Drought Types Research Articles

Characterization of the complete chloroplast genome sequence of Lycium qingshuiheense (Solanaceae)

Lycium qingshuiheense is a typical drought and salt-alkali-tolerant plant, which has been added to the new species of Lycium in recent years. Here, we first sequenced the complete chloroplast genome of L. qingshuiheense to investigate its evolutionary relationship within the family Solanaceae. Results suggested that the circular complete chloroplast genome of L. qingshuiheense was 154,945 bp in length, including a large single-copy (LSC) of 85,930 bp, a small single-copy (SSC) of 18,203 bp, and two inverted repeats (IRs) of 25,406 bp. The GC content accounts for 37.90% and annotated 131 genes, including 86 protein-coding genes, eight rRNA genes, and 37 tRNA genes. A neighbor-joining phylogenetic tree revealed that L. qingshuiheense was a sister species to L. ruthenicum. Our study provides a new insight into the systematic evolution of Lycium in the Solanaceae family.

Assessment of the Global Relationship of Different Types of Droughts in Model Simulations Under High Anthropogenic Emissions

AbstractThis study provides a global analysis of the relationship between drought metrics obtained from several climatic, hydrologic and ecological variables in a climate change framework using CMIP6 model data. A comprehensive analysis of the evolution of drought severity on a global scale is carried out for the historical experiment (1850–2014) and for future simulations under a high emissions scenario (SSP5‐8.5). This study focuses on comparing trends in the magnitude and duration of drought events according to different standardized indices over the world land‐surface area. The spatial and temporal relationship between the different drought indices on a global scale was also evaluated. Overall, there is a fairly large consensus among models and drought metrics in pointing to drought increase in southern North America, Central America, the Amazon region, the Mediterranean, southern Africa and southern Australia. Our results show important spatial differences in drought projections, which are highly dependent on the drought metric employed. While a strong relationship between climatic indices was evident, climatic and ecological drought metrics showed less dependency over both space and time. Importantly, our study demonstrates uncertainties in future projections of drought trends and their interannual variability related to the relationship among indices, stressing the importance of coherent climatic, hydrological and plant physiological patterns when analyzing CMIP6 model simulations of droughts under a warming climate scenario.

Prediction of the Hydrological Drought Index (HDI) based on Rain Simulation Data using an Artificial Neural Network (ANN) in the Randugunting Watershed, Rembang Regency

Randugunting Watershed, with the main river Randugunting River, originates from the North Limestone Mountains of Rembang Regency. Because of its cyclical nature, the river flow discharge is continually subject to change. The discharge rises during rainy weather and falls during dry weather. Due to this issue, Rembang will likely experience drought throughout the dry season. The objectives of this study are to: (1) determine the drought index and its sharpness based on the Hydrological Drought Index Method (HDI) and (2) make drought predictions using the HDI based on discharge for the years 2023–2026 using simulated rain data with Artificial Neural Networks (ANN). Calculation of regional rainfall using the Thiessen Polygon Method. To find simulated rain and drought prediction based on the ANN with Backpropagation algorithm using Mathlab software. From the analysis indicate that the number of months that would experience wet conditions are decreasing from 7 months in 2023 and 2024 to 6 months in 2025 and only 3 months in 2026. In the anticipated drought from 2023 to 2026, there will be 14 dry months, 8 very dry months, and 3 extremely dry months. The examination of the hydrological drought’s duration revealed that the typical drought period fell between May and November.

