Climate Response And Reconstruction Based On Tree-ring Width And Wood Density In The Monsoon Marginal Zone And The Qinling Mountains

The continuous global warming leads to frequent extreme climate events,which affects human activities and the development of various industries.China contains four arid and humid regions,and the precipitation isolines can distinguish the climate characteristics of different regions.In order to response the possible extreme climate events of different regions in the future more accurately,there is a need to understand the characteristics and driving mechanism of historical climate change of different precipitation isolines and to predict future climate change.Tree-ring width is one of the most widely used indexes in the study of historical climate change and climate reconstruction.Wood density combined with tree-ring width can indicate historical climate change information more comprehensively.In this study,we selected Lamashan（LMS）which located in the marginal region of the EASM,Nanwutai（NWT）and Muwangshan（MWS）which located in the north and south slope of the Qinling mountains as our sampling sites.The tree-ring width chronologies and wood density chronologies were established.The similarities and differences of the climate responses of different tree-ring indexes to climate factors in different regions were discussed,and appropriate climate factors were selected for climate reconstruction.The main research results are as follows:1.Using Pinus tabulaeformis samples collected from LMS,NWT and MWS.The tree-ring width（TRW）chronology from 1710 to 2012 was established in the LMS.The TRW chronology from 1782 to 2020 and 1786-2019 maximum latewood density（MXD）chronology were established in NWT.The TRW chronology from 1851-2020,MXD chronology for 1864-2019,and minimum earlywood density（MND）chronology from1859-2019 were established in the MWS.2.The climate response analysis in LMS show that the highest correlation is between TRW chronology and the May-August Palmer drought severity index（PDSI）（r=0.695,n=67,p<0.001）.Thus we reconstructed the May–August PDSI(PDSI₅₈)from 1710 to2012 in the marginal region of the EASM.The reconstructed drought series records historical drought events and exhibits an obvious drying trend since the 1950s,which may be related to the increase of anthropogenic sulfate aerosols.Spatial correlation analysis shows that PDSI₅₈ can represent the drought variability on the northernmost margin of the EASM.The PDSI₅₈ is significantly correlated with the East Asian summer monsoon index and the Asian polar vortex area index,indicating that the winter Asian polar vortex area index has a delayed effect on the EASM precipitation in the following summer.Both of them have a strong influence on drought variabilities over the northern marginal region of the EASM.3.The climate response analysis in NWT show that the TRW chronology has the most significant correlation with the April-June precipitation（r=0.664,n=59,p<0.001）.The MXD chronology shows a highly positive correlation with the April-July precipitation,and negatively correlated with the May-July mean temperature and mean maximum temperature.We reconstructed the April-June precipitation(P₄₆)changes from 1782 to 2020 based on the climate response analysis.This reconstructed precipitation series records the severe drought events in Chinese history.The reconstructed P₄₆ is positively correlated with precipitation reconstructions of the Huashan and western Qinling and shows a good spatial representation.The reconstructed P₄₆ shows a significant correlation with the East Asian monsoon,which well reflected the intensity variation of the East Asian monsoon.The reconstructed P₄₆was significantly correlated with PDO index.The possible mechanism affecting the precipitation in NWT may be PDO affects the precipitation in the study area by affecting the position and intensity of the East Asian monsoon.The EEMD period analysis and the wavelet analysis also improved our conclusion.4.The climate response analysis in MWS show that the TRW chronology is significantly correlated with May-June mean relative humidity（r=0.691,n=61,p<0.0001）,the MXD chronology is most significantly correlated with the August-September mean maximum temperature（r=0.706,n=62,p<0.0001）,and the MND chronology is significantly correlated with the May-June mean maximum temperature（r=0.692,n=61,p<0.0001）.The response of tree ring density to climate in sub-humid area was discussed and the possible changes of tracheid area and cell wall thickness during the tree growth were analyzed.The MND chronology and MXD chronology were used to reconstruct May-June mean maximum temperature(T₅₆)and August-September mean maximum temperature(T₈₉).The reconstructed T₅₆ and T₈₉ both well preserved the high-frequency and low-frequency information and recorded the drought events in history.More than half of the coldest decades in both sequences reflects the cooling effect after the volcanic eruption.The reconstructed temperature series correlate well with the surrounding temperature series reconstructed by wood density and has a good spatial representation,indicating the reconstructed temperature series can represent the variation of the mean maximum temperature in the Qinling Mountains and some loess Plateau regions.The correlation analysis with SPEI indicate that the two reconstructed series also represent the regional dry-wet veriation in MWS.5.The climatic response correlation and difference analysis results of tree-ring width and wood density on the two precipitation line gradients are as follows.TRW is significantly negatively correlated with MND in MWS.In NWT,TRW is significantly positively correlated with MXD.Both of results are well reflected.relationship between width and density in the northern hemisphere.The analysis of the same indicators at different research points show that the TRW chronology of the three sampling sites is negatively correlated with the May-June temperature in the current year,indicating that the temperature at the early stage of growth has a significant impact on the tree-ring width.The TRW of the three sampling sites all show positive responses to precipitation,but the TRW response in the MWS is weak,which well reflects the different responses of TRW in different regions due to regional precipitation differences.The results of the MXD chronology climate responses analysis show that MXD of NWT was negatively correlated with the temperature in the early growing season,and MXD of MWS was positively correlated with the temperature in the late growing season,but both showed a positive correlation with the precipitation in the early growing season.The results indicate that the increase of temperature in the early growing season of trees intensified the drought stress,which was not conducive to the thickening of late wood cell wall,and the high precipitation in the early growing season was conducive to the alleviation of drought stress,which was conducive to the thickening of late wood cell wall.