N. Pérez-Harguindeguy A,Y, S. Díaz A, E. Garnier B, S. Lavorel C, H. Poorter D, P. Jaureguiberry A,
M. S. Bret-Harte E, W. K. CornwellF, J. M. CraineG, D. E. Gurvich A, C. Urcelay A,
E. J. VeneklaasH, P. B. ReichI, L. PoorterJ, I. J. WrightK, P. RayL, L. Enrico A, J. G. PausasM,
A. C. de VosF, N. BuchmannN, G. Funes A, F. Quétier A,C, J. G. HodgsonO, K. ThompsonP,
H. D. MorganQ, H. ter SteegeR, M. G. A. van der HeijdenS, L. SackT, B. BlonderU, P. PoschlodV,
M. V. Vaieretti A, G. Conti A, A. C. StaverW, S. AquinoX and J. H. C. CornelissenF
AInstituto Multidisciplinario de Biología Vegetal (CONICET-UNC) and FCEFyN, Universidad Nacional de Córdoba, CC 495, 5000 Córdoba, Argentina.
BCNRS, Centre d’Ecologie Fonctionnelle et Evolutive (UMR 5175), 1919, Route de Mende, 34293 Montpellier Cedex 5, France.
CLaboratoire d’Ecologie Alpine, UMR 5553 du CNRS, Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France.
DPlant Sciences (IBG2), Forschungszentrum Jülich, D-52425 Jülich, Germany.
EInstitute of Arctic Biology, 311 Irving I, University of Alaska Fairbanks, Fairbanks, AK 99775-7000, USA. FSystems Ecology, Faculty of Earth and Life Sciences, Department of Ecological Science, VU University, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands.
GDivision of Biology, Kansas State University, Manhtattan, KS 66506, USA.
HFaculty of Natural and Agricultural Sciences, School of Plant Biology, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia.
IDepartment of Forest Resources, University of Minnesota, 1530 N Cleveland Avenue, St Paul, MN 55108, USA and Hawkesbury Institute for the Environment, University of Western Sydney, Locked Bag 1797, Penrith, NSW 2751, Australia.
JCentre for Ecosystems, Forest Ecology and Forest Management Group, Wageningen University, PO Box 47, 6700 AA Wageningen, The Netherlands.
KDepartment of Biological Sciences, Macquarie University, Sydney, NSW 2109, Australia.
LDepartment of Biological Sciences, Stanford University, Stanford, CA, USA.
MCentro de Investigaciones sobre Desertiﬁcación (CIDE-CSIC), IVIA Campus, Carretera Nàquera km 4.5, 46113 Montcada, Valencia, Spain.
NInstitute of Agricultural Sciences, ETH Zurich, Universitätstrasse 2, LFW C56, CH-8092 Zürich, Switzerland. OPeak Science and Environment, Station House, Leadmill, Hathersage, Hope Valley S32 1BA, UK. PDepartment of Animal and Plant Sciences, The University of Shefﬁeld, Shefﬁeld S10 2TN, UK.
QNSW Department of Primary Industries, Forest Resources Research Beecroft, NSW 2119, Australia.
RNaturalis Biodiversity Center, Leiden, and Institute of Environmental Biology, Ecology and Biodiversity Group, Utrecht University, Utrecht, The Netherlands.
SEcological Farming Systems, Agroscope Reckenholz Tänikon, Research Station ART, Reckenholzstrasse 191, 8046 Zurich, Switzerland and Plant-Microbe Interactions, Institute of Environmental Biology, Faculty of Science, Utrecht University, Utrecht, The Netherlands.
TDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, 621 Charles E. Young Drive South, Los Angeles, CA 90095-1606, USA.
UDepartment of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA.
VInstitute of Botany, Faculty of Biology and Preclinical Medicine, University of Regensburg, D-93040, Regensburg, Germany.
WDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.
XCentro Agronómico Tropical de Investigación y Enseñanza, CATIE 7170, Cartago, Turrialba 30501, Costa Rica.
YCorresponding author. Email: firstname.lastname@example.org
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 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.
Additional keywords: biodiversity, ecophysiology, ecosystem dynamics, ecosystem functions, environmental change, plant morphology.
