ACER project members; Sanchez Goñi, Maria Fernanda; Desprat, Stéphanie; Daniau, Anne-Laure; Allen, Judy R M; Anderson, R Scott; Behling, Hermann; Bonnefille, Raymonde; Cheddadi, Rachid; Combourieu-Nebout, Nathalie; Dupont, Lydie M; Fletcher, William J; González, Catalina; Grigg, Laurie D; Grimm, Eric C; Hayashi, Ryoma; Helmens, Karin F; Hessler, Ines; Heusser, Linda E; Hooghiemstra, Henry; Huntley, Brian; Igarashi, Yaeko; Irino, Tomohisa; Jacobs, Bonnie Fine; Jiménez-Moreno, Gonzalo; Kawai, Sayuri; Kumon, Fujio; Lawson, Ian T; Lebamba, Judicael; Ledru, Marie-Pierre; Lézine, Anne-Marie; Liew, Ping-Mei; Londeix, Laurent; López-Martinez, Constancia; Magri, Donatella; Maley, Jean; Margari, Vasiliki; Marret, Fabienne; Müller, Ulrich C; Naughton, Filipa; Novenko, Elena Y; Oba, Tadamichi; Roucoux, Katherine H; Takahara, Hikaru; Tzedakis, Polychronis C; Vincens, Annie; Whitlock, Cathy L; Willard, Debra A; Yamamoto, Masanobu (2017): CLAM age model and biomes of sediment core Siberia1 [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.872819
Always quote citation above when using data! You can download the citation in several formats below.
Related to:
Fletcher, William J; Sanchez Goñi, Maria Fernanda; Allen, Judy R M; Cheddadi, Rachid; Combourieu-Nebout, Nathalie; Huntley, Brian; Lawson, Ian T; Londeix, Laurent; Magri, Donatella; Margari, Vasiliki; Müller, Ulrich C; Naughton, Filipa; Novenko, Elena Y; Roucoux, Katherine H; Tzedakis, Polychronis C (2010): Millennial-scale variability during the last glacial in vegetation records from Europe. Quaternary Science Reviews, 29(21-22), 2839-2864, https://doi.org/10.1016/j.quascirev.2009.11.015
Hessler, Ines; Dupont, Lydie M; Bonnefille, Raymonde; Behling, Hermann; González, Catalina; Helmens, Karin F; Hooghiemstra, Henry; Lebamba, Judicael; Ledru, Marie-Pierre; Lézine, Anne-Marie; Maley, Jean; Marret, Fabienne; Vincens, Annie (2010): Millennial-scale changes in vegetation records from tropical Africa and South America during the last glacial. Quaternary Science Reviews, 29(21-22), 2882-2899, https://doi.org/10.1016/j.quascirev.2009.11.029
Jiménez-Moreno, Gonzalo; Anderson, R Scott; Desprat, Stéphanie; Grigg, Laurie D; Grimm, Eric C; Heusser, Linda E; Jacobs, Bonnie Fine; López-Martinez, Constancia; Whitlock, Cathy L; Willard, Debra A (2010): Millennial-scale variability during the last glacial in vegetation records from North America. Quaternary Science Reviews, 29(21-22), 2865-2881, https://doi.org/10.1016/j.quascirev.2009.12.013
Sanchez Goñi, Maria Fernanda; Desprat, Stéphanie; Daniau, Anne-Laure; Bassinot, Franck C; Polanco-Martínez, Josué M; Harrison, Sandy P; Allen, Judy R M; Anderson, R Scott; Behling, Hermann; Bonnefille, Raymonde; Burjachs, Francesc; Carrión, José S; Cheddadi, Rachid; Clark, James S; Combourieu-Nebout, Nathalie; Courtney-Mustaphi, Colin J; DeBusk, Georg H; Dupont, Lydie M; Finch, Jemma M; Fletcher, William J; Giardini, Marco; González, Catalina; Gosling, William D; Grigg, Laurie D; Grimm, Eric C; Hayashi, Ryoma; Helmens, Karin F; Heusser, Linda E; Hill, Trevor R; Hope, Geoffrey; Huntley, Brian; Igarashi, Yaeko; Irino, Tomohisa; Jacobs, Bonnie Fine; Jiménez-Moreno, Gonzalo; Kawai, Sayuri; Kershaw, A Peter; Kumon, Fujio; Lawson, Ian T; Ledru, Marie-Pierre; Lézine, Anne-Marie; Liew, Ping-Mei; Magri, Donatella; Marchant, Robert; Margari, Vasiliki; Mayle, Francis E; McKenzie, G Merna; Moss, Patrick T; Müller, Stefanie; Müller, Ulrich C; Naughton, Filipa; Newnham, Rewi