Palmer Drought Severity Index Research Articles

Response of radial growth of Pinus wallichiana to climate change in Mount Qomolangma, Tibet, China

Global warming would significantly impact tree growth in the Tibetan Plateau. However, the specific effects of climate change on the radial growth of Pinus wallichiana in Mount Qomolangma are still uncertain. To investigate the responses of radial growth of P. wallichiana to climate change, we analyzed tree-ring samples in Mount Qomolangma. We removed the age-related growth trends and established three chronologies by using the modified negative exponential curve, basal area index, and regional curve standardization, and conducted Pearson correlation and moving correlation analyses to examine the association between radial growth of P. wallichiana and climatic factors. The results showed that this region had experienced a significant upward trend in temperature and that the Palmer drought severity index (PDSI) indicated a decreasing trend since 1980s, while the relative humi-dity changed from a significant upward to a downward trend around 2004, implying the climate shifted toward warmer and drier. Results of Pearson correlation analysis indicated a significant and positive relationship between the radial growth of P. wallichiana and the minimum temperature of April-June and July-September, and precipitation of January-April in the current year. The radial growth of P. wallichiana was significantly and negatively associated with the relative humidity of June, July, and August in the current year. As temperature rose after 1983, the relationship between radial growth of P. wallichiana and the minimum temperature in July and September of the current year increased from a non-significant association to a significant and positive association, while the relationship between radial growth of P. wallichiana and relative humidity in August and precipitation in September of the current year changed from non-significant correlation to a significant and negative correlation. Results of the moving correlation analysis suggested that the radial growth of P. wallichiana showed a significant and stable correlation with the July-September minimum temperature of the current year. Under the background of climate warming, the rapid increases of temperature would accelerate the radial growth of P. wallichiana in Mount Qomolangma.

Exploring the impact of the recent global warming on extreme weather events in Central Asia using the counterfactual climate data ATTRICI v1.1

We study the impact of recent global warming on extreme climatic events in Central Asia (CA) for 1901-2019 by comparing the composite representation of the observational climate with a hypothetical counterfactual one that does not include the long-term global warming trend. The counterfactual climate data are produced based on a simple detrending approach, using the global mean temperature (GMT) as the independent variable and removing the long-term trends from the climate variables of the observational data. This trend elimination is independent of causality, and the day-to-day variability in the counterfactual climate remains preserved. The analysis done in the paper shows that the increase in frequency and magnitude of extreme temperature and precipitation events can be attributed to global warming. Specifically, the probability of experiencing a +7 K temperature anomaly event in CA increases by up to a factor of seven in some areas due to global warming. The analysis reveals a significant increase in heatwave occurrences in Central Asia, with the observational climate dataset GSWP3-W5E5 (later called also factual) showing more frequent and prolonged extreme heat events than hypothetical scenarios without global warming. This trend, evident in the disparity between factual and counterfactual data, underscores the critical impact of recent climatic changes on weather patterns, highlighting the urgent need for robust adaptation and mitigation strategies. Additionally, using the self-calibrated Palmer drought severity index (scPDSI), the sensitivity of dry and wet events to the coupled precipitation and temperature changes is analyzed. The areas under dry and wet conditions are enhanced under the observational climate compared to a counterfactual scenario, especially over the largest deserts in CA. The expansion of the dry regions aligns well with the pattern of desert development observed in CA in recent decades.

Effects of weather and climate on fluctuations of grain prices in southwestern Bohemia, 1725–1824 CE

