Impacts of preseason drought on vegetation spring phenology across the Northeast China Transect

Enhanced autumn phenology model incorporating agricultural drought

The impacts of various drought types on autumn phenology have yet to be extensively explored. We address the influence of pre-season agricultural and meteorological droughts on autumn phenology in the Northern Hemisphere. To this end, enhanced autumn phenology models incorporating drought factors was developed, contributing to a deeper understanding of these complex interactions. The study reveals that there was no significant trend of advancement or delay in the End of Season (EOS) across the Northern Hemisphere based on SIF estimates from 2001 to 2020. The cumulative and delayed impacts of pre-season agricultural drought on EOS were found to be more pronounced than those associated with meteorological drought. The analysis of various evaluation indexes shows that the performance of the Cooling Degree Days (CDD) model incorporating the Standardized Soil Moisture Drought Index (CDDSSMI) in simulating EOS in the Northern Hemisphere is >14 % higher than that of the standard CDD model. Additionally, the performance of the CDD model with the Standardized Precipitation Index (CDDSPI) in simulating EOS in the Northern Hemisphere is improved by >5.6 % compared to the standard CDD model. A comparison of future EOS projections across various models reveals that the CDD model significantly overestimates EOS in different scenarios (SSP245 and SSP585). The CDDSSMI model projects EOS approximately 7 days earlier than the CDD model, and the CDDSPI model projects EOS approximately 5 days earlier than the CDD model. This study highlights the diverse impacts of drought types on plant autumn phenology and underscores the significance of parameterizing drought impacts in autumn phenology models.

The impact of compound drought and heatwave events from 1982 to 2022 on the phenology of Central Asian grasslands

In the context of global warming, the occurrence and severity of extreme events like atmospheric drought (AD) and warm spell duration index (WSDI) have increased, causing significant impacts on terrestrial ecosystems in Central Asia's arid regions. Previous research has focused on single extreme events such as AD and WSDI, but the effect of compound hot and dry events (CHWE) on grassland phenology in the arid regions of Central Asia remains unclear. This study utilized structural equation modeling (SEM) and the Pettitt breakpoint test to quantify the direct and indirect responses of grassland phenology (start of season - SOS, length of season - LOS, and end of season - EOS) to AD, WSDI, and CHWE. Furthermore, this research investigated the threshold of grassland phenology response to compound hot and dry events. The research findings indicate a significant increasing trend in AD, WSDI, and CHWE in the arid regions of Central Asia from 1982 to 2022 (0.51 day/year, P < 0.01; 0.25 day/year, P < 0.01; 0.26 day/year, P < 0.01). SOS in the arid regions of Central Asia showed a significant advancement trend, while EOS exhibited a significant advance. LOS demonstrated an increasing trend (-0.23 day/year, P < 0.01; -0.12 day/year, P < 0.01; 0.56 day/year). The temperature primarily governs the variation in SOS. While higher temperatures promote an earlier SOS, they also offset the delaying effect of CHWE on SOS. AD, temperature, and CHWE have negative impacts on EOS, whereas WSDI has a positive effect on EOS. AD exhibits the strongest negative effect on EOS, with an increase in AD leading to an earlier EOS. Temperature and WSDI are positively correlated with LOS, indicating that higher temperatures and increased WSDI contribute to a longer LOS. The threshold values for the response of SOS, EOS, and LOS to CHWE are 16.14, 18.49, and 16.61 days, respectively. When CHWE exceeds these critical thresholds, there are significant changes in the response of SOS, EOS, and LOS to CHWE. These findings deepen our understanding of the mechanisms by which extreme climate events influence grassland phenology dynamics in Central Asia. They can contribute to better protection and management of grassland ecosystems and help in addressing the impacts of global warming and climate change in practice.

