# New quantified climate reconstruction in southern China suggests a potential influence of winter cloud cover across East Asia during the Holocene

Xiao Zhang, Cong Chen, Kexin Wang, Meihuan Li, Yuanfu Yue, Jun Cheng, Mengna Liao, Kai Li, Lina Liu, Zhanghua Wang, et al.

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## To cite this version:

Xiao Zhang, Cong Chen, Kexin Wang, Meihuan Li, Yuanfu Yue, et al. New quantified climate reconstruction in southern China suggests a potential influence of winter cloud cover across East Asia during the Holocene. Science of the Total Environment, 2025, 958, pp.178008. 10.1016/j.scitotenv.2024.178008. hal-05393369

HAL Id: hal-05393369

https://cnrs.hal.science/hal-05393369v1

Submitted on 2 Dec 2025

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Distributed under a Creative Commons Attribution 4.0 International License
New quantified climate reconstruction in southern China suggests a
potential influence of winter cloud cover across East Asia during the
Holocene

Xiao Zhang a, Cong Chen b,c,*, Kexin Wang a, Meihuan Li b, Yuanfu Yue d, Jun Cheng e,
Mengna Liao a, Kai Li a, Lina Liu a, Zhanghua Wang f, Rachid Cheddadi g, Qiuchi Wan h,
Yongjie Tang b, Zhuo Zheng b,c, Kangyou Huang b,c,*

<sup>a</sup> College of Life Sciences, Zhejiang Normal University, 321004 Jinhua, China

b Guangdong Key Lab of Geodynamics and Geohazards, School of Earth Sciences and Engineering, Sun Yat-sen University, Zhuhai 519082, China

c Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China

d Guangxi Laboratory on the Study of Coral Reef in the South China Sea, Coral Reef Research Centre of China, School of Marine Sciences, Guangxi University, Nanning 530004, China

e Center for Ocean-Atmosphere Interaction Research, Nanjing University of Information Science and Technology, Nanjing 210044, China

f State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China

g Institute of Evolutionary Sciences of Montpellier, University of Montpellier, Montpellier 34000, France

h School of Geography, South China Normal University, Guangzhou 510635, China
ABSTRACT

Previous studies have advanced our understanding of paleoclimate features and dynamics in East Asia, particularly within the East Asian monsoon domain (EAMD) since the last glacial period. However, a lack of quantitative reconstructions in the boundary area between tropical and subtropical zones has largely hindered our spatial comprehension of the relationship between precipitation and temperature throughout the EAMD. In this study, we present a continuous pollen record from the Pearl River delta over the past 13.2 ka and a quantitative climate reconstruction using an updated modern pollen dataset. The findings indicate that from 13.2 ka to 9.9 ka, the study area was encompassed by mid-montane moist evergreen broadleaved forest (EBLF), transitioning to semi-humid EBLF or lowland monsoon EBLF during the late Holocene. Anthropochory plants have emerged as dominant taxa by about 1.9 ka, indicating a large-scale impact of human activities. The results of quantitative climate reconstruction indicate that the range of annual precipitation varies by ca. 80-120 mm, and the changing pattern is consistent with the traditional 'Holocene thermal maximum' mode, with summer solar radiation potentially being the primary controlling factor. The range of annual temperature variability fall between 19.5 °C and 22.5 °C, exhibiting a warming trend likely influenced by changes in Northern Hemisphere ice volume. There is a phase difference of about 2-4 ka between the peak values of precipitation and temperature. The variation patterns of change across eastern Asia exhibit distinct differences when compared to the proxy records in the EAMD. It appears that such asynchrony between precipitation and temperature is more pronounced in southern China. In comparison with model simulations, it is believed that spatiotemporal variation in winter cloud cover may play a crucial role in explaining this phenomenon of regional heterogeneity.

Keywords: Pollen analysis, Pearl River delta, Quantitative reconstruction, East Asia monsoon, The Holocene
# 1. Introduction

As a major component of the Asian monsoon system, East Asia monsoon variability controls almost all aspects of hydrology and ecol ogy of East Asia (An et al., 2014). To date, analysis of responses of monsoonal circulation to insolation forcing in East Asia monsoon domain (EAMD) have been mostly based on speleothem oxygen isotopic records, though the correlation between rainfall and δ18O is extremely complex (Cheng et al., 2022). These stalagmite records have provided valuable insights into the influence of the East Asian monsoon, including temperature gradients between hemispheres (Cheng et al., 2020), vari ations in high-latitude ice volume (Wang et al., 2007; Yu et al., 2009), meridional migration of the Intertropical Convergence Zone (ITCZ) (Asmerom et al., 2020), and fluctuations in CO2 concentration (Xia et al., 2017). An increasing number of quantitative precipitation records in EAMD during the last glacial period have been reconstructed using modern and fossil pollen data (Zheng et al., 2016; Lu et al., 2024a, 2024b), encom passing regions in northern China (Stebich et al., 2015; Chen et al., 2015), southwestern China (Zhang et al., 2023; Xiao et al., 2023); Ti betan Plateau (Lu et al., 2011; Zhao et al., 2021); central China (Sun et al., 2019; Huang et al., 2023), and eastern China (Li et al., 2018; Lu et al., 2019). This research presents reliable observations of monsoon variability and its driving mechanisms, providing high-resolution quantitative paleoclimate reconstructions that fill existing gaps in spatial coverage.
However, as highlighted by Lu et al. (2024a), a key challenge in current quantitative reconstructions lies in the lack of precipitation reconstruction findings within tropical regions. For instance, Zhou et al. (2022) collected pollen-based precipitation records from various latitudes in China and revealed distinct temporal variations in these records, i.e. ‘time-transgressive’ pattern, which primarily attributed to monthly solar radiation changes, while the Western Pacific Subtropical High is believed to play a crucial regulatory role. Never theless, due to the absence of reliable precipitation data in tropical regions, this conclusion remains somewhat contentious. Another poorly understood aspect pertains to the spatial and tem poral relationship between precipitation and temperature in the EAMD, particularly during the Holocene (Lu et al., 2024b). In this region, the simultaneous occurrence of high rainfall and temperatures is a significant climatic characteristic, with elevated temperatures typically accompanied by abundant precipitation during the annual warm season. This climate greatly benefits crop growth under favorable water and temperature conditions, however, it can also result in flooding and subsequent agricultural yield reduction due to concentrated annual rainfall. Previous studies have indicated that EAMD exhibits synchronous variations in temperature and rainfall on a centennial or millennial timescale during the Holocene, with temperature reconstructions primarily reflecting changes in summer temperatures (Chen et al., 2023a, 2023b; Kaufman and Broadman, 2023). However, there is currently a lack of research investigating the relationship between precipitation and annual or winter temperatures. Wu et al. (2023) compiled published temperature records from China since the Holocene and discovered notable disparities in temperature changes among different regions. The result shows that there are significant differences in the trends of reconstructed Holocene temperature change based on the same proxy across different regions, with some regions even lacking a typical Ho locene thermal maximum (HTM) mode. For instance, central China frequently demonstrates a ‘cooling’ pattern while northeast and south west China tend to exhibit a warming middle Holocene. It is noteworthy that only a small fraction of the temperature records accompanied by precipitation indicators from the same materials, thereby resulting in an ambiguous relationship between the two climate variables despite numerous climate reconstruction findings within the EAMD (Lu et al., 2024a, 2024b). Furthermore, even for co-reconstructed temperature and precipitation records obtained from identical cores, variations in their patterns may still exist among neighboring regions. For example, the pollen-based precipitation and temperature records exhibit a synchro nous pattern during the Holocene in TCQH lake (Xiao et al., 2023). Both variables peaked in the early Holocene and gradually declined there after. However, reconstruction results from Xingyun lake in the same southwestern region indicate that the warm period occurred during the middle Holocene, lagging ca. 2000 years behind high precipitation (Wu et al., 2018). Similarly, this phenomenon is also observed in re constructions from central China, such as Dajiuhu (Sun et al., 2019; Zhang et al., 2023) and Jianghan Plain
(Huang et al., 2023). In a recent study, Wu et al. (2023) utilized brGDGT to reconstruct temperature records of the Huguangyan (HGY) Maar lake in tropical China, eluci dating the pivotal role played by high-latitude ice volume, winter monsoon dynamics, and late Holocene ITCZ movement in driving thermal fluctuations since the last glacial period. However, due to an absence of reliable precipitation data in the region, the relationship between temperature and precipitation variations remains ambiguous. Therefore, in order to effectively adapt to the potential severe climate conditions in EAMD in the future, it is imperative to acquire a comprehensive understanding of the relationship between precipitation and temperature since the deglaciation, particularly in the boundary area between tropical and subtropical zones. The Pearl River delta (PRD), one of the most populated economic centres in the world, characterized by a high sedimentation rate in the estuary and nearshore areas, has accumulated substantial Quaternary deposits that hold abundant information regarding paleoclimate and land-sea interactions (Zong et al., 2015). Despite extensive research on sedimentary environments (Xiong et al., 2020; Tang et al., 2023), coastal zone changes (Chen et al., 2019), and human-environment relationships (Ma et al., 2020) in the region, there remains a lack of continuous quantitative paleoclimate records since the last deglaciation due to limitations in available research materials. By using early pollen data, Zhao et al. (2014) successfully quantitatively reconstructed climate change in the PRD since the late Holocene. The findings revealed a decreasing trend in both temperature and precipitation. However, due to constraints imposed by limited research materials and modern pollen data availability, they were unable to adequately address issues pertaining to spatial variations of the climate variables in the EAMD. Additionally, considering the PRD's geographical location in the north ern part of the South China Sea and its proximity to the EAPD boundary, it is important to account for potential ‘edge effects’ (i.e. the process of climate reconstruction may encounter insufficient climate gradients if the research site is located at the edge of the modern dataset) when conducting climate quantification in this region (Juggins and Birks, 2012). Therefore, further research is imperative to effectively mitigate its impact. Here, we present a pollen record from the PRD in tropical China since the deglaciation period, enabling us to quantitatively reconstruct the spatiotemporal variations in precipitation and temperature. By estab lishing correlations between this dataset and other climate records within the EAMD, we gain insights into the dynamic changes in tem perature and precipitation patterns across tropical regions and East Asia during the Holocene, as well as their underlying influencing factors. This study provides invaluable data to support future research aimed at comprehending the intricate relationships between climate variables and extreme weather events in tropical regions under projected global warming.

