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Assessing the Importance of Climate Variables for the Spatial Distribution of Modern Pollen Data in China

Published online by Cambridge University Press:  20 January 2017

Jianyong Li ,
Qinghai Xu ,
Zhuo Zheng ,
Houyuan Lu ,
Yunli Luo ,
Yuecong Li ,
Chunhai Li  and
Heikki Seppä
Jianyong Li
Affiliation:
Department of Geosciences and Geography, University of Helsinki, Gustaf Hällströmin katu 2a, P.O. Box 64, Helsinki 00014, Finland
Qinghai Xu*
Affiliation:
Institute of Nihewan Archaeology Research, Hebei Normal University, East Road of Southern 2nd Ring, Shijiazhuang 050024, China College of Resources and Environment Science, Hebei Normal University, East Road of Southern 2nd Ring, Shijiazhuang 050024, China Hebei Key Laboratory of Environmental Change and Ecological Construction, Hebei Normal University, East Road of Southern 2nd Ring, Shijiazhuang 050024, China MOE Key Laboratory of Western China's Environmental System, Lanzhou University, Southern Tianshui Road, Lanzhou 730000, China
Zhuo Zheng
Affiliation:
Department of Earth Sciences, Sun Yat-sen University, Xingang Xi Road, Guangzhou 510275, China
Houyuan Lu
Affiliation:
Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beitucheng Western Road, Beijing 100029, China
Yunli Luo
Affiliation:
Institute of Botany, Chinese Academy of Sciences, Xiangshan Nanxincun, Beijing 100093, China
Yuecong Li
Affiliation:
College of Resources and Environment Science, Hebei Normal University, East Road of Southern 2nd Ring, Shijiazhuang 050024, China Hebei Key Laboratory of Environmental Change and Ecological Construction, Hebei Normal University, East Road of Southern 2nd Ring, Shijiazhuang 050024, China
Chunhai Li
Affiliation:
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, East Beijing Road, Nanjing 210008, China
Heikki Seppä
Affiliation:
Department of Geosciences and Geography, University of Helsinki, Gustaf Hällströmin katu 2a, P.O. Box 64, Helsinki 00014, Finland
*
*Corresponding author at: East Road of Southern 2nd Ring, Shijiazhuang 050024, Hebei Province, China., E-mail address:[email protected] (Q. Xu).
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Abstract

To assess the importance of climate variables for the distribution of modern pollen data in China, we present a continental-scale dataset consisting of 1374 samples. Boosted regression trees and constrained ordination techniques are employed to quantify the importance of six climate variables (annual precipitation, PANN; actual/potential evapotranspiration ratio, Alpha; mean annual temperature, TANN; mean temperature of the warmest month, MTWA; mean temperature of the coldest month, MTCO; annual sum of the growing degree days above 5°C, GDD5) for the distribution of individual pollen taxa and modern pollen assemblages. The results show that taxon-specific responses to the climate variables display a wide regional diversity and that the climate variables with low collinearity that best account for the spatial variability of modern pollen assemblages differ regionally. PANN is the most important variable in northwestern and northeastern China and the Tibetan Plateau, while MTWA and MTCO are the dominant variables in east-central and southern China. This suggests that the climate variables that can be optimally reconstructed from fossil pollen data vary in different bioclimatic regions of China. This feature is typical to many continental-scale modern pollen datasets and needs to be considered in pollen-based climate reconstructions.