Received 23 November 2011, accepted 29 January 2013, published online 26 April 2013
Introduction and discussion ….. 169
1 Selection of species and individuals ….. 170
- 1.1 Selection of species ….. 170
- 1.2 Selection of individuals within a species ….. 171
- 1.3 Replicate measurements ….. 172
2 Whole-plant traits ….. 172
- 2.1 Life history and maximum plant lifespan ….. 172
- 2.2 Life form ….. 173
- 2.3 Growth form ….. 173
- 2.4 Plant height ….. 175
- 2.5 Clonality, bud banks and below-ground storage organs ….. 176
- 2.6 Spinescence ….. 177
- 2.7 Branching architecture ….. 178
- 2.8 Leaf area : sapwood area ratio ….. 178
- 2.9 Root-mass fraction ….. 179
- 2.10 Salt resistance ….. 179
- 2.11 Relative growth rate and its components ….. 181
- 2.12 Plant ﬂammability ….. 182
- 2.13 Water-ﬂux traits ….. 184
3 Leaf traits ….. 186
- 3.1 Speciﬁc leaf area ….. 186
- 3.2 Area of a leaf ….. 189
- 3.3 Leaf dry-matter content ….. 190
- 3.4 Leaf thickness ….. 190
- 3.5 pH of green leaves or leaf litter ….. 191
- 3.6 Leaf nitrogen (N) concentration and leaf phosphorous (P) concentration ….. 192
- 3.7 Physical strength of leaves ….. 193
- 3.8 Leaf lifespan and duration of green foliage ….. 195
- 3.9 Vein density ….. 197
- 3.10 Light-saturated photosynthetic rate ….. 198
- 3.11 Leaf dark respiration ….. 198
- 3.12 Photosynthetic pathway ….. 199
- 3.13 C-isotope composition as a measure of intrinsic water-use efﬁciency ….. 200
- 3.14 Electrolyte leakage as an indicator of frost sensitivity ….. 201
- 3.15 Leaf water potential as a measure of water status ….. 202
- 3.16 Leaf palatability as indicated by preference by model herbivores ….. 203
- 3.17 Litter decomposability ….. 205
4 Stem traits ….. 207
- 4.1 Stem-speciﬁc density ….. 207
- 4.2 Twig dry-matter content and twig drying time ….. 209
- 4.3 Bark thickness (and bark quality) ….. 209
- 4.4 Xylem conductivity ….. 210
- 4.5 Vulnerability to embolism ….. 211
5 Below-ground traits ….. 212
- 5.1 Speciﬁc root length ….. 212
- 5.2 Root-system morphology ….. 214
- 5.3 Nutrient-uptake strategy ….. 214
6 Regenerative traits ….. 215
- 6.1 Dispersal syndrome ….. 215
- 6.2 Dispersule size and shape ….. 216
- 6.3 Dispersal potential ….. 216
- 6.4 Seed mass ….. 217
- 6.5 Seedling functional morphology ….. 218
- 6.6 Resprouting capacity after major disturbance ….. 218
Acknowledgements ….. 220
References ….. 220
Introduction and discussion
Environmental changes such as those on climate, atmospheric composition, land use and biotic exchanges are triggering unprecedented ecosystem changes. The need to understand and predict them has given new stimulus to a long tradition of study of the plant features (traits) that reﬂect species ecological strategies and determine how plants respond to environmental factors, affect other trophic levels and inﬂuence ecosystem properties (Kattge et al. 2011). There is mounting evidence that variation in plant traits, and trait syndromes (i.e. recurrent associations of plant traits), within and among species, is associated with many important ecological processes at a range of scales. This has resulted in strong demand for standardised ways to measure ecologically meaningful plant traits. The predecessor of the present handbook (Cornelissen et al. 2003) was written to address that need, by providing standardised, easily implemented trait-measurement recipes for researchers worldwide. This updated version is an extension of that global collective initiative, with an even broader scope.
The identiﬁcation of general plant trait trade-offs associated with strategies and trait syndromes across ﬂoras, taxa and ecosystems has been a long-standing focus in plant ecology, and has attracted increasing interest in recent decades (e.g. Chapin et al. 1993; Grime et al. 1997; Reich et al. 1997; Cornelissen et al. 1999; Aerts and Chapin 1999; Westoby et al. 2002; Díaz et al. 2004; Wright et al. 2004; Cornwell et al. 2008; Baraloto et al. 2010a; Freschet et al. 2010; Ordoñez et al. 2010; Kattge et al. 2011). Ample evidence indicates that plant traits and trait syndromes signiﬁcantly affect ecosystem processes and services (for overviews, see Lavorel and Garnier 2002; Díaz et al. 2007; Chapin et al. 2008; De Bello et al. 2010; Cardinale et al. 2012). As a consequence, trait-based approaches are currently also gaining momentum in the ﬁelds of agronomy and forestry (e.g. Brussaard et al. 2010; Garnier and Navas 2012), conservation (e.g. Mace et al. 2010), archaeobotany (e.g. Jones et al. 2010), and at the interface between the evolution and ecology in communities and ecosystems (e.g. Edwards et al. 2007; Cavender-Bares et al. 2009; Faith et al. 2010; Srivastava et al. 2012).
The quantiﬁcation of vegetation changes in the face of modiﬁcations in climate at the global scale has been signiﬁcantly improved with the use of dynamic global vegetation models (DGVMs) (Cramer et al. 2001; Arneth et al. 2010). However, current-generation DGVMs do not yet incorporate continuous variation in plant traits among plant species or types (Cornwell et al. 2009). Next-generation models could beneﬁt from the incorporation of functional traits and syndromes that are simple and general enough to be assessed at the regional and global scales, and yet informative enough to relate to biogeochemical dynamics, dispersal and large-scale disturbance (Ollinger et al. 2008; Stich et al. 2008; Doherty et al. 2010; Harrison et al. 2010; Ma et al. 2011).
As a consequence of this surge of theoretical and practical interest, there has been a rapid expansion of large regional and global trait databases (e.g. Díaz et al. 2004; Wright et al. 2004; Kleyer et al. 2008; Cornwell et al. 2008; Chave et al. 2009; Paula et al. 2009; Baraloto et al. 2010a; Zanne et al. 2010; Fortunel et al. 2012; Patiño et al. 2012). The TRY Initiative (Kattge et al. 2011; see Box 1) is compiling a communal worldwide database of plant traits, an unprecedented step in improving the capacity of the scientiﬁc community to access and utilise plant-trait information. In this context, standardisation of protocols applicable under a wide range of situations and geographical contexts becomes even more important.
In this manual, we consider plant functional traits to be any morphological, physiological or phenological feature, measurable for individual plants, at the cell to the whole- organism level, which potentially affects its ﬁtness (cf. McGill et al. 2006; Lavorel et al. 2007; Violle et al. 2007) or its environment (Lavorel and Garnier 2002). As proposed by Lavorel et al. (2007), we will call the particular value or modality taken by the trait at any place and time an ‘attribute’. Functional traits addressed in the present handbook range from simple indicators of plant function (e.g. leaf nutrient concentrations as an indicator of both potential rates of metabolism and of quality as food for herbivores) to plant functions themselves (e.g. palatability, decomposability, capacity to resprout after a ﬁre), always measured at the species level. The traits contained in the handbook represent a set of functional traits of vascular plants that (1) can together represent key plant responses to the environment as well as key plant effects on ecosystem processes and services at various scales from local plots to landscapes to biomes, (2) can help answer questions of ecological and evolutionary theory as well as practical ones related to nature conservation and land management (see Box 2 for a Discussion) and (3) are in most cases candidates for relatively easy, inexpensive and standardised measurement in many biomes and regions.