2. Study area

The PRD lies on the northern coast of the South China Sea (Fig. 1). The catchment area of the Pearl
River system lies within the continental landscape of southeast China, or the Cathaysia Block,
which has gone through a gradual regional subsidence caused by continental extension of the Block
(Zong et al., 2015). As a result, during the last interglacial and the present interglacial, the high sea
level have twice opened an accommodation space for deltaic sedimentation (Fu et al., 2020). The
local climate is dominated by Asian monsoon circulation, with warm and humid conditions in
spring and summer. In autumn and winter, this region is usually cool and dry (Zong et al., 2012).
The mean annual temperature (MAT) of the core locality is ca. 21.8 °C, and the mean annual
precipitation (MAP) is ca. 1820 mm, with a peak in July.

The catchment area is covered by a (sub)tropical evergreen broadleaved forest with warm temperate
forest on mountain slopes. The regional natural plants are dominantly C3 plants, mixed with some
C4 grasses on mountain tops or saltmarsh (Zong et al., 2013), whilst sugarcane is one of the major
agricultural crops in the central deltaic area today (Yu et al., 2010; Shi et al., 2022).

3. Materials and methods

3.1. Materials

3.1.1. Study core
The study core, Minzhong (MZ) (113.540° E, 22.636° N, 0.4 m a.s.l), was drilled using the XY-150 hydraulic core drilling rig from the northern coast of the South China Sea, Guangdong province in 2019 (Fig. 1b). The core is 64.2 m long and covers all the sediment to the bedrock. It is important to note that the upper 2.4 m of the core comprises typical artificial fill soil, while natural sediment exists below this depth. Consequently, we have excluded this sediment from subsequent studies, resulting in a coring recovery rate of approximately 96.2 %.

### 3.1.2. Modern pollen dataset

The modern pollen data is from the updated modern pollen database of East Asia, with number of 5405 sample sites (Zheng and Huang, 2022). The majority of modern samples are sourced from the soil surface, while others are obtained from lake sediment, moss pollsters, dust-flux collectors, and air trappers. In total, these modern samples encompass a comprehensive collection of 581 pollen/spore taxa. They effectively represent diverse vegetation types across China, including forests, meadows, steppes, shrubs, and deserts. Meteorological data used to interpolate climate data at each sample site are average values recorded in a 30 year period (1981–2010) at 756 meteorological stations in China. The selected interpolation method was thin plate splines regression, which involves use of a spline function and Kriging interpolation. The six variables were selected to characterize the climate at each modern pollen sampling site in this manner: mean annual precipitation (MAP), mean summer precipitation (MSP), mean winter precipitation (MWP), mean annual temperature (MAT), mean summer temperature (MST) and mean winter temperature (MWT).

## 3.2. Methods

### 3.2.1. Laboratory analysis

The chronology of the core is based on accelerator mass spectrometry radiocarbon (AMS 14C) and the age-depth model was constructed using the Bayesian Bacon method (Blaauw and Christen, 2011). In total, 131 fossil samples of MZ core were collected for pollen analysis. For each pollen sample, 5–15 g of sediment was weighed and processed by heavy liquid separation (Moore et al., 1991). On average, 504 terrestrial pollen grains were counted per sample, with proportional numbers of fern and algal spores. All percentages quoted for pollen grains and spores in this work are based on the summed counts of pollen grains from terrestrial taxa. TILIA 3.0.1 (Grimm, 1991–1993) was used to calculate pollen percentages and plot the pollen diagram.

### 3.2.2. Numerical analyses

To simplify the elucidation of the implications conveyed by the fossil pollen data of MZ core, we employed principal component analysis (PCA), a statistical technique used to investigate the interrelationships among multidimensional variables (Birks et al., 1998). Statistical analyses were based on pollen taxa (percentage values) that occurred in at least five samples with an abundance >2 %, thus a total of 31 pollen taxa were selected. In the subsequent process of climate quantification reconstruction, a set of detrended correspondence analyses (DCA) was initially employed as an initial step in the data screening procedure to calculate the compositional gradient length of modern pollen assemblages for each circular subset. This calculation aimed to determine whether a linear- or unimodal-based response model should be applied for constrained ordination (Lepš and Šmilauer, 2003). If the length of the first DCA axis exceeds 4 standard deviation units of turnover (SD), canonical correspondence analysis (CCA) should be utilized. Conversely, if the length is below 3 SD, redundancy analysis (RDA) is more appropriate. When the length falls between 3 and 4 SD, both CCA and RDA can yield reasonable results (Legendre and Gallagher, 2001). Since all subsets have scores above 3 SD on their respective first DCA axes in this study, a series of CCA with forward selection was conducted for each subset at the following step. The statistical outcomes were visualized using Canoco 5.

