Publications

Publications

Peer-reviewed research using and describing BIEN

Merged and DOI-verified bibliography from the BIEN publications page and BIEN literature-cited workflow. Entries are ordered reverse-chronologically and link to DOI resolvers.

Citation Grouping Overview

  • BIEN core publications: Papers describing the BIEN ecosystem, scope, and primary infrastructure.
  • BIEN tools and services: Papers for BIEN services and standards (for example TNRS, GNRS, and metadata standards).
  • Applied research using BIEN data: Peer-reviewed studies using BIEN occurrence, trait, plot, or range products.
  • Code-linked RBIEN studies: Studies with public code examples for BIEN/RBIEN analyses.
  • Citation practice: Cite BIEN core paper(s), relevant tool/service paper(s), and report access date, query scope, and filters.

How to cite BIEN

When you use BIEN data or the BIEN R package, cite both of the following:

  1. Enquist BJ, Boyle B, Maitner BS, et al. (2026). BIEN: A biodiversity informatics ecosystem advancing open and reproducible workflows for plant observation, plot and trait data. Methods in Ecology and Evolution, 17(5), 1556–1584. https://doi.org/10.1111/2041-210X.70274
  2. Maitner BS, Boyle B, Casler N, Condit R, Donoghue J, Durán SM, Guaderrama D, Hinchliff CE, Jørgensen PM, Kraft NJB, McGill B, Merow C, Morueta-Holme N, Peet RK, Sandel B, Schildhauer M, Smith SA, Svenning J-C, Thiers B, Violle C, Wiser S, Enquist BJ (2018). The BIEN R package: a tool to access the Botanical Information and Ecology Network (BIEN) database. Methods in Ecology and Evolution, 9(2), 373–379. https://doi.org/10.1111/2041-210X.12861

Also record the access date, query scope, and key filters/validation rules used,

and cite the specific tool paper (TNRS, GNRS, Plant-O-Matic, RMMS, Veg-X) when you

rely on that service.

—

Complete bibliography (reverse chronological)

2026

  1. Enquist BJ, Boyle B, Maitner BS, Feng X, Newman EA, Jørgensen PM, et al. (2026). BIEN: A biodiversity informatics ecosystem advancing open and reproducible workflows for plant observation, plot and trait data. Methods in Ecology and Evolution, 17(5), 1556–1584. https://doi.org/10.1111/2041-210X.70274 — [BIEN core]

2025

  1. Moulatlet GM, Merow C, Maitner B, Boyle B, Feng X, Frazier AE, et al. (2025). General laws of biodiversity: Climatic niches predict plant range size and ecological dominance globally. Proceedings of the National Academy of Sciences, 122(46), e2517585122. https://doi.org/10.1073/pnas.2517585122 — [research: occurrence, range/SDM, trait]
  2. Feng X, Smith AB, Boyle B, Chen X, Enquist BJ, Gallagher R, Hammock J, et al. (2025). The next stage of biodiversity informatics: community-driven synthesis and integration of biodiversity databases. BioScience, 75(11), 913–925. https://doi.org/10.1093/biosci/biaf112 — [BIEN core]

2023

  1. Cai L, et al. (2023). Global models and predictions of plant diversity based on advanced machine learning techniques. New Phytologist, 237(4), 1432–1445. https://doi.org/10.1111/nph.18533 — [research: occurrence] (online-first 2022; print vol. 237 is 2023)

2022

  1. Boyle BL, et al. (2022). The Geographic Name Resolution Service: a tool for the standardization and indexing of world political division names, with applications to species distribution modeling. PLOS ONE, 17(11), e0268162. https://doi.org/10.1371/journal.pone.0268162 — [web service]