This is a recipe book to be used in the ﬁeld and in the laboratory, and contains comprehensive, detailed, step-by-step recipes for direct and, as far as possible, unambiguous use in any terrestrial biome. To that end, we have had to make hard choices. We did not intend to provide a comprehensive list of all traits that could potentially be measured nor a thorough description of the theory behind each trait. Rather, the present handbook contains consensus traits and methods that researchers have identiﬁed as being useful, reliable and feasible to be applied in large-scale comparative efforts. Some of them are well known and widely used, whereas for others, relatively novel methods are described. Particular emphasis is given to recipes appropriate for areas with high species richness, incompletely known ﬂoras and modest research budgets. We give only brief ecological background for each trait, with a short list of references with further details on signiﬁcance, methodology and existing large datasets. The main section of each recipe contains a brief, standardised protocol, and under the heading Special cases or extras, we give pointers to interesting additional methods and parameters. Readers can ﬁnd complementary methods and additional discussions and comments in speciﬁc associated web pages (see Box 1). Speciﬁc citations have not been included in the recipe descriptions. We hope that the authors of relevant publications (most of them cited at the end of each recipe) will understand this choice, made for clarity and brevity, and in full recognition of the important contribution that each of them and many additional studies have made to the theory and measurement procedure for each trait.
|Box 1. Useful links for plant functional-trait workers|
To ﬁnd on-line protocols and updates related to this handbook: Nucleo Diversus/Tools (http://www.nucleodiversus.org). To submit corrections, additions and comments to improve this handbook: email@example.com.
Various complementary protocols for speciﬁc plant (eco-)physiological as well as environmental measurements not covered in this handbook can be accessed through the fellow project: Prometheus Wiki (Sack et al. 2010; http://prometheuswiki.publish.csiro.au/tiki-index.php).
To share plant functional-trait data with other researchers (both as a provider and as a recipient): TRY Worldwide Initiative and Database (Kattge et al. 2011; www.try-db.org).
To calculate functional diversity metrics and indices with your trait data: FDiversity Free Software Package (Casanoves et al. 2011; www.fdiversity. nucleodiversus.org)
|Box 2. Why measure plant traits and which traits to measure?|
Plant functional traits give better insight into the constraints and opportunities faced by plants in different habitats than does taxonomic identity alone (Southwood 1977; Grime 1979). They also provide understanding of how functional diversity in the broad sense underpins ecosystem processes and the beneﬁts that people derive from them (Chapin et al. 2000; Díaz et al. 2007), and offer the possibility of comparing distant ecosystems with very little taxonomic overlap (Reich et al. 1997; Díaz et al. 2004; Cornwell et al. 2008). The plant-trait approach often provides unique mechanistic insights into several theoretical and practical questions, although it is not necessarily less laborious or less expensive than other methods.
Which traits to measure to answer which questions? No methods handbook can answer the question of what are the best traits to measure, because this strongly depends on the questions at hand, the ecological characteristics and scale of the study area, and on practical circumstances. For instance, there is not much point in comparing multiple species for succulence within wet environments or for ﬂammability within areas that burn only very rarely, whereas such data might be useful as a reference in larger- scale studies. In addition, rather than setting limits to researchers’ curiosity, this trait handbook aims at inspiring others to come up with and measure traits not covered here, including ‘new’ traits, to help answer exciting novel questions. Some examples of additional interesting traits not covered here are in the introductory text of Cornelissen et al. (2003). The ﬁrst and foremost criterion in deciding what traits to aim for is the process of interest. Is the intended study about fundamental plant or organ design in response to environmental variation in the present or about the evolution that gave rise to today’s spectrum of designs? Is it about plant growth, reproduction or dispersal over the landscape? Does it involve plant survival in response to resources or disturbance? Is the main questionabout response to or effects on water, soil nutrient or ﬁre regimes? Is it about vegetation feedbacks to atmosphereand climate? Does it involve the juvenile stage, the persistence of adults? Does it involve pollinators, dispersers or herbivores? Does the target process occur above or below ground? Is the focus on coarse differences across or among regions or continents or on subtle differences among individuals of two slightly different local populations? Are speciﬁc ecosystem services to people assessed or predicted? All these and further types of questions will have a direct impact on the selection of traits. Although there is no limit to the number of relevant traits in different research contexts, a small number of traits have been considered relevant almost universally, because they are at the core of the plant life cycle (Grime et al. 1997; Westoby 1998). These are plant size (usually expressed as height), seed size (usually expressed as seed mass) and the structure of leaf tissue (often expressed as speciﬁc leaf area or leaf dry-matter content). Beyond this, there are some ‘core lists’ of plant traits that are considered important for plant resource use, regeneration, dispersal and response to widespread disturbances (e.g. Hodgson et al. 1999; McIntyre et al. 1999; Weiher et al. 1999; Lavorel and Garnier 2002; Knevel et al. 2003). A discussion of these is beyond the scope of the present manual, and readers are referred to these papers for a ﬁrst introduction. For a particular question, the brief ecological background, and especially the list of references provided for each trait, should help identify the most appropriate traits to measure. Logistic and ﬁnancial considerations are equally relevant. For example, if resources are limited for measuring relative growth rate on hundreds of species representing a large gradient of productivity, the speciﬁc leaf areas and stem-speciﬁc densities of these species might serve as less precise but still useful proxies for broad patterns of variation in growth and vegetation productivity. Similarly, the choice of traits would be slightly different if the limiting factor is labour force or access to sophisticated analytical laboratories, or if the project involves an intensive one-off measurement campaign carried out by highly trained specialists or recurrent measurements by third parties. The recipes provided here, including the sections on Special cases or extras, should assist in making those decisions.
