Cited by 380Research Data Management PracticesSpecies Distribution and Climate ChangeEcology and Vegetation Dynamics Studies

The DOI matches its Crossref record; 64 of the 65 references it cites were found in a registry or an index, and 1 are not checked yet.

Data integration enables global biodiversity synthesis

Open access

Heberling, J. Mason, Miller, Joseph T., Noesgaard, Daniel, Weingart, Scott B., Schigel, Dmitry·2021·Proceedings of the National Academy of Sciences

DOI 10.1073/pnas.2018093118PMC PMC8017944

Open this paper in CoChat — free account

Abstract

Significance: As anthropogenic impacts to Earth systems accelerate, biodiversity knowledge integration is urgently required to support responses to underpin a sustainable future. Consolidating information from disparate sources (e.g., community science programs, museums) and data types (e.g., environmental, biological) can connect the biological sciences across taxonomic, disciplinary, geographical, and socioeconomic boundaries. In an analysis of the research uses of the world’s largest cross-taxon biodiversity data network, we report the emerging roles of open-access data aggregation in the development of increasingly diverse, global research. These results indicate a new biodiversity science landscape centered on big data integration, informing ongoing initiatives and the strategic prioritization of biodiversity data aggregation across diverse knowledge domains, including environmental sciences and policy, evolutionary biology, conservation, and human health.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1073/pnas.2018093118

Cites

64 of 65 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Latent dirichlet allocation
(2003) · Journal of Machine Learning Research · doi:10.5555/944919.944937 · Cited by 32,337
Very high resolution interpolated climate surfaces for global land areas
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. (2005) · International Journal of Climatology · doi:10.1002/joc.1276 · Cited by 19,860
The FAIR Guiding Principles for scientific data management and stewardship
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., et al. (2016) · Scientific Data · doi:10.1038/sdata.2016.18 · Cited by 18,423
Maximum entropy modeling of species geographic distributions
Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006) · Ecological Modelling · doi:10.1016/j.ecolmodel.2005.03.026 · Cited by 15,396
Latent Dirichlet Allocation
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2002) · The MIT Press eBooks · doi:10.7551/mitpress/1120.003.0082 · Cited by 12,683
Species Distribution Models: Ecological Explanation and Prediction Across Space and Time
Elith, J., & Leathwick, J. R. (2009) · Annual Review of Ecology, Evolution, and Systematics · doi:10.1146/annurev.ecolsys.110308.120159 · Cited by 6,707
Probabilistic topic models
Blei, D. M. (2012) · Communications of the ACM · doi:10.1145/2133806.2133826 · Cited by 5,516
Accelerated modern human–induced species losses: Entering the sixth mass extinction
Ceballos, G., Ehrlich, P. R., Barnosky, A. D., García, A., Pringle, R. M., & Palmer, T. M. (2015) · Science Advances · doi:10.1126/sciadv.1400253 · Cited by 4,220
Promoting an open research culture
Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., Breckler, S. J., Buck, S., Chambers, C. D., Chin, G., Christensen, G., et al. (2015) · Science · doi:10.1126/science.aab2374 · Cited by 2,708
TRY plant trait database – enhanced coverage and open access
Kattge, J., Bönisch, G., Díaz, S. M., Lavorel, S., Prentice, I. C., Leadley, P., Tautenhahn, S., Werner, G. D. A., Aakala, T., Abedi, M., et al. (2019) · Global Change Biology · doi:10.1111/gcb.14904 · Cited by 2,210

