The DOI matches its Crossref record; 47 of the 48 references it cites were found in a registry or an index.
BHPMF – a hierarchical Bayesian approach to gap‐filling and trait prediction for macroecology and functional biogeography
Open accessAbstract
Aim: Functional traits of organisms are key to understanding and predicting biodiversity and ecological change, which motivates continuous collection of traits and their integration into global databases. Such trait matrices are inherently sparse, severely limiting their usefulness for further analyses. On the other hand, traits are characterized by the phylogenetic trait signal, trait–trait correlations and environmental constraints, all of which provide information that could be used to statistically fill gaps. We propose the application of probabilistic models which, for the first time, utilize all three characteristics to fill gaps in trait databases and predict trait values at larger spatial scales. Innovation: For this purpose we introduce BHPMF, a hierarchical B ayesian extension of probabilistic matrix factorization (PMF). PMF is a machine learning technique which exploits the correlation structure of sparse matrices to impute missing entries. BHPMF additionally utilizes the taxonomic hierarchy for trait prediction and provides uncertainty estimates for each imputation. In combination with multiple regression against environmental information, BHPMF allows for extrapolation from point measurements to larger spatial scales. We demonstrate the applicability of BHPMF in ecological contexts, using different plant functional trait datasets, also comparing results to taking the species mean and PMF. Main conclusions: Sensitivity analyses validate the robustness and accuracy of BHPMF: our method captures the correlation structure of the trait matrix as well as the phylogenetic trait signal – also for extremely sparse trait matrices – and provides a robust measure of confidence in prediction accuracy for each missing entry. The combination of BHPMF with environmental constraints provides a promising concept to extrapolate traits beyond sampled regions, accounting for intraspecific trait variability. We conclude that BHPMF and its derivatives have a high potential to support future trait‐based research in macroecology and functional biogeography.
Overview
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
Cites
Statistics
Verification
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?
In the citing paper
“This approach has been shown to provide significant improvements in the accuracy of predicting plant traits over traditional methods [47].”
From Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data (2017) · cites this paper as [47]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Multiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
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
mice: Multivariate Imputation by Chained Equations in R
Buuren, S. V., & Groothuis-Oudshoorn, K. (2011) · Journal of Statistical Software · doi:10.18637/jss.v045.i03 · Cited by 13,870
Missing data: our view of the state of the art
Schafer, J. L., & Graham, J. W. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.2.147 · Cited by 11,638
Matrix Factorization Techniques for Recommender Systems
Koren, Y., Bell, R. M., & Volinsky, C. (2009) · Computer · doi:10.1109/mc.2009.263 · Cited by 11,232
The worldwide leaf economics spectrum
Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z., Bongers, F., Cavender-Bares, J., Chapin, T., Cornelissen, J. H. C., Diemer, M., et al. (2004) · Nature · doi:10.1038/nature02403 · Cited by 9,021
Self-citationProbabilistic Matrix Factorization
Mnih, A., & Salakhutdinov, R. (2007) · neural information processing systems · Cited by 3,538
Towards a worldwide wood economics spectrum
Chave, J., Coomes, D. A., Jansen, S., Lewis, S. L., Swenson, N. G., & Zanne, A. E. (2009) · Ecology Letters · doi:10.1111/j.1461-0248.2009.01285.x · Cited by 3,354
TRY – a global database of plant traits
KATTGE, J., DÍAZ, S., LAVOREL, S., PRENTICE, I. C., LEADLEY, P., BÖNISCH, G., GARNIER, E., WESTOBY, M., REICH, P. B., WRIGHT, I. J., et al. (2011) · Global Change Biology · doi:10.1111/j.1365-2486.2011.02451.x · Cited by 2,638
Self-citation
Research works printed but not linked: 2
- ArcGIS Desktop E., 2011, Release 10.1
- Salakhutdinov S., 2008, Advances in Neural Information Processing Systems 20 (NIPS 07)
Cited by
Sorted by citations
Items 101–200 of 200
The fallacy of single imputation for trait databases: Use multiple imputation instead
Blomberg, S. P., & Todorov, O. S. (2025) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.14494 · Cited by 15
Walker, T. W. N., Gavazov, K., Guillaume, T., Lambert, T., Mariotte, P., Routh, D., Signarbieux, C., Block, S., Münkemüller, T., Nomoto, H. A., et al. (2022) · eLife · doi:10.7554/elife.78555 · Cited by 15
Trait filtering in island floras: A conceptual framework
Schrader, J., Wright, I. J., Kreft, H., Dixon, K. W., Gallagher, R. V., Andrew, S. C., Weigelt, P., & Westoby, M. (2023) · Journal of Biogeography · doi:10.1111/jbi.14703 · Cited by 15
Self-citationMederer, D., Feilhauer, H., Cherif, E., Berger, K., Hank, T., Kovach, K. R., Dao, P. D., Lu, B., Townsend, P. A., & Kattenborn, T. (2024) · ISPRS Open Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.ophoto.2024.100080 · Cited by 14
Using Plant Functional Traits to Define the Biomass Energy Potential of Invasive Alien Plant Species
Ceriani, A., Fratte, M. D., Agosto, G., Montagnoli, A., & Cerabolini, B. E. L. (2023) · Plants · doi:10.3390/plants12183198 · Cited by 13
Kretz, L., Schnabel, F., Richter, R., Raabgrund, A., Kattge, J., Andraczek, K., Kahl, A., Künne, T., & Wirth, C. (2025) · Plant Biology · doi:10.1111/plb.70024 · Cited by 13
Self-citationA Cautionary Note on Phylogenetic Signal Estimation from Imputed Databases
Jardim, L., Bini, L. M., Diniz‐Filho, J. A. F., & Villalobos, F. (2021) · Evolutionary Biology · doi:10.1007/s11692-021-09534-0 · Cited by 13
Integration and harmonization of trait data from plant individuals across heterogeneous sources
Lenters, T. P., Henderson, A., Dracxler, C. M., Elias, G. A., Kamga, S. M., Couvreur, T. L. P., & Kissling, W. D. (2021) · Ecological Informatics · doi:10.1016/j.ecoinf.2020.101206 · Cited by 13
Veeken, A., Santos, M. J., McGowan, S., Davies, A. L., & Schrodt, F. (2022) · Ecology Letters · doi:10.1111/ele.14063 · Cited by 13
Self-citationLatitudinal Variation in Plant Functional Types
Gillison, A. N. (2018) · Geobotany studies · doi:10.1007/978-3-319-68738-4_2 · Cited by 13
Self-citationVleminckx, J., Hogan, J. A., Metz, M. R., Comita, L. S., Queenborough, S. A., Wright, S. J., Valencia, R., Zambrano, M., & Garwood, N. C. (2023) · New Phytologist · doi:10.1111/nph.19388 · Cited by 12
Self-citationThe impact of trait number and correlation on functional diversity metrics in real-world ecosystems
