@article{CaoTianTelfordetal.2017,
  author    = {Cao, Xianyong and Tian, Fang and Telford, Richard J. and Ni, Jian and Xu, Qinghai and Chen, Fahu and Liu, Xingqi and Stebich, Martina and Zhao, Yan and Herzschuh, Ulrike},
  title     = {Impacts of the spatial extent of pollen-climate calibration-set on the absolute values, range and trends of reconstructed Holocene precipitation},
  series = {Quaternary science reviews : the international multidisciplinary research and review journal},
  volume    = {178},
  journal   = {Quaternary science reviews : the international multidisciplinary research and review journal},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0277-3791},
  doi       = {10.1016/j.quascirev.2017.10.030},
  pages     = {37 -- 53},
  year      = {2017},
  abstract  = {Pollen-based quantitative reconstructions of past climate variables is a standard palaeoclimatic approach. Despite knowing that the spatial extent of the calibration-set affects the reconstruction result, guidance is lacking as to how to determine a suitable spatial extent of the pollen-climate calibration-set. In this study, past mean annual precipitation (P-ann) during the Holocene (since 11.5 cal ka BP) is reconstructed repeatedly for pollen records from Qinghai Lake (36.7 degrees N, 100.5 degrees E; north-east Tibetan Plateau), Gonghai Lake (38.9 degrees N, 112.2 degrees E; north China) and Sihailongwan Lake (42.3 degrees N, 126.6 degrees E; north-east China) using calibration-sets of varying spatial extents extracted from the modern pollen dataset of China and Mongolia (2559 sampling sites and 168 pollen taxa in total). Results indicate that the spatial extent of the calibration-set has a strong impact on model performance, analogue quality and reconstruction diagnostics (absolute value, range, trend, optimum). Generally, these effects are stronger with the modern analogue technique (MAT) than with weighted averaging partial least squares (WA-PLS). With respect to fossil spectra from northern China, the spatial extent of calibration-sets should be restricted to radii between ca. 1000 and 1500 km because small-scale calibration-sets (<800 km radius) will likely fail to include enough spatial variation in the modern pollen assemblages to reflect the temporal range shifts during the Holocene, while too broad a scale calibration-set (>1500 km radius) will include taxa with very different pollen-climate relationships. (C) 2017 Elsevier Ltd. All rights reserved.},
  language  = {en}
}
@article{TianHerzschuhTelfordetal.2014,
  author    = {Tian, Fang and Herzschuh, Ulrike and Telford, Richard J. and Mischke, Steffen and Van der Meeren, Thijs and Krengel, Michael},
  title     = {A modern pollen-climate calibration set from central-western Mongolia and its application to a late glacial-Holocene record},
  series = {Journal of biogeography},
  volume    = {41},
  journal   = {Journal of biogeography},
  number    = {10},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0305-0270},
  doi       = {10.1111/jbi.12338},
  pages     = {1909 -- 1922},
  year      = {2014},
  abstract  = {AimFossil pollen spectra from lake sediments in central and western Mongolia have been used to interpret past climatic variations, but hitherto no suitable modern pollen-climate calibration set has been available to infer past climate changes quantitatively. We established such a modern pollen dataset and used it to develop a transfer function model that we applied to a fossil pollen record in order to investigate: (1) whether there was a significant moisture response to the Younger Dryas event in north-western Mongolia; and (2) whether the early Holocene was characterized by dry or wet climatic conditions. LocationCentral and western Mongolia. MethodsWe analysed pollen data from surface sediments from 90 lakes. A transfer function for mean annual precipitation (P-ann) was developed with weighted averaging partial least squares regression (WA-PLS) and applied to a fossil pollen record from Lake Bayan Nuur (49.98 degrees N, 93.95 degrees E, 932m a.s.l.). Statistical approaches were used to investigate the modern pollen-climate relationships and assess model performance and reconstruction output. ResultsRedundancy analysis shows that the modern pollen spectra are characteristic of their respective vegetation types and local climate. Spatial autocorrelation and significance tests of environmental variables show that the WA-PLS model for P-ann is the most valid function for our dataset, and possesses the lowest root mean squared error of prediction. Main conclusionsPrecipitation is the most important predictor of pollen and vegetation distributions in our study area. Our quantitative climate reconstruction indicates a dry Younger Dryas, a relatively dry early Holocene, a wet mid-Holocene and a dry late Holocene.},
  language  = {en}
}