Leif Schulman

Temperature plays a pivotal role in defining the distribution of species and the fitness of individuals within species' ranges. Phenotypic plasticity can allow individuals to cope with varying environmental conditions, including rapid climate change. Populations at range edges experience more variable conditions than core populations and thus are hypothesized to exhibit higher thermal plasticity. However, as the strength of plasticity often varies between individuals, it can also differ among local populations at range edges. We studied the extent of and variation in thermal plasticity for several traits within and between populations of the perennial herb Plantago lanceolata L. (Plantaginaceae) at its northern range edge. We sampled seeds from nine sites within a 50 × 50 km region and grew them under three temperature regimes in a greenhouse. We measured traits related to size, flowering, pathogen responses, and inflorescence pigmentation. We expected to find higher plasticity in traits less strongly connected to fitness and that differences between individuals would outweigh differences between populations in underpinning this variation in plasticity. Our results show thermal plasticity in leaf size and abundance, flowering probability and abundance, and pigmentation. Notably, we also found increased pathogen symptoms and higher infection rates of one of two viruses screened, highlighting the potential for changes in pathogen sensitivity and exposure under climate change. Importantly, in all traits but flower abundance, more variation in plasticity was attributable to differences within populations than between populations. Although this contribution was small in magnitude compared to thermal effects on traits, the higher intra‐ versus interpopulation variation in plasticity suggests that differences between individuals provide most of the variation in thermal plasticity, which may be driven by small‐scale variations in habitat conditions, highlighting the need for conservation strategies that consider microhabitat variation to support short‐term adaptive responses to thermal variability.

The landscape of biodiversity data infrastructures and organisations is complex and fragmented. Many occupy specialised niches representing narrow segments of the multidimensional biodiversity informatics space, while others operate across a broad front, but differ from others by data type(s) handled, their geographic scope and the life cycle phase(s) of the data they support. In an effort to characterise the various dimensions of the biodiversity informatics landscape, we developed a framework and dataset to survey these dimensions for ten organisations (DiSSCo, GBIF, iBOL, Catalogue of Life, iNaturalist, Biodiversity Heritage Library, GeoCASe, LifeWatch, eLTER ELIXIR), relative to both their current activities and long-term strategic ambitions. The survey assessed the contact between the infrastructure organisations by capturing the breadth of activities for each infrastructure across five categories (data, standards, software, hardware and policy), for nine types of data (specimens, collection descriptions, opportunistic observations, systematic observations, taxonomies, traits, geological data, molecular data and literature) and for seven phases of activity (creation, aggregation, access, annotation, interlinkage, analysis and synthesis). This generated a dataset of 6,300 verified observations, which have been scored and validated by leading members of each infrastructure organisation. The resulting data allow high-level questions about the overall biodiversity informatics landscape to be addressed, including the greatest gaps and contact between organisations.

The landscape of biodiversity data infrastructures and organisations is complex and fragmented. Many occupy specialised niches representing narrow segments of the multidimensional biodiversity informatics space, while others operate across a broad front but differ from others by data type(s) handled, their geographic scope and the life cycle phase(s) of the data they support. In an effort to characterise the various dimensions of the biodiversity informatics landscape, we developed a framework and dataset to survey these dimensions for ten organisations (DiSSCo, GBIF, iBOL, Catalogue of Life, iNaturalist, Biodiversity Heritage Library, GeoCASe, LifeWatch, eLTER, ELIXIR), relative to both their current activities and long-term strategic ambitions. The survey assessed the contact between the infrastructure organisations by capturing the breadth of activities for each infrastructure across five categories (data, standards, software, hardware and policy), for nine types of data (specimens, collection descriptions, opportunistic observations, systematic observations, taxonomies, traits, geological data, molecular data, and literature), and for seven phases of activity (creation, aggregation, access, annotation, interlinkage, analysis, and synthesis). This generated a dataset of 6,300 verified observations, which have been scored and validated by leading members of each infrastructure organisation. The resulting data allows high-level questions about the overall biodiversity informatics landscape to be addressed, including the greatest gaps and contact between organisations.