This new handbook both updates theory, methods and databases covered by its predecessor (Cornelissen et al. 2003), and provides protocols for several additional plant functional traits, especially for organs other than the leaf. It has better coverage of (1) measurements important in less studied biomes and ecosystems, (2) ﬂoras with special adaptations and (3) plant functions related to carbon and nutrient cycling, herbivory, water dynamics and ﬁre. We hope that the focus on practical techniques and streamlined trait recipes will help this handbook become a useful reference in laboratories and in the ﬁeld for studies around the world. We strongly invite users to share their experiences with us about both general issues and speciﬁc details of these protocols (see Box 1), so that the next edition will be an even better bed-side table companion.
1 Selection of species and individuals
This section presents guidelines for selecting species and individuals within species for trait measurement, as well as general considerations of the necessary number of replicates. In addition, suggested numbers of replicates for all traits are given in Appendix 1.
1.1 Selection of species
Study objectives will always determine which species are selected for trait measurement. For species-level analyses of trait variation, and for identifying general strategies or syndromes of resource use, or trade-offs at the local, regional or global scale (e.g. Reich et al. 1997; Westoby et al. 1998; Díaz et al. 2004; Wright et al. 2004; Gubsch et al. 2011), species or populations from a broad range of environments and phylogenetic groups should be selected. For questions about evolution, the choice of species may be based on the inclusion of representatives of different enough phylogenetic groups, or on other phylogenetically relevant criteria (such as being members of particular clades), with little consideration about their abundance in situ. In contrast, when trying to understand how environmental variables shape vegetation characteristics, or how vegetation characteristics affect local ﬂows of matter and energy (e.g. primary and secondary production, carbon, water and mineral nutrient cycling), the main criterion for species selection should be local abundance. In those cases, species should be selected that collectively make up for ~80% of cumulative relative abundance, following Garnier et al. (2004) and Pakeman and Quested (2007) (see speciﬁcs for abundance measurements below). Exceptions may be made if this criterion would imply measurements for an impracticably large numbers of species,
e.g. communities with unusually high species richness per unit area, especially combined with a very high evenness. Examples are tropical rainforests and fynbos vegetation, in which well over 100 species per plot may be needed to reach the 80% biomass threshold.
In forests and other predominantly woody vegetation, the most abundant species of the understorey may also be included (e.g. when the research question relates to the whole-community or ecosystem level), even if their biomass is much lower than that of the overstorey woody species. In predominantly herbaceous communities, species contribution to a particular community may vary with time during a growing season. As a ﬁrst step, we suggest that the relative abundance and the traits should be measured at the time of peak standing biomass of the community. This does not always apply to reproductive structures, which obviously have to be measured when they are present and fully developed, which sometimes does not coincide with the time of maximum vegetative growth.
For comparing sites or for monitoring trends in ecosystem- level properties across environmental conditions (e.g. pollution, or different regional climate or fertility levels), indicator species can be selected on the basis of the sensitivity of their trait values to the environmental factor of interest, and their importance locally and regionally, as well as for the ease with which they can be found and identiﬁed in the ﬁeld (independent of their relative abundance) (Ansquer et al. 2009; De Bello et al. 2011). In this sense, it may be useful to distinguish ‘variable’ traits from more ‘stable’ traits (Garnier et al. 2007). Although most traits show some variation within species along environmental gradients, or in response to speciﬁc environmental changes, the intraspeciﬁc variation of so-called ‘stable traits’ is low compared with their interspeciﬁc variation. The reverse is the case for so-called ‘variable traits’, which implies that they should preferably be measured in more than one site or condition across the habitat range (Garnier et al. 2007). By contrast, ‘stable traits’ can be measured for any representative population from the entire gradient. Traits known to often be ‘variable’ include vegetative and reproductive plant height, mineral nutrient concentration in leaves, onset of ﬂowering, branching architecture and spinescence. Traits that are relatively ‘stable’ include categorical traits, such as life form, clonality, dispersal and pollination modes, and to a lesser degree photosynthetic type (C3 or C4). Some quantitative traits such as leaf and stem dry matter content, or leaf toughness can be ‘stable’ along certain gradients, e.g. of nutrients or disturbance, but not along others, e.g. a light gradient (cf. Poorter et al. 2009). Species may therefore vary in which quantitative traits are stable across given gradients, so tests should be made before a trait is taken to be stable for a given species (Albert et al. 2010, 2012; Hulshof and Swenson 2010; Messier et al. 2010; Moreira et al. 2012).
Appendix 1 gives a rough indication of the within-species variability (coefﬁcients of variation; i.e. standard deviation divided by the mean, hereafter CV) for some of the quantitative traits described in the present handbook, along with the more frequently used units and the range of values that can be expected. Appendix 1 summarises ﬁeld data collected in several studies for a wide range of species coming from different environments. Because of the low number of replicates generally used, each of the individual estimates bears an uncertainty (and CV will likely increase as scale increases); however, by looking at the range of CVs calculated across a wide range of species, a reasonable estimate of the typical within-species-at-a-site variability can be obtained. We, therefore, present in Appendix 1 the 20th and 80th percentiles of the CV distribution.
