Unpacking ancient agricultural systems using chemotaxonomy to classify Poaceae pollen from Nar Gölü,Cappadocia,Türkiye

Abstract

Current morphological palynological methods for taxonomic discrimination of wild Poaceae versus domesticated cereals result in high levels of uncertainty. This uncertainty complicates the use of pollen records when investigating changes in historical landscapes managed by communities since the first evidence of cereal cultivation. To improve taxonomic resolution in the Poaceae family, we applied a chemotaxonomic approach using pollen chemical traits measured by Fourier-transform infrared (FTIR) microspectroscopy. Predictive classifier models trained on the pollen-derived chemotaxonomic data of 22 modern grass taxa yielded an accuracy of 87.4%, indicating a strong taxonomic signal. Next, subfossil pollen from Nar Gölü, in Cappadocia, Türkiye, was classified according to the closest match from modern pollen chemistry reference library. Our study shows that such subfossil pollen classification, although challenging, is possible when the chemistry of the subfossils lies within the modern reference range, and therefore exhibit chemical signatures comparable to extant pollen. For this reason, novelty detection techniques were employed to distinguish subfossil spectra non-existent (novel) to the modern dataset and reject their classifications. This study represents the first attempt to use chemotaxonomy to classify subfossil pollen. We provide an assessment of the potential of such methods for future applications, such as palaeoecological research to classify cryptic pollen assemblages and further unpack ancient agricultural systems.