The Finnish Biodiversity Information Facility (FinBIF) Research Infrastructure (Schulman et al. 2021) is a national service with a broad coverage of the components of biodiversity informatics (Bingham et al. 2017). Data flows are managed under a single information technology (IT) architecture. Services are available in a single, branded on-line portal. Data are collated from all relevant sources e.g., research institutes, scientific collections, public authorities and citizen science projects, whose data represent a major contribution. The challenge is to analyse, classify and share good quality data in a way that the user understands its utility. Need for quality data The philosophy of FinBIF is that all observation records are important, and that all data are assessed for quality and able to be annotated. The challenge is that, in practice, many users desire data with 100% reliability. In our experience, most user concerns about data quality are related to citizen science data. Researchers are usually able to manage raw data to serve their purposes. However, decision-making authorities often have less capacity to analyse the data and thus require data that can be used instantly. Therefore, we need tools to provide users the data that are the most relevant and reliable for their specific use. For all users, standardized metadata (information about datasets) are key, when the user has doubts about the fitness-for-use of a particular dataset. There is also a need to provide data in different formats to serve various users. Finally, the service has to be machine-actionable (using an application programming interface (API) and R-package) as well as human-accessible for viewing and downloading data. Quality assignment FinBIF data accuracy varies significantly within and between datasets, and observers. Two quality-based classifications suitable for filtering are therefore applied. The dataset origin filter is based on the quality of a whole dataset (e.g. citizen science project) and includes three broad classes assigned with an appropriate quality label: Datasets by Professionals, by Specialists and by Citizen Scientists. The observation reliability filter is based on a single observation and on annotations by FinBIF users. This classification includes Expert verified, Community verified, Unassessed (default for all records), Uncertain, and Erroneous. The dataset origin does not necessarily determine the quality of the individual records in it. Observations made by citizen scientists are often accurate, while there may be errors in the professionally collected data. Records are frequently subject to annotation, which raises their quality over time (e.g., iNaturalist). Naturally, evidence (e.g., media, detailed descriptions, specimens) is needed for reliable identification. Annotating data When observations are compiled at FinBIF’s portal (Laji.fi), they are initially “Unassessed” (unless they have otherwise been assessed at the original source). When annotating occurrences, volunteers can make various entries using the tools provided. The aim of the commentary is to improve the quality of the observation data. Annotators are divided into two categories with two different roles: As a basic user, anyone who has logged in at Laji.fi can make comments or tag observations for review by experts. Users defined as experts have wider rights than basic users and their comments carry more weight. The most desired actions of expert users are to classify observations into confidence levels or to give them new or refined identifications. As a basic user, anyone who has logged in at Laji.fi can make comments or tag observations for review by experts. Users defined as experts have wider rights than basic users and their comments carry more weight. The most desired actions of expert users are to classify observations into confidence levels or to give them new or refined identifications. Information about new comments passes to the observer if the observation is recorded by using the FinBIF Observation Management System “Notebook”. However, comments cannot yet be automatically forwarded e.g., to the primary data management systems at the original source. Annotations add extra indications of quality. They do not replace or delete the original information. Nevertheless, annotations can change a record’s taxonomic identification, and by default, a record will be handled based on its latest identification. R-package for researchers and Public Authority Portal (PAP) for decision makers FinBIF has produced an R programming language interface to its API, which makes the publicly available data in FinBIF accessible from within R. For authorities, the PAP offers direct access to all available species information to authorised users, including sensitive and restricted-use data.

