Globally, ultramafic outcrops are renowned for hosting floras with high levels of endemism, including plants with specialised adaptations such as nickel or manganese hyperaccumulation. Soils derived from ultramafic regoliths are generally nutrient-deficient, have major cation imbalances, and have concomitant high concentrations of potentially phytotoxic trace elements, especially nickel. The South and Southeast Asian region has the largest surface occurrences of ultramafic regoliths in the world, but the geoecology of these outcrops is still poorly studied despite severe conservation threats. Due to the paucity of systematic plant collections in many areas and the lack of georeferenced herbarium records and databased information, it is not possible to determine the distribution of species, levels of endemism, and the species most threatened. However, site-specific studies provide insights to the ultramafic geoecology of several locations in South and Southeast Asia. The geoecology of tropical ultramafic regions differs substantially from those in temperate regions in that the vegetation at lower elevations is generally tall forest with relatively low levels of endemism. On ultramafic mountaintops, where the combined forces of edaphic and climatic factors intersect, obligate ultramafic species and hyperendemics often occur. Forest clearing, agricultural development, mining, and climate change-related stressors have contributed to rapid and unprecedented loss of ultramafic-associated habitats in the region. The geoecology of the large ultramafic outcrops of Indonesia’s Sulawesi, Obi and Halmahera, and many other smaller outcrops in South and Southeast Asia, remains largely unexplored, and should be prioritised for study and conservation.

Ecosystem-bedrock interactions power the biogeochemical cycles of Earth’s shallow crust, supporting life, stimulating substrate transformation, and spurring evolutionary innovation. While oxidative processes have dominated half of terrestrial history, the relative contribution of the biosphere and its chemical fingerprints on Earth’s developing regolith are still poorly constrained. Here, we report results from a two-year incipient weathering experiment. We found that the mass release and compartmentalization of major elements during weathering of granite, rhyolite, schist and basalt was rock-specific and regulated by ecosystem components. A tight interplay between physiological needs of different biota, mineral dissolution rates, and substrate nutrient availability resulted in intricate elemental distribution patterns. Biota accelerated CO2 mineralization over abiotic controls as ecosystem complexity increased, and significantly modified the stoichiometry of mobilized elements. Microbial and fungal components inhibited element leaching (23.4% and 7%), while plants increased leaching and biomass retention by 63.4%. All biota left comparable biosignatures in the dissolved weathering products. Nevertheless, the magnitude and allocation of weathered fractions under abiotic and biotic treatments provide quantitative evidence for the role of major biosphere components in the evolution of upper continental crust, presenting critical information for large-scale biogeochemical models and for the search for stable in situ biosignatures beyond Earth.

Failure of sulfate-reducing bacteria (SRB)-mediated treatment of acid mine drainage (AMD) in cold regions due to inhibition of bacteria by acidic pH and low temperature can be overcome by enriching...

In this study, hierarchies of probabilistic models are evaluated for their ability to characterize the untemplated addition of adenine and uracil to the 3’ ends of mitochondrial mRNAs of the human pathogen Trypanosoma brucei, and for their generative abilities to reproduce populations of these untemplated adenine/uridine “tails”. We determined the most ideal Hidden Markov Models (HMMs) for this biological system. While our HMMs were not able to generatively reproduce the length distribution of the tails, they fared better in reproducing nucleotide composition aspects of the tail populations. The HMMs robustly identified distinct states of nucleotide addition that correlate to experimentally verified tail nucleotide composition differences. However they also identified a surprising subclass of tails among the ND1 gene transcript populations that is unexpected given the current idea of sequential enzymatic action of untemplated tail addition in this system. Therefore, these models can not only be utilized to reflect biological states that we already know about, they can also identify hypotheses to be experimentally tested. Finally, our HMMs supplied a way to correct a portion of the sequencing errors present in our data. Importantly, these models constitute rare simple pedagogical examples of applied bioinformatic HMMs, due to their binary emissions.