Abstract. Grain prices in early modern Europe reflected the effects of weather and climate on crop yields and a complex array of societal and socio-economic factors. This study presents a newly developed series of grain prices for Sušice (southwestern Bohemia, Czech Republic) for the period 1725–1824 CE, based on various archival sources. It aims to analyse their relationships with weather and climate, represented by temperature, precipitation, and drought (self-calibrated Palmer Drought Severity Index, scPDSI) reconstructions, as well as particular weather extremes and anomalies reported in documentary evidence. Wheat, rye, barley, and oats series in Sušice showed high mutual correlations. The mean highest prices during the year typically occurred from May to July before the harvest, while prices usually declined afterwards. Wheat, rye, and barley prices were significantly negatively correlated with spring temperatures and positively correlated with scPDSI from winter to summer. This indicates that wetter winters, cooler and wetter springs, and wetter summers contributed to higher prices. The extremely high grain prices in the years 1746, 1771–1772, 1802–1806, and 1816–1817 were separately analysed with respect to weather and climate patterns and other socio-economic and political factors. The results obtained were discussed in relation to data uncertainty, factors influencing grain prices, and the broader European context.

Does snow storage affect the Palmer drought severity index? Revisiting PDSI drought indicator via conceptual model and large-scale information

Climate change and its impacts have significantly altered the hydro-climatological conditions worldwide. Accurate monitoring of drought is a crucial work for assessing water availability and environmental suitability. The Palmer Drought Severity Index (PDSI) is a key indicator used to measure hydrological drought. However, its application in mountainous and snow-covered regions is limited due to the indicator's inadequate representation of snow hydrology and its impact during spring and summer. In this research, the authors aimed to enhance the PDSI drought indicator by incorporating snow storage and snowmelt processes via conceptual approach and large-scale snow information. Four different scenarios were developed and tested in the Gheshlagh watershed, a mountainous basin in western Iran. To ensure a comprehensive analysis, the Standardized Precipitation Index (SPI) was also employed to evaluate the results. Additionally, an alternative water balance model, better suited for the watershed, was used in place of the Palmer two-soil-layer water balance model. While the simulated indicators showed good agreement with the benchmark PDSI model, the results revealed significant changes in drought indicators, particularly during summer and spring, when considering snow storage. Moreover, the impact of using a different water balance model was found to be more influential than incorporating snow storage in the PDSI framework. Based on the findings, the authors recommend revisiting the PDSI approach by incorporating region-specific water balance models and accounting for the effects of snow storage.

Tree-Ring Inferred Drought Variations in the Source Region of the Yangtze, Yellow, and Mekong Rivers over the Past Five Centuries

The climate in the source region of the Yangtze River, Yellow River, and Mekong River is of great research interest because of its sensitivity to global change and its importance in regulating water resources to densely populated and vast areas downstream. A five-century long record of spring (May–June) for the Palmer Drought Severity Index (PDSI) was reconstructed for this region using tree-ring width chronologies of Qilian juniper (Juniperus przewalskii Kom.) from five high-elevation sites. The reconstruction explained 46% variance in the PDSI during the instrumental period 1955–2005. The reconstructed PDSI showed that the occurrence of dry extremes became frequent during the last century relative to the previous four centuries. The standard deviation of the reconstructed PDSI in the 100-year window showed that the recent century held apparent high values of standard deviation in the long-term context. Sustained droughts occurred in periods 1582–1631, 1737–1757, 1772–1791, 1869–1891, 1916–1939, and 1952–1982, whereas relatively wet intervals were observed in 1505–1527, 1543–1564, 1712–1736, 1792–1816, 1852–1868, 1892–1915, and 1983–2008. Notably, in the context of the past five centuries, the study region showed an increased inter-annual variability in the recent century, suggesting an intensified hydroclimatic activity possibly associated with global warming. Moreover, through diagnostic analysis of atmospheric circulation, we found that the negative phase East Asian–Pacific teleconnection pattern may be likely to trigger drought in the study region.

