Recently, a number of measures of functional diversity have been proposed for data on species presences and absences. One of the most fashionable methods uses cluster analysis of species computed from a matrix of functional characters. Functional diversity is then summarized as the sum of branch lengths of the dendrogram (FDD). Like other graph-theoretical measures of functional diversity, FDD is an increasing function of species richness. This makes FDD inadequate for comparative studies if we want to quantify a component of functional diversity that is not directly related to differences in species counts. The aim of this paper is thus to develop a graph-theoretical measure of functional diversity that does not depend of species richness. The edges of the minimum spanning tree, calculated from the pair-wise inter-species dissimilarity matrix based on functional traits, are ranked and then a power law relationship is established with the cumulative distances. We empirically demonstrate that the exponent of this relationship is independent of species richness and is therefore a suitable measure of functional diversity.
Botta-Dukát, Z. 2005. Rao’s quadratic entropy as a measure of functional diversity based on multiple traits.
J. Veg. Sci.
Botta-Dukát Z., 'Rao’s quadratic entropy as a measure of functional diversity based on multiple traits' (2005) 16J. Veg. Sci.: 533-540.
Botta-Dukát Z.Rao’s quadratic entropy as a measure of functional diversity based on multiple traitsJ. Veg. Sci.200516533540)| false
Mouillot, D. and J.B. Wilson. 2002. Can we tell how a community was constructed? A comparison of five evenness indices for their ability to identify theoretical models of community construction.
Theor. Popul. Biol.
Wilson J.B., 'Can we tell how a community was constructed? A comparison of five evenness indices for their ability to identify theoretical models of community construction' (2002) 61Theor. Popul. Biol.: 141-151.
Wilson J.B.Can we tell how a community was constructed? A comparison of five evenness indices for their ability to identify theoretical models of community constructionTheor. Popul. Biol.200261141151)| false
Madhur Anand, CAN (forest ecology, computational ecology, and ecological complexity)
S. Bagella, ITA (temporal dynamics, including succession, community level patterns of species richness and diversity, experimental studies of plant, animal and microbial communities, plant communities of the Mediterranean)
P. Batáry, HUN (landscape ecology, agroecology, ecosystem services)
P. A. V. Borges, PRT (community level patterns of species richness and diversity, sampling in theory and practice)
A. Davis, GER (supervised learning, multitrophic interactions, food webs, multivariate analysis, ecological statistics, experimental design, fractals, parasitoids, species diversity, community assembly, ticks, biodiversity, climate change, biological networks, cranes, olfactometry, evolution)
Z. Elek, HUN (insect ecology, invertebrate conservation, population dynamics, especially of long-term field studies, insect sampling)
T. Kalapos, HUN (community level plant ecophysiology, grassland ecology, vegetation-soil relationship)
G. M. Kovács, HUN (microbial ecology, plant-fungus interactions, mycorrhizas)
W. C. Liu,TWN (community-based ecological theory and modelling issues, temporal dynamics, including succession, trophic interactions, competition, species response to the environment)
L. Mucina, AUS (vegetation survey, syntaxonomy, evolutionary community ecology, assembly rules, global vegetation patterns, mediterranean ecology)
P. Ódor, HUN (plant communities, bryophyte ecology, numerical methods)
F. Rigal, FRA (island biogeography, macroecology, functional diversity, arthropod ecology)
D. Rocchini, ITA (biodiversity, multiple scales, spatial scales, species distribution, spatial ecology, remote sensing, ecological informatics, computational ecology)
F. Samu, HUN (landscape ecology, biological control, generalist predators, spiders, arthropods, conservation biology, sampling methods)