How species abundance should be measured to determine the species making up 80% of cumulative abundance (e.g. whether to lay out transects, select points or quadrats at random or systematically, or to follow a different method) is beyond the scope of the present handbook and is extensively covered in plant- ecology and vegetation-science textbooks. However, it should be noted that different methods are relevant to different ecological questions and associated traits (Lavorel et al. 2008; see also Baraloto et al. 2010b, speciﬁcally for tropical forest). Taxon-free approaches that do not require species identiﬁcation offer an alternative to estimates of relative abundance, and effectively capture the contribution of more abundant species. These include measuring traits regardless of species identity, along a transect (‘trait-transect’ method, Gaucherand and Lavorel 2007), or for individuals rooted nearest to random sampling points, as long as the canopy structure is quite simple (‘trait-random’ method – Lavorel et al. 2008). Methods of taxon-free sampling have also been applied to tropical forests, being, in this case, strongly based on the frequency or basal area of individual trees (Baraloto et al. 2010b). Trait values obtained through these methods can differ from those obtained using the standard approach of selecting robust, ‘healthy-looking’ plants for trait measurement (see Section 1.2).
1.2 Selection of individuals within a species
For robust comparisons across species, traits should be generally measured on reproductively mature, healthy-looking individuals, unless speciﬁc goals suggest otherwise. To avoid interaction with the light environment, which may strongly depend on neighbouring vegetation, often plants located in well lit environments, preferably totally unshaded, should be selected. This is particularly important for some leaf traits (see Section 3.1). This criterion creates sampling problems for true shade species found, e.g. in the understorey of closed forests, or very close to the ground in multilayered grasslands. Leaves of these species could be collected from the least shady places in which they still look healthy and not discoloured (see Section 3.1). Plants severely affected by herbivores or pathogens should be excluded. If feasible, for consistency among sets of measurements, use the same individual to measure as many different traits as possible. Deﬁning ‘individuals’ reliably may be difﬁcult for clonal species (see Section 2.5), so the fundamental unit on which measurements are taken should be the ramet, deﬁned here as a recognisably separately rooted, above-ground shoot. This choice is both pragmatic and ecologically sound, because genets are often difﬁcult to identify in the ﬁeld and, in any case, the ramet is likely to be the unit of most interest for most functional, trait-related questions (however, be aware that sampling of neighbouring ramets may not provide biologically independent replicates for species-level statistics). Individuals for measurement should be selected at random from the population of appropriate plants, or by using a systematic transect or quadrat
1.3 Replicate measurements
Trait values are often used comparatively, to classify species into different functional groups or to analyse variation across species within or between ecosystems or geographical regions. This type of research almost inevitably implies a conﬂict between scale and precision; given constraints of time and labour, the greater the number of species covered, the fewer replicate measurements can be made for each species. The number of individuals (replicates) selected for measurement should depend on the natural within- species variability in the trait of interest (see Section 1.1 for a discussion on within-species variability), as well as on the number or range of species to be sampled. Appendix 1 shows the minimum and preferred number of replicates for different traits, mainly based on common practice. The most appropriate sample size depends on the purpose and scope of the study. Ideally, researchers should check within-species CV at their site before deciding this. In broad-scale interspeciﬁc studies, one may sample relatively few plants of any given species, whereas when the study concerns just a small number of species or a modest local gradient, one may need to sample more heavily within each species. It is highly recommended to quantify the relative contributions of intra- v. interspeciﬁc variation. A formal analysis of statistical power based on an assumed or known variance among individuals, compared with that among species means, can be used. Commonly used statistical packages generally include routines for power analysis, as well as for variance component analyses (used to partition variance among different levels, e.g. species v. individuals). Other more powerful techniques can also be used, such as mixed models (Albert et al. 2010; Messier et al. 2010; Moreira et al. 2012).
2 Whole-plant traits
Plant lifespan (usually measured in years) is deﬁned as the time period from establishment until no live part remains of the respective individual. Maximum plant lifespan is an indicator of population persistence and is therefore strongly related to land use and climate change. Lifespan is limited in non-clonal plants but may be apparently nearly unlimited in clonal plants.
Maximum lifespan is strongly positively associated with environmental stress regimes, e.g. low temperatures and low nutrient availability. The relationship with disturbance frequency is mostly negative, although long-lived (resprouting) clonal plants may also tolerate frequent disturbance. There may be a trade-off between maximum lifespan and dispersal in time and space. Long-lived species often exhibit a short-lived seed bank and produce seeds or fruits with low dispersal potential, in contrast to short-lived species, which often have a very long-lived seed bank and/or high dispersal potential.
How to assess?
(A) Life history
This simple classiﬁcation distinguishes among the common types of timing and duration of survival behaviour of individual plants in the absence of disturbances or catastrophes.
(1) Annual. Plant senesces and dies at the end of its ﬁrst growing season (from seed), after producing seed, which may propagate a new plant in the future (a winter annual germinates in late summer or autumn, and so has two seasons, although the ﬁrst may be very short).
(2) Biennial. Plant grows vegetatively the ﬁrst season, then ﬂowers in the second to produce seed, followed by senescence and death of the shoot and root system.
(3) Perennial. The individual survives for at least three growing seasons.
(a) Monocarpicperennials. After several to many seasons of vegetative growth, the plant produces seeds, then senesces and dies
(b) Polycarpic perennials. All or much of the stem and root system normally survives the harsh or dormant period between growing seasons; stem has lateral thickening over the years.
(i) Herbaceous perennial. Aerial shoots (and sometimes roots) die off as growing season ends; in the next season, new shoots grow from a perennating organ such as a bulb, corm, rhizome or ‘root crown’ (bud-bearing stem base or hemicryptophytes) near or below ground surface.
(ii) Woody perennial retains, from one growing season into the next, some living, leaf-bearing shoots, which die by the end of their third season or later.