Spatial Heterogeneity in the Response of Winter Wheat Yield to Meteorological Dryness/Wetness Variations in Henan Province, China

Knowledge of the responses of winter wheat yield to meteorological dryness/wetness variations is crucial for reducing yield losses in Henan province, China’s largest winter wheat production region, under the background of climate change. Data on climate, yield and atmospheric circulation indices were collected from 1987 to 2017, and monthly self-calibrating Palmer drought severity index (sc-PDSI) values were calculated during the winter wheat growing season. The main results were as follows: (1) Henan could be partitioned into four sub-regions, namely, western, central-western, central-northern and eastern regions, based on the evolution characteristics of the time series of winter wheat yield in 17 cities during the period of 1988–2017. Among them, winter wheat yield was high and stable in the central-northern and eastern regions, with a remarkable increasing trend (p < 0.05). (2) The sc-PDSI in February had significantly positive impacts on climate-driven winter wheat yield in the western and central-western regions (p < 0.05), while the sc-PDSI in December and the sc-PDSI in May had significantly negative impacts on climate-driven winter wheat yield in the central-northern and eastern regions, respectively (p < 0.05). (3) There were time-lag relationships between the sc-PDSI for a specific month and the atmospheric circulation indices in the four sub-regions. Furthermore, we constructed multifactorial models based on selected atmospheric circulation indices, and they had the ability to simulate the sc-PDSI for a specific month in the four sub-regions. These findings will provide scientific references for meteorological dryness/wetness monitoring and risk assessments of winter wheat production.

Drought Offsets the Controls on Colored Dissolved Organic Matter in Lakes

The concentration of colored dissolved organic matter (CDOM) in lakes is strongly influenced by climate, land cover, and topographic settings, but it is not known how drought may affect the relative importance of these controls. Here, we evaluate the controls of CDOM during two summers with strongly contrasting values of the Palmer drought index (PDI), indicating wet vs. dry conditions. We hypothesized that lake CDOM during a wet summer season is regulated mainly by the surrounding land cover to which the lakes are hydrologically connected, while, during drought, the lakes are disconnected from the catchment and CDOM is regulated by climatic and morphometric factors that govern the internal turnover of CDOM in the lakes. A suite of climate, land cover, and morphometric variables was assembled and used to explain remotely sensed CDOM values for 255 boreal lakes distributed across broad environmental and geographic gradients in Sweden and Norway. We found that PDI explained the variability in CDOM among lakes in a dry year, but not in a wet year, and that severe drought strongly decreased CDOM during the dry year. Large lakes, especially, with a presumed high degree of catchment uncoupling, showed low CDOM during the dry year. However, in disagreement with our hypothesis, climate, land cover, and morphometry all showed a stronger impact on lake CDOM in wet vs. dry years. Thus, drought systematically weakened the predictability of CDOM variations at the same time as CDOM was offset toward lower values. Our results show that drought not only has a direct effect on CDOM, but also acts indirectly by changing the spatial regulation of CDOM in boreal lakes.

Advanced stacked integration method for forecasting long-term drought severity: CNN with machine learning models

Study regionEight governorates in upper Egypt namely Aswan, Asyut, Beni-Suef, Fayoum, Luxor, Minya, Qena and Sohag. Study focusThis study aims to develop novel hybrid machine learning (ML) models for forecasting the drought phenomena based on limited inputs for the eight Egyptian govern-orates, and ii) evaluate the performance and accuracy of the developed ML models for predicting Palmer Drought Severity Index (PDSI) to recommend the optimal model based on performance statistical metrics. The hybrid ML models were Convolution Neural Networks (CNN)-Long Short-Term Memory (LSTM), CNN-Random Forest (RF), CNN-Support Vector Machine (SVR), and CNN-Extreme Gradient Boosting (XGB). New hydrological insights for the regionResults showed that CNN-LSTM model outperformed the others followed by CNN-RF. Values of NSE, MAE, MARE, IA, R2, and RMSE for CNN-LSTM were 0.885, 0.915, − 2.073, 0.967, 0.885, and 0.573, respectively. For the testing stage CNN-SVR model was found to perform the best; average values of NSE, MAE, MARE, IA, R2, and RMSE were 0.828, 0.364, − 2.903, 0.950, 0.828 and 0.688, respectively. This study provided a way forward for convenient estimation of the PDSI Index from the meteorological data in terms of advancing deep learning algorithms. The developed hybrid models, more or less, can satisfactory predict PDSI values. Additionally, the study suggests the CNN-LSTM model as the most suitable model to advance future investigation in the study area.

