End Of The Growing Season Research Articles

Influence of vegetation phenological carryover effects on plant autumn phenology under climate change

Vegetation phenological carryover effects refer to the influence of previous phenological events on the current or subsequent ones. These effects can modulate the responses of autumn phenology to climate change, but the magnitude and duration of this effect remain poorly understood. Therefore, we employed multiple remote sensing datasets from 1982 to 2018 in the Northern Hemisphere (> 30°N) and partial correlation to investigate the influence of the carryover effect and environmental factors on the end of the growing season (EOS) over time. The importance of the variables in the projection score was used to quantify their relative importance. Our results showed that the previous year's EOS had a robust positive impact on the EOS for 40.02 % of the study area during 1982–2015, which was mainly located in the northern 50°N region. In contrast, the start of the growing season (SOS) was the main contributor to the EOS during 2001–2018, mainly at 40°N-50°N and in northern Russia. The carryover effect persisted into the subsequent year, but its strength and positive impacts varied dramatically in the next year. Concurrently, the mean correlation coefficient between climate factors and EOS rose from 0.20 to 0.22. Notably, the correlation coefficient for frost day frequency increased significantly (P < 0.05) from 0.15 to 0.36, with its influence area expanding from 10.29 % to 11.85 % of the study area. Compared with climate factors, the phenological carryover effect was the dominant driver of the EOS for each vegetation type, accounting for 72.8 % and 44.23 % of the total pixels during 1982–2015 and 2001–2018, respectively. Our study reveals a cascade of ecological consequences that extend beyond the initial occurrence and emphasizes the interconnectedness of growth stages in the plant life cycle, providing valuable insights into the adaptability and vulnerability of plant communities.

Effects of Extreme Climatic Events on the Autumn Phenology in Northern China Are Related to Vegetation Types and Background Climates

The increased intensity and frequency of extreme climate events (ECEs) have significantly impacted vegetation phenology, further profoundly affecting the structure and functioning of terrestrial ecosystems. However, the mechanisms by which ECEs affect the end of the growing season (EOS), a crucial phenological phase, remain unclear. In this study, we first evaluated the temporal variations in the EOS anomalies in Northern China (NC) based on the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from 2001 to 2018. We then used event coincidence analysis (ECA) to assess the susceptibility of EOS to four ECEs (i.e., extreme heat, extreme cold, extreme wet and extreme dry events). Finally, we examined the dependence of the response of EOS to ECEs on background climate conditions. Our results indicated a slight decrease in the proportion of areas experiencing extreme heat and dry events (1.10% and 0.66% per year, respectively) and a slight increase in the proportion of areas experiencing extreme wet events (0.77% per year) during the preseason period. Additionally, EOS exhibited a delaying trend at a rate of 0.25 days/a during the study period. The susceptibility of EOS to ECEs was closely related to local hydrothermal conditions, with higher susceptibility to extreme dry and extreme hot events in drier and warmer areas and higher susceptibility to extreme cold and extreme wet events in wetter regions. Grasslands, in contrast to forests, were more sensitive to extreme dry, hot and cold events due to their weaker resistance to water deficits and cold stress. This study sheds light on how phenology responds to ECEs across various ecosystems and hydrothermal conditions. Our results could also provide a valuable guide for ecosystem management in arid regions.

Disentangling the Effects of Atmospheric and Soil Dryness on Autumn Phenology across the Northern Hemisphere

