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opencc-by-4.0Feb 2020View details →

A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 1967-2015

Glacier surface mass balance (SMB) data are crucial to understand and quantify the regional effects of climate on glaciers and the high-mountain water cycle, yet observations cover only a small fraction of glaciers in the world. We present a dataset of annual glacier-wide surface mass balance of all the glaciers in the French Alps for the 1967-2015 period. This dataset has been reconstructed using deep learning (i.e. a deep artificial neural network), based on direct and remote sensing SMB observations, meteorological reanalyses and topographical data from glacier inventories. This data science reconstruction approach is embedded as a SMB component of the open-source ALpine Parameterized Glacier Model (ALPGM: https://zenodo.org/record/3609136). An extensive cross-validation allowed to assess the method’s validity, with an estimated average error (RMSE) of 0.49 m.w.e. a-1, an explained variance (r2) of 79% and an average bias of +0.017 m.w.e. a-1. We estimate an average regional area-weighted glacier-wide SMB of -0.72±0.20 m.w.e. a-1 for the 1967-2015 period, with moderately negative mass balances in the 1970s (-0.52 m.w.e. a-1) and 1980s (-0.12 m.w.e. a-1), and an increasing negative trend from the 1990s onwards, up to -1.39 m.w.e. a-1 in the 2010s. Following a topographical and regional analysis, we estimate that the massifs with the highest mass losses for this period are the Chablais (-0.90 m.w.e. a-1) and Ubaye and Champsaur (-0.91 m.w.e. a-1 both) ranges, and the ones presenting the lowest mass losses are the Mont-Blanc and Oisans ranges (-0.74 and -0.78 m.w.e. a-1 respectively). This dataset provides relevant and timely data for studies in the fields of glaciology, hydrology and ecology in the French Alps, in need of regional or glacier-specific meltwater contributions in glacierized catchments. The SMB dataset is comprised of multiple CSV files, one for each of the 661 glaciers from the 2003 glacier inventory (Gardent et al., 2014), named with its GLIMS ID and RGI ID with the following format: GLIMS-ID_RGI-ID_SMB.csv. Both indexes are used since some glaciers that split into multiple sub-glaciers do not have an RGI ID. Split glaciers have the GLIMS ID of their "parent" glacier and an RGI ID equal to 0. Every file contains one column for the year number between 1967 and 2015 and another column for the annual glacier-wide SMB time series. Glaciers with remote sensing-derived observations (Rabatel et al., 2016) include this information as an additional column. This allows the user to choose the source of data, with remote sensing data having lower uncertainties (0.35±0.06 () m.w.e. a-1 as estimated in Rabatel et al. (2016)). Columns are separated by semicolon (;). All topographical data for the 661 glaciers can be found in the updated version of the 2003 glacier inventory included in the Supplementary material.

opencc-by-4.0Sep 2019View details →

Figs 1-8. Ceratophysella macrocantha Stach, 1946 in Ceratophysella macrocantha Stach, 1946 (Collembola, Hypogastruridae): a redescription of a forgotten species from the Alps

Figs 1-8. Ceratophysella macrocantha Stach, 1946. (1) Chaetotaxy of antennal segments III and IV, dorsal side. (2) Postantennal or- gan and adjacent ocelli. (3) Maxillary head, dorsal side. (4) Maxillary head, ventral side. (5) Chaetotaxy of thoracic tergum II. (6) Chaetotaxy of abdominal terga III-VI. (7) Claw III with empodial appendage. (8) Dens and mucro of furca. Scale lines: 1-2; 3-4; 5-6; 7-8 to same scale. Abbreviations: or - subapical organite on antennal segment IV; ms - microsensillum; a1, a2, a3 - setae of a-row; m2, m3, m4 - setae of m-row; p1, p2, p4 - setae of p-row; s - body sensilla; 1, 2, 3, 4, 5, 6 - maxillary lamellae. The longitudinal axis of the body is indicated by a broken line. ►

