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Many desiccation-tolerant plants are widely distributed and exposed to substantial environmental variation across their native range. These environmental differences generate site-specific selective pressures that could drive natural variation in desiccation tolerance across populations. If identified, such natural variation can be used to target tolerance-enhancing characteristics and identify trait associations within a common genetic background. Here, we tested for natural variation in desiccation tolerance across wild populations of the South African resurrection plant Myrothamnus flabellifolia. We surveyed a suite of functional traits related to desiccation tolerance, leaf economics, and reproductive allocation in M. flabellifolia to test for trait associations and tradeoffs. Despite considerable environmental variation across the study area, M. flabellifolia plants were extremely desiccation tolerant at all sites, suggesting that tolerance is either maintained by selection or fixed in these populations. However, we detected notable associations between environmental variation, population characteristics, and fitness traits. Relative to mesic sites, plants in xeric sites were more abundant and larger, but were slower growing and less reproductive. The negative association between growth and reproduction with plant size and abundance pointed towards a potential growth–abundance tradeoff. The finding that M. flabellifolia is more common in xeric sites despite reductions in growth rate and reproduction suggests that these plants thrive in extreme aridity. 

Abstract. The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM.We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.