Contrasting characteristics and drivers of dry and warm snow droughts in China's largest inland river basin

Study regionThe largest inland river basin in China (the Tarim River Basin) Study focusThis study introduces a novel classification scheme for dry and warm snow droughts with focus on their duration, severity, and intensity. The Nonparametric Standardized SWE Index (NSWEI) and the Standardized Precipitation Index (SPI) were employed to assess these drought types. The optimal parameters-based geographical detector (OPGD) model and machine learning (including random forest model and Shapley-XGBoost algorithm) were applied to reveal the spatial and time dynamic driving forces of droughts. New hydrological insights for the regionsResults indicated that warm-type droughts occurred more frequently and with greater intensity, exhibiting a larger spatial coverage compared to dry-type droughts, which can be attributed to warm-type droughts dominated by temperature and vapor pressure deficit, whereas dry-type are predominantly influenced by relative humidity and solar radiation. Moreover, the dynamics of snow droughts exhibited a contrasting pattern between the south (experiencing an upward trend) and the north (experiencing a descending trend). In the south, dry-type droughts were exacerbated by the strength of North Pacific Oscillation (PDO)-precipitation coupling, while warm-type droughts are influenced by the strength of North Atlantic Oscillation (NAO)-precipitation coupling and El Niño Southern Oscillation (ENSO)-precipitation.

Effects of multi-year droughts on the precipitation-runoff relationship: An integrated analysis of meteorological, hydrological, and compound droughts

Multi-year droughts cause severe water scarcity, ecosystem collapse, and significant socio-economic losses. Understanding the impact of these droughts on the precipitation-runoff (PR) relationship is crucial for managing water resources and mitigating drought-related damage. However, previous research focuses mainly on the influence of multi-year meteorological droughts on the PR relationship, neglecting multi-year hydrological droughts and their compound effects. Studies also generally overlook the speed and volume of precipitation-to-runoff conversion, considering only the quality of PR relationship. Furthermore, there is a lack of effective simulation methods using the intensity of multi-year droughts to understand the PR relationship. To address these gaps, this study defines multi-year compound droughts and employs three key parameters, namely, the determination of coefficient (R2), linear regression slope, and runoff coefficient, to assess the impact of multi-year droughts on changes in the PR relationship's quality, precipitation-to-runoff conversion speed, and runoff volume. A random forest model is then employed to simulate these parameters based on the intensity of multi-year droughts. Case studies conducted in three basins within the arid-semiarid region of northern China as well as in three basins in the humid region of southern China reveal that multi-year droughts result in water shortages and have a significant impact on the PR relationship. Among different types of multi-year droughts, hydrological droughts have the greatest impact on the PR relationship, followed by compound and meteorological droughts, respectively. During meteorological, hydrological, and compound drought periods, the average rainfall (runoff) is lower by 26 – 30% (33 – 58%), 18 – 28% (36 – 60%), and 18 – 26% (30 – 58%) respectively compared to non-drought periods. Furthermore, the PR relationship remains stable in the rivers of the humid region in southern China. In contrast, the Loess Plateau region in northern China exhibits a substantial decrease in both the speed and volume of precipitation-to-runoff conversion. Interestingly, this decline is not accompanied by a significant increase in the R2 of the PR relationship. The random forest approach effectively simulates key parameters of the PR relationship based on the intensity of multi-year droughts. These findings hold crucial implications for the long-term regional water resource planning.

Flash Drought in the South of Yangtze River and the Potential Impact of North Atlantic Sea Surface Temperature

AbstractFlash droughts (FDs), a type of drought with rapid onset, occurred in growing season have damaging impacts on crops, ecosystem and hence livelihoods. However, the associated physical mechanism were not well understood, which prohibits a skillful early warning. Based on the reanalysis data for 1961–2022, we diagnosed the characteristics, antecedent meteorological conditions and large‐scale atmospheric circulation of FDs over the region south of Yangtze River (SYR), a hotspot region of FDs. The FDs tend to occur during the periods before (i.e., from April to mid‐June) and after (i.e., early July–September) Meiyu season (B‐Meiyu and A‐Meiyu periods). Large precipitation deficits and rapid elevated temperature caused by anomalous subsidence and moisture divergence are responsible for the onset of FDs during the two periods. The North Atlantic tripole‐like sea surface temperature anomaly (SSTA) modes have potential impact on the anomalous circulations via modulating Rossby wave trains, but with different locations among the two periods. During B‐Meiyu period, the SSTA mode is characterized by positive SSTA over subtropical North Atlantic and negative SSTAs over the tropical and mid‐latitude ocean, triggering a “+ − + − + −” circulation pattern over North Atlantic–Eurasia, which reinforces the East Asian trough (EAT). Anomalous northeasterly winds dominate the SYR suppressing moisture transport from the tropics. The SSTA mode locates farther to the north during A‐Meiyu period, inducing a “+ − + − +” wave train over mid‐latitude North Atlantic‐Eurasia, leading to the strengthening of the western Pacific subtropical high. The high‐pressure anomalies control the SYR, resulting in anomalous subsidence and hence negative precipitation anomalies.

