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Reconstructions of eastern African vegetation and climate are critical for understanding primate and large mammal evolution in the Neogene. Insight into past ecological conditions can be gleaned from lipid biomarkers preserved in sedimentary archives, providing evidence for the role of habitats (e.g. open vs. closed vegetation) on evolutionary trait selection. A common paleoecological proxy is the 𝛿¹³C of n-alkanes, which integrates the distinct isotopic signatures of C3 and C4 vegetation. In typical modern tropical ecosystems, “woody” vegetation uses C3 photosynthesis while “grassy” vegetation uses C4 photosynthesis. Under these conditions, mixing models can then estimate the fraction of woody cover of a landscape. While the use of photosynthetic pathways to infer plant functional type (PFT) is powerful, this paradigm does not hold prior to the rise of C4 grasses at 10 Ma, leaving a gap in understanding of ecosystem structure in the early-mid Miocene. To address this issue, we investigate whether n-alkane chain length distributions (rather than 𝛿¹³C) hold information about plant functional type independent of photosynthetic pathway. Here, we present n-alkane chain length data from over 800 modern plant samples, representing a variety of different photosynthetic pathways, growth forms, habitats, and locations. This dataset comprises a significant literature review component, as well as over 400 new distributions generated in this study. We build upon our previous work using PCA and turn to non-linear methods – including both supervised neural network classifiers and unsupervised dimensionality reduction – to determine the potential of n-alkane distributions for PFT identification. Successful differentiation between woody and grassy PFTs using modern plant n-alkane chain lengths will provide a foundation for applying this tool to the geologic record. Our method will compliment well-established isotopic measurement practices while offering the novel ability to reconstruct vegetation structure in pure C3 ecosystems. This represents a particularly powerful tool for understanding ecological history prior to the rise of C4 grasses. 

AGU Fall Meeting, Chicago, Il, December 12-16, 2022; Presentation PP22E-0879 

Presentation PP22E-0874 

AGU Fall Meeting, Chicago, Il, December 12-16, 2022; Presentation PP12C-0652