{"paper_id":"1adaa121-cd0e-446a-954e-c074aaf890e0","body_text":"Balancing the supply and demand for taxonomy: \nan analysis of European taxonomic capacity and \npolicy needs \n \nQuentin Groom1*, Melanie De Nolf1, Lina M. Estupinan-Suarez2,3, Sofie Meeus1 \n \n1. Meise Botanic Garden, Nieuwelaan 38, 1860 Meise, Belgium \n2. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig \nPuschstrasse 4,  04103 Leipzig, Germany \n3. Institute of Biology, Martin Luther University Halle-Wittenberg, Halle (Saale) 06108, \nGermany \n \n \n* Corresponding author  \ne-mail: quentin.groom@plantentuinmeise.be  \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nAbstract \nTaxonomy is a cornerstone of biological science and essential to biodiversity policy, yet it \nfaces persistent structural challenges collectively known as the “taxonomic impediment”. \nThese include limited capacity, uneven geographic and taxonomic coverage, and a \ndisconnect between the supply of expertise and its societal demand. In this study, we \npresent a meta-research analysis of taxonomic activity in Europe over the past decade, \ndrawing on publication metadata from OpenAlex, Wikidata, and GBIF. Using an open and \nreproducible workflow, we identify more than 31,000 authors affiliated with European \ninstitutions who have contributed to taxonomic publications, and we assess their taxonomic \nand institutional distribution. We explore how this supply of expertise compares with the \nkinds of demands that arise from European biodiversity policy, including legally binding \ninstruments such as the Birds and Habitats Directives and the Marine Strategy Framework \nDirective, as well as strategic initiatives focused on invasive alien species, crop wild \nrelatives, and species of conservation concern. Our results highlight clear imbalances in \ncapacity across taxonomic groups and regions, with some politically and ecologically \nsignificant taxa receiving comparatively little attention. This work illustrates how openly \navailable data can be used to evaluate taxonomic capacity and its alignment with policy \nneeds, and it provides a framework for others to adopt in support of more strategic planning \nand investment in taxonomy. \n \nKeywords: research prioritisation, taxonomic capacity, taxonomic expertise, bibliographic \nanalysis, IUCN Red List, invasive alien species, crop wild relatives, biodiversity policy \n \n1 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\n1. Introduction \nEvery day, species are disappearing from our planet at an alarming rate, yet our \nunderstanding of even the most basic building blocks of life remains incomplete. While the \n\"taxonomic impediment\" – the challenge of cataloguing Earth’s biodiversity – is often cited as \na primary obstacle and has been acknowledged by the Convention on Biological Diversity \n(Convention on Biological Diversity 2007), the reality is far more complex. The concept of a \n\"taxonomic impediment\" has been frequently discussed in relation to the various challenges \nthat impede progress in cataloguing Earth’s biodiversity. These include limited funding, a \nshortage of expert taxonomists, technological constraints, restricted data accessibility, and a \nlack of global collaboration and standardised methodologies (Ebach et al. 2011; Raposo et \nal. 2021; Engel et al. 2021). \nTaxonomy is a fundamental discipline of biology, it is essential for detailed communication \nabout the diversity of life. Taxonomists possess a wide range of skills, from applying \nnomenclature codes and identifying specimens to evaluating traits through microscopy, \nchemistry, and genetics. They are involved in teaching, identification, monitoring biodiversity, \nand generating new knowledge on evolution, form, and function (Boxshall 2020; \nLagomarsino & Frost 2020). Effective investment in taxonomy requires balancing the study \nof certain taxa, the discovery of new species, the focus on particular issues (e.g., invasive \nalien species), and the need for sound taxonomic foundations for applied research and \nconservation. \nIn this context, taxonomists have long complained about the evaluation of their work by the \nuse of publication citation and Impact Factors that fail to capture the true scientific and \nsocietal impact of their research (Krell 2002; Agnarsson & Kuntner 2007; Ebach et al. 2011). \nScientific citation practices fail to pick up the impact of describing new species and fail to \nrecognise the long shelf life of taxonomic research in comparison to the other sciences. Yet \nwhile taxonomists believe they are underappreciated, there seems to be little self-reflection \nby taxonomists on what impactful taxonomy really is: which taxa are most impactful to study, \nand what outputs of taxonomy are most useful to science and society? Public funders \ntypically prioritise societal and political needs when issuing calls for research funding, and \ninstitutions likely align their decisions on recruitment, discretionary funding, and \ninfrastructure investment with these perceived needs (Norn et al. 2024). These priorities can \nbe national, such as the development of a national biodiversity strategy, or global, in \nresponse to frameworks like the Global Biodiversity Framework (Convention on Biological \nDiversity 2022). \nFrom a public policy standpoint, species are not equally important (Czech et al. 1998); \ndecisions regarding funding and conservation efforts often prioritise species that directly \nimpact human wellbeing, such as those that cause or carry disease, or those that provide \nfood, energy, or other ecosystem services. The prioritisation of societal needs by public \nfunders therefore implicitly suggests that a \"gap-filling\" approach—the idea that taxonomy \nshould aim to describe every species on Earth, irrespective of the potential impact or \nusefulness of that knowledge—may not always align with strategic funding priorities. \nAlternatively, frameworks such as Sabatier's Advocacy Coalition Framework (ACF) (Sabatier \n1988) and the concept of co-production (Jasanoff 2004) suggest a dynamic, two-way \ninteraction between research and policy, an interaction that funders are increasingly trying to \n2 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nsupport (Tseng et al. 2022). Research is strategically used by competing coalitions to shape \npolicy agendas, while policy priorities, in turn, influence the research deemed relevant and \nfundable. This is paralleled in the case of scientific initiatives involving the general public and \ninvasive alien species. In this case a beneficial cycle can be created whereby \ncommunity-based data collection can directly inform policy decisions and policy needs can \ndrive public participation in scientific research (Groom et al. 2019). \nThere are numerous demands for taxonomy across various sectors of society and policy, \nmaking it challenging to evaluate all of them comprehensively. In this study, we focused on \nthe taxonomy needs that are relevant across Europe, aiming to provide insights for