Wetting or greening? Probing the global trends in Vegetation Condition Index (VCI)

Vegetation Condition Index (VCI), as a widely used drought index for monitoring vegetation drought stress and estimating drought trends, is constructed by normalizing the long-term satellite-based Normalized Difference Vegetation Index (NDVI) data. However, under global greening, vegetation across different regions has shown an increasing trend in greenness, which may cause VCI to inherit the greening trend in NDVI and further hamper its ability in drought trend analysis. Therefore, this study quantitatively explored the underlying relationship among VCI, global greening, and drought from 2001 to 2021 to examine the utility of VCI in a changing environment. Multi-source indicators were employed as surrogates for vegetation greenness and drought, respectively. Particularly, the Leaf Area Index (LAI) and Net Primary Production (NPP) were used as proxies for vegetation greenness while the Root-Zone Soil Moisture (RZSM), Palmer Drought Severity Index (PDSI), and Standardized Precipitation-Evapotranspiration Index (SPEI) were used for drought indices. Based on Sen’s slope estimator, Mann-Kendall (MK) test, and partial correlation analysis, our results show that the proportion of pixels with an increasing trend in VCI is approximately 38.5%, which is similar to the greenness-related indices (i.e., NPP [26.47%] and LAI [59.14%]), and is significantly higher than the other drought indices (i.e., RZSM [19.83%], PDSI [10.38%], and SPEI [9.32%]). Furthermore, our results demonstrate that the VCI, as a drought index, exhibits a closer correlation with greenness-related indicators (LAI and NPP) than other drought indices (RZSM, PDSI, and SPEI). These results reveal the potential limitations in the practical applications of VCI and could enhance our understanding of vegetation dynamics and drought trends, especially in the current greening globe. Additionally, this study serves as a cautionary note for the scientific community involved in drought monitoring, emphasizing that the VCI may not be a suitable tool for evaluating long-term trends in drought impacts on vegetation.

Dryland hydroclimatic response to large tropical volcanic eruptions during the last millennium

Drylands are highly vulnerable to climate change due to their fragile ecosystems and limited ability to adapt. In contrast to the global drying after tropical volcanic eruptions shown previously, we demonstrate that large tropical volcanic eruptions can induce significant two-year hydroclimatic wetting over drylands by employing the last millennium simulations. During this wetting period, which extends from the first to the third boreal winter after the eruption, several hydroclimatic indicators, such as self-calibrating Palmer Drought Severity Index based on the Penman-Monteith equation for potential evapotranspiration (scPDSIpm), standard precipitation evapotranspiration index (SPEI), aridity index (AI), top-10cm soil moisture (SM10cm), and leaf area index (LAI), show significant positive anomalies over most drylands. The primary contribution to the wetting response is the potential evapotranspiration (PET) reduction resulting from dryland surface cooling and reduced solar radiation, as well as a weak contribution from increased precipitation. The latter is due to the wind convergence into drylands caused by slower tropical cooling compared to drylands. The wetting response of drylands to volcanic eruptions also demonstrates some benefits over the global hydrological slowdown resulting from stratospheric aerosol injection, which replicates the cooling effects of volcanic eruptions to address global warming.

Drought stress and its characteristics in China from 2001 to 2020 considering vegetation response and drought creep effect

Study areaChina Study focusDrought is an extremely serious disaster, typically characterized by slow onset, long duration, and cumulative impacts on multifaceted aspects. Developing a combined index that integrates its various characteristics can help deepen our understanding of drought evolution and provide accurate references for farmers to take drought mitigation measures. In this study, we proposed a Modified version of the Type Response-Aided Drought Index (MTRADI), simultaneously considering the various responses of different vegetation and the slow-varying properties of drought development. New hydrological insights for the regionsThe suitability of MTRADI was evaluated through correlation analysis with Palmer Drought Severity Index (PDSI) and qualitative comparison with Meteorological Drought Composite Index (MCI) maps. The MTRADI achieved significantly higher correlation coefficients with the PDSI, outperforming other combined drought indices. Based on the run theory, Mann-Kendall (MK) test, and Sen’s slope, drought characteristics and trends in mainland China during 2001–2020 were analyzed and the results show that drought frequency and severity are relatively higher in eastern Inner Mongolia, North China Plain, and Northeast of China. Furthermore, areas with significant wetting trends are observed to be mainly distributed near the Hu line, indicating that the water conditions in China are gradually improving at the transition zone of arid and humid climate regions.

