Computing additive beta-diversity from presence and absence scores: a critique and alternative parameters.
Whittaker first proposed to measure the variation in species composition among plots or beta-diversity as the ratio between regional diversity (gamma-diversity) and average local diversity (alpha-diversity). More recently, an alternative way of partitioning diversity for which beta-diversity is obtained as the difference between gamma-diversity and average alpha-diversity has become very popular for linking the structure of species assemblages to ecosystem functioning in a spatially explicit manner. Unfortunately, additive beta-diversity computed from species presences and absences suffers from the major drawback of being dependent on regional species richness. For instance, if the separation between beta-diversity and gamma-diversity is incomplete, so that variation in species composition is affected by species richness, then differences in beta-diversity values among different sets of plots could reflect differences in the species count rather than any fundamental difference in species composition among the plots. Based on the above observation, in this paper I will first propose a basic requirement for beta-diversity measures that adequately captures our intuitive notion of independence of species richness. Next, I will show that additive beta-diversity computed from species presence and absence scores can be interpreted within the framework of fuzzy set theory. Finally, based on this unusual "fuzzy" interpretation of additive beta-diversity, I will introduce two families of parametric beta-diversity measures whose members have varying sensitivities to the presence of rare and frequent species.
Ricotta
Carlo
C
Department of Plant Biology, University of Rome La Sapienza, Piazzale Aldo Moro 5, 00185 Rome, Italy. carlo.ricotta@uniroma1.it
D000818:Animals; D044822:Biodiversity; D017753:Ecosystem; D017143:Fuzzy Logic; D007558:Italy; D015233:Models, Statistical; D011157:Population Dynamics; D013045:Species Specificity