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Functional trait variation and sampling strategies in species‐rich plant communities
Author(s) -
Baraloto Christopher,
Timothy Paine C. E.,
Patiño Sandra,
Bonal Damien,
Hérault Bruno,
Chave Jerome
Publication year - 2010
Publication title -
functional ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.272
H-Index - 154
eISSN - 1365-2435
pISSN - 0269-8463
DOI - 10.1111/j.1365-2435.2009.01600.x
Subject(s) - resampling , sampling (signal processing) , biology , trait , statistics , sampling design , ecology , plot (graphics) , range (aeronautics) , variance (accounting) , mathematics , computer science , demography , sociology , composite material , computer vision , population , materials science , accounting , filter (signal processing) , business , programming language
Summary 1. Despite considerable interest in the application of plant functional traits to questions of community assembly and ecosystem structure and function, there is no consensus on the appropriateness of sampling designs to obtain plot‐level estimates in diverse plant communities. 2. We measured 10 plant functional traits describing leaf and stem morphology and ecophysiology for all trees in nine 1‐ha plots in terra firme lowland tropical rain forests of French Guiana ( N = 4709). 3. We calculated, by simulation, the mean and variance in trait values for each plot and each trait expected under seven sampling methods and a range of sampling intensities. Simulated sampling methods included a variety of spatial designs, as well as the application of existing data base values to all individuals of a given species. 4. For each trait in each plot, we defined a performance index for each sampling design as the proportion of resampling events that resulted in observed means within 5% of the true plot mean, and observed variance within 20% of the true plot variance. 5. The relative performance of sampling designs was consistent for estimations of means and variances. Data base use had consistently poor performance for most traits across all plots, whereas sampling one individual per species per plot resulted in relatively high performance. We found few differences among different spatial sampling strategies; however, for a given strategy, increased intensity of sampling resulted in markedly improved accuracy in estimates of trait mean and variance. 6. We also calculated the financial cost of each sampling design based on data from our ‘every individual per plot’ strategy and estimated the sampling and botanical effort required. The relative performance of designs was strongly positively correlated with relative financial cost, suggesting that sampling investment returns are relatively constant. 7. Our results suggest that trait sampling for many objectives in species‐rich plant communities may require the considerable effort of sampling at least one individual of each species in each plot, and that investment in complete sampling, though great, may be worthwhile for at least some traits.