Flagged first, then by citations

Show all 65 references

Sorted by citations

Items 301–380 of 380

Peer Review #1 of "Enhancing georeferenced biodiversity inventories: automated information extraction from literature records reveal the gaps (v0.1)"
(2022) · PeerJ · doi:10.7287/peerj.13921v0.1/reviews/1
Peer Review #2 of "Enhancing georeferenced biodiversity inventories: automated information extraction from literature records reveal the gaps (v0.2)"
(2022) · PeerJ · doi:10.7287/peerj.13921v0.2/reviews/2
Peer Review #2 of "Enhancing georeferenced biodiversity inventories: automated information extraction from literature records reveal the gaps (v0.1)"
(2022) · PeerJ · doi:10.7287/peerj.13921v0.1/reviews/2
Peer Review #1 of "Enhancing georeferenced biodiversity inventories: automated information extraction from literature records reveal the gaps (v0.2)"
(2022) · PeerJ · doi:10.7287/peerj.13921v0.2/reviews/1
The scope and scale of the life sciences (‘Nature’s envelope’)
Patterson, D. J. (2022) · Research Ideas and Outcomes · doi:10.3897/rio.8.e96132
Preface: Georeferenced Freshwater Biodiversity Data
Kamburska, L., Fontaneto, D., Rogora, M., & Schigel, D. (2023) · Journal of Limnology · doi:10.4081/jlimnol.2023.2138
Self-citation
CLAVE TAXONÓMICA PARA LA IDENTIFICACIÓN DE CONCHAS VIRTUALES DE GASTRÓPODOS MARINOS DE LA FAUNA CUBANA
Armiñana–García, R., Cruz, D. C.-D. L., Rodríguez-González, A. M., Jiménez-Mendoza, M. E., Hernández-Cauich, E. A., Mijangos-Domínguez, M., Fimia-Duarte, R., & Iannacone‍, J. (2022) · Paideia · doi:10.31381/paideiaxxi.v12i2.5021
Big Data for Beginners
Huybrechts, P. (2023) · Biodiversity Information Science and Standards · doi:10.3897/biss.7.111301
Data integration of SAP business one with website and mobile using AIP (accelerated implementation program) method for configuration
Fakhrurroja, H., Lubis, M., & Ailatat, H. (2023) · AIP conference proceedings · doi:10.1063/5.0118829
Possible solutions for the conservation of benthic habitats and organisms
Lopez, J. V. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-824112-7.00005-4
Spaceborne Remote Sensing of Biodiversity
Gillespie, T. W., & Rocchini, D. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13220-9.00016-0
Quantitative Analysis of Factors Influencing Damage to Old-Growth Hemiboreal Stands as a Result of a Catastrophic Windthrow, Based on Remote Sensing and Merged Data
Ivanova, N., Shashkov, M., Lebedev, A. V., & Shanin, V. N. (2024) · Russian Journal of Ecology · doi:10.1134/s1067413624602008
Quantitative analysis of factors influencing damage to old-growth hemiboreal stands as a result of a catastrophic windthrow, based on remote sensing and merged data
Ivanova, N., Shashkov, M., Lebedev, A. V., & Shanin, V. N. (2024) · Экология · doi:10.31857/s0367059724040043
Experience of regional projects for digitisation of literature heritage
Ivanova, N., Shashkov, M., Созонтов, А. Н., Filippova, N. V., Ermolov, S. A., Sokolova, S. S., Ustinova, A. L., & Plakkhina, E. V. (2024) · Doklady Meždunarodnoj konferencii "Matematičeskaâ biologiâ i bioinformatika" · doi:10.17537/icmbb24.53
New record of a rare robber fly Stiphrolamyra pleskei (Becker, 1913) (Diptera: Asilidae: Asilinae) for Kurdistan, Iraq
Ahmed, S. H. A., & Majeed, S. I. (2024) · Zootaxa · doi:10.11646/zootaxa.5543.1.9
geoSABINA: a unified plant ecology database for SpainPreprint
Goicolea, T., Morales‐Barbero, J., García‐Viñás, J. I., Gastón, A., Aroca‐Fernández, M. J., Calleja, J. A., Moreno‐Piraján, J. C., Ramos‐Gutiérrez, I., Rodríguez, M. Á., Lima, H., et al. (2025) · Research Square · doi:10.21203/rs.3.rs-5928444/v1
Commentary on "Preliminary Species Hypotheses" in Entomological Taxonomy: A Global Data and FAIR Infrastructure Perspective
Islam, S. (2025) · Biodiversity Data Journal · doi:10.3897/bdj.13.e141562
Global Research Trends in Mathematical Problem-Solving Skills: A Bibliometric Review of 2020–2024 Publications