Qualitative distinction between life-history classes
A plant with any perennating organ other than the seed is either a perennial or a biennial (the latter only by a storage taproot). If biennial, there should be individuals with a storage root but not an inﬂorescence, and others with both. A plant that lacks specialised perennating organs may still be perennial, by resprouting from its root-crown. If so, the crown will normally carry wrinkles or scars from bud outgrowth in previous seasons, and can eventually become quite thick and even woody (a caudex); in contrast, the root of an annual is usually relatively soft and smooth, its thickness extending continuously into the stem. A perennial in its ﬁrst year of growth may resemble an annual in these respects, except that perennial wild plants usually do not ﬂower in their ﬁrst year, whereas an annual always does (many horticultural perennials, however, have been selected to do so).
(B) Maximum plant lifespan quantitative assessment
In gymnosperms and angiosperms, even in some non-woody ones, species maximum lifespan can be estimated by counting the number of annual rings representing annual tissue increments. Recently, a study on 900 temperate herbaceous species revealed annual rings in perennating structures in more than 80% of the species. However, the formation of annual rings can depend on habitat conditions. Annual rings will be found in vegetation zones with clear seasonality (cold (winter) or drought seasons) such as the polar, boreal or austral, temperate and even in Mediterranean- type zones. In the two latter climate zones, annual rings may sometimes be absent. In some cases, annual rings may even be found in tropical species, especially in regions with a distinct dry and wet season. Maximum lifespan within a population is studied in the largest and/or thickest individuals. Data are collected from a minimum of 10, preferably 20 individuals (replicates). In woody species (trees, shrubs, dwarf shrubs), annual rings are determined either by cutting out a whole cross-section or a ‘pie slice’ of the main stem (trunk), or by taking a core with a pole-testing drill (tree corer). It is important to obtain a rather smooth surface for clear observation. The annual rings can usually be counted under a dissection microscope. Often a cross-section of a shoot does not represent the maximum age as precisely as the root collar (root- stem transition zone of primary roots), which is especially true for most shrubs where single shoots have a limited age. We, therefore, recommend digging out woody plants a bit and taking (additional) samples from the root collar. In herbaceous species, annual rings are mostly found at the shoot base or in the root collar, and also in rhizomes. Here, microscopic cross-sections are essential and have to be treated ﬁrst by ‘eau de javelle’ to remove the cytoplasm and then stained (fuchsin, chryosidine, astrablue (FCA); alternatively, astrablue and safranin) to make the annual rings visible. In some cases, polarised light has proven to be useful to identify the annual rings. Maximum lifespan of a species or population is deﬁned as the largest number of annual rings counted among all samples (although the mean lifespan of all individuals may be informative too).
Special cases or extras
(1) In clonal plants, the identiﬁcation of (maximum) lifespan is more complicated. If a ramet never becomes independent from the genet and will never be released from the mother plant, annual rings in the tap root (e.g. Armeria maritima, Silene acaulis) or annual morphological markers along the rhizome or stolon (e.g. Lycopodium annotinum, Dictamnus albus) are also a suitable tool to identify maximum lifespan of a genet. In the latter case, maximum lifespan can be higher if part of the rhizome or stolon is already decomposed. However, in clonal plants where the genet consists of more or less independent ramets, genet age can be estimated only indirectly by means of size or diameter of a genet in relation to mean annual size increment.
(2) Geophyte species, especially monocotyledons, may disappear above ground for up to several years before reappearing. In such cases, only permanent-plot research with individually marked individuals will give an idea about the maximum lifespan of those species.
(3) Cold-climate dwarf shrubs. In some of these species, e.g. the heather Cassiope tetragona, lateral annual rings are often very hard to discern, whereas annual shoot-length increments of woody stems can be distinguished under a microscope through the winter-mark septa separating them and through the annual sequence of distances between leaf scars.
(4) Life history and location. Life history varies with location and should preferably be assessed in the ﬁeld rather than by reference to ﬂoras. In particular, many short-lived, faster- growing species fall into different life-history categories in different regions and a few differ among habitats, even within the same region. References on theory and signiﬁcance: Rabotnov (1950); Schweingruber (1996); Fischer and Stöcklin (1997); Larson (2001); Schweingruber and Poschlod (2005); De Witte and Stöcklin (2010). More on methods: Tamm (1972); Gatsuk et al. (1980); Cherubini et al. (2003); Rozema et al. (2009).
2.2 Life form
Plant life-form classiﬁcation sensu Raunkiaer (1934) is a simple but still a useful way of functionally classifying plants. More information is given in Material S1, available as Supplementary Material for this paper.
2.3 Growth form
Growth form is mainly determined by the direction and extent of growth, and any branching of the main-shoot axis or axes. These affect canopy structure, including its height, and both the vertical and horizontal distribution of leaves. Growth form may be associated with ecophysiological adaptation in many ways, including maximising photosynthetic production, sheltering from severe climatic conditions, or optimising the height and positioning of the foliage to avoid or resist grazing by particular herbivores, with rosettes and prostrate growth forms being associated with high grazing pressure by mammals.
How to record?
Growth form is a hierarchical trait assessed through ﬁeld observation or descriptions or ﬁgures or photographs in the literature. Because we are classifying types along a continuum, intermediate forms, between the categories recognised here, may be encountered, as well as occasional unique forms lying outside any of these categories.
(A) Terrestrial, mechanically and nutritionally self-supporting plants
(1) Herbaceous plants have either no or at most modest secondary growth, with stem and root tissues that are rather soft compared with typical wood.
(a) Rosette plant. Leaves concentrated on a short, condensed section of stem or rhizome (see Category C under Section 2.5 for a deﬁnition of rhizome), at or very close to the soil surface; with an inﬂorescence (or single-ﬂower peduncle) bearing either no or reduced leaves (bracts) produced from the rosette axis, above ground level. Graminoids whose principal photosynthetic leaves are attached to the base of their aerial stems (e.g. ‘bunch grasses’) fall in this category.
