Swiss Federal Institute for Forest, Snow and Landscape Research

About: Swiss Federal Institute for Forest, Snow and Landscape Research is a facility organization based out in Birmensdorf, Switzerland. It is known for research contribution in the topics: Climate change & Soil water. The organization has 1256 authors who have published 3222 publications receiving 161639 citations. The organization is also known as: WSL.

Environmental predictors of species richness in forest landscapes: abiotic factors versus vegetation structure

Abstract: Aim To investigate the performance and relative importance of abiotic and biotic predictors of species richness of three taxa in forest-dominated landscapes across an environmentally heterogeneous mountain region. Location Switzerland (central Europe). Methods We used a broad set of nationally available environmental predictors grouped into (1) climate, (2) topography and soil and (3) 3-D vegetation structure derived from airborne Light Detection and Ranging (LiDAR) data to spatially predict the forest species richness of vascular plants, butterflies and breeding birds. We used presence data of 212 plant, 157 butterfly and 92 bird species from multiple transect samples in > 220 1 km2 squares at elevations between 261 and 2123 m a.s.l. across 41,248 km2. We applied an ensemble modelling approach consisting of five modelling techniques and evaluated their predictive performance using the cross-validated percentage of explained variance of each predictor group separately and the combinations thereof. We investigated the relative importance and response of each predictor and partitioned the variation into independent and shared components per variable group. Results Climate performed best in predicting forest species richness across taxa. Vegetation structure particularly improved the predictions of butterfly and bird species richness, while soil pH was an important predictor for forest plant species richness. Climate appeared to be mainly indirectly related to butterfly species richness, via correlations with habitat type and structure. The strength and direction of the relationships between the predictors and species richness were taxon-specific with low cross-taxon congruence. Main conclusions The growing availability of LiDAR data offers powerful new tools for describing vegetation structure and associated animal habitat quality across large areas. This will further our understanding of niche-driven assembly processes in forest landscapes. Although climate was the dominant factor controlling species richness across taxa from different trophic levels, the taxon-specific distributional pattern and response to environmental conditions emphasize the difficulty of accounting for a range of taxa in prioritising biodiversity conservation measures.

Regional Scale Mapping of Grassland Mowing Frequency with Sentinel-2 Time Series

Abstract: Grassland use intensity is a topic of growing interest worldwide, as grasslands are integral in supporting biodiversity, food production, and regulating of the global carbon cycle. Data available for characterizing grasslands management are largely descriptive and collected from laborious field campaigns or questionnaires. The recent launch of the Sentinel-2 earth monitoring constellation provides new possibilities for high temporal and spatial resolution remote sensing data covering large areas. This study aims to evaluate the potential of a time series of Sentinel-2 data for mapping of mowing frequency in the region of Canton Aargau, Switzerland. We tested two cloud masking processes and three spatial mapping units (pixels, parcel polygons and shrunken parcel polygons), and investigated how missing data influence the ability to accurately detect and map grassland management activity. We found that more than 40% of the study area was mown before 15 June, while the remaining part was either mown later, or was not mown at all. The highest accuracy for detection of mowing events was achieved using additional clouds masking and size reduction of parcels, which allowed correct detection of 77% of mowing events. Additionally, we found that using only standard cloud masking leads to significant overestimation of mowing events, and that the detection based on sparse time series does not fully correspond to key events in the grass growth season.

Infrasound produced by debris flow: propagation and frequency content evolution

Abstract: Rapid mass movements such as avalanches, debris flows, and rock fall are periodic or episodic phenomena that occur in alpine regions. Recent studies have shown that debris flows generate characteristic signals in the low-frequency infrasonic spectrum (4–15 Hz). Infrasound can travel thousands of kilometers and can still be detectable. This characteristic provides a basis for the development of wide area automated monitoring systems that can operate in locations unaffected by the activity of the process. This study focuses on the infrasound vibrations produced by a debris flow at the Lattenbach torrent, Tyrol (Austria), and by two events at the Illgraben torrent, Canton of Valais (Switzerland). The Lattenbach torrent is a very active torrent, which is located in the west of Tyrol in a geologic fault zone between the Silvrettakristallin and the Northern Limestone Alps. It has a large supply of loose sediment. The Illgraben torrent, which is well known for its frequent sediment transport and debris flow activity, has been equipped with instruments for debris flow monitoring since the year 2000. This study shows that debris flow emits low-frequency infrasonic signals that can be monitored and correlated with seismic signals. During the passage of the debris flow, several surges were identified by ultrasonic gauges and detected in the time series and the running spectra of infrasonic data.