Impact of plant diversity and management intensity on magnitude and stability of productivity in North American grazing lands

AbstractQuestionsGrasslands provide important provisioning services worldwide and their management has consequences for these services. Management intensification is a widespread land‐use change and has accelerated across North America to meet rising demands on productivity, yet its impact on the relationship between plant diversity and productivity is still unclear. Here, we investigated the relationship between plant diversity and grassland productivity across nine ecoclimatic domains of the continental United States. We also tested the effect of management intensification on diversity and productivity in four case studies.MethodsWe acquired remotely sensed gross primary productivity data (GPP, 1986–2018) and plant diversity data measured at different spatial scales (1, 10, 100, 400 m2), as well as climate variables including the Palmer drought index from two ecological networks. We used general linear mixed models to relate GPP to plant diversity across sites. For the case study analysis, we used linear mixed models to relate plant diversity to management intensity, and tested if the management intensity influenced the relationship between GPP (mean and temporal variation) and drought.ResultsAcross all sites, we observed positive relationships among species richness, productivity, and the temporal stability of mean annual biomass production. These relationships were not affected by the scale at which species richness was observed. In three out of the four case studies, we observed that management effects on species richness were only significant at broader scales (i.e., ≥10 m2) with no clear effect found at the commonly used 1‐m2 quadrat scale. In one case study, species‐poor, intensively managed pastures presented the highest productivity but were more sensitive to dry conditions than less intensified pastures. However, in other case studies, we did not observe significant effects of management intensity on the magnitude or stability of productivity.ConclusionsGeneralization across studies may be difficult and require the development of intensification indices general enough to be applied across diverse management strategies in grazilands. Understanding how management intensification affects grassland productivity will inform the development of sustainable intensification strategies.

Radial growth response of Pinus Yunnanensis to climate in high mountain forests of northwestern Yunnan, southwestern China

Understanding the relationship between tree growth and environmental conditions is essential to elucidating the impact of global climate change on forest ecosystems. We used the dendrochronology method to examine the growth sensitivity of a typical conifer to climate change in mountain forests of Central Hengduan Mountain. The study involved the establishment of tree ring width chronologies of Pinus yunnanensis in both Haba Snow Mountain (HB) and Yulong Snow Mountain (YL) in northwestern Yunnan, enabling the detection of the relationship between its radial growth and climates, i.e., monthly total precipitation, monthly temperatures (average minimum, mean and maximum) and monthly Palmer Drought Severity Index (PDSI). Response function and redundancy analysis (RDA) were used to identify correlations between climate variables and radial growth, and moving interval analysis was applied to determine the stability of climate-growth relationship. The findings demonstrated that the growth of P. yunnanensis had similar response patterns to climate change at two sites, exhibiting growth synchronization and common signals. Specifically, the radial growth of P. yunnanensis was negatively correlated with May temperature, while temperature in current October significantly promoted radial growth. Precipitation in June was the common climate variable with inverse effects between two sites, with positive impacts on YL and negative impacts on HB. The results of moving interval analysis were consistent with response function and RDA, presenting significant correlations in many years for those climatic variables significantly affecting tree growth. Stability analysis also revealed that the climate-growth relationship could fluctuate over a small range of time scales, induced by an abrupt change in climate. A forecast of strengthen in growth of P. yunnanensis forests was expected, since increases in precipitation and temperature of most months would benefit tree growth, and negative impacts of May temperature would be offset by the increase of precipitation in the corresponding month. These results could provide a basis for developing sustainable strategies of forest management under the climate change.

