CoChat
Sign Up
Cited by 614

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Global trait–environment relationships of plant communities

Bruelheide, Helge, Dengler, Jürgen, Purschke, Oliver, Lenoir, Jonathan, Jiménez-Alfaro, Borja, Hennekens, Stephan M., Botta-Dukát, Zoltán, Chytrý, Milan, Field, Richard, Jansen, Florian, Kattge, Jens, Pillar, Valério D., Schrodt, Franziska, Mahecha, Miguel D., Peet, Robert K., Sandel, Brody, van Bodegom, Peter, Altman, Jan, Alvarez-Dávila, Esteban, Arfin Khan, Mohammed A. S., Attorre, Fabio, Aubin, Isabelle, Baraloto, Christopher, Barroso, Jorcely G., Bauters, Marijn, Bergmeier, Erwin, Biurrun, Idoia, Bjorkman, Anne D., Blonder, Benjamin, Čarni, Andraž, Cayuela, Luis, Černý, Tomáš, Cornelissen, J. Hans C., Craven, Dylan, Dainese, Matteo, Derroire, Géraldine, De Sanctis, Michele, Díaz, Sandra, Doležal, Jiří, Farfan-Rios, William, Feldpausch, Ted R., Fenton, Nicole J., Garnier, Eric, Guerin, Greg R., Gutiérrez, Alvaro G., Haider, Sylvia, Hattab, Tarek, Henry, Greg, Hérault, Bruno, Higuchi, Pedro, Hölzel, Norbert, Homeier, Jürgen, Jentsch, Anke, Jürgens, Norbert, Kącki, Zygmunt, Karger, Dirk N., Kessler, Michael, Kleyer, Michael, Knollová, Ilona, Korolyuk, Andrey Y., Kühn, Ingolf, Laughlin, Daniel C., Lens, Frederic, Loos, Jacqueline, Louault, Frédérique, Lyubenova, Mariyana I., Malhi, Yadvinder, Marcenò, Corrado, Mencuccini, Maurizio, Müller, Jonas V., Munzinger, Jérôme, Myers-Smith, Isla H., Neill, David A., Niinemets, Ülo, Orwin, Kate H., Ozinga, Wim A., Penuelas, Josep, Pérez-Haase, Aaron, Petřík, Petr, Phillips, Oliver L., Pärtel, Meelis, Reich, Peter B., Römermann, Christine, Rodrigues, Arthur V., Sabatini, Francesco Maria, Sardans, Jordi, Schmidt, Marco, Seidler, Gunnar, Silva Espejo, Javier Eduardo, Silveira, Marcos, Smyth, Anita, Sporbert, Maria, Svenning, Jens-Christian, Tang, Zhiyao, Thomas, Raquel, Tsiripidis, Ioannis, Vassilev, Kiril, Violle, Cyrille, Virtanen, Risto, Weiher, Evan, Welk, Erik, Wesche, Karsten, Winter, Marten, Wirth, Christian, Jandt, Ute·2018·Nature Ecology & Evolution
DOI 10.1038/s41559-018-0699-8
Open this paper in CoChat — free account

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41559-018-0699-8

Cites

3 of 3 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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?

  • Changes in species composition and associated plant traits impact ecosystem processes and functioning and the resilience of ecosystems to current anthropogenic or climatic pressures.

    “Changes in species composition and associated plant traits ultimately impact ecosystem processes and functioning (Bruelheide et al., 2018;Fortunel et al., 2016), and its resilience to withstand current anthropogenic or climatic pressures.”

    From Pre‐contact and post‐colonial ecological legacies shape Surinamese rainforests (2024) · cites this paper as Bruelheide et al., 2018

