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  • 2015-2019  (4)
  • 1990-1994  (5)
Document type
Keywords
Publisher
Years
Year
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Journal of paleolimnology 11 (1994), S. 311-312 
    ISSN: 1573-0417
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Geosciences
    Type of Medium: Electronic Resource
    Location Call Number Limitation Availability
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of paleolimnology 8 (1993), S. 85-95 
    ISSN: 1573-0417
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Geosciences
    Type of Medium: Electronic Resource
    Location Call Number Limitation Availability
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Journal of paleolimnology 9 (1993), S. 297-299 
    ISSN: 1573-0417
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Geosciences
    Type of Medium: Electronic Resource
    Location Call Number Limitation Availability
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Climate dynamics 6 (1992), S. 233-239 
    ISSN: 1432-0894
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Physics
    Notes: Abstract Results of high-resolution AMS 14C dating of terrestrial plant macrofossils from late-glacial and early-Holocene lake deposits in Switzerland show three periods with constant radiocarbon ages. These plateaux of constant age occur at 12700, 10000, and 9500 y BP. A comparison of this radiocarbon chronology with a varve chronology documents discrepancies between the sidereal and the radiocarbon time-scale for the late-glacial period. The age-plateaux and the time-scale discrepancies have a significant impact on the estimation of rates of change during this period: estimates of rates of change can be very misleading if calculated on the basis of radiocarbon ages. This is illustrated by an example of estimated rates of late-glacial and early Holocene palynological change in Switzerland.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Hydrobiologia 214 (1991), S. 53-57 
    ISSN: 1573-5117
    Keywords: varve chronology ; Younger Dryas ; Late-Glacial ; AMS-14C-datings
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstracts Despite extensive AMS-14C dating series on Late-glacial terrestrial plant remains, a precise estimate of the duration of the Younger Dryas biozone (sensu Ammann & Lotter, 1989) is hampered by the occurrence of a period of constant 14C-age at 10 000 yr B.P. However, varve counts at Soppensee suggest that the Younger Dryas biozone comprises approx. 680–720 varves, and that the phase of constant radiocarbon age includes between 270–310 varves.
    Type of Medium: Electronic Resource
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  • 6
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    Unknown
    PANGAEA
    In:  European Pollen Database (EPD)
    Publication Date: 2024-02-16
    Keywords: Abies; Acer; AGE; Alnus; Apiaceae; Artemisia; Asteraceae; Betula; Botrychium; Brassicaceae; Buxus; Campanulaceae; Cannabaceae; Carpinus betulus; Caryophyllaceae; Castanea; Centaurea cyanus; Centaurea nigra-type; Ceratophyllum: spines; Cerealia; Chenopodiaceae; Cichorioideae; Corylus; Counting, palynology; Cyperaceae; DEPTH, sediment/rock; Dryopteris filix-mas; EPD; Ephedra distachya; Ephedra fragilis; Equisetum; Ericaceae; Fabaceae; Fagus; Filipendula; Frangula alnus; Fraxinus excelsior; Gramineae; Hedera helix; Helianthemum; Hippophae rhamnoides; Ilex aquifolium; Indeterminable: unknown; Juglans; Juniperus; KULC; KULLENBERG corer; Lamiaceae; Liliaceae; Lotus; Lycopodium (added); Lycopodium (counted); Lycopodium tablets; Lygeum spartum; Lythrum; Malvaceae; Mentha-type; Monolete spore(s); Myriophyllum; Nuphar; Nymphaea; Pediastrum; Picea; Pinus; Pinus, stomata; Plantago; Plantago alpina-type; Plantago lanceolata; Plantago major/media; Polygonum amphibium; Polypodium; Populus; Potamogeton; Quercus; Ranunculaceae; Ranunculus subgen. Batrachium; Rosaceae; Rosaceae trees; Rubiaceae; Rumex; Salix; Sample volume; Sanguisorba minor; Sanguisorba officinalis; Saxifraga oppositifolia-type; Secale; Selaginella selaginoides; SO8923; Soppensee; Sparganium; Sphagnum; Spores, trilete; Taxus; Thalictrum; Thelypteris palustris; Tilia; Trapa; Trifolium; Typha; Ulmus; Urtica; Varia; Viburnum; Viscum; Zea mays
    Type: Dataset
    Format: text/tab-separated-values, 23571 data points
    Location Call Number Limitation Availability
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  • 7
    facet.materialart.