Ohlert, T., Kimmel, K. A., Avolio, M. L., Chang, C. C., Forrestel, E. J., Gerstner, B. P., Hobbie, S. E., Reich, P. B., Whitney, K. D., & Komatsu, K. J. (2024) · PLoS ONE · doi:10.1371/journal.pone.0306342 · Cited by 12
Self-citationThe effect of niche filtering on plant species abundance in temperate grassland communities
Cubino, J. P., Axmanová, I., Lososová, Z., Večeřa, M., Bergamini, A., Bruelheide, H., Dengler, J., Jandt, U., Jansen, F., Pätsch, R., et al. (2021) · Functional Ecology · doi:10.1111/1365-2435.13994 · Cited by 12
Jing, H., Xiong, X., Jiang, F., Pu, X., Ma, W., Li, D., Liu, Z., & Wang, Z. (2023) · Science China Life Sciences · doi:10.1007/s11427-022-2338-1 · Cited by 11
Kambach, S., Attorre, F., Axmanová, I., Bergamini, A., Biurrun, I., Bonari, G., Carranza, M. L., Chiarucci, A., Chytrý, M., Dengler, J., et al. (2024) · Global Change Biology · doi:10.1111/gcb.17189 · Cited by 12
A causal trait model for explaining foliar water uptake capacity
Matos, I. S., Rifai, S. W., Gouveia, W. F., Menor, I. O., Mantuano, D. G., & Rosado, B. H. P. (2024) · Journal of Vegetation Science · doi:10.1111/jvs.13258 · Cited by 11
Use and misuse of trait imputation in ecology: the problem of using out‐of‐context imputed values
Gorné, L. D., Aguirre‐Gutiérrez, J., Souza, F. C., Swenson, N. G., Kraft, N. J. B., Marimon, B. S., Baker, T. R., de Lima, R. A. F., Vilanova, E., Álvarez‐Dávila, E., et al. (2025) · Ecography · doi:10.1111/ecog.07520 · Cited by 11
Self-citationRauschkolb, R., Herben, T., Kattge, J., Knickmann, B., Linstädter, A., Menzel, A., Mora, K., Nordt, B., Vitasse, Y., Weigelt, P., et al. (2025) · Functional Ecology · doi:10.1111/1365-2435.70020 · Cited by 11
Self-citationCrowdsourced biodiversity monitoring fills gaps in global plant trait mapping
Lusk, D., Wolf, S., Svidzinska, D., Dormann, C. F., Kattge, J., Bruelheide, H., Sabatini, F. M., Damasceno, G., Moreno‐Martínez, Á., Violle, C., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-68996-y · Cited by 14
Self-citationStructure optimization of prior-knowledge-guided neural networks
Atwya, M., & Panoutsos, G. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.03.008 · Cited by 12
Crowd-sourced trait data can be used to delimit global biomes
Scheiter, S., Wolf, S., & Kattenborn, T. (2024) · Biogeosciences · doi:10.5194/bg-21-4909-2024 · Cited by 11
Finding fungal ecological strategies: Is recycling an option?
Zanne, A. E., Powell, J. R., Flores‐Moreno, H., Kiers, E. T., Padje, A. V. ’., & Cornwell, W. K. (2019) · Fungal ecology · doi:10.1016/j.funeco.2019.100902 · Cited by 11
Toward a global repository of insect traits ( GRIT )
Cardoso, P., Baker, N. J., Boieiro, M., Bonte, D., Borges, P. A. V., Braby, M. F., Branco, V. V., Chobanov, D., Correia, L., Dalton, D. T., et al. (2025) · Insect Conservation and Diversity · doi:10.1111/icad.70035 · Cited by 10
Schrodt, F., de la Barreda-Bautista, B., Williams, C., Boyd, D. S., Schaepman‐Strub, G., & Santos, M. J. (2020) · Springer eBooks · doi:10.1007/978-3-030-33157-3_17 · Cited by 10
Self-citationMinding the gap: Range size and economic use drive functional trait data gaps in the Atlantic forest
Petisco‐Souza, A. C., Brum, F. T., Marcilio‐Silva, V., Zwiener, V. P., Zanella, A., Dias, A. S., González‐Melo, A., Jansen, S., Mazzochini, G. G., Niinemets, Ü., et al. (2023) · Biological Conservation · doi:10.1016/j.biocon.2023.110087 · Cited by 10
