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Data from: Exploring the visual world of fossilized and modern fungus gnat eyes (Diptera: Keroplatidae) with X-ray microtomography

Citation

Taylor, Gavin; Hall, Stephen; Gren, Johan; Baird, Emily (2019), Data from: Exploring the visual world of fossilized and modern fungus gnat eyes (Diptera: Keroplatidae) with X-ray microtomography, Dryad, Dataset, https://doi.org/10.5061/dryad.s502854

Abstract

Animal eyes typically possess specialised regions for guiding different behavioural tasks within their specific visual habitat. These specializations, and evolutionary changes to them, can be crucial for understanding an animal’s ecology. Here, we explore how the visual systems of some of the smallest flying insects, fungus gnats, have adapted to different types of forest habitat over time (~30 mya to today). Unravelling how behavioural, environmental and phylogenetic factors influence the evolution of visual specialisations is difficult, however, because standard quantitative techniques often require fresh tissue and/or provide data in eye-centric coordinates that prevent reliable comparisons between species with different eye morphologies. Here, we quantify the visual world of three gnats from different time periods and habitats using X-ray microtomography to create high resolution 3D models of the compound eyes of specimens in different preservation states – fossilized in amber, dried or stored in ethanol. We present a method for analysing the geometric details of individual corneal facets and for estimating and comparing the sensitivity, spatial resolution, and field of view of species across geographical space and evolutionary time. Our results indicate that, despite their miniature size, fungus gnats do have variations in visual properties across their eyes. We also find some indication that these visual specializations vary across species and may represent adaptations to their different forest habitats. Overall, the findings demonstrate how such investigations can be used to study the evolution of visual specializations – and sensory ecology in general – across a range of insect taxa from different geographical locations and across time.

Methods

This dataset was collected using microCT imaging at the 4D Imaging Lab at Lund University. The data was then manually processed in Amira and further calculations were then performed in Matlab. See the Methods and Supplemental Methods sections of Taylor et al. for further information.

Usage Notes

Amira Demo

An example of the Amira analysis procedure described by Talyor et al. Opening the .hx file in Amira will open an Amira project in which all of the described analysis steps have been completed.

Amira_demo.zip

 

Gnat Eye Data

The data require for and resulting from the computational analysis described by Taylor et al. The Zip archive contains a folder for each gnat (Ancient, Tropical, Temperate) which each contain the eye surface (in .stl format), one or more pairs of lines and path files (in .am format) and required transformations (in .txt format) to run the analysis scripts. The lends diameter, inter-facet angle and eye parameter calculated for each facter are included in .csv and .mat format.

Gnat_eye_data.zip


Gnat Compound Eyes and Labels

Raw volumes and label volumes for eyes and heads. These data are archived at MorphoSource project ID 699. 

 

Github gavinscode/museum-sample-eye-analysis.git

Matlab scripts required for analysis and plotting.

Funding

Carl Tryggers Stiftelse för Vetenskaplig Forskning, Award: CTS15:38

Air Force Office of Scientific Research, Award: FA8655-12-1-2136

Vetenskapsrådet, Award: 2014-4762

Lund University Faculty of Natural Sciences

Royal Physiographic Society of Lund