In recent decades, drought has intensified along with continuous global warming, significantly impacting terrestrial vegetation. High atmospheric water demand, indicated by vapor pressure deficit (VPD), and insufficient soil moisture (SM) are considered the primary factors causing drought stress in vegetation. However, the influences of VPD and SM on the autumn phenology are still unknown. Using satellite observations and meteorological data, we examined the impacts of VPD and SM on the end of the growing season (EOS) across the Northern Hemisphere (&gt;30°N) from 1982 to 2022. We found that VPD and SM were as important as temperature, precipitation, and radiation in controlling the variations in the EOS. Moreover, the EOS was predominantly influenced by VPD or SM in more than one-third (33.8%) of the study area. In particular, a ridge regression analysis indicated that the EOS was more sensitive to VPD than to SM and the other climatic factors, with 25% of the pixels showing the highest sensitivity to VPD. In addition, the effects of VPD and SM on the EOS varied among biome types and climate zones. VPD significantly advanced the EOS in 25.8% of temperate grasslands, while SM had the greatest impact on advancing the EOS in 17.7% of temperate coniferous forests. Additionally, 27.7% of the midlatitude steppe (BSk) exhibited a significant negative correlation between VPD and the EOS, while 19.4% of the marine west coast climate (Cfb) showed a positive correlation between SM and the EOS. We also demonstrated that the correlation between VPD and the EOS was linearly affected by VPD and the leaf area index, while the correlation between SM and the EOS was affected by SM, precipitation, and the leaf area index. Our study highlights the importance of VPD and SM in regulating autumn phenology and enhances our understanding of terrestrial ecosystem responses to climate change.

Reversal of the Spatiotemporal Patterns at the End of the Growing Season of Typical Steppe Vegetation in a Semi-Arid Region by Increased Precipitation

Vegetation phenology serves as a sensitive indicator of climate change. However, the mechanism of the hydrothermal role in vegetation phenology changes is still controversial. Utilizing the data on the Fraction of Absorbed Photosynthetically Active Radiation (FPAR) from MODIS and meteorological data, the study employed the dynamic threshold method to derive the end of the growing season (EOS). The research delved into the spatiotemporal patterns of the EOS for typical steppe vegetation in the semi-arid region of Inner Mongolia spanning the period from 2003 to 2022. Furthermore, the investigation scrutinized the response of EOS to temperature and precipitation dynamics. The results showed that (1) the dynamic threshold method exhibited robust performance in the EOS of typical steppe vegetation, with an optimal threshold of 45% and a Root Mean Square Error (RMSE) of 5.5 days (r = 0.81); (2) the spatiotemporal patterns of the EOS of typical steppe vegetation in the semi-arid region experienced a noteworthy reversal from 2003 to 2022; (3) the lag effects of precipitation and temperature on the EOS were found, and the lag time scales were mainly 1 month and 2 months. The increase in precipitation in August was the key reason for the reversal of the EOS, and satisfying the precipitation was a prerequisite for the temperature to delay the EOS. The study emphasizes the important role of water availability in regulating the response of the EOS to hydrothermal factors and highlights the utility and reliability of FPAR in monitoring the EOS of typical steppe vegetation.

Vegetation Phenology Changes and Recovery after an Extreme Rainfall Event: A Case Study in Henan Province, China

Extreme rainfall can severely affect all vegetation types, significantly impacting crop yield and quality. This study aimed to assess the response and recovery of vegetation phenology to an extreme rainfall event (with total weekly rainfall exceeding 500 mm in several cities) in Henan Province, China, in 2021. The analysis utilized multi-sourced data, including remote sensing reflectance, meteorological, and crop yield data. First, the Normalized Difference Vegetation Index (NDVI) time series was calculated from reflectance data on the Google Earth Engine (GEE) platform. Next, the ‘phenofit’ R language package was used to extract the phenology parameters—the start of the growing season (SOS) and the end of the growing season (EOS). Finally, the Statistical Package for the Social Sciences (SPSS, v.26.0.0.0) software was used for Duncan’s analysis, and Matrix Laboratory (MATLAB, v.R2022b) software was used to analyze the effects of rainfall on land surface phenology (LSP) and crop yield. The results showed the following. (1) The extreme rainfall event’s impact on phenology manifested directly as a delay in EOS in the year of the event. In 2021, the EOS of the second growing season was delayed by 4.97 days for cropland, 15.54 days for forest, 13.06 days for grassland, and 12.49 days for shrubland. (2) Resistance was weak in 2021, but recovery reached in most areas by 2022 and slowed in 2023. (3) In each year, SOS was predominantly negatively correlated with total rainfall in July (64% of cropland area in the first growing season, 53% of grassland area, and 71% of shrubland area). In contrast, the EOS was predominantly positively correlated with rainfall (51% and 54% area of cropland in the first and second growing season, respectively, and 76% of shrubland area); however, crop yields were mainly negatively correlated with rainfall (71% for corn, 60% for beans) and decreased during the year of the event, with negative correlation coefficients between rainfall and yield (−0.02 for corn, −0.25 for beans). This work highlights the sensitivity of crops to extreme rainfall and underscores the need for further research on their long-term recovery.