Gaikwad, J., Triki, A., & Bouaziz, B. (2019) · Biodiversity Information Science and Standards · doi:10.3897/biss.3.37091 · Cited by 10
Extinction selectivity obscures patterns of trait‐dependent endangerment in Columbiformes
Martínez-Rubio, N., Sayol, F., & Lapiedra, O. (2024) · Global Ecology and Biogeography · doi:10.1111/geb.13851 · Cited by 7
Trait‐based numerical classification of mesic and wet grasslands in Poland
Lengyel, A., Swacha, G., Botta‐Dukát, Z., & Kącki, Z. (2019) · Journal of Vegetation Science · doi:10.1111/jvs.12850 · Cited by 9
Towards an Ecological Trait-data StandardPreprint
Schneider, F. D., Jochum, M., Provost, G. L., Ostrowski, A., Penone, C., Fichtmueller, D., Güntsch, A., Goßner, M. M., König‐Ries, B., Manning, P., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/328302 · Cited by 9
Komatsu, K. J., Avolio, M. L., Cubino, J. P., Schrodt, F., Auge, H., Cavender-Bares, J. M., Clark, A. T., Flores‐Moreno, H., Grman, E., Harpole, W. S., et al. (2024) · Scientific Data · doi:10.1038/s41597-024-03637-x · Cited by 9
Self-citationVernham, G., Bailey, J. J., Field, R., & Schrodt, F. (2024) · Global Ecology and Biogeography · doi:10.1111/geb.13904 · Cited by 8
Self-citationNetwork-informed analysis of a multivariate trait-space reveals optimal trait selection
Pan, Q., Bauters, M., Peaucelle, M., Ellsworth, D. S., Kattge, J., & Verbeeck, H. (2025) · Communications Biology · doi:10.1038/s42003-025-07940-0 · Cited by 8
Self-citationGaps in Global Alien Plant Trait Data and How to Fill Them
Grenié, M., Bruelheide, H., Dawson, W., Essl, F., van Kleunen, M., Kühn, I., Kreft, H., Pyšek, P., Weigelt, P., & Winter, M. (2025) · Global Ecology and Biogeography · doi:10.1111/geb.70131 · Cited by 8
Vleminckx, J., Bauman, D., Demanet, M., Hardy, O. J., Doucet, J., & Drouet, T. (2020) · Journal of Vegetation Science · doi:10.1111/jvs.12861 · Cited by 8
Huang, Y., Cai, H., Jian, S., Wang, J., Kollmann, J., Hui, D., Zhang, L., Lü, H., & Ren, H. (2023) · Journal of Environmental Management · doi:10.1016/j.jenvman.2023.118512 · Cited by 8
Sanders, T. B., Solan, M., & Godbold, J. A. (2025) · Functional Ecology · doi:10.1111/1365-2435.14743 · Cited by 8
Li, X., Burrows, G. E., Dong, N., Jordan, G. J., Kattge, J., Lenz, T. I., Niinemets, Ü., Onoda, Y., Poorter, H., Sack, L., et al. (2025) · New Phytologist · doi:10.1111/nph.70397 · Cited by 7
Self-citationMapping Plant Functional Traits Using Gap‐Filled Datasets to Inform Management and Modelling
Andrew, S. C., Martín‐Forés, I., Guerin, G. R., Coleman, D., Falster, D. S., Wenk, E. H., Wright, I. J., & Gallagher, R. V. (2025) · Global Ecology and Biogeography · doi:10.1111/geb.70136 · Cited by 7
Self-citationSiefert, A., Laughlin, D. C., & Sabatini, F. M. (2024) · Journal of Vegetation Science · doi:10.1111/jvs.13314 · Cited by 7
Martín‐Forés, I., Andrew, S. C., Guerin, G. R., & Gallagher Rachael, V. (2023) · CABI eBooks · doi:10.1079/9781800622197.0005 · Cited by 7
A Multi-Stage Approach for Knowledge-Guided Predictions With Application to Additive Manufacturing
Chung, S., Chou, C.-H., Fang, X., Kontar, R. A., & Okwudire, C. E. (2022) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2022.3160420 · Cited by 7
Guo, W., Serra-Diaz, J. M., Schrodt, F., Eiserhardt, W. L., Maitner, B., Merow, C., Violle, C., Blach‐Overgaard, A., Zhang, J., Anand, M., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.06.02.128975 · Cited by 7