Magnitude and direction of green-up date in response to drought depend on background climate over Mongolian grassland

Increasing drought is one major consequence of ongoing global climate change and is expected to cause significant changes in vegetation phenology, especially for naturally vulnerable ecosystems such as grassland. However, the linkage between the response characteristic of green-up date (GUD) to drought and background climate remains largely unknown. Here, we focused on how the GUD of Mongolian grassland responds to extreme drought events (EDE). We first extracted the GUD from the MODIS Enhanced Vegetation Index data during 2001-2020 and identified the preseason EDE using the standardized precipitation evapotranspiration index data. Subsequently, we quantified the response of GUD to preseason EDE (DGUD) in each pixel as the difference in GUD between drought and normal years. The effect of 12 factors on DGUD was analyzed using the random forest algorithm. The results showed that the GUD under EDE may delay or advance by > 20 days compared to normal years. For the regions with mean annual temperature > -2 °C, the GUD was delayed under EDE due to the dominant role of water restriction on GUD, while the GUD was advanced under EDE in colder areas due to the warmer temperature during drought. However, the magnitude of delay in GUD under drought was greater in regions with less precipitation and more severe droughts. Our results could help to develop appropriate management strategies to mitigate the impacts of drought on grasslands.

Climate extremes drive the phenology of a dominant species in meadow steppe under gradual warming

Plant phenology in terrestrial ecosystems, especially in the Northern Hemisphere, is expected to change owing to the projected increasing frequency and intensity of climate extremes in the context of global warming. Although such changes under mean climate change have been extensively reported in the literature, little is known about the impacts of climate extremes. In this study, climatic changes and their effects on plant phenology were characterized using long-term climatic and phenological data from the start and end of the growing season (SOS and EOS, respectively) from 2005 to 2020 for Stipa baicalensis, a dominant species in a temperate meadow steppe. The results showed that the temperature, including the mean and minimum temperatures, and extreme warm indices significantly increased; however, annual precipitation, and the frequency of extreme cold and precipitation events decreased. The SOS of S. baicalensis was initially earlier and later, whereas the EOS trended to be delayed. However, the growing season (LOS) was slightly prolonged. Compared with the indices under mean temperature, the pre-season (before SOS or EOS) minimum temperature dominantly affected SOS and EOS, whereas the mean and extreme precipitation slightly affected them. Furthermore, the findings showed that plant phenology responded to extreme temperatures quicker and stronger than mean temperatures. This study provides insight into how key extreme climatic factors could affect plant phenophases and improve and refine the phenological model. This could also be useful in enhancing grassland ecosystem management and sustainable development.

Drought impacts on hydrology and water quality under climate change

The Intergovernmental Panel on Climate Change (IPCC) has predicted that droughts are projected to affect global hydrology and water quality in varying ways, resulting in a considerable challenge to water availability for society, environment, and ecosystems. This study employed the Soil and Water Assessment Tool to evaluate how drought affects hydrology and water quality in the Miyun Reservoir watershed, coupled with bias-corrected climate projections in the Representative Concentration Pathway 8.5 scenario, accommodating the intercoupling effects of precipitation shifts and rising temperatures. The standardized precipitation index (SPI), standardized runoff index (SRI), and standardized soil moisture index (SSWI) were used to characterize meteorological, hydrological, and agricultural droughts that occur in the different phases in the hydrological cycle. Climate change had the most significant impact on agricultural drought. SSWI were projected to considerably increase in intensity, frequency, and duration in most subbasins by up to 15 %, 55 %, and 45 %, respectively, and showed a strong correlation with meteorological and hydrological droughts (correlation coefficients r = 0.54, 0.57, and 0.60 with SPI for the baseline, near future and far future periods, and 0.91, 0.87, and 0.89 with SRI for the three periods, respectively). Hydrological components, sediment export, and nutrient loss were highly correlated with changes in drought indexes, with r ranging between -0.68 and 0.34 in the near future period and -0.62 and 0.53 in the far future period. Drought conditions of surface runoff and soil water dominated the changes in sediment export, and hydrological drought was the major cause for reduced nutrient loads. In addition to drought impacts, the synergistic effects of increasing precipitation and rising temperature led to a certain degree of increase in sediment and nutrient exports. The results of this study emphasize the need to enhance the resilience of watershed systems to the predicted increases in the intensity, frequency, and duration of droughts.