Spatial and Temporal Variations of Vegetation Phenology and Its Response to Land Surface Temperature in the Yangtze River Delta Urban Agglomeration

In the Yangtze River Delta urban agglomeration, which is the region with the highest urbanization intensity in China, the development of cities leads to changes in land surface temperature (LST), while vegetation phenology varies with LST. To investigate the spatial and temporal changes in vegetation phenology and its response to LST in the study area, this study reconstructed the time series of the enhanced vegetation index (EVI) based on the MODIS EVI product and extracted the vegetation phenology indicators in the study area from 2002 to 2020, including the start of the growing season (SOS), the end of the growing season (EOS), and the growing season length (GSL), and analyzed the temporal–spatial patterns of vegetation phenology and LST in the study area, as well as the correlation between them. The results show that (1) SOS was advanced, EOS was postponed, and GSL was extended in the study area from 2002 to 2020, and there were obvious differences in the vegetation phenology indicators under different land covers and cities; (2) LST was higher in the southeast than in the northwest of the study area from 2002 to 2020, with an increasing trend; and (3) there are differences in the response of vegetation phenology to LST across land covers and cities, and SOS responds differently to LST at different times of the year. EOS shows a significant postponement trend with the annual mean LST increase. Overall, we found differences in vegetation phenology and its response to LST under different land covers and cities, which is important for scholars to understand the response of vegetation phenology to urbanization.

Characterizing Vegetation Phenology Shifts on the Loess Plateau over Past Two Decades

Phenology is a critical mirror reflecting vegetation growth and has a major impact on terrestrial ecosystems. The Loess Plateau (LP) is a paramount ecological zone in China that has experienced considerable vegetation changes. However, understanding the dynamics of vegetation phenology is limited by ambiguous vegetation interpretation and anthropogenic-induced forces. This study combined the multi-climatic and anthropogenic datasets to characterize the interactions between phenology shifts and environmental variables. The principal findings were as follows: (1) Phenological shifts exhibit spatial heterogeneity and an interannually increasing trend in greenness (R2 &gt; 0.6, p &lt; 0.05). Notably, SOS (the start of the growing season) advances while EOS (the end of the growing season) delays in both the southeastern and northwestern regions. (2) SOS and EOS, primarily in the range of 100–150 and 285–320 days, respectively. Phenological changes vary depending on vegetation types. The forest has an early SOS, within 80–112 days, and a delayed EOS, within 288–320 days. The SOS of shrub is mainly within 80–144 days. (3) EOS shows a strong response to the preseason of each climate variable. Precipitation (R = 0.76), soil moisture (R = −0.64), and temperature (R = 0.89) are the governing determinants in shaping vegetation phenology. In addition, agriculture and urbanization play a significant role in shaping the spatial variations of SOS. These findings provide a basis for a systematic understanding of the processes that affect vegetation growth, which is crucial for maintaining the health and sustainability of arid and semiarid ecosystems.

Evaluating the effect of Multi-Scale droughts on autumn phenology of global land biomes with satellite observation

The end of the growing season (EOS), autumn phenology, is a significant indicator of vegetation health in terrestrial ecosystems. Higher frequency and intensity droughts are expected to have a greater impact on ecosystem homeostasis, and an urgent determination of the impact of temporal effects on autumn phenology is imperative to improve the understanding of ecosystem resilience and resistance and the stability of plant carbon sinks. This study aims to quantitatively assess the response of global autumn phenology to observed drought cumulative and lagged effects based on EOS and multi time-scales drought index (the Standardized Precipitation and Evapotranspiration Index, SPEI), and analyze the potential impact path of climate variables on EOS-SPEI relationship. Our results suggested that the cumulative and lagged effects of drought had a significant impact on the autumn phenology of approximately 27.00% and 48.73% of the vegetated area, respectively. The accumulated months were mostly concentrated on shorter time scales (1- to 3-month), and the lagged effect was mostly concentrated on 1 to 3 lagged months. These two effects on EOS were similar in different biomes and water availability, demonstrating that diverse biomes have different adaptation strategies to drought and the importance of water available for ecosystem drought mitigation. Precipitation and solar radiation had a direct negative impact on evaporation, whereas evaporation had a substantial directly positive impact on the intensity of drought effect on autumn phenology. The interaction between the climatic variables results in the accumulated months being directly positively regulated by thermal radiation, while the lagged months were directly positively influenced by precipitation, which indicates that the hydrothermal conditions at the onset of EOS occurrence govern the autumn phenology response to drought more than the occurrence time of EOS.