In an effort to characterise the various dimensions of activity within the biodiversity informatics landscape, we developed a framework to survey these dimensions for ten major organisations*1 relative to both their current activities and long-term strategic ambitions. This survey assessed the contact between these infrastructure organisations by capturing the breadth of activities for each infrastructure across five categories (data, standards, software, hardware and policy), for nine types of data (specimens, collection descriptions, opportunistic observations, systematic observations, taxonomies, traits, geological data, molecular data, and literature), and for seven phases of activity (creation, aggregation, access, annotation, interlinkage, analysis, and synthesis). This generated a dataset of 6,300 verified observations, which have been scored and validated by leading members of each infrastructure organisation. In this analysis of the resulting data, we address a set of high-level questions about the overall biodiversity informatics landscape, looking at the greatest gaps, overlap and possible rate-limiting steps. Across the infrastructure organisations, we also explore how far each is in relation to achieving its ambitions and the extent of its niche relative to other organisations. Our results show that when viewed by scope, most infrastructures occupy a relatively narrow niche in the overall landscape of activity, with the notable exception of the Global Biodiversity Information Facility (GBIF) and possibly LifeWatch. Niches associated with molecular data and biological taxonomy are very well filled, suggesting there is still considerable room for growth in other areas, with the Distributed System of Scientific Collections (DiSSCo) and the Integrated European Long-Term Ecosystem Research Infrastructure (eLTER RI) showing the highest levels of difference between their current activities and stated ambitions, potentially reflecting the relative youth of these organisations. iNaturalist, the Biodiversity Heritage Library and Catalogue of Life all occupy narrow and tightly circumscribed niches. These organisations are also amongst the closest to achieving their stated ambitions within their respective areas of activity. The largest gaps in infrastructure activity relate to the development of hardware and standards, with many gaps set to be addressed if the stated ambitions of those surveyed come to fruition. Nevertheless, some gaps persist, outlining a potential role for this survey as a planning tool to help coordinate and align investment in future biodiversity informatics activities. GBIF and LifeWatch are the two infrastructures where there is the most similarity in ambition with DiSSCo, with the greatest overlap concentrated on activities related to data/content, specimen data and their shared ambition to interlink information. While overlap appears intense, the analysis is limited by the resolution of the survey framework and ignores existing collaborations between infrastructures. In addition to presenting the results of this survey, we outline our plans to publish this work and a proposal to develop the methodology as an interactive web-based tool. This would allow other projects and infrastructures to self-score their activities and visualise their niche within the current landscape, encouraging better global alignment of activities. For example, our results should make it easier for initiatives to strengthen collaboration and differentiate work when their activities overlap. Likewise, this approach would be useful for funding agencies when targeting gaps in the informatics landscape or increasing the technical maturity of certain critical activities, e.g., to improve immature data standards. While no framework is perfect, we hope to encourage a dialogue on the potential for taking an algorithmic approach to community alignment and see this as a means of strengthening community cooperation when addressing problems that require global cooperation.

Biodiversity informatics has advanced rapidly with the maturation of major biodiversity data infrastructures (BDDIs), such as the Global Biodiversity Information Facility sharing unprecedented data volumes. Nevertheless, taxonomic, temporal and spatial data coverage remains unsatisfactory. With an increasing data need, the global BDDIs require continuous inflow from local data mobilisation, and national BDDIs are being developed around the world. The global BDDIs are specialised in certain data types or data life cycle stages which, despite possible merits, renders the BDDI landscape fragmented and complex. That this often is repeated at the national level creates counterproductive redundancy, complicates user services, and frustrates funders. Here, we present the Finnish Biodiversity Information Facility (FinBIF) as a model of an all-inclusive BDDI. It integrates relevant data types and phases of the data life cycle, manages them under one IT architecture, and distributes the data through one service portal under one brand. FinBIF has experienced diverse funder engagement and rapid user uptake. Therefore, we suggest the integrated and inclusive approach be adopted in national BDDI development.

The Paleontological Collection (PalCo) is one of partial collections of the Finnish Museum of Natural History Luomus. General principles and guidelines for the collections are defined in the General Collection Policy of Luomus. The PalCo Policy is subordinate to the General Collection Policy of Luomus, clarifying its content with reference to the special characteristics of the paleontological collections. The PalCo includes fossil plant, invertebrate and vertebrate specimens worldwide in scope and from all geologic ages to support Finnish research and educational projects. The coverage emphasizes Paleozoic and Quaternary specimens from Finland, the Baltic countries and Scandinavia. The PalCo Policy defines the purpose of the collections, the objectives, the distribution of responsibilities for collection management and maintenance in the organisation, and the principles of collection accumulation, preservation, accessibility and use.