### 3.2.3. A framework of quantitative reconstruction
### 3.2.3.1. Reconstruction model and calibration set selection.

In order to achieve more accurate quantitative reconstruction of paleoclimate, we assessed the appropriateness of various calibration models for the selected modern pollen database, including Best Analogue Technique (BAT), Weighted Averaging (WA), Weighted Averaging Partial Least Squares (WAPLS), Local-Weighted Weighted-Averaging (LW-WA) and Locally Weighted-Weighted Average Partial Least Squares (LW-WAPLS) models (Birks, 2012) (Fig. 2). All models were employed in software R. The ‘Analogue’ package was utilized for BAT (Simpson and Oksanen, 2016), while the ‘rioja’ package was employed for the remaining models (Juggins, 2017). The selection of the calibration set for the transfer function models, which is a crucial concern in the initial stages of the reconstruction process, tends to be disregarded (Trachsel and Telford, 2016). Previous work has indicated that a radius of 800–1500 km from a focal research site is the most suitable for setting a modern pollen sampling area to establish climate-vegetation relationships (Cao et al., 2017). Thus, in this study, we initially selected eight radius (800–1500 km, 100 km interval) for comparative analysis to the optimal area for modern pollen sampling around the MZ core (Fig. 3). A total of 1468 modern pollen sites were included within a radius of 1500 km. To obtain a high-quality training-set or calibration-set, we screened some of the data for reliability. It should be noted that Quercus pollen in the modern dataset is identified solely as either evergreen type (E) or deciduous (D) type. We cannot distinguish Quercus of evergreen sclerophyll (ES) type from lowland evergreen Quercus, which originate from two different vegetation belts and very different climate conditions in the selected dataset (Zhang et al., 2018). However, the PRD region is definitely unsuitable for the growth of Quercus (ES), neither today nor to the last glacial maximum (LGM), as it prefers a very cold and dry environment found in southwestern China (Yang et al., 2009). Therefore, to enhance the accuracy of the reconstruction results, we excluded 152 samples of Quercus (E) with a high proportion that were distributed above 2600 m a.s.l., based on the modern distribution characteristics of Quercus (ES) in the selected dataset. Consequently, 1316 modern samples were chosen for quantitative reconstruction.

### 3.2.3.2. Climate variables selection.

The selection of climate variables for reconstruction in most previous studies is predominantly based on subjective judgment rather than rigorous data analysis (Liang et al., 2020). To ascertain the primary climatic factors governing regional vegetation in this study, we employed diverse methods to analyze modern pollen dataset. Variance Inflation Factors (VIF) were used to examine the degree of multicollinearity among the selected bioclimatic variables, and to identify a minimum set of independent variables with the lowest intercorrelations. VIF derived from CCA were used to eliminate variables with high levels of redundancy until a low VIF value was achieved (Terbraak and Verdonschot, 1995). The Pearson correlation coefficient was employed to identify co-linear relationships among the climate variables in modern samples (Birks, 2012). The contribution of each climate variable was calculated by determining the ratio of the constrained eigenvalue to the first unconstrained eigenvalue in CCA. Variables with lower interpretation amounts were removed accordingly (Cao et al., 2017).

### 3.2.3.3. Evaluation and validation.

To evaluate the goodness of matches between the calibration set and fossil pollen assemblages, ‘minimum dissimilarity (min DC)’ values were calculated. A useful rule of thumb is that a fossil sample has no analogues where the min DC for the sample is greater than the 10th percentile of the distribution of dissimilarity values of the calibration samples (Birks, 2012). If the min DC is less than the 5th percentile, the fossil sample is considered to have good analogues (Birks, 2012). The ‘palaeoSig’ package in ‘R’ was used for the goodness of matching test (Telford, 2019). The statistical performance of the selected model was evaluated using bootstrapping cross-validation (Birks, 2012). Model statistics included the root mean square error (RMSE) and coefficient of determination (R2), which measured the agreement between observed and predicted values. The model with the smallest RMSE and highest R2 was chosen along with its corresponding calibration set
(Juggins, 2013). Additionally, cross-validation provided an estimation of prediction error for the reconstructed results. To further assess the reliability of reconstructed climate variables, we applied a 'significance test'. Specifically, the fossil pollen data were subjected to RDA to determine the maximum amount of variance explicable by one axis and generate 999 reconstructions using the same modern and fossil data (Birks, 2012; Telford and Birks, 2011). In this approach, if the reconstructions with real climatic data explain more of the variance in the fossil data than 95% (or other selected threshold) of the reconstructions with random climatic data, the reconstructions are regarded as significant. The 'palaeoSig' package was also used for these tests of the quantitative reconstructions (Telford, 2019).

### 3.2.4. Model simulations

The TraCE 21 ka experiments are performed by the Community Climate System Model version 3 (CCSM3) from the National Center for Atmospheric Research (NCAR), which is a fully coupled atmosphere-ocean-sea ice-land surface climate model without flux adjustment (Collins et al., 2006). The experiment set contains a full forcing simulation (TraCE-FULL) from 22 ka BP to 1990 CE. In this study, we initially employed the TraCE model to simulate the annual and seasonal climate variables of the PRD, encompassing precipitation and temperature. Furthermore, we conducted separate simulations to assess disparities in cloud cover between the early and late Holocene periods during both winter and summer seasons within the EAMD.

## 4. Results

### 4.1. Sediment lithology and core chronology

The uppermost 2.4 m sediment of MZ core was artificial fill soil. This is followed by a layer of grey clay (2.4-30.1 m) and a uniform grey silt layer in 30.1-44.3 m. The deposit between 44.3 m and 64.2 m consists of yellow-grey coarse gravel sand with a diameter of about 3-5 mm and massive bedding, which was considered as the bed retention facies of the last glacial period (Shi et al., 2022). Thus, we mainly focus on the upper 44.3 m of the core in this study. The chronology of the core is based on accelerator mass spectrometry radiocarbon (AMS 14C) dating of 11 samples of plant fragments and bulk organic sediments by Beta Analytic Inc., Miami, USA (Table 1). The age-depth model was constructed using the Bayesian Bacon method (Blaauw and Christen, 2011) and suggested that the core spans the last ca. 13.5 ka (Fig. 4). Sedimentation rates from 12.0 to 17.5 m are fairly high, while those from 17.5 to 22.0 m are lower. The average temporal sampling resolution is ca. 103 years.

### 4.2. Fossil pollen record

In total, 141 pollen and spore types were identified in 131 samples from the MZ core. The most abundant and representative taxa are shown in the pollen diagram (Fig. 5). All the pollen assemblages are dominated by arboreal and herbaceous pollen. The most abundant evergreen taxa are Castanopsis and Cyclobalanopsis, which collectively account for 70-85% of the total pollen content. Other frequently detected taxa in assemblages include arboreal taxa are Pinus, Alnus, Carya, Corylus as well as Juglans, and herbaceous taxa such as Artemisia, Poaceae and Cyperaceae. Based on a CONISS analysis of the pollen data, the pollen sequence was divided into the following four main zones.