countries \nwithin the European Union, as well as neighbouring and affiliated nations. However, we \nrecognize the diverse national demands for taxonomy, which can vary significantly \ndepending on the predominant habitats within each country—such as marine, alpine, \nfreshwater, peatland, and karst environments. Additionally, these demands are influenced by \nhistorical connections to former colonies and their biodiversity, current links to overseas \nterritories, as well as by key industries like agriculture, forestry, and fisheries, and local \nenvironmental challenges such as pollution (Evans et al. 2013; Moersberger et al. 2024). \nWe particularly focus on policy areas with a clear need of taxonomic services, invasive alien \nspecies, crop wild relatives, conservation worthy species and specific policy instruments of \nthe European Union. For example, Since 2014 the European Union has legislated against a \nblacklist of invasive species that bans the trade and mandates the control of these species. \nWhile taxonomic knowledge is needed to positively identify these species, their names, and \ntheir scope, there are a much larger number of species that may become established in \nEuropean countries, and for which taxonomic expertise is needed to ensure rapid detection \nand potential eradication. For this reason we also used a list of species created in a horizon \nscanning exercise that used expert opinion to identify species that show invasiveness on \nother continents and may become established in Europe (Roy et al. 2019). \nThe IUCN Red List of Threatened Species (hereafter referred to as the Red List) is a critical \ntool for conservation policy, serving as a comprehensive repository of species assessments \nthat inform and shape conservation strategies worldwide (IUCN 2022, 2025). With its \ndetailed, species-level insights into the five primary drivers of biodiversity loss, the Red List \nis invaluable for policy initiatives like the EU Biodiversity Strategy for 2030, which seeks to \nhalve the number of Red List species impacted by invasive alien species (European \nCommission. Directorate General for Environment. 2021).  \nCrop wild relatives (CWR) are recognised as an irreplaceable genetic resource for the \nimprovement of crops (Heywood et al. 2007). Effective policies for crop wild relatives should \npromote their conservation, establishing national, regional, and global information systems, \nand developing mechanisms to prioritise conservation efforts, and should promote the \nintegration of CWR conservation and other conservation of plant genetic resources. \nThere are also specific legal instruments of the European Union such as the Birds Directive \n(Directive 2009/147/EC) which is one of the cornerstone legislative frameworks for \nbiodiversity conservation in the European Union. It aims to protect all wild bird species \nnaturally occurring in Europe by safeguarding their habitats, regulating hunting, and \nestablishing Special Protection Areas. The directive relies heavily on accurate species \n3 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nidentification and taxonomic clarity to inform conservation measures and reporting \nobligations. \nThe Habitats Directive (Directive 92/43/EEC) complements the Birds Directive by focusing \non the conservation of natural habitats, wild fauna, and flora across Europe. It underpins the \nNatura 2000 network of protected areas, requiring regular monitoring and assessment of \nspecies and habitat conditions. Taxonomic expertise is essential to the directive’s \nimplementation, particularly for less well-known taxa such as plants, invertebrates, and fungi \nlisted in the annexes. \nThe Marine Strategy Framework Directive (Directive 2008/56/EC) provides a framework for \nthe protection of the marine environment across Europe. It aims to achieve Good \nEnvironmental Status of the EU's marine waters, requiring comprehensive monitoring of \nmarine biodiversity. Reliable taxonomy is critical for assessing species diversity, detecting \ninvasive species, and evaluating ecosystem health indicators. \nMore recently the EU Pollinators Initiative addresses the decline of wild pollinating insects, \nespecially bees, hoverflies, and butterflies. While not a directive, it is an integral part of the \nEU Biodiversity Strategy for 2030 and influences agricultural policy and funding calls. Its \nsuccess depends on taxonomic accuracy to monitor pollinator populations, inform \nconservation actions, and support citizen science engagement. \nAddressing these challenges, this study examines policy areas with a clear need for \ntaxonomic services, including invasive alien species, crop wild relatives, and \nconservation-worthy species, within the framework of EU policy instruments. Building on the \nrecommendations from the European Red List of Insect Taxonomists (Hochkirch et al. 2022), \nwe broaden both the taxonomic and geographic scope, implementing an open and \nreproducible workflow to monitor capacity. Unlike previous studies that focus solely on \ntaxonomic capacity, our study takes a novel approach by examining the interplay between \ntaxonomic expertise and policy needs, using an open and reproducible workflow to assess \nthe alignment of taxonomic research with key policy areas in Europe. \nWe assessed the supply of taxonomists by analysing the authorship of taxonomic literature. \nTo do this, we developed an automated workflow that draws data from the APIs of three \nopen sources: \n● OpenAlex, a database that provides comprehensive metadata about academic \npublications, authors, institutions, and research topics to facilitate scholarly discovery \nand analysis. \n● Wikidata, a collaboratively edited knowledge base that provides structured data to \nsupport Wikimedia projects, and beyond, enabling data-driven applications and \nresearch. \n● The Global Biodiversity Information Facility (GBIF), an international network and data \ninfrastructure that provides access to data on observations of all types of life on \nEarth. \nThe objective of this study is to spark meaningful discussion about the future of taxonomic \nresearch and how it is prioritised. We aim to inspire dialogue on the evaluation and \n4 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nmonitoring of taxonomy, emphasizing the importance of balancing the supply and demand \nfor taxonomic expertise in planning, training, and recruitment for the field's future, informing \neffective resource allocation in a politically driven landscape. We also encourage others to \nreplicate our work in their own countries or regions, to compare and contrast their findings \nwith ours, contributing to a more evidence-based and politically informed approach to \nbiodiversity conservation. \n2. Materials and Methods \n2.1 Policy relevant data \nCrop wild relatives data for Europe were downloaded from the database of the Germplasm \nResources Information Network online database (USDA, Agricultural Research Service, \nNational Plant Germplasm System 2024). IUCN Red List of Threatened Species were \ndownloaded from their online database (IUCN 2025) selecting taxa for Europe and status of \nTaxonomic Research Needed. The full European Redlist was sourced from the European \nEnvironment Agency (European Environmental Agency 2019).  