New handbook for standardised measurement of plant functional traits worldwide

Abstract

The authors regret that elements of Appendix 1 were incorrect in the original publication. The correct version of Appendix 1 is given below. Appendix 1. Summary of plant traits Summary of plant traits included in the handbookThe range of values corresponds to those generally reported for field-grown plants. Ranges of values are based on the literature and the authors' datasets and do not always necessarily correspond to the widest ranges that exist in nature or are theoretically possible. Recommended sample size indicates the minimum and preferred number of individuals to be sampled, so as to obtain an appropriate indication of the values for the trait of interest; when only one value is given, it corresponds to the number of individuals ( = replicates); when two values are given, the first one corresponds to the number of individuals and the second one to the number of organs to be measured per individual. Note that one replicate can be compounded from several individuals (for smaller species), whereas one individual cannot be used for different replicates. The expected coefficient of variation (CV) range gives the 20th and the 80th percentile of the CV ( = s.d. scaled to the mean) as observed in several datasets obtained for a range of field plants for different biomes. Numbering of plant traits corresponds with the numbering of the chapters in the handbook Abstract. 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 ecosystemlevel 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 ...

The global spectrum of plant form and function

“…In the case of unpublished records, they were measured following the protocols specified in the context of the LEDA project (https://www.leda-traitbase.org) or in ref. 239 (http://www. nucleodiversus.org/index.php?mod=page&id=79).…”

Functional traits in agriculture: agrobiodiversity and ecosystem services

“…There will be a need to determine and measure the relevant functional traits for the different taxa in the different components of the system and for the ecosystem processes of interest. A guide should be used to select traits and determine standard measurement [75,76]. metrics of functional trait composition can then be calculated (e.g., mean values or diversity, depending on the service of interest [77]).…”

Does greater specific leaf area plasticity help plants to maintain a high performance when shaded?

“…Specific leaf area, the ratio of leaf area to leaf dry mass, is a key functional trait of plants underlying variation in growth rate among species (Pérez-Harguindeguy et al, 2013). SLA is also a major trait in the worldwide leaf economics spectrum, which reflects the range of fast to slow returns on nutrient and dry mass investment in leaves among species (Wright et al, 2004;Flores et al, 2014).…”

“…Plants usually develop a higher SLA when grown under low-light conditions (Reich et al, 2003;Rozendaal et al, 2006;Feng and van Kleunen, 2014). This response could help plants to increase the efficiency of light capture and maximize carbon gain in such environments (Evans and Poorter, 2001;Gommers et al, 2013), because SLA tends to scale positively with the mass-based light-saturated photosynthetic rate (Pérez-Harguindeguy et al, 2013). Therefore, it is generally assumed that the plastic response of SLA enables plants to maintain a high performance under shading, and has to constitute adaptive plasticity (Valladares and Niinemets, 2008;van Kleunen et al, 2011;Feng and van Kleunen, 2014).…”