#### 4.2.1. Zone 1 (13.2-12.0 cal ka BP, 44.3-39.5 m)
In this zone, the mean percentage of arboreal pollen is high (89.1%), and the dominant taxon is Cyclobalanopsis (27.1%) and Castanopsis (37.8%). Other frequent evergreen taxa are Altingia (1.8%), Elaeocarpus (1.7%), Eurya (3.6%), Mallotus (1.4%) and Moraceae (1.9%). The percentage of deciduous taxa is relatively high (7.9%), such as Carya (1.4%), Juglans (1.3%) and Ulmaceae (0.6%). The most abundant herbaceous taxa is Poaceae (4.0%). In addition, the proportion of ferns is relatively high at this stage (39.1%).
4.2.2. Zone 2 (12.0–9.5 cal ka BP, 39.5–29.5 m) The percentage of arboreal pollen (93.2 %) in this zone is slightly higher than in Zone 1, and the abundance of Castanopsis pollen is increased from 47.8 to 65.3 %. The proportion of Castanopsis exhibited an initial increase followed by a distinct decrease in this Zone. In contrast, the percentage of Cyclobalanopsis displayed a decline initially and subsequently experienced an increase (14.5 %). There is a slightly decrease in pollen from deciduous (5.5 %) and herbaceous (3.8 %) taxa.

4.2.3. Zone 3 (9.5–1.8 cal ka BP, 29.5–11.0 m) This zone is characterized by the abundance of arboreal pollen (84.7 %) and a slightly increase in herbaceous pollen (17.2 %). It is divided into two subzones:

4.2.3.1. Zone 3a (9.5–2.7 cal ka BP, 29.5–17.5 m). The percentage of arboreal pollen (85.3 %) in this zone is slightly lower than in zone 2 and the percentage of Cyclobalanopsis is reduced from 14.5 to 10.1 %. Conversely, the pollen percentages of evergreen broadleaved trees including Castanopsis (66.4 %), Celastraceae (2.2 %) and Rubiaceae (3.1 %) increase to their maximum values within the core. The percentage of herbaceous taxa is slightly higher, with Poaceae (4.2 %) and Artemisa (2.1 %) being the most abundant.

4.2.3.2. Zone 3b (2.7–1.8 cal ka BP, 17.5–11.0 m). Compared with pollen zone 3a, the proportion of arboreal pollen is still high but slightly decreased (84.1 %). The proportion of evergreen taxa decreased, and deciduous taxa increased gradually. Castanopsis (59.5 %) and Cyclobalanopsis (8.6 %) are still the dominant taxa, although their percentages declined slightly. The proportion of shrubs has increased in this zone, which has the highest abundance of pollen from the subtropical Mallotus (peaking at 5.3 %). The proportion of herbaceous taxa continues to increase.

4.2.4. Zone 4 (since 1.8 cal ka BP, 11.0–2.4 m) This zone is characterized by a markedly increased herbaceous pollen content (40.9 %), with Poaceae (27.5 %) and Artemisa (4.2 %) being the most abundant taxa. The proportion of deciduous taxa and conifer pollen also increases significantly, while that of arboreal taxa clearly declines. Some evergreen taxa (e.g. Elaeocarpus, Ilex, Macarange and Theaceae) are the lowest proportion of the entire core, while the abundance of Alnus (3.1 %), Corylus (2.8 %), and Cyperaceae (5.3 %) pollen rises to the highest.

4.3. Ordination of pollen assemblages

PCA of the relative frequencies of pollen of 31 selected taxa in the 131 samples of the MZ core yielded first and second Principal Components (PCs) with variance explained of 69.9 % and 21.5 %, respectively (Fig. 6). The results of PCA suggest that the taxa composition of the MZ core can be broadly categorized into four groups (Fig. 6a). Firstly, taxa such as Castanopsis, Rubiaceae, Mallotus, and Celastraceae exhibit negative loadings for PC1 and are commonly found in tropical and subtropical semi-humid EBLF or monsoon EBLF regions. It can be inferred that PC1 primarily represents the combined influence of precipitation and temperature. Taxa with negative loadings for PC2 include Cyclobalanopsis, Theaceae, Eurya, and Altingia. These vegetation types also thrive in relatively warm and humid climatic conditions, predominantly as dominant taxa in mid-montane moist EBLF habitats which are slightly colder/drier compared to the previous group of taxa. In addition, taxa such as Poaceae and Artemisia, which are mainly herbs, along with the typical component of secondary forest Alnus, have positive loadings for PC1 and negative loadings for PC2. Hence, it can be inferred that anthropogenic activities exert a significant influence on the spatial distribution of pollen taxa in this direction. The PCA analysis of the pollen data delineated four distinct regions, corresponding to the aforementioned four pollen zones (Fig. 6b). Notably, Holocene Zones 3 exhibited significantly negative positions along PC1, indicating warmer/wetter climatic conditions during those periods. Conversely, samples from Zone 1 and 2 (deglaciation) displayed positive positions on PC2, suggesting slightly cooler and drier environmental conditions at that time. Interestingly, all samples from Zone 4 clustered in the upper right region, implying a
limited association be tween vegetation taxa and climate change during this phase due to direct human influences.

## 4.4. Quantitative climate reconstruction

### 4.4.1. Climatic variables for quantitative reconstruction

As a rule of thumb, if the VIF values exceed 5, some of the six variables in this study are strongly correlated, without an independent effect on the regression procedure, thereby implying that these redundant variables should be excluded until all remaining variables have VIF values smaller than 5 (Brien, 2007), some of the six variables in this study are strongly correlated, without an independent effect on the regression procedure, thereby implying that these redundant variables should be excluded until all remaining variables have VIF values smaller than 5. In this study, VIFs derived from CCA were used to remove the six variables containing large amounts of repeated information until the VIF value was small. The results show that the best variables among the climatic parameters of the MZ cores are MAT and MAP, especially for the 1400 km radius subset (Table 2). An array of partial CCA together with Monte Carlo permutation tests for the select dataset, run with each of the initial six climatic parameters as the sole constraining variable and the other parameters as covariables, indicated that the variables MAP and MAT used in this study are highly significant when solely explaining the variance of pollen data (Table 2). Moreover, correlation analysis showed that the Spearman coefficients of MAT vs. MST/MWT and MAP vs. MSP were high, particularly with a coefficient of 0.95 for MAT and MWT, suggesting their strong linear relationships (Fig. 7), and confirming that MAT and MAP were sufficiently representative climate variables to describe glacial-interglacial variability. Thus, MAP and MAT should the most appropriate climate variable for final reconstruction.

### 4.4.2. The performance of different models

In this study, the error estimates show that WAPLS provided rela tively lower RMSE for climatic variables than the other transfer function methods (WA, LW-WA and LW-WAPLS) (Table 3). The calibration models, in general, demonstrate statistical robustness with RMSE values ranging from 2.5 to 4.2 °C for MAT and 160 to 230 mm for MAP, accompanied by consistently high R2 values exceeding 0.6. Notably, the WAPLS model exhibits the lowest RMSE and higher R2 for MZ core. Moreover, previous studies have also found that WAPLS was most suitable for calibration of pollen records with no significant changes in vegetation types (Zhao et al., 2021). Thus, WAPLS was finally selected as the most reliable model for final climate reconstruction.