M; Oba, Tadamichi; Pérez-Obiol, Ramon P; Pini, Roberta; Ravazzi, Cesare; Roucoux, Katherine H; Rucina, Stephen M; Scott, Louis; Takahara, Hikaru; Tzedakis, Polychronis C; Urrego, Dunia H; van Geel, Bas; Valencia, Bryan G; Vandergoes, Marcus J; Vincens, Annie; Whitlock, Cathy L; Willard, Debra A; Yamamoto, Masanobu (2017): The ACER pollen and charcoal database: a global resource to document vegetation and fire response to abrupt climate changes during the last glacial period. Earth System Science Data, 9(2), 679-695, https://doi.org/10.5194/essd-9-679-2017
Takahara, Hikaru; Igarashi, Yaeko; Hayashi, Ryoma; Kumon, Fujio; Liew, Ping-Mei; Yamamoto, Masanobu; Kawai, Sayuri; Oba, Tadamichi; Irino, Tomohisa (2010): Millennial-scale variability in vegetation records from the East Asian Islands: Taiwan, Japan and Sakhalin. Quaternary Science Reviews, 29(21-22), 2900-2917, https://doi.org/10.1016/j.quascirev.2009.11.026
Project(s):
Coverage:
Latitude: -17.090000 * Longitude: -64.720000
Minimum DEPTH, sediment/rock: 0.010 m * Maximum DEPTH, sediment/rock: 7.420 m
Parameter(s):
# | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
---|---|---|---|---|---|---|
1 | DEPTH, sediment/rock | Depth sed | m | Geocode | ||
2 | Calendar age, minimum/young | Cal age min | ka BP | Sanchez Goñi, Maria Fernanda | Classical age-modeling approach, CLAM (Blaauw, 2010) | CLAM_min95 |
3 | Calendar age, maximum/old | Cal age max | ka BP | Sanchez Goñi, Maria Fernanda | Classical age-modeling approach, CLAM (Blaauw, 2010) | CLAM_max95 |
4 | Calendar age | Cal age | ka BP | Sanchez Goñi, Maria Fernanda | Classical age-modeling approach, CLAM (Blaauw, 2010) | CLAM_best |
5 | Accumulation model | Accu model | a/cm | Sanchez Goñi, Maria Fernanda | Classical age-modeling approach, CLAM (Blaauw, 2010) | |
6 | Type of age model | Age model type | Sanchez Goñi, Maria Fernanda | |||
7 | Sample ID | Sample ID | Sanchez Goñi, Maria Fernanda | ACER sample ID | ||
8 | Pollen, temperate mountain forest | Pollen te mountain forest | % | Sanchez Goñi, Maria Fernanda | ||
9 | Pollen, warm-temperate forest | Pollen wte forest | % | Sanchez Goñi, Maria Fernanda | ||
10 | Pollen, tropical forest | Pollen tr forest | % | Sanchez Goñi, Maria Fernanda |
License:
Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC-BY-NC-ND-3.0)
Size:
363 data points
Data
1 Depth sed [m] | 2 Cal age min [ka BP] | 3 Cal age max [ka BP] | 4 Cal age [ka BP] | 5 Accu model [a/cm] | 6 Age model type | 7 Sample ID | 8 Pollen te mountain forest [%] | 9 Pollen wte forest [%] | 10 Pollen tr forest [%] |
---|---|---|---|---|---|---|---|---|---|
0.010 | 8872 | 51.389 | 22.917 | 82.292 | |||||
0.140 | 8873 | 18.443 | 14.344 | 90.984 | |||||
0.200 | 8874 | 29.655 | 12.414 | 91.034 | |||||
0.220 | 8875 | 28.173 | 13.003 | 89.164 | |||||
0.320 | 8876 | 30.279 | 18.725 | 85.657 | |||||
0.430 | 8877 | 33.799 | 18.715 | 79.330 | |||||
0.530 | 8878 | 38.462 | 33.333 | 84.615 | |||||
0.760 | 8879 | 49.796 | 25.714 | 81.224 | |||||
0.890 | 11.26190 | 11.47160 | 11.36950 | 176.085 | Linear interpolation | 8880 | 62.951 | 21.639 | 47.541 |
0.990 | 12.85900 | 13.11750 | 12.98070 | 76.342 | Linear interpolation | 8881 | 79.394 | 41.818 | 43.333 |
1.070 | 13.41070 | 13.74520 | 13.59140 | 76.342 | Linear interpolation | 8882 | 73.734 | 37.025 | 44.620 |
1.180 | 14.08540 | 14.67830 | 14.43120 | 76.342 | Linear interpolation | 8883 | 78.696 | 46.087 | 35.000 |
