Pixel2Paleo - High-resolution imaging of lake sediments

Lake sediments preserve critical information about past environmental changes, yet traditional analytical approaches examine proxies in isolation at limited resolution. We present a framework for integrating multiple non-destructive, high-resolution imaging techniques to generate comprehensive, openly accessible datasets that capture the full complexity of sedimentary biogeochemical signals.

We combine three complementary imaging methods at resolutions of 40-200 μm: μXRF elemental mapping (inorganic composition), Hyperspectral Imaging (HSI, pigment analysis), and Mass Spectrometry Imaging (MSI, organic molecules). This generates datasets with up to 3,000 variables per pixel, enabling deductive exploration of sediment patterns rather than traditional single-proxy reconstructions.

A critical challenge is the lack of standardised protocols for acquiring, processing, and sharing high-resolution imaging data. Building on the open-source napari-sediment environment, we aim to create accessible tools for data harmonisation, enabling consistent integration and analysis of independent datasets.

Our approach emphasises FAIR data principles. We are establishing protocols for long-term storage and exploring integration with existing databases (e.g., PANGAEA, Neotoma). The goal is to create a publicly accessible biogeochemical fingerprint database that links sediment composition to specific environmental conditions—analogous to genetic databases.

Initial applications focus on Swiss lakes spanning various trophic states and altitudes, with records covering 16,000 years. Linking recent sediments (~200 years) to instrumental monitoring data will allow us to validate biogeochemical signals and establish reference fingerprints.

This framework follows the philosophy of PalaeOpen closely by: (1) making high-resolution multi-proxy downcore datasets publicly available, (2) providing standardised workflows enhancing data interoperability, and (3) enabling large-scale comparative analyses informing conservation strategies. The resulting database will facilitate accurate interpretations of past changes and improve our ability to anticipate ecosystem responses to climate change, ensuring sedimentary archives contribute maximally to understanding and protecting natural heritage.