### 4.4.3. Climate changes since the deglaciation

The quantitative results of the two climate variables (MAP and MAT) over the last 13.2 ka are displayed in Fig. 8. The pollen-based MAP reconstruction exhibits an upward trend during the deglaciation (ca. 13.2–10.0 ka), attaining its peak value (ca. 1810–1840 mm) in the early Holocene (ca. 9.2–6.8 ka), and subsequently undergoing a gradual decline. The mean amplitude of precipitation changes since 13.2 ka was ca. 80–120 mm, i.e. about 18 % of that today. The minimum amount of precipitation occurred at ca. 12.3 ka, which coincides with the Younger Dryas (YD) event. As for temperature reconstruction, the output MAT curve shows a variability ranging from 19.5 °C to 22.5 °C since 13.2 ka. The trend of temperature change since the deglaciation period follows a similar pattern to that of precipitation, with an initial rise followed by a decline. However, the increase in temperature persisted until ca. 7.2 ka and subsequently decreased after reaching its peak during the mid-late Holocene (ca. 7.2–2.8 ka). The quantified results demonstrate a asyn chronous variation between MAP and MAT changes since the deglaciation period, especially during the early-mid Holocene.

## 5. Discussion

### 5.1. Vegetation succession
Our well-dated pollen record of MZ core provides a comprehensive understanding of the regional vegetation response to tropical climatic variations since 13.2 ka (Fig. 5). The findings indicate that the research area was predominantly occupied by evergreen broadleaved forests (EBLF) during 13.2–1.8 ka, with Castanopsis and Cyclobalanopsis as the dominant taxa. Throughout the deglaciation period (13.2–9.5 ka), the relatively higher abundances of Cyclobalanopsis, Pinus, and deciduous taxa, such as Carya, Corylus and Ulmaceae, indicate the presence of comparatively colder and drier conditions (Flora of China, 2013). In the early to mid-Holocene (9.5–1.8 ka), there was a peak in the proportion of Castanopsis and numerous (sub)tropical evergreen taxa such as Celastraceae, Ilex, Macaranga, and Rubiaceae. This could be interpreted as an adaptive response to gradual climate warming and intensified East Asian Summer Monsoon (Marcott et al., 2013). During 12.5–12 ka, a significant decline in the concentrations of Castanopsis and other tropical taxa was observed, accompanied by an increase in the abundance of Cyclobalanopsis and Poaceae. This abrupt shift towards colder climatic conditions may correspond to the YD event. The pollen diagram and the PCA results of the MZ site illustrates the vegetation history encompassing the deglaciation and Holocene, which corroborates the findings from the other cores from the PRD region, such as QZK6 (Zhao et al., 2014) and BS01 (Zhang et al., 2024a, 2024b). Moreover, the (sub)tropical pollen taxa identified in MZ core exhibit parallels with other broader-ranging pollen records. For instance, the proportion of Cyclobalanopsis in the HGY Maar lake record clearly decreased during the transition from the deglaciation to the Holocene (Mei et al., 2017), concurrently, Castanopsis experienced a abrupt increase during the early Holocene in the pollen record of Shuangchi Maar lake (Dodson et al., 2019). The pollen record from core NPK2 suggests that during the last glacial period, the vegetation in northeast Thailand was predominantly characterized by EBLF, with Cyclobalanopsis and Pinus being the most abundant taxa (Penny, 2001). However, there was a rapid transition to a tropical rainforest ecosystem primarily composed of Rubiaceae, Combretaceae, and Myrtaceae during the Holocene. These pollen records indicate that although the expansion of deciduous broadleaved forests (DBLF) in northern China extended to the southern subtropical regions during the deglaciation (Li et al., 2019; Wang et al., 2018), their migration did not encompass the PRD, Indochina Peninsula, and other East Asian tropical areas (Zheng et al., 2023). It is noteworthy that the pollen records from the tropical maar lakes show a predominant representation of Poaceae taxa during the glacial period, such as HGY (Mei et al., 2017) and TY (Chen et al., 2023a, 2023b), which diverges from the MZ or the other cores of PRD and can likely be attributed to localized fluctuations in water levels. According to the principles of physiognomy, ecological phenomena, and acclimatization, the subtropical EBLF was categorized into five subclasses, namely semi-humid EBLF, monsoon EBLF, mid-montane moist EBLF, montane mossy EBLF, and montane mossy dwarf EBLF (Flora of China, 2013). Among these, the montane mossy (dwarf) EBLF have formed only in very specific topographic habitats such as near mountain summits. The semi-humid EBLF and monsoon EBLF, characterized by taxa such as Castanopsis, Cyclobalanopsis, and Lauraceae, which highly consistent with the main taxa of our pollen record during the early to mid-Holocene. Nevertheless, compared with the former two forest types, the proportion of Cyclobalanopsis is relatively higher in the modern mid-montane moist EBLF, and besides dominant taxa of Faga ceae, Theaceae and Magnoliaceae etc. also appear as co-dominants (Tang, 2015). These floristic assemblages exhibit a higher degree of resemblance to the pollen records documented during the deglaciation of the MZ core. Thus, during the transition from the deglaciation to the Holocene warm period, the vegetation types surrounding the study area might have progressively shifted from mid-montane moist EBLF to semi-humid EBLF or monsoon EBLF. The latter two forest types demonstrate a comparatively narrower contemporary distribution range in contrast to the former, yet exhibit more intricate vegetation characteristics (Flora of China, 2013), implying that biodiversity was notably higher during the transition from deglaciation to the Holocene in the PRD region. In addition, modern (sub)tropical regions exhibit a distribution range of Cyclobalanopsis that is ca. 200–300 m higher than that of Castanopsis (Flora of China, 2013). This suggests, based on temperature lapse rate calculations, that the average temperature during the deglaciation in our study area was ca. 1–3 °C lower than in the early-mid Holocene. This finding is
basically consistent with our aforementioned quantified values and the other tropical reconstructed
results (Li et al., 2023). Since 1.8 ka, an abrupt escalation in the abundance of secondary genera
such as Alnus, Pinus, Corylus, and an increase in the proportion of Poaceae, have occurred. This
unambiguously demonstrates significant human interference in the regional vegetation, further
corroborating the dissemination and evolution timeline of rice or sugarcane agriculture in the PRD
region (Ma et al., 2020; Shi et al., 2022).

