Functional trait variation and sampling strategies in species-rich plant communities

By C. Baraloto, C. E. T. Paine, S. Patiño, Damien Bonal, Bruno Hérault, Jérôme Chave. 2010

185 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/d38184c6393b5395da170baa991364613e91cc52

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In Ecological Modeling

In Ecology, Evolution, Behavior and Systematics

In Nature and Landscape Conservation

Citations in the corpus

Effects of disturbance intensity on species and functional diversity in a tropical forest (2012, background): “Leaf trait variation across species is large compared with variation within species (Rozendaal, Hurtado & Poorter 2006), and our average trait value per species should therefore be a relatively good estimator for community-level properties (Baraloto et al. 2010).”
Functional traits shape ontogenetic growth trajectories of rain forest tree species (2011, methodology): “Recent evidence shows wood density and other stem traits to vary independently of the leaf economics spectrum (Baraloto et al. 2010b), suggesting the existence of at least four trait-defined axes of plant strategies (leaf– height–seed–stem).”
Contrasting above‐ground biomass balance in a Neotropical rain forest (2010, methodology): “To avoid bias due to regional database compilation (Baraloto et al. 2010), wood density at 12% humidity were measured on wood samples (see Kollmann & Cote 1968 for methods used) from trees logged in the same plot network (Gourlet-Fleury et al.”
Functional explanations for variation in bark thickness in tropical rain forest trees (2010, methodology): “found in Baraloto et al. (2010) and at http://bridge.”
Scaling from Traits to Ecosystems: Developing a General Trait Driver Theory via Integrating Trait-Based and Metabolic Scaling Theories (2015, background): “271Scaling from Traits to Ecosystems estimates of the underlying distributions, as guided by sampling theory and statistics (Baraloto et al., 2010; Paine et al., 2011).”
Growth responses of neotropical trees to logging gaps (2010, background): “Given that large trait data bases on tropical trees are now emerging (Ollivier, Baraloto & Marcon 2007; Baraloto et al. 2010), testing and demonstrating the ability of functional traits to accurately predict growth behaviour could have important implications for developing, in the future, robust pos”
Using functional traits and phylogenetic trees to examine the assembly of tropical tree communities (2012, methodology): “Nevertheless, using traits to delineate the niches of species is not without problems either; relevant functional traits may not be measurable for all or a subset of the species (especially rare ones), or may simply be overlooked (Baraloto et al. 2010a).”
Do plant traits retrieved from a database accurately predict on‐site measurements? (2013, background): “This has already been shown for the site scale (Baraloto et al. 2010; Hulshof & Swenson 2010; Messier, McGill & Lechowicz 2010; Albert et al. 2012) and as our results show is potentiated when traits are retrieved from a database.”
Connecting the green and brown worlds . allometric and stoichiometric predictability of above- and below-ground networks (2013, background): “Shan et al. (2012) explored correlations among traits and how they might vary jointly (Baraloto et al., 2010; Lambers and Poorter, 1992; Reich et al., 2006; Wright et al., 2004).”
A global meta-analysis of the relative extent of intraspecific trait variation in plant communities. (2015, unknown): “Despite the predictive power that may come from considering ITV in plant community studies, a practical limitation is the difficulty of measuring trait values on a large number of individuals per species, particularly in species-rich communities (Baraloto et al. 2010).”
New handbook for standardised measurement of plant functional traits worldwide (2013, background): “…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).”
TRY – a global database of plant traits (2011, background): “…a con- sequence studies on trait variation so far have either been focussed on the local to regional scale including a range of different traits (e.g. Baraloto et al., 2010), while studies at the global scale were restricted to individual aspects of plant functioning, e.g. the leaf economic…”