    Unknown
    PANGAEA
    In:  Supplement to: Finsinger, Walter; Heiri, Oliver; Valsecchi, Verushka; Tinner, Willy; Lotter, André F (2007): Modern pollen assemblages as climate indicators in southern Europe. Global Ecology and Biogeography, 16(5), 567-582, https://doi.org/10.1111/j.1466-8238.2007.00313.x
    Publication Date: 2024-03-06
    Description: Aim and Location: Our aim is to develop pollen-climate inference models for southern Europe and to test their performance and inference power by cross-validation with modern climate data. Surface sediments collected from lakes along a climate gradient from the winter-cold/summer-wet Alps to winter-wet/summer-dry Sicily were analysed for modern pollen assemblages. Methods: For each lake, mean monthly temperatures, seasonal precipitation and site-specific climate uncertainties have been estimated. Pollen-climate relationships were studied using numerical analyses, and inference models were derived by partial least squares (PLS) and weighted-averaging PLS (WA-PLS) regressions for January and July temperatures (T ), and for winter, spring and summer precipitation (P). In order to assess whether these variables are also of ecological importance for vegetation in the subregions, we split the data set into an Alpine and a Mediterranean subset. Results: Low bootstrap cross-validated root mean square errors of prediction (RMSEP) for January T (1.7 °C), July T (2.1 °C) and summer P (38 mm), as well as low RMSEPs expressed as a percentage of the gradient length (8 -9%), indicate a good inference power. Models revealed excellent to good performance statistics for January T, July T and summer P (r2 = 0.8), and for winter and spring P (r 2 = c. 0.5). We show that the variables with the highest explanatory power differ between the two subregions. These are summer T and P for the Alpine set, and January T, winter P and July T for the Mediterranean set. Main conclusions: The study reveals the influence of climatic conditions during the growing season on modern pollen assemblages and indicates the potential of pollen data for long-term climate reconstructions of parameters such as winter precipitation and temperature, which seem to be the main factors having an influence on the variability of Mediterranean climate. These models may therefore provide important information on past regional climate variability in southern Europe.
    Keywords: Abies; Acer; Achillea-type; Aconitum; Aesculus; Aethusa cynapium-type; Alchemilla-type; Allium-type; Alnus glutinosa-type; Alnus viridis; Ambrosia-type; Amorpha fruticosa; Anemone hortensis; Anemone nemorosa-type; Anthericum-type; Anthriscus sylvestris-type; Apium inundatum-type; Arbutus-type; Artemisia; Asplenium-type; Asteroideae; Athyrium filix-femina; Betula; Biviere_Cesaro; Biviere Cesaro, BC; Botrychium; Bupleurum-type; Buxus; Calluna vulgaris; Caltha-type; Campanula; Carpinus; Caryophyllaceae; Castanea sativa; Cedrus; Celtis; Centaurea nigra-type; Centaurea solstitialis; Cerastium cerastioides-type; Cerastium fontanum-type; Cerealia; Chaerophyllum hirsutum-type; Chamaerops humilis; Chenopodiaceae-type; Cichorioideae; Cirsium; Cistus crispus-type; Cistus salvifolius; Clematis group; Cornus mas; Cornus sanguinea; Corylus avellana; Crassula; Cruciferae; Cryptogramma crispa; Cryptomeria-type; Cystopteris fragilis; Date/Time of event; Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; Dianthus-type; Dryopteris