The Genomic Resources Collection is a separate, independently managed part of the natural history collections of the Finnish Museum of Natural History Luomus specifically intended for consumptive research. The GRC policy deals with the materials that are archived for the very purpose of enabling the study of biological diversity at the genome level, DNA extractions of animal, fungal and plant specimens, and animal tissue samples stored deep-frozen for purposes of future DNA extraction. The GRC policy defines the purpose of the collections, the objectives and content of the procedures and activities related to them, the distribution of responsibilities for collection management and maintenance in Luomus, and the principles of collection accumulation, preservation and accessibility. The aim of the GRC is to store and loan genomic samples for research purposes. In taxonomic coverage the collection overlaps with all the taxonomically delimited specimen collections managed by the Zoology and Botany Units, but is distinguished as being directed to preserve the genomic (DNA) information irrespective of the phenotypic variation that are the focus of specimen collections. The GRC includes both Finnish and foreign samples, all legally and ethically obtained, mostly linked to a specimen voucher in the taxonomic collections. The GRC samples are documented and trackable in Luomus collections management system. In accordance with the Universities Act, the GRC belongs to the national natural science collections of Luomus. For their part, the GRC collection implement the mission of Luomus, which is to be “responsible for the preservation, accumulation and exhibition of the national natural history collections and for research and education relating to them”.

The Distributed System of Scientific Collections (DiSSCo) Research Infrastructure (RI) is presently in its preparatory phase. DiSSCo is developing a new distributed RI to operate as a one-stop-shop for the envisaged European Natural Science Collection (NSC) and all its derived information. Through mass digitisation, DiSSCo will transform the fragmented landscape of NSCs, including an estimated 1.5 billion specimens, into an integrated knowledge base that will provide interconnected evidence of the natural world. Data derived from European NSCs underpin countless discoveries and innovations, including tens of thousands of scholarly publications and official reports annually (supporting legislative and regulatory processes on sustainability, environmental change, land use, societal infrastructure, health, food, security, etc.); base-line biodiversity data; inventions and products essential to bio-economy; databases, maps and descriptions of scientific observations; educational material for students; and instructive and informative resources for the public. To expand the user community, DiSSCo will strengthen capacity building across Europe for maximum engagement of stakeholders in the biodiversity-related field and beyond, including industry and the private sector, but also policy-driving entities. Hence, it is opportune to reach out to relevant stakeholders in the European environmental policy domain represented by the European Environment Agency (EEA). The EEA aims to support sustainable development by helping to achieve significant and measurable improvement in Europe's environment, through the provision of timely, targeted, relevant and reliable information to policy-making agents and the public. The EEA provides information through the European Environment Information and Observation System (Eionet). The aim of this white paper is to open the discussion between DiSSCo and the EEA and identify the common service interests that are relevant for the European environmental policy domain. The first section describes the significance of (digital) Natural Science Collections (NHCs). Section two describes the DiSSCo programme with all DiSSCo aligned projects. Section three provides background information on the EEA and the biodiversity infrastructures that are developed and maintained by the EEA. The fourth section illustrates a number of use cases where the DiSSCo consortium sees opportunities for interaction between the DiSSCo RI and the Eionet portal of the EEA. Opening the discussion with the EEA in this phase of maturity of DiSSCo will ensure that the infrastructural design of DiSSCo and the development of e-Services accommodate the present and future needs of the EEA and assure data interoperability between the two infrastructures. The aim of this white paper is to present benefits from identifying the common service interests of DiSSCo and the EEA. A brief introduction to natural science collections as well as the two actors is given to facilitate the understanding of the needs and possibilities in the alignment of DiSSCo with the EEA.

The collection policy of the Finnish Museum of Natural History Luomus is hierarchically structured. General principles and guidelines are defined in the General Collections Policy. Subordinate to it, the collection policies for the individual sub-collections implement and specify these guidelines and instructions, considering the special nature of each sub-collection. The invertebrate collections policy in 2017 was the first sub-collection policy to observe this hierarchical structure, and was guided by the standards set by the European SYNTHESYS collections management self-assessment procedure. The invertebrate collections policy directs all activities related to the Luomus invertebrate collections (apart from DNA and tissue samples), which comprise the separately managed entomological collections (ca. 9 million specimens) and collections of other invertebrates (0.4 million). The policy defines the purpose of the collections, outlines the objectives and content of procedures and activities related to them, the division of responsibilities for the administration and care of the collections within the organisation, and the principles and practices for the acquisition, preservation, accessibility and use of the collections.