Keywords

Constrained ordination techniquesBoosted regression treesSpatial distributionClimate variablesClimate reconstructionsModern pollen dataChina
Type
Research Article
Information
Quaternary Research , Volume 83 , Issue 2 , March 2015 , pp. 287 - 297
Copyright
University of Washington

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References

Aertsen, W., Kint, V., De Vos, B., Deckers, J., Van Orshoven, J., and Muys, B. (2011). Predicting forest site productivity in temperate lowland from forest floor, soil and litterfall characteristics using boosted regression trees. Plant and Soil 354, 157–172.Google Scholar
Bartlein, P.J., Harrison, S.P., Brewer, S., Connor, S., Davis, B.A.S., Gajewski, K., Guiot, J., Harrison-Prentice, T.I., Henderson, A., Peyron, O., Prentice, I.C., Scholze, M., Sepp", H., Shuman, B., Sugita, S., Thompson, R.S., Viau, A.E., Williams, J., and Wu, H. (2011). Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis. Climate Dynamics 37, 775–802.Google Scholar
Birks, H.J.B. (1995). Quantitative palaeoenvironmental reconstructions. Maddy, D., Brew, J.S. Statistical Modelling of Quaternary Science Data Technical Guide 5 Quaternary Research Association, Cambridge.161–254.Google Scholar
Birks, H.J.B. (1998). Numerical tools in palaeolimnology: progress, potentialities, and problems. Journal of Paleolimnology 20, 307–332.Google Scholar
Birks, H.J.B., Heiri, O., Sepp", H., and Bjune, A.E. (2010). Strengths and weaknesses of quantitative climate reconstructions based on late-Quaternary biological proxies. The Open Ecology Journal 3, 68–110.CrossRefGoogle Scholar
Borcard, D., Legendre, P., and Drapeau, P. (1992). Partialling out the spatial component of ecological variation. Ecology 73, 1045–1055.Google Scholar
Chakona, A., and Swartz, E.R. (2012). Contrasting habitat associations of imperilled endemic stream fishes from a global biodiversity hot spot. BMC Ecology 12, 19.Google Scholar
Chang, D.H.S. (1983). The Tibetan Plateau in relation to the vegetation of China. Annals of Missouri Botanical Garden 70, 564–570.CrossRefGoogle Scholar
Cour, P. (1974). Nouvelles techniques de d"tection des flux et des retomb"es polliniques: "tude de la s"dimentation des pollens et des spores " la surface du sol. Pollen et Spores 16, 103–142.Google Scholar
Cour, P., Zheng, Z., Duzer, D., Calleja, M., and Yao, Z. (1999). Vegetation and climatic significance of modern pollen rain in northern and western Tibet. Review of Palaeobotany and Palynology 104, 183–204.CrossRefGoogle Scholar
Davis, B.A.S., Brewer, S., Stevenson, A.C., Guiot, J., and Contributors, Data (2003). The temperature of Europe during the Holocene reconstructed from pollen data. Quaternary Science Reviews 22, 1701–1716.Google Scholar
Davis, B.A.S., Zanon, M., Collins, P., Mauri, A., Bakker, J., Barboni, D., Barthelmes, A., Beaudouin, C., Bjune, A.E., Bozilova, E., Bradshaw, R.H.W., Brayshay, B.A., Brewer, S., Brugiapaglia, E., Bunting, J., Connor, S.E., Beaulieu, J.-L., Edwards, K., Ejarque, A., Fall, P., Florenzano, A., Fyfe, R., Galop, D., Giardini, M., Giesecke, T., Grant, M.J., Guiot, J., Jahns, S., Jankovsk", V., Juggins, S., Kahrmann, M., Karpi"ska-Ko?aczek, M., Ko?aczek, P., K"hl, N., Kune", P., Lapteva, E.G., Leroy, S.A.G., Leydet, M., L"pez S"ez, J.A., Masi, A., Matthias, I., Mazier, F., Meltsov, V., Mercuri, A.M., Miras, Y., Mitchell, F.J.G., Morris, J.L., Naughton, F., Nielsen, A.B., Novenko, E., Odgaard, B., Ortu, E., Overballe-Petersen, M.V., Pardoe, H.S., Peglar, S.M., Pidek, I.A., Sadori, L., Sepp", H., Severova, E., Shaw, H., ?wi"ta-Musznicka, J., Theuerkauf, M., Tonkov, S., Veski, S., Knaap, W.O., Leeuwen, J.F.N., Woodbridge, J., Zimny, M., and Kaplan, J.O. (2013). The European Modern Pollen Database (EMPD) project. Vegetation History and Archaeobotany 22, 521–530.CrossRefGoogle Scholar
