Abstract
Plant functional response groups (PFGs) are now widely established as a tool to investigate plant—environment relationships. Different statistical methods to form PFGs are used in the literature. One way is to derive emergent groups by classifying species based on correlation of biological attributes and subjecting these groups to tests of response to environmental variables. Another way is to search for associations of occurrence data, environmental variables and trait data simultaneously. The fourth-corner method is one way to assess the relationships between single traits and habitat factors. We extended this statistical method to a generally applicable procedure for the generation of plant functional response groups by developing new randomization procedures for presence/absence data of plant communities. Previous PFG groupings used either predefined groups or emergent groups i.e. classifications based on correlations of biological attributes (Lavorel et al Trends Ecol Evol 12:474–478, 1997), of the global species pool and assessed their functional response. However, since not all PFGs might form emergent groups or may be known by experts, we used a permutation procedure to optimise functional grouping. We tested the method using an artificial test data set of virtual plants occurring in different disturbance treatments. Direct trait-treatment relationships as well as more complex associations are incorporated in the test data. Trait combinations responding to environmental variables could be clearly distinguished from non-responding combinations. The results are compared with the method suggested by Pillar (J Veg Sci 10:631–640) for the identification of plant functional groups. After exploring the statistical properties using an artificial data set, the method is applied to experimental data of a greenhouse experiment on the assemblage of plant communities. Four plant functional response groups are formed with regard to differences in soil fertility on the basis of the traits canopy height and spacer length.
Similar content being viewed by others
References
Bugmann H (1996) Functional types of trees in temperate and boreal forests: classification and testing. J Veg Sci 7: 359–370
Castro H, Lehsten V, Freitas H (submitted) Functional response and effect traits in relation to land use change in the Montado
Condit R, Hubbell SP, Foster RB (1996) Assessing the response of plant functional types to climatic change in tropical forests. J Veg Sci 7: 405–416
Cornelissen JHC, Lavorel S et al (2003) A handbook of protocols for standardised and easy measurement of plant functional traits worldwide. Aust J Plant Physiol 51: 335–380
Doledec S, Chessel D, terBraak CJF, Champely S (1996) Matching species traits to environmental variables: a new three-table ordination method. Environ Ecol Stat 3: 143–166
Fernandez AR, Laffraga JM, Ortega F (1993) Strategies in mediterranean grassland annuals in relation to stress and disturbance. J Veg Sci 4: 313–322
Gotelli NJ (2000) Null model analysis of species co-occurrence patterns. Ecology 81: 2606–2621
Gotelli NJ, Graves GR (1996) Null models in ecology. Smisonian Institution Press, Washington
Gotelli NJ, Lewis FG, Young CM (1987) Body-size differences in a colonizing amphipod—mollusk assemblage. Oecologia 72: 104–108
Henle K, Davis KF, Kleyer M, Margules C, Settele J (2004) Predictors of species sensitivity to fragmentation. Biodivers Conserv 13: 207–251
Hope ACA (1968) A simplified Monte Carlo significance test procedure. J Roy Statist Soc Ser B 30: 582–598
Jauffret S, Lavorel S (2003) Are plant functional types relevant to describe degradation in arid, southern Tunisian steppes?. J Veg Sci 14: 399–408
Kahmen S, Poschlod P (2004) Plant functional trait responses to grassland succession over 25 years. J Veg Sci 15: 21–32
Kleyer M (1999) Distribution of plant functional types along gradients of disturbance intensity and resource supply in an agricultural landscape. J Veg Sci 10: 697–708
Kleyer M (2002) Validation of plant functional types across two contrasting landscapes. J Veg Sci 13: 167–178
Klimes L, Klimesova J (1999) CLO-PLA2—a database of clonal plants in central Europe. Plant Ecol 141: 9–19
Lavorel S, Garnier E (2002) Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. Funct Ecol 16: 545–556
Lavorel S, McIntyrre S, Landsberg J, Forbes TDA (1997) Plant functional classification from general groups to specific groups based on response to disturbance. Trends Ecol Evol 12: 474–478
Lavorel S, Rochette C, Lebreton JD (1999) Functional groups for response to disturbance in Mediterranean old fields. Oikos 84: 480–498
Legendre P, Galzin R, Vivien M (1997) Relating behavior to habitat: solutions to the fourth-corner problem. Ecology 78: 547–562
Lehsten V (2005) Functional analysis and modelling of vegetation. Oldenburg, Carl von Ossietzky University. Ph.D. Thesis, online available at http://docserver.bis.uni-oldenburg.de/publikationen/dissertation/2005/lehfun05/lehfun05.html
Lehsten V, Kleyer M (2007) Turnover of plant trait hierarchies in simulated community assembly in response to fertility and disturbance. Ecol Modell 203: 270–278
Manly BFJ (1997) Randomisation, bootstrap and Monte Carlo methods in biology. Chapman and Hall
Marby C, Ackerly D, Fritz G (2000) Landscape and species-level distribution of morphological and life history traits in a temperate woodland flora. J Veg Sci 11: 213–224
McIntyre S, Diaz S, Lavorel S, Cramer W (1999) Plant functional types and disturbance dynamics—introduction. J Veg Sci 10: 604–608
McIntyre S, Lavorel S (2001) Livestock grazing in subtropical pastures: steps in the analysis of attribute response and plant functional types. J Ecol 89: 209–226
Nygaard B, Ejrnaes R (2004) A new approach to functional interpretation of vegetation data. J Veg Sci 15: 49–56
Pillar V (1999) On the identification of optimal plant functional types. J Veg Sci 10: 631–640
Pillar VD (2003) An improved method for searching plant functional types by numerical analysis. J Veg Sci 14: 323–332
Reginster I, Rounsevell M (2006) Scenarios of future urban land use in Europe. Environ Plann B Plann Des 33: 619–636
Ribera I, Doledec S, Downie IS, Foster GN (2001) Effect of land disturbance and stress on species traits of ground beetle assemblages. Ecology 82: 1112–1129
Sale PF (1978) Coexistence of coral reef fishes—a lottery for living space. Environ Biol Fishes 3: 85–102
Semenova GV, van der Maarel E (2000) Plant functional types—a strategic perspective. J Veg Sci 11: 917–922
Skarpe C (1996) Plant functional types and climate in a southern African savanna. J Veg Sci 7: 397–404
Suding KN, Goldberg DE, Hartman KM (2003) Relationships among species traits: separating levels of response and identifying linkages to abundance. Ecology 84: 1–16
Vesk PA, Leishman MR, Westoby M (2004) Simple traits do not predict grazing response in Australian dry shrublands and woodlands. J Appl Ecol 22–31
Whittaker RH, Goodman D (1979) Classifying species according to their demographic strategy 1. Population fluctuations and environmental heterogeneity. Am Nat 113: 185–200
Wright IJ, Westoby M, Reich PB (2002) Convergence towards higher leaf mass per area in dry and nutrient-poor habitats has different consequences for leaf life span. J Ecol 90: 534–543
Zaman A, Simberloff D (2002) Random binary matrices in biogeographical ecology—instituting a good neighbor policy. Environ Ecol Stat 9: 405–421
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lehsten, V., Harmand, P. & Kleyer, M. Fourth-corner generation of plant functional response groups. Environ Ecol Stat 16, 561–584 (2009). https://doi.org/10.1007/s10651-008-0098-4
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10651-008-0098-4