Refined Analysis of Vegetation Phenology Changes and Driving Forces in High Latitude Altitude Regions of the Northern Hemisphere: Insights from High Temporal Resolution MODIS Products

The vegetation patterns in high-latitude and high-altitude regions (HLAR) of the Northern Hemisphere are undergoing significant changes due to the combined effects of global warming and human activities, leading to increased uncertainties in vegetation phenological assessment. However, previous studies on vegetation phenological changes often relied on long-term time series of remote sensing products for evaluation and lacked comprehensive analysis of driving factors. In this study, we utilized high temporal resolution seamless MODIS products (MODIS-NDVISDC and MODIS-EVI2SDC) to assess the vegetation phenological changes in High-Latitude-Altitude Regions (HLAR) of the Northern Hemisphere. We quantified the differences in vegetation phenology among different land-use types and determined the main driving factors behind vegetation phenological changes. The results showed that the length of the growing season (LOS) derived from MODIS-NDVISDC was 8.9 days longer than that derived from MODIS-EVI2SDC, with an earlier start of the growing season (SOS) by 1.5 days and a later end of the growing season (EOS) by 7.4 days. Among different vegetation types, deciduous needleleaf forests exhibited the fastest LOS extension (p &lt; 0.01), while croplands showed the fastest LOS reduction (p &lt; 0.05). Regarding land-use transitions, the conversion of built-up land to forest and grassland had the longest LOS. In expanding agricultural areas, the LOS of land converted from built-up land to cropland was significantly higher than that of other land conversions. We analyzed human activities and found that as the human footprint gradient increased, the LOS showed a decreasing trend. Among the climate-related factors, the dominant response of phenology to temperature was the strongest in the vegetation greening period. During the vegetation browning period, the temperature control was weakened, and the control of radiation and precipitation was enhanced, accounting for 20–30% of the area, respectively. Finally, we supplement and prove that the highest contributions to vegetation greening in the Northern Hemisphere occurred during the SOS period (May–June) and the EOS period (October). Our study provides a theoretical basis for vegetation phenological assessment under global change. It also offers new insights for land resource management and planning in high-latitude and high-altitude regions.

Impact of Preseason Climate Factors on Vegetation Photosynthetic Phenology in Mid-High Latitudes of the Northern Hemisphere.

During the period preceding the vegetation growing season (GS), temperature emerges as the pivotal factor determining phenology in northern terrestrial ecosystems. Despite extensive research on the impact of daily mean temperature (Tmean) during the preseason period, the influence of diurnal temperature range (DTR) on vegetation photosynthetic phenology (i.e., the impact of the plant photosynthetic cycle on seasonal time scale) has largely been neglected. Using a long-term vegetation photosynthetic phenology dataset and historical climate data, we examine vegetation photosynthetic phenology dynamics and responses to climate change across the mid-high latitudes of the Northern Hemisphere from 2001 to 2020. Our data reveal an advancing trend in the start of the GS (SOS) by -0.15 days per year (days yr-1), affecting 72.1% of the studied area. This is particularly pronounced in western Canada, Alaska, eastern Asia, and latitudes north of 60°N. Conversely, the end of the GS (EOS) displays a delaying trend of 0.17 days yr-1, impacting 62.4% of the studied area, especially northern North America and northern Eurasia. The collective influence of an earlier SOS and a delayed EOS has resulted in the notably prolonged length of the GS (LOS) by 0.32 days yr-1 in the last two decades, affecting 70.9% of the studied area, with Eurasia and western North America being particularly noteworthy. Partial correlation coefficients of the SOS with preseason Tmean, DTR, and accumulated precipitation exhibited negative values in 98.4%, 93.0%, and 39.2% of the study area, respectively. However, there were distinct regional variations in the influence of climate factors on the EOS. The partial correlation coefficients of the EOS with preseason Tmean, DTR, and precipitation were positive in 58.6%, 50.1%, and 36.3% of the region, respectively. Our findings unveil the intricate mechanisms influencing vegetation photosynthetic phenology, holding crucial significance in understanding the dynamics of carbon sequestration within terrestrial ecosystems amidst climate change.