De'ath, G. ('ath, 2007). ), Boosted trees for ecological modeling and prediction. Ecology 88, 243–251.Google Scholar
Domr"s, M., and Peng, G. (1988). The Climate of China. Springer Verlag, Berlin.Google Scholar
Elith, J., Graham, C.H., Anderson, R.P., Dud"k, M., Ferrier, S., Guisan, A., Hijmans, R.J., Huettmann, F., Leathwick, J.R., Lehmann, A., Li, J., Lohmann, L.G., Loiselle, B.A., Manion, G., Moritz, C., Nakamura, M., Nakazawa, Y., Overton, M.C.J., Peterson, A.T., Phillips, S.J., Richardson, K.S., Scachetti-Pereira, R., Schapire, R.E., Sober"n, J., Williams, S., Wisz, M.S., and Zimmermann, N.E. (2006). Novel methods improve prediction of species' distributions from occurrence data. Ecography 29, 129–151.CrossRefGoogle Scholar
Elith, J., Leathwick, J.R., and Hastie, T. (2008). A working guide to boosted regression trees. Journal of Animal Ecology 77, 802–813.Google Scholar
Fang, J.Y., Song, Y.C., Liu, H.Y., and Piao, S.L. (2002). Vegetation"climate relationship and its application in the division of vegetation zone in China. Acta Botanica Sinica 44, 1105–1122.Google Scholar
Finsinger, W., Heiri, O., Valsecchi, V., Tinner, W., and Lotter, A.F. (2007). Modern pollen assemblages as climate indicators in southern Europe. Global Ecology and Biogeography 16, 567–582.Google Scholar
Fr"chette, B., de Vernal, A., Guiot, J., Wolfe, A.P., Miller, G.H., Fredskild, B., Kerwin, M.W., and Richard, P.J.H. (2008). Methodological basis for quantitative reconstruction of air temperature and sunshine from pollen assemblages in Arctic Canada and Greenland. Quaternary Science Reviews 27, 1197–1216.Google Scholar
Friedman, J.H. (2001). Greedy function approximation: a gradient boosting machine. Annals of Statistics 29, 1189–1232.CrossRefGoogle Scholar
Gajewski, K., L"zine, A.M., Vincens, A., Delestan, A., Sawada, M., the African Pollen Database, (2002). Modern climate"vegetation"pollen relations in Africa and adjacent areas. Quaternary Science Reviews 21, 1611–1631.CrossRefGoogle Scholar
Gil-Romera, G., Neumann, F.H., Scott, L., Sevilla-Callejo, M., and Fern"ndez-Jalvo, Y. (2014). Pollen taphonomy from hyaena scats and coprolites: preservation and quantitative differences. Journal of Archaeological Science 46, 89–95.Google Scholar
Guiot, J., Wu, H., Jiang, W.Y., and Luo, Y.L. (2008). East Asian Monsoon and paleoclimatic data analysis: a vegetation point of view. Climate of the Past 4, 137–145.CrossRefGoogle Scholar
Guisan, A., Weiss, S.B., and Weiss, A.D. (1999). GLM versus CCA spatial modeling of plant species distribution. Plant Ecology 143, 107–122.Google Scholar
Harrison, S.P., Prentice, I.C., Sutra, J.-P., Barboni, D., Kohfeld, K.E., and Ni, J. (2009). Towards a global scheme of plant functional types for ecosystem modelling, palaeoecology and climate impact research. Journal of Vegetation Science 21, 300–317.Google Scholar
Heikkinen, R.K., Luoto, M., Virkkala, R., and Rainio, K. (2004). Effects of habitat cover, landscape structure and spatial variables on the abundance of birds in an agricultural-forest mosaic. Journal of Applied Ecology 41, 824–835.Google Scholar
Herzschuh, U., Kramer, A., Mischke, S., and Zhang, C.J. (2009). Quantitative climate and vegetation trends since the late glacial on the northeastern Tibetan Plateau deduced from Koucha Lake pollen spectra. Quaternary Research 71, 162–171.CrossRefGoogle Scholar
