, on the metadata file, original attributes terms to corresponding Darwin Core ones. Then, the data and their metadata files can be processed in order to automatically create the necessary files for a Darwin Core Archive. By acting at the metadata level, associated with accessible raw data files, we can associate raw attribute names to standardized ones, and then, potentially create data standards.

Researchers have become accustomed to online access to data about specimens held in natural history collections. Over several decades, metadata standards have been developed to facilitate the sharing and aggregation of this data, notably Darwin Core and ABCD (Access to Biological Collections Data) developed under the auspices of TDWG but other standards developed in other communities, have also proved useful notably EML (Ecological Metadata Language) and GML (Geography Markup Language). Data aggregators have arisen to both, drive standards development and take advantage of the vast number of records made available through this community effort. Examples include Atlas of Living Australia and spin off Atlas projects, EoL (Encyclopedia of Life), iDigBio, Global Biodiversity Information Facility (GBIF), WFO (World Flora Online). There are still many “dark specimens” that are not visible to the web and efforts continue to digitise metadata on these objects and make them available. The vast majority of the data that has been liberated so far, has therefore been text based and the standards reflect this, although many institutions and projects are also producing large numbers of images and other media. There have been media extensions to some standards to accommodate the sharing of images and other multimedia formats. However, these are restricted to metadata about media objects rather than the exchange of media objects themselves. For example, two extensions to Darwin Core are Audubon Core, which is designed to “determine whether a particular resource or collection will be fit for some particular biodiversity science application before acquiring the media.” and the Simple Multimedia extension, which is a “simple extension for exchanging metadata about multimedia resources”. Therefore image exchange, in particular, has not used open standards. Projects have relied on transferring high resolution versions of images (e.g. submission of type specimen images to JSTOR) or cut down compressed versions (e.g. many herbarium specimens submitted to GBIF or Europeana). The network has not allowed access to high resolution versions of images as curated by the host institutions themselves beyond basic links to web pages. If high resolution images have been published in online catalogues, they have been made available using a hotchpotch of different technologies including the now defunct Java Applets and Adobe Flash player. The network has not supported different views of the same specimen or annotations of those views, or integration of audio and moving images. In an ideal world a researcher should be able to view and annotate images of specimens held across multiple collections in a unified way, and the host institutions should have access to those annotations and statistics on how their specimens are being used. How can we achieve this? The sharing of multimedia representations of objects online is not a problem unique to the biodiversity community. Scholars in museums and archives of all kinds are facing the same issues. In 2011 the British Library, Stanford University, the Bodleian Libraries (Oxford University), the Bibliothèque nationale de France, Nasjonalbiblioteket (National Library of Norway), Los Alamos National Laboratory Research Library, and Cornell University came together to develop an exchange standard called IIIF (International Image Interoperability Framework). This framework now consists of six APIs (Application Programming Interface), four stable and two in beta, to publish and integrate image and other multimedia resources in a uniform manner and has been adopted by many institutions and commercial partners in the digital humanities. Applications based on IIIF enable many of the features desired by biodiversity researchers. The notion of sharing and annotating specimen images is not new to the natural history community. MorphBank, founded in 1998, has grown to allow much of this desirable functionality but at the cost and fragility of being a centralised database. The question we should perhaps be asking is: how can we make the biodiversity data sharing network as a whole more like MorphBank? From 2019 to 2021, part of the EU-funded Synthesys+ programme will support the adoption of IIIF as a unified way to publish images of natural history specimens. We aim to have a set of exemplar institutions publishing IIIF manifests for some millions of specimens by the end of the project and one or more demonstration applications in place. We hope this will act as a catalyst for wider adoption in the natural history community. A key goal is to integrate image data served using IIIF with metadata available via CETAF (Consortium of European Taxonomic Facilities) specimen identifiers. If IIIF were ubiquitous in the natural history community, building tools that implemented this functionality would be feasible. A brief demonstration of a herbarium specimen browser, Herbaria Mundi, will be given. It will illustrate how specimens hosted in different institutions can be manipulated in a single interface. The architecture that supports this behaviour will be explained and its challenges, by implementing the institutions discussed.