Responses of phenology to preseason drought and soil temperature for different land cover types on the Mongolian Plateau

Drought and heat caused major disturbance in nature by interfering with plant phenology, and can also alter the vulnerability and resilience of terrestrial ecosystems. Existing research on the Mongolian Plateau has primarily focused on studying the response of the start (SOS) and end (EOS) of the growing season to drought and heat variations. However, there is still a lack of comprehensive understanding regarding the coupled effects of drought and heat on phenology across different land cover types. In this study, we retrieved SOS and EOS based on 34-year (1982–2015) normalized difference vegetation index (NDVI) dataset from Global Inventory Modeling and Mapping Studies (GIMMS). Results showed that grasslands and the Gobi-Desert show rapid advancement in SOS, and forests presented the slowest advancement in SOS, but SOS in croplands were delayed. EOS across four land cover types advanced, with the Gobi-Desert showed the highest rate of advancement and forests the lowest. Using the Palmer Drought Severity Index (PDSI) and soil temperature as the indicators of drought and thermal conditions, the responses of SOS and EOS to these two climate variables were evaluated. The advanced SOS driven by lower drought severity was detected in forests, grasslands, croplands and the Gobi-Desert. The dominant response of EOS to drought severity was positive in croplands, grasslands and forests, except for the Gobi-Desert, where drought severity had negative effects on EOS. Compared with the daily average soil temperature (STmean), the daily maximum soil temperature (STmax, daytime), and the daily minimum soil temperature (STmin, nighttime), the daily diurnal soil temperature range (DSTR, where DSTR = STmax − STmin) between night and day were the most suitable indicators for assessing the response of SOS and EOS to soil temperature. Strong negative correlation between SOS and the preseason DSTR was pronounced in all land cover types on the Mongolian Plateau. However, EOS was negatively correlated with the preseason DSTR only in the Gobi-Desert. Last but not least, normalized sensitivity assessments reveal that the negative impacts of DSTR on SOS and EOS were the main controlling factors on the Mongolian Plateau phenology, followed by the couple negative effects of drought severity and DSTR.

A comparative study of various drought indices at different timescales and over different record lengths in the arid area of northwest China.

Although many drought indices have been developed to monitor drought conditions, their applicability differs across climatic regions, which results in different characteristics of drought index assessments at different timescales and over different record lengths. Therefore, the applicability of precipitation-based and precipitation-evapotranspiration/temperature-based drought indices was examined in this study using the Generalized Extreme Value Index (GEVI), Homogeneity Index (HI) of precipitation and temperature, K index (K), precipitation anomaly percentage (Pa), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI), and China-Z Index (CZI) over different record lengths and at a timescale range of 1-24months. In addition, the results that were obtained using these indices were compared with the Self-Calibrating Palmer Drought Severity Index (scPDSI). The stability, accuracy, and consistency of the different drought indices were evaluated using precipitation and evapotranspiration/temperature data (1-24months) collected from different climatic regions in the arid area of northwest China in the 1961-2017 period. The results indicated that the Pa, CZI, K, and SPEI were more stable; the SPI, SPEI, and HI were more accurate; and the GEVI, SPI, HI, and SPEI were more consistent with the scPDSI. In addition, the results indicated that it is more appropriate to select a long record length (> 35 years) to monitor drought when sufficient data are available. However, defining constant drought classes may not be appropriate for all drought timescales. In fact, precipitation and evapotranspiration data from different timescales had different optimal distribution functions. The drought indices also demonstrated that they were applicable to a temperate arid area in the study region. In addition, the HI and SPEI better captured the precipitation and evapotranspiration/temperature characteristics, while the CZI, K, and Pa overestimated or underestimated the frequency of different drought classes at different timescales to some extent in the study region. The results of this study suggest that greater priority should be given to the precipitation-evapotranspiration-based indices. In addition, it is suggested to change the drought index class thresholds in future related studies on drought event recognition at different timescales to ensure more accurate drought monitoring.

