<scp>BIEN</scp> : A biodiversity informatics ecosystem advancing open and reproducible workflows for plant observation, plot and trait data

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.

Institutions

Publication Details

Journal
Methods in Ecology and Evolution
Published
2026-03-24
DOI
https://doi.org/10.1111/2041-210x.70274
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

BIEN : A biodiversity informatics ecosystem advancing open and reproducible workflows for plant observation, plot and trait data

Methods in Ecology and Evolution
Species Distribution and Climate Change
article

BIEN : A biodiversity informatics ecosystem advancing open and reproducible workflows for plant observation, plot and trait data

article en

Abstract

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.

Methods in Ecology and Evolution
Universidade Federal de Minas Gerais (BR), University of North Carolina at Chapel Hill (US), James Madison University (US), Centre National de la Recherche Scientifique (FR), Naturalis Biodiversity Center (NL), California Native Plant Society (US), University of Leeds (GB), Santa Fe Institute (US), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR), Conservation International (US), University of Arizona (US), University of Connecticut (US), École Pratique des Hautes Études (FR), University of California, Los Angeles (US), Pontificia Universidad Católica de Chile (CL), Santa Clara University (US), Utrecht University (NL), Korea University (KR), Université de Montpellier (FR), Aarhus University (DK), University of Missouri–St. Louis (US), Charles University (CZ), Purdue University West Lafayette (US), Blackstone (United States) (US), Arizona Science Center (US), San Bernardino Valley College (US), New York Botanical Garden (US), Denver Botanic Gardens (US), Centre d'Écologie Fonctionnelle et Évolutive (FR), Institut Botànic de Barcelona (ES), Institute for Biodiversity (DE), National Center for Ecological Analysis and Synthesis (US), Diversité, adaptation et développement des plantes (FR), Gobierno de Chile (CL), Institut de Recherche pour le Développement (FR), University of Chile (CL), University of South Florida St. Petersburg (US), University of Maine (US), Manaaki Whenua – Landcare Research (NZ)
Life in Land
Openalex Percentile: Top 9%
Species Distribution and Climate Change
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.