Filling gaps in our understanding of belowground plant traits across the world: an introduction to a Virtual Issue.

Temperate North American forest communities have changed considerably in response to logging, fragmentation, herbivory, and other global change factors. Significant changes in the structure and composition of seemingly undisturbed Wisconsin forest communities have occurred over the past 50 years, including widespread declines in alpha and beta species diversity. To investigate how shifts in species composition have affected distributions of plant functional traits, we first compiled extensive data on understory plant species traits. We then computed community-weighted trait means and functional diversity metrics for communities in both the 1950s and 2000s. We examined how trait values and diversity varied across environmental gradients and among Wisconsin's four main ecoregions. Trait means and diversity values reflect conspicuous gradients in species composition, soils, and climatic conditions. Over the past 50 years, values of most traits have changed as communities shifted toward species with higher leaf nutrient levels and specific leaf area, particularly in the southern ecoregions. Trait richness and diversity have declined, particularly in historically species- and trait-rich unglaciated southwestern Wisconsin. Reductions in within-site trait diversity may be diminishing the ability of these forest communities to resist or resiliently respond to shifts in environmental conditions. Despite changes in trait and community composition, trait-environment relationships measured directly via fourth-corner analysis remain strong for most plant traits. Nevertheless, accelerating ecological change (including climate change) could outstrip the ability of plant species and traits to match their environment, particularly in more fragmented landscapes.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Future changes in key plant traits across Central Europe vary with biogeographical status, woodiness, and habitat type

Biological Information Standards

Agricultural Biodiversity has been defined by the Convention on Biological Diversity as the set of elements of biodiversity that are relevant to agriculture and food production. These elements are arranged into an agro-ecosystem that compasses "the variability among living organisms from all sources including terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part: this includes diversity within species, between species and of ecosystems" (UNEP 1992). As with any other field in Biology, Agricultural Biodiversity work produces data. In order to publish data in a way it can be efficiently retrieved on web, one must describe it with proper metadata. A metadata element set is a group of statements made about something. These statements have three elements, named subject (thing represented), predicate (space filled up with data) and object (data itself). This representation is called triples. For example, the title is a metadata element. A book is the subject; title is the predicate; and The Chronicles of Narnia is the object. Some metadata standards have been developed to describe biodiversity data, as ABCD Data Schema, Darwin Core (DwC) and Ecological Metadata Language (EML). The DwC is said to be the most used metadata standard to publish data about species occurrence worldwide (Global Biodiversity Information Facility 2019). "Darwin Core is a standard maintained by the Darwin Core maintenance group. It includes a glossary of terms (in other contexts these might be called properties, elements, fields, columns, attributes, or concepts) intended to facilitate the sharing of information about biological diversity by providing identifiers, labels, and definitions. Darwin Core is primarily based on taxa, their occurrence in nature as documented by observations, specimens, samples, and related information" (Biodiversity Information Standards (TDWG) 2014). Within this thematic context, a master research project is in progress at the Federal University of Minas Gerais in partnership with the Brazilian Agricultural Research Corporation (EMBRAPA). It aims to apply the DwC on Brazil’s Agricultural Biodiversity data. A pragmatic analysis of DwC and DwC Extensions demonstrated that important concepts and relations from Agricultural Biodiversity are not represented in DwC elements. For example, DwC does not have significant metadata to describe biological interactions, to convey important information about relations between organisms in an ecological perspective. Pollination is one of the biological interactions relevant to Agricultural Biodiversity, for which we need enhanced metadata. Given these problems, the principles of metadata construction of DwC will be followed in order to develop a metadata extension able to represent data about Agricultural Biodiversity. These principles are the Dublin Core Abstract Model, which present propositions for creating the triples (subject-predicate-object). The standard format of DwC Extensions (see Darwin Core Archive Validator) will be followed to shape the metadata extension. At the end of the research, we expect to present a model of DwC metadata record to publish data about Agricultural Biodiversity in Brazil, including metadata already existent in Simple DwC and the new metadata of Brazil’s Agricultural Biodiversity Metadata Extension. The resulting extension will be useful to represent Agricultural Diversity worldwide.