Multiscale Spatiotemporal Dynamics of Drought within the Yellow River Basin (YRB): An Examination of Regional Variability and Trends

Drought, as a recurring extreme climatic event, inflicts diverse impacts on ecological systems, agricultural productivity, water resources, and socio-economic progress globally. Discerning the drought patterns within the evolving environmental landscape of the Yellow River Basin (YRB) is imperative for enhancing regional drought management and fostering ecological conservation alongside high-quality development. This study utilizes meteorological drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the self-calibrating Palmer Drought Severity Index (scPDSI), for a detailed spatiotemporal analysis of drought conditions. It examines the effectiveness of these indices in the basin’s drought monitoring, offering a comprehensive insight into the area’s drought spatiotemporal dynamics. The findings demonstrate the following: (1) SPEI values exhibit distinct fluctuation patterns at varying temporal scales, with more pronounced fluctuations at shorter scales. Drought years identified via the 12-month SPEI time scale include 1965, 1966, 1969, 1972, 1986, 1997, 1999, 2001, and 2006. (2) A modified Mann–Kendall (MMK) trend test analysis of the scPDSI time series reveals a worrying trend of intensifying drought conditions within the basin. (3) Correlation analysis between SPEI and scPDSI across different time scales yields correlation coefficients of 0.35, 0.54, 0.69, 0.76, and 0.62, highlighting the most substantial correlation at an annual scale. Spatial correlation analysis conducted between SPEI and scPDSI across various scales reveals that, within diverse temporal ranges, the correlation peaks at a 12-month time scale, with subsequent prominence observed at 6 and 24 months. This observed pattern accentuates the applicability of scPDSI in the monitoring of medium- to long-term drought phenomena.

Growth-climate relationships of four tree species in the subtropical evergreen broad-leaved forests in Southwest China

Subtropical forests are an important carbon sink, yet our understanding on tree growth response to inter-annual climate variability remains limited. This study investigated the growth-climate relationships of four evergreen broad-leaved tree species (Stewartia pteropetiolata W. C. Cheng, Schima noronhae Reinw. ex Bl. Bijdr, Machilus gamblei King ex J. D. Hooker, and Machilus yunnanensis Lec) in the subtropical evergreen broad-leaved forests (EBFs) in the Ailao Mountains of Yunnan province, southwest China. We constructed tree ring-width residual chronologies for each species and correlated them with daily and monthly climate data. Ring-width chronologies of S. pteropetiolata and S. noronhae were positively correlated with precipitation, relative humidity, and self-calibrated Palmer drought index (scPDSI) during autumn of the previous year and spring-to-early summer of the current year, indicating that these two Theaceae species were sensitive to moisture availability. Tree radial growth of two Machilus species was primarily limited by excessive precipitation and dense cloud cover during the rainy season in this middle montane cloud forest. Moving correlations between climate variables and radial growth of all species were temporally unstable, with a weakening response to climate variability in recent decades. We highlight the dendroclimatic potential of evergreen broad-leaved tree species in moist subtropical forests. The findings offer a pertinent perspective, emphasizing the necessity of separately considering distinct ecological indicators for trees in order to obtain a comprehensive understanding of climate-growth responses within highly diverse subtropical forests.

Climate change has driven multidecadal declines in lake levels in central Alberta, Canada

