Standard descriptive matrices in the identification of exophytophagous caterpillars
Description
The data set consists of numerically encoded morphological, autecological and behavioral characters of 83 species of exophytophagous lepidopteran larvae primarily belonging to the informal Macrolepidoptera group. By inspecting all of their polyphenisms, in terms of morphology, resources and habits, the data set encompasses 582 fully described cases. Each case is labeled according to the nature of the variable character class: e stands for autecological or habitual profile, and is accompanied by consecutive numbers; m stands morphological polyphenisms, and both letters present state that the species has two-level variability.
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Steps to reproduce
The matrix was created m by assigning 83 species used for the visual representation a state for all other characters, including autecology. Each state is a description of a certain feature with all known variation. The matrix is limited to fully grown caterpillars, hibernation, molt and prepupal changes. If a species has multiple states of the same morphological character, each morphological polyphenism was described seperately and named accordingly (the name of the particular habitus was derived from its most prominent attribute and additionally labelled with an “m” in the dataset). If a species had variation in autecological and behavioural characters, the outcomes were recorded with numbers to prevent evolutional implications and the context of eco-type (e.g., e1, e2…etc.; in which the “e” stand for ecological/resource polyphenism) If there is variation in both classes of characters, all logically possible combinations were recorded with an additional “me” abbreviation prefix (see Dataset). The data set consists of 582 fully described cases of various polyphenisms, derived from 83 species belonging to 14 families, each assigned to one of the states of 34 morphological and 7 autecological or behavioural characters imputed as categorical variables.
Institutions
- Universitet u Nisu Prirodno-Matematicki fakultet