Herzschuh, U., Birks, H.J.B., Mischke, S., Zhang, C.J., and B"hner, J. (2010). A modern pollen"climate calibration set based on lake sediments from the Tibetan Plateau and its application to a Late Quaternary pollen record from the Qilian Mountains. Journal of Biogeography 37, 752–766.Google Scholar
Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., and Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25, 1965–1978.Google Scholar
Hijmans, R.J., Phillips, S.J., Leathwick, J.R., and Elith, J. (2012). R package "dismo": species distribution modeling, Version 0.7-23. http://CRAN.R-462project.org/package=dismo.Google Scholar
Hou, H.Y. (1983). Vegetation of China with reference to its geographical distribution. Annals of the Missouri Botanical Garden 70, 509–549.Google Scholar
Hou, X. (2001). Vegetation Atlas of China. Science Press, Beijing.Google Scholar
Jiang, W.Y., Guo, Z.T., Sun, X.J., Wu, H.B., Chu, G.Q., Yuan, B.Y., Hatt", C., and Guiot, J. (2006). Reconstruction of climate and vegetation changes of Lake Bayanchagan (Inner Mongolia): holocene variability of the East Asian monsoon. Quaternary Research 65, 411–420.Google Scholar
Jiang, W.Y., Guiot, J., Chu, G.Q., Wu, H.B., Yuan, B.Y., Hatt", C., and Guo, Z.T. (2010). An improved methodology of the modern analogues technique for palaeoclimate reconstruction in arid and semi-arid regions. Boreas 39, 145–153.CrossRefGoogle Scholar
Juggins, S. (2013). Quantitative reconstructions in palaeolimnology: new paradigm or sick science?. Quaternary Science Reviews 64, 20–32.Google Scholar
Juggins, S., and Birks, H.J.B. (2012). Quantitative environmental reconstructions from biological data. Birks, H.J.B., Lotter, A.F., Juggins, S., Smol, J.P. Tracking environmental change using lake sediments Data Handling and Numerical Techniques. 5, Springer, Dordrecht.431–494.Google Scholar
Kennedy, P. (1992). A Guide to Econometrics. Blackwell, Oxford.Google Scholar
Kint, V., Vansteenkiste, D., Aertsen, W., De Vos, B., Bequet, R., Van Acker, J., and Muys, B. (2012). Forest structure and soil fertility determine internal stem morphology of Pedunculate oak"a modelling approach using Boosted Regression Trees. European Journal of Forest Research 131, 609–622.Google Scholar
Klemm, A., Herzschuh, U., Pisaric, M.F.J., Telford, R.J., Heim, B., and Pestryakova, L.A. (2013). A pollen"climate transfer function from the tundra and taiga vegetation in arctic Siberia and its applicability to a Holocene record. Palaeogeography, Palaeoclimatology, Palaeoecology 386, 702–713.Google Scholar
Legendre, P., and Birks, H.J.B. (2012). Chapter 8: From classical to canonical ordination. Birks, H.J.B., Lotter, A.F., Juggins, S., Smol, J.P. Tracking Environmental Change Using Lake Sediments: Data Handling and Numerical Techniques Springer, Dordrecht.201–248.Google Scholar
Li, Y.C., Xu, Q.H., Yang, X.L., Chen, H., and Lu, X.M. (2005). Pollen"vegetation relationship and pollen preservation on the Northeastern Qinghai"Tibetan Plateau. Grana 44, 160–171.Google Scholar
Li, Y.C., Xu, Q.H., Liu, J.S., Yang, X.L., and Nakagawa, T. (2007). A transfer-function model developed from an extensive surface-pollen data set in northern China and its potential for palaeoclimate reconstructions. The Holocene 17, 897–905.Google Scholar
Li, Y.Y., Zhou, L.P., and Cui, H.T. (2008). Pollen indicators of human activity. Chinese Science Bulletins 53, 991–1002.Google Scholar
Li, J.Y., Zhao, Y., Xu, Q.H., Zhuo, Z., Lu, H.Y., Luo, Y.L., Li, Y.C., Li, C.H., and Sepp", H. (2014). Human influence as a potential source of bias in pollen-based climate reconstructions. Quaternary Science Review 99, 112–121.CrossRefGoogle Scholar
Liu, H.Y., Wei, F.L., Liu, K., and Zhu, J.L. (2008). Determinants of pollen dispersal in the East Asian steppe at different spatial scales. Review of Palaeobotany and Palynology 149, 219–228.Google Scholar