Drought risk assessment for early maize growth in Northeast China based on a reconstructed phenological dataset

AbstractDrought is one of the meteorological disasters to which maize is most vulnerable during its seedling stage in Northeast China. The absence of phenological data impedes the precise evaluation of the likelihood of drought during this phase. In response to these issues, this study develops a phenology model and reconstructing the data. Furthermore, it effectively assessed drought risk at the site scale by utilizing drought indicators. Using reconstructed phenological data from 217 sites from 1981 to 2015, we analysed the duration and trends of each phenological period and assessed the spatial and temporal distribution of drought frequency at each growth stage. The study demonstrated that the average date ranges for the sowing, emergence, three‐leaf, and seven‐leaf stages annually were 115–138 days, 130–151 days, 135–160 days, and 150–180 days, respectively. Additionally, there was a significant trend towards earlier dates in all phenological stages. Our research reveals notable fluctuations in drought frequency during various growth stages of early maize in Northeast China. Particularly, the period from the three‐leaf to the seven‐leaf stages emerges as the most drought‐prone, while the initial emergence to three‐leaf stage also shows considerable vulnerability. On average, the frequency of drought events during the critical three‐ to seven‐leaf stage stands at 35%. This average is surpassed in regions like Heilongjiang, northwest Jilin, northern Inner Mongolia, and southwest Liaoning, indicating a heightened risk in these areas. The early maize growth stage drought types are mainly light and moderate drought, with the three‐leaf to seven‐leaf stage, and Heilongjiang and Inner Mongolia, as the key stages and regions of concern, respectively. Identifying the principal types of drought and their occurrence in distinct regions and growth stages is pivotal for averting and reducing disasters.

Chronic drought decreased organic carbon content in topsoil greater than intense drought across grasslands in Northern China

Grasslands are expected to experience extreme climatic events such as extreme drought due to rising global temperatures. However, we still lack evidence of how extreme drought influence soil organic carbon (SOC) content in grassland ecosystems. We experimentally imposed extreme drought in two ways – chronic drought (66 % reduction in precipitation from May to August) and intense drought (100 % reduction in precipitation from June to July) to measure the effects of these two drought types on (SOC) content across six grassland sites that spanning desert steppe, typical steppe and meadow steppe in northern China. The experiment followed a randomized complete block design with six replicates of each treatment at each site. Our results showed that both chronic and intense drought decreased SOC content in the topsoil (0–10 cm) and the loss was higher in arid grasslands (desert steppe and typical steppe). Chronic drought decreased SOC content more than intense drought, with the effect again being strongest in arid grasslands. Furthermore, the response of SOC content to extreme drought was linked with the response of net primary productivity. Specifically, the response of SOC content was negatively correlated with drought sensitivity of above-ground net primary productivity (ANPP) but positively correlated with drought sensitivity of belowground NPP (BNPP). Overall, our results suggest that shifts in grassland SOC content with future drought will depend on the types of drought as well as the productivity responses and local climatic conditions such as precipitation, temperature, and aridity. The differential extreme drought impacts described here may facilitate predictions of climate change impacts on ecosystem carbon cycling.

