GSA Annual Meeting in Seattle, Washington, USA - 2017

Paper No. 174-18
Presentation Time: 9:00 AM-6:30 PM

RESPONSE OF LEAF EPIDERMAL CELL ARCHITECTURE TO CLIMATE - A POTENTIAL PALEOPROXY


AUBERY, Rose1, URBAN, Michael A.2, DUNN, Regan E.3, BARCLAY, Richard S.4 and PUNYASENA, Surangi W.2, (1)Department of Plant Biology, University of Illinois, 505 S. Goodwin Avenue, Urbana, IL 61801, (2)Department of Plant Biology, University of Illinois, 505 S. Goodwin Ave., Urbana, IL 61801, (3)Biology, University of Washington, 24 Kincaid Hall, PO BOX 351800, Seattle, WA 98195, (4)Department of Paleobiology, Smithsonian Institution, P.O. Box 37012, Washington, DC 20530-7012, aubery2@illinois.edu

Fossilized leaf cuticle are an untapped resource in the reconstruction of paleoclimate and paleovegetation. Leaf cuticle is common in sediments ranging from the Paleozoic to Quaternary. Leaf cuticle studies have most often focused on reconstructing past atmospheric pCO2 using stomatal index. However, leaf development is influenced by many environmental cues and other epidermal features could also serve as a proxy for additional variables, such as temperature and precipitation. To identify differences among cuticle that can reveal information about climate, we need to first look at modern leaves to gather how they respond to known climate variability. We sampled leaf material from herbarium specimens as well as from Jack Wolfe’s collection of leaf assemblages of modern Red Maple (Acer rubrum) and Rocky Mountain Maple (Acer glabrum). These samples span the whole range of each species and represent a continuum of variation in precipitation and temperature. We then macerated, stained, and mounted cuticle to slides and imaged them with a slide scanner. Images of these modern samples allow us to find differences in shape and size of epidermal cells, which is indicative of the temperature and precipitation the leaf received during growth. These images are the basis of ongoing work on the automated morphological analysis of leaf cuticle, investigating differences in cell margins (e.g., crenulation) of the cuticle, as well as the size and shape of cells on the adaxial side of the leaf. Using deep-learning neural nets, we will quantify the cuticle morphology and identify its response to climate. Our results will lay the foundation for a new paleoclimate proxy, as this automated system can be directly applied to fossil cuticle data.