Impacts of climate change on vegetation phenology over the Great Lakes Region of Central Asia from 1982 to 2014

Dryland ecosystems in the Great Lakes Region of Central Asia (GLRCA) are highly sensitive to climate change due to the climate of spring precipitation. Although shifts in vegetation phenology have been widely attributed to rising temperature, the effects of solar radiation and drought on phenology remain largely unknown. Understanding the mechanisms of vegetation phenology response to climatic factors is essential for assessing the impact of climate change on dryland ecosystems. In this study, we investigated the spatial and temporal variations of vegetation phenology across the GLRCA using a long-term series of Normalized Difference Vegetation Index (NDVI), and then examined the response of vegetation phenology to climate change within different climate zones by combining with climate data (surface temperature, soil moisture, short-wave radiation, and standardized precipitation evapotranspiration index (SPEI)). The results suggested that the start of growing season (SGS) and the end of growing season (EGS) were significantly earlier regionally by -0.143 days/year and -0.363 days/year, respectively. Because of changes in SGS and EGS, length of growing season (LGS) across the GLRCA was shortened at a rate of -0.442 days/yr, which was mainly attributed to advanced EGS. Additionally, SGS of vegetation was negatively correlated with surface temperature but positively correlated with soil moisture and SPEI. These results indicated that surface temperature was a major determinant of advanced spring phenology, while increased soil moisture and mitigated drought would delay spring phenology. The response of autumn phenology to surface temperature and short-wave radiation varied across different climate zones. In arid climate zone, autumn phenology was obviously advanced with the increase of surface temperature and short-wave radiation. In cold climate zone, higher surface temperature and short-wave radiation postponed autumn phenology. Meanwhile, the thermal growing season did not accurately characterize the actual vegetation growing season because GLRCA phenology was different from most of Northern Hemisphere.

Preseason drought controls on patterns of spring phenology in grasslands of the Mongolian Plateau

Climate change has led to frequent drought events on the Mongolian Plateau; however, the pattern of preseason drought impacts on the start of the growing season (SOS) in grasslands is unclear. To determine how preseason drought controls the SOS in Mongolian Plateau grasslands, we quantitatively studied the sensitivity characteristics of the standardized precipitation evapotranspiration index-3 (SPEI-3) to the SOS and spatiotemporal differences based on meteorological and remote sensing datasets. The results show that: 1) in the past 34 years, the regions with a trend for earlier SOS in Mongolian Plateau grasslands were mainly distributed in the typical steppe region, accounting for 30% of the total area, while 13% of the pixels showed a delayed trend, mainly occurring in desert steppes, and the remaining 57% of the pixels did not show a significant change (P < 0.05); 2) preseason drought had an obvious inhibitory effect on grassland SOS, especially on typical steppes; 3) according to the SPEI-3, in the Mongolian Plateau grasslands, the SOS was advanced by 11 days when the SPEI-3 < 0.63, but the SOS was delayed by 3 days when the SPEI-3 > 0.63; and 4) the sensitivity of the SOS to preseason drought significantly decreased from 1982 to 2015 in Mongolian Plateau grasslands. Our results can be used to improve the interpretation of the SOS response to drought in the land surface model.

Interannual variability in summer climate change controls GPP long-term changes

Global environmental change is rapidly altering the dynamics of terrestrial vegetation, with implications for the functioning of the Earth system and the provision of ecosystem services. How vegetation responds to a changing environment is an important scientific issue, but there is a lack of coverage of the relative contributions that long-term variation and interannual variability in vegetation across seasons play in ecosystem response to global change. Here, we used four terrestrial ecosystem models provided by MsTMIP to examine four key environmental drivers of gross primary productivity (GPP) change over the period 1901-2010. Our findings showed that (1) for all seasons, interannual variability in climate change are the main environmental factor controlling seasonal GPP variability. (2) Summer is the key season controlling the variation of annual GPP, and its long-term trend and interannual variability can explain 61.50% of the variation of grassland GPP in China. (3) Interannual variability in summer climate change exceeded the CO₂ fertilization effect and nitrogen deposition as the controlling component (more than 40%) of long-term variation in Chinese grassland GPP. These studies highlight the important role of interannual variability in climate in reshaping the seasonality of vegetation growth, and will provide a precursor to future environmental drivers that can be precisely attributed to global vegetation change.