filix-mas-type; Echium; Elaeagnus; Empetrum-type; Ephedra distachya-type; Ephedra fragilis-type; Erica arborea-type; Ericaceae; Eucalyptus; Euphorbia; Event label; Fagus; Falcaria vulgaris-type; Fallopia convolvulus-type; Filipendula; Frangula alnus; Fraxinus excelsior; Fraxinus ornus; GC; GCUWI; Gentiana pneumonanthe-type; Geranium; Gramineae; Gravity corer; Gravity corer, UWITEC; Gypsophila repens-type; Hedera-type; Helianthemum; Helleborus viridis; Heracleum-type; HONK; HON-Kajak sediment corer; Humulus lupulus; Humulus-type; Huperzia selago; Hypericum perforatum-type; Identification; Italy; Juglans; Juniperus; Lac_des_Grenouilles; Lac des Grenouilles, GREN; Lago_Albano; Lago_Buse; Lago_Calamone; Lago_Campagna; Lago_Cece; Lago_Colbricon_inferiore; Lago_Colbricon_superiore; Lago_Cornisello_inferiore; Lago_Cornisello_superiore; Lago_del_Segrino; Lago_dellAccesa; Lago_dellAquilente; Lago_delle_Lame; Lago_delle_Trote; Lago_dellOrgials; Lago_di_Alice_Superiore; Lago_di_Alserio; Lago_di_Ballone; Lago_di_Bertignano; Lago_di_Bolsena; Lago_di_Bracciano; Lago_di_Burano; Lago_di_Caldaro; Lago_di_Caldonazzo; Lago_di_Campo; Lago_di_Candia; Lago_di_Caselette; Lago_di_Cei; Lago_di_Comabbio; Lago_di_Fibreno; Lago_di_Fraturno; Lago_di_Ganna; Lago_di_Lases; Lago_di_Lavarone; Lago_di_Martignano; Lago_di_Meugliano; Lago_di_Mezzano; Lago_di_Monate; Lago_di_Moncrivello; Lago_di_Montorfano; Lago_di_Nemi; Lago_di_Paterno; Lago_di_Pojala; Lago_di_Rascino; Lago_di_San_Floriano; Lago_di_San_Michele; Lago_di_Santa_Colomba; Lago_di_SantAnna_di_Vinadio; Lago_di_Sibolla; Lago_di_Tovel; Lago_di_Valdurna; Lago_di_Varese; Lago_di_Varsi; Lago_di_Ventina; Lago_di_Vico; Lago_Fedaia; Lago_Gemini_inferiore; Lago_Ghirla; Lago_Giulianello; Lago_Grande_di_Avigliana; Lago_Grande_di_Monticchio-2; Lago_Idro; Lago_Lamar; Lago_Laudemio; Lago_Lauson; Lago_Lungo; Lago_Lusia_III; Lago_Madrano; Lago_Monticolo_Grande; Lago_Moregna; Lago_Padule_Cerretano; Lago_Pusiano; Lago_San_Puoto; Lago_Santo; Lago_Santo_Parmense; Lago_Santo_Terlago; Lago_Scuro_Cerretano; Lago_Scuro_delle_Agoraie; Lago_Scuro-Polverosa; Lago_Sfondato; Lago_Sirino; Lago_Sirio; Lago_Stellune; Lago_Trearie; Lago_Verde_del_Passo_del_Brattello; Lago_Viverone; Lago Albano, ALB; Lago Buse, BUSE; Lago Calamone, CAL; Lago Campagna, CAM; Lago Cece, CECE; Lago Colbricon inferiore, COLI; Lago Colbricon superiore, COLS; Lago Cornisello inferiore, COIN; Lago Cornisello superiore, COSU; Lago dellAccesa, ACC; Lago dellAquilente, AQUI; Lago delle Lame, LAM; Lago delle Trote, TROT; Lago dellOrgials, ORG; Lago del Segrino, SEG; Lago di Alice Superiore, ALI; Lago di Alserio, ALS; Lago di Ballone, BAL; Lago di Bertignano, BERT; Lago di Bolsena, BOLS; Lago di Bracciano, BRA; Lago di Burano, BUR; Lago di Caldaro, CALD; Lago di Caldonazzo, CA; Lago di Campo, PT 16; Lago di Candia, CAN; Lago di Caselette, CAS; Lago di Cei, CEI; Lago di Comabbio, COM; Lago di Fibreno, FIBR; Lago di Fraturno, FRAT; Lago di Ganna, GAN; Lago di Lases, LAS; Lago di Lavarone, LA; Lago di Martignano, MART; Lago di Meugliano, MEU; Lago di Mezzano, MEZ; Lago di Monate, MONA; Lago di Moncrivello, MOC; Lago di Montorfano, MON; Lago di Nemi, NEMI; Lago di Paterno, PAT; Lago di Pojala, PT 41; Lago di Rascino, RASC; Lago di San Floriano, SFLO; Lago di San Michele, LSM; Lago di Santa Colomba, SCOL; Lago di SantAnna di Vinadio, SANN; Lago di Sibolla, SIB; Lago di Tovel, TOV; Lago di Valdurna, VALD; Lago di Varese, VARE; Lago di