ORCID

Abstract

Pollen analysis (palynology) is a valuable tool for palaeoecology, providing long-term records of vegetation change for reconstructions of past environments and revealing insights into historical climate variability, environmental change, and the vulnerability of ecosystems in response to anthropogenic impacts. However, its application in contributing to evidence-based conservation and restoration management depends on the accurate identification of fossil and sub-fossil pollen. This remains a persistent challenge for the Poaceae family (grasses), whose pollen grains are morphologically similar and often cannot be distinguished below the family level using traditional light microscopy. As a result, species-level changes in grassland communities are often obscured within palaeoecological records, limiting understanding of long-term vegetation dynamics particularly in ecologically important upland and moorland ecosystems. Thus, this thesis evaluates the potential of infrared spectroscopy to overcome these taxonomic limitations. The application of Fourier-Transform Infrared (FT-IR) spectroscopy to five ecologically important upland Poaceae taxa achieved complete species separation and 100% classification accuracy using machine learning approaches; species discrimination was driven by distinctive protein, lipid, and carbohydrate-associated signatures. For the first time, Optical-PhotoThermal Infrared (O-PTIR) spectroscopy was applied to chemical palynology, enabling non-destructive, sub-micron analysis of individual pollen grains. Results demonstrated that O-PTIR can detect subtle biochemical differences with high reproducibility. Analysis of chemically treated Molinia caerulea grains revealed genuine biochemical differences are driving separation between pollen grains instead of within-grain surface heterogeneity. O-PTIR assessment of pollen collected from six UK field locations further showed that between-grain variability accounted for most of the spectral variation, while environmental gradients had limited influence on sporopollenin chemistry. Together, these findings demonstrate that FT-IR and O-PTIR spectroscopy provide complementary approaches for improving the taxonomic resolution of morphologically similar Poaceae pollen and establishes a methodological framework for future species-level identification of fossil and sub-fossil Poaceae pollen.

Awarding Institution(s)

University of Plymouth

Supervisor

Ralph Fyfe, Simon Ussher, Mark Fitzsimons

Document Type

Thesis

Publication Date

2026

Embargo Period

2026-10-07

Deposit Date

October 2026

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Download

Share

COinS