2020

  1. Hannah L, Roehrdanz PR, Marquet PA, Enquist BJ, Midgley G, Foden W, et al. (2020). 30% land conservation and climate action reduces tropical extinction risk by more than 50%. Ecography, 43(7), 943–953. https://doi.org/10.1111/ecog.05166 — [research: range/SDM, conservation]
  2. Jardine EC, et al. (2020). The global distribution of grass functional traits within grassy biomes. Journal of Biogeography, 47(2), 553–565. https://doi.org/10.1111/jbi.13764 — [research: trait]

2019

  1. Enquist BJ, Feng X, Boyle B, Maitner B, Newman EA, Jørgensen PM, et al. (2019). The commonness of rarity: global and future distribution of rarity across land plants. Science Advances, 5(11), eaaz0414. https://doi.org/10.1126/sciadv.aaz0414 — [research: occurrence, range/SDM]
  2. Feng X, et al. (2019). A checklist for maximizing reproducibility of ecological niche models. Nature Ecology & Evolution, 3(10), 1382–1395. https://doi.org/10.1038/s41559-019-0972-5 — [research: occurrence, range/SDM]
  3. McFadden IR, Sandel B, Tsirogiannis C, Morueta-Holme N, Svenning J-C, Enquist BJ, Kraft NJB (2019). Temperature shapes opposing latitudinal gradients of plant taxonomic and phylogenetic β diversity. Ecology Letters, 22(7), 1126–1135. https://doi.org/10.1111/ele.13269 — [research: occurrence, phylogenetic]
  4. Šímová I, et al. (2019). The relationship of woody plant size and leaf nutrient content to large-scale productivity for forests across the Americas. Journal of Ecology, 107(5), 2278–2290. https://doi.org/10.1111/1365-2745.13163 — [research: trait, plot]
  5. Steidinger BS, et al. (2019). Climatic controls of decomposition drive the global biogeography of forest-tree symbioses. Nature, 569(7756), 404–408. https://doi.org/10.1038/s41586-019-1128-0 — [research; verify BIEN centrality — primarily GFBI forest-inventory data]
  6. Merow C, Maitner BS, Owens HL, Kass JM, Enquist BJ, Jetz W, Guralnick R (2019). Species' range model metadata standards: RMMS. Global Ecology and Biogeography, 28(12), 1912–1924. https://doi.org/10.1111/geb.12993 — [data standard]

2018

  1. Maitner BS, Boyle B, Casler N, Condit R, Donoghue J, Durán SM, et al. (2018). The BIEN R package: a tool to access the Botanical Information and Ecology Network (BIEN) database. Methods in Ecology and Evolution, 9(2), 373–379. https://doi.org/10.1111/2041-210X.12861 — [BIEN core]
  2. Echeverría-Londoño S, Enquist BJ, Neves DM, Violle C, Boyle B, Kraft NJB, et al. (2018). Plant functional diversity and the biogeography of biomes in North and South America. Frontiers in Ecology and Evolution, 6, 219. https://doi.org/10.3389/fevo.2018.00219 — [research: trait, occurrence]
  3. Šímová I, et al. (2018). Spatial patterns and climate relationships of major plant traits in the New World differ between woody and herbaceous species. Journal of Biogeography, 45(4), 895–916. https://doi.org/10.1111/jbi.13171 — [research: trait]
  4. Eiserhardt WL, et al. (2018). A roadmap for global synthesis of the plant tree of life. American Journal of Botany, 105(3), 614–622. https://doi.org/10.1002/ajb2.1041 — [research; perspective/roadmap — verify BIEN centrality]

2017

  1. Csergő AM, et al. (2017). Less favourable climates constrain demographic strategies in plants. Ecology Letters, 20(8), 969–980. https://doi.org/10.1111/ele.12794 — [research; verify BIEN centrality — demographic data from COMPADRE]
  2. Serra-Diaz JM, Enquist BJ, Maitner B, Merow C, Svenning J-C (2017). Big data of tree species distributions: how big and how good? Forest Ecosystems, 4, 30. https://doi.org/10.1186/s40663-017-0120-0 — [research: occurrence, range/SDM]

