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BACKGROUND: Patterns of protective health behaviors, such as handwashing and sanitizing during the COVID-19 pandemic, may be predicted by macro-level variables, such as regulations specified by public health policies. Health behavior patterns may also be predicted by micro-level variables, such as self-regulatory cognitions specified by health behavior models, including the Health Action Process Approach (HAPA). PURPOSE: This study explored whether strictness of containment and health policies was related to handwashing adherence and whether such associations were mediated by HAPA-specified self-regulatory cognitions. METHODS: The study (NCT04367337) was conducted among 1,256 adults from Australia, Canada, China, France, Gambia, Germany, Israel, Italy, Malaysia, Poland, Portugal, Romania, Singapore, and Switzerland. Self-report data on cross-situational handwashing adherence were collected using an online survey at two time points, 4 weeks apart. Values of the index of strictness of containment and health policies, obtained from the Oxford COVID-19 Government Response Tracker database, were retrieved twice for each country (1 week prior to individual data collection). RESULTS: Across countries and time, levels of handwashing adherence and strictness of policies were high. Path analysis indicated that stricter containment and health policies were indirectly related to lower handwashing adherence via lower self-efficacy and self-monitoring. Less strict policies were indirectly related to higher handwashing adherence via higher self-efficacy and self-monitoring. CONCLUSIONS: When policies are less strict, exposure to the SARS-CoV-2 virus might be higher, triggering more self-regulation and, consequently, more handwashing adherence. Very strict policies may need to be accompanied by enhanced information dissemination or psychosocial interventions to ensure appropriate levels of self-regulation.

Over the past 70 years, the world has witnessed extraordinary growth in crop productivity, enabled by a suite of technological advances, including higher yielding crop varieties, improved farm management, synthetic agrochemicals, and agricultural mechanization. While this “Green Revolution” intensified crop production, and is credited with reducing famine and malnutrition, its benefits were accompanied by several undesirable collateral effects (Pingali, 2012). These include a narrowing of agricultural biodiversity, stemming from increased monoculture and greater reliance on a smaller number of crops and crop varieties for the majority of our calories. This reduction in diversity has created vulnerabilities to pest and disease epidemics, climate variation, and ultimately to human health (Harlan, 1972). The value of crop diversity has long been recognized (Vavilov, 1992). A global system of genebanks (e.g., www.genebanks.org/genebanks/) was established in the 1970s to conserve the abundant genetic variation found in traditional “landrace” varieties of crops and in crop wild relatives (Harlan, 1972). While preserving crop variation is a critical first step, the time has come to make use of this variation to breed more resilient crops. The DivSeek International Network (https://divseekintl.org/) is a scientific, not-for-profit organization that aims to accelerate such efforts.

Genetic diversity is key to crop improvement. Owing to pervasive genomic structural variation, a single reference genome assembly cannot capture the full complement of sequence diversity of a crop species (known as the ‘pan-genome’1). Multiple high-quality sequence assemblies are an indispensable component of a pan-genome infrastructure. Barley (Hordeum vulgare L.) is an important cereal crop with a long history of cultivation that is adapted to a wide range of agro-climatic conditions2. Here we report the construction of chromosome-scale sequence assemblies for the genotypes of 20 varieties of barley—comprising landraces, cultivars and a wild barley—that were selected as representatives of global barley diversity. We catalogued genomic presence/absence variants and explored the use of structural variants for quantitative genetic analysis through whole-genome shotgun sequencing of 300 gene bank accessions. We discovered abundant large inversion polymorphisms and analysed in detail two inversions that are frequently found in current elite barley germplasm; one is probably the product of mutation breeding and the other is tightly linked to a locus that is involved in the expansion of geographical range. This first-generation barley pan-genome makes previously hidden genetic variation accessible to genetic studies and breeding.