Hendriani, M., Arnawa, I. M., & Zainil, M. (2025) · Seminars in Medical Writing and Education · doi:10.56294/mw2025453 · Cited by 2
Contributions to the knowledge of pitvipers (Viperidae, Gloydius) in the Democratic People’s Republic of Korea: identification, description of specimens, and geographical distribution
Shin, Y., Othman, S. N., Kohler, D. B., Maslova, I. V., Messenger, K. R., & Borzée, A. (2025) · ZooKeys · doi:10.3897/zookeys.1249.142916
Enhancing the climate resilience of protected area networks in drylands: a spatiotemporal optimization framework integrating connectivity and protection effectiveness
Wang, Y., Cui, H., Huang, K., Yu, Q., Avirmed, B., Zhao, J., Liu, Y., Yang, X., Chi, B., & Long, J. (2025) · Environmental Research Letters · doi:10.1088/1748-9326/adfced
UrbanAnts: An R Shiny app for exploring ant diversity data in urban environments
Gonçalves, D. C. D. O., da Silva, N. S., do Prado, L. P., & Morini, M. S. D. C. (2025) · Food and Ecological Systems Modelling Journal · doi:10.3897/fmj.6.155397
Mozambique's Colonial‐Era Non‐Human Primate Collection at the National Museum of Natural History and Science of Lisbon: Taxonomy, Provenance, and Historical Context
Osório, M., & Veracini, C. (2025) · American Journal of Biological Anthropology · doi:10.1002/ajpa.70174
Assessing the Landscape of Digital Species Identifiers
Correia, R. A., & Isaac, M. (2025) · Communications in computer and information science · doi:10.1007/978-3-032-06136-2_29
The cartogram Package for Mapping Ecological Patterns
Marchetto, E., Jeworutzki, S., & Nowosad, J. (2026) · Use R! · doi:10.1007/978-3-031-99665-8_14
Understudied Carnivora (Mammalia) of Kenya: mobilizing specimen data from the National Museums of Kenya for conservation planning
Ferguson, A. W., Lira‐Noriega, A., Agatha, S., Agwanda, B. R., Bartonjo, M., Chege, M., Chemwa, A. W., Grant, S. C., Kageche, H., Kimuyu, D. M., et al. (2025) · Biological Journal of the Linnean Society · doi:10.1093/biolinnean/blaf127 · Cited by 1
A curated and harmonized floristic database from Corrientes, Argentina: one of the most diverse subtropical regions in South America
Cuña, N. P., do Pico, G. M. V., Almirón, N. E. A., Moreno, E. M. S., Kovalsky, I. E., Luque, J. M. R., Silva, G. C., & Neffa, V. G. S. (2025) · Biological Journal of the Linnean Society · doi:10.1093/biolinnean/blaf151
Digitisation of historical specimens from the Hog Island Audubon Camp Natural History Collection, Maine
Mason, S. C., Weidensaul, S., Dougherty, A. H., Doyle, A., Rady, M., Semmler, L., Steinbicker, M., Mick, M., Lark, E., Snyder, E., et al. (2026) · Biodiversity Data Journal · doi:10.3897/bdj.14.e182222
Advances in the Biogeography of Neotropical Mammals
Arregoitia, L. D. V., & Villalobos, F. (2026) · Handbook of the Mammals of Middle and South America. · doi:10.1007/978-3-031-43163-0_25-1
Mapping scientific production in the Tocantins–Araguaia Basin in Brazil Central: application of automated content analysis in freshwater studies
Soares, P. T., Bini, L. M., Filho, J. A. F. D., Vieira, L. C. G., Telles, M. P. D. C., Nunes, R., & Nabout, J. C. (2026) · Limnology · doi:10.1007/s10201-025-00826-4
‘EcoCleanR': enhancing data quality of biogeographic ranges with application for marine invertebrates
Soni, P., Hendy, A., & Bottjer, D. J. (2026) · Ecography · doi:10.1002/ecog.08203
Calibration of the species threat abatement and restoration metric's threat abatement component in a Costa Rican landscape
Mair, L., Brooks, T. M., Jiménez, R. R., Macfarlance, N. B. W., Nello, T., Vergez, A., Bennun, L., Curet, F., Dakmejian, A., Ellis, E. A., et al. (2026) · Conservation Biology · doi:10.1111/cobi.70231
The Neotropical Copepoda Database
dos Santos‐Silva, E. N., Cavalcanti, M. J., & Geraldes-Primeiro, L. J. D. O. (2026) · Nauplius · doi:10.1590/2358-2936e20260594
The City Nature Challenge increases urban biodiversity knowledge and public engagement with blue spacesPreprint
Morgan, M. C., Hopkins, C. R., Forster, R. M., & Gómez, Á. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.19.712856