2016

  1. Doughty CE, et al. (2016). Megafauna extinction, tree species range reduction, and carbon storage in Amazonian forests. Ecography, 39(2), 194–203. https://doi.org/10.1111/ecog.01587 — [research: range/SDM]
  2. Engemann K, Sandel B, Boyle BL, Enquist BJ, Jørgensen PM, Kattge J, et al. (2016). A plant growth form dataset for the New World. Ecology, 97(11), 3243. https://doi.org/10.1002/ecy.1569 — [research: trait/data paper]
  3. Engemann K, Sandel B, Morueta-Holme N, Enquist BJ, Peet RK, Wiser S, Svenning J-C (2016). Patterns and drivers of plant functional group dominance across the Western Hemisphere: a macroecological re-assessment based on a massive botanical dataset. Botanical Journal of the Linnean Society, 180(2), 141–160. https://doi.org/10.1111/boj.12362 — [research: occurrence, trait]
  4. Morueta-Holme N, Blonder B, Sandel B, McGill BJ, Peet RK, Ott JE, et al. (2016). A network approach for inferring species associations from co-occurrence data. Ecography, 39(12), 1139–1150. https://doi.org/10.1111/ecog.01892 — [research: occurrence]
  5. Goldsmith GR, Morueta-Holme N, Sandel B, et al. (2016). Plant-O-Matic: a dynamic and mobile guide to all plants of the Americas. Methods in Ecology and Evolution, 7(8), 960–965. https://doi.org/10.1111/2041-210X.12548 — [tool]

2015

  1. Blonder B, Nogués-Bravo D, Borregaard MK, Donoghue JC, Jørgensen PM, Kraft NJB, et al. (2015). Linking environmental filtering and disequilibrium to biogeography with a community climate framework. Ecology, 96(4), 972–985. https://doi.org/10.1890/14-0589.1 — [research: occurrence]
  2. Engemann K, Enquist BJ, Sandel B, Boyle B, Jørgensen PM, Morueta-Holme N, et al. (2015). Limited sampling hampers "big data" estimation of species richness in a tropical biodiversity hotspot. Ecology and Evolution, 5(3), 807–820. https://doi.org/10.1002/ece3.1405 — [research: occurrence]
  3. Šímová I, Violle C, Kraft NJB, Storch D, Svenning J-C, Boyle B, et al. (2015). Shifts in trait means and variances in North American tree assemblages: species richness patterns are loosely related to the functional space. Ecography, 38(7), 649–658. https://doi.org/10.1111/ecog.00867 — [research: trait]

2014

  1. Lamanna C, Blonder B, Violle C, Kraft NJB, Sandel B, Šímová I, et al. (2014). Functional trait space and the latitudinal diversity gradient. Proceedings of the National Academy of Sciences, 111(38), 13745–13750. https://doi.org/10.1073/pnas.1317722111 — [research: trait, occurrence]

2013

  1. Boyle B, Hopkins N, Lu Z, Raygoza Garay JA, Mozzherin D, Rees T, Matasci N, Narro ML, Piel WH, McKay SJ, Lowry S, Freeland C, Peet RK, Enquist BJ (2013). The taxonomic name resolution service: an online tool for automated standardization of plant names. BMC Bioinformatics, 14, 16. https://doi.org/10.1186/1471-2105-14-16 — [tool]
  2. Morueta-Holme N, Enquist BJ, McGill BJ, Boyle B, Jørgensen PM, Ott JE, et al. (2013). Habitat area and climate stability determine geographical variation in plant species range sizes. Ecology Letters, 16(12), 1446–1454. https://doi.org/10.1111/ele.12184 — [research: occurrence, range/SDM]