Self-citationGlobal functional shifts in trees driven by alien naturalization and native extinction
Guo, W.-Y., Serra-Diaz, J. M., Guo, K., Boonman, C. C. F., Schrodt, F., Maitner, B., Merow, C., Violle, C., Anand, M., Bruun, H. H., et al. (2026) · Nature Plants · doi:10.1038/s41477-025-02207-2 · Cited by 6
Self-citationBuilding trait datasets: effect of methodological choice on a study of invasion
Palma, E., Vesk, P. A., & Catford, J. A. (2022) · Oecologia · doi:10.1007/s00442-022-05230-8 · Cited by 6
Environmental drivers of taxonomic and functional turnover of tree assemblages in Europe
Cubino, J. P. (2022) · Oikos · doi:10.1111/oik.09579 · Cited by 6
Kloos, S., Lüpke, M., Estrella, N., Ghada, W., Kattge, J., Bucher, S. F., Buras, A., & Menzel, A. (2024) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2024.175753 · Cited by 6
Self-citationWorthy, S. J., Luong, J. C., Wainwright, B. E., Aguiñaga, J., Auge, H., Barcu, A. C., Batbaatar, A., Beard, K. H., Bork, E. W., Brafford, K. E., et al. (2026) · Nature Ecology & Evolution · doi:10.1038/s41559-026-02989-4 · Cited by 5
Trait‐based approaches to restoration ecology: Synthesizing insights from diverse systems
Briand, J. K., Hosler, S. C., Merchant, T. K., Vinebrooke, R. D., Ostertag, R., Symons, C. C., Cadotte, M. W., Eviner, V. T., Bracken, M. E. S., Carlson, R. R., et al. (2026) · Ecological Applications · doi:10.1002/eap.70193 · Cited by 5
Dugerdil, L., Peyron, O., Violle, C., Joannin, S., Ménot, G., Denelle, P., Bruelheide, H., Chytrý, M., Field, R., Hatim, M. Z., et al. (2025) · Journal of Biogeography · doi:10.1111/jbi.15100 · Cited by 5
Self-citationPhylogenetically informed predictions outperform predictive equations in real and simulated data
Gardner, J. D., Baker, J., Venditti, C., & Organ, C. L. (2025) · Nature Communications · doi:10.1038/s41467-025-61036-1 · Cited by 5
Panter, C. T., Kambach, S., Bachman, S. P., Baines, O., Bruelheide, H., Sporbert, M., Hähn, G. J. A., Field, R., & Schrodt, F. (2025) · Nature Communications · doi:10.1038/s41467-025-63566-0 · Cited by 5
Self-citationGlobal patterns of plant form and function are strongly determined by evolutionary relationshipsPreprint
Capdevila, P., Walker, T. W. N., Schrodt, F., Rodríguez‐Caro, R. C., & Salguero‐Gómez, R. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.13.523963 · Cited by 5
Self-citationSoil water, plant functional traits and their interaction jointly shaped sap flow density
Zhang, Y., Chen, X., Guo, Y., Zuo, Z., Amantai, N., & Tang, Z. (2025) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2025.110881 · Cited by 4
A Global Regionalisation of Tree Functional Capacity
Jimenez, Y. G., Paz, A., Bialic‐Murphy, L., Crowther, T. W., & Maynard, D. S. (2025) · Global Ecology and Biogeography · doi:10.1111/geb.70083 · Cited by 4
Distribution patterns and climate limitations of typical shrublands in northern China
Guo, Y., Gheyret, G., Liu, T., ZHANG, Y., MuYi, K. A. N. G., Mohhamot, A., Liu, H., Ma, W., Wang, R., Yu, S., et al. (2020) · Scientia Sinica Vitae · doi:10.1360/ssv-2020-0186 · Cited by 4
Seed Production and 22 Years of Climatic Changes in an Everwet Neotropical Forest
Vleminckx, J., Hogan, J. A., Metz, M. R., Comita, L. S., Queenborough, S. A., Wright, S. J., Valencia, R., Zambrano, M., & Garwood, N. C. (2025) · Ecology Letters · doi:10.1111/ele.70019 · Cited by 4
Self-citationSpatial exploration of plant functional types: insights from bibliometric meta-analysis