(b) Elongated, leaf-bearing rhizomatous. The permanent axis is an elongated rhizome that directly bears photosynthetic leaves that extend individually up into the light. The rhizome can be located either at or below ground level (e.g. Pteridium aquilinum (bracken fern), Viola spp., Iris spp.), or (epiphytes) on an above-ground support such as a tree branch. Aerial inﬂorescences (or single-ﬂower peduncles) with either reduced leaves (bracts), or none, may grow out from the rhizome.
(c) Cushion plant (pulvinate form). Tightly packed foliage held close to soil surface, with relatively even and rounded canopy form (many alpine plants have this form).
(d) Extensive-stemmed herb develops elongated aerial stem(s) whose nodes bear photosynthetic leaves that are distributed nearly throughout the canopy of the plant, except when shed from its more basal parts during later growth, and lacking in distally developed inﬂorescences. Graminoids (rhizomatous or not) with leafy aerial stems fall here.
(e) Tussock. Many individual shoots of a dense colony or clone grow upward, leaving behind a tough, mostly dead supporting column topped by living shoots with active leaves (e.g. the Arctic cotton grass, Eriophorum vaginatum).
(2) Semi-woody plants. Stem without secondary growth but often toughened by scleriﬁcation (or, alternatively, with relatively feeble, soft or ‘anomalous’ secondary growth).
(a) Palmoid. Bears a rosette-like canopy of typically large, often compound leaves atop a usually thick (‘pachycaulous’), columnar, unbranched or little- branched stem (e.g. palms (Pandanus), tree ferns). Certain tropical or alpine Asteraceae such as Espeletia spp., cycads, Dracaena, arborescent Yucca spp. and some Bombacaceae can be regarded as having this growth form, although their stems undergo more extensive secondary growth (see also ‘Corner model’ within the references below).
(b) Bambusoid. An excurrently branched (cf. Point A.3.d.i in the present Section) trunk lacking or having only weak secondary growth is stiffened by scleriﬁcation to support a vertically extensive, sometimes tree-sized canopy (bamboos; various tall, herbaceous dicots such as Chenopodium, Amaranthus and Helianthus).
(c) Stem succulent. A usually leaﬂess photosynthetic stem with extensive, soft, water-storage tissue and only limited secondary growth (cacti, and cactoid plants of other families; most leaf succulents fall instead into one of the subclasses of Points A.1 or A.3 in the present Section).
(3) Woody plants develop extensive, usually tough, secondary xylem and phloem from vascular cambium, and corky outer bark from cork cambium (woody vines are covered in Point B.3 of the present Section).
(a) Prostrate subshrub. Long-lived woody stem growing horizontally at ground level (examples include many Arctic willows and ericoids).
(b) Dwarf shrub, or subshrub, with usually multiple, ascending, woody stems less than 0.5 m tall.
(c) Shrub. Woody plant between 0.5 m and ~5 m tall, with canopy typically carried by several trunks that are usually thinner and younger than typical mature tree trunks.
(d) Tree. Woody plant usually >5 m tall, with main canopy elevated on a long-lived, substantial, usually single (but upwardly branching), trunk.
(i) Excurrent. Single main axis (trunk) extends up to, or almost to, the top, with shorter, ascending or horizontal branches giving a conical or (in mature trees) columnar form to the crown.
(ii) Deliquescent. Trunk divides, somewhere above its base, into two to several, more or less equal branches that continue branching upward to produce a wider, more ﬂat-topped crown.
(e) Dwarf tree. Morphology as in one of Types (i) or (ii) but substantially <5 m tall. Many forest understorey trees, but also in various climatically or nutritionally challenging, unshaded habitats, such as ‘pine barrens’, semi-deserts, certain tropical cloud forests, bogs and near-timberline vegetation.
(B) Plants structurally or nutritionally supported by other plants or by special physical features
(1) Epiphyte. Plant that grows attached to the trunk or branch of a shrub or tree (or to anthropogenic supports) by aerial roots, normally without contact with the ground (e.g. many tropical orchids and Bromeliaceae).
(2) Lithophyte. Plant that grows in or on rocks (e.g. many species of ferns, species of Nepenthes, Utricularia forestii, Cymbalaria muralis).
(3) Climber. Plant that roots in the soil but relies, at least initially, on external support for its upward growth and leaf positioning.
(a) Herbaceous vine. Usually attaches to its support either by twining or by means of tendrils.
(b) Woody vine, including liana. Often attaches to a support by means of aerial roots.
(c) Scrambler. Grows up through a sufﬁciently dense canopy of other plants, without any means of attachment (e.g. Galium spp.).
(d) Strangler. May start epiphytically (but become soil-rooted) or by climbing from ground level. However, by secondary growth, it later becomes self-supporting, and may eventually envelope the initially supporting stem (e.g. certain tropical Ficus spp.).
(4) Submersed or ﬂoating hydrophyte. Herbaceous, aquatic plant that relies on surrounding water for physical support. (Emergent hydrophytes (‘helophytes’) mostly fall into one of the subgroups of Point A.1 in the present Section.)
(5) Parasite or saprophyte obtains important nutritional needs directly or indirectly from other vascular plants (parasite) or from dead organic matter in the soil (saprophyte) (see Nutrient uptake in Material S2 where other more speciﬁc forms of parasitism are covered).
References on theory, signiﬁcance and large datasets: Cain (1950); Ellenberg and Müller-Dombois (1967); Whittaker (1975); Barkman (1988, and references therein); Rundel (1991); Richter (1992); Box (1996); Ewel and Bigelow (1996); Cramer (1997); Lüttge (1997); Medina (1999); McIntyre and Lavorel (2001).
More on methods: Barkman (1988, and references therein).
