@phdthesis{Cao2014,
  author    = {Cao, Xianyong},
  title     = {Vegetation and climate change in eastern continental Asia during the last 22 ka inferred from pollen data synthesis},
  pages     = {156},
  year      = {2014},
  language  = {en}
}
@article{CaoHerzschuhTelfordetal.2014,
  author    = {Cao, Xianyong and Herzschuh, Ulrike and Telford, Richard J. and Ni, Jian},
  title     = {A modern pollen-climate dataset from China and Mongolia: assessing its potential for climate reconstruction},
  series = {Review of palaeobotany and palynology : an international journal},
  volume    = {211},
  journal   = {Review of palaeobotany and palynology : an international journal},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0034-6667},
  doi       = {10.1016/j.revpalbo.2014.08.007},
  pages     = {87 -- 96},
  year      = {2014},
  abstract  = {A modern pollen dataset from China and Mongolia (18-52 degrees N, 74-132 degrees E) is investigated for its potential use in climate reconstructions. The dataset includes 2559 samples, 229 terrestrial pollen taxa and four climatic variables - mean annual precipitation (P-ann): 35-2091 mm, mean annual temperature (T-ann): -12.1-25.8 degrees C, mean temperature in the coldest month (Mt(co).): -33.8-21.7 degrees C, and mean temperature in the warmest month (Mt(wa)): 03-29.8 degrees C. Modern pollen-climate relationships are assessed using canonical correspondence analysis (CCA), Huisman-Olff-Fresco (HOF) models, the modern analogue technique (MAT), and weighted averaging partial least squares (WA-PLS). Results indicate that P-ann is the most important climatic determinant of pollen distribution and the most promising climate variable for reconstructions, as assessed by the coefficient of determination between observed and predicted environmental values (r(2)) and root mean square error of prediction (RMSEP). Mt(co) and Mt(wa) may be reconstructed too, but with caution. Samples from different depositional environments influence the performance of cross-validation differently, with samples from lake sediment-surfaces and moss polsters having the best fit with the lowest RMSEP. The better model performances of MAT are most probably caused by spatial autocorrelation. Accordingly, the WA-PLS models of this dataset are deemed most suitable for reconstructing past climate quantitatively because of their more reliable predictive power. (C) 2014 Elsevier B.V. All rights reserved.},
  language  = {en}
}
@article{KoenigZhenHelmingetal.2014,
  author    = {Koenig, H. J. and Zhen, L. and Helming, K. and Uthes, S. and Yang, L. and Cao, Xianyong and Wiggering, Hubert},
  title     = {Assessing the impact of the sloping land conversion programme on rural sustainability in Guyuan, Western China},
  series = {Land degradation \& development},
  volume    = {25},
  journal   = {Land degradation \& development},
  number    = {4},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {1085-3278},
  doi       = {10.1002/ldr.2164},
  pages     = {385 -- 396},
  year      = {2014},
  abstract  = {The goal of China's sloping land conversion programme (SLCP) is to combat soil erosion and to reduce rural poverty. An ex-ante assessment of possible SLCP impacts was conducted with a focus on rural sustainability, taking the drought-prone region of Guyuan in Western China as an example. The Framework for Participatory Impact Assessment (FoPIA) was used to conduct two complementary impact assessments, one assessing SLCP impacts at regional level and a second one assessing alternative forest management options, to explore possible trade-offs among the economic, social and environmental dimensions of sustainability. Regional stakeholders assessed the SLCP to be capable of reducing soil erosion but felt it negatively affected rural employment, and a further continuation of the Programme was advocated. Assessment of three forest management scenarios by scientists showed that an orientation towards energy forests is potentially beneficial to all three sustainability dimensions. Ecological forests had disproportionate positive impacts on environmental functions and adverse impact on the other two sustainability dimensions. Economic forests were assessed to serve primarily the economic and social sustainability dimensions, while environmental impacts were still tolerable. The FoPIA results were evaluated against the available literature on the SLCP. Overall, the assessment results appeared to be reasonable, but the results of the regional stakeholders appeared to be too optimistic compared with the more critical assessment of the scientists. The SLCP seems to have the potential to tackle soil erosion but requires integrated forest management to minimize the risk of water stress while contributing to economic and social benefits in Guyuan. Copyright (C) 2012 John Wiley \& Sons, Ltd.},
  language  = {en}
}
@article{XuCaoTianetal.2014,
  author    = {Xu, QingHai and Cao, Xianyong and Tian, Fang and Zhang, ShengRui and Li, YueCong and Li, ManYue and Li, Jie and Liu, YaoLiang and Liang, Jian},
  title     = {Relative pollen productivities of typical steppe species in northern China and their potential in past vegetation reconstruction},
  series = {Science China},
  volume    = {57},
  journal   = {Science China},
  number    = {6},
  publisher = {Science China Press},
  address   = {Beijing},
  issn      = {1674-7313},
  doi       = {10.1007/s11430-013-4738-7},
  pages     = {1254 -- 1266},
  year      = {2014},
  abstract  = {The Relative Pollen Productivities (RPPs) of common steppe species are estimated using Extended R-value (ERV) model based on pollen analysis and vegetation survey of 30 surface soil samples from typical steppe area of northern China. Artemisia, Chenopodiaceae, Poaceae, Cyperaceae, and Asteraceae are the dominant pollen types in pollen assemblages, reflecting the typical steppe communities well. The five dominant pollen types and six common types (Thalictrum, Iridaceae, Potentilla, Ephedra, Brassicaceae, and Ulmus) have strong wind transport abilities; the estimated Relevant Source Area of Pollen (RSAP) is ca. 1000 m when the sediment basin radius is set at 0.5 m. Ulmus, Artemisia, Brassicaceae, Chenopodiaceae, and Thalictrum have relative high RPPs; Poaceae, Cyperaceae, Potentilla, and Ephedra pollen have moderate RPPs; Asteraceae and Iridaceae have low RPPs. The reliability test of RPPs revealed that most of the RPPs are reliable in past vegetation reconstruction. However, the RPPs of Asteraceae and Iridaceae are obviously underestimated, and those of Poaceae, Chenopodiaceae, and Ephedra are either slightly underestimated or slightly overestimated, suggesting that those RPPs should be considered with caution. These RPPs were applied to estimating plant abundances for two fossil pollen spectra (from the Lake Bayanchagan and Lake Haoluku) covering the Holocene in typical steppe area, using the "Regional Estimates of Vegetation Abundance from Large Sites" (REVEALS) model. The RPPs-based vegetation reconstruction revealed that meadow-steppe dominated by Poaceae, Cyperaceae, and Artemisia plants flourished in this area before 6500-5600 cal yr BP, and then was replaced by present typical steppe.},
  language  = {en}
}