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 ...

Question: A set of easily-measured ('soft') plant traits has been identified as potentially useful predictors of ecosystem functioning in previous studies. Here we aimed to discover whether the screening techniques remain operational in widely contrasted circumstances, to test for the existence of axes of variation in the particular sets of traits, and to test for their links with 'harder' traits of proven importance to ecosystem functioning. Location: central-western Argentina, central England, northern upland Iran, and northeastern Spain. Recurrent patterns of ecological specialization: Through ordination of a matrix of 640 vascular plant taxa by 12 standardized traits, we detected similar patterns of specialization in the four floras. The first PCA axis was identified as an axis of resource capture, usage and release. PCA axis 2 appeared to be a size-related axis. Individual PCA for each country showed that the same traits remained valuable as predictors of resource capture and utilization in all of them, despite their major differences in climate, biogeography and land-use. The results were not significantly driven by particular taxa: the main traits determining PCA axis 1 were very similar in eudicotyledons and monocotyledons and Asteraceae, Fabaceae and Poaceae. Links between recurrent suites of 'soft' traits and 'hard' traits: The validity of PCA axis 1 as a key predictor of resource capture and utilization was tested by comparisons between this axis and values of more rigorously established predictors ('hard' traits) for the floras of Argentina and England. PCA axis 1 was correlated with variation in relative growth rate, leaf nitrogen content, and litter decomposition rate. It also coincided with palatability to model generalist herbivores. Therefore, location on PCA axis 1 can be linked to major ecosystem processes in those habitats where the plants are dominant. Conclusion: We confirm the existence at the global scale of a major axis of evolutionary specialization, previously recog-nised in several local floras. This axis reflects a fundamental trade-off between rapid acquisition of resources and conservation of resources within well-protected tissues. These major trends of specialization were maintained across different environmental situations (including differences in the proximate causes of low productivity, i.e. drought or mineral nutrient deficiency). The trends were also consistent across floras and major phylogenetic groups, and were linked with traits directly relevant to ecosystem processes.

Question: A set of easily-measured ('soft') plant traits has been identified as potentially useful predictors of ecosystem functioning in previous studies. Here we aimed to discover whether the screening techniques remain operational in widely contrasted circumstances, to test for the existence of axes of variation in the particular sets of traits, and to test for their links with 'harder' traits of proven importance to ecosystem functioning. Location: central-western Argentina, central England, northern upland Iran, and northeastern Spain. Recurrent patterns of ecological specialization: Through ordination of a matrix of 640 vascular plant taxa by 12 standardized traits, we detected similar patterns of specialization in the four floras. The first PCA axis was identified as an axis of resource capture, usage and release. PCA axis 2 appeared to be a size-related axis. Individual PCA for each country showed that the same traits remained valuable as predictors of resource capture and utilization in all of them, despite their major differences in climate, biogeography and land-use. The results were not significantly driven by particular taxa: the main traits determining PCA axis 1 were very similar in eudicotyledons and monocotyledons and Asteraceae, Fabaceae and Poaceae. Links between recurrent suites of 'soft' traits and 'hard' traits: The validity of PCA axis 1 as a key predictor of resource capture and utilization was tested by comparisons between this axis and values of more rigorously established predictors ('hard' traits) for the floras of Argentina and England. PCA axis 1 was correlated with variation in relative growth rate, leaf nitrogen content, and litter decomposition rate. It also coincided with palatability to model generalist herbivores. Therefore, location on PCA axis 1 can be linked to major ecosystem processes in those habitats where the plants are dominant. Conclusion: We confirm the existence at the global scale of a major axis of evolutionary specialization, previously recog-nised in several local floras. This axis reflects a fundamental trade-off between rapid acquisition of resources and conservation of resources within well-protected tissues. These major trends of specialization were maintained across different environmental situations (including differences in the proximate causes of low productivity, i.e. drought or mineral nutrient deficiency). The trends were also consistent across floras and major phylogenetic groups, and were linked with traits directly relevant to ecosystem processes.