4.3 Article

Modern pollen-climate relationships in north Xinjiang, northwestern China: Implications for pollen-based reconstruction of Holocene climate

期刊

HOLOCENE
卷 27, 期 7, 页码 951-966

出版社

SAGE PUBLICATIONS LTD
DOI: 10.1177/0959683616678464

关键词

Altay Mountains; China; Jungar Desert; modern pollen-climate relationships; pollen ratios; variation partitioning

资金

  1. National Key Research and Development Program of China [2016YFA0600501]
  2. National Natural Science Foundation of China [41125006, 41330105]
  3. China Scholarship Council [201206180028]
  4. Faculty of Health and Life Science at Linnaeus University (Sweden)
  5. Chinese High-end Foreign Experts Recruitment Program [20151300002]

向作者/读者索取更多资源

Fossil pollen records are widely used to reconstruct past climate. Such reconstructions require that the relationships between pollen assemblages, vegetation, and climate are well understood. These can be studied in present circumstances given we assume that modern vegetation and climate are analogous to past ones. In this study, we analyze pollen-vegetation-climate relationships in the Jungar desert and Altay Mountains, northwestern China, a region for which careful reconstruction of past climate is needed to answer unsolved questions on past climate in an area located at the boundary between two different climate regimes (westerlies and monsoon). We use a dataset of 66 surface pollen samples from forest, meadow, steppe, and desert vegetation and six related climate variables, T-ann, T-Jan, T-Jul, P-ann, P-Jan, and P-Jul. Principal components analysis, redundancy analysis, Monte Carlo permutation tests, and variation partitioning are applied to quantify these relationships. We also assess pollen ratios as indices of aridity. We find that (1) P-ann is the major climatic factor influencing pollen assemblages, followed by P-Jul, (2) the two variables are not correlated, and (3) the shared effect of (1) P-Jan and P-Jul, (2) P-Jan and P-ann, (3) P-Jul and T-ann, and (4) T-ann, T-Jan, and T-Jul explains a larger portion of the variation in pollen data than the individual effect of each variable. Therefore, robust pollen-climate transfer functions can be developed for P-ann and P-Jul, and several climate variables treated in combination. Artemisia/Chenopodiaceae is a strong index of aridity and Artemisia/Gramineae might be a useful index of P-ann and P-Jul.

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