Drought and water-use efficiency are dominant environmental factors affecting greenness in the Yellow River Basin, China

Revegetation is accelerating globally because of its benefits in terms of ecosystem restoration, desertification prevention, and warming mitigation. The Yellow River Basin (YRB), as an ecological barrier in northern China, has implemented revegetation projects (such as the 'Grain for Green' program) for over two decades. However, a consensus on whether a significant change in greenness has been achieved and to what extent have environmental factors contributed to this change, as well as their importance ranking, is lacking. Leaf area index (LAI) is a critical indicator for estimating global greenness and projecting the dynamics of climate change. Herein, we apply four methods (Geodetector, random forest, multiple linear regression, and structural equation models) to explore the contribution of different environmental factors to greenness using the LAI in the YRB. We found that greenness has been increasing (greening over 67.22% (p < 0.05; 47.7%) of the YRB) with great spatial heterogeneity in the entire basin since 2000. Specifically, the greening process differed with elevation and slope. Temperature vegetation dryness index (TVDI) and water-use efficiency (WUE) dominated the greening; however, the three subregions evaluated revealed differing performance. In the upstream region, LAI increased by 0.031 y^-1. The primary positive factors of greening change were WUE and the annual highest value of daily minimum temperature; the negative factors were TVDI and the highest number of consecutive days when precipitation <1 mm. In the midstream region, LAI increased by 0.025 y^-1; greenness was mainly affected by the negative interaction of TVDI and the positive interaction of WUE. Annual maximum consecutive 5-day precipitation and annual count when daily minimum temperature < 0 °C had a great indirect impact on greenness, mainly through TVDI and WUE. In the downstream region, LAI increased by 0.045 y^-1, and the main driving factors were the annual lowest value of daily minimum temperature with a negative influence and the annual lowest value of daily maximum temperature with a positive influence. In addition, we found that the effect of the interaction of any two driving factors on greenness was greater than or equal to the single effect of a driving factor. This study concludes that drought and WUE are important predictors to evaluate the greenness in arid and semi-arid regions. We emphasise that the selection and assessment of greenness factors should follow a scientific and rigorous process rather than experience, and increased attention should be paid to the interaction of multiple factors. Furthermore, the perspective of system analysis will deepen our understanding of vegetation change in a vulnerable ecosystem.

Responses of Vegetation Autumn Phenology to Climatic Factors in Northern China

Understanding the dynamics of vegetation autumn phenology (i.e., the end of growing season, EOS) is crucial for evaluating impacts of climate change on vegetation growth. Nevertheless, responses of the EOS to climatic factors were unclear at the regional scale. In this study, northern China was chosen for our analysis, which is a typical ecologically fragile area. Using the Enhanced Vegetation Index (EVI) and climatic data from 1982 to 2016, we extracted the EOS and analyzed its trends in northern China by using the linear least-squares regression and the Bayesian change-point detection method. Furthermore, the partial correlation analysis and multivariate regression analysis were used to determine which climatic factor was more influential on EOS. The main findings were as follows: (1) multi-year average of EOS mainly varied between 275 and 305 day of year (DOY) and had complicated spatial differences for different vegetation types; (2) the percentage of the pixel showing delaying EOS (65.50%) was larger than that showing advancing EOS (34.50%), with a significant delaying trend of 0.21 days/year at the regional scale during the study period. As for different vegetation types, their EOS trends were similar in sign but different in magnitude; (3) temperature showed a dominant role in governing EOS trends from 1982 to 2016. The increase in minimum temperature led to the delayed EOS, whereas the increase in maximum temperature reversed the EOS trends. In addition to temperature, the impacts of precipitation and radiation on EOS trends were more complex and largely depended on the vegetation types. These findings can provide a crucial support for developing vegetation dynamics models in northern China.

Spatiotemporal Characteristics and Heterogeneity of Vegetation Phenology in the Yangtze River Delta