Kiran, G. S., Mohanta, A., Malhi, R. K. M., Prajapati, P. C., Oza, K. K., & Rajput, S. (2025) · Discover Plants. · doi:10.1007/s44372-025-00203-6 · Cited by 4
Knowledge Incorporation for Machine Learning in Condition Monitoring: A Survey
Hagendorfer, E. J. (2021) · International Symposium on Electrical, Electronics and Information Engineering (ISEEIE) · doi:10.1145/3459104.3459144 · Cited by 4
Hogan, J. A., Xu, H., & Baraloto, C. (2023) · Plant Ecology · doi:10.1007/s11258-023-01314-4 · Cited by 4
Haubrock, P. J., Soto, I., & Macêdo, R. L. (2025) · Journal of Applied Ecology · doi:10.1111/1365-2664.70110 · Cited by 3
He, Y., Liu, Z., Lai, J., & Mao, L. (2026) · Ecography · doi:10.1002/ecog.08026 · Cited by 3
Liu, C., Haesen, S., Dengler, J., Vynokurov, D., Biurrun, I., Kozub, Ł., Dembicz, I., Naqinezhad, A., Tóthmérész, B., Borovyk, D., et al. (2026) · Global Ecology and Biogeography · doi:10.1111/geb.70217 · Cited by 3
Environment shapes tree community traits in China's forests
Zhang, H., Yan, Y., Guo, Q., Guo, Y., Sheremetiev, S. N., & Tang, Z. (2022) · Journal of Vegetation Science · doi:10.1111/jvs.13146 · Cited by 3
Disturbance regimes drive widespread plant range disequilibrium in Europe alongside climate change
Pang, S. E. H., Buitenwerf, R., Baines, O., Aćić, S., Bernhardt‐Römermann, M., Biurrun, I., Bonari, G., Bruun, H. H., Byun, C., Chacón‐Madrigal, E., et al. (2026) · Nature Ecology & Evolution · doi:10.1038/s41559-026-03119-w · Cited by 3
Self-citationWalther, G., Jandt, U., Kattge, J., & Römermann, C. (2022) · Ecology and Evolution · doi:10.1002/ece3.9375 · Cited by 3
Self-citationSantoro, M., Cartus, O., Carvalhais, N., Rozendaal, D. M. A., Avitabile, V., Araza, A. B., de Bruin, S., Herold, M., Quegan, S., Rodríguez‐Veiga, P., et al. (2020) · doi:10.5194/essd-2020-148-supplement · Cited by 2
Langan, L., Kattenborn, T., Römermann, C., Scheiter, S., Anders, T., Wolf, S., de Paula, M. D., & Hickler, T. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.14.648688 · Cited by 2
Accounting for functional diversity in biodiversity protection measures
Lee, J. S., Brazill‐Boast, J., Cornwell, W. K., & Gallagher, R. V. (2025) · Plants People Planet · doi:10.1002/ppp3.70126 · Cited by 1
Huang, J., Yu, F., Wang, Y., Shu, L., Fang, M., Xu, M., Wang, X., Jin, S., Luo, S., & Gu, D. (2026) · Ecology and Evolution · doi:10.1002/ece3.73457 · Cited by 1
Martín‐Forés, I., Morgan, R. V., Andrew, S. C., Gallagher, R. V., & Guerin, G. R. (2026) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2026.181791 · Cited by 1
Kambach, S., Jandt, U., Acosta, A. T. R., Álvarez‐Martínez, J. M., Axmanová, I., Bazzichetto, M., Bergmeier, E., Bernhardt‐Römermann, M., Biurrun, I., Bonari, G., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-72112-5 · Cited by 1
Functional group classification using consensus clustering
Pavez, P. U., Paz, A., & Maynard, D. S. (2026) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1014278 · Cited by 1
Robustness and limitations of maximum entropy in plant community assembly
Gerkema, J., Bunker, D. E., Cunliffe, A. M., Bazzato, E., Marignani, M., Sitzia, T., Aubin, I., Chelli, S., Rosell, J. A., Poschlod, P., et al. (2025) · Ecological Informatics · doi:10.1016/j.ecoinf.2025.103031 · Cited by 1
Applying Bayesian Growth Modeling In Machine Learning For Longitudinal Data
Udomvisawakul, A. (2021) · Scholarship & Creative Works - Digital UNC a service of University Libraries (University of Northern Colorado) · Cited by 1