Lu, H.Y., Wu, N.Q., Liu, K.B., Zhu, L.P., Yang, X.D., Yao, T.D., Wang, L., Li, Q., Liu, X.Q., Shen, C.M., Li, X.Q., Tong, G.B., and Jiang, H. (2011). Modern pollen distributions in Qinghai"Tibetan Plateau and the development of transfer functions for reconstructing Holocene environmental changes. Quaternary Science Reviews 30, 947–966.Google Scholar
Luo, C.X., Zheng, Z., Tarasov, P., Nakagawa, T., Pan, A.D., Xu, Q.H., Lu, H.Y., and Huang, K.Y. (2010). A potential of pollen-based climate reconstruction using a modern pollen"climate dataset from arid northern and western China. Review of Palaeobotany and Palynology 160, 111–125.Google Scholar
Mac Nally, R. (2002). Multiple regression and inference in ecology and conservation biology: further comments on identifying important predictor variables. Biodiversity and Conservation 11, 1397–1401.Google Scholar
Marquardt, D.W. (1970). Generalized inverses, ridge regression, biased linear estimation, and nonlinear estimation. Technometrics 12, 591-256.Google Scholar
Meng, G.L., and Wang, S.Q. (1987). Quaternary pollen assemblages from Core BC-1 in Bohai Sea and the palaeoclimate reconstructions. Oceanography and Limnology of China 18, 253–263.(in Chinese).Google Scholar
Minckley, T.A., Bartlein, P.J., Whitlock, C., Shuman, B.N., Williams, J.W., and Davis, O.K. (2008). Associations among modern pollen, vegetation, and climate in western North America. Quaternary Science Reviews 27, 1962–1991.Google Scholar
New, M., Lister, D., Hulme, M., and Makin, I. (2002). A high-resolution data set of surface climate over global land areas. Climate Research 21, 2217–2238.Google Scholar
O'Brien, R.M. ('Brien, 2007). ), A caution regarding rules of thumb for variance inflation factors. Quality & Quantity 41, 673–690.Google Scholar
Oksanen, J., Blanchet, F.G., Kindt, R., Legendre, P., Minchin, P.R., O'Hara, R.B., Simpson, G.L., Solymos, P., Stevens, M.H.H., and Wagner, H. (2013). Vegan: Community Ecology Package. http://CRAN.R-project.org/package=vegan.Google Scholar
Palm, J., van Schaik, N.L.M., and Schrder, B. (2013). Modelling distribution patterns of anecic, epigeic and endogeic earthworms at catchment-scale in agro-ecosystems. Pedobiologia 56, 23–31.Google Scholar
Pan, Y., and Jackson, R.T. (2008). Ethnic difference in the relationship between acute inflammation and serum ferritin in US adult males. Epidemiology and Infection 136, 421–431.Google Scholar
Pan, T., Dai, E.F., and Wu, S.H. (2010). Relationship between surface pollen and modern vegetation in Southwestern China. Journal of Mountain Science 7, 176–186.Google Scholar
Phuphumirat, W., Gleason, F.H., Phongpaichit, S., and Mildenhall, D.C. (2011). The infection of pollen by zoosporic fungi in tropical soils and its impact on pollen preservation: a preliminary study. Nova Hedwigia 92, 233–244.Google Scholar
Prentice, I.C. (1980). Multidimensional scaling as a research tool in Quaternary palynology: a review of theory and methods. Review of Palaeobotany and Palynology 31, 71–104.Google Scholar
Prentice, I.C., Guiot, J., Huntley, B., Jolly, D., and Cheddadi, R. (1996). Reconstructing biomes from palaeoecological data: a general method and its application to European pollen data at 0 and 6 ka. Climate Dynamics 12, 185–194.CrossRefGoogle Scholar
R Development Core Team, (2012). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna.Google Scholar
Ren, G.Y. (2000). Decline of the mid- to late Holocene forests in China: climatic change or human impact?. Journal of Quaternary Science 15, 273–281.Google Scholar
