Global biodiversity is rapidly declining, primarily due to agricultural production driven by both domestic and transboundary consumption. This study addresses the challenges posed by inconsistent spatiotemporal biodiversity data by developing a time series of biodiversity loss footprints based on Biodiversity Intactness Index (BII). Numerous land use, land cover, and auxiliary datasets were integrated to produce a consistent time series of high-resolution harmonized land use (HHLU) maps. These maps were utilized to quantify spatial BII using linear-mixed effect models. Biodiversity intactness loss (BII footprint) was subsequently attributed to specific crops and livestock commodities. This study provides comprehensive global datasets, including HHLU and BII maps, and synthesized BII footprints across 14 biomes, 193 countries and territories, 154 crop items, and 9 livestock categories from 2000 to 2020. These datasets facilitate spatiotemporal analyses to identify trends and patterns in global biodiversity integrity and biodiversity footprints, thereby elucidating the ecological trade-offs embedded in international trade. These insights can encourage appropriate interventions to transform consumption patterns and supply chains toward the effective conservation of global biodiversity.
- MeSH
- Biodiversity * MeSH
- Livestock MeSH
- Conservation of Natural Resources * MeSH
- Crops, Agricultural MeSH
- Agriculture * MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Dataset MeSH
Sorghum virgatum (Sv) is a wild subspecies of sorghum (Sorghum bicolor ssp. Verticilliflorum (L.) Moench). We employed Hi-C sequencing and HiFi technology in this study, successfully assembly a high-quality genome for Sv. This assembled genome is 795 Mb in total and scaffold N50 is 62.47 Mb. Within the Sv genome, 27,851 protein-coding genes were predicted. Repeat annotation detected 563.96 Mb of repetitive elements, making up 71.86% of the genome. This chromosome-level sv genome offers valuable insights to support comparative genomic studies within the Poaceae family, and it will aid genome-driven breeding and germplasm enhancement for modern sorghum.
- MeSH
- Chromosomes, Plant * MeSH
- Genome, Plant * MeSH
- Repetitive Sequences, Nucleic Acid MeSH
- Sorghum * genetics MeSH
- Publication type
- Journal Article MeSH
- Dataset MeSH
Soil microbes drive ecosystem function and play a critical role in how ecosystems respond to global change. Research surrounding soil microbial communities has rapidly increased in recent decades, and substantial data relating to phospholipid fatty acids (PLFAs) and potential enzyme activity have been collected and analysed. However, studies have mostly been restricted to local and regional scales, and their accuracy and usefulness are limited by the extent of accessible data. Here we aim to improve data availability by collating a global database of soil PLFA and potential enzyme activity measurements from 12,258 georeferenced samples located across all continents, 5.1% of which have not previously been published. The database contains data relating to 113 PLFAs and 26 enzyme activities, and includes metadata such as sampling date, sample depth, and soil pH, total carbon, and total nitrogen. This database will help researchers in conducting both global- and local-scale studies to better understand soil microbial biomass and function.
- MeSH
- Databases, Factual * MeSH
- Ecosystem MeSH
- Enzymes * MeSH
- Phospholipids * MeSH
- Fatty Acids * MeSH
- Soil chemistry MeSH
- Soil Microbiology * MeSH
- Publication type
- Journal Article MeSH
- Dataset MeSH
- Names of Substances
- Enzymes * MeSH
- Phospholipids * MeSH
- Fatty Acids * MeSH
- Soil MeSH
The Indo-European Cognate Relationships (IE-CoR) dataset is an open-access relational dataset showing how related, inherited words ('cognates') pattern across 160 languages of the Indo-European family. IE-CoR is intended as a benchmark dataset for computational research into the evolution of the Indo-European languages. It is structured around 170 reference meanings in core lexicon, and contains 25731 lexeme entries, analysed into 4981 cognate sets. Novel, dedicated structures are used to code all known cases of horizontal transfer. All 13 main documented clades of Indo-European, and their main subclades, are well represented. Time calibration data for each language are also included, as are relevant geographical and social metadata. Data collection was performed by an expert consortium of 89 linguists drawing on 355 cited sources. The dataset is extendable to further languages and meanings and follows the Cross-Linguistic Data Format (CLDF) protocols for linguistic data. It is designed to be interoperable with other cross-linguistic datasets and catalogues, and provides a reference framework for similar initiatives for other language families.
