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Data from: Surf and Turf Vision: Patterns and predictors of visual acuity in compound eye evolution

Citation

Feller, Kathryn et al. (2020), Data from: Surf and Turf Vision: Patterns and predictors of visual acuity in compound eye evolution, Dryad, Dataset, https://doi.org/10.5061/dryad.3n5tb2rdr

Abstract

Eyes have the flexibility to evolve to meet the ecological demands of their users. Relative to camera-type eyes, the fundamental limits of optical diffraction in arthropod compound eyes restricts the ability to resolve fine detail (visual acuity) to much lower degrees. We tested the capacity of several ecological factors to predict arthropod visual acuity, while simultaneously controlling for shared phylogenetic history. In this study, we have generated the most comprehensive review of compound eye visual acuity measurements to date, containing 375 species that span six of the major arthropod classes. An arthropod phylogeny, made custom to this database, was used to develop a phylogenetically-corrected generalized least squares (PGLS) linear model to evaluate four ecological factors predicted to underlie compound eye visual acuity: environmental light intensity, foraging strategy (predator vs. non-predator), horizontal structure of the visual scene, and environmental medium (air vs. water). To account for optical constraints on acuity related to animal size, body length was also included, though this did not show a significant effect in any of our models. Rather, the PGLS revealed that the strongest predictors of compound eye acuity are described by a combination of environmental medium, foraging strategy, and environmental light intensity.

Methods

Data were collected via a literature review of compound eye visual acuity measurements and ecological factor assignments. A phylogeny was built custom to the species represented in this database by mining sequences from GenBank. 

Usage Notes

Data provided here are supplemental to the database published in our paper. Please see paper for how gene assemblies provided here were used to build the tree in "Tree data" folder. All files provided in PGLS folder are sufficient to run PGLS code. See code annotations for further details.