en:
This dataset comprises of a post-processed set of terrestrial laser scans (TLS’s) of Antarctic sea ice obtained during the Sea Ice Physics and Ecosystem Experiment-2 (SIPEX-2, http://seaice.acecrc.org.au/sipex2012/) in September-November 2012. The post-processing steps include the registration of the individual scans into a single 3-dimensional point cloud, the removal of unwanted noise caused by particles in the air (i.e., snow crystals), and the final generation of surface grids based on the cleaned individual point returns. The final product includes the ‘xyz’ coordinates of the individual point measurements, and gridded surfaces covering study areas of 100m x 100 m, and at resolutions of 0.01 m, 0.1 m, 0.25 m, 0.5 m and 1 m for each of the survey dates. Additionally, subgrid statistics that include the mean elevation, standard deviation, minimum and maximum elevations, range, and number of point returns in each gridcell are generated. The final product is provided in space-delimited text files, with the surface grids provided in Digital Terrain Model (DTM) format ready for visualization in any GIS software.
How to cite:
Please also cite the original publication when using this data set.: Trujillo, E., K. Leonard, T. Maksym, and M. Lehning (2016), Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice, J. Geophys. Res. Earth Surf., 121, doi:[10.1002/2016JF003893](https://dx.doi.org/10.1002/2016JF003893).

en: tls terrestrial-laser-scans sea-ice sea-ice-elevation polar

en: High resolution sea ice surface topography from the SIPEX-2 expedition, East Antarctica, 2012

de:
Resource Title: Data processing documentation
    Size: 848896 bytes
    Format: application/msword
    URL: https://www.envidat.ch/dataset/c88b82ed-d54e-43e6-b4e4-7ae1ee06a014/resource/bb51210c-6738-41d4-b4a4-31dd08f4725e/download/tlssipex-2metadata.doc
    Description:

format: msword

de:
Resource Title: Post Processed TLS's
    Size: 932144467 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c88b82ed-d54e-43e6-b4e4-7ae1ee06a014/resource/2557ecb5-e65d-4d60-97ce-fd6696ee2d00/download/10-16904-9sipex2dat.zip
    Description: Compressed dat files

polar

display_name: polar

sea-ice

display_name: sea-ice

sea-ice-elevation

display_name: sea-ice-elevation

terrestrial-laser-scans

display_name: terrestrial-laser-scans

tls

display_name: tls


$oid: OBSOLETE

en:
The attached data are some large GIS raster files (GeoTIFFs) made with Natural Earth data. Natural Earth is a free vector and raster map data @ naturalearthdata.com. The data used for creating these large files was the "Cross Blended Hypso with Shaded Relief and Water". Data was concatenated to achieve larger and larger files. Internal pyramids were created, in order that the files can be opened easily in a GIS software such as QGIS or by a (future) GIS data visualisation module integrated in EnviDat.
Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com

envidat

approval_status: approved

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

it: EnviDat è il portale dati del WSL che fornisce un accesso unificato e gestito ai dati di monitoraggio ambientale e di ricerca. Il portale ha la capacità di ospitare e pubblicare serie di dati preziosi e unici che vengono condivisi in tutto il mondo. Così facendo, EnviDat promuove la ricerca e contribuisce al progresso della scienza ambientale.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

en: Large GIS raster data derived from Natural Earth Data (Cross Blended Hypso with Shaded Relief and Water)

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

de:
Resource Title: map preview 0.5MB
    Size: 482223 bytes
    Format: image/jpeg
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.68/gisdata/tiny_map_preview.jpg
    Description:

format: jpeg

de:
Resource Title: Bulk Data Access
    Size: 111669149696 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.68%2F
    Description: Link to the S3 bucket where all the data resources can be downloaded in bulk

gis

display_name: gis

large-files

display_name: large-files

natural-earth

display_name: natural-earth

qgis

display_name: qgis


en:
This dataset contains all data on which the following publication below is based.
Paper Citation:
Risch, A.C., Frossard, A., Schütz, M., Frey, B., Morris, A.W., Bump, J.K. (accepted) Effects of elk and bison carcasses on soil microbial communities and ecosystem functions in Yellowstone, USA. (accepted). Functional Ecology
doi: ...
Methods
Study area and study sites
This study was conducted in YNP’s Northern Range (NR), located in north-western Wyoming and south-western Montana, USA (~44.9163° N, 110.4169° W). The NR expands over ~1000 km2 and features long cold winters and short dry summers. Grasslands and shrublands dominate the NR that is the home of large migratory herds of bison (winter counts 2017: ~3919 individuals; Geremia, Wallen, & White, 2017) and elk (~5349 individuals) as well as their main predators, approximately five packs of wolves with a total of 33 individuals (Smith et al., 2017). As part of a long-term research program within YNP, wolf predation has been studied since their reintroduction in 1995.
For our study, we received ground-truthed coordinates of bison and elk carcasses from winter 2016/17 (November 2016 through April 2017) from the YNP Wolf Project. Between June 20 and July 1, 2017, we visited 24 carcasses in total. At five sites, we could not sample as the carcasses were no longer found. In total we located remains (hairmats, rumen content, bones, teeth) of 19 adult male and female carcasses (7 bison, 12 elk; Supplementary Table 1). Live body weights of adult bison and elk are approximately 730 kg (male bison), 450 kg (female bison), 330 kg (male elk), and 235 kg (female elk, Meagher, 1973; Quimby & Johnson, 1951).
The kills and subsequent consumption happened between 34 and 173 days prior to our sampling (hereafter “days since kill”, DSK), for which we accounted in our statistics. Note that wolves and other scavengers consumed the soft tissue of the carcasses quickly, hence, there is close to no soft tissue left for decomposition as compared to an intact body left on the soil surface. The 19 carcass sites covered the extent of YNP’s NR, with both bison and elk carcasses showing similar distributions; elevation ranged from 1703 to 2884 m a.s.l. (Supplementary Fig 1 & Supplementary Table 1). The carcasses were all located in grassland or sage-brush shrubland, with or without sparsely scattered trees, and both bison and elk carcasses showed the same distribution of DSK. At each study site, we selected a reference plot (hereafter “control”) that was of comparable size, slope aspect and vegetation to the carcass location (hereafter “carcass”). The control was at least 10 m away (Danell, Berteaux, & Brathen, 2002; Melis et al., 2007) from the carcass itself to ensure the absence of potential direct and indirect carcass effects (paired design; (Bump, Webster, et al., 2009; Bump, Peterson, et al., 2009).
Ecosystem functions and soil properties
We randomly collected 50 g of mineral soil from three locations on both control and carcass plots to a depth of 5 cm with sterile techniques and gently mixed the material to obtain a composite sample. Half the soil sample was immediately bagged in plastic bags (whirl packs), stored in a cooler with ice packs (~5 ºC), sieved (2-mm) and frozen within 4-6 hours of collection to assess soil microbial communities. For this purpose, we extracted total genomic DNA from 0.5 g soil using the PowerSoil DNA Isolation Kit (Qiagen, Hilden, Germany). DNA concentrations were measured using PicoGreen (Molecular Probes, Eugene, OR, USA). PCR amplifications of partial bacterial small-subunit ribosomal RNA genes (region V3–V4 of 16S rRNA) and fungal ribosomal internal transcribed spacers (region ITS2) were performed as described previously (Frey et al., 2016). Each sample consisting of 40 ng DNA was amplified in triplicate and pooled before purification with Agencourt AMPure XP beads (Beckman Colter, Berea, CA, USA) and quantified with the Qubit 2.0 fluorometric system (Life Technologies, Paisley, UK). Amplicons were sent to the Genome Quebec Innovation Center (Montreal, Canada) for barcoding using the Fluidigm Access Array technology and paired-end sequencing on the Illumina MiSeq v3 platform (Illumina Inc., San Diego, CA, USA).
Quality control of bacterial and fungal reads was performed using a customized pipeline (Supplementary Table 2; Frey et al., 2016). Paired-ends reads were matched with USEARCH (Edgar & Flyvbjerg, 2015), substitution errors were corrected using Bayeshammer (Nikolenko, Korobeynikov, & Alekseyev, 2013) and PCR primers were trimmed (allowing for 1 mismatch, read length -300 bp for 16S and -200 bp for ITS primers) using Cutadapt (M. Martin, 2011). Sequences were dereplicated and singleton reads removed prior to clustering into operational taxonomic units (OTUs) at 97% identity using USEARCH (Edgar, 2013). The remaining centroid sequences were tested for the presence of ribosomal signatures using Metaxa2 (Bengtsson-Palme et al., 2015) or ITSx (Bengtsson-Palme et al., 2013). Taxonomic assignments of the OTUs were obtained using Bayesian classifier (Wang, Garrity, Tiedje, & Cole, 2007) with a minimum bootstrap support of 60% implemented in mothur (Schloss et al., 2009) by querying the bacterial and fungal reads against the SILVA Release 128 (Quast et al., 2013) and UNITE 8.0 (Abarenkov et al., 2010) reference databases for 16S and ITS OTUs, respectively.
Abundances of the bacterial 16S rRNA gene and fungal ITS amplicon were determined by quantitative real-time PCR (qPCR) on an ABI7500 Fast Real-Time PCR system (Applied Biosystems, Foster City, CA, USA) as described previously (Frossard et al., 2018). The same primers (without barcodes) and cycling conditions as for the sequencing approach were used for the 16S and ITS qPCR. Three standard curves per target region were obtained using tenfold serial dilutions of plasmids generated from cloned targets (Frey, Niklaus, Kremer, Lüscher, & Zimmermann, 2011). Data were converted to represent mean copy number of targets per gram of soil (dry weight).
The other half of the soil sample was bagged in paper, dried to constant weight at 60°C, passed through a 2 mm sieve and analyzed for total C and N concentration with a CE Instruments NC 2100 soil analyzer (CE Elantech Inc., Lakewood NJ, USA). We also collected 20 mature and undamaged leaves of the dominant grass species growing on control and carcass sites, but taxa were not recorded. The plant material was dried at 60°C, finely ground till homogenized and also analyzed to obtain total C and N concentrations. Soil temperature (10 cm depth) was measured with a waterproof digital thermometer (Barnstead International, Dubuque IA, USA) at three locations each at the control and carcass site. Soil moisture (0 – 10 cm depth) was measured with time domain reflectometry (Field-Scout TDR-100; Spectrum Technologies, Plainfield IL, USA) at five randomly chosen points on control and carcass sites. We measured soil respiration at five randomly chosen points at both control and carcass sites with a PP-Systems SRC-1 soil respiration chamber (closed circuit) attached to a PP-Systems EGM-4 infrared gas analyzer (PP-Systems, Amesbury, MA, USA). For each measurement the soil chamber (15 cm high; 10 cm diameter) was tightly placed on the soil surface, after clipping plants to avoid measuring plant respiration or photosynthesis. Measurements were conducted over 120 s.
In addition, we assessed the decomposition rates of standardized OM using the cotton strip assay (Latter & Howson, 1977; Latter & Walton, 1988). Cotton cloth tensile strength loss (CTSL) is a measure of decomposition, and an index to express the combined effect of soil microclimatic, physical, chemical and biological properties on decomposition while accounting for OM quality (Latter & Walton, 1988; Risch, Jurgensen, & Frank, 2007; Withington & Sanford Jr., 2007). We placed five 20 cm wide x 13 cm long sheets of 100% unbleached cotton cloth (American Type SM 1/18’’, Warp: 34/1, Weft: 20/1, Weave plain, 29.5 picks/cm warp, 22 picks/cm weft, 237 g/m2; Daniel Jenny & Co., Switzerland;) at each carcass and control site vertically into the soil by making slits with a flat spade to a depth of 12 cm. We inserted each cloth with the spade, and then pushed the slit closed to assure tight contact with the soil. The cloths were retrieved after 18 to 27 days. After retrieval, the cloths were air-dried, remaining soil gently removed by hand, and 1.5 cm wide strips were cut at the 3.5-5.0 cm (top) and the 9-10.5 cm (bottom) soil depth. The strips were equilibrated at 50 % relative humidity and 20°C for 48 hours (climate chamber) prior to strength testing (Scanpro Awetron TH-1 tensile strength tester; AB Lorentzen and Wettre, Kista, Sweden). Cotton rotting rate (CRR) = (CTScontrol - CTSfinal/CTSfinal)1/3 * (365/t), where CTScontrol is the cotton tensile strength of a control cloth and CTSfinal the cotton tensile strength of the incubated sample, t is the incubation period in days. Control cloths were inserted into the ground and immediately retrieved to account for tensile strength loss associated with cloth insertion. We averaged the CRR of top and bottom strips for further analyses as no difference was found between the two. All sampling and cloth insertion took place between June 20 and July 1, 2017, cloths were retrieved between July 17 and 20, 2017. Soil respiration, average CRR, vegetation N concentration and vegetation C:N ratio are defined as ecosystem functions, soil C and N concentration, soil temperature and moisture as soil abiotic properties, and bacterial and fungal richness (number of taxa), diversity (Shannon) and abundance as soil biotic properties.
Statistical analyses
Univariate analyses for ecosystem functions, soil biotic and abiotic properties
We tested whether individual ecosystem functions, soil biotic and abiotic properties differed between carcass and control (“Location”), bison and elk (“Species”) and days since kill (“DSK”). For this purpose, we used linear mixed effect models (LMM, “nlme” package v 3.1 – 131.1 in R v 3.4.4; Pinheiro, Bates, DebRoy, & Sarkar, 2018; R Core Team, 2019) with Location, Species, Location x Species and DSK as fixed effects. Site was included as random effect to account for the paired design. We developed a separate model for all dependent variables. All but bacterial richness, fungal richness, fungal diversity and vegetation N concentration were natural-log transformed to meet model assumptions. For each LMM, we calculated contrasts to assess the specific comparisons we were interested in with the “lsmeans” package v 2.27-62 (Lenth & Love, 2018): 1) carcass vs control, 2) carcass bison vs control bison, and 3) carcass elk vs control elk. We also tested whether we had differences between bison and elk carcasses or the sites where bison and elk were killed and included contrasts 4) carcass bison vs carcass elk and 5) control bison vs control elk.
We calculated the log response ratio (LRR = ln[carcass/control]) to obtain carcass effects for all variables for both species separately. LRR - 0 indicates higher value at control compared to carcass, LRR - 0 indicates higher values at carcass compared control. We used LRRs for visualization and to assess spatial patterns in carcass effects across YNP. For this purpose we calculated the Moran’s I statistic for each ecosystem function, soil biotic and abiotic property based on a latitude-longitude matrix with the “moran.test” function in the “spdep” package version 1.1-3 (Bivand et al., 2019).
Multivariate analyses
Rare OTUs, defined as OTUs with a low abundance of reads, were retained in multivariate methods because they only marginally influence these analyses (Gobet, Quince, & Ramette, 2010). Bray–Curtis dissimilarity matrices were generated based on square-root-transformed matrices. We used Principal Coordinate Analyses (PCoA) to assess how soil bacterial and fungal communities differed between control and carcass of bison and elk (“vegan” package v 2.5-4, Oksanen et al., 2019). We then extracted PCoA axes scores 1 and 2 and used LMM (“nlme” package) with Location, Species, Location x Species and DSK as fixed effects. Site was, again, included as random effect. We again calculated the contrasts as described above using the “lsmeans” package. We also assessed how ecosystem functions, and soil abiotic and biotic properties were related to the soil bacteria and fungi community structure associated with bison and elk control and carcasses using the “envfit” function in the “vegan” package (Oksanen et al., 2019).
Indicator species analyses were performed using the multipatt function implemented in the “indicspecies” package version 1.7.6 with 100000 permutations (De Caceres & Jansen, 2016). This step allowed to identify OTUs that led to changes in multivariate patterns between control and carcass of both bison and elk separately (De Cáceres, Legendre, & Moretti, 2010). The multipatt function uses a point biserial correlation coefficient statistical test. Indicator OTUs were defined as bacterial and fungal OTUs with more than 50 sequences, i.e., removing rare taxa and taxa with low abundances containing little indicator information (Rime et al., 2015) and that were significantly correlated with Location (p - 0.05, correlation coefficient - 0.3). A heatmap of these OTUs were generated with the vegan and ggplot2 packages. The indicator analyses were performed in R version 3.3.3 (R Core Team, 2017).
References
Abarenkov, K., Henrik Nilsson, R., Larsson, K.-H., Alexander, I. J., Eberhardt, U., Erland, S., … Kõljalg, U. (2010). The UNITE database for molecular identification of fungi – recent updates and future perspectives. New Phytologist, 186(2), 281–285. doi:10.1111/j.1469-8137.2009.03160.x
Bengtsson-Palme, J., Hartmann, M., Eriksson, K. M., Pal, C., Thorell, K., Larsson, D. G. J., & Nilsson, R. H. (2015). metaxa2: improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data. Molecular Ecology Resources, 15(6), 1403–1414. doi:10.1111/1755-0998.12399
Bengtsson-Palme, J., Ryberg, M., Hartmann, M., Branco, S., Wang, Z., Godhe, A., … Nilsson, R. H. (2013). Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data. Methods in Ecology and Evolution, 4(10), 914–919. doi:10.1111/2041-210X.12073
Bivand, R., Altman, M., Anselin, L., Assuncao, R., Berke, O., Blanchet, G., … Yu, D. (2019). spdep: Spatial dependence, weighthing schemes, statistics. R package version 1.1-3.
Bump, J. K., Peterson, R. O., & Vucetich, J. A. (2009). Wolves modulate soil nutrient heterogeneity and foliar nitrogen by configuring the distribution of ungulate carcasses. Ecology, 90(11), 3159–3167.
Bump, J. K., Webster, C. R., Vucetich, J. A., Peterson, R. O., Shields, J. M., & Powers, M. D. (2009). Ungulate carcasses perforate ecological filters and create biogeochemical hotspots in forest herbaceous layers allowing trees a competitive advantage. Ecosystems, 12(6), 996–1007. doi:10.1007/s10021-009-9274-0
Danell, K., Berteaux, D., & Brathen, K. A. (2002). Effect of muskox carcasses on nitrogen concentration in tundra vegetation. Arctic, 55(4), 389392.
De Caceres, M., & Jansen, F. (2016). indicspecies: relationship between species and groups of species. R package version 1.7.6.
De Cáceres, M., Legendre, P., & Moretti, M. (2010). Improving indicator species analysis by combining groups of sites. Oikos, 119(10), 1674–1684. doi:10.1111/j.1600-0706.2010.18334.x
Edgar, R. C. (2013). UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature Methods, 10, 996.
Edgar, R. C., & Flyvbjerg, H. (2015). Error filtering, pair assembly and error correction for next-generation sequencing reads. Bioinformatics, 31(21), 3476–3482. doi:10.1093/bioinformatics/btv401
Frey, B., Niklaus, P. A., Kremer, J., Lüscher, P., & Zimmermann, S. (2011). Heavy-machinery traffic impacts methane emissions as well as methanogen abundance and community structure in oxic forest soils. Applied and Environmental Microbiology, 77(17), 6060–6068. doi:10.1128/AEM.05206-11
Frey, B., Rime, T., Phillips, M., Stierli, B., Hajdas, I., Widmer, F., & Hartmann, M. (2016). Microbial diversity in European alpine permafrost and active layers. FEMS Microbial Ecology, 92(3), fiw018.
Frossard, A., Donhauser, J., Mestrot, A., Gygax, S., Bååth, E., & Frey, B. (2018). Long- and short-term effects of mercury pollution on the soil microbiome. Soil Biology and Biochemistry, 120, 191–199. doi:https://doi.org/10.1016/j.soilbio.2018.01.028
Geremia, C., Wallen, R., & White, P. J. (2017). Status report of the Yellowstone bison population, September 2017. Yellowstone National Park, Mammoth, WY, USA: National Park Service, Yellowstone Center for Resources.
Gobet, A., Quince, C., & Ramette, A. (2010). Multivariate cutoff level analysis (MultiCoLA) of large community data sets. Nucleic Acids Research, 38(15), e155–e155. doi:10.1093/nar/gkq545
Latter, P., & Howson, G. (1977). The use of cotton strips to indicate cellulose decomposition in the field. Pedobiologia, (17), 145–155.
Latter, P., & Walton, D. (1988). The cotton strip assay for cellulose decomposition studies in soil: history of the assay and development. In Cotton strip assay: an index for decomposition in soils (pp. 7–9). ITE Symposium, Institute of Terrestrial Ecology, Natural Environment Research Council, UK.
Lenth, R., & Love, J. (2018). lsmeans: least-squares means. R package version 2.27-62.
Martin, M. (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.Journal, 17(1), 10–12.
Meagher, M. M. (1973). The bison of Yellowstone National Park. NPS Scientific Monograph (Vol. 1). National Park Service, Yellowstone Center for Resources.
Melis, C., Selva, N., Teurlings, I., Skarpe, C., Linnell, J. D. C., & Andersen, R. (2007). Soil and vegetation nutrient response to bison carcasses in Białowieża Primeval Forest, Poland. Ecological Research, 22(5), 807–813. doi:10.1007/s11284-006-0321-4
Nikolenko, S. I., Korobeynikov, A. I., & Alekseyev, M. A. (2013). BayesHammer: Bayesian clustering for error correction in single-cell sequencing. BMC Genomics, 14(1), S7. doi:10.1186/1471-2164-14-S1-S7
Oksanen, J., Blanchet, F. G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., … Wagner, H. H. (2019). vegan: community ecology package. R package version 2.5-4.
Pinheiro, J., Bates, D., DebRoy, S., & Sarkar, D. (2018). nlme: Linear and nonlinear mixed effect models. R package version 3.1-131.1.
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., … Glöckner, F. O. (2013). The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research, 41(Database issue), D590–D596. doi:10.1093/nar/gks1219
Quimby, D. C., & Johnson, D. E. (1951). Weights and measurements of Rocky Mountain elk. Journal of Wildlife Management, 15, 57–62.
R Core Team. (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Zurich, Switzerland.
R Core Team. (2019). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
Rime, T., Hartmann, M., Brunner, I., Widmer, F., Zeyer, J., & Frey, B. (2015). Vertical distribution of the soil microbiota along a successional gradient in a glacier forefield. Molecular Ecology, 24(5), 1091–1108. doi:10.1111/mec.13051
Risch, A. C., Jurgensen, M. F., & Frank, D. A. (2007). Effects of grazing and soil micro-climate on decomposition rates in a spatio-temporally heterogeneous grassland. Plant and Soil, 298(1–2), 191–201. doi:10.1007/s11104-007-9354-x
Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., … Weber, C. F. (2009). Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology, 75(23), 7537–7541. doi:10.1128/AEM.01541-09
Smith, D., Stahler, D., Cassidy, K., Stahler, E., Metz, M., Cassidy, B., … Cato, E. (2018). Yellowstone National Park wolf project annual report 2017. Yellowstone National Park, Mammoth, WY, USA: National Park Service, Yellowstone Center of Resources.
Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007). Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology, 73(16), 5261–5267. doi:10.1128/AEM.00062-07
Withington, C., & Sanford Jr., R. (2007). Decomposition rates of buried substances increase with altitude in a forest-alpine tundra ecotone. Soil Biology and Biochemistry, (39), 68–75.
Please cite this paper together with the citation for the datafile.

en: Elk and bison carcasses in Yellowstone, USA

en: carcass soil-biodiversity wolf carrion decomposition yellowstone bacteria detritus fungi biogeochemical-cycling

format: XLS

bacteria

display_name: bacteria

biogeochemical-cycling

display_name: biogeochemical-cycling

carcass

display_name: carcass

carrion

display_name: carrion

decomposition

display_name: decomposition

detritus

display_name: detritus

fungi

display_name: fungi

soil-biodiversity

display_name: soil-biodiversity

wolf

display_name: wolf

yellowstone

display_name: yellowstone


en:
This dataset contains the data used  and collected to investigate the reliability of avalanche size estimates and avalanche outlines (see related publications). Namely this is
 Avalanche size estimates
* the 10 pictures depicting avalanches
* the survey results from the 170 participants
 Avalanche outlines mapped from oblique photographs
* the pictures of the six avalanches
* the avalanche outlines mapped by the 10 participants
* the reference mapped from the georeferenced photographs
 Avalanche outlines from remotely-sensed imagery
* the orthophotos in the four different resolutions (2m, 1m, 50cm, 25cm)
* the area of interest (AoI) delimiting the research area
* the avalanche mappings in each resolution for all five participants
* the shade masks used to separate illuminated and shaded areas
The acquisition of the orthophotos has been partially supported by the Swiss National Science Foundation (SNF; Grant N°200021_172800).

en: avalanche-size-estimation remote-sensing avalanche reliability avalanche-mapping

en: Data reliability study: avalanche size estimates and outlines

format: ZIP

avalanche

display_name: avalanche

avalanche-mapping

display_name: avalanche-mapping

avalanche-size-estimation

display_name: avalanche-size-estimation

reliability

display_name: reliability

remote-sensing

display_name: remote-sensing


en:
We developed a workflow to generate Large Scale Hazard Simulations for avalanches based on digital elevation models and information on the protective function of the forest. This datasets contains the potential avalanche release areas (PRA) as polygons, the simulation outputs (maximum pressure, maximum flow velocity and maximum flow height) as .tif rasters and the outlines of the simulated avalanches (polygon) for the entire area of the canton of Grisons (7105 km2). The simulations are performed for the scenarios wit return periods of 10, 30, 100 and 300 years, once with (FOR) and once without (NoFor) taking the effect of the forest into account.
The details can be found in this publication:
Bühler, Y., Bebi, P., Christen, M., Margreth, S., Stoffel, L., Stoffel, A., Marty, C., Schmucki, G., Caviezel, A., Kühne, R., Wohlwend, S., and Bartelt, P.: Automated avalanche hazard indication mapping on state wide scale, Nat. Hazards Earth Syst. Sci. Discuss., 2022, 1-22, 10.5194/nhess-2022-11, 2022.

en: modelling hazard-mapping avalanche release ramms impact-pressure

en: Large Scale Hazard Indication Simulations for avalanches, canton of Grisons

de:
Resource Title: Scenario 10 years without forest
    Size: 924911068 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/60fe952f-bdec-418b-9399-36bdb4ef2faf/download/10ynofor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 100 years with forest
    Size: 805376043 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/01d6b5be-6c29-4e2e-99da-f964c91de64f/download/100yfor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 10years with Forest
    Size: 661720583 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/d3574570-66a9-4c25-b196-727a7123dd7a/download/10yfor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 300 years with forest
    Size: 846835441 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/3d0bff73-c8e1-4f2e-9a38-f83b3a4b98ee/download/300yfor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 30 years without forest
    Size: 945391364 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/d332e2fd-d8b0-4d4b-9c3e-fefed822908a/download/30ynofor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 30 years with forest
    Size: 692742534 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/5986053e-b75f-484b-8adc-c3e19261adef/download/30yfor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Scenario 100 years without forest
    Size: 1020375084 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/d5c001b9-1321-4f3d-9f93-89b0c9479dd0/download/100ynofor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

de:
Resource Title: Extent of the canton of Grisons
    Size: 685814 bytes
    Format: application/json
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/70e9127c-8510-497c-a3f5-9637aa6d2b8e/download/extent_kt_gr.json
    Description:

format: JSON

media_type: application/json

de:
Resource Title: Scenario 300 years without forest
    Size: 1042271198 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/e6f8ad1b-8e7e-442e-a2f9-7c8cff814110/resource/953acbf3-3a6a-4df1-acf8-ef4108f5f0a9/download/300ynofor.7z
    Description: PRA_.shp = avalanche release areas shape file with the attributes in the attribute table
_maxHEIGHT.tif = maximum flow height [m]
_maxPRESSURE.tif = maximum impact pressure [kPa]
_maxVELOCITY.tif = maximum flow velocity [m/s]
_outlines = outline shape file of every avalanche simulation linked to the PRA shape file by ID

hazard-mapping

display_name: hazard-mapping

impact-pressure

display_name: impact-pressure

modelling

display_name: modelling

ramms

display_name: ramms

release

display_name: release


en:
Outlines of 6'041 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 16 January 2019. The dataset was acquired following a period with very high avalanche danger. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping16012019.pdf)
The generation of the data is described in:
Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.
The data was comprehensivly validated in a subset area in
Hafner, E.D.; Techel, F.; Leinss, S.; Bühler, Y., 2021: Mapping avalanches with satellites - evaluation of performance and completeness. Cryosphere, 15, 2: 983-1004. doi: 10.5194/tc-15-983-2021

en: natural-hazard hazard-mapping satellite snow avalanche

en: SPOT6 Avalanche outlines 16 January 2019

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow


en: Snow and air data was monitored at Gotschnagrat (LON: 46.859 LAT: 9.849) by an infrarot radiometer (Campbell SI-111) for snow temperature (°C), a snow height sensor (Lufft SHM-31) for snow height change (cm) and a temperature and humidity sensor (Campbell CS-215) for air temperature (°C) and relative humidity (%). No filter was applied to the sensors and the smapling frequency was 1 Hz.

en: Snow Drift Station - Snow and Air Data

en: snow snow-temperature raclets temperature snow-depth snow-height

de:
Resource Title: Air Temperature
    Size: 1049937 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c589c4cf-9f53-4d76-b1df-bae465ddda1f/resource/78d7e676-0f61-45a9-9dcf-67d0404e5382/download/air_temperature.xlsx
    Description: The air temperature (°C) was measured with a Campbell CS-215 which was mounted at a height of 2.2 m above ground. The time is given in UTC+1.

de:
Resource Title: Snow Surface Temperature
    Size: 1101244 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c589c4cf-9f53-4d76-b1df-bae465ddda1f/resource/7a1b830b-a1a2-42b8-8789-915904920f54/download/snow_surface_temperature.xlsx
    Description: The snow surface temperature (°C) was measured with a Campbell SI-111 at 0.7 m above ground. The time is given in UTC+1.

de:
Resource Title: Relative Humidity
    Size: 991506 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c589c4cf-9f53-4d76-b1df-bae465ddda1f/resource/64062bd7-0d09-4038-95cc-1028e196698e/download/air_relative_humidity.xlsx
    Description: The relative humidity (%) was measured with a Campbell CS-215 at a height of 2.2 m above ground. The time is given in UTC+1.

de:
Resource Title: Snow Depth
    Size: 830403 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/c589c4cf-9f53-4d76-b1df-bae465ddda1f/resource/50a2778f-14cd-4871-a9cc-67c1a4d1b31d/download/snow_depth.xlsx
    Description: The snow depth (cm) was measured with a Lufft SHM-31 which was mounted at 1.7 m above ground. The time is given in UTC+1.

raclets

display_name: raclets

snow-depth

display_name: snow-depth

snow-height

display_name: snow-height

snow-temperature

display_name: snow-temperature

temperature

display_name: temperature


en:
Validation points, validation area, ground truth coverage, SPOT 6 avalanche outlines, Sentinel-1 avalanche outlines, Sentinel-2 avalanche outlines, Davos avalanche mapping (DAvalMap) avalanche outlines as shapefiles and a detailed attribute description (DataDescription_EvalSatMappingMethods.pdf).
Coordinate system: CH1903+_LV95
The generation of this dataset is described in detail in:
Hafner, E. D., Techel, F., Leinss, S., and Bühler, Y.: Mapping avalanches with satellites – evaluation of performance and completeness, The Cryosphere, https://doi.org/10.5194/tc-2020-272, 2021.

en: avalanche-hazard-mapping validation satellite snow avalanche

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

de: EnviDat

en: Satellite avalanche mapping validation data

avalanche

display_name: avalanche

avalanche-hazard-mapping

display_name: avalanche-hazard-mapping

validation

display_name: validation


en:
This data set contains the produced snow depth maps as well as the reference data set (manual and snow pole measurements) from our paper "Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping".
Abstract. Snow depth has traditionally been estimated based on point measurements collected either manually or at automated weather stations. Point measurements, though, do not represent the high spatial variability of snow depths present in alpine terrain. Photogrammetric mapping techniques have progressed in recent years and are capable of accurately mapping snow depth in a spatially continuous manner, over larger areas, and at various spatial resolutions. However, the strengths and weaknesses associated with specific platforms and photogrammetric techniques, as well as the accuracy of the photogrammetric performance on snow surfaces have not yet been sufficiently investigated. Therefore, industry-standard photogrammetric platforms, including high-resolution satellites (Pléiades), airplane (Ultracam Eagle M3), Unmanned Aerial System (eBee+ with S.O.D.A. camera) and terrestrial (single lens reflex camera, Canon EOS 750D), were tested for snow depth mapping in the alpine Dischma valley (Switzerland) in spring 2018. Imagery was acquired with airborne and space-borne platforms over the entire valley, while Unmanned Aerial Systems (UAS) and terrestrial photogrammetric imagery was acquired over a subset of the valley. For independent validation of the photogrammetric products, snow depth was measured by probing, as well as using remote observations of fixed snow poles.
When comparing snow depth maps with manual and snow pole measurements the root mean square error (RMSE) values and the normalized median deviation (NMAD) values were 0.52 m and 0.47 m respectively for the satellite snow depth map, 0.17 m and 0.17 m for the airplane snow depth map, 0.16 m and 0.11 m for the UAS snow depth map. The area covered by the terrestrial snow depth map only intersected with 4 manual measurements and did not generate statistically relevant measurements. When using the UAS snow depth map as a reference surface, the RMSE and NMAD values were 0.44 m and 0.38 m for the satellite snow depth map, 0.12 m and 0.11 m for the airplane snow depth map, 0.21 and 0.19 m for the terrestrial snow depth map. When compared to the airplane dataset over a large part of the Dischma valley (40 km2), the snow depth map from the satellite yielded a RMSE value of 0.92 m and a NMAD value of 0.65 m. This study provides comparative measurements between photogrammetric platforms to evaluate their specific advantages and disadvantages for operational, spatially continuous snow depth mapping in alpine terrain over both small and large geographic areas.

en: airplane snow-depth snow-water-equivalent terrestrial uas photogrammetry satellite

en: Photogrammetric snow depth maps from satellite-, airplane-, UAS and terrestrial platforms from the Davos region (Switzerland)

envi

de: Umwelt

en: Environment

de:
Resource Title: Snow depth map terrestrial (Canon EOS 750D), Schürlialp, Davos, Switzerland
    Size: 141435530 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/78c3e0a0-c377-4421-86c4-550c38ebcd14/download/hs_ground_based_20180407_0_11.tif
    Description: Resolution 0.11 m
Coordinate system: LV95 LHN95

format: TIFF

media_type: image/tiff

de:
Resource Title: Manual and snow pole measurements, Schürlialp, Davos, Switzerland
    Size: 4150 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/1021ffa6-1311-45d3-a47d-61a0a18987cd/download/schneehohenzusammenfassung_fur_publikation.txt
    Description: This text file contains the average value for each manual snow depth measurements and the measured value of the snow pole measurements. The coordinates are in the horizontal Swiss coordinate system LV95. These values are used as reference measurement for comparison 1 as descriped in the paper.

format: TXT

media_type: text/plain

de:
Resource Title: Snow depth map satellite (Pléiades), Schürlialp, Davos, Switzerland
    Size: 2662248 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/d1d2303e-db33-4a7b-b517-452c7f68d3d6/download/hs_pleiades_2m_aligned_on_ebee.tif
    Description: Resolution: 2 m
Coordinate system: LV95 LHN95
© CNES 2018, Distribution Airbus DS

de:
Resource Title: Snow depth map UAS (eBee+), Schürlialp, Davos, Switzerland
    Size: 1063331206 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/bc0acce9-36df-4c77-a83a-2a959ff34b23/download/hs_20180407_schurlialp_ebee_0_09m.tif
    Description: Resolution: 0.9 m
Coordinate system: LV95 LHN95

de:
Resource Title: Snow depth map airplane (Ultracam Eagle M3), Schürilalp, Davos, Switzerland
    Size: 474100554 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/bb6310e8-dfa1-4dc7-b7a6-823cbaca24f8/download/hs_ultracam_20180411_0_11_ebee.tif
    Description: Resolution: 0.11 m
Coordinate system: LV95 LHN95

de:
Resource Title: Snow depth map airplane (Ultracam Eagle M3), Dischma valley, Davos, Switzerland
    Size: 455957254 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/94e7debd-7500-444e-8727-56e18a3aa583/download/hs_ultracam_lhn95_als_0_5m.tif
    Description: Resolution: 0.5 m
Coordinate system: LV95 LHN95

de:
Resource Title: Snow depth map satellite (Pléiades), Dischma valley, Davos, Switzerland
    Size: 48454014 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/a41c5b83-a803-4527-b6f9-4d365ef84228/resource/e33b05cc-077b-4ad8-8449-095d4c6d2761/download/hs_pleiades_lh95_2m_on_al.tif
    Description: Resolution: 2 m
Coordinate system: LV95 LHN95
© CNES 2018, Distribution Airbus DS

airplane

display_name: airplane

photogrammetry

display_name: photogrammetry

snow-water-equivalent

display_name: snow-water-equivalent

terrestrial

display_name: terrestrial

uas

display_name: uas


en:
This data set contains roughly 5600 photographs of plants and plant parts from 153 sites recorded in all major biogeographic regions of Switzerland using smartphone cameras. Image names contain a letter referring to depicted plant parts: b = bark, i = inflorescence, f = infructescense, s = several parts, v = vegetative parts.
Photos are grouped in folders by observation (individual or population), i.e., photos in the same folder are of the same species, observed at the same time and sampling plot. At a higher organisational level, these folders are grouped by sampling plot (usually 3×3 m in open areas and 10×10 m in forests). The main folder contains metadata including taxon name, sampling time and location, as well as the TypoCH habitat type encoded as integers.
This data set accompanies the following publication:
Popp, M. R., Zimmermann, N. E. & Brun, P. Evaluating the use of automated plant identification tools in biodiversity monitoring—a case study in Switzerland. _Ecological Informatics_ **103316** (2025) doi:[10.1016/j.ecoinf.2025.103316](https://doi.org/10.1016/j.ecoinf.2025.103316).

en: testing vascular-plants plant-species photo species-observations

en: Photos of vegetative and reproductive parts of 560 vascular plant species taken in all biogeographic regions of Switzerland

photo

display_name: photo

plant-species

display_name: plant-species

species-observations

display_name: species-observations

testing

display_name: testing

vascular-plants

display_name: vascular-plants


en: “Flavescence dorée” (FD) is a quarantine grapevine disease associated with FD phytoplasmas (FDp). In Switzerland, FD was identified in 2004 in the southernmost part of Canton Ticino (TI) and then rapidly propagated throughout the entire regional winegrowing area despite the mandatory control measures. The reported widespread distribution of gone-wild grapevines (GWGV) in TI raised the hypothesis of a potential role of GWGV as an FDp reservoir and as a habitat for FDp vectors. To test this assumption, GWGV and FDp vectors were sampled in 13 plots to attest their infection status and compare the FDp genetic profiles. The primary (Scaphoideus titanus) and best-candidate alternative (Orientus ishidae) vectors were collected throughout the season and were found in moderate to high abundance in all the study area. The infection rate of both GWGV and S. titanus followed the historical gradient of S. titanus arrival and dispersal in TI with a clear geographic distinction between the southern and northern part of TI. Interestingly, the rate measured for S. titanus was similar to that observed in highly FD-infested cultivated vineyards. Moreover, the genetic profiles of the infected GWGV and S. titanus samples were identical to those commonly observed in cultivated vineyards (map M54). Importantly, four specimens of O. ishidae were also found harboring the same genotype. This study emphasizes the importance of GWGV (and abandoned vineyards) and alternative vectors for the FD epidemics in FD-infested regions, as well as a potential origin for FD outbreaks in areas currently designated as FDp-free.

en: genotyping orientus-ishidae switzerland scaphoideus-titanus grapevine-yellows southern-switzerland flavescence-doree

en: Gone-wild grapevines in forests host phytoplasma genotypes linked to grapevines Flavescence doree epidemics in cultivated vineyards and competent vectors

de:
Resource Title: Fig1.tif
    Size: 9840462 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/7f549751-89fa-4ec7-bff2-2ebe6dbb752c/download/fig1.tif
    Description: Location of the experimental plots in Canton Ticino
(a) Location of the study area within Switzerland; T = Ticino
(b) Black dots: plots hosting GWGVs monitored for the presence of FDp-infected insect and plant samples.
Sopra = Sopraceneri (Ticino); Sotto = Sottoceneri (Ticino). Grey areas = cultivated vineyard area.

de:
Resource Title: Online_Resource_1.docx
    Size: 28482 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/5cb014fc-23e8-48dc-a60d-fdadd4630c78/download/online_resource_1.docx
    Description: Phytoplasma sequences from this work and reference strains with their GenBank accession number, hosts, geographic origin and reference.

de:
Resource Title: Table_1.docx
    Size: 20794 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/82445fda-75b9-490c-a8e8-a71958f2e3db/download/table_1.docx
    Description: Plot characteristics in terms of coordinates, region, mean slope, closest distance from nearest cultivated vineyard (DV), distance range between yellow sticky trap and nearest forest edge (DF), last time registered as cultivated vineyard (Last_T); absolute captures (N) and mean captures per hundred leaves (mean/100 leaves ± SE) during nymph collection for Scaphoideus titanus and Orientus ishidae, absolute captures (N) and mean captures per single yellow sticky trap (mean/trap ± SE).

de:
Resource Title: Table_3.docx
    Size: 15404 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/cfc1e011-612e-48ce-99ee-73427264ab12/download/table_3.docx
    Description: Results of molecular analysis for the detection of Flavescence dorée phytoplasma in symptomatic and asymptomatic leaf samples collected from gone-wild grapevines; number of analyzed and infected leaf samples, and map genotype (conducted on all FDp-infected samples).

de:
Resource Title: Table_2.docx
    Size: 16961 bytes
    Format: application/vnd.openxmlformats-officedocument.wordprocessingml.document
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/bade5ec3-6d04-4fcb-a35f-dccec84dd114/download/table_2.docx
    Description: Molecular characterization of the Flavescence dorée phytoplasma detected in Scaphoideus titanus and Orientus ishidae specimens collected on gone-wild grapevines; number of analyzed and infected insect specimens and genotype profile for the map, vmpA and malG genes.

de:
Resource Title: Fig3.jpg
    Size: 3981322 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/8649c388-56cc-44eb-8ae5-10c43a41fecf/download/fig3.jpg
    Description: Phylogenetic tree of the map (a; partial) and vmpA (b) genes sequences from Scaphoideus titanus, Orientus ishidae and gone-wild grapevines obtained in this work and reference strains from Genbank (see Online Resource 1). Maximum likelihood phylogeny based on nucleotide sequences of (A) map (543 bp) and (B) vmpA (465 bp) genes. The numbers on branches indicate the level of bootstrap support (500 replicates). Support values above 70% are labeled. The scale bar shows the number of substitutions per site.

de:
Resource Title: Fig2a.tif
    Size: 27909824 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/cec4b2d9-9530-44c4-9306-d594edae3fbc/resource/8ef34548-f561-4866-91d4-d9eb418f0fe1/download/fig2a.tif
    Description: Flavescence dorée detection on the analyzed insect (a) and gone-wild grapevine (b) samples
(a)	Circles: location with insect vectors tested for Flavescence dorée phytoplasma; horizontal bar: S. titanus FDp-infected with map-genotype M54; diagonal line top right to bottom left; O. ishidae FDp-infected with map-genotype M54; diagonal line top left to bottom right: O. ishidae FDp-infected with map-genotype M50
(b)	Circles: Gone-wild grapevines (GWGV) tested for FDp; vertical bar: symptomatic and FDp-infected samples; horizontal bar: asymptomatic and FDp-infected samples. Sopra = Sopraceneri (Ticino); Sotto = Sottoceneri (Ticino). Grey areas = cultivated vineyard area.

flavescence-doree

display_name: flavescence-doree

genotyping

display_name: genotyping

grapevine-yellows

display_name: grapevine-yellows

orientus-ishidae

display_name: orientus-ishidae

scaphoideus-titanus

display_name: scaphoideus-titanus

southern-switzerland

display_name: southern-switzerland

switzerland

display_name: switzerland


en: Earth’s snow cover is very dynamic on diurnal time scales. The changes to the snow structure during this metamorphism have wide ranging impacts such as on avalanche formation and on the capacity of surface snow to exchange trace gases with the atmosphere. Here, we investigate the influence of dry metamorphism, which involves fluxes of water vapor, on the chemical reactivity of bromide in the snow. For this, the heterogeneous reactive loss of ozone at a concentration of 5-6E12 molecules cm-3 is investigated in artificial, shock-frozen snow samples doped with 6.2 uM sodium bromide and with varying metamorphism history. The oxidation of bromide in snow is one reaction initiating polar bromine releases and ozone depletions.

en: solution brine chemistry interface ozone alpine heterogeneous snow laboratory-study arctic antarctica metamorphism reaction

envidat

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

de: EnviDat: das Umwelt-Datenportal

en: Data set on bromide oxidation by ozone in snow during metamorphism from laboratory study

de:
Resource Title: Matlab Data
    Size: 1008529 bytes
    Format: application/x-matlab
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/2cbff0e6-bf62-4476-a533-10cb745520ed/download/edebeli_acp_2020__data.mat
    Description: All data as Matlab mat file

de:
Resource Title: Matlab Script to view and plot data
    Size: 9299 bytes
    Format: application/vnd.wolfram.mathematica.package
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/b718b5db-b15c-4f88-95a9-ce649b79308a/download/edebeli_acp_2019__snowbrmet.m
    Description:

de:
Resource Title: Readme file
    Size: 503143 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/b6633dad-a0a5-497e-b393-d7c6ee018c0a/resource/d41fa166-35e9-430f-b96d-a5862556d9cd/download/edebeli_acp_2019__snowbrmet.pdf
    Description: This file shows data, code, and plots.

format: PDF

media_type: application/pdf

alpine

display_name: alpine

antarctica

display_name: antarctica

arctic

display_name: arctic

brine

display_name: brine

chemistry

display_name: chemistry

heterogeneous

display_name: heterogeneous

interface

display_name: interface

laboratory-study

display_name: laboratory-study

metamorphism

display_name: metamorphism

ozone

display_name: ozone

reaction

display_name: reaction

snow

display_name: snow

solution

display_name: solution


hymenoptera

en:
Hymenopteran data from all historic up to the recent projects (29.10.2019) of WSL, collected with various standardized methods in landscapes of different types.
Data are provided on request to contact person against bilateral agreement.

en: urban arthropoda agricultural hymenoptera hautfluger forests

de: EnviDat

en: Hymenoptera

title_for_slug: hymenoptera

envi

de: Umwelt

agricultural

display_name: agricultural

arthropoda

display_name: arthropoda

forests

display_name: forests

hautfluger

display_name: hautfluger

hymenoptera

display_name: hymenoptera

urban

display_name: urban


en:
Important note: From 2025 the NEAD format is being transformed into the interoperable CSV (iCSV) format, a formalized and standardized evolution of the NEAD format. Furthermore, iCSV should be backwards compatible with NEAD. More information on the new iCSV format will be linked here in due time.
Acknowledgement: The NEAD format includes NetCDF metadata and is proudly inspired by both SMET and NetCDF formats. NEAD is designed as a long-term data preservation and exchange format.
The NEAD specifications were presented at the "WMO Data Conference 2020 - Earth System Data Exchange in the 21st Century" (Virtual Conference).
-----------------------
Summary:
The Non-Binary Environmental Data Archive (NEAD) format is being developed as a generic and intuitive format that combines the self-documenting features of NetCDF with human readable and writeable features of CSV. It is designed for exchange and preservation of time series data in environmental data repositories.
License: The NEAD specifications are released to the public domain under a Creative Commons CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

en: meteorological-data-format csv nead metadata-convention research-data-management

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

en: Non-Binary Environmental Archive Data (NEAD) format

de:
Resource Title: NEAD on GitHub
    Size: 1024 bytes
    Format: No Info
    URL: https://github.com/GEUS-PROMICE/NEAD
    Description:

de:
Resource Title: NEAD syntax v0.1 (EBNF)
    Size: 3383 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/d51285c9-953d-42e5-a925-20209cde10e5/resource/bf21243d-cdb9-47a8-a15b-d42efaef5d82/download/ebnf.txt
    Description:

de:
Resource Title: PyNEAD (future reference implementation)
    Size: 1024 bytes
    Format: No Info
    URL: https://github.com/GEUS-PROMICE/pyNEAD
    Description:

de:
Resource Title: MeteoIO (future reference implementation)
    Size: 1024 bytes
    Format: text/html
    URL: https://www.slf.ch/en/services-and-products/meteoio.html
    Description:

format: HTML

media_type: text/html

csv

display_name: csv

metadata-convention

display_name: metadata-convention

meteorological-data-format

display_name: meteorological-data-format

nead

display_name: nead

research-data-management

display_name: research-data-management


en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present downscaled climate data for the CORDEX EUR11 domain at a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperature lapse rates. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height. The resulting data consist of a daily temperature and precipitation timeseries.
The data is distributed under a: Creative Commons: Attribution 4.0 International (CC BY 4.0) license.

en: minimum-temperature europe air-temperature eur11 precipitation maximum-temperature cordex daily-climate

en: High resolution climate data for Europe

envi

en: Environment

de:
Resource Title: CHELSA_EUR11 technical documentation
    Size: 713475 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/9e2c4a69-443d-4eb1-b8ab-697fd50bc7d2/resource/bc1df26a-0b8f-4547-872d-f00ed45db554/download/chelsa_eur11_technical_documentation.pdf
    Description: Technical documentation of the data with variable names and methodology.

de:
Resource Title: Data Access
    Size: 2199023255552 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav2&prefix=EUR11%2F
    Description:

air-temperature

display_name: air-temperature

cordex

display_name: cordex

daily-climate

display_name: daily-climate

europe

display_name: europe

maximum-temperature

display_name: maximum-temperature

minimum-temperature

display_name: minimum-temperature

precipitation

display_name: precipitation


en: This dataset contains four years of daily measurements of the natural isotopic composition (2H, 18O) of precipitation and stream water at the Alp catchment (area 47 km2) in Central Switzerland and two of its tributaries (0.73 km2 and 1.55 km2). In addition, the dataset contains daily measurements of key hydrometeorological variables.

en: alptal stream-water hydrology catchment stable-water-isotope precipitation

en: Four years of daily stable water isotope data in stream water and precipitation from three Swiss catchments

de:
Resource Title: Data Set Documentation: alptal_Isotopes_daily_2015-2019_v2
    Size: 158372 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/6a2fefc6-ce6d-4eb7-9ea9-c37b64959437/resource/d26ca42e-4cdb-4ef8-bf35-a87d5239757d/download/data-set-documentation_sdata-21-00930.pdf
    Description: Documentations contains meta data of the data columns and information about the study catchments.

de:
Resource Title: Alptal_Isotopes_daily_2015-2019_v2.txt
    Size: 760332 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/6a2fefc6-ce6d-4eb7-9ea9-c37b64959437/resource/7865517d-357b-4e08-8b6a-b405eca4e547/download/alptal_isotopes_daily_2015-2019_v2.txt
    Description: Version 2 of the dataset contains additional information on:
- line-conditioned (lc) excess
- precipitation sample volumes
- isotope data quality

de:
Resource Title: Alptal_Isotopes_daily_2015-2019
    Size: 717293 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/6a2fefc6-ce6d-4eb7-9ea9-c37b64959437/resource/8a06beab-3092-45d3-ad41-a59d79e6cb71/download/alptal_isotopes_daily_2015-2019.txt
    Description: Single comma-separated txt-file with daily data of stable water isotopes measured in streamwater and precipitation in the Swiss Alptal catchment and two of its tributaries (Erlenbach and Vogelbach), as well as daily data of key hydrometeorological variables from the Alptal valley

alptal

display_name: alptal

catchment

display_name: catchment

hydrology

display_name: hydrology

stable-water-isotope

display_name: stable-water-isotope

stream-water

display_name: stream-water


en:
Angle of repose experiments were performed with different snow types at temperatures between -2 and -40°C. They were used to  examine granular snow dynamics on the grain-scale with focus on the role of grain shape and cohesion. The angle of repose was observed by sieving snow onto a round, freestanding base until a stationary heap was formed.
This dataset consists of  1) the images of the experimental heaps that were taken to determine the angle of repose, 2) one binary 3D micro computed tomography image of each snow type. The CT images were taken with the SLF micro-CT40 to characterize snow properties and grain shape.
The experiments with natural snow types (rounded and faceted grains) and spherical model snow allowed for an examination of the differences in granular properties between natural grain shapes and spherical particles in view of Discrete Element Modelling. With the chosen temperatures, the effect of sintering could be observed that increases the angle of repose with increasing temperature.

en: granular-snow grain-shape fast-sintering angle-of-repose discrete-element-modelling

en: Angle of repose experiments with natural and spherical snow

de:
Resource Title: README.txt
    Size: 1024 bytes
    Format: text/plain
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.149/2020_aor_paper_willibald_jog/readme.txt
    Description:

de:
Resource Title: Angle of repose and 3D CT images
    Size: 4831838208 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.149/2020_aor_paper_willibald_jog
    Description: 5 Snow types were examined and glass beads as a cohesion-less reference, named as follows:

RG: rounded grains (sieved with 0.7 - 1.4 mm)

FC: faceted grains (1.4 - 2 mm)

FCS: small faceted grains (0.7 - 1.4 mm)

IB: ice beads (4 mm)

IBS: small ice beads (2 - 2.2 mm)

GB: glass beads(2 mm)

angle-of-repose

display_name: angle-of-repose

discrete-element-modelling

display_name: discrete-element-modelling

fast-sintering

display_name: fast-sintering

grain-shape

display_name: grain-shape

granular-snow

display_name: granular-snow


en:
This data set includes material and results described in the related research article:
Bergfeld, B., van Herwijnen, A., Reuter, B., Bobillier, G., Dual, J., and Schweizer, J.: Dynamic crack propagation in weak snowpack layers: Insights from high-resolution, high-speed photography, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2020-360, in review, 2021.
 Context:
In order to study crack propagation in weak snowpack layers in great detail, we recorded Propagation Saw Test (PST) experiments using a high-speed camera and applied digital image correlation (DIC) to derive displacement and strain fields in the slab, weak layer, and substrate. We demonstrated the versatility and accuracy of the DIC method by showing measurements from three PST experiments, resulting in slab fracture, crack arrest and full propagation in the related publication.
 Content:
- Supplementary material for related publication
- Ilustrative videos showing crack propagation
- High-speed recordings of the Experiments
(the raw .cine files are available upon request)
Processed Data containing:
   - displacement, velocity and acceleration fields for the three PSTs
   - speed and touchdown dataset

en: snow-avalanche snow-mechanics experiment crack-propagation snow

envidat

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

de: EnviDat: das Umwelt-Datenportal

en: Dataset for "Dynamic crack propagation in weak snowpack layers: Insights from high-resolution, high-speed photography"

de:
Resource Title: Crack speed and Touchdown distance data
    Size: 1818413 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/be3f7643-88ab-456c-9554-aa068ac76bb7/resource/4d88c59e-44a7-4c9f-84b8-ffd6f499f05f/download/speeds_and_touchdown_datasets.zip
    Description: Data is stored as netcdf files as python/xarray Datasets.
Datasets are self-explaining and contain the necessary information and metadata.
Information on how to load the netCDF files (datasets) can be found at "http://xarray.pydata.org/en/stable/"

media_type: application/zip

de:
Resource Title: Supplementary material
    Size: 299124 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/be3f7643-88ab-456c-9554-aa068ac76bb7/resource/89d474b4-0965-4b96-ac8e-ff80e5aa0bd5/download/2020_bergfeld_crack_propagation_dynamics-supplement.pdf
    Description: # Supplementary material to the publication Bergfeld et al 2021
- description of the reverse crack
- additional snowpack parameters derived from the SMP measurements

de:
Resource Title: Videos
    Size: 17687958 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/be3f7643-88ab-456c-9554-aa068ac76bb7/resource/a2beba55-6766-4666-b03a-24673b2d1f8e/download/reduced_raw_videos.zip
    Description: The videos are .mp4 exports of the raw files (reduced 50 times in time)

de:
Resource Title: DIC Data
    Size: 28991029248 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=doi/envidat.231/bergfeld_et_al_2021/
    Description: Data contains the displacement, strain, velocity and acceleration fields measured during the crack propagation process in our three example Propagation Saw Tests (PSTs). Data is stored as netcdf files as python/xarray Datasets. Datasets are self-explaining and contain the necessary metadata (field notes on the PSTs, camera settings, Digital Image Corrrelation parameters, preprocessing parameters).

Information on how to load the netCDF files (datasets) can be found at "http://xarray.pydata.org/en/stable/"

de:
Resource Title: Videos of crack propagation
    Size: 421948545 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/be3f7643-88ab-456c-9554-aa068ac76bb7/resource/08523c06-7691-4a95-ac18-9782e3fc0306/download/cracking_videos.zip
    Description: The videos show the cracking process in three example Propagation Saw Tests (flat field). The upper panel shows strain on top of the recorded movie frames. The second row shows vertical (*w*, blue line) and horizontal (*u*, orange line) displacement fields. The third and fourth row show the first and second time derivatives, namely the velocity and acceleration field.

crack-propagation

display_name: crack-propagation

experiment

display_name: experiment

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-mechanics

display_name: snow-mechanics


en:
This dataset contains data and scripts for "CRYOWRF - a validation and the effect of blowing snow on the Antarctic SMB" (Gerber et al., submitted).
* Simulation_setup: Namelists and input information to run the simulation. Some input files need to be downloaded from Sharma et a., 2021.
* Static_input: Static topography input file of WRF (geo_em.d01).
* WRF_27km_NoahMP: Preprocessed WRF output of the simulation run with the WRF using the surface parameterization Noah-MP to reproduce the figures and results in the paper.
* WRF_27km_CRYOWRF: Preprocessed WRF output of the simulation run with CRYOWRF to reproduce the figures and results in the paper.
* Scripts_Reproducibility: Python scripts to reproduce the figures and results in the paper.
Note:
* To run some of the scripts Atmospheric Weather station data needs to be prepared using Gerber and Lehning, 2022.
* AWS data is not provided and needs to be downloaded from the corresponding databases. Please make sure to comply with the respective terms and conditions.

en: blowing-snow cryowrf surface-mass-balance reproducibility antarctica

de: EnviDat

en: Reproducibility dataset for CRYOWRF validation

envi

de: Umwelt

de:
Resource Title: Scripts_Reproducibility_v2
    Size: 3051205 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/d05a9210-b303-45cc-8f2d-f4292951df2e/download/scripts_reproducibility_v2.zip
    Description: Python scripts to reproduces figures in Gerber et al., 2022, revised

de:
Resource Title: WRF_27km_NoahMP
    Size: 6657199309 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.347/WRF_27km_NoahMP.zip
    Description: Processed WRF output (run with Noah-MP land surface model) used for the analysis and the figures in the paper.

de:
Resource Title: Static_input
    Size: 5034051 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/aa57ffee-2ec1-4561-8673-cf3d03cedeaf/download/static_input.zip
    Description: Static input data from the WRF simulations (used in the python scripts in Scripts_Reproducibility).

de:
Resource Title: Scripts_Reproducibility_v1
    Size: 3227134 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/65815232-fd6a-4d1d-a280-a1ebc1c30375/download/scripts_reproducibility.zip
    Description: Python scripts to reproduces figures in Gerber et al., 2022, submitted.

de:
Resource Title: WRF_27km_CRYOWRF
    Size: 28991029248 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.347/WRF_27km_CRYOWRF.zip
    Description: Processed CRYOWRF output used for the analysis and the figures in the paper.

de:
Resource Title: Simulation_setup
    Size: 10669 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/73ebfcbc-bd0b-4d56-b162-2e86de009d1c/resource/79646165-0b4f-4495-b06a-dcd52d403019/download/simulation_setup.zip
    Description: Namelist and input files and information to run the WRF and CRYOWRF simulations used in the paper.

antarctica

display_name: antarctica

blowing-snow

display_name: blowing-snow

cryowrf

display_name: cryowrf

reproducibility

display_name: reproducibility

surface-mass-balance

display_name: surface-mass-balance


en:
Data accompanying David Wagners' Dissertation.
Covers model results and various input from ALPINE3D and SNOWPACK adjusted for sea ice during MOSAiC.

en: snow-distribution drifting-and-blowing-snow surface-mass-balance arctic-sea-ice spatial-variability

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

en: MOSAIC Snow on Sea Ice Data

de:
Resource Title: SNOWPACK setup for MOSAiC
    Size: 2386070 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.381/snowpack_jgr.zip
    Description:  The zip file contains both input and output data as well as the model configuration as used in the submitted manuscript "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

The zip file contains 2 main folders:
* SNOWPACK_JGR_ALPHA1
* SNOWPACK_JGR_ALPHA3

In the SNOWPACK_JGR_ALPHA1 (reference "SP_R" simulation) and SNOWPACK_JGR_ALPHA3 (comparison "SP_C" scenario) folders you find the corresponding inputs, outputs and configuration as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each SNOWPACK_JGR_ALPHA/setup/io.ini file. The input data is already linked accordingly in each io.ini file.

To reproduce the results, download and compile the source code for the adjusted SNOWPACK model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/snowpack.git under the "snowpack_mosaic" branch. After installing, you can run the provided model setup uploaded here.

de:
Resource Title: ALPINE3D setup for MOSAiC
    Size: 9663676416 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.381/a3d_jgr.zip
    Description: The zip file contains a folder structure that must be kept as it is in order to run the simulation in the current configuration.
The setup contains both input and output data as well as the model configuration as used in the submitted manuscript
"Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".

The zip file contains 3 main folders:
* base_setup_files
* a3d_jgr_alpha1
* a3d_jgr_alpha3

The "base_setup_files" contains all input files that are necessary to run the reference (R) simulation ("a3d_jgr_alpha1" folder) and the comparison "C" scenario ("a3d_jgr_alpha3") folder. In the a3d_jgr_alpha1 and a3d_jgr_alpha3 folders you find the corresponding outputs as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each a3d_jgr_alphax/setup/io.ini file. The input data is already linked accordingly in each io.ini file.

a3d_jgr_alpha1 also contains the detailed snow profiles for each point along the transects.

To reproduce the results, download and compile the source code for the adjusted ALPINE3D model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/alpine3d.git under the "alpine3d_mosaic" branch. After installing, you can run the provided model setup uploaded here.

arctic-sea-ice

display_name: arctic-sea-ice

drifting-and-blowing-snow

display_name: drifting-and-blowing-snow

snow-distribution

display_name: snow-distribution

spatial-variability

display_name: spatial-variability


en:
This dataset provides a Swiss-wide mosaic of night-time lights, derived from SDGSAT-1 GLI satellite imagery. The mosaic contains median radiance values based on observations from winter 2023/24. Poor-quality images (due to factors such as clouds, inconsistent geometric accuracy or excessive noise) have been manually excluded.
The potential of SDGSAT-1 night-time lights data for ecological applications is discussed in Weber et al. ([2025](https://doi.org/10.1002/rse2.70011)).
**Two mosaic types are available**
-PAN Radiance (10 m resolution) with three bands: Panchromatic Low (PL), Panchromatic High (PH), and High Dynamic Range (HDR)
-RGB Radiance (40 m resolution) with three bands: Red, Green, and Blue
**Additional layers for PAN/RGB include**
-Number of observations per pixel (OBS)
-Standard deviation of radiance values per pixel (SD)
**Additional information**
-Radiance values were calculate based on the calibration values (gain, bias) V3.0
-Radiance values were converted to nW/cm^2/sr
-Of the three panchromatic bands, HDR is recommended for use as it is the weighted average of 50% of the PL and PH data.
-Access and more information about SDGSAT-1 data: [sdgsat.ac.cn](https://www.sdgsat.ac.cn)
**Attribution**
This dataset is based on SDGSAT-1 imagery provided by the International Research Center of Big Data for Sustainable Development Goals (CBAS). It is acknowledged that the SDGSAT-1 data are kindly provided by CBAS for non-commercial use.
For questions or collaboration, contact: dominique.weber@wsl.ch

en: remote-sensing alan sdgsat-1 conservation ecology light-pollution

envidat

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

en: SDGSAT-1 Night-Time Lights Mosaic for Switzerland

envi

en: Environment

de:
Resource Title: SDGSAT-1 RGB SD
    Size: 49250595 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/ba3f98b9-2a9d-49b4-aa44-17549fa73d5d/download/sdgsat1_gli_2023-2024_rgb_sd.tif
    Description: Standard deviation (SD) of all radiance values which were used to generate the RGB mosaic.

- GeoTIFF, 40 m resolution, EPSG:2056
- Band 1: SD of RED, Band 2: SD of GREEN, Band 3: SD of BLUE

de:
Resource Title: SDGSAT-1 PAN Radiance
    Size: 260859708 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/9c85891b-eac8-46b3-91d9-c0abf10ac640/download/sdgsat1_gli_2023-2024_pan_median_radiance.tif
    Description: Swiss-wide panchromatic night-time lights mosaic showing median radiance values from SDGSAT-1 GLI observations in winter 2023/2024.

- GeoTIFF, 10 m resolution, EPSG:2056
- Band 1: PL, Band 2: PH, Band 3: HDR

de:
Resource Title: SDGSAT-1 RGB Radiance
    Size: 26283647 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/b93e8d1e-8f29-40b9-a120-e363f9617bb7/download/sdgsat1_gli_2023-2024_rgb_median_radiance.tif
    Description: Swiss-wide RGB night-time lights mosaic showing median radiance values from SDGSAT-1 GLI observations in winter 2023/2024.

- GeoTIFF, 40 m resolution, EPSG:2056
- Band 1: RED, Band 2: GREEN, Band 3: BLUE

de:
Resource Title: SDGSAT-1 PAN SD
    Size: 728641887 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/72b94910-5a08-4d43-8023-8c8ddcaf8168/download/sdgsat1_gli_2023-2024_pan_sd.tif
    Description: Standard deviation (SD) of all radiance values which were used to generate the panchromatic mosaic.

- GeoTIFF, 10 m resolution, EPSG:2056
- Band 1: SD for PL, Band 2: SD for PH, Band 3: SD for HDR

de:
Resource Title: SDGSAT-1 PAN OBS
    Size: 33168454 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/8849653f-4efb-4f50-bb15-05542f229615/download/sdgsat1_gli_2023-2024_pan_nbr_obs.tif
    Description: Number of observations (OBS) which were used to generate the panchromatic mosaic.

- GeoTIFF, 10 m resolution, EPSG:2056
- OBS with identical values for each band

de:
Resource Title: SDGSAT-1 RGB OBS
    Size: 3384417 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/2782cc68-abae-40ef-82be-91c9167292cb/resource/96befb49-9ab3-419f-abc9-694ecd0c1257/download/sdgsat1_gli_2023-2024_rgb_nbr_obs.tif
    Description: Number of observations (OBS) which were used to generate the RGB mosaic.

- GeoTIFF, 40 m resolution, EPSG:2056
- OBS with identical values for each band

alan

display_name: alan

conservation

display_name: conservation

ecology

display_name: ecology

light-pollution

display_name: light-pollution

remote-sensing

display_name: remote-sensing


en:
This dataset contains datasets of sub-canopy meteorological variables acquired in coniferous forest stands in Switzerland (Davos, Engadine) and Finland (Sodankylä) during the winters 2018 and 2019. The data are presented and used in the publication:
Mazzotti, G., Essery, R., Webster, C., Malle, J.,  & Jonas T. (2020)
Process-level evaluation of a high-resolution forest snow model using observations from mobile multi-sensor platforms
Water Resources Research, under review
The above publication must be cited when using this dataset, and the user is referred to the publication for additional detail.
Data are grouped into 4 folders:
1) Point data includes wind speed data measured with stationary meteorological stations
2) Transect data includes data of incoming short- and longwave radiation, air and snow surface temperature acquired with an automated calblecar system along within-stand transects
3) Grid data includes data of incoming short- and longwave radiation, air and snow surface temperature acquired on 40x40m gridded plots using a handheld instrument, as well as snow depth data measured at the same grids.
Canopy structure information derived from hemispherical images is included for each all surveyed locations as well, and an overview of the field sites is provided.

en: snow-models forest-structure meteorological-data forest-snow snow-energy-balance

envidat

de: EnviDat: das Umwelt-Datenportal

de: EnviDat

en: Distributed sub-canopy datasets from mobile multi-sensor platforms (CH / FIN, 2018-2019) for hyper-resolution forest snow model evaluation

de:
Resource Title: Point data
    Size: 195016 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0fb10027-6f49-4953-8683-76fc83ea1154/resource/05210541-6b04-487b-bf39-8817d31d5106/download/point_data.zip
    Description: Wind speed data acquired with the portable meteorological stations

de:
Resource Title: Grid data
    Size: 11193263 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0fb10027-6f49-4953-8683-76fc83ea1154/resource/a5d954ef-a693-4e43-8e66-75ed21178a92/download/grid_data.zip
    Description: Canopy structure and snow depth data at the grids

de:
Resource Title: Transect data
    Size: 1360922505 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0fb10027-6f49-4953-8683-76fc83ea1154/resource/f2dc7eef-dc3c-46f5-99ca-9c12ac154175/download/transect_data.zip
    Description: All meteorological and canopy structure data acquired at cable car transects

de:
Resource Title: Site overview
    Size: 203756 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/0fb10027-6f49-4953-8683-76fc83ea1154/resource/b6151bb0-2568-4ae8-b91a-7e2d572e01b9/download/field_sites_overview.jpg
    Description: Overview of field sites

forest-snow

display_name: forest-snow

forest-structure

display_name: forest-structure

meteorological-data

display_name: meteorological-data

snow-energy-balance

display_name: snow-energy-balance

snow-models

display_name: snow-models


en:
This dataset contains all data, on which the following publication below is based.
**Paper Citation**:
Neff, F., Korner-Nievergelt, F., Rey, E., Albrecht, M., Bollmann, K., Cahenzli, F., Chittaro, Y., Gossner, M. M., Martínez-Núñez, C., Meier, E. S., Monnerat, C., Moretti, M., Roth, T., Herzog, F., Knop, E. 2022. Different roles of concurring climate and regional land-use changes in past 40 years' insect trends. Nature Communications, DOI: [10.1038/s41467-022-35223-3](https://doi.org/10.1038/s41467-022-35223-3)
Please cite this paper together with the citation for the datafile. Please also refer to this publication for details on the methods.
 Summary
Mean annual occupancy estimates for 390 insect species (215 butterflies [Papilionoidea, incl. Zygaenidae moths], 103 grasshoppers [Orthoptera], 72 dragonflies [Odonata]) for nine bioclimatic zones in Switzerland. Covers the years 1970-2020 (for butterflies) and 1980-2020 (for grasshoppers and dragonflies). Mean occupancy denotes the average number of 1 km x 1 km squares in a zone occupied by the focal species. Occupancy estimates stem from occupancy-detection models run with species records data hosted and curated by [info fauna](http://www.infofauna.ch). Data on the level of single MCMC iterations of model fitting are included (4000 sampling iterations). The nine bioclimatic zones were defined based on biogeographic regions and two elevation classes (square above or below 1000 m. asl)

en: elevation infospecies occupancy-models insects switzerland butterflies insect-decline biogeographical-region

en: Mean insect occupancy 1970–2020

envi

de: Umwelt

format: CSV

biogeographical-region

display_name: biogeographical-region

butterflies

display_name: butterflies

elevation

display_name: elevation

infospecies

display_name: infospecies

insect-decline

display_name: insect-decline

insects

display_name: insects

occupancy-models

display_name: occupancy-models

switzerland

display_name: switzerland


en:
Silvopastoral systems are highly productive and combine long-term wood production with annual provision of forage for livestock. In the Swiss Jura Mountains these systems are a key component of the landscape. As in other cold biomes, climate change can potentially accelerate landscape change within these historically sustainable systems.
In order to anticipate the evolution of subalpine wooded pasture ecosystems under future climate and land-use changes, this project focused on the interplay between soil, vegetation and climate. It was aimed at providing experimental evidence for chief ecosystem processes, with emphasis on the quality of the ecosystem services provided. The main interest was placed on vegetation turf resistance to climate change along an unwooded – sparsely wooded - densely wooded pasture gradient (land-use intensity), where plant productivity, diversity and succession along with rates of carbon cycling and microbial activity provided measures of ecosystem functioning at both plot and landscape level.
Experimental transplantation of monolith soil turfs to lower altitudes allowed to simulate soil warming and reduced annual precipitation. In order to simulate a year-round warmer and drier climate the natural climate variation along an altitudinal gradient was used as a proxy. The aim was to simulate realistic climate change scenarios for the second half of the 21st century predicted by the IPCC report and downscaled for Switzerland providing regionalized interpolated projections integrating therein trends for temperature increase and precipitation decrease. By using permanent meteorological stations within the network of the Federal Office of Meteorology and Climatology (MeteoSwiss), we obtained high resolution regional data on the variation of mean annual temperature (MAT) and mean annual precipitation (MAP) in relation to altitude in the Swiss Jura Mountains. We observed a general increase of +0.5 K in MAT and a decrease of -20 % MAP for each 100 m decrease in altitude along the SE slope of the Swiss Jura Mountains. These relationships served for the selection of the transplantation sites such that in comparison to a control site at 1350 m a.s.l. (Combe des Amburnex, N 46°54’, E 6°23’) a +2 K MAT and -20 % MAP was achieved at 1010 m a.s.l. (Saint-George, N 46°52’, E 6°26’), a +4 K MAT and -40 % MAP at 570 m a.s.l., (Arboretum d’Aubonne, N 46°51’, E 6°37’), and a +5 K MAT and -50 % MAP at 395 m a.s.l. (Les Bois Chamblard, N 46°47’, E 6°41’). The two stations at 1010 m a.s.l. and 570 m a.s.l. corresponded to the IPCC scenario A1B for a moderate increase in greenhouse gas emissions and to scenario A2 for a high increase in greenhouse gas emissions, respectively. The station at 395 m a.s.l. was chosen to represent an extreme scenario with climate variables lying at the positive tail distribution of model predictions under the A2 scenario.
Soil cores were assembled into rectangular PVC boxes of 60  80 cm2 size and of 35 cm height. All mesocosms were dug down to surface level into previously prepared trenches in the ground thus preventing lateral heat exchange with the atmosphere. Since at each site the mesocosms were placed in a common garden with no light interception, mesocosms with turfs from the two wooded pastures were shaded from direct sun light to simulate the natural light conditions in the corresponding habitats. Each mesocosm was equipped with a drainage system and was connected to a water tank thus representing a zero potential lysimeter collecting soil solution and precipitation/snowmelt runoff. ECH2O EC-TM sensor probes coupled to Em50 data-loggers (Decagon Devices, Inc., USA) recorded soil temperature and volumetric water content in each mesocosm at the top-soil (0 to -3 cm) every minute and data were averaged over one hour intervals. Climate parameters at each transplantation site were monitored continuously throughout the experiment by means of automated weather stations (Sensor Scope Sàrl, Switzerland), measuring rain precipitation (non-heated tipping bucket gauges) and air temperature and humidity 2 m above the ground surface at one minute intervals.
A list of above- and belowground variables were measured to assess the resilience of biogeochemical processes, plant productivity, tree regeneration, and carbon sequestration for each respective land-use practice. Furthermore, the experimental data were used to improve on (parameterization) the existing spatially explicit, dynamic model WoodPaM and refine the modelʼs climatic and land-use variables so that different scenarios of climate change and land use change could be simulated. Natural and management induced disturbance patterns were incorporated into the model.
The data have been made available within the project CCES Mounted. The climate stations Sensorscope are still in use within the project CLIMARBRE (Wald und Klimawandel, WSL/BAFU).
References
1. Puissant, J., Cécillon, L., Mills, R.T.E., Robroek, B.J.M. Gavazov, K., De Danieli, S., Spiegelberger, T., Buttler, A., Brun, J.J. 2015. Seasonal influence of climate manipulation on microbial community structure and function in mountain soils. Soil Biology and Biochemistry 80: 296–305.
2. Mills, R., K. Gavazov, T. Spiegelberger, D. Johnson and A. Buttler 2014. Diminished soil functions occur under simulated climate change in a sup-alpine pasture, but heterotrophic temperature sensitivity indicates microbial resilience. Science of the Total Environment, vol. 473–474(0): 465-472.
3. Gavazov, K., Spiegelberger, T. and Buttler, A. 2014. Transplantation of subalpine wood-pasture turfs along a natural climatic gradient reveals lower resistance of unwooded pastures to climate change compared to wooded ones. Oecologia (174) : 1425-1435.
4. Peringer A., Siehoff S., Chételat J., Spiegelberger T., Buttler A. & Gillet F. 2013. Past and future landscape dynamics in pasture-woodlands of the Swiss Jura Mountains under climate change. Ecology and Society, 18, 3: 11. DOI: 10.5751/ES-05600-180311. [online] URL: http://www.ecologyandsociety.org/vol18/iss3/art11/
5. Gavazov, K. S., A. Peringer, A. Buttler, F. Gillet and T. Spiegelberger. 2013. Dynamics of Forage Production in Pasture-woodlands of the Swiss Jura Mountains under Projected Climate Change Scenarios. Ecology and Society 18 (1): 38. [online] URL: http://www.ecologyandsociety.org/vol18/iss1/art38/

en: transplantation-experiment climate-change biogeochemisty silvopastoral-systems soil

en: Biogeochemical data from a transplantation experiment of monolith soil turfs along an altitudinal gradient to simulate climate change scenarios

biogeochemisty

display_name: biogeochemisty

climate-change

display_name: climate-change

silvopastoral-systems

display_name: silvopastoral-systems

soil

display_name: soil

transplantation-experiment

display_name: transplantation-experiment


en: Included are three direct numerical simulations results of Stokes flow in three heterogeneous porous media obtained with OpenFoam simulations. In addition we include three data files that contain point-based extracted pores based on the post-processing as reported in the submitted paper "Local hydraulic resistance in heterogeneous porous media" in GRL.

en: heterogeneous-porous-media pore-shape-factors local-hydraulic-resistance permeability laminar-flow

en: Hydraulic resistance of pores in porous media using DNS of laminar flow

de:
Resource Title: Porous Media 1
    Size: 2133521698 bytes
    Format: text/x-vtk
    URL: https://www.envidat.ch/dataset/751f37f1-e38f-4393-a407-81272c406197/resource/d73518e6-e77a-49b9-b9f5-f0ff7f2b68d2/download/porousmedia1.vtk
    Description: Direct numerical simulations to obtain local pressure and velocity field.

de:
Resource Title: Results postprocessing
    Size: 9410122 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/751f37f1-e38f-4393-a407-81272c406197/resource/dffdd55f-2faf-48f5-b512-54667b812196/download/results_pm123.zip
    Description: The results of the pore identification and integration. The results are stored as follows. Each individual iso-pressure patch (first two columns) has an identification number Np. There is more information stored than needed, such as which patches are neighbors, and what there positions are, however to assess the local hydraulic resistance you need the integrated pore identification number stored under 'tracks'. All patches belonging to the same pore have the same track number. We stored the local pressure value under 'p_i', integrated flux Q under 'Q_i', total surface area A under 'A_i' and distance dx under 'dx_int', circularity C under 'phi_i'. There are attributes stored with other identifiers such as _p and _l, they refer to the two closest neighboring patches at iso-pressure values p_i+dp and p_i-dp respectively. To obtain the exact results this data has to be preprocessed such as described in the supplementary materials of the paper.

de:
Resource Title: Porous Media 3
    Size: 987993407 bytes
    Format: text/x-vtk
    URL: https://www.envidat.ch/dataset/751f37f1-e38f-4393-a407-81272c406197/resource/0556e308-a93f-421a-b18e-29d4f2f8440f/download/porousmedia3.vtk
    Description: Direct numerical simulations to obtain local pressure and velocity field.

de:
Resource Title: Porous Media 2
    Size: 1981993868 bytes
    Format: text/x-vtk
    URL: https://www.envidat.ch/dataset/751f37f1-e38f-4393-a407-81272c406197/resource/a497def0-27b4-4517-9f80-fed465177d30/download/porousmedia2.vtk
    Description: Direct numerical simulations to obtain local pressure and velocity field.

heterogeneous-porous-media

display_name: heterogeneous-porous-media

laminar-flow

display_name: laminar-flow

local-hydraulic-resistance

display_name: local-hydraulic-resistance

permeability

display_name: permeability

pore-shape-factors

display_name: pore-shape-factors