Traits Without Borders: Integrating Functional Diversity Across Scales.

By C. P. Carmona, Francesco de Bello, N. Mason, J. Lepš. Trends in Ecology & Evolution, 2016

421 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/fbcde4da8ea29bdeac048a81b2b19e4e61eba64e

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Citations in the corpus

Decoupling phylogenetic and functional diversity to reveal hidden signals in community assembly (2017, background): “It is worth noticing that accounting for intraspecific trait variability is also possible with the approach, e.g. by using trait overlap in hypervolumes or trait probability density curves to estimate pairwise dissimilarity between species (Carmona et al. 2016).”
Shifts in plant functional composition following long‐term drought in grasslands (2019, background): “Functional composition responds variably to drought (Cantarel et al., 2013; Copeland et al., 2016; Qi et al., 2015), with long‐term droughts largely understudied at broad spatial scales.”
The Multidimensional Stoichiometric Niche (2017, background): “These two patterns are: (1) the overlap that occurs when groups or organisms share a similar portion of the stoichiometric niche volume; and (2) the overlap that occurs when one group of organisms occupies a subset of the stoichiometric volume occupied by the other group (see Carmona et al., 2016).”
Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits (2017, positive): “We believe that the use of the standardized protocols can overcome this gap and we recommend not to report only species trait means for the traits measured, but also measures such a standard deviation (Carmona et al. 2016).”
Functional diversity metrics using kernel density n-dimensional hypervolumes (2020, methodology): “Alpha FD is simply the total volume of the functional niche hyperspace—but see Carmona et al. (2016b, 2016a, 2019) for an alternative estimation based on trait probability density (TPD). kernel.beta This function can be used to estimate beta diversity based on the framework recently proposed by…”
Functional richness: Overview of indices and underlying concepts (2018, methodology): “All these TPDi (i.e. TPD at the individual level) are then summed to obtain the trait distribution probability for each species (TPDS,, see Carmona et al. (2016a) for more details on the computation of the TPD framework).”