Abstract
The number of species (species richness) is certainly the most widely used descriptor of plant diversity. However, estimating richness is a difficult task because plant censuses are prone to overlooking and identification errors that may lead to spurious interpretations. We used calibration data from the French ICP-level II plots (RENECOFOR) to assess the magnitude of the two kinds of errors in large forest plots. Eleven teams of professional botanists recorded all plants on the same eight 100-m² plots in 2004 (four plots, eights teams) and 2005 (four plots, nine teams including six from 2004), first independently and then consensually. On average, 15.5% of the shrubs and trees above 2 m were overlooked and 2.3% not identified at the species level or misidentified. On average, 19.2% of the plant species below 2 m in height were overlooked and 5.3% were misidentified and 1.3% were misidentified at the genus level (especially bryophytes). The overlooking rate also varied with plant species, morphological type, plot and team. It was higher when only one botanist made the census. It rapidly decreased with species cover and increased with plot species richness, the recording time of the census in the tree layer and the number of the censuses carried out during the day in the ground layer. Familiarity of the team with the local flora reduced the risk of overlooking and identification errors, whereas training had little impact. Differences in species richness (over space or time) in large plots should be cautiously interpreted, especially when several botanists participate in the survey. In particular, the quality of the data needs to be evaluated using calibration training and, if necessary, may be improved by involving more experienced botanists working in teams and by fixing a minimum recording time.
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References
Archaux F, Bergès L, Chevalier R (2007) Are plant censuses carried out on small quadrats more reliable than on larger ones? Plant Ecol 188:179–190
Archaux F, Gosselin F, Bergès L, Chevalier R (2006) Effects of sampling time, quadrat richness and observer on exhaustiveness of plant censuses. J Veg Sci 17:299–306
Aubert M, Alard D, Bureau F (2003) Diversity of plant assemblages in managed temperate forests: a case study in Normandy (France). For Ecol Manage 175:321–337
Bates D, Maechler M, Dai B (2008) The lme4 Package. Available at: http://lme4.r-forge.r-project.org/
Camaret S, Bourjot L, Dobremez JF (2004) Suivi de la composition floristique des placettes du réseau (1994/95–2000) et élaboration d’un programme d’assurance qualité intensif. Office National des Forêts, Direction Technique, Fontainebleau
de Vries W, Reinds G, Posch M, Sanz MJ, Krause G, Calatayud V, Renaud J, Dupouey J, Sterba H, Vel E, Dobbertin M, Gundersen P, Voogd J (2003) Intensive monitoring of forest ecosystems in Europe, Technical Report 2003. EC-UN/ECE, Brussels, Geneva
Gégout JC, Coudun C, Bailly G, Jabiol B (2005) EcoPlant: a forest site database linking floristic data with soil and climate variables. J Veg Sci 16:257–260
Grabherr G, Gottfried M, Pauli H (1994) Climate effects on mountain plants. Nature 369:448
Gray AN, Azuma DL (2005) Repeatability and implementation of a forest vegetation indicator. Ecol Indic 5:57–71
Kercher SM, Frieswyk CB, Zedler JB (2003) Effects of sampling teams and estimation methods on the assessment of plant cover. J Veg Sci 14:899–906
Kirby KJ, Bines T, Burn A, Mackintosh J, Pitkin P, Smith I (1986) Seasonal and observer differences in vascular plant records from British woodlands. J Ecol 74:123–132
Klimeš L, Dancák M, Hájek M, Jongepierová I, Kucera T (2001) Scale-dependent biases in species counts in a grassland. J Veg Sci 12:699–704
Lepš J, Hadincová V (1992) How reliable are our vegetation analyses? J Veg Sci 3:119–124
Nilsson IN, Nilsson SG (1985) Experimental estimates of census efficiency and pseudoturnover on islands: error trend and between-observer variation when recording vascular plants. J Ecol 73:65–70
Økland RH (1995) Changes in the occurrence and abundance of plant species in a Norwegian boreal coniferous forest, 1988–1993. Nordic J Bot 15:415–438
R Development Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org
Scott WA, Hallam CJ (2002) Assessing species misidentification rates through quality assurance of vegetation monitoring. Plant Ecol 165:101–115
Thimonier A, Dupouey JL, Bost F, Becker M (1994) Simultaneous eutrophication and acidification of a forest ecosystem in North-East France. New Phytol 126:533–539
Tutin TG, Heywood VH, Burges NA, Moore DM, Valentine DH, Walters SM, Webb DA (1968–1980, 1993) Flora Europaea. Cambridge University Press, 5 vols
van Tol G, van Dobben HF, Schmidt P, Klap JM (1998) Biodiversity of Dutch forest ecosystems as affected by receding groundwater levels and atmospheric deposition. Biodiv Cons 7:221–228
Vellend M, Verheyen K, Flinn KM, Jacquemyn H, Kolb A, van Calster H, Peterken G, Graae BJ, Bellemare J, Honnay O, Brunet J, Wulf M, Gerhardt F, Hermy M (2007) Homogenization of forest plant communities and weakening of species–environment relationships via agricultural land use. J Ecol 95:565–573
Acknowledgements
We thank Frédéric Gosselin for help in data analysis, Victoria Moore for carefully re-reading the manuscript and Leos Klimeš and two reviewers for constructive comments on the manuscript.
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Archaux, F., Camaret, S., Dupouey, JL. et al. Can we reliably estimate species richness with large plots? an assessment through calibration training. Plant Ecol 203, 303–315 (2009). https://doi.org/10.1007/s11258-008-9551-6
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DOI: https://doi.org/10.1007/s11258-008-9551-6