Plant functional traits are the features (morphological, physiological, phenological) that represent ecological strategies and determine how plants respond to environmental factors, affect other trophic levels and influence ecosystem properties. Variation in plant functional traits, and trait syndromes, has proven useful for tackling many important ecological questions at a range of scales, giving rise to a demand for standardised ways to measure ecologically meaningful plant traits. This line of research has been among the most fruitful avenues for understanding ecological and evolutionary patterns and processes. It also has the potential both to build a predictive set of local, regional and global relationships between plants and environment and to quantify a wide range of natural and human-driven processes, including changes in biodiversity, the impacts of species invasions, alterations in biogeochemical processes and vegetation–atmosphere interactions. The importance of these topics dictates the urgent need for more and better data, and increases the value of standardised protocols for quantifying trait variation of different species, in particular for traits with power to predict plant- and ecosystem-level processes, and for traits that can be measured relatively easily. Updated and expanded from the widely used previous version, this handbook retains the focus on clearly presented, widely applicable, step-by-step recipes, with a minimum of text on theory, and not only includes updated methods for the traits previously covered, but also introduces many new protocols for further traits. This new handbook has a better balance between whole-plant traits, leaf traits, root and stem traits and regenerative traits, and puts particular emphasis on traits important for predicting species’ effects on key ecosystem properties. We hope this new handbook becomes a standard companion in local and global efforts to learn about the responses and impacts of different plant species with respect to environmental changes in the present, past and future.

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New handbook for standardised measurement of plant functional traits worldwide

Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests.

Physiological ecologists often analyze the responses of physiological or bio- chemical traits to environmental factors such as temperature, irradiance, water potential, or the concentrations of CO2, 0, and inorganic nutrients. The data for such a response curve typically are gathered by sequential sampling of the same plant or animal, and their analysis should explicitly allow for this repeated-measures design. Unfortunately, the sta- tistical analysis of response curves in ecology generally has either been ignored or incorrectly done. In an effort to encourage rigorous analysis of response data, we address statistical treatment of response curves and illustrate the correct alternatives that are available. Four different statistical methods for analyzing response curves are considered: analysis of vari- ance with repeated measures (ANOVAR), multivariate analysis of variance with repeated measures (MANOVAR), a nonparametric split-plot analysis (NP split-plot) and parametric comparison of models fitted to the data by nonlinear regression. Analyses of the CO2 dependence of photosynthesis in the C4 grass Echinochloa crus-galli following chilling are used as examples of these different methods. ANOVAR, potentially the most powerful analysis, makes stringent assumptions about the variance-covariance structure of the data. Within limits these assumptions can be relaxed and a corrected significance level used. When the variance-covariance structure badly violates the ANOVAR assumptions, MANOVAR or NP split-plot are viable alter- natives. In physiological ecology, however, the use of MANOVAR frequently is limited by small sample sizes and the tendency for the number of levels of the treatment factor to exceed the sample size. Greater attention to experimental design can avoid this problem. The NP split-plot is based on simple assumptions and could be widely used. The comparison of curves fitted by nonlinear regression is also distribution free and provides an interesting alternative when the responses are amenable to fitting. For any of these analyses to be viable the thoughtful choice of experimental protocols and design is essential.

The statistical analysis of ecophysiological response curves obtained from experiments involving repeated measures

We examined biomass allocation patterns throughout the entire vegetative growth phase for three species of annual plants along three separate gradients of resource availability to determine whether observed patterns of allocational plasticity are consistent with optimal partitioning theory. Individuals of the annual plant species Abutilon theophrasti, Chenopodium album, and Polygonum pensylvanicum were grown from locally field-gathered seed in controlled greenhouse conditions across gradients of light, nutrients, and water. Frequent harvests were used to determine the growth and allocation (root vs. shoot, and leaf area vs. biomass) responses of these plants over a 57-d period. Growth analysis revealed that each species displayed significant plasticity in growth rates and substantial amounts of ontogenetic drift in root:shoot biomass ratios and ratios of leaf area to biomass across each of the three resource gradients. Ontogenetically controlled comparisons of root:shoot and leaf area ratios across light ...

A. Barnes

Papers

The Biometry of Plant Growth