- MeSH
- Language * MeSH
- Humans MeSH
- Linguistics * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Dataset MeSH
- Geographicals
- Europe MeSH
Trait-based ecology relies on high-quality, well-documented data to explore how plant traits relate to environmental conditions, community assembly, and ecosystem functioning. However, the reuse and synthesis of trait data across studies remain limited by several constraints: a lack of detailed metadata, heterogeneous protocols, absence of individual-level measurements, and underrepresentation of certain trait types-particularly below-ground traits. Many existing datasets also lack the environmental details necessary to investigate trait-environment relationships at local scales. Here, we present FAIRTraits, a comprehensive dataset that addresses these limitations by compiling 189,452 records of quantitative trait measurements collected between 1997 and 2023 from 1955 populations of 240 vascular plant species in the Northern Mediterranean Basin, a region known both for its exceptional biodiversity and as a climate change hotspot. All data were collected by a single research group using consistent and well-documented field and laboratory protocols, ensuring internal consistency across traits, species, sites, and years. FAIRTraits includes 180 traits measured at the individual or replicate level, with no aggregation. It features an unprecedented diversity of traits spanning all major plant organs-leaves, stems, roots, and reproductive parts. These include widely used traits such as specific leaf area and plant height, but also traits that are rarely reported, especially below-ground traits related to root morphology, as well as mechanical properties, phenology, and microbial associations. In addition to raw measurements, species are annotated with categorical descriptors (e.g., life form, photosynthetic pathway, and successional status), and species-level values taken from a Mediterranean flora, for key traits such as reproductive phenology and maximum height. To support analyses that account for environmental variability, each observation is linked to detailed descriptors of the plot where the individual was sampled, including climate data, soil physicochemical properties, and disturbance regime. Full metadata on sampling protocols and measurement methods are provided for every trait and environmental variable. FAIRTraits was built in compliance with the FAIR principles of data management (Findable, Accessible, Interoperable, and Reusable). Metadata are described using the Ecological Metadata Language (EML); trait definitions are standardized using community-endorsed semantic resources. The data are archived across two interoperable repositories: GBIF (via Darwin Core and trait-specific extensions) for taxon-trait associations and InDoRES for environmental and contextual data. These efforts ensure long-term preservation, data traceability, and seamless integration with plant trait databases such as BROT or TRY, and cross-organism initiatives such as the Open Traits Network or the Encyclopedia of Life. FAIRTraits offers a robust, richly documented, and reusable resource for investigating plant functional strategies, trait-environment relationships, and scaling from individuals to communities and ecosystems. It also provides a concrete example of how trait datasets can meet the highest standards of data quality and interoperability-serving as a model for future community-led initiatives in functional ecology. The FAIRTraits database is released under the CC-BY Attribution 4.0 International license.
- Keywords
- FAIR principles, Mediterranean Biogeographic Region, biodiversity standards, ecosystem properties, environmental conditions, gas exchange, leaf, stem, root and reproductive traits, litter mass loss, phenology, plant functional traits, terminological resources, trait‐based ecology,
- MeSH
- Databases, Factual * MeSH
- Plant Physiological Phenomena * MeSH
- Plants * classification MeSH
- Publication type
- Journal Article MeSH
- Dataset MeSH
- Geographicals
- Mediterranean Region MeSH
Plant functional trait-based approaches are powerful tools to assess the consequences of global environmental changes for plant ecophysiology, population and community ecology, ecosystem functioning, and landscape ecology. Here, we present data capturing these ecological dimensions from grazing, nitrogen addition, and warming experiments conducted along a 821 m a.s.l. elevation gradient and from a climate warming experiment conducted across a 3,200 mm precipitation gradient in boreal and alpine grasslands in Vestland County, western Norway. From these systems we collected 28,762 plant and leaf functional trait measurements from 76 vascular plant species, 88 leaf assimilation-temperature responses, 577 leaf handheld hyperspectral readings, 2.26 billion leaf temperature measurements, 3,696 ecosystem CO2 flux measurements, and 10.69 ha of multispectral (10-band) and RGB cm-resolution imagery from 4,648 individual images obtained from airborne sensors. These data augment existing longer-term data on local climate, soils, plant populations, plant community composition, and ecosystem functioning from within the same experiments and study systems and from similar systems in other mountain regions globally.