Pontasch, S. (2014) · doi:10.26686/wgtn.17006911 · Cited by 1
Hoss, D., Richter, A., Vélez‐Martin, E., Menezes, L. D. S., Overbeck, G. E., Debastiani, V. J., & Pillar, V. D. (2022) · doi:10.22541/au.166627302.27738942/v2 · Cited by 1
TraitCH: a multi-taxa functional trait dataset for Switzerland and EuropePreprint
Chauvier, Y., Adde, A., Bergamini, A., Rambold, G., Stofer, S., Graf, N., Gross, A., Blaser, S., Roberts, S. P. M., Potts, S. G., et al. (2026) · Earth System Science Data Discussions · doi:10.5194/essd-2025-754 · Cited by 1
A Deep Model Framework for Morphological Trait Imputation Across Taxonomic Groups
Wang, Y., Shi, X., Bai, Y., Zhu, H., Yin, X., Song, P., Ergu, D., Zhang, T., Pan, S., Gu, Z., et al. (2026) · Integrative Zoology · doi:10.1111/1749-4877.70178
Using the plant trait-based approach to study temperate grassland ecology and restoration
Hodge, J. (2026) · Warwick Research Archive Portal (University of Warwick) · doi:10.82444/warw.33768820
The assembly of island floras from a macroecological perspective.
König, C. (2019) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-7236
Li, Y. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-21964-1.00064-1
Cascading ecological risks and threshold effects in urban–buffer systemsPreprint
Li, H., Wang, Y., Liu, X., Wang, L., Shi, M., & Zhao, H. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5521928
Niittynen, P., Heikkinen, R. K., Hällfors, M. H., Määttänen, A.-M., Norros, V., & Kemppinen, J. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.03.709463
Trait misalignment risk in North American forests under climate changePreprint
Pickering, A., Newbold, T., Pigot, A. L., Tovar, C., & Maynard, D. S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.13.711509
Three key directions toward the development of a holistic crop modelling framework
Arnillas, C. A., Shah, L., Martin, A. R., & Arhonditsis, G. B. (2026) · Ecological Informatics · doi:10.1016/j.ecoinf.2026.103723
Predicting decay in functional diversity in plant communities under future climatesPreprint
Lee, J., Cornwell, W. K., Teckentrup, L., Brazill‐Boast, J., & Gallagher, R. V. (2026) · doi:10.32942/x2hw9n
En dehors de la norme : déviation de l'optimalité écologique et originalité fonctionnelle
Grenié, M. (2020) · theses.fr (ABES) · doi:10.70675/f05ff132zfc27z4c70zbb53z73e833ab6182
A Neural-Symbolic learning framework to produce interpretable predictions for image classification
Bennetot, A. (2022) · theses.fr (ABES) · doi:10.70675/2b59f598z2028z49afz8a20z29b21f19f394
Predicting decay in functional diversity in plant communities under future climatesPreprint
Lee, J., Cornwell, W. K., Teckentrup, L., Brazill‐Boast, J., & Gallagher, R. V. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6582147
He, C. N., Wang, S., Tang, Z., Chang, J., & Fang, J. (2026) · Global Ecology and Biogeography · doi:10.1111/geb.70235
Trait Gap-filling for Global Angiosperms: Method Comparison and Trait DistributionPreprint
Xu, Q., Xu, J., Luo, A., Waris, K., Wang, Z., & Li, Y. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6885422
Mleci, J. Y., Meerts, P., Vleminckx, J., Mushagalusa, F. C., Bopeke, B., Kalenga, M., & Drouet, T. (2026) · Ecosphere · doi:10.1002/ecs2.70639
Field measurements reveal local limits of imputed functional traits in tropical trees
