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Modelling Climate Using Leaves of Nothofagus cunninghamii—Overcoming Confounding Factors

Authors :
Kathryn E. Hill
Stuart C. Brown
Alice Jones
Damien Fordham
Robert S. Hill
Source :
Sustainability; Volume 15; Issue 9; Pages: 7603
Publication Year :
2023
Publisher :
Multidisciplinary Digital Publishing Institute, 2023.

Abstract

Fossil leaf anatomy has previously been used as a proxy for paleoclimate. However, the exposure of leaves to sun or shade during their growth can lead to morphotype differences that confound the interpretation of fossil leaf anatomy in relation to climate and prevent reliable paleoclimate reconstruction. This work aims to model the differences in leaf anatomy that are due to various climatic drivers and differences attributable to sun or shade positions, using Nothofagus cunninghamii as the model species. Leaves from the sun and shade parts of three trees have been sampled from each of 11 sites in Victoria and Tasmania, Australia. The gross morphological and cuticular features have been scored and modelled with climate data from the sites. Random forest models can accurately predict Nothofagus cunninghamii contemporary climatic conditions of the spring temperature and summer rainfall based on leaf anatomical measurements. Leaf area, stomatal density and epidermal cell density are the most accurate predictors of whether a leaf grew in the sun or shade. Leaf area is also the strongest predictor of the maximum and minimum spring temperatures and rainfall. The models have implications for the use of fossilised leaves in paleoclimate reconstruction. The models we have built can be used to effectively predict whether a fossil leaf was from a sun or shade position on the tree and thus enable more reliable inference of paleoclimate by removing the confounding issues of variable leaf anatomy due to sun exposure during growth. Finally, these models could conceivably be used to make predictions of past paleoclimatic conditions provided suitable training and validation data on climatic conditions are available.

Details

Language :
English
ISSN :
20711050
Database :
OpenAIRE
Journal :
Sustainability; Volume 15; Issue 9; Pages: 7603
Accession number :
edsair.doi.dedup.....8666b7942e114be8a288b97cb7d562e7
Full Text :
https://doi.org/10.3390/su15097603