Model‐Based Data Integration Improves Species Distribution Models for Data‐Deficient and Narrow‐Ranged Hummingbird Species
Mäkinen, J., Cohen, J., & Jetz, W. (2026) · Diversity and Distributions · doi:10.1111/ddi.70157
Leveraging local species data, a global database, and an occupancy model to explore bee–plant interactions
Lee, M. J., DiRenzo, G. V., Diao, C., & Seltmann, K. C. (2026) · Ecological Applications · doi:10.1002/eap.70221
Urbanisation of Floodplains Reduces Species Richness of Several Taxonomic Groups Worldwide
Burriat, J., Belletti, B., Dolédec, S., & Kaufmann, B. (2026) · Global Ecology and Biogeography · doi:10.1111/geb.70227
Local interaction networks reconstructed from global biodiversity data improve pollinator restoration decision makingPreprint
Baiotto, T., Cosma, C. T., Cheung, Y. Y. J., Narango, D. L., Woodard, J., McCarville, P., Echeverri, A., Horne, G. M., Wood, E. M., Williams, N. M., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.30.715389
A global tour of iNaturalist mammal data: status, trends, and outlook for macroecology and conservation
Jensen, A. J., Ackley, T., Alyetama, M., Cove, M. V., Fritzsche, L., Goldstein, B. R., Herrera, D. J., Jenkins, L., Kierepka, E. M., McMurry, S., et al. (2026) · Journal of Mammalogy · doi:10.1093/jmammal/gyag025
Unlocking biodiversity data with robotic imaging and AI-driven transcription of natural history collections
Johnson, C. A., Willigan, E., Hwang, E. Y., Austin, P. M., Chang, K. L., Daly, P., Davis, A., Gonzalez, J. M., Kao, C.-N., Mifsud, I. E. J., et al. (2026) · Science Advances · doi:10.1126/sciadv.aeb6975
Distribution and First Insights into Habitat Preferences of the Armless Snake Eel Dalophis imberbis (Delaroche, 1809) (Anguilliformes: Ophichthidae) from New Occurrence Sites in the Central Mediterranean Sea
Battiata, M., Sirchia, B., & Brutto, S. L. (2026) · Oceans · doi:10.3390/oceans7030041
A data-driven redefinition of global biodiversity hotspotsPreprint
Liu, X. W., Lindenmayer, D. B., Chapman, C. A., Garber, P. A., Li, R. K., Grueter, C. C., Wu, R., & Yang, Y. P. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.07.721789
Blue genes, green promises: linking marine gene patents to biotechnology and sustainable development
Zhivkoplias, E. K., Dunshirn, P., Jouffray, J., Jaspars, M., & Blasiak, R. (2026) · Frontiers in Marine Science · doi:10.3389/fmars.2026.1833479
Geographic biases and gaps in the sampling of plant–pollinator networks
Brito, E. L. S., McDonald, R., Almeida‐Neto, M., & Ponisio, L. C. (2026) · Ecography · doi:10.1002/ecog.08368
Mobilizing bibliographic, natural history collections and citizen science data for addressing biodiversity biases: A case study with the herpetofauna of an endemic rich island nation
de Sousa, A. C. A., Santos, B. S., Parrinha, D., BARBOSA, M., Marques, M. P., Passos, P., & Ceríaco, L. M. P. (2026) · Natural History Collections and Museomics · doi:10.3897/nhcm.3.184711
Christa Deeleman-Reinhold (1930-2025): An AI-generated memorial dataset of specimens cited across a career in arachnology
Miller, J. (2026) · Biodiversity Data Journal · doi:10.3897/bdj.14.e164744
Self-citation
Big data analysis of animal movements in aquatic ecosystems with acoustic telemetryPreprint
Lavender, E., Futia, M. H., Scheidegger, A., Biber, S. W., Brodersen, J., Briers, R. A., Thorburn, J., & Albert, C. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.01.729394
From promises to practice: a call for building an integrated, decolonial, and stable framework for Amazonian science
Rabelo, R. M., Juen, L., Rodrigues, D., Penha, D., Hirota, M., & Rosa, C. (2026) · Perspectives in Ecology and Conservation · doi:10.1016/j.pecon.2026.05.003
Parcelas-CL: a community-sourced vegetation dataset for multi-scale biodiversity monitoring in ChilePreprint