The Impact of Urbanization on Spatial–Temporal Variation in Vegetation Phenology: A Case Study of the Yangtze River Delta, China

The response of vegetation phenology to urbanization has become a growing concern. As impervious surfaces change as urbanization advances, the variation in vegetation phenology at the dynamic urbanization level was analyzed to significantly quantify the impact of urbanization processes on vegetation phenology. Based on the MOD13Q1 vegetation index product from 2001 to 2020, vegetation phenology parameters, including the start of the growing season (SOS), the end of the growing season (EOS), and the length of the growing season (GSL), were extracted, and the spatial–temporal variation in vegetation phenology, as well as its response to urbanization, was comprehensively analyzed. The results reveal that (1) from 2001 to 2020, the average rates of change for the SOS, EOS, and GSL were 0.41, 0.16, and 0.57 days, respectively. (2) The vegetation phenology changes showed significant spatial–temporal differences at the urbanization level. With each 10% increase in the urbanization level, the SOS and EOS were advanced and delayed by 0.38 and 0.34 days, respectively. (3) The urban thermal environment was a major factor in the impact of urbanization on the SOS and EOS. Overall, this study elucidated the dynamic reflection of urbanization in phenology and revealed the complex effects of urbanization on vegetation phenology, thus helping policymakers to develop effective strategies to improve urban ecological management.

Decoding autumn phenology: Unraveling the link between observation methods and detected environmental cues.

Leaf coloring and fall mark the end of the growing season (EOS), playing essential roles in nutrient cycling, resource allocation, ecological interactions, and as climate change indicators. However, understanding future changes in autumn phenology is challenging due to the multitude of likely environmental cues and substantial variations in timing caused by different derivation methods. Yet, it remains unclear whether these two factors are independent or if methodological uncertainties influence the environmental cues determined. We derived start of growing season (SOS) and EOS at a mixed beech forest in Central Germany for the period 2000-2020 based on four different derivation methods using a unique long-term data set of in-situ data, canopy imagery, eddy covariance measurements, and satellite remote sensing data and determined their influence on a predictor analysis of leaf senescence. Both SOS and EOS exhibited substantial ranges in mean onset dates (39.5 and 28.6 days, respectively) across the different methods, although inter-annual variations and advancing SOS trends were similar across methods. Depending on the data, EOS trends were advanced or delayed, but inter-annual patterns correlated well (mean r = .46). Overall, warm, dry, and less photosynthetically productive growing seasons were more likely to be associated with a delayed EOS, while colder, wetter, and more photosynthetically productive vegetation periods resulted in an earlier EOS. In addition, contrary to recent results, no clear influence of pre-solstice vegetation activity on the timing of senescence was detected. However, most notable were the large differences in sign and strength of potential drivers both in the univariate and multivariate analyses when comparing derivation methodologies. The results suggest that an ensemble analysis of all available phenological data sources and derivation methods is needed for general statements on autumn phenology and its influencing variables and correct implementation of the senescence process in ecosystem models.

