Using novel biochemical and modelling techniques to reveal the past extent of native food plants in Victoria, southeast Australia. - Wills, Alastair (2023)
Under the compounded stresses of anthropogenic climate change, biodiversity losses, and a global agricultural system reliant on a small number of crops, agricultural productivity is projected to increase its risk of collapse as humanity progresses through the 21st century. Within this prescient modern context, archaeological and palaeoecological sciences can play an important role in shaping humanity’s future by drawing upon its past. The exploration of ancient and Indigenous food systems globally has been suggested as offering new pathways for sustainable agricultural practices in the future. However, studying ancient food histories using palaeoecological methods is inhibited broadly by taxonomic resolution issues, which limit researchers’ abilities to explore ancient food plant histories quantitatively. Palynology, a discipline of palaeoecological study in the Quaternary sciences, as the study of ancient pollen and spores, has operated within these constraints since its conception in 1916. In this thesis, I have employed novel chemotaxonomic (classification of species based on their biochemistry) techniques which can improve the taxonomic resolution of modern pollen to a species level and have extended these methods to the sub-fossil record. This method relies on obtaining vibrational spectra of pollen sporopollenin (the wall material of pollen) using microscopic Fourier transform infrared spectroscopy (FTIR) analyses and classifying the data using the Random Forest (RF) machine learning algorithm. Additionally, I have applied the mechanistic Regional Estimates of VEgetation from Large Sites (REVEALS) model to quantify vegetation extent from sub-fossil pollen. My results indicate that chemotaxonomy is a viable pathway to improve taxonomic fidelity in palaeoecological records and can be combined with vegetation reconstruction techniques. I find that interspecific signals are present within pollen vibrational spectra and can be used to reconstruct ancient and Indigenous food plant histories. Thus, I present the first quantitative reconstruction of an Indigenous staple food plant, a first for Australia. Furthermore, I present the world’s first test of quantified vegetation extent reconstructions of taxa identified by chemotaxonomy.