Cerda, J. M., Miranda, A., Altamirano, A., Becerra, P. I., Dobbs, C., Galleguillos, M., Miranda, M. D., Morales, N. S., Ovalle, J. F., Venegas‐González, A., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-9986019/v1
A scalable exemplar-based method for aligning biological taxonomies
Rees, J., Franz, N. M., & Sterner, B. (2026) · Biodiversity Data Journal · doi:10.3897/bdj.14.e191754
Connecting links with code: AI in morphological evolution
Singh, N., Chaturvedi, P., & Saxena, D. (2026) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2026.1825851
AdriaVeg: an integrated vegetation database for ecological monitoring and conservation along the central Adriatic coast (Italy)
de Francesco, M. C., Carranza, M. L., Rasino, M. D. V., Varricchione, M., & Stanisci, A. (2026) · Vegetation Ecology and Diversity · doi:10.3897/ved.190831
AI and Data Analytics in Biodiversity Conservation: Insights from Research and Applications
Choudhary, S. (2026) · Springer eBooks · doi:10.1007/978-3-032-28217-0_3
Designing for biodiversity data in place: Species, encounters, and interfaces
Whitelaw, M., Mackenzie, A., Westgate, M., & Morrow, K. (2026) · People and Nature · doi:10.1002/pan3.70384
Les collections biologiques du domaine du Paraclet :un référentiel taxonomique et un socle pédagogiquepour l’Office français de la biodiversité
FILLERIN, E., MARIN, L., & Denys, G. P. J. (2026) · Naturae · doi:10.5852/naturae2026a8
New species of Microlicia (Melastomataceae) and identification key for the genus in Ouro Preto, Minas Gerais, Brazil
Romero, R., Bertolini, M. A., Paranhos, G. M., & Versiane, A. F. A. (2026) · Anais da Academia Brasileira de Ciências · doi:10.1590/0001-3765202620250968
A comprehensive assessment framework of jurisdiction-level ecosystem diversity based on multisource data: a case study of Laifeng County, Hubei Province, China
Li, A., Zhang, J., Li, K., & Li, Z. (2026) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2026.1869892
Integrating Biosynthetic, Genomic and Ecological Open Data for Medicinal Plant Research: A Leakage-Aware Evidence-Prioritization Framework
Samarina, L. S., Terletskaya, N. V., & Orlov, Y. L. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27156801
Thinking big: the case for experimental macroecology
Matias, M. G., Alexander, J. M., Freestone, A. L., Araújo, M. B., & Vandvik, V. (2026) · Ecography · doi:10.1002/ecog.09026
Beyond Balance: An Ethnography of Validity and Engagement in Citizen Science Practice
Schwarzfuchs, E. N. (2026) · Social Studies of Science · doi:10.1177/03063127261465311
Quality Assurance Framework for the Design, Collection and Curation of Standard Data Products From a Distributed Ecology Network
Buckley, Y. M., Finn, A., Molloy, A., Csergő, A. M., Crone, E. E., Smith, A. L., Elderd, B. D., McKeon, C. M., Roach, D. A., Childs, D. Z., et al. (2026) · Ecology and Evolution · doi:10.1002/ece3.74000
From collection to sharing: Strategies for standardising and publishing occurrence data in biodiversity platforms in the UFMG-AC Acarological Collection
de Assis-Silva, M. H., Góes-Neto, A., & Pepato, A. R. (2026) · Natural History Collections and Museomics · doi:10.3897/nhcm.3.195668
Peyzaj geçirgenliği ve tür gözlemlerinin bütünleşik kullanımıyla ekolojik koridorların belirlenmesi: Tavas, Denizli
Ünver, A., & Sarun, F. (2026) · TURKISH JOURNAL OF FOREST SCIENCE · doi:10.32328/turkjforsci.1872903
Assessing the Conservation Status, Drivers of Threat and Available Occurrence Records of Sub‐Saharan African Freshwater Molluscs: Gaps and Patterns
Kruger, M., der Colff, D. V., & Malherbe, W. (2026) · African Journal of Ecology · doi:10.1111/aje.70216
Improving Fine-Grained Tree Species Recognition with Taxonomy-Aware Angular-Margin LearningPreprint
Keskes, M. I., & Niță, M. D. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7317101
Untapped potential of European natural history collections of megadiverse Diptera
Nania, D., Pape, T., Meier, R., Mengual, X., McAlister, E., Hartop, E., Стоев, П., BUELVAS, D. A., Douglas, R., Ekrem, T., et al. (2026) · BioScience · doi:10.1093/biosci/biag123
