Changes in species composition in alpine snowbeds with climate change inferred from small-scale spatial patterns

Alpine snowbeds are characterised by a very short growing season. However, the length of the snow-free period is increasingly prolonged due to climate change, so that snowbeds become susceptible to invasions from neighbouring alpine meadow communities. We hypothesised that spatial distribution of species generated by plant interactions may indicate whether snowbed species will coexist with or will be out-competed by invading alpine species – spatial aggregation or segregation will point to coexistence or competitive exclusion, respectively. We tested this hypothesis in snowbeds of the Swiss Alps using the variance ratio statistics. We focused on the relationships between dominant snowbed species, subordinate snowbed species, and potentially invading alpine grassland species. Subordinate snowbed species were generally spatially aggregated with each other, but were segregated from alpine grassland species. Competition between alpine grassland and subordinate snowbed species may have caused this segregation. Segregation between these species groups increased with earlier snowmelt, suggesting an increasing importance of competition with climate change. Further, a dominant snowbed species (Alchemilla pentaphyllea) was spatially aggregated with subordinate snowbed species, while two other dominants (Gnaphalium supinum and Salix herbacea) showed aggregated patterns with alpine grassland species. These dominant species are known to show distinct microhabitat preferences suggesting the existence of hidden microhabitats with different susceptibility to invaders. These results allow us to suggest that alpine snowbed areas are likely to be reduced as a consequence of climate change and that invading species from nearby alpine grasslands could outcompete subordinate snowbed species. On the other hand, microhabitats dominated by Gnaphalium or Salix seem to be particularly prone to invasions by non-snowbed species.

Mineralogy-based quantitative precipitation and temperature reconstructions from annually laminated lake sediments (Swiss Alps) since AD 1580

[1] We present quantitative autumn, summer and annual precipitation and summer temperature reconstructions from proglacial annually laminated Lake Silvaplana, eastern Swiss Alps back to AD 1580. We used X-ray diffraction peak intensity ratios of minerals in the sediment layers (quartz qz, plagioclase pl, amphibole am, mica mi) that are diagnostic for different source areas and hydro-meteorological transport processes in the catchment. XRD data were calibrated with meteorological data (AD 1800/1864–1950) and revealed significant correlations: mi/pl with SON precipitation (r = 0.56, p < 0.05) and MJJAS precipitation (r = 0.66, p < 0.01); qz/mi with MJJAS temperature (r = −0.72, p < 0.01)and qz/am with annual precipitation (r = −0.54, p < 0.05). Geological catchment settings and hydro-meteorological processes provide deterministic explanations for the correlations. Our summer temperature reconstruction reproduces the typical features of past climate variability known from independent data sets. The precipitation reconstructions show a LIA climate moister than today. Exceptionally wet periods in our reconstruction coincide with regional glacier advances.

High-resolution summer temperature reconstruction from Lake Silvaplana based on in-situ reflectance spectroscopy

Annually laminated (varved) sediments of proglacial Lake Silvaplana (46 ̊27’N, 9 ̊48’E, 1791 m a.s.l., Engadine, eastern Swiss Alps) provide an excellent archive for quantitative high-resolution (seasonal – annual) reconstruction of high- and lowfrequency climate signals back to AD 1580. The chronology of the core is based on varve counting, Cs-137, Pb-210 and event stratigraphy. In this study we present a reconstruction based on in-situ reflectance spectroscopy. In situ reflectance spectroscopy is known as a cost- and time-effective non destructtive method for semi-quantitative analysis of pigments (e.g., chlorines and carotenoids) and of lithoclastic sediment fractions. Reflectance-dependent absorption (RDA) was measured with a Gretac Macbeth spectrolino at 2 mm resolution. The spectral coverage ranges from 380 nm to 730 nm at 10 nm band resolution. In proglacial Lake Silvaplana, 99% of the sediment is lithoclastic prior to AD 1950. Therefore, we concentrate on absorption features that are characteristic for lithoclastic sediment fractions. In Lake Silvaplana, two significant correlations that are stable in time were found between RDA typical for lithoclastics and meteorological data: (1) the time series R 570 /R 630 (ratio between RDA at 570 nm and 630 nm) of varves in Lake Silvaplana and May to October temperatures at nearby station of Sils correlate highly significantly (calibration period AD 1864 – 1951, r = 0.74, p < 0.01 for 5ptsmoothed series; RMSE is 0.28 ̊C, RE = 0.41 and CE = 0.38), and (2) the minimum reflectance within the 690nm band (min690) data correlate with May to October (calibration period AD 1864 – 1951, r = 0.68, p < 0.01 for 5pt-smoothed series; RMSE = 0.22 ̊C, RE = 0.5, CE = 0.31). Both proxy series (min690nm and R 570 /R 630 values) are internally highly consistent (r = 0.8, p < 0.001). In proglacial Lake Silvaplana the largest amount of sediment is transported by glacial meltwater. The melting season spans approximately from May to October, which gives us a good understanding of the geophysical processes explaining the correlations between lithoclastic proxies and the meteorological data. The reconstructions were extended back to AD 1580 and show a broad corresponddence with fully independent reconstructions from tree rings and documentary data.