Ren, G.Y. (2007). Changes in forest cover in China during the Holocene. Vegetation History and Archaeobotany 16, 119–126.Google Scholar
Salonen, J.S., Sepp", H., Luoto, M., Birks, H.J.B., and Bjune, A.E. (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.Google Scholar
Salonen, J.S., Luoto, M., Alenius, T., Heikkila, M., Sepp", H., Telford, R.J., and Birks, H.J.B. (2014). Reconstructing palaeoclimatic variables from fossil pollen using boosted regression trees: comparison and synthesis with other quantitative reconstruction methods. Quaternary Science Reviews 88, 69–81.Google Scholar
Sch"bitz, F., Wille, M., Francois, J.-P., Haberzettl, T., Quintana, F., Mayr, C., L"cke, A., Ohlendorf, C., Mancini, V., Paez, M.M., Prieto, A.R., and Zolitschka, B. (2013). Reconstruction of palaeoprecipitation based on pollen transfer functions"the record of the last 16 ka from Laguna Potrok Aike, southern Patagonia. Quaternary Science Reviews 71, 175–190.Google Scholar
Sepp", H., Birks, H.J.B., Odland, A., Poska, A., and Veski, S. (2004). A modern pollen"climate calibration set from northern Europe: developing and testing a tool for palaeoclimatological reconstructions. Journal of Biogeography 31, 251–267.Google Scholar
Shen, C.M., Liu, K.B., Tang, L.Y., and Overpeck, J.T. (2006). Quantitative relationships between modern pollen rain and climate in the Tibetan Plateau. Review of Palaeobotany and Palynology 140, 61–77.CrossRefGoogle Scholar
Shen, C.M., Liu, K.B., Morrill, C., Overpeck, J.T., Peng, J.L., and Tang, L.Y. (2008). Ecotone shift and major droughts during the mid-late Holocene in the central Tibetan Plateau. Ecology 89, 1079–1088.Google Scholar
St. Jacques, J.M., Cumming, B.F., and Smol, J.P. (2008). A pre-European settlement pollen"climate calibration set for Minnesota, USA: developing tools for palaeoclimatic reconstructions. Journal of Biogeography 35, 306–324.Google Scholar
Tarasov, P.E., Guiot, J., Cheddadi, R., Andreev, A.A., Bezusko, L.G., Blyakharchuk, T.A., Dorofeyuk, N.I., Filimonova, L.V., Volkova, V.S., and Zernitskaya, V.P. (1999). Climate in northern Eurasia 6000 years ago reconstructed from pollen data. Earth and Planetary Science Letters 171, 635–645.Google Scholar
ter Braak, C.J.F. (1986). Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology 67, 1167–1179.Google Scholar
ter Braak, C.J.F., and Prentice, I.C. (1988). A theory of gradient analysis. Advances in Ecological Research 18, 271–317.Google Scholar
ter Braak, C.J.F., and "milauer, P. (1998). CANOCO Reference Manual and User's Guide to Canoco for Windows: Software for Canonical Community Ordination (Version 4). Microcomputer Power, Ithaca, New York.Google Scholar
ter Braak, C.J.F., and "milauer, P. (2002). CANOCO Reference Manual and Canodraw for Windows User's Guide: Software for Canonical Community Ordination (version 4.5). Microcomputer Power, Ithaca, New York.Google Scholar
ter Braak, C.J.F., and "milauer, P. (2012). Canoco Reference Manual and User's Guide: Software for Ordination, version 5.0. Microcomputer Power, Ithaca, New York.Google Scholar
Tian, F., Herzschuh, U., Telford, R.J., Mischke, S., Van der Meeren, T., and Krengel, M. (2014). A modern pollen"climate calibration set from central-western Mongolia and its application to a late glacial"Holocene record. Journal of Biogeography 41, 1909–1922.Google Scholar
Viau, A.E., Gajewski, K., Sawada, M.C., and Fines, P. (2006). Millenial-scale temperature variability in North America during the Holocene. Journal of Geophysical Research 111, D09102.Google Scholar
Wang, H., Prentice, I.C., and Ni, J. (2013). Data-based modelling and environmental sensitivity of vegetation in China. Biogeosciences 10, 5817–5830.Google Scholar