Assessing the role of drought in dust storm formation in the Tigris and Euphrates basin

Drought is a common meteorological phenomenon and one of the world's most costly natural hazards. A large part of the Tigris and Euphrates basin (TEB) is located in the arid and semi-arid regions of western Asia and suffers from drought. Drought has many destructive effects on the environment and human societies, among which the formation of dust storms, is a major global challenge. This study aims to figure out the role of different types of drought on dust storm formation in the TEB. Standardized precipitation index (SPI), Tasseled Cap greenness index, and surface water area changes based on time series of satellite remote sensing data were considered as proxies to investigate meteorological, agricultural, and hydrological droughts, respectively. Our results show that the continuation of the 5-month and 27-month meteorological droughts are followed by agricultural and hydrological droughts, respectively. In recent decades, the TEB has experienced two prominent drought periods in 2008–2012 and 2021–2022, resulting in a 214 % and 200 % increase in dust events, respectively, compared to the 23-year (2000−2022) average. Overall, 84 %, 10 %, and 6 % of the TEB dust events can be attributed to meteorological, agricultural, and hydrological droughts, respectively.

Probabilistic Forecast of Ecological Drought in Rivers Based on Numerical Weather Forecast from S2S Dataset

Ecological droughts in rivers, as a new type of drought, have been greatly discussed in the past decade. Although various studies have been conducted to identify and evaluate ecological droughts in rivers from different indices, a forecast model for this type of drought is still lacking. In this paper, a numerical weather forecast, a hydrological model, and a generalized Bayesian model are employed to establish a new general framework for the probabilistic forecasting of ecological droughts in rivers, and the Daitou section in China is selected as the study area to examine the performance of the new framework. The results show that the hydrological model can accurately simulate the monthly streamflow with a Nash–Sutcliffe efficiency of 0.91 in the validation period, which means that the model can be used to reconstruct the natural streamflow from the impact of an upstream reservoir. Based on a comparison of ecological drought events from the observed and model-simulated streamflow series, the events from the observed series have a larger deficit volume and a longer duration of ecological droughts after 2014, indicating that human activities may lead to a more severe situation of ecological droughts. Furthermore, due to the uncertainty of precipitation forecasts, a probabilistic precipitation forecast is employed for probabilistic ecological drought forecasting. Compared to the deterministic forecast, the probabilistic ecological drought forecast has better performance, with a Brier score decrease of 0.35 to 0.18 and can provide more information about the risk of ecological droughts. In general, the new probabilistic framework developed in this study can serve as a basis for the development of early-warning systems and countermeasures for ecological droughts.

Analyzing the dynamical relationships between meteorological and hydrological drought of Wadi Mina basin, Algeria using a novel multiscale framework

Understanding the relationship between hydrological and meteorological drought in drought-prone regions is critical for proper reservoir management. This study presents a novel multiscale framework for investigating the associations between hydrological and meteorological drought based on the Time-Dependent Intrinsic Correlation (TDIC) method. Firstly, the characteristics of short, medium and long term standardized precipitation index (SPI) and the standardized runoff index (SRI) of the Wadi Mina basin (Algeria) have been analyzed based on data from 6 rainfall and hydrometric stations. Then an Improved Complete Ensemble Empirical Mode Decomposition with adaptive noise (ICEEMDAN) method is used to decompose the most correlated SPI and SRI series to different scales. A stronger association between the two types of droughts is evident in the low-frequency trend component regardless of the station, but their evolution pattern does not remain the same. Subsequently, a TDIC based running correlation analysis is performed between the modes to examine the SPI–SRI associations over the time domain and across the time scales. TDIC analysis has proven the dynamic behavior in the SPI–SRI associations bearing frequent alterations in nature and strength across the process scales and along the time domain. In general, at the intra-annual scales the SPI–SRI correlations are mostly weak positive with localized alterations to negative along the time domain, whereas the relationship is dominantly strong positive and long range at inter-annual scales up to 4 years. This dynamic behavior in the SPI–SRI association and the evolution pattern of trend decipher that the rainfall processes are not directly transferred to streamflow drought, but it also gets controlled by many other local meteorological processes.