Invasive alien species on the \nhorizon for Europe were sourced from the supplementary data of (Roy et al. 2019). The list \nof European pollinator species was taken from Reverté et al. (2023). Species pertinent to the \nMarine Strategy Framework Directive were taken from (Palialexis & Boschetti 2021).  \nA primary challenge encountered during the analysis of EU biodiversity legislation was the \ndecentralised nature of information. Key data are distributed across various web portals, \nincluding those of the European Environment Agency (EEA), the European Nature \nInformation System (EUNIS), and other organisations. Consequently, retrieving essential \ninformation, such as the lists of species covered by the Nature Directives, was a \ntime-intensive undertaking. Furthermore, these sources are often not machine-readable and \nlack consistent identifiers that link to other taxonomic resources, complicating automated \ndata integration. As a result, these data are often difficult for web browsers to identify and \nare not consistently available in readily usable tabular formats. To facilitate reproducibility \nand further analysis, species lists used in the subsequent analyses, along with their \nassociated taxonomy, have been compiled into tabular format and made publicly available \non Zenodo (Estupinan-Suarez 2025). \n2.2 A workflow to identify European authors of taxonomic \narticles \nThe workflow we have created, firstly identifies taxonomic journals and extracts articles \npublished in them from the last 10 years. Secondly, it uses keywords in the title and abstract \nto identify those papers that are considered to be the work of taxonomists, whether or not \nthis was the main role of the author(s), or a subsidiary one. The resulting corpus of \ntaxonomic literature was then used to identify the institutional affiliation of the authors, \nrestricting it to institutions based in Europe1, and their taxonomic focus. Automatic \n1 European Political Community plus Vatican City, and the dependencies/territories of European \ncountries that themselves are in Europe.  \n5 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\ndisambiguation of authors with manual validation allowed us to avoid double counting of \nauthors. The workflow is largely written in Python (version 3.9.18) and made available on \nZenodo (De Nolf et al. 2025). Though to take advantage of the metacoder package (version \n0.3.7) heattree.R was written in R (version 4.3.2) (Foster et al. 2017). Additional R packages \ninclude gridExtra (2.3) and rcartocolor (2.1.1). The key Python packages required for these \nscripts to run are pandas (2.1.4), numpy (1.26.4), requests (2.31.0), geopandas (0.12.2), \nmatplotlib (3.9.2), seaborn (0.12.2), SPARQLWrapper (2.0.0), fiona (1.8.22), shapely (2.0.1). \n(i) Taxonomic journal selection \nWe used three methods to find journals that could contain taxonomic articles, from two \nsources: Wikidata and OpenAlex. We used the requests Python package to access their \nAPIs. Wikidata provides structured data by linking entities with unique Q numbers and their \nattributes or relationships using P numbers for properties. Using list_journal.py we searched \nfor all the scientific journals (Q5633421) or academic journals (Q737498) in Wikidata with \nproperties ‘main subject’ (P921) or ‘field of work’ (P101) linked to the items ‘taxonomy’ \n(Q8269924), ‘biological classification’ (Q11398), ‘plant taxonomy’ (Q1138178), ‘animal \ntaxonomy’ (Q1469725), ‘systematics’ (Q3516404), ‘biological nomenclature’ (Q522190), \n‘botanical nomenclature’ (Q3310776),  ‘zoological nomenclature’ (Q3343211), \n‘phylogenetics’ (Q171184) or ‘animal phylogeny’ (Q115135896). \nSimilarly, we downloaded all journal records from Wikidata with a property of ‘IPNI \npublication ID’ (P2008), or ‘ZooBank publication ID’ (P2007), meaning any journal with any \nof those IDs attached. Note that although IPNI is a resource on the names of vascular \nplants, the bibliographic details from IPNI also contain details of bryological, mycological and \nphycological journals. \nIn addition, we searched OpenAlex for all journals, referred to more broadly as 'sources' in \nOpenAlex, that are associated with the concept 'taxonomy' (C58642233) (Priem et al. 2022). \nIn OpenAlex each work is tagged with multiple concepts, based on the title, abstract, and the \ntitle of its host venue using an automated classifier that was trained on Microsoft Academic \nGraph’s corpus (Priem et al. 2022). Concepts for sources are generated from the most \nfrequently applied concepts to works hosted by this source. \nFor each journal we retained the display name (title), Wikidata ID, OpenAlex ID, ISSN, \nISSN-L, IPNI publication ID, ZooBank publication ID, dissolved status and dissolved year. \nJournals found through different methods but with the same Wikidata ID and OpenAlex ID, \nwere deduplicated. In the downstream analysis, the journals were accessed via OpenAlex, \nso any journal that lacked an OpenAlex ID could not be used. The Jupyter notebook \nJournals.ipynb provided can be used to examine the sources of the journals we discovered \n(Groom & Meeus 2025). \n(ii) Article selection \nWe used the OpenAlex API to request European articles from the preselected journals, \npublished between 2014 and 2023 inclusive. This meant searching for the OpenAlex journal \nID using the primary_location.source.id filter, selecting articles written by at least one author \naffiliated to an institution located in these European countries using the \n6 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nauthorships.countries filter and a list of European two-letter country codes, and setting the \nbegin and end dates to 2014-01-01 and 2023-12-31 in the configuration file. \nArticles were filtered for specific keywords to extract taxonomic articles. We selected these \nwords through an interactive refinement process. This involved two main steps: identifying \nand excluding articles unrelated to taxonomy, and finding and verifying that relevant articles \nwere included. This keyword filter searches the title and abstract for words such as \ntaxonomic, taxon, checklist, nov. (only in abstract), new species, novel species, new genus, \nand new genera and their translations in Bulgarian, Czech, French, German, Hungarian, \nItalian, Polish, Portuguese, Romanian, Russian, and Spanish. It also searched the concepts \nOpenAlex has associated with the article: taxonomy (C58642233) and taxon (C71640776). \nFinally, all articles were filtered to ensure they were part of the OpenAlex Life Sciences \ndomain (https://openalex.org/domains/1). \n(iii) Taxonomic processing \nIn `parse_taxonomy.py`, the filtered taxonomic articles were parsed for species names. \nSpecifically, the script uses regular expressions to