2.4 Plant height
Plant height is the shortest distance between the upper boundary of the main photosynthetic tissues (excluding inﬂorescences) on a plant and the ground level, expressed in metres. Plant height, or maximum height (Hmax), is the maximum stature a typical mature individual of a species attains in a given habitat. Hmax is associated with growth form, position of the species in the vertical light gradient of the vegetation, competitive vigour, reproductive size, whole-plant fecundity, potential lifespan, and whether a species is able to establish and attain reproductive size between two disturbance events (such as e.g. ﬁre, storm, ploughing, grazing).
What and how to measure?
Healthy plants should be sampled that have their foliage exposed to full sunlight (or otherwise plants with the strongest light exposure for that species). Because plant height is quite variable both within and across species, there are three ways to estimate Hmax, depending on species size and the number of plants and time available, including the following: (1) for short species, measurements are taken preferably on at least 25 mature individuals per species; (2) for tall tree species, height measurements are time-consuming, and for these, the height of the ﬁve tallest mature individuals can be measured; and (3) for trees, when more time is available, measure ~25 individuals that cover the entire range of their height and diameter. Use an asymptotic regression to relate height to diameter, and derive the asymptote from the regression coefﬁcients, or use the formula to calculate the height of the thickest individual in the stand.
The height to be measured is the height of the foliage of the species, not the height of the inﬂorescence (or seeds, fruits), or the main stem if this projects above the foliage. For herbaceous species, this is preferably carried out towards the end of the growing season. The height recorded should correspond to the top of the general canopy of the plant, discounting any exceptional branches, leaves or photosynthetic portions of the inﬂorescence.
For estimating the height of tall trees, some options are
(1) a telescopic stick with decimetre marks; and
(2) trigonometric methods such as the measurement of the horizontal distance from the tree to the observation point (d) and, with a clinometer or laser, the angle between the horizontal plane and the tree top (a) and between the horizontal plane and the tree base (b); tree height (H) is then calculated as H = d x [tan(a) + tan(b)]; height estimates are most accurate if the measurement angle is between 30 degrees (easier to deﬁne the highest point in the crown) and 45 degrees (a smaller height error caused by inaccuracy in the readings); the horizontal distance between the observer and the stem should preferably equal 1–1.5 times the tree height.
Special cases or extras
(1) Rosettes. For plants with major leaf rosettes and proportionally very little photosynthetic area higher up, plant height is based on the rosette leaves.
(2) Herbaceous. For herbaceous species, vegetative plant height may be somewhat tricky to measure (if the plant bends, or if inﬂorescence has signiﬁcant photosynthetic portions), whereas reproductive plant height can be ‘safer’ in this sense. Additionally, some authors have suggested that the projection of an inﬂorescence above the vegetative part of the plant may be a useful trait in responses to disturbance, so both of these heights should be useful to measure. Others, while recording maximum canopy height, arbitrarily use a leaf length of two-thirds of the largest leaf as the cut-off point to estimate the position of a transition between vegetative and reproductive growth.
(3) Epiphytes. For epiphytes or certain hemi-parasites (which penetrate tree or shrub branches with their haustoria), height is deﬁned as the shortest distance between the upper foliage boundary and the centre of their basal point of attachment.
(4) Large spreading crowns. For trees with large spreading crowns, it is difﬁcult to estimate the height above the tree stem. For such individuals, it is easier to measure (with an optical rangeﬁnder or laser) the vertical height as the distance from eye to a location at the crown margin that is level with the tree top; multiply this by the sine of the sighting angle to the horizontal (as measured with a clinometer) and add the vertical height from eye level down to tree base (a subtraction if eye level is below tree base level).
(5) Dense undergrowth. For vegetation types with dense undergrowth that makes the measurement of Hmax difﬁcult, there are modiﬁed versions of the equation above; they involve the use of a pole of known height that must be placed vertically at the base of the tree.
References on theory, signiﬁcance and large datasets: Gaudet and Keddy (1988); Niklas (1994); Hirose and Werger (1995); Thomas (1996); Westoby (1998); Kohyama et al. (2003); King et al. (2006); Poorter et al. (2006, 2008); Moles et al. (2009).
More on methods: Korning and Thomsen (1994); Thomas (1996); Westoby (1998); McIntyre et al. (1999); Weiher et al. (1999).
Clonality is the ability of a plant species to reproduce or regenerate itself vegetatively, thereby producing new ‘ramets’ (above- ground units) and expanding horizontally. Clonality can give plants competitive vigour and the ability to exploit patches rich in key resources (e.g. nutrients, water, light). Clonal behaviour may be an effective means of short-distance migration under circumstances of poor seed dispersal or seedling recruitment. Clonality also gives a plant the ability to form a bud bank, which can be a very important determinant of recovery and persistence after environmental disturbances. The bud bank consists of all viable axillary and adventitious buds that are present on a plant and are at its disposal for branching, replacement of shoots, regrowth after severe seasons (winter, dry season, ﬁre season), or for vegetative regeneration after injury (adventitious buds that arise after the injury, which are an important means of regeneration in some plants, apparently lie outside the ‘bud bank’ concept). Both the characteristics of the bud bank and the type of clonal growth exhibited by plants determine their ability to recover from disturbances (see Material S3 for a protocol for Characterisation of the bud bank, based on Klimeš and Klimešová 2005). Clonal organs, especially below-ground ones, also serve as storage and perennating organs; a sharp distinction between these functions is often impossible.
How to collect and classify?
For above-ground clonal structures, observe a minimum of ﬁve plants that are far enough apart to be unlikely to be interconnected, and that are well developed. For below-ground structures, dig up a minimum of ﬁve healthy-looking plants (Appendix 1). In some cases (large and heavy root systems), partial excavation may give sufﬁcient evidence for classiﬁcation. It is best to assess clonality and bud banks near the end of the growing season. Remove the soil and dead plant parts before counting buds or cl