5.2. Reliability evaluation of reconstruction

The relevant evaluation of reliability is crucial before delving into the practical significance of the
afore-mentioned quantitative recon struction results (Birks, 2012). The climate quantitative
reconstruction framework employed in this study has undergone rigorous quality evaluation of the
reconstruction process from multiple perspectives to ensure accuracy. This includes assessing the
calibration set's quality, prediction error, statistical significance of the reconstruction sequence, and
ecological explanation. The goodness of fit analysis revealed that 98 % of the fossil samples exhibit
a strong correspondence with modern samples, as indicated by squared residual distances falling
below the 90th percentile. This dem onstrates that nearly all fossil samples bear significant
resemblances to their counterparts in the calibration set (Fig. 9a). Consequently, our framework has
successfully identified a high-quality calibration set, which serves as a reliable foundation for
subsequent analyses. In addition, results of the leave-one-out cross-validation pollen- inferred
MAP/MAT of predicted vs. observed values reflects the good inference power of the calibration set
and model (Fig. 9b, e). The RMSE for the reconstruction of MAT and MAP are 2.8 ° C and 174.3
mm, respectively. Both variables exhibit correlation coefficients (R2) higher than 0.7. Furthermore,
the RMSE values fall within the range of climate fluctuations observed during the Holocene,
thereby mitigating the po tential misinterpretation of trends caused by errors. To further assess the
reliability of the reconstructed climate vari ables, we carried out a ‘significance test’. Specifically,
the fossil pollen data were analyzed using RDA to determine the maximum amount of variance
explained by one axis. Some 999 reconstructions were gener ated using the same modern and fossil
data. In this approach, if the re constructions with real climatic data explain more of the variance in
the fossil data than 95 % (or other selected threshold) of the reconstructions based on random
climatic data, then the reconstructions can be considered significant (Birks, 2012). In this study, the
significance tests showed that the two selected climate variables (MAT and MAP) explain more of
the variance than 95 % of the random reconstructions (Fig. 9d), further validating the climatic factor
selection and high credibility of the reconstruction. It is noteworthy that both MSP and MWT have
also passed the ‘significance test’. Based on the analysis results of the aforementioned modern
pollen data, both reconstructed MSP and MWT exhibit similar trends to the reconstructed MAP and
MAT, respectively, indirectly suggesting that our reconstruction of MAP is primarily influ enced by
summer conditions, while MAT more prominently reflects changes in winter temperatures. In
addition to statistical analysis, a robust ecological explanation provides support for the reliability of
MAP and MAT reconstructions (Fig. 9c, f). The selected taxa for the pollen dataset range from 1100
to 2200 mm for MAP and 5 to 27 ° C for MAT. The average optimal value of MAP in the modern
calibration set was ca. 1700 mm, while the MAT was around 15 ° C. Although the mean values of
these two climate variables are slightly lower than those in modern climate data of PRD region, the
selected modern databases encompass sufficient climate gradients both upward and downward to
cover the climate fluctuations since deglaci ation in PRD, effectively minimizing the potential
errors caused by ‘edge-effect’ (Birks, 2012). Therefore, the calibration set selected by the rigorous
analysis is effective in avoiding the underestimation or over estimation of the transfer function due
to the selection of modern sample unevenness. Importantly, it should be noted that the natural
vegetation types in the PRD region have been significantly disrupted by anthropogenic ac tivities
since 1.8 ka, resulting in a rapid proliferation of Poaceae, Pinus, and secondary plants (Ma et al.,
2020; Shi et al., 2022). Consequently, the reliability of climate reconstruction results from this
period is compromised. Similar instances of unreliable reconstruction outcomes due to human
interventions during the late Holocene can also be observed in certain pollen-based paleoclimate
records within the Asian monsoon region, such as Southwest (Xiao et al., 2023; Zhang et al., 2023), Central (Huang et al., 2023), Eastern (Lu et al., 2019) and Northern China (Stebich et al., 2015).

