• TigerAce@lemmy.dbzer0.com
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      10 minutes ago

      Largest, not oldest. In Oregon, between 2500 and 8500 years old. But fungi existed before plants did, 1.3 billion and plants 700 million years ago. So fungi are much older.

        • PattyMcB@lemmy.world
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          7 minutes ago

          Heh… learn something new every day

          Edit: it sounds like it’s a hot topic

          It is widely considered a fungus, but the debate is ongoing.

          • in_my_honest_opinion@piefed.social
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            4 minutes ago

            From the paper I linked, it’s really interesting. They think it might be a giant eukaryote previously undefined.

            We hypothesized that if P. taiti was a fungus, fossilization products resulting from the selective preservation or diagenetic alteration of glucan sugars would be present, derived from the original main composition of the cell walls including chitin (a polymer of N-acetyl glucosamine), or resulting from the recombination of glucan and protein into new melanoidin-like compounds, like those found in Fungi and arthropods in the Rhynie chert (39). To test this hypothesis, the previously assembled dataset of 47 samples, representing six higher taxonomic groups (39), was combined with 55 additional samples from these six groups and P. taiti (see the Supplementary Materials for full spectra for each sample, images of all sample spots, and details of taxonomic assignment). We then developed a novel analytic pipeline comprising two key steps: data exploration (step 1) and modelling (step 2) (fig. S3 and Supplementary Text Extended Methods). Step 1 aimed to show that biologically informative spectral bands correlated with taxonomic classification of specimens and that molecular fingerprints of organisms in the Rhynie chert retained information regarding their biological affinities, and to select the most relevant spectral features for further modelling. In step 2, we built classification models using supervised machine learning approaches to provide a robust statistical framework to accept or reject the taxonomic classification of each sample based on the selected spectral features.