|Title||Geochemical zones and environmental gradients for soils from the central Transantarctic Mountains, Antarctica|
|Publication Type||Journal Article|
|Year of Publication||2021|
|Authors||Diaz, MA, Gardner, CB, Welch, SA, W. Jackson, A, Adams, BJ, Wall, DH, Hogg, ID, Fierer, N, W. Lyons, B|
|Pagination||1629 - 1644|
Previous studies have established links between biodiversity and soil geochemistry in the McMurdo Dry Valleys, Antarctica, where environmental gradients are important determinants of soil biodiversity. However, these gradients are not well established in the central Transantarctic Mountains, which are thought to represent some of the least hospitable Antarctic soils. We analyzed 220 samples from 11 ice-free areas along the Shackleton Glacier (~85°S), a major outlet glacier of the East Antarctic Ice Sheet. We established three zones of distinct geochemical gradients near the head of the glacier (upper), its central part (middle), and at the mouth (lower). The upper zone had the highest water-soluble salt concentrations with total salt concentrations exceeding 80 000 µg g-1, while the lower zone had the lowest water-soluble N:P ratios, suggesting that, in addition to other parameters (such as proximity to water and/or ice), the lower zone likely represents the most favorable ecological habitats. Given the strong dependence of geochemistry on geographic parameters, we developed multiple linear regression and random forest models to predict soil geochemical trends given latitude, longitude, elevation, distance from the coast, distance from the glacier, and soil moisture (variables which can be inferred from remote measurements). Confidence in our random forest model predictions was moderately high with R2 values for total water-soluble salts, water-soluble N:P, ClO4-, and ClO3- of 0.81, 0.88, 0.78, and 0.74, respectively. These modeling results can be used to predict geochemical gradients and estimate salt concentrations for other Transantarctic Mountain soils, information that can ultimately be used to better predict distributions of soil biota in this remote region.