Abstract

Mongolia is an arid land with limited freshwater availability. Recent changes in climate as well as changes in livestock management in the post-Soviet era may threaten the quality and availability of these freshwater resources and emphasize the need to characterize current conditions relative to a long-term baseline. Because diatoms are responsive to changes in water chemistry and are commonly preserved in lake sediments, they can be used as indicators of both present and past water quality. To these ends, we have developed a diatom-based calibration set and quantitative inference models for the region. Physical and chemical factors and modern diatom communities were sampled at 54 sites in western Mongolia in the Altai and Khangai mountains and the Valley of the Great Lakes. Canonical correspondence analysis (CCA) demonstrated that both salinity and total phosphorus accounted for statistically significant fractions of the variation in 151 diatom taxa across the 54 sampled sites. Diatom-based inference models were developed with weighted averaging (WA) techniques and showed strong predictive capabilities and low prediction errors for salinity and total phosphorus. These models are now available to help identify and interpret historical and future disturbances to this sensitive and globally important eco-region.

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