2011

  1. Sandel B, Arge L, Dalsgaard B, Davies RG, Gaston KJ, Sutherland WJ, Svenning J-C (2011). The influence of Late Quaternary climate-change velocity on species endemism. Science, 334(6056), 660–664. https://doi.org/10.1126/science.1210173 — [research; foundational BIEN-group paper — predates the BIEN R package]
  2. Wiser SK, Spencer N, De Cáceres M, Kleikamp M, Boyle B, Peet RK (2011). Veg-X — an exchange standard for plot-based vegetation data. Journal of Vegetation Science, 22(4), 598–609. https://doi.org/10.1111/j.1654-1103.2010.01245.x — [data standard]

—

Additional RBIEN studies with code (also listed in the code table below)

  • Ochoa D et al. (2025). Late Miocene greening of the Peruvian Desert. Communications Earth & Environment, 6(1), 391. https://doi.org/10.1038/s43247-025-02322-0 — Code
  • Dobson KC, Zarnetske PL (2025). A Global Meta-Analysis of Passive Experimental Warming Effects on Plant Traits and Community Properties. Global Change Biology, 31(6), e70306. https://doi.org/10.1111/gcb.70306 — Code
  • Liu Y et al. (2025). An Updated Environmental Resistance Model for Predicting the Spread of Invasive Species. Journal of Biogeography, 52(5), e15089. https://doi.org/10.1111/jbi.15089 — Code
  • Van Nuland ME et al. (2024). Climate mismatches with ectomycorrhizal fungi contribute to migration lag in North American tree range shifts. PNAS, 121(23), e2308811121. https://doi.org/10.1073/pnas.2308811121 — Code
  • Ten Caten C, Dallas T (2024). Latitudinal specificity of plant-avian frugivore interactions. Journal of Animal Ecology, 93(7), 958-969. https://doi.org/10.1111/1365-2656.14116 — Code
  • Chen Q et al. (2024). Change in functional trait diversity mediates the effects of nutrient addition on grassland stability. Journal of Ecology, 112(11), 2598-2612. https://doi.org/10.1111/1365-2745.14404 — Code
  • da Silva Oliveira EV, Landim MF, Gouveia SF (2024). Multiple aspects of tree beta diversity in coastal ecosystems in Brazil. Journal of Biogeography, 51(8), 1458-1468. https://doi.org/10.1111/jbi.14842 — Code
  • Vasconcelos T (2023). A trait-based approach to determining principles of plant biogeography. American Journal of Botany, 110(2), e16127. https://doi.org/10.1002/ajb2.16127 — Code
  • McKeon CM, Kelly R, Borger L, De Palma A, Buckley YM (2023). Human land use is comparable to climate as a driver of global plant occurrence and abundance across life forms. Global Ecology and Biogeography, 32(9), 1618-1631. https://doi.org/10.1111/geb.13713 — Code
  • Stemkovski M et al. (2023). Disorder or a new order: How climate change affects phenological variability. Ecology, 104(1), e3846. https://doi.org/10.1002/ecy.3846 — Code
  • Wu Y, Ricklefs RE (2023). Linking multiple hypotheses to a unifying framework of range-size variation: A case study with American oaks (Quercus spp.). Global Ecology and Biogeography, 32(1), 95-106. https://doi.org/10.1111/geb.13610 — Code
  • AuBuchon-Elder T et al. (2023). Plant conservation assessment at scale: Rapid triage of extinction risks. Plants, People, Planet, 5(3), 386-397. https://doi.org/10.1002/ppp3.10355 — Code
  • Lyu L et al. (2022). An integrated high-resolution mapping shows congruent biodiversity patterns of Fagales and Pinales. New Phytologist, 235(2), 759-772. https://doi.org/10.1111/nph.18158 — Code
  • Kim S, Sales L, Carreira D, Galetti M (2022). Frugivore distributions are associated with plant dispersal syndrome diversity in the Caribbean archipelagos. Diversity and Distributions, 28(12), 2521-2533. https://doi.org/10.1111/ddi.13503 — Code
  • Galanis A et al. (2022). Bee foraging preferences, microbiota and pathogens revealed by direct shotgun metagenomics of honey. Molecular Ecology Resources, 22(7), 2506-2523. https://doi.org/10.1111/1755-0998.13626 — Code
  • Engel T et al. (2021). Using coverage-based rarefaction to infer non-random species distributions. Ecosphere, 12(9), e03745. https://doi.org/10.1002/ecs2.3745 — Code
  • Flower C et al. (2021). Human food use increases plant geographical ranges in the Sonoran Desert. Global Ecology and Biogeography, 30(7), 1461-1473. https://doi.org/10.1111/geb.13311 — Code
  • Devenish C et al. (2021). Multi-decadal land use impacts across the vast range of an iconic threatened species. Diversity and Distributions, 27(11), 2218-2230. https://doi.org/10.1111/ddi.13395 — Code
  • Harbert RS, Baryiames AA (2020). cRacle: R tools for estimating climate from vegetation. Applications in Plant Sciences, 8(2), e11322. https://doi.org/10.1002/aps3.11322 — Code