opencc-by-4.0Feb 2020View details →

A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 1967-2015

Glacier mass balance (MB) data are crucial to understand and quantify the regional effects of climate on glaciers and the high-mountain water cycle, yet observations cover only a small fraction of glaciers in the world. We present a dataset of annual glacier-wide surface mass balance of all the glaciers in the French Alps for the 1967-2015 period. This dataset has been reconstructed using deep learning (i.e. a deep artificial neural network), based on direct MB observations and remote sensing annual estimates, meteorological reanalyses and topographical data from glacier inventories. The method’s validity was assessed through an extensive cross-validation against a dataset of 32 glaciers , with an estimated average error (RMSE) of 0.55 m.w.e. a-1, an explained variance (r2) of 75% and an average bias of -0.021 m.w.e. a-1. We estimate an average regional area-weighted glacier-wide MB of -0.71±0.21 (1 sigma) m.w.e. a-1 for the 1967-2015 period, with negative mass balances in the 1970s (-0.44 m.w.e. a-1), moderately negative in the 1980s (-0.16 m.w.e. a-1), and an increasing negative trend from the 1990s onwards, up to -1.34 m.w.e. a-1 in the 2010s. A comparison with ASTER-derived geodetic MB for the 2000-2015 period showed important differences with the photogrammetric geodetic MB used to train our model. When recalibrating our reconstructions with the new ASTER-derived geodetic MB, the estimated average regional area-weighted glacier-wide MB (1967-2015) is reduced to -0.64±0.21 (1 sigma) m.w.e. a-1. Following a topographical and regional analysis, we estimate that the massifs with the highest mass losses for the 1967-2015 period are the Chablais (-0.93 m.w.e. a-1), Champsaur and Haute-Maurienne (-0.86 m.w.e. a-1 both) and Ubaye ranges (-0.83 m.w.e. a-1), and the ones presenting the lowest mass losses are the Mont-Blanc (-0.69 m.w.e. a-1), Oisans and Haute-Tarentaise ranges (-0.75 m.w.e. a-1 both). This dataset provides relevant and timely data for studies in the fields of glaciology, hydrology and ecology in the French Alps, in need of regional or glacier-specific annual net glacier mass changes in glacierized catchments. The MB dataset is presented in two different formats: (a) A single netCDF file containing the MB reconstructions, the glacier RGI and GLIMS IDs and the glacier names. This file contains all the necessary information to correctly interact with the data, including some metadata with the authorship and data units. (b) A dataset comprised of multiple CSV files, one for each of the 661 glaciers from the 2003 glacier inventory (Gardent et al., 2014), named with its GLIMS ID and RGI ID with the following format: GLIMS-ID_RGI-ID_SMB.csv. Both indexes are used since some glaciers that split into multiple sub-glaciers do not have an RGI ID. Split glaciers have the GLIMS ID of their "parent" glacier and an RGI ID equal to 0. Every file contains one column for the year number between 1967 and 2015 and another column for the annual glacier-wide MB time series. Glaciers with remote sensing-derived estimates (Rabatel et al., 2016) include this information as an additional column. This allows the user to choose the source of data, with remote sensing data having lower uncertainties (0.35±0.06 () m.w.e. a-1 as estimated in Rabatel et al. (2016)). Columns are separated by semicolon (;).

opencc-zeroAug 2020View details →

Data from: Dispersal barriers and opportunities drive multiple levels of phylogeographic concordance in the Southern Alps of New Zealand

Phylogeographic concordance, or the sharing of phylogeographic patterns among co-distributed species, suggests similar responses to topography or climatic history. While the orientation and timing of breaks between lineages are routinely compared, spatial dynamics within regions occupied by individual lineages provide a second opportunity for comparing responses to past events. In environments with complex topography and glacial history, such as New Zealand's South Island, geographically nested comparisons can identify the processes leading to phylogeographic concordance between and within regional genomic clusters. Here, we used single nucleotide polymorphisms (obtained via ddRADseq) for two co-distributed forest beetle species, Agyrtodes labralis (Leiodidae) and Brachynopus scutellaris (Staphylinidae), to evaluate <a name="_Hlk34399639">the role of climate change and topography in shaping phylogeographic concordance at two, nested spatial scales: do species diverge over the same geographic barriers, with similar divergence times? And within regions delimited by these breaks</a>, do species share similar spatial dynamics of directional expansion or isolation-by-distance? We found greater congruence of phylogeographic breaks between regions divided by the strongest dispersal barriers (i.e., the Southern Alps). However, these shared breaks were not indicative of shared spatial dynamics within the regions they delimit, and the most similar spatial dynamics between species occurred within regions with the strongest gradients in historical climatic stability. Our results indicate that lack of concordance as traditionally detected by lineage turnover does not rule out the possibility of shared histories, and variation in the presence and type of concordance may provide insights into the different processes shaping phylogeographic patterns across geologically dynamic regions.