### 5.3. Possible forcing of hydroclimate and thermal variations

Our pollen-based MAP shows lower values during the deglaciation and increases in the early Holocene, maintaining high values until ca. 6 ka, followed by a gradual decrease. The rainfall experiences a subse quent increase at 2–3 ka, as evidenced by the findings from the previous pollen-based precipitation in the PRD (Zhao et al., 2014). To investigate the factors that directly and indirectly control the rainfall variations at PRD since deglaciation, we compare our result with proxy records of broad-scale atmospheric circulations (Fig. 10). The result shows that the precipitation variation is perfectly consistent with the titanium con centration data from the Cariaco Basin, indicating that the tightly linking between tropical EASM and the position of the ITCZ at orbital timescales, with high rainfall corresponding to strong monsoonal cir culation and northward movement of the ITCZ (Haug et al., 2001). The north–south migration of the ITCZ, although insufficient to fully account for precipitation changes in low–latitude regions on decadal to centen nial timescales (Yan et al., 2015), undeniably remains one of the primary influencing factors for rainfall variations in East Asia at orbital scales. In addition, the millennial to orbital timescale migration of the mean annual position of the ITCZ is strongly related to changes in the mean summer temperature (MST) variations associated with summer inter- tropical insolation gradient (SITIG) (Reichart, 1997), Northern Hemi sphere high-latitude climate (Wang et al., 2007) and the Atlantic meridional overturning circulation (AMOC) (Chiang and Bitz, 2005). Among these factors, the fluctuation in MST may be considered as the most crucial determinant influencing hydroclimate variations in the PRD. This is supported by the remarkable consistency observed between our reconstructed MAP and stalagmite records in East Asia (Cheng et al., 2016) and model simulations (Liu et al., 2018). As shown in Fig. 10, the higher TraCE simulated MST of PRD and SITIG during the early and middle Holocene resulted in intensified ocean-to-land thermal gradi ents, thereby enhancing monsoon circulation and increasing water vapor transport to the PRD. Consequently, this favored an augmentation of summer precipitation, and vice versa. In a recent study, three pollen records were employed in east Asian monsoon domine, comprising two from the southwest region (TCQH and CH) and one from central China (DJH), to quantitatively reconstruct the paleoclimate variations since the last glacial period (Zhang et al., 2023). The findings also underscore the influence of interhemispheric temperature gradients and climate teleconnections between high and low latitudes on monsoon variability in glacial-interglacial scales. In contrast to precipitation changes, our reconstructed MAT show higher values during the late Holocene compared to the early Holocene, indicating a warming trend. This finding is generally consistent with TraCE simulations except for the last 2000 years (Fig. 10). However, both quantified and simulated MAT/MWT differ significantly from simulated MST in the PRD, suggesting that winter signals are more pronounced in reconstructed MAT changes than summer signals. In a recent study, REVEALS model was employed to calibrate the recon struction findings of the Holocene in South China, revealing that annual/winter temperatures exhibited an upward trend during the late Holocene unaffected by anthropogenic influences (Wan et al., 2024). By integrating pollen data from 642 sites across North America and Europe, Marsicek et al. (2018) conducted a comprehensive reconstruction of Holocene temperature variations, encompassing MAT, MWT and MST. Their analysis unveiled a consistent warming trend in both MAT and MWT throughout the Holocene until 2 ka. In contrast, MST exhibited an initial increase during the early Holocene but gradually declined thereafter. This finding is highly congruous with our climate recon struction of MZ core. Thus, it is noteworthy that the aforementioned results are not only observed in tropical regions of China, but also ex tends to a broader geographical scope. The pollen-based thermal proxies we employed, similar to numerous alternative indicators showing an upward trend in winter temperatures during the Holocene (Rao et al., 2016; Luo et al., 2023; Charbit et al., 2007), exhibit a robust agreement with ice volume data for the Northern Hemisphere (NH) (Fig. 10e). This concurrence suggests that ice sheet variations were
a key factor governing MAT variations in tropical China. In a recent study, Li et al. (2023) employed brGDGTs extracted from sediment of HGY Maar Lake to quantitatively reconstruct the mean annual air temperature (MAAT) record since 21 ka, which exhibits a high degree of concordance with our own quantified MAT. This inves tigation underscores the significance of ice sheet fluctuations, winter monsoon variability, and shifts in the ITCZ during the late Holocene in exerting influence on regional temperature changes. In addition, during the deglaciation period to the Holocene, there is a clear upward trend observed in sea surface temperature (SST) and ma rine δ18O records derived from planktonic foraminifera in the western Pacific Ocean (Jian et al., 2020). The magnitude of SST increase aligns with our reconstructed MAT, indicating a close relationship between El Niño-Southern Oscillation (ENSO) variability and MAT changes in the study area (Fig. 10g). Generally, El Niño exhibits a significant positive correlation with winter air temperature variability, particularly when negative temperature anomalies occur in eastern China during EP La Niña phases (Wang et al., 2015). An amplified ENSO during the late Holocene and a weakened ENSO during the middle Holocene have also been acknowledged (Carré et al., 2014), although their long-term connection with climate patterns in China remains unclear. To conclude, our reconstructed temperature findings once again validate that the primary source of uncertainty regarding Holocene temperatures stems from seasonal biases present within temperature proxies (Bova et al., 2021). 5.4. Decoupled precipitation and temperature variability in the Holocene The co-occurrence of rain and heat is a distinctive characteristic of the East Asian monsoon climate. Specifically, elevated temperatures during summer are frequently accompanied by substantial precipitation. However, this feature is more pronounced on a short-term scale within summer variations and does not hold true when observed over a mil lennium timescale (Lu et al., 2024a, 2024b). Our quantified precipita tion record shows an initial increase followed by a subsequent decrease from the early Holocene (10–6 ka) to the late Holocene (6–2 ka), which aligns with the north-south movement of ITCZ associated with the MST variations. Nevertheless, there exists a notable disparity in the quanti fied MAP and MAT using the identical methodology. According to conventional wisdom, fluctuations in insolation at high latitudes in the northern Hemisphere have been responsible for climate shifts from cold glacial to warmer and wetter interglacials like the Ho locene (Tzedakis et al., 2017). Consequently, a decline in insolation could directly result in decreased temperature and precipitation within this region. Nevertheless, our reconstructed MAT do not correspond with alterations observed in annual solar radiation at similar latitudes (Laskar et al., 2004). This inconsistency might stem from high-latitude areas being more susceptible to changes in summer insolation due to their larger proportion of continental landmasses. Conversely, tropical regions with comparatively less continental landmass relative to oceans experience potential influences on annual or winter temperature through interactions between the ocean and atmosphere (Marcott et al., 2013). In order to gain a deeper understanding of the relationship between precipitation and temperature in the East Asian monsoon region during the Holocene, we conducted a collection and selection of quantified climate records from different latitude. As shown in Fig. 11, with the exception of tropical regions, there is a lack of synchronization between annual or seasonal precipitation and temperature changes in other areas of the East Asian monsoon region during the Holocene. Recently, 67 quantified temperature records in China were con ducted and categorized into four distinct patterns of change (Wu et al., 2023). Among these, both the central and northern regions of China exhibited a gradual decline from the early to late Holocene, indicating a ‘cooling’ or ‘MHW’ pattern, whilst records show a relatively colder mid- Holocene and warmer late Holocene in the westerlies domain. This spatial heterogeneity of Holocene temperature variability is attributed to the modulation of monsoon systems, including the warming effect of Asia summer monsoon and the cooling effect of the East Asian winter monsoon. However, during the mid/late Holocene, there were high values of precipitation records in certain areas such as XJ (Lu et al., 2019), GH (Chen et al., 2015), BYCG (Jiang et al., 2006), SHLW (Stebich et al., 2015) and YL (Zhou et al., 2022). It is evident that the precipi tation in these regions did not synchronize with annual temperature changes and the duration of high temperature/precipitation signifi cantly differed from (sub)tropical regions (Fig. 11). According to Zhou et al. (2022), there has been a
distinct ‘time-transgressive’ pattern of precipitation from south to north within the EAMD during the Holocene. The primary driver behind this pattern is variations in monthly solar radiation across latitudes. Additionally, it has been proposed that contemporary fluctuations in summer monsoon precipitation within this region are influenced by the northward movement of the Western Pacific Subtropical High (WPSH) (Yu et al., 2013). These studies indicate that the decoupled annual or seasonal climate variations during the Holocene in EAMD, i.e. there is a phase difference of about 2–4 ka between the peak values of precipitation and temperature, may be primary attributed to differences in influence factors among different climate variables from a broader perspective. However, at a regional scale, we suggest that this asynchrony may be more closely associated with variations in local cloud cover. Thicker layers of clouds have the ability to reflect solar radiation, thereby influencing air and soil temperatures. According to meteorological station data, there has been an inverse correlation between total cloud cover and sunshine hours in the EAMD over the past 50 years (Wang et al., 2024). Conversely, it has exhibited a positive correlation with humidity and precipitation. Based on this inference, it is speculated that higher cloud cover during the early Holocene in the PRD region would have accompanied increased precipitation, resulting in reduced annual or winter air temperature due to an enhanced albedo effect. Wu et al. (2018) reconstructed summer temperatures (pollen) and annual precipitation (δ18O) records from XY lake in southwestern China using the same sediment. They observed that there was a lag of ca. 2000 years between precipitation and temperature increase, which high lighting the influence of early Holocene cloud cover on climate variables in this region. Similar results were also evident in climate re constructions from CH (Zhang et al., 2023) and QH lake (Wang et al., 2021). These studies propose that during the early Holocene, high cloud cover associated with increased precipitation may have contributed to disparities between rainfall and temperature not only in subtropical regions of China but also on a larger scale. To gain a deeper compre hension of the influence of cloud cover on climate factors, the TraCE was employed to simulate the temporal variations in seasonal cloud cover within the EAMD during the early and late Holocene in this study, specifically focusing on the disparity between average cloud cover from 10 to 6 ka and 6–2 ka (Fig. 12). The findings indicate a significant in crease in winter cloud cover during the early Holocene compared to the late Holocene in southern China, while northern China experienced an opposite trend. Conversely, summer cloud cover exhibited a slightly higher value during the early Holocene in northern and western regions of China. Moreover, there was a more pronounced variation in winter cloud cover during both periods of the Holocene (–13–24 %), as opposed to summer (–7–7 %). Thus, it can be inferred that the winter cloud cover in the EAMD during the Holocene may exhibit similar annual or winter temporal variations to precipitation, i.e. during the early Holocene, there was a relatively high winter cloud cover in (sub) tropical regions, accompanied by increased rainfall and lower annual or winter temperatures. Subsequently, central and northern China experi enced high winter cloud cover during the middle and late Holocene respectively. The hypothesis provides a plausible explanation for the observed disparity in temporal patterns between annual temperature and precipitation in East Asia during the Holocene, with regional vari ations contributing to this lack of synchronicity. Specifically, there is a clear phase difference of precipitation from central to northern regions, while the temperature phase difference pattern is more pronounced in southern areas (Lu et al., 2024b). A recent study suggests that the var iations in East Asian monsoon may exert a more pronounced influence on regional temperatures during the Holocene, as compared to solar radiation and greenhouse gases in the Northern Hemisphere, thereby indirectly corroborating the aforementioned hypothesis (Wu et al., 2023). It is important to mention that not all climate records in East Asia from the same region show asynchronous patterns. For instance, annual temperature records from TCQH (Xiao et al., 2023), Tiancai (TC) (Zhang et al., 2017), YZH (Wu et al., 2023) and other areas in the southwest indicate higher temperatures during the early Holocene, while precipi tation records from central regions like JZ (Huang et al., 2023) suggest relative humidity during this period. These discrepancies imply that high winter cloud cover in southern China during the early Holocene may be a regional contributing factor, which is supported by our simulation results (Fig. 12). Furthermore, variations in dating accuracy and reconstruction methods could also
contribute to these differences. In general, the relationship between precipitation and temperature
during the Holocene in EAMD exhibits a high degree of complexity. While variations in winter
cloud cover regulated by solar radiation may constitute one of the significant factors contributing to
asynchronous changes, these variations ultimately arise from the synergistic effects of multiple
driving forces. Our findings provide novel empirical support for investigating climate-related issues
pertaining to the EAMD under con ditions of global warming.