Wen, R.L., Xiao, J.L., Chang, Z.G., Zhai, D.Y., Xu, Q.H., Li, Y.C., and Itoh, S. (2010). Holocene precipitation and temperature variations in the East Asian monsoonal margin from pollen data from Hulun Lake in northeastern Inner Mongolia, China. Boreas 39, 262–272.Google Scholar
Wen, R.L., Xiao, J.L., Ma, Y.Z., Feng, Z.D., Li, Y.C., and Xu, Q.H. (2013). Pollen"climate transfer functions intended for temperate eastern Asia. Quaternary International 311, 3–11.Google Scholar
Whitmore, J., Gajewski, K., Sawada, M., Williams, J.W., Shuman, B., Bartlein, P.J., Minckley, T., Viau, A.E., Webb III, T., Anderson, P.M., and Brubaker, L.B. (2005). North American and Greenland modern pollen data for multi-scale paleoecological and paleoclimatic applications. Quaternary Science Reviews 24, 1828–1848.Google Scholar
Williams, J.W., and Shuman, B.N. (2008). Obtaining accurate and precise environmental reconstructions from the modern analog technique and North American surface pollen dataset. Quaternary Science Reviews 27, 669–687.Google Scholar
Xiao, X.Y., Shen, J., and Wang, S.M. (2011). Spatial variation of modern pollen from surface lake sediments in Yunnan and southwestern Sichuan Province, China. Review of Palaeobotany and Palynology 165, 224–234.CrossRefGoogle Scholar
Xu, J.S. (1982). Pollen assemblages from cores in the Yellow Sea and its palaeogeographical significance since the Late Pleistocene, selected papers from the first symposium of the Palynological Society of China. Scenic Press, Beijing.22–31.(in Chinese).Google Scholar
Xu, Q.H., Xiao, J.L., Li, Y.C., Tian, F., and Nakagawa, T. (2010). Pollen-based quantitative reconstruction of Holocene climate changes in the Daihai Lake area, Inner Mongolia, China. Journal of Climate 23, 2856–2868.Google Scholar
Zhang, Y., Kong, Z.C., Wang, G.H., and Ni, J. (2010). Anthropogenic and climatic impacts on surface pollen assemblages along a precipitation gradient in north-eastern China. Global Ecology and Biogeography 19, 621–631.Google Scholar
Zhao, Y., Xu, Q.H., Huang, X.Z., Guo, X.L., and Tao, S.C. (2009). Difference of modern pollen assemblages from lake sediments and surface soils in arid and semi-arid China and their significance for pollen-based quantitative climate reconstruction. Review of Palaeobotany and Palynology 156, 519–524.Google Scholar
Zhao, Y., Liu, H.Y., Li, F.R., Huang, X.Z., Sun, J.H., Zhao, W.W., Herzschuh, U., and Tang, Y. (2012). Application and limitations of the Artemisia/Chenopodiaceae pollen ratio in arid and semi-arid China. The Holocene 22, 1385–1392.Google Scholar
Zheng, Z., Huang, K.Y., Xu, Q.H., Lu, H.Y., Cheddadi, R., Luo, Y.L., Beaudouin, C., Luo, C.X., Zheng, Y.W., Li, C.H., Wei, J.H., and Du, C.B. (2008). Comparison of climatic threshold of geographical distribution between dominant plants and surface pollen in China. Science in China Series D: Earth Sciences 51, 1107–1120.CrossRefGoogle Scholar
Zheng, Z., Wei, J.H., Huang, K.Y., Xu, Q.H., Lu, H.Y., Tarasov, P., Luo, C.X., Beaudouin, C., Deng, Y., Pan, A.D., Zheng, Y.W., Luo, Y.L., Nakagawa, T., Li, C.H., Yang, S.X., Peng, H.H., and Cheddadi, R. (2014). East Asian pollen database: modern pollen distribution and its quantitative relationship with vegetation and climate. Journal of Biogeography 41, 1819–1832.CrossRefGoogle Scholar
Zhu, C., Chen, X., Zhang, G.S., Ma, C.M., Zhu, Q., Li, Z.X., and Xu, W.F. (2008). Spore-pollen-climate factor transfer function and paleoenvironment reconstruction in Dajiuhu, Shennongjia, Central China. Chinese Science Bulletin 53, 42–49.CrossRefGoogle Scholar
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