Background and aimsBoth soil properties and plant traits shape the diversity, composition and functions of plant-associated soil microbial communities. However, the relative influence of these factors is poorly understood, as are interactive effects between factors and the degree to which their influence varies among climate zones.MethodsTo address this gap, we compared the diversity and composition of soil microbial communities associated with co-occurring C3 and C4 grasses from arid and mesic environments, and plant traits influencing them.ResultsClimate emerged as the main determinant of plant traits and microbial community properties. Within each climatic region, above- and below-ground traits and soil properties differentially affected microbial community composition, and their relative influence varied among communities. In both mesic and arid environments aboveground traits related to quantity and quality of leaf litter (e.g., specific leaf area, leaf C content) and nutrient availability were the most influential variables for community composition. However, in arid regions, belowground traits (i.e., root tissue density and specific root area) significantly contributed to structure the eukaryotic community, supporting the role of roots as important driver of eukaryotic differentiation in constrained environments. Further, the presence of C4 plants in the arid region resulted in higher relative abundance of ciliate protists and higher recruitment of potentially beneficial microbial community members from green algae mediated by drought adaptation traits (e.g. decreased abundance of fine roots).ConclusionsOverall, our study revealed a differential response of microbial communities to environmental conditions, suggesting that soil microbial community composition is influenced by trade-offs between host adaptive traits across distinct climatic regions.

Understanding the trait–environment relationships has been a core ecological research topic in the face of global climate change. However, the strength of trait–environment relationships at the local and regional scales in temperate forests remains poorly known. In this study, we investigated the local and regional scale forest plots of the natural broad-leaved temperate forest in northeastern China, to assess what extent community-level trait composition depends on environmental drivers across spatial scales. We measured five key functional traits (leaf area, specific leaf area, leaf carbon content, leaf nitrogen content, and wood density) of woody plant, and quantified functional compositions of communities by calculating the “specific” community-weighted mean (CWM) traits. The sum of squares decomposition method was used to quantify the relative contribution of intraspecific trait variation to total trait variation among communities. Multiple linear regression model was then used to explore the community-level trait–environment relationships. We found that (i) intraspecific trait variation contributed considerably to total trait variation and decreased with the spatial scale from local to regional; (ii) functional composition was mainly affected by soil and topography factors at the local scale and climate factor at the regional scale, while explaining that variance of environment factors were decreased with increasing spatial scale; and (iii) the main environment driver of functional composition was varied depending on the traits and spatial scale. This work is one of the few multi-scale analyses to investigate the environmental drivers of community functional compositions. The extent of intraspecific trait variation and the strength of trait–environment relationship showed consistent trends with increasing spatial scale. Our findings demonstrate the influence of environmental filtering on both local- and regional-scale temperate forest communities, and contribute to a comprehensive understanding of trait–environment relationships across spatial scales.

BackgroundTo address the lack of evidence supporting invasion by three invasive plant species (Imperata cylindrica, Lantana camara, and Chromolaena odorata) in tropical ecosystems, we compared the ecophysiological and leaf anatomical traits of these three invasive alien species with those of species native to Sempu Island, Indonesia. Data on four plant traits were obtained from the TRY Plant Trait Database, and leaf anatomical traits were measured using transverse leaf sections.ResultsTwo ecophysiological traits including specific leaf area (SLA) and seed dry weight showed significant association with plant invasion in the Sempu Island Nature Reserve. Invasive species showed higher SLA and lower seed dry weight than non-invasive species. Moreover, invasive species showed superior leaf anatomical traits including sclerenchymatous tissue thickness, vascular bundle area, chlorophyll content, and bundle sheath area. Principal component analysis (PCA) showed that leaf anatomical traits strongly influenced with cumulative variances (100% in grass and 88.92% in shrubs), where I. cylindrica and C. odorata outperformed non-invasive species in these traits.ConclusionsThese data suggest that the traits studied are important for plant invasiveness since ecophysiological traits influence of light capture, plant growth, and reproduction while leaf anatomical traits affect herbivory, photosynthetic assimilate transport, and photosynthetic activity.