Studies Using RBIEN with Associated Code Examples

These studies provide concrete examples of how BIEN data are accessed and analyzed with RBIEN-oriented workflows. The table lists a regular citation, the publication DOI link, and an associated open code link.

Citation Paper Link Code Link
Van Nuland ME, Qin C, Pellitier PT, Zhu K, Peay KG (2024). Climate mismatches with ectomycorrhizal fungi contribute to migration lag in North American tree range shifts. Proceedings of the National Academy of Sciences, 121(23), e2308811121. https://doi.org/10.1073/pnas.2308811121 https://zenodo.org/records/11003760
Vasconcelos T (2023). A trait-based approach to determining principles of plant biogeography. American Journal of Botany, 110(2), e16127. https://doi.org/10.1002/ajb2.16127 https://github.com/tncvasconcelos/synthesis
McKeon CM, Kelly R, B�f6rger L, De Palma A, Buckley YM (2023). Human land use is comparable to climate as a driver of global plant occurrence and abundance across life forms. Global Ecology and Biogeography, 32(9), 1618-1631. https://doi.org/10.1111/geb.13713 https://zenodo.org/records/7554843
Stemkovski M, Bell JR, Ellwood ER, Inouye BD, Kobori H, Lee SD, Lloyd-Evans T, Primack RB, Templ B, Pearse WD (2023). Disorder or a new order: How climate change affects phenological variability. Ecology, 104(1), e3846. https://doi.org/10.1002/ecy.3846 https://github.com/stemkov/pheno_variance
Lyu L, Leugger F, Hagen O, Fopp F, Boschman LM, Strijk JS, Albouy C, Karger DN, Brun P, Wang Z, Zimmermann NE, Pellissier L (2022). An integrated high-resolution mapping shows congruent biodiversity patterns of Fagales and Pinales. New Phytologist, 235(2), 759-772. https://doi.org/10.1111/nph.18158 https://gitlab.ethz.ch/gdplants/gdplants
Engel T, Blowes SA, McGlinn DJ, May F, Gotelli NJ, McGill BJ, Chase JM (2021). Using coverage-based rarefaction to infer non-random species distributions. Ecosphere, 12(9), e03745. https://doi.org/10.1002/ecs2.3745 https://github.com/T-Engel/betaC
Ochoa D, Carr�e9 M, Montenegro JF, DeVries TJ, Caballero-Rodr�edguez D, Rodr�edguez-Reyes O, Barbosa-Espitia A, Cardich J, Cruz-Acevedo E, Cruz D, et al. (2025). Late Miocene greening of the Peruvian Desert. Communications Earth & Environment, 6(1), 391. https://doi.org/10.1038/s43247-025-02322-0 https://github.com/Paleo-flora/AGL-Miocene
Ten Caten C, Dallas T (2024). Latitudinal specificity of plant-avian frugivore interactions. Journal of Animal Ecology, 93(7), 958-969. https://doi.org/10.1111/1365-2656.14116 https://doi.org/10.6084/m9.figshare.22280629
Dobson KC, Zarnetske PL (2025). A Global Meta-Analysis of Passive Experimental Warming Effects on Plant Traits and Community Properties. Global Change Biology, 31(6), e70306. https://doi.org/10.1111/gcb.70306 https://github.com/SpaCE-Lab-MSU/OTCMetaAnalysis/tree/published