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

Flagged first, then by citations

Research works printed but not linked: 50

  1. Warming, E. Lehrbuch der ökologischen Pflanzengeographie – Eine Einführung in die Kenntnis der Pflanzenvereine (Borntraeger, Berlin, 1896).
  2. Ordoñez, J. C. A global study of relationships between leaf traits, climate and soil measures of nutrient fertility. Glob. Ecol. Biogeogr. 18, 137–149 (2009). · DOI
  3. Garnier, E., Navas, M.-L. & Grigulis, K. Plant Functional Diversity – Organism Traits, Community Structure, and Ecosystem Properties (Oxford Univ. Press, Oxford, 2016). · DOI
  4. Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016). · DOI
  5. Moles, A. T. et al. Global patterns in plant height. J. Ecol. 97, 923–932 (2009). · DOI
  6. Reich, P. B. The world-wide ‘fast–slow’ plant economics spectrum: a traits manifesto. J. Ecol. 102, 275–301 (2014). · DOI
  7. Adler, P. B. et al. Functional traits explain variation in plant life history strategies. Proc. Natl Acad. Sci. USA 111, 740–745 (2014). · DOI
  8. Marks, C. O. & Lechowicz, M. J. Alternative designs and the evolution of functional diversity. Am. Nat. 167, 55–67 (2006). · DOI
  9. Grime, J. P. Trait convergence and trait divergence in herbaceous plant communities: mechanisms and consequences. J. Veg. Sci. 17, 255–260 (2006). · DOI
  10. Muscarella, R. & Uriarte, M. Do community-weighted mean functional traits reflect optimal strategies?. Proc. R. Soc. B 283, 20152434 (2016). · DOI
  11. Swenson, N. G. & Weiser, M. D. Plant geography upon the basis of functional traits: an example from eastern North American trees. Ecology 91, 2234–2241 (2010). · DOI
  12. Fyllas, N. M. et al. Basin-wide variations in foliar properties of Amazonian forest: phylogeny, soils and climate. Biogeosciences 6, 2677–2708 (2009). · DOI
  13. Swenson, N. G. et al. Phylogeny and the prediction of tree functional diversity across novel continental settings. Glob. Ecol. Biogeogr. 26, 553–562 (2017). · DOI
  14. Swenson, N. G. et al. The biogeography and filtering of woody plant functional diversity in North and South America. Glob. Ecol. Biogeogr. 21, 798–808 (2012). · DOI
  15. Wright, I. J. et al. Global climatic drivers of leaf size. Science 357, 917–921 (2017). · DOI
  16. Mayfield, M. M. & Levine, J. M. Opposing effects of competitive exclusion on the phylogenetic structure of communities. Ecol. Lett. 13, 1085–1093 (2010). · DOI
  17. Kraft, N. J. B. et al. Community assembly, coexistence and the environmental filtering metaphor. Funct. Ecol. 29, 592–599 (2015). · DOI
  18. Barboni, D. et al. Relationships between plant traits and climate in the Mediterranean region: a pollen data analysis. J. Veg. Sci 15, 635–646 (2004). · DOI
  19. Borgy, B. et al. Plant community structure and nitrogen inputs modulate the climate signal on leaf traits. Glob. Ecol. Biogeogr. 26, 1138–1152 (2017). · DOI
  20. van Bodegom, P. M., Douma, J. C. & Verheijen, L. M. A fully traits-based approach to modeling global vegetation distribution. Proc. Natl Acad. Sci. USA 111, 13733–13738 (2014). · DOI
  21. Moles, A. T. et al. Which is a better predictor of plant traits: temperature or precipitation? J. Veg. Sci. 25, 1167–1180 (2014). · DOI · Paper page
  22. Ordoñez, J. C. et al. Plant strategies in relation to resource supply in mesic to wet environments: does theory mirror nature?. Am. Nat. 175, 225–239 (2010). · DOI
  23. Simpson, A. J., Richardson, S. J. & Laughlin, D. C. Soil–climate interactions explain variation in foliar, stem, root and reproductive traits across temperate forests. Glob. Ecol. Biogeogr. 25, 964–978 (2016). · DOI
  24. Lienin, P. & Kleyer, M. Plant leaf economics and reproductive investment are responsive to gradients of land use intensity. Agric. Ecosyst. Environ. 145, 67–76 (2011). · DOI
  25. Maire, V. et al. Habitat filtering and niche differentiation jointly explain species relative abundance within grassland communities along fertility and disturbance gradients. New Phytol. 196, 497–509 (2012). · DOI
  26. Craine, J. M. et al. Global patterns of foliar nitrogen isotopes and their relationships with climate, mycorrhizal fungi, foliar nutrient concentrations, and nitrogen availability. New Phytol. 183, 980–992 (2009). · DOI
  27. Güsewell, S. N:P ratios in terrestrial plants: variation and functional significance. New Phytol. 164, 243–266 (2004). · DOI
  28. Reich, P. B. & Oleksyn, J. Global patterns of plant leaf N and P in relation to temperature and latitude. Proc. Natl Acad. Sci. USA 101, 11001–11006 (2004). · DOI
  29. Scheiter, S., Langan, L. & Higgins, S. I. Next generation dynamic global vegetation models: learning from community ecology. New Phytol. 198, 957–969 (2013). · DOI · Paper page
  30. Boyle, B. et al. The Taxonomic Name Resolution Service: an online tool for automated standardization of plant names. BMC Bioinform. 14, 16 (2013). · DOI
  31. Bremer, B. et al. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG III. Bot. J. Linn. Soc. 161, 105–121 (2009). · DOI
  32. Kattge, J. et al. TRY ‒ a global database of plant traits. Glob. Change Biol. 17, 2905–2935 (2011). · DOI · Paper page
  33. Shan, H. et al. Gap filling in the plant kingdom – trait prediction using hierarchical probabilistic matrix factorization. In Proc. 29th Int. Conf. Machine Learning (ICML 2012) 1303−1310 (Omnipress, Madison, 2012).
  34. Fazayeli, F. et al. Uncertainty quantified matrix completion using Bayesian Hierarchical Matrix factorization. In Proc. 13th Int. Conf. Machine Learning and Applications (ICMLA 2014) 312−317 (Institute of Electrical and Electronics Engineers, Danvers, 2014). · DOI
  35. Borgy, B. et al. Sensitivity of community-level trait–environment relationships to data representativeness: a test for functional biogeography. Glob. Ecol. Biogeogr. 26, 729–739 (2017). · DOI
  36. Herz, K. et al. Drivers of intraspecific trait variation of grass and forb species in German meadows and pastures. J. Veg. Sci. 28, 705–716 (2017). · DOI
  37. Karger, D. N. et al. Climatologies at high resolution for the Earth’s land surface areas. Sci. Data 4, 170122 (2017). · DOI
  38. Karger, D. N. et al. Climatologies at High Resolution for the Earth Land Surface Areas (Version 1.1) (World Data Center for Climate (WDCC) at DKRZ, 2016); http://chelsa-climate.org/downloads/
  39. Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc 137, 553–597 (2011). · DOI · Paper page
  40. Synes, N. W. & Osborne, P. E. Choice of predictor variables as a source of uncertainty in continental-scale species distribution modelling under climate change. Glob. Ecol. Biogeogr. 20, 904–914 (2011). · DOI
  41. Enquist, B. et al. Scaling from traits to ecosystems: developing a general trait driver theory via integrating trait-based and metabolic scaling theories. Adv. Ecol. Res. 52, 249–318 (2015). · DOI
  42. Buzzard, V. et al. Re-growing a tropical dry forest: functional plant trait composition and community assembly during succession. Funct. Ecol. 30, 1006–1013 (2016). · DOI
  43. Rao, C. R. Diversity and dissimilarity coefficients: a unified approach. Theor. Popul. Biol. 21, 24–43 (1982). · DOI
  44. Champely, S. & Chessel, D. Measuring biological diversity using Euclidean metrics. Environ. Ecol. Stat 9, 167–177 (2002). · DOI
  45. Hawkins, B. A. et al. Structural bias in aggregated species-level variables driven by repeated species co-occurrences: a pervasive problem in community and assemblage data. J. Biogeogr. 44, 1199–1211 (2017). · DOI
  46. Knijnenburg, T. A. et al. Fewer permutations, more accurate P-values. Bioinformatics 25, i161–i168 (2009). · DOI
  47. Friendly, M. Corrgrams: exploratory displays for correlation matrices. Am. Stat. 56, 316–324 (2002). · DOI
  48. Lengyel, A., Chytrý, M. & Tichý, L. Heterogeneity-constrained random resampling of phytosociological databases. J. Veg. Sci 22, 175–183 (2011). · DOI
  49. Baselga, A. The relationship between species replacement, dissimilarity derived from nestedness, and nestedness. Glob. Ecol. Biogeogr. 21, 1223–1232 (2012). · DOI
  50. Garnier, E. et al. Towards a thesaurus of plant characteristics: an ecological contribution. J. Ecol. 105, 298–309 (2017). · DOI