1.430 | 16.84620 | 17.19890 | 17.04020 | 110.512 | Linear interpolation | 8885 | 59.375 | 50.000 | 42.188 |
1.520 | 17.87970 | 18.16580 | 18.03490 | 110.512 | Linear interpolation | 8886 | 73.204 | 45.856 | 36.188 |
1.620 | 18.74570 | 19.03780 | 18.90440 | 58.160 | Linear interpolation | 8887 | 71.256 | 42.271 | 38.164 |
1.740 | 19.45670 | 19.72830 | 19.60230 | 58.160 | Linear interpolation | 8888 | 68.912 | 46.632 | 38.601 |
1.850 | 20.09950 | 20.37190 | 20.24210 | 58.160 | Linear interpolation | 8889 | 55.328 | 52.869 | 47.131 |
2.060 | 21.27690 | 21.62530 | 21.46340 | 58.160 | Linear interpolation | 8891 | 20.765 | 24.044 | 79.781 |
2.150 | 21.77450 | 22.17020 | 21.98690 | 58.160 | Linear interpolation | 8892 | 42.508 | 42.508 | 58.410 |
2.260 | 22.37970 | 22.84080 | 22.62660 | 58.160 | Linear interpolation | 8893 | 42.085 | 42.471 | 60.618 |
2.370 | 22.98010 | 23.51430 | 23.26640 | 58.160 | Linear interpolation | 8894 | 47.003 | 49.211 | 50.789 |
2.480 | 23.55700 | 24.04890 | 23.82010 | 45.872 | Linear interpolation | 8895 | 60.725 | 46.828 | 41.994 |
2.620 | 24.26300 | 24.64530 | 24.46230 | 45.872 | Linear interpolation | 8896 | 42.424 | 46.465 | 62.626 |
2.710 | 24.70390 | 25.05270 | 24.87520 | 45.872 | Linear interpolation | 8897 | 30.153 | 33.206 | 70.992 |
2.920 | 25.66480 | 26.07570 | 25.83850 | 45.872 | Linear interpolation | 8899 | 54.724 | 51.969 | 53.150 |
3.030 | 26.05020 | 26.47430 | 26.22780 | 22.810 | Linear interpolation | 8900 | 34.118 | 34.510 | 64.314 |
3.120 | 26.27620 | 26.64680 | 26.43300 | 22.810 | Linear interpolation | 8901 | 51.341 | 47.893 | 55.172 |
3.230 | 26.54140 | 26.86540 | 26.68390 | 22.810 | Linear interpolation | 8902 | 42.088 | 41.414 | 61.616 |
3.340 | 26.80050 | 27.09500 | 26.93490 | 22.810 | Linear interpolation | 8903 | 28.188 | 44.295 | 82.550 |
3.640 | 27.45130 | 27.78630 | 27.61910 | 22.810 | Linear interpolation | 8906 | 42.021 | 43.617 | 62.766 |
4.020 | 31.59680 | 32.43620 | 31.90150 | 32.663 | Linear interpolation | 8910 | 37.555 | 30.131 | 73.799 |
4.110 | 31.89600 | 32.63280 | 32.19550 | 32.663 | Linear interpolation | 8911 | 34.855 | 35.685 | 64.730 |
4.220 | 32.22290 | 32.90640 | 32.55470 | 32.663 | Linear interpolation | 8912 | 40.741 | 23.906 | 77.441 |
4.310 | 32.46670 | 33.17840 | 32.84870 | 32.663 | Linear interpolation | 8913 | 57.186 | 32.934 | 64.072 |
4.400 | 32.69640 | 33.50530 | 33.14270 | 32.663 | Linear interpolation | 8914 | 46.403 | 23.381 | 72.662 |
4.510 | 8915 | 57.801 | 24.823 | 62.411 | |||||
4.600 | 8916 | 60.245 | 29.052 | 68.502 | |||||
4.710 | 8917 | 61.584 | 27.566 | 66.569 | |||||
4.800 | 8918 | 64.213 | 33.756 | 60.914 | |||||
4.910 | 8919 | 67.890 | 29.052 | 65.443 | |||||
5.000 | 8920 | 53.516 | 21.875 | 72.656 | |||||
5.220 | 8921 | 58.621 | 29.502 | 67.050 | |||||
5.340 | 8922 | 47.887 | 22.183 | 74.648 | |||||
5.450 | 8923 | 49.521 | 19.169 | 68.051 | |||||
5.560 | 8924 | 50.962 | 26.282 | 66.667 | |||||
5.670 | 8925 | 43.986 | 20.275 | 66.667 | |||||
5.790 | 8926 | 67.925 | 38.208 | 47.406 | |||||
5.900 | 8927 | 46.429 | 17.411 | 73.214 | |||||
6.010 | 8928 | 44.817 | 26.220 | 65.854 | |||||
6.560 | 8929 | 49.438 | 26.217 | 74.157 | |||||
6.690 | 8930 | 44.838 | 21.829 | 79.056 | |||||
6.790 | 8931 | 48.679 | 41.132 | 57.736 | |||||
6.980 | 8932 | 49.083 | 32.569 | 61.239 | |||||
7.100 | 8933 | 28.409 | 14.015 | 89.015 | |||||
7.210 | 8934 | 48.985 | 40.609 | 70.051 | |||||
7.320 | 8935 | 39.643 | 25.714 | 71.786 | |||||
7.420 | 8936 | 50.445 | 27.596 | 64.392 |