PANGAEA_989985 Pollen-based summer and winter Holocene palaeoclimate reconstruction of the Lago Grande di Monticchio (Italy) d'Oliveira, Léa; Maignan, Adrien; Peyron, Odile; Joannin, Sébastien; Combourieu-Nebout, Nathalie; Genet, Marion; Lestienne, Marion; Dugerdil, Lucas; Fernandez, Giada; Giaccio, Biagio; Monaco, Lorenzo; Nomade, Sébastien; Pereira, Alison; Scao, Vincent; Regnier, Edouard; Balasse, Marie; Ménot, Guillemette Pollen-based summer and winter Holocene palaeoclimate reconstruction of the Lago Grande di Monticchio (Italy) 2026-02-13 PANGAEA Dataset https://doi.pangaea.de/10.1594/PANGAEA.989985 Investigator Adrien Maignan adrien.maignan@hotmail.fr Investigator Léa d'Oliveira lea.d-oliveira@umontpellier.fr Earth Science Uniform resource locator/link to reference Identification DEPTH, sediment/rock Calendar age Temperature, air, annual mean Temperature, air, summer, June-August Temperature, air, winter, December-February Precipitation, annual mean Precipitation, summer, June-August Precipitation, winter, December-February geoscientificInformation brGDGTs Drilling/coring Holocene Italy MONTI23-II Paleoclimate reconstructions Pollen Boosted Regression Trees (BRT), according to Salonen et al. (2012) Modern Analogue Technique (MAT), according to Guiot (1990) Random Forests (RF) method, according to Breiman et al. (2001) Weighted averaging partial least squares regression (WA-PLS) method, according to ter Braak and Juggins (1993) Weighted average 2023-05-31 2023-05-31 Complete 40.9296 40.9296 15.605699 15.605699 0.05 m (DEPTH, sediment/rock) 8.145 m (DEPTH, sediment/rock) unrestricted CC-BY-4.0: Creative Commons Attribution 4.0 International English PANGAEA Data Publisher for Earth & Environmental Science https://www.pangaea.de/ Data Center Contact Michael Diepenbroek info@pangaea.de

Leobener Str.

Bremen Bremen 28359 Germany online 3094 data points text/tab-separated-values d'Oliveira, Léa; Maignan, Adrien; Peyron, Odile; Joannin, Sébastien; Combourieu-Nebout, Nathalie; Genet, Marion; Lestienne, Marion; Dugerdil, Lucas; Fernandez, Giada; Giaccio, Biagio; Monaco, Lorenzo; Nomade, Sébastien; Pereira, Alison; Scao, Vincent; Regnier, Edouard; Balasse, Marie; Ménot, Guillemette (submitted): North–south Holocene seasonal contrast on the Italian peninsula: clarification of the latitudinal transition zone based on the multi-proxy study of Lago Grande di Monticchio. Quaternary Science Reviews Allen, Judy R M; Huntley, Brian; Watts, William A (2021): Lago Grande di Monticchio pollen dataset (Version 1.1) [Dataset] [dataset]. Neotoma Paleoecology Database, https://doi.org/10.21233/KVNC-0856 Breiman, Leo (2001): Random Forests. Machine Learning, 45(1), 5-32, https://doi.org/10.1023/A:1010933404324 Guiot, Joel (1990): Methodology of the last climatic cycle reconstruction in France from pollen data. Palaeogeography, Palaeoclimatology, Palaeoecology, 80(1), 49-69, https://doi.org/10.1016/0031-0182(90)90033-4 Salonen, J Sakari; Seppä, Heikki; Luoto, Miska; Bjune, Anne Elisabeth; Birks, H John B (2012): A North European pollen–climate calibration set: analysing the climatic responses of a biological proxy using novel regression tree methods. Quaternary Science Reviews, 45, 95-110, https://doi.org/10.1016/j.quascirev.2012.05.003 ter Braak, Cajo J F; Juggins, Steve (1993): Weighted averaging partial least squares regression (WA-PLS): an improved method for reconstructing environmental variables from species assemblages. Hydrobiologia, 269-270(1), 485-502, https://doi.org/10.1007/BF00028046

This dataset contains raw annual, summer and winter palaeoclimate (temperature and precipitation) quantitative reconstructions of Lago Grande di Monticchio sedimentary record. The pollen fossil record (Site name: MONTICCHIO; doi:10.21233/KVNC-0856) was extracted from the Neotoma Paleoecology Database (https://www.neotomadb.org/). Palaeoclimate reconstructions are based on four different methods: Modern Analogue Technique (MAT; Guiot 1990), Weighted Averaging Partial Least Squares (WA-PLS; ter Braak and Juggins 1993), Boosted Regression Trees (BRT; Salonen et al. 2012) and Random Forest (RF; Breiman et al. 2001). In addition, the method-weighted average palaeoclimate signal is provided. Depth is expressed in meters (m), age in kilo years calibrated Before Present (ka cal BP), temperatures in degrees Celsius (°C) and precipitation in millimetres (mm). ** For all details see the full metadata description at "https://doi.pangaea.de/10.1594/PANGAEA.989985"!

https://doi.org/10.1007/BF00028046 Weighted averaging partial least squares regression (WA-PLS): an improved method for reconstructing environmental variables from species assemblages https://doi.org/10.1007/BF00028046 Weighted averaging partial least squares regression (WA-PLS) method, according to ter Braak and Juggins (1993) https://doi.org/10.1016/0031-0182(90)90033-4 Methodology of the last climatic cycle reconstruction in France from pollen data https://doi.org/10.1016/0031-0182(90)90033-4 Modern Analogue Technique (MAT), according to Guiot (1990) https://doi.org/10.1016/j.quascirev.2012.05.003 A North European pollen–climate calibration set: analysing the climatic responses of a biological proxy using novel regression tree methods https://doi.org/10.1016/j.quascirev.2012.05.003 Boosted Regression Trees (BRT), according to Salonen et al. (2012) https://doi.org/10.1023/A:1010933404324 Random Forests https://doi.org/10.1023/A:1010933404324 Random Forests (RF) method, according to Breiman et al. (2001) https://doi.org/10.21233/KVNC-0856 Lago Grande di Monticchio pollen dataset (Version 1.1) [Dataset] DIF 9.4 2026-02-13 2026-07-15