search the title and abstract for word \ngroups that are capitalised like “Genus species”. Possible species names were matched to \nthe GBIF taxonomic backbone (GBIF Secretariat 2023): if the word group matched one of \nthe species names found in the backbone, it was saved and added as metadata to the \narticle. Additionally, the rest of the text was searched for other species of the same genus \nlike “G. species” and again matched to the backbone. \n(iv) Author processing and disambiguation \nOpenAlex provides a list of “authorships” for each article, containing for each author their \nname, IDs, institutions mentioned in the article, countries where they work, and much more. \n`get_authors.py` extracts the authors from the articles dataframe. This list of authors is \ndeduplicated based on the OpenAlex author ID. The algorithm finds articles with at least one \nEuropean author, but they may have collaborated internationally, so the authors are filtered \nto only include those with European affiliations. \nAlthough OpenAlex usually correctly assigns a single author ID to distinct individuals, it \nsometimes fails to detect duplicates, assigning multiple IDs to the same person. We resolved \nambiguities among possibly duplicated authors from taxonomic articles by considering their \nnames, affiliations and taxonomic group of expertise. We created a dataset of authors and \ngenerated simplified versions of their names: one consisting of their stripped names with \nspaces, periods and hyphens removed, and one consisting of their first initial and last name. \nWe then checked all authors with the same truncated name. Two authors are matched and \nconsidered to be the same person if one of two cases is true: either they have the exact \nsame stripped name and work at the same institution or they have the same truncated \nname, work at the same institution and work on the same taxonomic orders. If one of these \nmatches occurs the information from the two author entries are then merged to create a \nunified record. The final disambiguated list is saved for further analysis. Some authors (5% \nbefore deduplication) study taxa without order rank assigned in the GBIF taxonomic \nbackbone. To disambiguate them we used the family rank. The number of taxonomists was \ncorrelated with national population size sourced from the World Bank (World Bank 2024). \n7 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\n2.3 Collectors of specimens in Europe \nIndividuals who collected specimens are listed in the Darwin Core recordedBy-field, while \nthose who determined the taxonomic identity of the specimens are listed in the \nidentifiedBy-field. If this is the same person as mentioned in the recordedBy term the same \nname may be used in the identifiedBy-field, or this field is often left blank. These fields \ncontain names of people as an uncontrolled text string that may contain the name of an \nindividual, an organisation, expedition, or multiple individuals. We use a count of the unique \nrecordedBy and identifiedBy as an indication of the number of actual people involved in \nrecording and identifying biodiversity in a country. \nAggregated counts of distinct recordedBy and identifiedBy fields were extracted from GBIF \nusing a SQL command querying the occurrence data to calculate, for each European \ncountry, the total number of records, the number of distinct observers (recordedBy), and the \nnumber of distinct identifiers (identifiedBy). We included only records with an \noccurrenceStatus of \"PRESENT\", excluded records flagged with the \nCOUNTRY_COORDINATE_MISMATCH issue, and restricted the dataset to the years 2014 \nto 2023. The results were grouped by country (countryCode) and sorted in ascending order. \n2.4 Analysis \nTo investigate the influence of biodiversity policies and species richness of orders on the \nnumber of authors involved in taxonomic research, we conducted a robust statistical analysis \n(Seabold, Skipper & Perktold 2010). The predictor variables are the number of named \nspecies in each order of plants, fungi and animals, and the number of species named in \neach policy. We began by log-transforming both predictor variables (policies and species \nrichness of orders) and the response variable (number of authors) using the natural \nlogarithm (log(x + 1)) to stabilise variance and improve normality. \nNumbers of described species in each taxonomic order were calculated from the GBIF \nTaxonomic Backbone (GBIF Secretariat 2023). This was done by counting the number of \naccepted species in the Backbone for each order. \nWe fitted two regression models using Robust Linear Models (RLM) with Huber's T norm to \nmitigate the influence of outliers: 1) A combined model that included species richness and \npolicy-related variables: 'taxonomicResearchNeeded', 'cropWildRelatives', 'iasListConcern', \n'horizonInvasives', 'habitatsDir', 'marineDir', 'redlistFull', 'birdDir', and 'pollinators'. 2) A \nreduced model including only species richness. \nTo assess the significance of policy predictors collectively, we compared the two models \nusing an F-test. We evaluated model assumptions by visually inspecting residuals through \nscatterplots and Q-Q plots and conducting a Shapiro-Wilk normality test on residuals. \nFinally, we identified the top residual outliers from the robust model to explore taxa that \ndeviated notably from the model predictions, potentially highlighting additional unmeasured \nfactors influencing research effort. The Python code for the statistical analysis can be found \nin (De Nolf et al. 2025). \n8 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\n3. Results \n3.1 Demands from biodiversity policy for taxonomists \n(i) Species of conservation concern \nOf the 13,918 European species on the Red List, 13.4% (1,866 species) have been \nclassified by assessors with the status of Taxonomic Research Needed indicating issues \nwith species delimitation. Among these, 4.5% are critically endangered (83 species), 8.1% \nendangered (152 species), and 10.3% vulnerable (193 species) (IUCN 2025). Additionally, \n13.3% (1850 species) of the European species on the Red List are classified as Data \nDeficient. A data deficient species lacks sufficient information for a proper conservation \nassessment, often due to a lack of data on its abundance, distribution, or taxonomy.  \nTaxonomically, the plant species in the Taxonomic Research Needed classification are \nprimarily from Tracheophyta (Magnoliopsida, Liliopsida), and Bryophyta, with minimal \nrepresentation of algal groups (Fig. 1). In the case of animals, Gastropoda, Insecta, and \nActinopterygii are the key groups, while classes like Clitellata, Echinodermata, and \nPlatyhelminthes are apparently underrepresented (Fig. 1). Few fungal species (N=77) are in \nthe Taxonomy Research Needed category, and these are largely from the Agaricomycetes. \nSimilarly, the EU Biodiversity Strategy for 2030’s European Red List of Species highlights \nplants mainly from Magnoliopsida and animals primarily comprising vertebrates, Gastropoda, \nand Insecta (Fig. 1, Table 1).  \n(ii) European crop wild relatives list \nFive hundred and twenty-four species of crop wild relatives are listed for Europe (USDA, \nAgricultural Research Service, National Plant Germplasm System 2024). The most \nspecies-rich genera are listed in Table S1 which consist of 43% of all crop wild relatives and \nthese come from only five families Fabaceae, Brassicaceae, Poaceae, Rosaceae and \nAmaryllidaceae. Among those are relatives of staples like wheat, forage crops like alfalfa, oil \ncrops like rape and fruits, such as peach. Therefore, even within the vascular plants these \nplants are narrow in taxonomic scope. \n(iii) Invasive alien species \nRoy et al. (2019) identified 120 species in a horizon scan for invasive species in Europe, and \nthese were ranked from medium to very high likelihood of establishment (Fig. 1). Among \nplants these are mainly in the Magnoliopsida and Lilopsida, though there are only 25 plants \nin the whole list. The animals included are from a wide variety of classes and orders \nincluding Insecta, Mollusca, Actinopterygii, Aves, Mammalia and Ascidiacea. \nAlso relevant is the Invasive Alien Species Regulation of the European Union (Regulation \n(EU) 1143/2014) (Table 1) which features a nearly equal representation of plants (41 \nspecies) and animals (47 species). The animals are mostly vertebrates, such as fish, birds, \nand mammals, and the plants are mostly Tracheophyta. \n9 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nThere are also a total of 9237 non-native species recorded in the European Union (Seebens \n2016; Haubrock et al. 2023). \n(iv) Species listed in European Union directives \nThe species listed in the Birds Directive, Habitats Directive and Marine Strategy Framework \nDirective largely focus on vertebrates, such as mammals, fish and birds, though the Habitats \nDirective does list some fungi and vascular plants (Table 1). The main taxonomic focus of \nthe Pollinators Initiative are Bees (Anthophila) and hoverflies (Syrphidae) and butterflies \n(Papilionoidea). \n3.2 The supply of taxonomic expertise \n(i) Workflow results \nOf the 2,686 journals identified, we focused on the 1,103 journals with OpenAlex IDs (Table \n2). However, only 474 of these journals were represented in the selected articles of \nEuropean affiliated authors. This discrepancy arises because approximately 24% of the \njournals identified had dissolved before our period of interest, while many others have \nceased publication but lack dissolution records in Wikidata. In a sample of 50 journal titles \nwith no OpenAlex ID and no dissolved date, 41 were in fact no longer publishing, and others \nwere unrelated to the biogeography of Europe, such as Sansevieria and the University of \nWyoming Publications in Science. Botany. Only one journal from this sample had articles \nwhich could have been included if it had an OpenAlex ID; this was the Atti della Società \nToscana di Scienze Naturali, Memorie, Serie B (Table 2). Most (92%) journals were uniquely \nidentified through their IPNI or Zoobank ID. OpenAlex concepts (4.2%) and Wikidata \nsubjects (1.0%) identified a small number of additional journals uniquely. \nSearching these journals in OpenAlex resulted in 33,499 articles with at least one author \nwith at least one European affiliation.  A word cloud (Fig. S1) visualises the most common \nwords occurring in the title and abstract of the articles found. In a random sample of 200 \narticles, we only found four articles that were not considered taxonomic in scope or 2%. \nWe identified 31,839 European authors, each with a unique OpenAlex ID, associated with \ntaxonomic articles. Following disambiguation, this number was reduced to 31,521. A \nsaturation curve of authors from those journals showed that further addition of journals was \nunlikely to significantly increase the number of publishing taxonomists we could identify (Fig. \nS2). A sample of 200 authors, all with the same truncated name format (first initial and last \nname), was reviewed. Among these, 21 authors were merged by the system, and all \nmergers were deemed appropriate upon manual verification. However, nine pairs of names \n(4.5%) were not merged by the system, despite manual checks confirming they referred to \nthe same individual. Authors with the same truncated names accounted for only 10% of all \nauthors in the dataset. Consequently, the estimated total number of authors inadvertently \nincluded was less than 0.5%. While this may lead to a slight overestimation in the number of \ntaxonomists, we deemed this acceptable within the scope of the analysis. \n10 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\n(ii) Taxonomic expertise \nWhere an author was able to be linked to a specific kingdom i.e. in 57% of the cases, 59.3% \npublished on Animalia, 38.0% on Plantae and 12.5% on Fungi. Seventeen percent had \npublished on more than one kingdom. The ten most frequently studied families, based on the \nnumber of published articles, were Asteraceae (400 articles), Staphylinidae (311), Fabaceae \n(297), Orchidaceae (297), Poaceae (262), Scarabaeidae (173), Curculionidae (168), \nLamiaceae (150), Erebidae (145), and Caryophyllaceae (139) (Fig. S3). \nPlant taxonomists focus largely on vascular plants, largely the Magnolopsida, Liliopsida and \nthe Pinopsida (Fig 2). Animal taxonomists have perhaps more diverse interests, but are \nmainly focused on vertebrates and insects. Many diverse groups of invertebrates are poorly \nstudied (Fig 2). Fungal taxonomists are dispersed across the kingdom, but not evenly. In the \nBasidiomycota the Agaricomycetes are most studied. Taxonomists are widely distributed \nacross the Ascomycota, some in lichenizing groups such as the Lecanoromycetes, and \nArthoniomycetes, other classes include numerous plant pathogens, such as \nDothideomycetes, Sordariomycetes and Eurotiomycetes. \n(iii) Geographic distribution \nIn Europe there is a clear east-west divide in the number of taxonomists (Fig 3A). However, \nas the number of taxonomists is strongly correlated with the population size of the country \n(Pearson r = 0.8640; p < 0.001; Fig. S4) on a per capita basis this division is weaker (Fig \n3B). On a per capita basis, Iceland, Estonia, Norway and the Czech Republic, Switzerland \nand Portugal stand out as having a high proportion of taxonomists. While the number of \ntaxonomists in a country will depend on many factors, we do see a strong correlation with \nthe population of that country. As the collecting of voucher specimens is also an important \naspect of professional taxonomy we also examined the number of unique collector and \nidentifier strings and their distribution in Europe. Unlike article authors it is not possible to \ndetermine the affiliation of collectors, only where the specimens were collected. \nNevertheless, a similar pattern to author affiliation was found, with eastern countries having \napparently fewer collectors and identifiers identified (Fig. S5). \n \n3.3 The relation