Justino, W. D. S., Negreiros, D., Andrade, L. R. D., Zanoni, I., Pereira, M. C. A., Pierce, S., & Fernandes, G. W. (2026) · Plant Ecology · doi:10.1007/s11258-026-01660-z
Trait–Climate Relationships Are Comparable for Modern Pollen Assemblages and Extant Vegetation Plots
Dugerdil, L., Peyron, O., Violle, C., Joannin, S., Ménot, G., Denelle, P., Bruelheide, H., Field, R., Hatim, M. Z., Gholizadeh, H., et al. (2026) · Global Ecology and Biogeography · doi:10.1111/geb.70303
Self-citationPredicting decay in functional diversity in plant communities under future climates
Lee, J. S., Cornwell, W. K., Teckentrup, L., Brazill‐Boast, J., & Gallagher, R. V. (2026) · Ecological Indicators · doi:10.1016/j.ecolind.2026.115545
No Signal of Biotic Resistance to Non‐Native Species Establishment in High‐Elevation Communities
Buhaly, M., Turner, S., Kreuz, N. K., Vandvik, V., Veltmann, B., Alexander, J. M., Lembrechts, J. J., Nijs, I., Alvarez, M. A., Arévalo, J. R., et al. (2026) · Journal of Vegetation Science · doi:10.1111/jvs.70174
Song, W., Luo, A., Li, Y., Li, Y., Cui, Y., Shrestha, N., & Wang, Z. (2026) · Acta Botanica Yunnanica · doi:10.1016/j.pld.2026.09.009
Evolutionary relationship between organellar DNA inheritance patterns and traits of seed plants
Konuma, T., & Makino, T. T. (2026) · American Journal of Botany · doi:10.1002/ajb2.70272
Metadata
- Authors
- Schrodt, F., Kattge, J., Shan, H., Fazayeli, F., Joswig, J., Banerjee, A., Reichstein, M., Bönisch, G., Díaz, S., Dickie, J., Gillison, A., Karpatne, A., Lavorel, S., Leadley, P., Wirth, C. B., Wright, I. J., Wright, S. J., & Reich, P. B.
- Affiliations
- University of Minnesota (US)
- German Centre for Integrative Biodiversity Research (DE)
- Microsoft (United States) (US)
- Max Planck Institute for Biogeochemistry (DE)
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
- Royal Botanic Gardens, Kew (GB)
- Center for Biodiversity Management Yungaburra 4884 Queensland Australia
- Centre National de la Recherche Scientifique (FR)
- Université Paris-Sud (FR)
- Macquarie University (AU)
- Smithsonian Tropical Research Institute (PA)
- Corresponding author
- Schrodt, Franziska
- ORCID
- Venue
- Global Ecology and Biogeography
- Publisher
- Wiley
- Published
- 2015-07-14
- Volume
- 24
- Issue
- 12
- Pages
- 1510-1521
- ISSN
- 1466-822X (ISSN-L)
- 1466-8238
- OpenAlex
- W2117380102
- Cited by
- 206
- References
- 48
- Citations by year
- 2026: 26 · 2025: 27 · 2024: 21 · 2023: 25 · 2022: 16 · 2021: 22 · 2020: 15 · 2019: 17 · 2018: 16 · 2017: 8 · 2016: 9 · 2015: 2
- FWCI
- 12.46
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Global Ecology and Biogeography (publishedVersion)
- Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
- Nottingham ePrints (University of Nottingham) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Smithsonian Digital Repository (Smithsonian Institution) (submittedVersion)
- Funders
- University of Minnesota
- Institute on the Environment
- NSF (IIS-0812183, IIS-0916750, IIS-1029711, IIS-1017647)
- NSF CAREER award (IIS-0953274)
- Topics
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
- Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Keywords
- Bayesian hierarchical model, probabilistic matrix factorization, functional traits, phylogenetic signal, trait prediction, taxonomic hierarchy, environmental constraints, plant functional traits, intraspecific trait variation, uncertainty estimation, macroecology, functional biogeography
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