Cited by

Sorted by citations

Metadata

Authors
Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez-Alfaro, B., Hennekens, S. M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., Kattge, J., Pillar, V. D., Schrodt, F., Mahecha, M. D., Peet, R. K., Sandel, B., van Bodegom, P., Altman, J., Alvarez-Dávila, E., Arfin Khan, M. A. S., Attorre, F., Aubin, I., Baraloto, C., Barroso, J. G., Bauters, M., Bergmeier, E., Biurrun, I., Bjorkman, A. D., Blonder, B., Čarni, A., Cayuela, L., Černý, T., Cornelissen, J. H. C., Craven, D., Dainese, M., Derroire, G., De Sanctis, M., Díaz, S., Doležal, J., Farfan-Rios, W., Feldpausch, T. R., Fenton, N. J., Garnier, E., Guerin, G. R., Gutiérrez, A. G., Haider, S., Hattab, T., Henry, G., Hérault, B., Higuchi, P., Hölzel, N., Homeier, J., Jentsch, A., Jürgens, N., Kącki, Z., Karger, D. N., Kessler, M., Kleyer, M., Knollová, I., Korolyuk, A. Y., Kühn, I., Laughlin, D. C., Lens, F., Loos, J., Louault, F., Lyubenova, M. I., Malhi, Y., Marcenò, C., Mencuccini, M., Müller, J. V., Munzinger, J., Myers-Smith, I. H., Neill, D. A., Niinemets, Ü., Orwin, K. H., Ozinga, W. A., Penuelas, J., Pérez-Haase, A., Petřík, P., Phillips, O. L., Pärtel, M., Reich, P. B., Römermann, C., Rodrigues, A. V., Sabatini, F. M., Sardans, J., Schmidt, M., Seidler, G., Silva Espejo, J. E., Silveira, M., Smyth, A., Sporbert, M., Svenning, J.-C., Tang, Z., Thomas, R., Tsiripidis, I., Vassilev, K., Violle, C., Virtanen, R., Weiher, E., Welk, E., Wesche, K., Winter, M., Wirth, C., & Jandt, U.
ORCID
Venue
Nature Ecology & Evolution
Publisher
Springer Science and Business Media LLC
Published
2018-11-19
Volume
2
Issue
12
Pages
1906-1917
ISSN
2397-334X
DOI
10.1038/s41559-018-0699-8
Cited by
614
References
3
Language
en
Licence

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