NDLI: Predicting species richness in tropical lichenized fungi with ‘modular’ combinations of character states

Content Provider	Springer Nature Link
Author	Lücking, Robert
Copyright Year	2012
Abstract	A numerical approach is presented to predict the number of potentially undiscovered species in groups of species that exhibit a ‘modular’ combination of character states, that is, nearly ‘free’ combination that is not random but allows for a wide range of cross-combination of character states. The method uses a character correlation index (CCI) based on observed versus expected frequencies of pairwise character state combinations in known species of a group to estimate the degree of potentially positive and negative evolutionary constraints in the co-occurrence of character states. For instance, if a character state combination, such as ‘muriform ascospores’ and ‘presence of norstictic acid’, occurs less frequently than expected by chance, it indicates the presence of a negative evolutionary constraint. If no such constraint is detected, but a particular character combination has not yet been observed in a described species, it can be predicted that yet undescribed species will exhibit that combination. The method can therefore be used to detect ‘gaps’ in the taxonomic record, i.e. character combinations that have not been detected in known species but are likely to occur in undiscovered species. Modular combination of character states appears to be particularly common in Fungi, including lichens, and the method was here used to predict species richness in the lichen genus Graphis, specifically the Graphis scripta group. A total of 42 species is known in this group and, out of a total of 240 possible character state combinations, a further 48 were found likely to represent undiscovered species, suggesting that the real species number in this group is close to 90 or about twice the number now known. This agrees well with previous estimates for undiscovered diversity of tropical lichen species and for the first time gives a taxonomic prediction of how such ‘missing’ species are expected to look like.
Starting Page	2341
Ending Page	2360
Page Count	20
File Format	PDF
ISSN	09603115
Journal	Biodiversity and Conservation
Volume Number	21
Issue Number	9
e-ISSN	15729710
Language	English
Publisher	Springer Netherlands
Publisher Date	2012-01-04
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Chi-Square test Graphidaceae Graphis scripta Non-metric multidimensional scaling Predictive numerical taxonomy Tree Biology Evolutionary Biology Plant Sciences
Content Type	Text
Resource Type	Article
Subject	Ecology Ecology, Evolution, Behavior and Systematics Nature and Landscape Conservation

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