The 600-mm precipitation isoline distinguishes tree-ring-width responses to climate in China

Abstract

The numerous temperature and precipitation reconstructions in China based on tree-ring-width data have played significant roles in furthering the understanding of past climate changes. However, the geographical variability in the responses of trees to climate variations in China remains largely undetermined. Here, we describe an important spatial boundary in the response of trees to climate variations, namely the 600-mm annual precipitation isoline. We found that, to the north of this line, tree-ring widths are usually positively correlated with precipitation and negatively correlated with growing-season temperature. To the south of this line, the tree-ring widths respond positively to temperature, and winter half-year temperatures are the main reconstructed parameters, especially on the third topographical step of China. We also found that precipitation reconstructions based on tree-ring data and the Palmer Drought Severity Index almost exclusively fall in the region of the 200- to 600-mm annual precipitation isolines, not other regions. Our findings indicate that, when using multiple tree-ring-width chronologies for large-scale past climate reconstructions, the climatic signal of each tree-ring-width series should be carefully considered.

Early summer hydroclimatic signals are captured well by tree-ring earlywood width in the eastern Qinling Mountains, central China

“…The correlation coefficients are reflected by the colored and different-size circles, which can be referred to using the color bar as shown at the bottom of the figure. The squares filled with light and dark gray indicate that the correlation coefficients are statistically significant at the 0.05 and 0.01 levels, respectively, which are tested using the Monte Carlo method (Efron and Tibshirani, 1986;Macias-Fauria et al, 2012). ter supply in the rainy season (July-August; Fig.…”

“…r represents the Pearson correlation coefficient between the reconstructed MJJ scPDSI and other hydroclimatic reconstruction over their common period. The significance level for all correlation coefficients was tested using the Monte Carlo method (Efron and Tibshirani, 1986;Macias-Fauria et al, 2012). simple curve fitting methods (Briffa et al, 1996).…”

“…The decadal and longer fluctuations were derived using the adaptive 10point Butterworth low-pass filter with 0.1 cutoff frequency (Mann, 2008). Statistically significant (p < 0.05) correlations are denoted as squares, which were tested using the Monte Carlo method (Efron and Tibshirani, 1986;Macias-Fauria et al, 2012).…”

Moisture variation inferred from tree rings in north central China and its links with the remote oceans

“…In China, most meteorological stations were established in the east after the 1960s 13 , 14 , which prevents us from probing into the climate change on longer time scales. Therefore, many researchers use different natural archives, such as lake sediments 15 , 16 , stalagmites 17 , 18 and tree rings 19 – 21 , to decode paleoclimate change at various timescales, and they have made great progress with these methods. Tree rings, as a widespread natural archive, are extensively used because of their high resolution.…”

Spring Hydroclimate Reconstruction on the South‐Central Tibetan Plateau Inferred From Juniperus Pingii Var. Wilsonii Shrub Rings Since 1605

“…Thus, climate proxies such as tree rings (Cook et al, 2010), ice (Yao et al, 2019), and lake sediment cores (Zhu et al, 2015) have been used to reconstruct past climate in this region. Among these proxies, tree rings play an important role in retrieving past climatic change from century to millennia time scales on the Tibetan Plateau (Fang et al, 2010; Gou et al, 2015; Liu et al, 2019; Shao et al, 2010; Yang et al, 2019; Zhang, Evans, & Lyu, 2015).…”