Spatiotemporal characteristics of meteorological drought events in 34 major global river basins during 1901–2021

Meteorological drought is a crucial driver of various types of droughts; thus, identifying the spatiotemporal characteristics of meteorological drought at the basin scale has implications for ecological and water resource security. However, differences in drought characteristics between river basins have not been clearly elucidated. In this study, we identify and compare meteorological drought events in 34 major river basins worldwide using a three-dimensional drought-clustering algorithm based on the standardised precipitation evapotranspiration index on a 12-month scale from 1901 to 2021. Despite synchronous increases in precipitation and potential evapotranspiration (PET), with precipitation increasing by more than three times the PET, 47 % (16/34) of the basins showed a tendency towards drought in over half their basin areas. Drought events occurred frequently, with more than half identified as short-term droughts (lasting less than or equal to three months). Small basins had a larger drought impact area, with major drought events often originating from the basin boundaries and migrating towards the basin centre. Meteorological droughts were driven by changes in sea surface temperature (SST), especially the El Niño Southern Oscillation (ENSO) or other climate indices. Anomalies in SST and atmospheric circulation caused by ENSO events may have led to altered climate patterns in different basins, resulting in drought events. These results provide important insights into the characteristics and mechanisms of meteorological droughts in different river basins worldwide.

Agricultural drought response to meteorological drought over different agro-climatic zones of the Ganga River basin

Abstract Drought directly impacts the agricultural ecosystem, thus causing significant threat to regional and global food security. Investigating the occurrence and propagation patterns of drought events is crucial for its better understanding and mitigation. The study investigates different agro-climatic regions of the Ganga River basin from 2001 to 2020 to quantify meteorological drought using the Standardized Precipitation Index (SPI). Additionally, the assessment of agricultural drought was conducted using the Standardized Soil Moisture Index (SSMI) and Normalized Difference Vegetation Index (NDVI). For understanding the propagation dynamics of drought, Pearson Correlation Coefficient (PCC)-based approach was employed to compute the propagation time between meteorological and agricultural drought types. Stronger correlations were observed between SPI and SSMI compared to SPI and NDVI anomaly, highlighting the direct connection between precipitation and soil moisture. The results of the present study show that the time for propagation ranges within 1–11 months across the Ganga basin as inferred from the maximum PCC values between the SPI and SSMI time series. The propagation rate from meteorological drought to agricultural drought varied from 29.03 to 73.33% among different agro-climatic regions. The insights gained from this analysis on propagation time and rate can inform policymakers in formulating appropriate measure.

Influence of varied drought types on soil conservation service within the framework of climate change: insights from the Jinghe River Basin, China

Influence of varied drought types on soil conservation service within the framework of climate change: insights from the Jinghe River Basin, China

Future changes in compound drought events and associated population and GDP exposure in China based on CMIP6

Compound drought events, in which several types of drought occur at the same time, usually causes more harm to human society than just one type of drought event on its own. In this study, skill scoring methods are used to evaluate models, and then several drought indices are calculated to characterize meteorological, agricultural, and hydrological droughts, separately. Finally, the projected future changes in compound drought events, and associated population and GDP exposure to them, are further studied based on CMIP6. The results show that the frequency of compound drought events is likely to increase in northern Northwest China, Southwest China, and South China, but decrease in North and Northeast China. The projected changes in duration and severity are similar to those of frequency, i.e., mainly increasing in a few parts of northern Northwest and South China, but decreasing in Northeast and North China. The population exposure to compound drought events is expected to increase greatly in the area south of the Yangtze River Basin, slightly in Northwest China, and decrease greatly in the northeast of the Yangtze River Basin. Both climate and population have important effects on the change in population exposure. Due to the expected rapid growth in GDP, the exposure of GDP to compound drought events in almost all regions of China is projected to increase in the future, especially in eastern China, and the relative contribution of the GDP effect to the change in GDP exposure will be the largest.摘要相较于一种类型的干旱, 几种类型的干旱同时发生的复合型干旱事件对人类社会造成的危害更加严重. 本研究采用CMIP6资料, 研究中国复合型干旱事件及其相关社会经济暴露度的未来变化. 结果表明, 西北北部, 西南和华南地区复合型干旱事件频次, 持续时间和严重程度增加, 而华北和东北地区则减少. 复合型干旱事件的人口暴露度在长江流域南部大幅增加, 在长江流域以北的东部大幅减少, 其中气候和人口均对人口暴露度的变化有重要影响. 由于GDP的快速增长, 中国未来几乎所有地区复合型干旱事件的GDP暴露度增加, 特别是在中国东部, GDP效应对GDP暴露度变化的相对贡献最大.