6. Conclusion

Our pollen analysis provides a continuous record of vegetation changes in the PRD since the deglaciation. The result shows that the study area was covered by mid-montane moist EBLF from 13.2 ka to 9.9 ka, with Cyclobalanopsis and Castanopsis being the most abundant taxa. Then shifted to semi-humid EBLF or monsoon EBLF during the transition from the deglaciation to the Holocene warm period. Over the past 1900 years, dominant taxa were anthropochory plant, which can be attributed to early human activities. By incorporating modern pollen data, the quantified climate records since 13.2 ka reveal an average magnitude of MAP fluctuations at ca. 80-120 mm, while MAT ranged from 19.5 °C to 22.5 °C. There is a distinct temporal disparity of ca. 2-4 ka between precipitation and annual temperature variations in the PRD during the Holocene. The quantified variation in precipitation aligns well with the movement of the ITCZ, which is influenced by MST; meanwhile, changes in ice volume in the Northern Hemisphere exert greater control over temperature fluctuations.

By comparing climate records in the EAMD, we have observed a latitudinal phasing in precipitation and temperature changes during the Holocene. This phasing is primarily evident in the precipitation records of central-northern China and the temperature records from southern to central regions. The asynchrony observed at large regional scales may potentially be attributed to variations in dominant controlling factors among different climate variables. Additionally, model simulations support the notion that local-scale differences in winter cloud cover could serve as another influential factor.

CRediT authorship contribution statement

Xiao Zhang: Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Data curation, Conceptualization, Funding acquisition. Cong Chen: Writing – review & editing, Method ology, Investigation. Kexin Wang: Validation, Software. Meihuan Li: Formal analysis, Investigation. Yuanfu Yue: Writing – review & editing, Validation. Jun Cheng: Validation, Software, Methodology, Data curation. Mengna Liao: Validation, Software, Methodology. Kai Li: Writing – review & editing, Software. Lina Liu: Software, Data curation. Zhanghua Wang: Methodology, Investigation. Rachid Cheddadi: Writing – review & editing. Qiuchi Wan: Methodology, Investigation, Formal analysis. Yongjie Tang: Investigation. Zhuo Zheng: Writing – review & editing, Methodology, Conceptualization. Kangyou Huang: Writing – review & editing, Methodology, Investigation, Funding acquisition, Conceptualization, Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments This work was supported by the National Key Research and Devel opment Program of China (2023YFC3008600 & 2022YFF0801501) and National Natural Science Foundation of China (42472246). Project supported by Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (No. SML2023SP239).

Data availability

Data will be made available on request.
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<figure><img src="image_3.png" /><figcaption>Fig. 1. (a) Topography and location of the MZ site and the cores used for correlation. Pollen-based, Sihailongwan (SHLW) (Stebich et al., 2015); Bayanchagan (BYCG) (Jiang et al., 2006); Gonghai (GH) (Chen et al., 2015); Dajiuhu (DJH) (Sun et al., 2019; Zhang et al., 2023); Jianghai plain (JZ) (Huang et al., 2023); Chaohu (CHH) (Li et al., 2018) Xinjie (XJ) (Lu et al., 2019); Caohai (CH) (Zhang et al., 2023, 2024a, 2024b); Dahu (Xiao et al., 2007); Shuizhuyang (SZY) (Zheng et al., 2023); Gaoyao (GY) (Zhang et al., 2024a, 2024b); Tianyang (TY) (Chen et al., 2023a, 2023b); Hugguangyan (HGY) (Li et al., 2023); MZ (this study). Stalagmite, Sanbao (SB) (Cheng et al., 2016); Dongge (DG) (Wang et al., 2007). (b) The PRD and locations of study core.</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>Fig. 2. Conceptual diagram illustrating the five different approaches (BAT, WA, WAPLS, LW-WA and LW-WAPLS) to multivariate calibration. (Modified from Birks, 2012).</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Fig. 3. Location of the study record and selected modern pollen sites. Topographic map of China and adjacent areas showing the location of the MZ core, and modern pollen sampling sites within 800–1500 km radii. DESE = Desert; STEP=Steppe; ALSM = Alpine shrub-land, meadow/tundra; CLMX = Cold mixed forest; ESQF = Evergreen sclerophyll Quercus forest; DBLF = Temperate deciduous broadleaved forest; EBLF=Subtropical evergreen broadleaved forest; TRFO = Tropical rainforest.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>Fig. 4. Lithology and age-depth model of the MZ core.</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Fig. 5. Pollen percentage diagram of selected taxa of MZ core. The solid and faded plots show the same percentage values on actual percentages and x3 exaggeration.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>Fig. 6. PCA ordination of pollen percentage data. (a) PCA results based on selected pollen taxa. (b) Biplot of the PCA result for pollen data.</figcaption></figure>

<figure><img src="image_9.png" /></figure>
Fig. 7. Results of a correlation analysis of six climate variables of selected 1049 modern samples. The MZ core was taken as the centers (r = 1400 km) of the corresponding modern pollen datasets.

<figure><img src="image_10.png" /></figure>

Fig. 8. Quantified (a) MAP and (b) MAT using the WAPLS calibration model based on pollen records of the MZ core. RMSE value is shown below.
<figure><img src="image_11.png" /><figcaption>Fig. 9. Reliability evaluation of pollen-based climate reconstruction of MZ core. (a) Scatter plots of squared chord distances between each fossil sample and nearest modern analog; scatter plots of observed and predicted (b) MAP and (e) MAT using WAPLS model; (d) significance test results; optima and tolerances of (c) MAP and (f) MAT for selected pollen taxa based on calculated weighted averages.</figcaption></figure>

<figure><img src="image_12.png" /><figcaption>Fig. 10. Comparison of the quantified MAP and MAT with correlated climate records. (a) the July 21 30° N–30° S insolation (SITIG) (Laskar et al., 2004) and Stalagmite δ18O values (Cheng et al., 2016); (b) pollen-based quantified MAP for QZK4 (Zhao et al., 2014) and MZ core; (c) Ti concentrations of Cariaco Basin (Haug et al., 2001). (d) TraCE simulated MST of MZ site; (e) ice volume of Northern Hemisphere simulated using ECHAM3 (Charbit et al., 2007) and brGDGTs-based MAAT of HGY Maar lake (Li et al., 2023); (f) Pollen-based quantified MAT for MZ core; (g)</figcaption></figure>
G. ruber δ18O and SST (based on G. ruber Mg/Ca) of western Pacific Ocean (Jian et al., 2020); (h) TraCE simulated MAT and MWT of PRD.

<figure><img src="image_13.png" /></figure>

Fig. 11. Selected quantified (a) precipitation and (b) temperature records since 12 ka in EAMD. SHLW (Stebich et al., 2015); GH (Chen et al., 2015); Hulun (HL) (Wen et al., 2009); XJ (Lu et al., 2019); CHH (Li et al., 2018); DJH (Zhu et al., 2009; Sun et al., 2019; Zhang et al., 2023); CH (Zhang et al., 2023); XY (Wu et al., 2018); Dahu (DH) (Zhou et al., 2022); Shuizhuyang (SZY) (Wang et al., 2017); Qionghai (QH) (Wang et al., 2021); HGY (Li et al., 2023); MZ (this study).
<figure><img src="image_14.png" /><figcaption>Fig. 12. TraCE simulated the disparities in cloud cover between the early (10–6 ka) and late (6–2 ka) Holocene. (a) Winter and (b) summer.</figcaption></figure>