Vegetation phenology and its spatiotemporal driving factors are essential to reflect global climate change, the surface carbon cycle and regional ecology, and further quantitative studies on spatiotemporal heterogeneity and its two-way driving are needed. Based on MODIS phenology, meteorology, land cover and other data from 2001 to 2019, this paper analyzes the phenology change characteristics of the Yangtze River Delta from three dimensions: time, plane space and elevation. Then, the spatiotemporal heterogeneity of phenology and its driving factors are explored with random forest and geographic detector methods. The results show that (1) the advance of start of season (SOS) is insignificant—with 0.17 days per year; the end of season (EOS) shows a significant delay—0.48 days per year. The preseason temperature has a greater contribution to SOS, while preseason precipitation is main factor in determining EOS. (2) Spatial differences of the phenological index do not strictly obey the change rules of latitude at a provincial scale. The SOS of Jiangsu and Anhui is earlier than that of Zhejiang and Shanghai, and EOS shows an obvious double-clustering phenomenon. In addition, a divergent response of EOS with elevation grades is found; the most significant changes are observed at grades below 100 m. (3) Land cover (LC) type is a major factor of the spatial heterogeneity of phenology, and its change may also be one of the insignificant factors driving the interannual change of phenology. Furthermore, nighttime land surface temperature (NLST) has a relatively larger contribution to the spatial heterogeneity in non-core urban areas, but population density (PD) contributes little. These findings could provide a new perspective on phenology and its complex interactions between natural or anthropogenic factors.

Long-Term Vegetation Phenology Changes and Responses to Preseason Temperature and Precipitation in Northern China

Due to the complex coupling between phenology and climatic factors, the influence mechanism of climate, especially preseason temperature and preseason precipitation, on vegetation phenology is still unclear. In the present study, we explored the long-term trends of phenological parameters of different vegetation types in China north of 30°N from 1982 to 2014 and their comprehensive responses to preseason temperature and precipitation. Simultaneously, annual double-season phenological stages were considered. Results show that the satellite-based phenological data were corresponding with the ground-based phenological data. Our analyses confirmed that the preseason temperature has a strong controlling effect on vegetation phenology. The start date of the growing season (SOS) had a significant advanced trend for 13.5% of the study area, and the end date of the growing season (EOS) showed a significant delayed trend for 23.1% of the study area. The impact of preseason precipitation on EOS was overall stronger than that on SOS, and different vegetation types had different responses. Compared with other vegetation types, SOS and EOS of crops were greatly affected by human activities while the preseason precipitation had less impact. This study will help us to make a scientific decision to tackle global climate change and regulate ecological engineering.

Populus euphratica Phenology and Its Response to Climate Change in the Upper Tarim River Basin, NW China

Quantifying the phenological variations of Populus euphratica Olivier (P. euphratica) resulting from climate change is vital for desert ecosystems. There has previously been great progress in the influence of climate change on vegetation phenology, but knowledge of the variations in P. euphratica phenology is lacking in extremely arid areas. In this study, a modified method was proposed to explore P. euphratica phenology and its response to climate change using 18-year Global Land Surface Satellite (GLASS) leaf area index (LAI) time series data (2000–2017) in the upper Tarim River basin. The start of the growing season (SOS), length of the growing season (LOS), and end of the growing season (EOS) were obtained with the dynamic threshold method from the reconstructed growth time series curve by using the Savitzky–Golay filtering method. The grey relational analysis (GRA) method was utilized to analyze the influence between the phenology and the key climatic periods and factors. Importantly, we also revealed the positive and negative effects between interannual climate factors and P. euphratica phenology using the canonical correlation analysis (CCA) method, and the interaction between the SOS in spring and EOS in autumn. The results revealed that trends of P. euphratica phenology (i.e., SOS, EOS, and LOS) were not significant during the period from 2000–2017. The spring temperature and sunshine duration (SD) controlled the SOS, and the EOS was mainly affected by the temperature and SD from June–November, although the impacts of average relative humidity (RH) and precipitation (PR) on the SOS and EOS cannot be overlooked. Global warming may lead to SOS advance and EOS delay, and the increase in SD and PR may lead to earlier SOS and later EOS. Runoff was found to be a more key factor for controlling P. euphratica phenology than PR in this region.