Centuries of Potato Late Blight: Tracking Global Epidemics and Managing Future Outbreaks
Ristaino, J. B. (2026) · Annual Review of Phytopathology · doi:10.1146/annurev-phyto-011325-113146
A workflow for impact indicators of alien species: A demonstration with Acacia species
Yahaya, M. M., Kumschick, S., MacFadyen, S., Landi, P., & Hui, C. (2026) · NeoBiota · doi:10.3897/neobiota.109.193861
Global Research Trends in Marine Invertebrate Macroecology and Macroevolution: A Scientometric Analysis and Systematic Mapping
Farias, M. C. L., Martínez, P. A., & Jacobina, U. P. (2026) · Thalassas An International Journal of Marine Sciences · doi:10.1007/s41208-026-01229-7
Biodiversity spillovers from terrestrial ecological restoration sites in southern California
Simons, A. L., Toy, J., Timlin-Broussard, C., & Lee, J. C. (2026) · Restoration Ecology · doi:10.1111/rec.70549
The Global Biodiversity Information Facility at 25
Miller, J., Mandeville, C. P., Schigel, D., Martínez, J. G., Nielsen, A. M., Sheldon, S., Hahn, A., Raymond, M. R., Bundgaard-Jensen, S., Laursen, M. B., et al. (2026) · Biodiversity Data Journal · doi:10.3897/bdj.14.e208528
Self-citation
Lithological context of source-audited nickel hyperaccumulator and accumulator plant records in Türkiye: A descriptive geobotanical synthesis
Ünver, A. (2026) · Anatolian Journal of Botany · doi:10.30616/ajb.1960053
Range‐Wide Molecular Systematics of Mastiff Bats Reveals Heterogeneous Lineage Differentiation and Two Unrecognised Lineages in the Neotropics
Acosta, D. B., Montani, M. E., de Weston, G. G., Merino, M. L., & Díaz, M. M. (2026) · Zoologica Scripta · doi:10.1111/zsc.70093
Guidelines and best practices for the scientific use of global iNaturalist data
Callaghan, C. T., Campbell, C. J., Widness, J., Goldstein, B. R., Mesaglio, T., Seltzer, C. E., Iwane, T., Guralnick, R., & Mason, B. M. (2026) · BioScience · doi:10.1093/biosci/biag135
Macroevolutionary dynamics and predictors of tropical rain forest plant diversity
Holzmeyer, L., Nge, F. J., Guerrero, S. A., Armstrong, K. E., Bazante, M. L., Bijmoer, R., Borosova, R., Bruy, D., Bunchalee, P., Chaowasku, T., et al. (2026) · Science Advances · doi:10.1126/sciadv.aee4197
Integrating molecular approaches for standardised monitoring of North Sea biodiversity and ecosystem dynamics
Valk, S., Doorenspleet, K., van Berkel, D., van den Brink, X., Jansen, L., Oosterbroek, S., Nijland, R., & Sumner-Hempel, A. (2026) · BMC Marine Science · doi:10.1186/s44479-026-00009-w
From raw occurrence records to accessible knowledge: Transforming biodiversity infrastructure through evidence-manifesting design
Bacu, V. I., Nandra, C. I., Ştefănuţ, T., Sabou, A., Miok, K., Patoka, J., Graham, Z. A., Hartzell, S. M., Lieb, D. A., Huber, A. F., et al. (2026) · Ecological Informatics · doi:10.1016/j.ecoinf.2026.104075 · Cited by 1
SAPU RESIK: An Open-Data Decision-Support Dashboard for Prioritizing Suckermouth Armored Catfish Surveys in Jakarta Urban Rivers
Aji, T. W., Sinambela, M., & Azizah, L. M. (2026) · International Conference on Information Technology and Computing (ICITCOM) · doi:10.1109/icitcom70739.2026.11714352
OptiScale: A data-driven framework for selecting spatial and temporal resolution in biodiversity analysis
Martinez, E. S., Tejada-Gutiérrez, E. L., Calcaterra, M., Eleiwa, A., Mateo, J., Solsona, F., Albert Sorribas, B., Marı́n-Sanguino, A., Asín, J., Vilaprinyó, E., et al. (2026) · Ecological Informatics · doi:10.1016/j.ecoinf.2026.104084
Ten rules for robust taxonomy in ecological datasets
de Lima, R. A. F., Grittz, G. S., Fernandes, M. F., ter Steege, H., Dexter, K. G., Phillips, O. L., Morim, M. P., Chave, J., Derroire, G., França, F. M., et al. (2026) · New Phytologist · doi:10.1111/nph.71658
Temporal dynamics of biodiversity data reveal emerging gaps in the monitoring of Brazilian anurans
Sardinha, T. A., & Nomura, F. (2026) · Biological Conservation · doi:10.1016/j.biocon.2026.112164