between the number of named taxa, policies \nand taxonomists \nThe robust regression analysis revealed significant associations between species richness, \nbiodiversity policies, and the number of authors involved in taxonomic research (Fig. S6). In \nthe species-only model, species richness alone demonstrated a highly significant positive \nrelationship with the number of authors (β = 0.662, p < 0.001). However, when biodiversity \npolicy variables were included in the combined model, the strength of this relationship \ndecreased (β = 0.471, p < 0.001), indicating that policy variables explained additional \nvariance previously attributed solely to species richness. \n \nSpecific biodiversity policies independently influencing taxonomic research included explicit \ntaxonomic research needs (β = 0.541, p < 0.001), the Habitats Directive (β = 0.348, p = \n11 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\n0.003), and the Birds Directive (β = 0.369, p = 0.041). Marine-related policies exhibited a \nnegative but significant effect (β = -0.273, p = 0.038). Other policy variables, such as crop \nwild relatives, the IAS list of Concern, invasive species on the horizon, Red Listed species, \nand pollinators, did not reach statistical significance individually (p > 0.05) (Fig. S7). \n \nAn F-test comparing the combined model with the species-only model confirmed that \nbiodiversity policies significantly improved the model’s explanatory power (p < 0.05), \nunderscoring the collective importance of policy factors beyond species richness alone. \n \nResidual diagnostics indicated deviation from normality (Shapiro-Wilk test, p < 0.001). While \nthis suggests a violation of the normality assumption, robust regression methods such as \nthose used in this analysis (RLM with Huber's T norm) are designed to mitigate the impact of \nnon-normal residuals. Consequently, the deviation from normality observed here is unlikely \nto substantially affect the validity of our conclusions. Nevertheless, the examination of top \nresidual outliers highlighted taxa potentially influenced by additional unmeasured factors, \nsuggesting avenues for future investigation. The Durbin-Watson test result (1.975) confirmed \nthat there was no significant autocorrelation among residuals, indicating independence of \nobservations. \n \nHowever, the Breusch-Pagan test for heteroscedasticity was highly significant (test statistic = \n309.45, p < 0.001), suggesting that residual variance is not constant across predicted \nvalues. This finding indicates that some variables may exert disproportionate effects across \ndifferent taxonomic groups. While robust regression reduces sensitivity to heteroscedasticity, \nthis remains a limitation of the model. Further exploration of transformations or stratified \nanalyses may be required in future research. \n \nDespite these limitations, the overall model results provide strong evidence that biodiversity \npolicy is related to taxonomic research effort, beyond what can be explained by species \nrichness alone. \n4. Discussion \nThe IUCN Red List, a cornerstone of conservation policy, exemplifies the critical need for \ntaxonomic precision. It identifies a substantial proportion of European species requiring \nfurther taxonomic study, particularly among plants such as Tracheophyta and animals \nincluding Gastropoda and Insecta. Taxonomic assessments of these threatened species are \nessential for achieving targets like the EU Biodiversity Strategy’s goal to reduce the impact \nof invasive alien species on vulnerable taxa. However, significant gaps in taxonomic \nexpertise remain for fungi, algae, and non-insect invertebrates. While policies such as the \nEU Soil Strategy for 2030, Marine Strategy Framework Directive, and Habitats Directive may \ncontribute to endangered species conservation, they fall short of fostering a deeper \nunderstanding of their taxonomy and conservation status. There is a catch-22 whereby rare \nspecies are not assessed because there is no one to study them, and there is no one to \nstudy them because there is no conservation policy driver until they are assessed. A positive \nexample that broke this cycle was a specific focus on Bryophytes in the Research Needed \ncategory in European red-lists which is likely the result of a targeted project from a large \ngroup of dedicated bryologists, funded at least in part through the LIFE project of the \n12 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nEuropean Commission, not necessarily a prior conservation priorities (Hodgetts 2019). A \nclear case of a known knowledge gap being addressed by funding and potentially leading to \nimproved conservation outcomes. \nFor invasive alien species, the demands are equally pressing. Horizon scans and the EU \nInvasive Alien Species Regulation prioritize taxonomic clarity for a diverse range of taxa, \nparticularly vertebrates and vascular plants. With over 9,000 non-native species recorded in \nEurope, accurate identification is essential for effective management (Seebens 2016). \nSimilarly, crop wild relatives demand taxonomic attention, especially within economically \nsignificant families. These taxa underpin agricultural resilience and food security, highlighting \nthe necessity of robust taxonomic frameworks to guide conservation (Heywood et al. 2007). \nLegal instruments like the EU Birds Directive, Habitats Directive, and Marine Strategy \nFramework Directive predominantly focus on vertebrates but extend to select fungi and \nvascular plants. Taxonomic expertise is essential for compliance, monitoring, and \nbiodiversity protection (Stephenson et al. 2022). Additionally, the EU Pollinators Initiative, \nwhile not a directive, underscores the critical role of taxonomy in supporting pollinator \nconservation efforts, focusing on groups such as bees, hoverflies, and butterflies. \nTherefore overall in the policy landscape, groups including vertebrates, vascular plants, and \nsome insect groups receive substantial attention. The question then is, are these policy \ndemands met by the supply of taxonomists, and if so is it the policies that drive the demand \nfor taxonomy, or the taxonomists that lead the formulation of policy? \nOur automated, reproducible workflow demonstrates the potential for large-scale systematic \nassessments of taxonomic capacity or the “supply of taxonomists” using open bibliographic \nresources. This kind of capacity assessment has been identified by the Convention on \nBiological Diversity (CBD) and its Global Taxonomy Initiative (GTI) as a critical foundation for \neffective biodiversity policy implementation (Convention on Biological Diversity 1998). The \nworkflow supports not only global analyses but can also be adapted to address the specific \nchallenges and priorities of particular regions or taxonomic groups, offering tailored metrics \nfor national and institutional reporting. As compared to manual methodologies for \ninventorizing taxonomic capacity, often limited in taxonomic and/or geographical scope (e.g. \nColl