Selenium Biofortification of Soybean Seeds Influences Physiological Responses of Seedlings to Osmotic Stress

Climate change poses a serious threat to agricultural production. Water deficit in agricultural soils is one of the consequences of climate change that has a negative impact on crop growth and yield. Selenium (Se) is known to be involved in plant defense against biotic and abiotic stress through metabolic, structural, and physiological activity in higher plants. The aim of this study was to investigate the physiological response of Se-biofortified soybean (Glycine max (L.) Merrill) seedlings under osmotic stress. For this research, we used biofortified soybean grain obtained after foliar Se biofortification in 2020. The experiment was conducted in a growth chamber with two cultivars (Lucija and Sonja) grown on filter paper in three replicates. The experiment was carried out with two watering treatments: distilled water (PEG-0) and 2.5% polyethylene glycol 6000 (PEG-2.5) on Se-biofortified seeds (Se) and nonbiofortified seeds (wSe). Contents of lipid peroxidation product (LP), free proline (PRO), total phenolic content (TP), ferric reducing antioxidant power (FRAP), and ascorbic acid (AA) were analyzed in 7-days-old seedlings. Significant differences were detected in the Se content of soybean grains between the two cultivars. A milder reaction to PEG-2.5 was observed in cultivar Lucija in both Se and wSe treatments, which might represent the mitigating effects of Se on osmotic stress in this cultivar. Contrarily, in cultivar Sonja, Se adversely affected all analyzed traits in the PEG-2.5 treatment. Ultimately, Se is a pro-oxidant in Sonja, whereas it represents an anti-oxidant in Lucija. In conclusion, different soybean cultivars show contrasting physiological reactions to both osmotic stress and Se. However, the activation of antioxidant pathways in Sonja can also be interpreted as added value in soybean seedlings as a functional food.

Multi-Year NDVI Values as Indicator of the Relationship between Spatiotemporal Vegetation Dynamics and Environmental Factors in the Qaidam Basin, China

The Qaidam Basin is a unique and complex ecosystem, wherein elevation gradients lead to high spatial heterogeneity in vegetation dynamics and responses to environmental factors. Based on the remote sensing data of Moderate Resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM) and Global Land Data Assimilation System (GLDAS), we analyzed the spatiotemporal variations of vegetation dynamics and responses to precipitation, accumulative temperature (AT) and soil moisture (SM) in the Qaidam Basin from 2001 to 2016. Moreover, the contribution of those factors to vegetation dynamics at different altitudes was analyzed via an artificial neural network (ANN) model. The results indicated that the Normalized Difference Vegetation Index (NDVI) values in the growing season showed an overall upward trend, with an increased rate of 0.001/year. The values of NDVI in low-altitude areas were higher than that in high-altitude areas, and the peak values of NDVI appeared along the elevation gradient at 4400–4600 m. Thanks to the use of ANN, we were able to detect the relative contribution of various environmental factors; the relative contribution rate of AT to the NDVI dynamic was the most significant (35.17%) in the low-elevation region (<2900 m). In the mid-elevation area (2900–3900 m), precipitation contributed 44.76% of the NDVI dynamics. When the altitude was higher than 3900 m, the relative contribution rates of AT (39.50%) and SM (38.53%) had no significant difference but were significantly higher than that of precipitation (21.97%). The results highlight that the different environmental factors have various contributions to vegetation dynamics at different altitudes, which has important theoretical and practical significance for regulating ecological processes.

Spatio-Temporal Evolution, Future Trend and Phenology Regularity of Net Primary Productivity of Forests in Northeast China

Net Primary Productivity (NPP) is one of the significant indicators to measure environmental changes; thus, the relevant study of NPP in Northeast China, Asia, is essential to climate changes and ecological sustainable development. Based on the Global Production Efficiency (GLO-PEM) model, this study firstly estimated the NPP in Northeast China, from 2001 to 2019, and then analyzed its spatio-temporal evolution, future changing trend and phenology regularity. Over the years, the NPP of different forests type in Northeast China showed a gradual increasing trend. Compared with other different time stages, the high-value NPP (700–1300 gC·m−2·a−1) in Changbai Mountain, from 2017 to 2019, is more widely distributed. For instance, the NPP has an increasing rate of 6.92% compared to the stage of 2011–2015. Additionally, there was a significant advance at the start of the vegetation growth season (SOS), and a lag at the end of the vegetation growth season (EOS), from 2001 to 2019. Thus, the whole growth period of forests in Northeast China became prolonged with the change of phenology. Moreover, analysis on the sustainability of NPP in the future indicates that the reverse direction feature of NPP change will be slightly stronger than the co-directional feature, meaning that about 30.68% of the study area will switch from improvement to degradation. To conclude, these above studies could provide an important reference for the sustainable development of forests in Northeast China.