Vegetation Phenological Differences Between Polar‐ and Equatorial‐Facing Slopes in the Three Rivers Source Region, Tibetan Plateau

AbstractVegetation growth is influenced by the microclimate driven by aspects, as evident in the asymmetric vegetation greenness on polar‐facing slopes (PFS) and equatorial‐facing slopes (EFS). However, it remains uncertain whether aspects influence vegetation phenology. To address this question, we defined the aspect‐induced phenological differences between PFS and EFS from 2019 to 2022 within each 3 × 3 km2 grid, using average phenological metrics extracted from Sentinel‐2 data. We found that the start of the growing season (SOS) occurs earlier on EFS in cold and humid regions, but in arid areas, PFS has an earlier SOS. The end of the growing season (EOS) consistently occurred later on EFS due to radiation limitations in autumn phenology. Employing the space‐for‐time approach, the observed distribution of phenological differences within the climate space could potentially indicate the phenological trends of different slope orientations in the future. Our study provides valuable insights into topographic regulation on vegetation phenology.

Altitude explains insignificant autumn phenological changes across regions with large topography relief in the Tibetan Plateau

The start of the growing season (SGS) and the end of the growing season (EGS) are widely employed in global change studies to represent the spring and autumn phenology, respectively. Despite the Tibetan Plateau (TP) experiencing significant warming in recent decades, EGS has exhibited only slight changes. Previous studies have concentrated on exploring the environmental regulation of phenology, ignoring the distinctive influences of elevation. Therefore, a more in-depth investigation into the underlying mechanism is warranted. In this study, we investigate the variability of EGS among alpine vegetation regions at different elevations and conduct an analysis based on satellite data. Phenology data of alpine vegetation are extracted from SPOT NDVI dataset spanning from 1999 to 2018, using a piecewise-logistic-maximum-ratio method. We analyze the factors influencing EGS trends at different elevations. The results show that the overall insignificant variation in EGS is mainly attributed to altitude. With the altitude increasing, the annual mean EGS experiences a delay of 0.28 days/100 m below 3500 m, while it advances by 0.2 days/100 m above 3500 m. The opposing shift in elevation below and above 3500 m leads to this counteraction. Elevation emerges as the predominant factor influencing EGS trends, explaining the highest variations (38 %), followed by SGS (22 %) and precipitation (22 %). The elevation effect is most pronounced in areas with substantial topography fluctuations. Moreover, the elevation lapse rate of EGS (ELR_EGS) exhibits an opposite trend with growing season (GS) temperature and a similar trend with GS precipitation between the regions below and above 3500 m, ultimately linking to this counteraction. This study underscores elevation is a critical regulator of vegetation EGS responses to climatic changes over the TP, revealing significant spatial heterogeneities in these responses.

Soil freeze–thaw cycles affect spring phenology by changing phenological sensitivity in the Northern Hemisphere

The use of frozen soil-vegetation feedback for predictive models is undergoing enormous changes under rapid climate warming. However, the influence of soil freeze–thaw (SFT) cycles on vegetation phenology and the underlying mechanisms remain poorly understood. By synthesizing a variety of satellite-derived data from 2002 to 2021 in the Northern Hemisphere (NH), we demonstrated a widespread positive correlation between soil thawing and the start of the growing season (SOS). Our results also showed that the SFT cycles had a significant impact on vegetation phenology mainly by altering the phenological sensitivities to daytime and nighttime temperatures, solar radiation and precipitation. Moreover, the effects of SFT cycles on the sensitivity of the SOS were more pronounced than those on the sensitivity of the end of the growing season (EOS) and the length of growing season (LOS). Furthermore, due to the degradation of frozen soil, the changes in phenological sensitivity in the grassland and tundra biomes were significantly larger than those in the forest. These findings highlighted the importance of incorporating the SFT as an intermediate process into process-based phenological models.

Dry season temperature and rainy season precipitation significantly affect the spatio-temporal pattern of rubber plantation phenology in Yunnan province.