Authors: Heberling, J. M., Miller, J. T., Noesgaard, D., Weingart, S. B., & Schigel, D.
Affiliations: Carnegie Museum of Natural History (US)
Global Biodiversity Information Facility (DK)
Carnegie Mellon University (US)
Corresponding author: Heberling, J. Mason
ORCID: Heberling, J. Mason
Miller, Joseph T.
Noesgaard, Daniel
Weingart, Scott B.
Schigel, Dmitry
Venue: Proceedings of the National Academy of Sciences
Publisher: National Academy of Sciences
Published: 2021-02
Volume: 118
Issue: 6
ISSN: 0027-8424 (ISSN-L)
1091-6490
DOI: 10.1073/pnas.2018093118
PMC: PMC8017944
OpenAlex: W3127515314
Cited by: 380
References: 65
Citations by year: 2026: 81 · 2025: 76 · 2024: 72 · 2023: 66 · 2022: 64 · 2021: 21
FWCI: 50.42
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
Locations: Proceedings of the National Academy of Sciences (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Topics: Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
Keywords: biodiversity data integration, GBIF, citizen science, species distribution modeling, macroecology
MeSH terms: Animals, Classification, Humans, Museums, Databases, Factual, Biodiversity

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data integration enables global biodiversity synthesis

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks