Mechanisms behind species-specific water economy responses to water level drawdown in peat mosses. (18th March 2020) - Bengtsson, Fia; Granath, Gustaf; Cronberg, Nils; Rydin, Håkan
Abstract: Background and Aims: The ecosystem engineers Sphagnum (peat mosses) are responsible for sequestering a large proportion of carbon in northern peatlands. Species may respond differently to hydrological changes, and water level changes may lead to vegetation shifts in peatlands, causing them to revert from sinks to sources of carbon. We aimed to compare species-specific responses to water level drawdown within Sphagnum, and investigate which traits affect water economy in this genus. Methods: In a mesocosm experiment, we investigated how water level drawdown affected water content (WC) in the photosynthetically active apex of the moss and maximum quantum yield of photosystem II (i.e. F v / F m ) of 13 Sphagnum species. Structural traits were measured, and eight anatomical traits were quantified from scanning electron microscopy micrographs. Key Results: Mixed-effects models indicated that at high water level, large leaves were the most influential predictor of high WC, and at low water level WC was higher in species growing drier in the field, with larger hyaline cell pore sizes and total pore areas associated with higher WC. Higher stem and peat bulk density increased WC, while capitulum mass per area and numerical shoot density did not. We observed a clear positive relationship between F v / F m and WC in wet-growing species. Conclusions: While we found that most hummock species had a relatively high water loss resistance, we propose that some species are able to maintain a high WC at drawdown by storing large amounts of water at a high water level. Our result showing that leaf traits are important warrants further research using advanced morphometric methods. As climate change may lead to more frequent droughts and thereby water level drawdowns in peatlands, a mechanistic understanding of species-specific traits and responses is crucial for predicting future changes in these systems.