The ongoing global warming trajectory poses extensive challenges to plant ecosystems, with rubber plantations particularly vulnerable due to their influence on not only the longevity of the growth cycle and rubber yield, but also the complex interplay of carbon, water, and energy exchanges between the forest canopy and atmosphere. However, the response mechanism of phenology in rubber plantations to climate change remains unclear. This study concentrates on sub-optimal environment rubber plantations in Yunnan province, Southwest China. Utilizing the Google Earth Engine (GEE) cloud platform, multi-source remote sensing images were synthesized at 8-day intervals with a spatial resolution of 30-meters. The Normalized Difference Vegetation Index (NDVI) time series was reconstructed using the Savitzky-Golay (S-G) filter, coupled with the application of the seasonal amplitude method to extract three crucial phenological indicators, namely the start of the growing season (SOS), the end of the growing season (EOS), and the length of the growing season (LOS). Linear regression method, Pearson correlation coefficient, multiple stepwise regression analysis were used to extract of the phenology trend and find the relationship between SOS, EOS and climate factors. The findings demonstrated that 1) the phenology of rubber plantations has undergone dynamic changes over the past two decades. Specifically, the SOS advanced by 9.4 days per decade (R2 = 0.42, p< 0.01), whereas the EOS was delayed by 3.8 days per decade (R2 = 0.35, p< 0.01). Additionally, the LOS was extended by 13.2 days per decade (R2 = 0.55, p< 0.01); 2) rubber phenology demonstrated a notable sensitivity to temperature fluctuations during the dry season and precipitation patterns during the rainy season. The SOS advanced 2.0 days (r =-0.19, p< 0.01) and the EOS advanced 2.8 days (r =-0.35, p< 0.01) for every 1°C increase in the cool-dry season. Whereas a 100 mm increase in rainy season precipitation caused the SOS to be delayed by 2.0 days (r = 0.24, p< 0.01), a 100 mm increase in hot-dry season precipitation caused the EOS to be advanced by 7.0 days (r =-0.28, p< 0.01); 3) rubber phenology displayed a legacy effect of preseason climate variations. Changes in temperature during the fourth preseason month and precipitation during the fourth and eleventh preseason months are predominantly responsible for the variation in SOS. Meanwhile, temperature changes during the second, fourth, and ninth preseason months are primarily responsible for the variation in EOS. The study aims to enhance our understanding of how rubber plantations respond to climate change in sub-optimal environments and provide valuable insights for sustainable rubber production management in the face of changing environmental conditions.

Drought decreased annual cumulative carbon uptake in Southwest China mainly through its influence on phenology rather than physiology

Drought poses a significant threat to the sustainability of ecosystems, particularly in regions like Southwest China, where it has been observed to substantially reduce the annual cumulative carbon uptake (ACCU). Understanding the mechanisms driving this reduction is therefore crucial for effective ecosystem management. To address this issue, this study decomposed ACCU into three indicators, i.e., start of the growing season (SOS), end of the growing season (EOS), and peak gross primary productivity (GPPmax), through the Statistical Model of Integrated Phenology and Physiology (SMIPP), and explored the response of ACCU to drought. The results revealed that phenology (SOS and EOS) and physiology (GPPmax) components collectively captured 74% of the variation in ACCU, confirming the applicability of the SMIPP model in Southwest China. Among the three indicators, GPPmax contributes to ACCU more than the two phenological indicators. We also found that, from 2001 to 2020, drought decreased ACCU by 65.58 Tg C through delying SOS, by 21.47 Tg C through advancing EOS, but increased ACCU by 11.15 Tg C through increasing GPPmax, resulting in a net loss of 75.90 Tg C in ACCU. Our findings highlight the predominant negative impact of drought on ACCU, achieved primarily through alterations in phenology. Overall, this study quantified the respective contributions of phenology and physiology in the response of ACCU to drought, and would inform the prediction of ACCU of ecosystems under future drought in Southwest China.

Spatiotemporal variations of leaf senescence velocity on the Tibetan Plateau grasslands

Leaf senescence plays a pivotal role in the regulation of carbon and nutrient cycles within terrestrial ecosystems. However, our understanding of leaf senescence velocity (LSV) remains comparatively limited when compared to the end of the growing season (EOS). In this study, we extracted the LSV in Tibet Plateau (TP) over the period 2001–2018 based on the satellite-derived normalized difference greenness index (NDGI), then we evaluated the influences of climate drivers on the spatio-temporal variations of LSV. Lastly, we explored the implications of LSV on vegetation growth by analyzing the correlation between LSV and the start of growing season (SOS) and the annual net primary production (NPP). Our findings revealed that the multi-year averaged LSV ranged from 30 to 70% mon-1 and displayed a discernible spatial gradient, declining from west to east, and the spatial pattern of LSV was mainly controlled by radiation. Trend tests and partial correlation analyses unveiled a temporal decrease in LSV within the central TP region, attributed to rising temperatures, while an increase was observed in the southwestern TP due to water deficits. We also found that LSV had a strong impact on current-year net NPP and following-year SOS. This suggests that LSV may play a significant role in regulating carbon exchange during the current year and influencing the onset of spring green-up in the subsequent year. By emphasizing the continuous nature of leaf senescence, our study provides fresh insights into the intricate interactions between vegetation growth and climate change, contributing to the existing body of knowledge in this field.