Flash Drought Typologies and Societal Impacts: A Worldwide Review of Occurrence, Nomenclature, and Experiences of Local Populations

Abstract Flash droughts, characterized by rapid onset and intensification, are increasingly occurring as a consequence of climate change and rising temperatures. However, existing hydrometeorological definitions fail to encompass the full range of flash droughts, many of which have distinct local physical attributes. Consequently, these events often go undetected or unforecast in generic global flash drought assessments and are underrepresented in research. To address this gap, we conducted a comprehensive survey to gather information on local nomenclature, characteristics, and impacts of flash droughts worldwide. The survey revealed the widespread occurrence of these phenomena, highlighting their underresearched nature. By analyzing case studies, through literature review often in local languages to unearth elusive studies, we identified five different types of flash droughts based on their specific characteristics. Our study aims to increase awareness about the complexity and diverse impacts of flash droughts, emphasizing the importance of considering regional contexts and the vulnerability of affected populations. The reported impacts underscore the need for better integration of all flash drought types in drought research, monitoring, and management. Monitoring a combination of indicators is crucial for timely detection and response to this emerging and escalating threat. Significance Statement This study aims to better understand flash droughts worldwide and their varying characteristics and impacts. We surveyed the experiences of people affected by flash droughts and then examined a wide range of literature, including non-English and nonacademic sources. This helped us understand how flash droughts can differ from those commonly studied in the United States and China. We identified and described five types of flash droughts, some of which may not be detected by current drought measurement methods. It is crucial to include all types of flash droughts in drought monitoring systems and management plans, as they are expected to become more common due to global warming. We can then better prepare for and reduce the impacts of this growing threat.

Response of solar-induced chlorophyll fluorescence-based spatial and temporal evolution of vegetation in Xinjiang to multiscale drought.

Climate change and human activities have increased droughts, especially overgrazing and deforestation, which seriously threaten the balance of terrestrial ecosystems. The ecological carrying capacity and vegetation cover in the arid zone of Xinjiang, China, are generally low, necessitating research on vegetation response to drought in such arid regions. In this study, we analyzed the spatial and temporal characteristics of drought in Xinjiang from 2001 to 2020 and revealed the response mechanism of SIF to multi-timescale drought in different vegetation types using standardized precipitation evapotranspiration index (SPEI), solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) data. We employed trend analysis, standardized anomaly index (SAI), Pearson correlation, and trend prediction techniques. Our investigation focused on the correlations between GOSIF (a new SIF product based on the Global Orbital Carbon Observatory-2), NDVI, and EVI with SPEI12 for different vegetation types over the past two decades. Additionally, we examined the sensitivities of vegetation GOSIF to various scales of SPEI in a typical drought year and predicted future drought trends in Xinjiang. The results revealed that the spatial distribution characteristics of GOSIF, normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) were consistent, with mean correlations with SPEI at 0.197, 0.156, and 0.128, respectively. GOSIF exhibited the strongest correlation with SPEI, reflecting the impact of drought stress on vegetation photosynthesis. Therefore, GOSIF proves advantageous for drought monitoring purposes. Most vegetation types showed a robust response of GOSIF to SPEI at a 9-month scale during a typical drought year, with grassland GOSIF being particularly sensitive to drought. Our trend predictions indicate a decreasing trend in GOSIF vegetation in Xinjiang, coupled with an increasing trend in drought. This study found that compared with that of the traditional greenness vegetation index, GOSIF has obvious advantages in monitoring drought in the arid zone of Xinjiang. Furthermore, it makes up for the lack of research on the mechanism of vegetation GOSIF response to drought on multiple timescales in the arid zone. These results provide strong theoretical support for investigating the monitoring, assessment, and prediction of vegetation response to drought in Xinjiang, which is vital for comprehending the mechanisms of carbon and water cycles in terrestrial ecosystems.

Exploring the Linkages Between Different Types of Drought and Their Impacts on Crop Production in Kyrgyzstan

Exploring the Linkages Between Different Types of Drought and Their Impacts on Crop Production in Kyrgyzstan

Global Patterns and Ecological Effects of Drought Intensification: A Multiscale Analysis

This study delineates the criteria for identifying different types of droughts based on root zone soil moisture deficits, categorizing them into sudden, general, and creeping droughts. By employing an adapted version of the drought detection method proposed by Yuan et al., drought events were analyzed across 26 IPCC-SREX regions using historical soil moisture data. Our findings demonstrate that sudden droughts, which entail a rapid decline in soil moisture, predominantly occur in climatic hotspots and have shown an increasing trend over the past four decades, particularly in Central Europe and South Asia. The research also explores the seasonality of droughts, noting that flash droughts typically align with the growing season, while creep droughts often commence later in the year, potentially affecting vegetation growth in subsequent seasons. The ecological impact assessment, based on the Normalized Difference Vegetation Index (NDVI), reveals a lag in vegetation response to rapid water stress, with a marked decline in health by the end of the drought onset phase. These results underscore the varying ecological responses to drought intensification and contribute to a better understanding of their global patterns and impacts.

Combined effects of mixing ratios and tree size: how do mixed forests respond to climate and drought events?

Although the relationship between biodiversity and ecosystem functionality (BEF) has been studied comprehensively, how the mixing ratio of tree species in mixed forests affects the response of trees to climate and drought remains an unexplored and rather unknown question. Hence, we established tree-ring chronologies for Pinus tabuliformis Carr. (P) and Quercus variabilis Blume. (Q) mixed forests with different mixing ratios. In the temperate region of China, we investigated three mixing ratios: 90% P and 10% Q (P9Q1), 60% P and 40% Q (P6Q4), and 20% P and 80% Q (P2Q8). We collected tree ring samples using three tree size categories: dominant, intermediate, and suppressed trees. We explored the climate sensitivity of these trees and their drought tolerance indices-resilience (Rs), resistance (Rt), and recovery (Rc) under two drought conditions: short-term drought (1993 drought) and long-term drought (1999-2015 drought). P6Q4 made P. tabuliformis more sensitive to the Palmer drought severity index (PDSI) from the previous year than the other two ratios. The effect of the mixing ratio on drought response was insignificant under short-term drought in both tree species. Rt, Rc, and Rs of P. tabuliformis decreased with an increasing Q. variabilis:P. tabuliformis ratio in long-term drought. Rt, Rc, and Rs of Q. variabilis were the highest in P6Q4. The sensitivity of trees to PDSI varied among classes and was influenced by the mixing ratio. Dominant trees were most sensitive to PDSI in P6Q4 and P2Q8, whereas intermediate and suppressed trees were more sensitive to PDSI in P9Q1. The impact of tree size on drought tolerance indices varied according to drought type and mixing ratio. These findings showed that the mixing ratio has a confounding effect on the drought sensitivity of temperate tree species. Differences in hydrological niches allow Q. variabilis to benefit from mixing with P. tabuliformis. Mixing with optimal proportion of P. tabuliformis maximizes the drought resilience of Q. variabilis. Additionally, weakly competitive species (P. tabuliformis) do not benefit from mixed forests during prolonged water deficits. This result complements previous arguments that species mixing reduces the biological vulnerability of individuals. This study emphasizes the importance of species selection based on the biological and physiological characteristics of tree species in the afforestation of mixed forests. It highlights the critical role of species mixing ratios in the resistance of mixed forest ecosystems to climate change, which may provide a reference for sustainable forest management.