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Ground temperature time series in European mountain permafrost
<p>RELATED PUBLICATION</p> <p>This dataset is related to the following publication:</p> <p><strong>Noetzli J., Isaksen, K., Barnett, J., Chrisitiansen, H.H., Delaloye, R., Etzelmueller, B., Farinotti, D., Gallemann, T., Guglielmin, M., Hauck, C., Hilbich, C., Hoelzle, M., Lambiel, C., Magnin, F., Oliva, M., Paro, L, Pogliotti, P., Riedl, C., Schoeneich, P., M., Valt, M., Vieli A., Philliips, M. (2024). Enhanced permafrost warming in Euro­pean mountains in the 21st century. Nature Communications, 15, 10508, <a href="https://doi.org/10.1038/s41467-024-54831-9">https://doi.org/10.1038/s41467-024-54831-9</a>.</strong></p> <p><strong>==> </strong></p> <p><strong>For information on the measurements, selection criteria, processing information and data providers please refer to the methods, data availability and acknowledgements sections of the related publication ! </strong></p> <p> </p> <p>---------------------------------------------------------------------------------------------------------------------------</p> <p>CONTENT</p> <p>The dataset includes monthly and annual time series of ground temperatures measured in 64 boreholes in European mountain permafrost areas and corresponding metadata.</p> <p>Temporal coverage: at least 10 years until 2022</p> <p>Spatial coverage: European mountain regions (Svalbard, Scandinavia, Iceland, European Alps, Sierra Nevada)</p> <p>Depth of measurements: at least 10 m; for all boreholes data of the sensors closest to 5, 10 and 20 m depth are included</p> <p>Monthly means are calculated from daily values and annual values are derived from monthly mean values.</p> <p> </p> <p>---------------------------------------------------------------------------------------------------------------------------</p> <p>DATA COMPILATION</p> <p>The data were compiled to derive 10-year and 20-year warming rates in European mountain permafrost in the study by Noetzli et al. (in review, see above). Data were collected from national permafrost observation networks as well as from individual institutions (e.g, universities, environmental agencies).</p> <p>The aquisition of long time series over decades requires long-term committment from the responsible institutions to maintain instruments and to collect and curate the data. Details on the data source for each time series can be found in the metadata file as well as in the related publication. The main data sources by country are given in the list below.</p> <table> <tbody> <tr> <td><strong>Country</strong></td> <td><strong>Data source (institution or national network)</strong></td> </tr> <tr> <td>Austria</td> <td>GeoSphere Austria</td> </tr> <tr> <td>France</td> <td>Réseau français d'observation du permafrost (PermaFrance, <a href="https://wslch365-my.sharepoint.com/personal/jeannette_noetzli_slf_ch/Documents/PermafrostEurope/permafrance.osug.fr">permafrance.osug.fr</a>)</td> </tr> <tr> <td>Germany</td> <td>Bavarian Environment Agency</td> </tr> <tr> <td>Iceland</td> <td>University of Oslo</td> </tr> <tr> <td>Italy</td> <td>ARPA Piemonte, ARPA Valle d'Aosta, ARPA Veneto, University of Insubria</td> </tr> <tr> <td>Norway</td> <td>Norwegian Permafrost Monitoring Network (<a href="https://cryo.met.no/">cryo.met.no</a> and <a href="http://sios-svalbard.org/">sios-svalbard.org</a>)</td> </tr> <tr> <td>Spain</td> <td>Universitat de Barcelona</td> </tr> <tr> <td>Svalbard</td> <td>Norwegian Permafrost Monitoring Network (<a href="https://cryo.met.no/">cryo.met.no</a> and <a href="http://sios-svalbard.org/">sios-svalbard.org</a>)</td> </tr> <tr> <td>Sweden</td> <td>University of Stockholm</td> </tr> <tr> <td>Switzerland</td> <td>Swiss Permafrost Monitoring Network PERMOS (<a href="http://www.permos.ch">http://www.permos.ch</a>)</td> </tr> </tbody> </table> <p> </p> <p>---------------------------------------------------------------------------------------------------------------------------</p> <p>FILES AND FORMAT</p> <p>This data set includes three csv-files: <br>1) metadata with information on the measurement location and data provider<br>2) monthly ground temperature time series and <br>3) annual ground temperature time series. </p> <p>The variables in the three files are described below. Data files are in long data format.</p> <p><strong>File 1 – borehole_overview.csv<br></strong>Key information on the boreholes, responsible institutions and contact persons.</p> <table> <tbody> <tr> <td><strong>Variable</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>Name</td> <td>Name of the borehole (as used in the related study)</td> </tr> <tr> <td>Country</td> <td>Alpha-2 code</td> </tr> <tr> <td>Region</td> <td>Larger region</td> </tr> <tr> <td>First_year</td> <td>First year of data</td> </tr> <tr> <td>Elevation [m asl.]</td> <td>Elevation of the borehole</td> </tr> <tr> <td>Lat [° N]</td> <td>Latitude</td> </tr> <tr> <td>Lon [° E]</td> <td>Longitude</td> </tr> <tr> <td>Depth [m]</td> <td>Total depth of the borehole</td> </tr> <tr> <td>DZAA [m]</td> <td>Depth of the Zero Annual Amplitude (uppermost sensor with annual amplitude ≤0.1)</td> </tr> <tr> <td>Phase lag</td> <td>Phase lag at 10 m depth compared to surface in months</td> </tr> <tr> <td>Morphology</td> <td>Main morphology of the site</td> </tr> <tr> <td>Surface_cover</td> <td>Main surface cover at the site</td> </tr> <tr> <td>Lithology</td> <td>Main lithology of the site</td> </tr> <tr> <td>Ice_content</td> <td>Basic classification by ground ice content at the site (no ice, ice-poor, ice-bearing, ice-rich), see publication for details</td> </tr> <tr> <td>Institution</td> <td>Responsible institution (in the year 2024)</td> </tr> <tr> <td>Contact_person</td> <td>Contact person (in the year 2024)</td> </tr> <tr> <td>Special_remarks</td> <td>Remarks on location, e.g. horizontal borehole</td> </tr> </tbody> </table> <p> </p> <p><strong>File 2 – permafrost_temperatures_european_mountains_monthly_2022.csv<br></strong>Time series of monthly mean ground temperatures at ca. 5, 10 and 20 m depth for 64 boreholes in European mountain permafrost until 2022.</p> <table> <tbody> <tr> <td><strong>Variable</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>bh</td> <td>Name of the borehole</td> </tr> <tr> <td>time [YYYY-MM-DD]</td> <td>Date</td> </tr> <tr> <td>depth [m]</td> <td>Depth of measurement</td> </tr> <tr> <td>temp [°C]</td> <td>Monthly mean ground temperature (aggregated from daily values)</td> </tr> <tr> <td>t_min [°C]</td> <td>Minimum daily ground temperature of the year</td> </tr> <tr> <td>t_max [°C]</td> <td>Maximum daily ground temperature of the year</td> </tr> <tr> <td>count</td> <td>Number of daily values available to calculate monthly mean values</td> </tr> <tr> <td>dclass [5, 10 or 20 m]</td> <td>Depth class defined for analyses in related study</td> </tr> </tbody> </table> <p> </p> <p><strong>File 3 – permafrost_temperatures_european_mountains_annual_2022.csv<br></strong>Time series of annual mean ground temperatures at ca. 5, 10 and 20 m depth for 64 boreholes in European mountain permafrost until 2022.</p> <table> <tbody> <tr> <td><strong>Variable</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>bh</td> <td>Name of the borehole</td> </tr> <tr> <td>time [YYYY]</td> <td>Year</td> </tr> <tr> <td>depth [m]</td> <td>Depth of measurement</td> </tr> <tr> <td>temp [°C]</td> <td>Annual mean ground temperature (aggregated from monthly values)</td> </tr> <tr> <td>t_min [°C]</td> <td>Minimum monthly ground temperature of the year</td> </tr> <tr> <td>t_max [°C]</td> <td>Maximum monthlyground temperature of the year</td> </tr> <tr> <td>count</td> <td>Number of monthly values available to calculate annual mean values</td> </tr> <tr> <td>dclass [5, 10 or 20 m]</td> <td>Depth class defined for analyses in related study</td> </tr> </tbody> </table> <p> </p> <p>---------------------------------------------------------------------------------------------------------------------------</p> <p>CONTACT</p> <p>For question related to this dataset please contact the corresponding author: jeannette.noetzli@slf.ch. <br>For questions related to a specific time series, see metadata for contact information.</p>
Supplementary data to "The effects of small-scale heterogeneity on biomonitoring of desmid phytobenthos in Central European temperate mountain peatlands"
<p>The supplementary data consist of the files including the species-in-samples data and their associated NCV scores used for the analyses described in the manuscript submitted to hydrobiologia. In addition, two R scripts used for the analyses are included, too.</p> <p> </p>
Fig. 6 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 6. Abundance (mean number of burrows/100 × 5 m transect) of S. citellus in 4 colonies in the study area in summer (for the period 2017–2021) N = Luda Yana; –– l –– = Belotrup; ---- l ---- = Panagyurski kolonii; u = Beli Manastiri
Fig. 5 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 5. Changes in the habitat suitability in the study area (white – not suitable, black – high suitability) of European souslik assessed by maxent modelling based on data from 2006–2018 (B) and extrapolated for the period 1985–2005 (A). The results are presented in
Fig. 3 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 3. Negative and positive anomalies (white and black bars) of the Mean Annual Temperature time series for the period of 1985–2018 (data from the meteorological station Sofia)
Fig. 2 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 2. Changes in the number of grazing livestock in the southern central Bulgarian planning region for the period 2001–2018
The most remarkable migrants: Systematic analysis of the Western European insect flyway at a Pyrenean mountain pass
<p>In 1950, David and Elizabeth Lack chanced upon a huge migration of insects and birds flying through the Pyrenean Pass of Bujaruelo, later describing the spectacle as combining both grandeur with novelty. The intervening years have seen many changes to land use and climate, posing the question as to the current status of this migratory phenomenon, while a lack of quantitative data has prevented insights into the ecological impact of this mass insect migration and into the factors affecting it. To address this, we revisited the site in autumn over a 4-year period and systematically monitored diurnal insect species and numbers. We document an annual mean of 17.1 million day-flying insects from 5 orders moving south, with 'mass migration' events associated with warmer temperatures, the presence of a headwind, sunlight, low windspeed, and low rainfall. Diptera dominated the migratory assemblage and annual numbers varied by more than fourfold with larger annual migration flows associated with higher autumn temperatures in Northwest Europe. Finally, using observed environmental thresholds for migration, we estimate an annual 'bioflow' of at least 14.6 billion day-flying insects migrating south over the whole Pyrenean Mountain range, highlighting the importance of this route for seasonal insect migrants.</p>
FIG. 1. — A in Biodiversity in mountain groundwater: the Mercantour National Park (France) as a European hotspot
FIG. 1. — A, Study area and location of sampling sites. Sites are numbered as in Table 1; B, Map of groundwater habitats (extracted from Cornu et al. 2013) with the limits of the Mercantour National Park in white.
FIG. 2 in Biodiversity in mountain groundwater: the Mercantour National Park (France) as a European hotspot
FIG. 2. — Some representative species collected in the Mercantour National Park:A, Troglochaetus beranecki Delachaux,1921, length 0.6 mm; B, Parabathynella sp., length 1.5 mm; C, Nipargus foreli Humbert, 1877, length 8 mm; D, Proasellus sp., length 4 mm. Photographs: A-C, M.-J. Dole-Olivier; D, F. Malard.
Рис. 8–13. ΔанΑшафты Южного УраΛа (8–11) и Русской равнины (12–13). 8 – разнотравная степь у поΑножия горы ВербΛюжка, местообитание Cionus rossicus; 9 – ксерофитные Λуга в пойме реки УраΛ вбΛизи горы ВербΛюжка, местообитание Cionus rossicus; 10 – южные степи в районе КзыΛаΑырского карстового поΛя, местообитание Cionus gebleri; 11 – степи низкогорий Южного УраΛа бΛиз с. КиΑрясово, местообитание Smicronyx albopictus; 12 – КаменноброΑские меΛовые горы на юго-запаΑе ПривоΛжской возвышенности, местообитание Mecinus janthiniformis, Smicronyx robustus и S. albopictus; 13 – меΛовой останец КобыΛья ГоΛова в прироΑном парке «Àонской», местообитание Mecinus janthiniformis. Figs 8–13. Landscapes of the Southern Urals (8–11) and the Russian Plain (12–13). 8 – forb steppe at the down of Verblyuzhka Mt., habitat of Cionus rossicus; 9 – xerophytic meadows in the floodplain of the Ural River near Verblyuzhka Mt., habitat of Cionus rossicus; 10 – southern steppes in the Kzyladyr karst area, habitat of Cionus gebleri; 11 – steppes of the low mountains of the Southern Urals near Kidryasovo village, habitat of Smicronyx albopictus; 12 – Kamennobrodsky chalk mountains in the southwest of the Volga Upland, habitat of Mecinus janthiniformis, Smicronyx robustus, and S. albopictus; 13 – Cretaceous outlier Kobyl'ya Golova in the Donskoy Nature Park, habitat of Mecinus janthiniformis. in Interesting records of weevils (Coleoptera: Curculionidae: Curculioninae) in the steppe zone of the European part of Russia and the Urals
Рис. 8–13. ΔанΑшафты Южного УраΛа (8–11) и Русской равнины (12–13). 8 – разнотравная степь у поΑножия горы ВербΛюжка, местообитание Cionus rossicus; 9 – ксерофитные Λуга в пойме реки УраΛ вбΛизи горы ВербΛюжка, местообитание Cionus rossicus; 10 – южные степи в районе КзыΛаΑырского карстового поΛя, местообитание Cionus gebleri; 11 – степи низкогорий Южного УраΛа бΛиз с. КиΑрясово, местообитание Smicronyx albopictus; 12 – КаменноброΑские меΛовые горы на юго-запаΑе ПривоΛжской возвышенности, местообитание Mecinus janthiniformis, Smicronyx robustus и S. albopictus; 13 – меΛовой останец КобыΛья ГоΛова в прироΑном парке «Àонской», местообитание Mecinus janthiniformis. Figs 8–13. Landscapes of the Southern Urals (8–11) and the Russian Plain (12–13). 8 – forb steppe at the down of Verblyuzhka Mt., habitat of Cionus rossicus; 9 – xerophytic meadows in the floodplain of the Ural River near Verblyuzhka Mt., habitat of Cionus rossicus; 10 – southern steppes in the Kzyladyr karst area, habitat of Cionus gebleri; 11 – steppes of the low mountains of the Southern Urals near Kidryasovo village, habitat of Smicronyx albopictus; 12 – Kamennobrodsky chalk mountains in the southwest of the Volga Upland, habitat of Mecinus janthiniformis, Smicronyx robustus, and S. albopictus; 13 – Cretaceous outlier Kobyl'ya Golova in the Donskoy Nature Park, habitat of Mecinus janthiniformis.
Data from: Effects of climate and forest development on habitat specialization and biodiversity in Central European mountain forests
Open the record for dataset details and reuse information.
The most remarkable migrants: Systematic analysis of the Western European insect flyway at a Pyrenean mountain pass
Open the record for dataset details and reuse information.
Lying deadwood retention affects microhabitat use of martens (Martes spp.) in European mountain forests
<p><span>Biodiversity loss due to intensive timber production is a ubiquitous conservation issue across temperate and boreal forest ecosystems. Retention forestry, the retention of deadwood and old-growth features within production forest, is one management strategy that has been implemented in various countries around the world to conserve a wide range of taxa within managed forests. The success and ecological implications of retention forestry are currently subject to intensive investigation and while some taxa like birds and insects have already been studied frequently, larger mammals have obtained less attention. Pine martens are one of the few larger mammals in central Europe preferring older forest and potentially profiting directly from deadwood retention as a consequence of implemented retention forestry. The goal of our study was to assess the response of European marten species to deadwood retention in montane mixed forests. Using marten detection rates from camera traps on 135 research plots we assessed the response of martens to deadwood on three different spatial scales using generalized linear mixed models. We found no effect of lying deadwood on marten detections on the plot scale (one-hectare) or in a ten-meter radius around the camera traps. However, we found a significant increase in marten detections if logs (>10 cm) were directly in front and in view of the camera trap. Our results show that deadwood retention as a measure of retention forestry does affect microhabitat use of martens, but not stand selection during the growing season. Logs directly in view of the camera trap increase marten detection rates as martens choose to move and forage along fallen trees when they are available. When using camera trapping to collect data on martens, trap positioning in front of logs can heavily bias trapping results when unaccounted for.</span></p>
Data from "Elevation affects both the occurrence of ungulate browsing and its effect on tree seedling growth for four major tree species in European mountain forests"
<p>This repository contains the field data used in the paper from Bernard et al. on the interactive effect of elevation and ungulate browsing on tree regeneration. This dataset is associated with a github repository containing the code to run the analyses of the paper, publicly available at https://github.com/jbarrere3/BaccaraPaper. </p><p> </p><p>Data were collected for the Baccara project, by Elena Granda, Raquel Benavides, Sonia Rabasa, Georges Kunstler, and Marco Heurich. </p>
Data from: Pervasive introgression during rapid diversification of the European mountain genus Soldanella (L.) (Primulaceae)
<p>Hybridization is a key mechanism involved in lineage diversification and speciation, especially in ecosystems that experienced repeated environmental oscillations. Recently radiated plant groups, which have evolved in mountain ecosystems impacted by historical climate change provide an excellent model system for studying the impact of gene flow on speciation. We combined organellar (whole plastome) and nuclear genomic data (RAD-seq) with a cytogenetic approach (rDNA FISH) to investigate the effects of hybridization and introgression on evolution and speciation in the genus <em>Soldanella</em> (snowbells, Primulaceae). Pervasive introgression has already occurred among ancestral lineages of snowbells and has persisted throughout the entire evolutionary history of the genus, regardless of the ecology, cytotype, or distribution range size of the affected species. The highest extent of introgression has been detected in the Carpathian species, which is also reflected in their extensive karyotype variation. Introgression occurred even between species with dysploid and euploid cytotypes, which were considered to be reproductively isolated. The magnitude of introgression detected in snowbells is unprecedented in other mountain genera of the European Alpine System investigated hitherto. Our study stresses the prominent evolutionary role of hybridization in facilitating speciation and diversification on the one hand, but also enriching previously isolated genetic pools. </p>
Fig. 4 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 4. Response curves, representing the dependence of predicted suitability both on the
Fig. 1 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria
Fig. 1. Satellite view of the study area. White circles represent the location of the colonies
FIG. 4 in Biodiversity in mountain groundwater: the Mercantour National Park (France) as a European hotspot
FIG. 4. — Continuation.
Data for: Use of viscera from hunted roe deer by vertebrate scavengers in summer in central European mountainous mixed forest
<p><span>Carrion is a valuable resource in forests, providing sustenance for vertebrate and invertebrate scavenger communities and contributing to ecosystem functions, such as nutrient cycling. Intensive ungulate hunting, and thereby extraction of carcasses, removes large quantities of potential carrion from the system, denying a valuable resource from scavenger fauna. It may be possible to reduce the loss and negative consequences to forest biodiversity by retaining evisceration residues from hunted deer, where full carcasses cannot be retained. However, what roll evisceration residues play as a resource for scavengers in temperate forests is not well understood. In this study, we exposed 47 carrion samples from hunted roe deer, in front of triple sets of camera traps, to examine how hunting remains are removed and fed upon by vertebrate scavengers. Overall, 70 % of the samples were completely removed from experimental sites by vertebrates. We detected twelve vertebrate taxa feeding on evisceration residues, including martens (<em>Martes</em> spp.), red kites (<em>Milvus milvus</em>) and garden dormice (<em>Eliomys quercinus</em>). Common buzzards (<em>Buteo buteo</em>) and Eurasian jays (<em>Garrulus glandarius</em>) were the most frequent feeders on carrion samples, while red foxes (<em>Vulpes vulpes</em>) displaced the largest proportion of samples. Finally, we found a range of insectivorous bird and mammal species using hunting remains as a source for invertebrate prey, while not scavenging on the remains directly. We demonstrate that evisceration residues can be a valuable resource for a wide range of taxa and suggest that viscera retention from hunted game may contribute to resource provisioning for scavengers in forest ecosystems. </span></p>
Data for: Effects of understory characteristics on browsing patterns of roe deer in central European mountain forests
<p><span>Selective browsing by deer on young trees may impede the management goal of increasing forest resilience against climate change and other disturbances. Deer population density is often considered the main driver of browsing impacts on young trees, however a range of other variables such as food availability also affect this relationship. In this study, we use browsing survey data from 135 research plots to explore patterns of roe deer (<em>Capreolus capreolus</em>) browsing pressure on woody plants in mountainous forests in central Europe. We fitted species-specific generalized linear mixed models for eight woody taxa, assessing potential effects of understory characteristics, roe deer abundance and lying deadwood on browsing intensity. Our study reveals conspecific and associational effects for woody taxa that are intermediately browsed by roe deer. Selective browsing pressure was mediated by preferences of plants, in that, browsing of strongly preferred woody taxa as for example mountain ash (<em>Sorbus aucuparia</em>) and of least preferred woody taxa e.g., Norway spruce (<em>Picea abies</em>) was not affected by the surrounding understory vegetation, while browsing pressure on intermediately browsed species like for example silver fir (<em>Abies alba</em>) was affected by understory characteristics. Contrary to our expectations, roe deer abundance was only positively associated with browsing pressure on silver fir and bilberry (<em>Vaccinium myrtillus</em>), while all other plants were unaffected by deer abundance. Finally, we did not find an influence of lying deadwood volume on the browsing pressure on any woody-plant species. Overall, our results indicate that patterns in browsing preference and intensity are species-specific processes and are partly affected by the surrounding understory vegetation. Current management strategies that aim to reduce browsing pressure through culling may be inefficient as they do not address other drivers of browsing pressure. However, managers also need to consider the characteristics of the local understory vegetation in addition to deer abundance, and design species-specific plans to reduce browsing on woody plant taxa.</span></p>
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Allen Brain Atlas
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OpenNeuro
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