Varsi, VAR; Lago di Ventina, VEN; Lago di Vico, VICO; Lago Fedaia, FED; Lago Gemini inferiore, GEMNF; Lago Ghirla, GHI; Lago Giulianello, GIUL; Lago Grande di Avigliana, AVG; Lago Grande di Monticchio, MONT 05/3A; Lago Idro, IDR; Lago Lamar, LAMR; Lago Laudemio, LL; Lago Lauson, LAUZ; Lagolo; Lagolo, LAG; Lago Lungo, LU; Lago Lusia III, LUSI; Lago Madrano, MADR; Lago Monticolo Grande, MGRA; Lago Moregna, MOR; Lago Padule Cerretano, PADC; Lago Pusiano, PUS; Lago San Puoto, SAP; Lago Santo (Cembra), SCEM; Lago Santo Parmense, SPA; Lago Santo Terlago, TERL; Lago Scuro Cerretano, SCER; Lago Scuro delle Agoraie (Lame), SCLA; Lago Scuro - Polverosa, SCPO; Lago Sfondato, PT 09; Lago Sirino, SI; Lago Sirio, SIR; Lago Stellune, STE; Lago Trearie, LT; Lago Verde del Passo del Brattello, VERD; Lago Viverone, VIV; Laguna_del_Faro; Laguna del Faro (Pantano Grande), LF; Lake; Larix; Latitude of event; Ligustrum; Lilium martagon-type; Linum austriacum-type; Liquidambar; Loiseleuria procumbens-type; Longitude of event; Lotus-type; Lythrum salicaria; Melampyrum; Mentha-type; Mercurialis; Minuartia rubra-type; Morus alba; Odontites-type; Olea; Onobrychis-type; Ononis-type; Ostrya-type; Pantano_Cuba; Pantano Cuba, PC; Papilionaceae; Peucedanum-type; Phillyrea; Picea; Pimpinella major-type; Pinus cembra; Pinus sylvestris-type; Pistacia; Plantago alpina-type; Plantago coronopus; Plantago lanceolata-type; Plantago major/media; Platanus; Polygonum amphibium; Polygonum aviculare; Polygonum viviparum; Polypodium vulgare-type; Populus; Potentilla-type; Primula farinosa; Primula veris-type; Prunus-type; Pteridium aquilinum; Pulsatilla; Quercus cerris-type; Quercus ilex-type; Quercus robur/Q. pubescens-type; Ranunculus acris-type; Rhamnus-type; Rhinanthus-type; Rhus group; Robinia pseudoacacia; Rosaceae; Rubiaceae; Rumex acetosa-type; Rumex acetosella-type; Sagina; Salix; Sambucus; Sample code/label; Sanguisorba minor ssp. minor; Sanguisorba officinalis; Saxifraga oppositifolia-type; Scrofulariaceae; Secale; Sedum; Senecio-type; Silene dioica-type; Silene vulgaris-type; Site; Solanum dulcamara; Solanum nigrum-type; Soldanella; Sorbus-type; Spores, monolete; Symphytum; Tamarix; Taxus; Thalictrum; Thesium humifusum; Tilia; Trifolium pratense-type; Trifolium repens-type; Trinia glauca-type; Trollius; Tsuga; Ulex-type; Ulmus; Umbelliferae; Urio_Quattrocchi; Urio Quattrocchi, UQ; Urtica pilulifera; Urtica urens; Vaccinium-type; Valeriana dioica-type; Valeriana officinalis-type; Veronica-type; Viburnum lantana; Vicia-type; Viscum; Vitis; Zea mays
    Type: Dataset
    Format: text/tab-separated-values, 17388 data points
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  • 8
    facet.materialart.
    Unknown
    PANGAEA
    In:  European Pollen Database (EPD)
    Publication Date: 2024-02-16
    Keywords: Depth, bottom/max; DEPTH, sediment/rock; Depth, top/min; EPD; KULC; KULLENBERG corer; Lithology/composition/facies; SO8923; Soppensee
    Type: Dataset
    Format: text/tab-separated-values, 3 data points
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  • 9
    facet.materialart.
    Unknown
    PANGAEA
    In:  European Pollen Database (EPD)
    Publication Date: 2024-02-16
    Keywords: Age, 14C calibrated; Calendar age; DEPTH, sediment/rock; EPD; KULC; KULLENBERG corer; SO8923; Soppensee
    Type: Dataset
    Format: text/tab-separated-values, 2 data points
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