Timoney, KP. 2024. Climate change has driven multidecadal declines in lake levels in central Alberta, Canada. Lake Reserv Manage. 40:205–220. This study examined water level data from 5 lakes in central Alberta to determine the timing and rates of change and to identify the causes for those changes. Over the past century, the estimated average levels of Beaverhill and Cooking lakes declined ∼3 m. Highest lake levels were observed ca. 1902–1904. Lake levels varied widely over the decades, punctuated by periods of high or low water conditions embedded within the longer term declines. Over the past 50 yr, average rates of lake drawdown were as follows: Miquelon −6.8 cm/yr, Cooking −4.4 cm/yr, Beaverhill −4.4 cm/yr, Hastings −0.9 cm/yr, and Ministik −0.7 cm/yr. Over time, annual temperature, evaporation, and net evaporation increased while annual precipitation, runoff, and Palmer Drought Severity Index (PDSI) decreased. Annual precipitation was significantly correlated with the levels of all 5 lakes, and with annual runoff and PDSI. Net evaporation was significantly correlated with temperature, runoff, PDSI, and the levels of all lakes but Ministik. Annual runoff was significantly correlated with the levels of all 5 lakes and PDSI. Conversely, neither annual temperature nor evaporation was correlated significantly with the annual lake levels. Annual levels of all 5 lakes were significantly correlated with each other. The lake level declines are part of a larger pattern of declining levels observed in other lakes in western North America over many decades. In central Alberta, data from several sources indicate accelerated rates of drawdown since the late 1970s to early 1980s at some lakes and accelerated declines since the mid to late 1990s at other lakes.

Radial growth responses of Larix gmelinii to drought events in dry and wet areas of northern temperate forests

Drought stress caused by global climate warming affects tree growth in both dry and wet areas. However, the differences in tree growth responses to drought in dry and wet areas are poorly understood. Here, we collected 93 tree cores to analyze the differences in the radial growth responses of larch (Larix gmelinii) under climate change and tree growth resilience under drought events in the Altai Mountains (dry area) and Changbai Mountains (wet area). The results showed that larch growth in the Altai Mountains was significantly positively correlated with the self-calibrating Palmer Drought Severity Index (sc-PDSI) in all months and precipitation in the previous growth season and May, whereas it was significantly (p < 0.05) negatively correlated with temperature in May and the previous June to August. In the Changbai Mountains, larch growth was significantly positively correlated with May maximum and mean temperature, and significantly positively and negatively correlated with precipitation in April and May，respectively (p < 0.05). The mean resistance (recovery) of larch growth to drought in wet areas were significantly stronger (weaker) than that in dry areas (p < 0.05). Moreover, strengthening the drought frequency led to a significant (p < 0.05) decline in larch resistance in dry areas. Therefore, warming-induced increases in drought stress will aggravate negative impacts on the radial growth of larch forests in temperate dry areas but not in wet areas in the future.

A novel index for vegetation drought assessment based on plant water metabolism and balance under vegetation restoration on the Loess Plateau

Vegetation is vital to the ecosystem, contributing to the global carbon balance, but susceptible to the impacts of climate change. Monitoring vegetation drought remains challenging due to the lack of widely accepted drought indices. This study focused on vegetation, and simulated the vegetation suitable water demand and soil available water supply (calculated by Remote-sensing-based Water Balance Assessment Tool model). The standardized Vegetation Water deficit Index (SVWDI) was established by calculating the vegetation water deficit, which reflects the response of vegetation to drought. We examined the spatiotemporal evolution of vegetation drought on the Loess Plateau and evaluated the applicability of standardized vegetation water deficit index. Our findings revealed that the standardized vegetation water deficit index demonstrated an overall upward trend across different time scales from 1991 to 2020. Drought conditions were concentrated in the first 20 years of the study period, but vegetation drought on the Loess Plateau has been alleviated in the past decade. Moreover, as the time scale extended, the trend of SVWDI generally decreased, with approximately 49.50 % (1-month scale), 46.66 % (3-month scale), 47.08 % (12-month scale), and 32.16 % (24-month scale) of the grid areas experiencing increased SVWDI. The correlation between SVWDI and tree-ring width index (TRWI) performed well under all precipitation gradients, but the Palmer drought severity index (PDSI) was only highly correlated with TRWI in regions with low precipitation. In terms of the relationship with vegetation health, SVWDI demonstrated the highest correlation with the normalized difference vegetation index (NDVI) across different time scales, followed by PDSI and standardized precipitation evapotranspiration index (SPEI). This study provides insights into the evolution of vegetation drought in response to climate change. The findings can guide initiatives such as returning farmland to forest and grassland on the Loess Plateau to aid climate change adaptation strategies.