Kim S, Sales L, Carreira D, Galetti M (2022). Frugivore distributions are associated with plant dispersal syndrome diversity in the Caribbean archipelagos. Diversity and Distributions, 28(12), 2521-2533. https://doi.org/10.1111/ddi.13503 https://github.com/sxk1332/Caribbean-fruit-frugivore
Galanis A, Vardakas P, Reczko M, Harokopos V, Hatzis P, Skoulakis EMC, Pavlopoulos GA, Patalano S (2022). Bee foraging preferences, microbiota and pathogens revealed by direct shotgun metagenomics of honey. Molecular Ecology Resources, 22(7), 2506-2523. https://doi.org/10.1111/1755-0998.13626 https://github.com/AGalanis97/Direct-shotgun-metagenomics-pub
Liu Y, Kartesz JT, Nishino M, Sturgeon DJE, Thomas MB (2025). An Updated Environmental Resistance Model for Predicting the Spread of Invasive Species. Journal of Biogeography, 52(5), e15089. https://doi.org/10.1111/jbi.15089 https://github.com/yunpengliu1994/ER-model
Wu Y, Ricklefs RE (2023). Linking multiple hypotheses to a unifying framework of range-size variation: A case study with American oaks (Quercus spp.). Global Ecology and Biogeography, 32(1), 95-106. https://doi.org/10.1111/geb.13610 https://zenodo.org/records/7094242
Chen Q, Wang S, Seabloom EW, Isbell F, Borer ET, et al. (2024). Change in functional trait diversity mediates the effects of nutrient addition on grassland stability. Journal of Ecology, 112(11), 2598-2612. https://doi.org/10.1111/1365-2745.14404 https://github.com/chqq365/plant-traits-compiled-for-NutNet
Harbert RS, Baryiames AA (2020). cRacle: R tools for estimating climate from vegetation. Applications in Plant Sciences, 8(2), e11322. https://doi.org/10.1002/aps3.11322 https://github.com/rsh249/cracle_examples
Flower C, Hodgson WC, Salywon AM, Maitner BS, Enquist BJ, Peeples MA, Blonder B (2021). Human food use increases plant geographical ranges in the Sonoran Desert. Global Ecology and Biogeography, 30(7), 1461-1473. https://doi.org/10.1111/geb.13311 https://doi.org/10.6078/D1PH79
Devenish C, Lees AC, Collar NJ, Marsden SJ (2021). Multi-decadal land use impacts across the vast range of an iconic threatened species. Diversity and Distributions, 27(11), 2218-2230. https://doi.org/10.1111/ddi.13395 https://github.com/Cdevenish/A_hyacinthinus_project
da Silva Oliveira EV, Landim MF, Gouveia SF (2024). Multiple aspects of tree beta diversity in coastal ecosystems in Brazil. Journal of Biogeography, 51(8), 1458-1468. https://doi.org/10.1111/jbi.14842 https://doi.org/10.6084/m9.figshare.23589237
AuBuchon-Elder T, Minx P, Bookout B, Kellogg EA (2023). Plant conservation assessment at scale: Rapid triage of extinction risks. Plants, People, Planet, 5(3), 386-397. https://doi.org/10.1002/ppp3.10355 https://github.com/ekellogg-lab/Androp_conservation

Botanical Information and Ecology Network 2026 . Powered by WordPress