Genetic diversity is key to crop improvement. Owing to pervasive genomic structural variation, a single reference genome assembly cannot capture the full complement of sequence diversity of a crop species (known as the 'pan-genome'1). Multiple high-quality sequence assemblies are an indispensable component of a pan-genome infrastructure. Barley (Hordeum vulgare L.) is an important cereal crop with a long history of cultivation that is adapted to a wide range of agro-climatic conditions2. Here we report the construction of chromosome-scale sequence assemblies for the genotypes of 20 varieties of barley-comprising landraces, cultivars and a wild barley-that were selected as representatives of global barley diversity. We catalogued genomic presence/absence variants and explored the use of structural variants for quantitative genetic analysis through whole-genome shotgun sequencing of 300 gene bank accessions. We discovered abundant large inversion polymorphisms and analysed in detail two inversions that are frequently found in current elite barley germplasm; one is probably the product of mutation breeding and the other is tightly linked to a locus that is involved in the expansion of geographical range. This first-generation barley pan-genome makes previously hidden genetic variation accessible to genetic studies and breeding.

Biodiversity is more than just the diversity of living species. It includes genetic and phenotypic diversity of organisms, functional diversity, interactions and the diversity of populations and whole ecosystems. The recent Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) report confirmed that our planet experiences a rapid loss of biodiversity with dramatic consequences for mankind. Answers to scientifically and societal relevant questions can only be found based on the availability of data integrated from multiple sources and building on different knowledge domains in science and society. The FAIR data principles provide a framework towards such integration. To foster access to interoperable data, NFDI4BioDiversity focuses on the following six objectives: 1) Promoting research data management as an integral part of biodiversity research, 2) Enabling FAIRness of data, 3) Consolidating FAIRness with quality, 4) Embedding NFDI4BioDiversity into the (inter-)national landscape, 5) Addressing NFDI-wide cross-cutting topics and 6) Promoting collaborative governance, viability and sustainability of data infrastructure services and science. These objectives are implemented by the NFDI4BioDiversity work programme and its five task areas: Task Area 1 - Community engagement (2involve): This task area will integrate across different knowledge holders and take care of research data management requests related to biodiversity data. A large part of all species data is collected by volunteers in natural history societies, NGOs, museums and citizen science projects as well as collected by different authorities This task area includes 23 use cases with community-driven topics and cross-domain user groups. Task Area 2 - National and international networking (2connect): This task area ensures that any cross-domain activities and developments of NFDI4BioDiversity are coordinated and in-line with the overall development of the NFDI as well as inte

Biodiversity is more than just the diversity of living species. It includes genetic and phenotypic diversity of organisms, functional diversity, interactions and the diversity of populations and whole ecosystems. The recent Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) report confirmed that our planet experiences a rapid loss of biodiversity with dramatic consequences for mankind. Answers to scientifically and societal relevant questions can only be found based on the availability of data integrated from multiple sources and building on different knowledge domains in science and society. The FAIR data principles provide a framework towards such integration. To foster access to interoperable data, NFDI4BioDiversity focuses on the following six objectives: 1) Promoting research data management as an integral part of biodiversity research, 2) Enabling FAIRness of data, 3) Consolidating FAIRness with quality, 4) Embedding NFDI4BioDiversity into the (inter-)national landscape, 5) Addressing NFDI-wide cross-cutting topics and 6) Promoting collaborative governance, viability and sustainability of data infrastructure services and science. These objectives are implemented by the NFDI4BioDiversity work programme and its five task areas: Task Area 1 - Community engagement (2involve): This task area will integrate across different knowledge holders and take care of research data management requests related to biodiversity data. A large part of all species data is collected by volunteers in natural history societies, NGOs, museums and citizen science projects as well as collected by different authorities This task area includes 23 use cases with community-driven topics and cross-domain user groups. Task Area 2 - National and international networking (2connect): This task area ensures that any cross-domain activities and developments of NFDI4BioDiversity are coordinated and in-line with the overall development of the NFDI as well as inte