ANALYTICAL DESCRIPTION OF DECAPOD CUTICLE MICROSTRUCTURE: INTEGRATION OF CUTICLE MORPHOLOGY INTO CLASSIFICATION

The cuticular microstructure of fossil decapods has received limited attention until recently. The few pioneering studies that have considered fossil cuticle have been descriptive and not comparative in nature. The microstructure of arthropod cuticle represents an untapped data set that has the potential to expand our knowledge of the phylogeny and autecology of fossil and living arthropods. Preliminary observations document a wide range of variation in cuticular architecture within the decapods. The first step in utilizing this data set is the creation of a standard system that can adequately describe the observed features. Purely descriptive treatments of material are highly accurate and possibly more encompassing than more numerical descriptions, but they are not easily organized to make comparisons in large data sets. The classification scheme presented here is based on morphologic character archetypes presented as line drawings; selection of certain characters can then be assigned both verbal and numerical coding. Observations of cuticle structures are based both on SEM and thin section preparations of the material. Ornamentation of the cuticle at a scale of less than 1mm is considered; larger structures fall within classical taxonomic treatments. Surface structures are divided into two size classes. The smaller of the two is defined and limited by the size of the cuticle-secreting cells. Internal structure of surface features, calcification style, and characterization of cuticle layers are among the other character classes included in this classification. The pilot study presented here is based on eleven species within nine families of decapods but will be adapted to fossil decapods and then other crustaceans. Once the classification has been refined and expanded to a usable format, future work will increase the number of described taxa and explore the conclusions that can be culled from this new data. This work may be especially helpful in the classification of problematic higher taxa.