- MeSH
- Ecosystem * MeSH
- Plant Physiological Phenomena * MeSH
- Climate Change * MeSH
- Plant Leaves MeSH
- Plants * MeSH
- Temperature MeSH
- Publication type
- Journal Article MeSH
- Dataset MeSH
- Geographicals
- Norway MeSH
Respiratory infections pose significant challenges to global health, impacting millions of individuals annually. Understanding the molecular mechanisms underlying the pathogenicity of these infections is crucial for developing effective interventions. RNA sequencing provides insights into a patient's global transcriptome changes, facilitating the identification of host gene signatures in response to infection and potential therapeutic targets. Here we present an extensive whole blood transcriptome dataset from a demographically diverse cohort of 502 patients with infections including COVID-19, seasonal coronavirus, influenza A or influenza B, sepsis, septic shock, and co-infections (Viral/Viral, Bacterial/Viral, Bacterial/Viral/Fungal, Viral/Fungal, Viral/ Viral/Fungal). The cohort size and depth of data showcase its potential to unravel respiratory infection pathogenesis for the development of better diagnostics, treatments, and preventive strategies for respiratory infections and future global health crises.
- MeSH
- Influenza, Human genetics MeSH
- COVID-19 genetics MeSH
- Respiratory Tract Infections * genetics blood virology MeSH
- Coinfection genetics MeSH
- Humans MeSH
- Transcriptome * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Dataset MeSH
Freshwater bivalves (FWB) are attracting scientific and societal attention given their essential ecosystem services, ecological functions, and poor conservation status. Current knowledge of the spatial distribution of West Palearctic FWB is poor preventing the understanding of biogeography and conservation planning. One of the priorities of the pan-European networking project "CONFREMU - Conservation of freshwater mussels: a pan-European approach" funded by the European Union, was to fill the knowledge gap on the distribution of FWB in Europe and adjacent regions. Based on the efforts of this network of scientists, we provide the most complete, taxonomically, and geographically accurate distribution of FWB species for the entire West Palearctic. The dataset contains 270,287 geo-referenced records of 93 native and 8 non-native FWB from 1674 to 2023. The dataset compiles information from private records from 82 specialists and multiple sources (e.g., published articles, grey literature, biodiversity databases, and scientific collections). This dataset, available online, represents an important data source for future studies on the biodiversity, biogeography, and conservation of these important organisms.
- MeSH
- Biodiversity MeSH
- Ecosystem MeSH
- Bivalvia * MeSH
- Animal Distribution * MeSH
- Fresh Water MeSH
- Conservation of Natural Resources MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Dataset MeSH
- Geographicals
- Europe MeSH
Psychological studies on close relationships have often overlooked cultural diversity, dynamic processes, and potentially universal principles that shape intimate partnerships. To address the limited generalizability of previous research and advance our understanding of romantic love experiences, mate preferences, and physical attractiveness, we conducted a large-scale cross-cultural survey study on these topics. A total of 404 researchers collected data in 45 languages from April to August 2021, involving 117,293 participants from 175 countries. Aside from standard demographic questions, the survey included valuable information on variables relevant to romantic relationships: intimate, passionate, and committed love within romantic relationships, physical-attractiveness enhancing behaviors, gender equality endorsement, collectivistic attitudes, personal history of pathogenic diseases, relationship quality, jealousy, personal involvement in sexual and/or emotional infidelity, relational mobility, mate preferences, and acceptance of sugar relationships. The resulting dataset provides a rich resource for investigating patterns within, and associations across, a broad range of variables relevant to romantic relationships, with extensive opportunities to analyze individual experiences worldwide.
- MeSH
- Adult MeSH
- Interpersonal Relations MeSH
- Love * MeSH
- Humans MeSH
- Marriage * MeSH
- Surveys and Questionnaires MeSH
- Sexual Behavior * MeSH
- Sexual Partners * psychology MeSH
- Cross-Cultural Comparison * MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Dataset MeSH
Cultivar Désirée is an important model for potato functional genomics studies to assist breeding strategies. Here, we present a haplotype-resolved genome assembly of Désirée, achieved by assembling PacBio HiFi reads and Hi-C scaffolding, resulting in a high-contiguity chromosome-level assembly. We implemented a comprehensive annotation pipeline incorporating gene models and functional annotations from the Solanum tuberosum Phureja DM reference genome alongside RNA-seq reads to provide high-quality gene and transcript annotations. Additionally, we provide a genome-wide DNA methylation profile using Oxford Nanopore reads, enabling insights into potato epigenetics. The assembled genome, annotations, methylation and expression data are visualised in a publicly accessible genome browser, providing a valuable resource for the potato research community.
