Sub-Arctic alpine Vaccinium vitis-idaea exhibits resistance to strong variation in snowmelt timing and frost exposure, suggesting high resilience under climatic change

No effect of snow on shrub xylem traits: Insights from a snow-manipulation experiment on Disko Island, Greenland

Widespread shrubification across the Arctic has been generally attributed to increasing air temperatures, but responses vary across species and sites. Wood structures related to the plant hydraulic architecture may respond to local environmental conditions and potentially impact shrub growth, but these relationships remain understudied. Using methods of dendroanatomy, we analysed shrub ring width (RW) and xylem anatomical traits of 80 individuals of Salix glauca L. and Betula nana L. at a snow manipulation experiment in Western Greenland. We assessed how their responses differed between treatments (increased versus ambient snow depth) and soil moisture regimes (wet and dry). Despite an increase in snow depth due to snow fences (28-39 %), neither RW nor anatomical traits in either species showed significant responses to this increase. In contrast, irrespective of the snow treatment, the xylem specific hydraulic conductivity (Ks) and earlywood vessel size (LA95) for the study period were larger in S. glauca (p < 0.1, p < 0.01) and B. nana (p < 0.01, p < 0.001) at the wet than the dry site, while both species had larger vessel groups at the dry than the wet site (p < 0.01). RW of B. nana was higher at the wet site (p < 0.01), but no differences were observed for S. glauca. Additionally, B. nana Ks and LA95 showed different trends over the study period, with decreases observed at the dry site (p < 0.001), while for other responses no difference was observed. Our results indicate that, taking into account ontogenetic and allometric trends, hydraulic related xylem traits of both species, along with B. nana growth, were influenced by soil moisture. These findings suggest that soil moisture regime, but not snow cover, may determine xylem responses to future climate change and thus add to the heterogeneity of Arctic shrub dynamics, though more long-term species- and site- specific studies are needed.

Investigating the long-term response of plateau vegetation productivity to extreme climate: insights from a case study in Qinghai Province, China

Over the past three decades, there has been a significant global climate change characterized by an increase in the intensity and frequency of extreme climate events. The vegetation status in Qinghai Province has undergone substantial changes, which are more pronounced than other regions in the Qinghai-Tibet Plateau. However, a clear understanding of the response characteristics of plateau vegetation to extreme climate events is currently lacking. In this study, we investigated the response of net primary productivity (NPP) to different forms of extreme climate events across regions characterized by varying levels of aridity and elevation gradients. Specifically, we observed a significant increase in NPP in relatively arid regions. Our findings indicate that, in relatively arid regions, single episodes of high-intensity precipitation have a pronounced positive effect (higher correlation) on NPP. Furthermore, in high-elevation regions (4000-6000 m), both the intensity and frequency of precipitation events are crucial factors for the increase in regional NPP. However, continuous precipitation can have significant negative impacts on certain areas within relatively wet regions. Regarding temperature, a reduction in the number of frost days within a year has been shown to lead to a significant increase in NPP in arid regions. This reduction allows vegetation growth rate to increase in regions where it was limited by low temperatures. Vegetation conditions in drought-poor regions are expected to continue to improve as extreme precipitation intensifies and extreme low-temperature events decrease.

Prediction of Snowmelt Days Using Binary Logistic Regression in the Umbria-Marche Apennines (Central Italy)

Snow cover in a mountain area is a physical parameter that induces quite rapid changes in the landscape, from a geomorphological point of view. In particular, snowmelt plays a crucial role in the assessment of avalanche risk, so it is essential to know the days when snowmelt is expected, in order to prepare operational alert levels. Moreover, melting of the snow cover has a direct effect on the recharge of the water table, as well as on the regulation of the vegetative cycle of mountain plants. Therefore, a study on snowmelt, its persistence on the ground, and the height of the snow cover in the Umbria-Marche Apennines in central Italy is of great interest, since this is an area that is extremely poorly sampled and analysed. This study was conducted on the basis of four mountain weather stations equipped with a recently installed sonar-based snow depth gauge, so that a relatively short period, 2010–2020, was evaluated. A trend analysis revealed non-significant decreases in snow cover height and snow persistence time, in contrast to the significant increasing trend of mean temperature, while parameters such as relative humidity and wind speed did not appear to have a dominant trend. Further analysis showed relationships between snowmelt and the climatic parameters considered, leading to the definition of a mathematical model developed using the binary logistic regression technique, and having a predictive power of 82.6% in the case of days with snowmelt on the ground. The aim of this study was to be a first step towards models aimed at preventing avalanche risk, hydrological risk, and plant species adaptation, as well as providing a more complete definition of the climate of the study area.