The Tibetan Plateau (TP) is often referred to as the “Asian Water Tower”, as it plays a crucial role in supplying water for ∼1.9 billion people. Lakes in this arid mountain region have a wide salinity gradient and are sensitive to the complex interactions between climate and the water cycle, affecting aquatic ecosystems and species distributions. Here, we analyzed relationships between measured environmental variables and the spatial distribution of surface sediment diatom assemblages from 45 lakes located throughout the TP with the intention of developing a diatom-inference model for salinity. Diatom assemblage composition and diversity differed among lakes from the western (W), southern (S), northern (N), and southeastern (E) regions of the TP. The most common taxa observed in the lake set, Pantocsekiella ocellata, Nitzschia palea, and Staurosira venter, tended to have widespread distributions across the TP. In general, diatom diversity and richness tended to be highest in lakes with salinity concentrations between 0.1 and 10 g/L and were lowest in high salinity lakes (>20 g/L) of the N region. Canonical correspondence analysis (CCA) identified lake water salinity and maximum lake depth as explaining a statistically significant portion of diatom assemblage variation. Weighted-averaging (WA) was used to develop a diatom-based salinity inference model (R2jack = 0.71, RMSEPjack = 0.28) based on diatom optima from freshwater to meso-hyposaline lakes of the TP. Diatom-salinity reconstructions and changes in diatom community composition can potentially be used to track long-term patterns in climate and environmental conditions across the highly complex mountain landscape of the TP.
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