et al., 2010; Hochkirch et al., 2022; Páll-Gergely et al., 2024), standardised \nmethodologies like this ensure that trends in authorship, focus, and capacity are monitored \nover time, providing a robust evidence base for decision-making in biodiversity conservation, \nresource allocation, and strategic planning. \nOur workflow identifies a large number of taxonomic journals, articles, and their associated \nauthors. OpenAlex, the bibliographic resource we rely on, claims to have about twice the \ncoverage of comparable services, including better representation of non-English works \n(https://docs.openalex.org/). While we cannot claim to achieve complete \ncoverage—especially given the minimal restrictions on where taxonomic acts can be \npublished—our focus is on mainstream, peer-reviewed journals where most professional \ntaxonomists in Europe publish. Also, while errors do exist in the used open resources—just \nbecause they are open—these errors are visible, and in the case of Wikidata, directly \ncorrectable by users. OpenAlex and the Taxonomic Backbone are not directly editable but \nare dynamic and incorporate user feedback. \n13 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nThe results of our workflow reveal an uneven geographic distribution of taxonomic expertise \nin Europe, with northern and western regions hosting the majority of taxonomists. Even on a \nper capita basis, eastern European countries have fewer taxonomists, though countries like \nEstonia, the Czech Republic, and Portugal stand out for their high concentration of \ntaxonomists relative to their population. \nAmong plant taxonomists the focus is on vascular plants, especially large and economically \nsignificant families. Conversely, groups like algae (particularly microalgae) remain \nunderstudied despite their taxonomic diversity. Among animals, vertebrates and insects \nreceive the most attention, whereas aquatic non-insect invertebrates are noticeably \nunderserved. For example, there are few taxonomists for phyla as Annelida, Brachiopoda, \nCnidaria and Porifera. Many fungal groups are particularly underrepresented despite their \necological and economic importance. For example, fungal taxonomy is concentrated in a few \nclasses like Agaricomycetes (Basidiomycota) and some plant-pathogenic Ascomycota. \nTaxonomy operates in a publicly funded, non-market-driven system where supply and \ndemand are not tightly coupled. Instead, taxonomic capacity is determined by institutional \npriorities and funding availability, often influenced by decision makers’ understanding of \nsocietal needs. This potential misalignment allows for both oversupply and unmet demand \nwithin the field, contributing to the \"taxonomic impediment\". \nWhile our study focuses on scientific publication as a measure of taxonomic capacity and \nexamines only a sample of demand-side drivers, it highlights critical trends. Expanding this \nevaluation to include other metrics, such as teaching, specimen collection, curation, and \ndigitization, could provide a more comprehensive picture of taxonomic capacity and its \nalignment with societal demands. \nOur results do demonstrate that there is some relationship between the number of \ntaxonomists and the attention demanded by policy. For example, vertebrates are frequently \nmentioned in EU policy, and indeed there are a comparatively high number of vertebrate \ntaxonomists. Likewise, there are many taxonomists of vascular plants and specific policy \ndrivers linked to these. However, a close correlation between human population in a country \nand the number of taxonomists  is probably because taxonomists in populous countries are \noften working on taxa outside their affiliated country, rather than populous countries being \nmore biodiverse, or that policies in populous countries demand more taxonomists (Mooney & \nMace 2009; Rodrigues et al. 2010). Furthermore, it is not always possible to determine \nlogical reasons for research funding decisions, because they are often influenced by \nsubjective factors, such as the perceived charisma or public appeal of certain species, rather \nthan being strictly guided by clear, data-driven conservation priorities (Bellon 2019). \nRecommendations for taxonomists, their institutions and their funders \nThe uneven geographic and taxonomic distribution of expertise underscores the need for \nbetter coordination among funders, institutions, and researchers. Systematic approaches to \nmeasure supply and demand, coupled with strategic partnerships, can help align taxonomic \nefforts with societal priorities, ensuring that outputs are impactful, adequately funded, and \nactionable for biodiversity conservation and sustainable management (Juffe-Bignoli et al., \n2016). \n14 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nEffective collaboration between taxonomists, policymakers, conservation practitioners, and \nfunders requires structured mechanisms for engagement. Platforms such as \nmultistakeholder forums, regional or international workshops, and decentralized networks \ncan facilitate co-developed research agendas, shared learning, and inclusive \ndecision-making (MacDonald et al. 2019; Leberger et al. 2024). \nTo further enhance coordination, national or regional taxonomic advisory \ncouncils—comprising representatives from government, academia, NGOs, and \nindustry—could help identify priorities, guide funding, and target underrepresented taxa and \nregions (e.g. aquatic invertebrates, fungi; Antonelli et al. 2023). Joint funding initiatives \namong public and private entities can also amplify impact by supporting research in \nbiodiversity-rich areas or on neglected groups. \nEmbedding taxonomic expertise within policymaking bodies would strengthen the \nscience-policy interface. Seconding taxonomists to environmental agencies, for instance, \nensures that policy decisions are grounded in up-to-date taxonomic knowledge (Owens, \n2015). At the same time, metrics and reporting systems can help track how research \ncontributes to policy objectives, conservation outcomes, or global biodiversity frameworks \n(Bénichou et al. 2018; Tancoigne & Ollivier 2017). \nBuilding capacity remains essential in bridging the gap between the supply and demand for \ntaxonomic expertise. Investments in training, research infrastructure, and collections that \nunderpin biodiversity studies, will ensure that the field has the resources it needs to thrive. \nTraining should include communication and policy engagement skills, while policymakers \ncould receive training on the significance of taxonomy and its application in decision-making, \nfostering mutual understanding and enhancing collaboration. Recognizing policy-engaged \nacademic work in career advancement would further incentivize impactful research. \nTogether, these measures can create an integrated and responsive taxonomic system. \nCo-developing goals ensures that research priorities reflect both scientific and policy needs, \nwhile shared evaluation frameworks and feedback mechanisms