BIEN : A biodiversity informatics ecosystem advancing open and reproducible workflows for plant observation, plot and trait data
Year: 2026
Type: article
Abstract: The rapid expansion of biodiversity data presents new opportunities to understand and forecast biosphere dynamics. However, disparate and dispersed data, taxonomic and geographic inconsistencies, pervasive quality issues, and a lack of reproducable workflows hinder synthesis, introduce biases and limit accurate assessment of biodiversity trends. The Botanical Information and Ecology Network (BIEN) addresses these challenges through two core contributions: (1) an ecosystem of modular, open‐source BIEN tools for collecting, harmonizing, validating, integrating, visualizing and analysing biodiversity data, and (2) a standardized, augmented and integrated global database (BIEN db) of plant occurrences, traits and geographic ranges. BIEN tools—including the Taxonomic Name Resolution Service (TNRS), Geographic Name Resolution Service (GNRS), Geocoordinate Validation Service (GVS) and Native Species Resolver (NSR)—enable the construction of analysis‐ready data sets. Using this framework, we integrated over 284 million botanical observation records. BIEN db (current version 4.2) is so far the most extensive compilation of standardized observation records and plant traits (25,932,454 unique trait observation records) for land plants, drawn from herbaria, ecological plots, citizen science and trait databases and integrated into a unified geospatial platform. Here, we present the BIEN workflow, the database and several use cases. The BIEN workflow and database support reproducible biodiversity science at scale. BIEN provides improved and unprecedented trait coverage, new estimates of total plant species richness, geographic ranges for over 250,000 species and global maps of plant biodiversity. These tools enable researchers to integrate disparate biodiversity observation records, generate tailored data sets, resolve taxonomic and geographic ambiguities, and estimate species richness across spatial and temporal scales for conservation and forecasting applications. BIEN provides a scalable, open and reproducible informatics platform that integrates global plant biodiversity data. By linking data infrastructure with accessible tools, BIEN democratizes biodiversity science. It enhances transparency, reproducibility and analytical capacity across the research community, enabling more scientists to address a wider range of questions in ecology, evolution and biodiversity science and engage in global change biology and biodiversity forecasting. BIEN offers a robust Open Science platform to understand and respond to the biodiversity crisis.
Source: Methods in Ecology and Evolution
Authors: Brian J. Enquist, Brad Boyle, Brian S. Maitner, Cory Merow, Ben S. Carlson, Xiao Feng, Gabriel M. Moulatlet, Erica A. Newman, Daniel S. Park, Michiel Pillet, Patrick R. Roehrdanz, Josep M. Serra‐Diaz, Rethvick S. Y. Babu, George G. C. Barbosa, Nathan Casler, John C. Donoghue, Daniel Guaderrama, Rohith K. Sajja, Thomas L. P. Couvreur, Matthew B. Jones, Peter M. Jørgensen, Nathan J. B. Kraft, Pablo A. Marquet, Brian J. McGill, Nirav Merchant, Naia Morueta‐Holme, Danilo M. Neves, Ary Oliveira‐Filho, Robert K. Peet, Oliver Phillips, Brody Sandel, Mark Schildhauer, Irena Simova, Hans ter Steege, Jens‐Christian Svenning, Barbara Thiers, Cyrille Violle, Jan J. Wieringa, Susan K. Wiser
Institutions: Santa Fe Institute, University of Arizona, University of South Florida St. Petersburg, University of Connecticut, University of North Carolina at Chapel Hill, James Madison University, Korea University, Purdue University West Lafayette, Conservation International, Consejo Superior de Investigaciones Científicas, Institut Botànic de Barcelona, BlackSky Global (United States), California Native Plant Society, San Bernardino Valley College, Naturalis Biodiversity Center, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Université de Montpellier, Diversité, adaptation et développement des plantes, Institut de Recherche pour le Développement, University of California, Santa Barbara, National Center for Ecological Analysis and Synthesis, University of California, Los Angeles, Centre National de la Recherche Scientifique, Pontificia Universidad Católica de Chile, Center for Mathematical Modeling, University of Chile, University of Maine, University of Copenhagen, Universidade Federal de Minas Gerais, University of Leeds, Santa Clara University, Charles University, Utrecht University, Aarhus University, New York Botanical Garden, Denver Botanic Gardens, École Pratique des Hautes Études, Centre d'Écologie Fonctionnelle et Évolutive, Manaaki Whenua – Landcare Research
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: gold
Estimated APC paid: $3,500
Funders: National Science Foundation, Aarhus Universitet, University of Arizona, Villum Fonden, Global Environment Facility, Ministerio de Ciencia, Innovación y Universidades, National Research Foundation, Danmarks Grundforskningsfond, Grantová Agentura České Republiky, Korea University, Aarhus Universitets Forskningsfond, Danmarks Frie Forskningsfond, Scheme for Promotion of Academic and Research Collaboration, Agencia Estatal de Investigación
Awards: Collaborative Research: Near Term Forecasts of Global Plant Distribution, Community Structure, and Ecosystem Function, G136433599, G2262748287, G2366894008, G2972307431, G3403109295, G3480869486, G3671676825, G425668148, G5238128993, G5239107149, NCEAS: National Center for Ecological Analysis and Synthesis, G5615013734, G5635532810, PSCIC Full Proposal: The iPlant Collaborative: A Cyberinfrastructure-Centered Community for a New Plant Biology, G7084143925, G717256432, Collaborative Research: ABI Development: Creating a generic workflow for scaling up the production of species ranges, G7863371703, G8059228646, G8497050386, The equilibrium theory of biodiversity dynamics - macroecological perspective, Collaborative Research: ABI Development: Creating a generic workflow for scaling up the production of species ranges
OpenAlex ID: W7140170656