Pollen data from surface-sediment samples from 92 lakes in Italy, 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

• Main Authors: Finsinger, Walter, Heiri, Oliver, Valsecchi, Verushka, Tinner, Willy, Lotter, André F
• Format: Dataset
• Language: English
• Published: PANGAEA - Data Publisher for Earth & Environmental Science 2018
• Subjects: Event label; Latitude of event; Longitude of event; Date/Time of event; Lake; Site; Identification; Sample code/label; DEPTH, sediment/rock; Depth, top/min; Depth, bottom/max; Abies; Acer; Aesculus; Alnus glutinosa-type; Alnus viridis; Amorpha fruticosa; Arbutus-type; Betula; Buxus; Calluna vulgaris; Carpinus; Castanea sativa; Celtis; Chamaerops humilis; Cistus crispus-type; Cistus salvifolius; Cornus mas; Cornus sanguinea; Corylus avellana; Cedrus; Cryptomeria-type; Elaeagnus; Empetrum-type; Ephedra distachya-type; Ephedra fragilis-type; Ericaceae; Erica arborea-type; Eucalyptus; Fagus; Frangula alnus; Fraxinus excelsior; Fraxinus ornus; Ulex-type; Hedera-type; Juglans; Juniperus; Larix; Ligustrum; Liquidambar; Loiseleuria procumbens-type; Olea; Ostrya-type; Phillyrea; Picea; Pinus cembra; Pinus sylvestris-type; Pistacia; Platanus; Populus; Prunus-type; Quercus cerris-type; Quercus robur/Q. pubescens-type; Quercus ilex-type; Rhamnus-type; Rhus group; Robinia pseudoacacia; Salix; Sambucus; Sorbus-type; Tamarix; Taxus; Tilia; Tsuga; Ulmus; Vaccinium-type; Viburnum lantana; Viscum; Vitis; Achillea-type; Aconitum; Aethusa cynapium-type; Alchemilla-type; Allium-type; Ambrosia-type; Anemone hortensis; Anemone nemorosa-type; Anthericum-type; Anthriscus sylvestris-type; Apium inundatum-type; Artemisia; Bupleurum-type; Caltha-type; Campanula; Caryophyllaceae; Centaurea nigra-type; Centaurea solstitialis; Cerastium cerastioides-type; Cerastium fontanum-type; Cerealia; Chaerophyllum hirsutum-type; Chenopodiaceae-type; Cirsium; Clematis group; Asteroideae; Cichorioideae; Crassula; Cruciferae; Dianthus-type; Echium; Euphorbia; Falcaria vulgaris-type; Fallopia convolvulus-type; Filipendula; Gentiana pneumonanthe-type; Geranium; Gramineae; Gypsophila repens-type; Helianthemum; Helleborus viridis; Heracleum-type; Humulus lupulus; Humulus-type; Hypericum perforatum-type; Linum austriacum-type; Lilium martagon-type; Lotus-type; Lythrum salicaria; Mentha-type; Melampyrum; Mercurialis; Minuartia rubra-type; Morus alba; Odontites-type; Onobrychis-type; Ononis-type; Papilionaceae; Peucedanum-type; Pimpinella major-type; Plantago alpina-type; Plantago coronopus; Plantago lanceolata-type; Plantago major/media; Polygonum aviculare; Polygonum amphibium; Polygonum viviparum; Potentilla-type; Primula farinosa; Primula veris-type; Pulsatilla; Ranunculus acris-type; Rhinanthus-type; Rosaceae; Rubiaceae; Rumex acetosa-type; Rumex acetosella-type; Sagina; Sanguisorba officinalis; Sanguisorba minor ssp. minor; Saxifraga oppositifolia-type; Scrofulariaceae; Secale; Sedum; Senecio-type; Silene dioica-type; Silene vulgaris-type; Solanum dulcamara; Solanum nigrum-type; Soldanella; Symphytum; Thalictrum; Thesium humifusum; Trifolium pratense-type; Trifolium repens-type; Trinia glauca-type; Trollius; Umbelliferae; Urtica pilulifera; Urtica urens; Valeriana dioica-type; Valeriana officinalis-type; Veronica-type; Vicia-type; Zea mays; Asplenium-type; Athyrium filix-femina; Botrychium; Cryptogramma crispa; Cystopteris fragilis; Dryopteris filix-mas-type; Huperzia selago; Spores, monolete; Polypodium vulgare-type; Pteridium aquilinum; HON-Kajak sediment corer; Gravity corer; Gravity corer, UWITEC; Rhamnus; Saxifraga oppositifolia
• Online Access: https://dx.doi.org/10.1594/pangaea.895780; https://doi.pangaea.de/10.1594/PANGAEA.895780

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.