maintain accountability and \nmutual trust. Ultimately, shared ownership of outcomes—whether in improved policies or \nresearch advances—will sustain and strengthen partnerships between science and society. \nLooking ahead, taxonomy stands at a transformative juncture. Innovations like artificial \nintelligence, metabarcoding, and automated monitoring tools offer vast new data and insight. \nWhile this data deluge presents challenges, it also empowers taxonomists to redefine their \nrole and deepen their societal impact. Harnessing these technologies will require sustained \ncollaboration across disciplines and sectors. By seizing this moment of change, the \ntaxonomic community can ensure that its work remains not only scientifically rigorous, but \nalso essential to the protection of biodiversity and the well-being of future generations. \n \n5. Conclusion \nTaxonomy is indispensable for addressing biodiversity challenges, yet its capacity remains \nweakly aligned with societal and policy demands. By adopting systematic approaches to \n15 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nassess and monitor taxonomic capacity, we can better prioritize investments and guide \ntaxonomists toward impactful research. The automated, reproducible workflow developed in \nthis study serves as a foundation for future work, enabling more informed decisions that \nsupport biodiversity conservation and sustainable development. \n \nAcknowledgements \nThis work was supported by the TETTRIs project, which receives funding from the European \nUnion’s Horizon Europe Innovation Actions under grant agreement No. 101081903 and by \nthe DiSSCo Flanders project, funded by the Research Foundation – Flanders (FWO) \nresearch infrastructure under grant number I001721N. Additional support was provided by \nthe B3 project (Biodiversity Building Blocks for Policy), funded by the European Union’s \nHorizon Europe Research and Innovation Programme under grant agreement No. \n101059592. \nData Availability Statement \nThe source code for the workflow and the data used is available on GitHub \n(https://github.com/AgentschapPlantentuinMeise/TETTRIs-mapping-taxonomists) and the \nlatest archived release is deposited on Zenodo (DOI: 10.5281/zenodo.13334248) and made \navailable under a CC-BY 4.0 license (De Nolf et al. 2025). The European border shapefiles \nused for map generation were obtained from Natural Earth \n(https://www.naturalearthdata.com), a public domain dataset. \nReferences \nAgnarsson I. & Kuntner M. 2007. Taxonomy in a Changing World: Seeking Solutions for a \nScience in Crisis. 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It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\npython. In: Proceedings of the 9th Python in Science Conference: 92–96. SciPy \nAustin, Texas. \nSeebens H. 2016. Global Alien Species First Record Database. \nStephenson P.J., Londoño-Murcia M.C., Borges P.A.V., Claassens L., Frisch-Nwakanma H., \nLing N., McMullan-Fisher S., Meeuwig J.J., Unter K.M.M., Walls J.L., Burfield I.J., Do \nCarmo Vieira Correa D., Geller G.N., Montenegro Paredes I., Mubalama L.K., \nNtiamoa-Baidu Y., Roesler I., Rovero F., Sharma Y.P., Wiwardhana N.W., Yang J. & \nFumagalli L. 2022. Measuring the Impact of Conservation: The Growing Importance \nof Monitoring Fauna, Flora and Funga. Diversity 14 (10): 824. \nhttps://doi.org/10.3390/d14100824 \nTancoigne E. & Ollivier G. 2017. 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Germplasm \nResources Information Network (GRIN Taxonomy). \nWorld Bank 2024. Population Estimates and Projections. \n \n \n \n \n21 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nTable 1: Number of species and other taxonomic ranks covered by EU legislation. '~' \ndenotes approximate values due to incomplete data or taxonomic uncertainties. Some \nspecies may be listed under multiple legislative acts. \nLegislation Species Taxonomy Reference \nBirds directive (Annex I) 193 Aves The Council of European \nCommunities (1979) \nHabitats Directive (Article \n17 checklist (2020)) \n~1510 Animals, fungi and \nplants \nThe Council of European \nCommunities (1992) \nMarine Water Framework \nDirective (Descriptor 1) \n368 Mostly vertebrates, \nsuch as fish, birds, \nand marina \nmammals and \nreptiles \nPalialexis & Boschetti \n(2021) \nIAS list of union Concern \n(2020) \n \n41 Plants \n& 47 \nAnimals \nThe animals are \nmostly vertebrates, \nsuch as fish, birds,  \nand mammals, and \nthe plant are mostly \nMagnoliopsida and \nLilopsida \nEuropean Parliament, \nCouncil of the European \nUnion (2019) \nPollinators Initiative 3051 Bees (Anthophila ) \nand hoverflies \n(Syrphidae) \n(European Commission. \nDirectorate General for \nEnvironment. 2021; \nReverté et al. 2023) \nEU Biodiversity Strategy \nfor 2030 European Red \nList of Species (Species \nVU or in a higher risk \ncategory) \n \n1864 The animals are \nmainly vertebrates, \nGastropoda and \nInsecta. The plants \nare mainly \nMagnoliopsida  \n(European Environmental \nAgency 2019) \n \n22 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nTable 2: A summary of the taxonomic journal selection results. Journals related to taxonomy \nand their relation to other journal identifiers. Only active journals with an OpenAlex ID were \nused to select taxonomic articles. \nCategory Number \nJournals identified and deduplicated 2686 \nJournals with a unique Wikidata ID 2502 \nJournals with a unique ISSN-L 1791 \nJournals with an OpenAlex ID 1021 \nDissolved journals 801 \nJournals with no OpenAlexID and not dissolved 914 \nActive journals that contained relevant articles 474 \n \n \n \n \n23 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\nFigure legends \n \nFigure 1. Phylogenies of the number of species in different policy relevant categories. \nNumber of species in (A) the taxonomic research-needed category in IUCN Redlists; (B) the \nEuropean Red List; (C) the European crop wild relatives; (D) the invasive alien species on \nthe horizon for future invasions; (E) the Union List of Concern for invasive species; (F) the  \nspecies named in the European Birds Directive; (G) the species named in the European \nHabitats Directive; (H) the species named in the European Marine Framework Directive and \n(I) the species important to the European Pollinator Initiative. The color gradient in the heat \ntrees ranges from yellow (low values) to blue (high values), with grey denoting the absence \nof species \n \nFigure 2. Phylogenies of the publication activity of taxonomists separated into the kingdoms \n(A) Plantae (B) Fungi and (C) Animalia. Tips represent orders, but only some classes and \nhigher taxa are labeled. \n \nFigure 3. The number of taxonomists affiliated with institutions within European countries as \na (A) total and as a (B) percentage of the population of each country. \n \n24 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint \n\n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 1, 2025. ; https://doi.org/10.1101/2025.07.31.666655doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}