opencc-zeroOct 2020View details →

Supplementary material 1 from: Vorstenbosch T, Essl F, Lenzner B (2020) An uphill battle? The elevational distribution of alien plant species along rivers and roads in the Austrian Alps. NeoBiota 63: 1-24. https://doi.org/10.3897/neobiota.63.55096

Plot information

opencc-zeroOct 2020View details →

Supplementary material 2 from: Vorstenbosch T, Essl F, Lenzner B (2020) An uphill battle? The elevational distribution of alien plant species along rivers and roads in the Austrian Alps. NeoBiota 63: 1-24. https://doi.org/10.3897/neobiota.63.55096

Appendix 1–8

opencc-zeroJan 2021View details →

Two ways to be endemic: Alps and Apennines are different functional refugia during climatic cycles

Endemics co-occur because they evolved in situ and persist regionally or because they evolved ex situ and later dispersed to shared habitats, generating evolutionary or ecological endemicity centres, respectively. We investigate whether different endemicity centres can intertwine in the region ranging from Alps to Sicily, by studying their butterfly fauna. We gathered an extensive occurrence dataset for butterflies of the study area (27,123 records, 269 species, in cells of 0.5x0.5 degrees of latitude-longitude). We applied molecular-based delimitation methods (GMYC model) to 26,557 COI sequences of Western Palearctic butterflies. We identified entities based on molecular delimitations and the most recent checklist of European butterflies and objectively attributed occurrences to their most probable entity. We obtained a zoogeographic regionalisation based on the 69 endemics of the area. Using phylogenetic ANOVA we tested if endemics from different centres differ from each other and from non-endemics for key ecological traits and divergence time. Endemicity showed high incidence in the Alps and Southern Italy. The regionalisation separated the Alps from the Italian Peninsula and Sicily. The endemics of different centres showed a high turnover and differed in phenology and distribution traits. Endemics are on average younger than non-endemics and the Peninsula-Sicily endemics also have lower variance in divergence than those from the Alps. The observed variation identifies Alpine endemics as paleoendemics, now occupying an ecological centre, and the Peninsula-Sicily ones as neoendemics, that diverged in the region since the Pleistocene. The results challenge the common view of the Alpine-Apennine area as a single "Italian refugium".

opencc-zeroJan 2021View details →

What are the most crucial soil variables for predicting the distribution of mountain plant species? a comprehensive study in the Swiss Alps

Aim: To investigate the potential of a large range of soil variables to improve topo-climatic models of plant species distributions in a temperate mountain region encompassing complex relief. Location: The western Swiss Alps. Methods: Fitting topo-climatic models for >60 plant species across >250 sites with and without added soil predictor variables (>30). Testing included: (i) which soil variables improve plant species distribution models; (ii) whether an optimal subset of soil variables can improve models for the majority of species and habitat types; and (iii) how much variation in plant species distributions soil variables alone explain. Results: Geochemical variables (i.e., CaO, pH and inorganic carbon) and a drainage indicator (i.e., bulk soil water content) improved the predictive abilities of the models across the large majority of alpine plant species. The improvement of the models after the addition of soil information varied strongly between plant species and habitat types, but a trade-off was found between the number of soil variables and the associated gain in model performance. Finally, across all species, one specific combination of soil variables–bulk soil water content + total phosphorus + δ13C–outperformed the commonly used topo-climatic variables. Main conclusions: Several soil variables significantly increased the predictive power of plant species distribution models in the temperate mountain region. Geochemical and drainage variables proved most important.

