Open AccessSampling intraspecific variability in leaf functional traits: Practical suggestions to maximize collected information
Author(s) -
Petruzzellis Francesco,
Palandrani Chiara,
Savi Tadeja,
Alberti Roberto,
Nardini Andrea,
Bacaro Giovanni
Publication year - 2017
Publication title -
ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.17
H-Index - 63
ISSN - 2045-7758
DOI - 10.1002/ece3.3617
Subject(s) - intraspecific competition , sampling (signal processing) , trait , biology , statistics , population , variance (accounting) , ecology , canopy , sample size determination , mathematics , demography , computer science , filter (signal processing) , computer vision , accounting , sociology , business , programming language
The choice of the best sampling strategy to capture mean values of functional traits for a species/population, while maintaining information about traits’ variability and minimizing the sampling size and effort, is an open issue in functional trait ecology. Intraspecific variability ( ITV ) of functional traits strongly influences sampling size and effort. However, while adequate information is available about intraspecific variability between individuals ( ITV BI ) and among populations ( ITV POP ), relatively few studies have analyzed intraspecific variability within individuals ( ITV WI ). Here, we provide an analysis of ITV WI of two foliar traits, namely specific leaf area ( SLA ) and osmotic potential (π), in a population of Quercus ilex L. We assessed the baseline ITV WI level of variation between the two traits and provided the minimum and optimal sampling size in order to take into account ITV WI , comparing sampling optimization outputs with those previously proposed in the literature. Different factors accounted for different amount of variance of the two traits. SLA variance was mostly spread within individuals (43.4% of the total variance), while π variance was mainly spread between individuals (43.2%). Strategies that did not account for all the canopy strata produced mean values not representative of the sampled population. The minimum size to adequately capture the studied functional traits corresponded to 5 leaves taken randomly from 5 individuals, while the most accurate and feasible sampling size was 4 leaves taken randomly from 10 individuals. We demonstrate that the spatial structure of the canopy could significantly affect traits variability. Moreover, different strategies for different traits could be implemented during sampling surveys. We partially confirm sampling sizes previously proposed in the recent literature and encourage future analysis involving different traits.