Effect of climate and moss vegetation on ground surface temperature and the active layer among different biogeographical regions in Antarctica
Authors | |
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Year of publication | 2020 |
Type | Article in Periodical |
Magazine / Source | Catena |
MU Faculty or unit | |
Citation | |
web | https://www.sciencedirect.com/science/article/abs/pii/S0341816220301120 |
Doi | http://dx.doi.org/10.1016/j.catena.2020.104562 |
Keywords | active layer thickness; antarctica; mosses; climate change; ecosystems; soil thermal regime |
Description | Ground surface temperature (GST) and active layer thickness (ALT) are key indicators of climate change (CC) in permafrost regions, with their relationships with climate and vegetation being crucial for the understanding of future climate change scenarios, as well as of CC feedbacks on the carbon cycle and water balance. Antarctic ice free-areas host simplified ecosystems with vegetation dominated by mosses and lichens, and an almost negligible anthropogenic impact, providing a good template of ecosystem responses to CC. At three different Antarctic Conservation Biogeographical Regions (ACBR) sites in Antarctica located between 74° and 60°S, we compared barren ground and moss vegetated sites to understand and quantify the effects of climate (air temperature and incoming radiation) and of vegetation on GST and ALT. Our data show that incoming radiation is the most important driver of summer GST at the southernmost site, while in the other sites air temperature is the main driver of GST. Our data indicate that there is a decoupling between ALT and summer GST, because the highest GST values correspond with the thinnest ALT. Moreover, our data confirm the importance of the buffering effect of moss vegetation on GST in Antarctica. The intensity of the effect of moss cover on GST and ALT mainly depends on the species-specific moss water retention capacity and on their structure. These results highlight that the correct assessment of the moss type and of its water retention can be of great importance in the accurate modelling of ALT variation and its feedback on CC. |
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