opencc-zeroDec 2015View details →

Data from: Genomic and phenotypic differentiation of Arabidopsis thaliana along altitudinal gradients in the North Italian Alps

Altitudinal gradients in mountain regions are short-range clines of different environmental parameters such as temperature or radiation. We investigated genomic and phenotypic signatures of adaptation to such gradients in five Arabidopsis thaliana populations from the North Italian Alps that originated from 580 to 2350 m altitude by resequencing pools of 19–29 individuals from each population. The sample includes two pairs of low- and high-altitude populations from two different valleys. High-altitude populations showed a lower nucleotide diversity and negative Tajima's D values and were more closely related to each other than to low-altitude populations from the same valley. Despite their close geographic proximity, demographic analysis revealed that low- and high-altitude populations split between 260 000 and 15 000 years before present. Single nucleotide polymorphisms whose allele frequencies were highly differentiated between low- and high-altitude populations identified genomic regions of up to 50 kb length where patterns of genetic diversity are consistent with signatures of local selective sweeps. These regions harbour multiple genes involved in stress response. Variation among populations in two putative adaptive phenotypic traits, frost tolerance and response to light/UV stress was not correlated with altitude. Taken together, the spatial distribution of genetic diversity reflects a potentially adaptive differentiation between low- and high-altitude populations, whereas the phenotypic differentiation in the two traits investigated does not. It may resemble an interaction between adaptation to the local microhabitat and demographic history influenced by historical glaciation cycles, recent seed dispersal and genetic drift in local populations.

opennotspecifiedDec 2016View details →

Fig. 6 in A new vertebrate for Europe: the discovery of a range-restricted relict viper in the western Italian Alps

Fig. 6. Pattern variation in adult male (left) and adult female (right) of Vipera walser sp. nov.

opennotspecifiedDec 2016View details →

Fig. 5 in A new vertebrate for Europe: the discovery of a range-restricted relict viper in the western Italian Alps

Fig. 5. Habitus of the holotype of Vipera walser sp. nov.

opennotspecifiedDec 2010View details →

FIGURE 22 in New data on the spider genus Troglohyphantes (Araneae, Linyphiidae) in the Italian Alps, with the description of a new species and a new synonymy

FIGURE 22. Sordellii- and ruffoi complexes: distribution in the Italian Alps.

opennotspecifiedDec 2010View details →

FIGURE 20 in New data on the spider genus Troglohyphantes (Araneae, Linyphiidae) in the Italian Alps, with the description of a new species and a new synonymy

FIGURE 20. Lucifuga- and exul complexes: distribution in the Italian Alps.

opennotspecifiedDec 2010View details →

FIGURE 19 in New data on the spider genus Troglohyphantes (Araneae, Linyphiidae) in the Italian Alps, with the description of a new species and a new synonymy

FIGURE 19. Polyophtalmus-, orphaeus- and microcymbium complexes: distribution in the Italian Alps.

FIGURE 9 in Biodiversity of oribatid mites (Acari: Oribatida) along an altitudinal gradient in the Central Alps

FIGURE 9. Mycobates sp. Ventral aspect.

FIGURE 8 in Biodiversity of oribatid mites (Acari: Oribatida) along an altitudinal gradient in the Central Alps

FIGURE 8. Mycobates sp. Lateral aspect.

FIGURE 7 in Biodiversity of oribatid mites (Acari: Oribatida) along an altitudinal gradient in the Central Alps

FIGURE 7. Mycobates sp. Dorsal aspect.

FIGURE 6 in Biodiversity of oribatid mites (Acari: Oribatida) along an altitudinal gradient in the Central Alps

FIGURE 6. Carabodes sp. Ventral aspect.

FIGURE 3 in Biodiversity of oribatid mites (Acari: Oribatida) along an altitudinal gradient in the Central Alps

FIGURE 3. General distribution of species in %.

FIGURE 5 in Biodiversity of oribatid mites (Acari: Oribatida) along an altitudinal gradient in the Central Alps

FIGURE 5. Carabodes sp. Lateral aspect.