Can land surface phenology from Sentinel-2 time-series be used as an indicator of Macaronesian ecosystem dynamics?

Land surface phenology (LSP), the study of phenological patterns of vegetation using vegetation index (VI) time-series derived from multi-spectral satellite imagery, has helped to improve the understanding of the seasonal dynamics of terrestrial ecosystems from local to global scale. High spatial resolution satellite observations have emerged as a new possibility for monitoring the seasonal dynamics of heterogeneous ecosystems. Under-studied Macaronesian ecosystems have specific characteristics that make LSP estimation a complex task (e. g., frequent cloud cover, frequent presence of atmospheric aerosols, different degrees of vegetation density, diversity of plant species, landscape heterogeneity). Thus, this study aims to analyse the potential of LSP based on Sentinel-2 data to monitor the phenological dynamics of vegetation in the Macaronesian ecosystems of Canary Islands (Spain). NDVI time-series were generated using Sentinel-2 data from January 2018 to December 2021. NDVI time-series were smoothed using double logistic function. Three phenometrics, such as the start of the growing season (SOS), the end of the growing season (EOS) and the length of the growing season (LOS), were extracted using a threshold-based method (20%) only for pixels where the mean NDVI value of the smoothed four-year time-series was higher than 0.2. Growing season of the major of Macaronesian vegetation started between late summer and late autumn (start of the wet season) and ended between early spring and early summer (end of the wet season). The most representative Macaronesian tree species had a clear and marked seasonality, except for the laurel forest species. SOS of Juniperus phoenicea subsp. turbinata was slightly later than for Olea europaea var. sylvestris and Pinus canariensis, while the mean EOS was slightly later for Olea europaea var. sylvestris. The intra-specific variability of SOS and EOS in the laurel forests was very high. LSP derived from Sentinel-2 data contributed to understand the seasonal dynamics of the main Macaronesian ecosystems. However, the heterogeneity of laurel forests made it difficult the LSP estimation in laurel forests. Thus, complementary phenological approaches are suggested to improve the knowledge of the seasonal dynamics of this Macaronesian ecosystem.

Forest Phenology under Differing Topographic Conditions: A Case Study of Changbai Mountain in Northeast China

Forest phenology is sensitive to climate change, and its responses affect many land surface processes, resulting in a feedback effect on climate change. Human activities have been the main driver of climate change’s long-term shifts in temperature and weather patterns. Forest phenology, understood as the timing of the annual cycles of plants, is extremely sensitive to changes in climate. Quantifying the responses of temperate forest phenology under an elevational range of topographic conditions that mimic climate change is essential for making effective adaptive forest ecosystem management decisions. Our study utilized the Google Earth Engine (GEE), gap filling, and the Savitzky–Golay (GF-SG) algorithm to develop a long-time series spatio-temporal remote sensing data fusion. The forest phenology characteristics on the north slope of Changbai Mountain were extracted and analyzed annually from 2013 to 2022. Our study found that the average start of the growing season (SOS) on the north slope of Changbai Mountain occurred between the 120th–150th day during the study period. The end of the growing season (EOS) occurred between the 270th–300th day, and the length of the growing season (LOS) ranged from the 110th–190th day. A transect from the northeast to southwest of the study area for a 10-year study period found that SOS was delayed by 39 d, the EOS advanced by 32 d, and the LOS was gradually shortened by 63 d. The forest phenology on the north slope of Changbai Mountain showed significant topographic differentiations. With an increase of 100 m in altitude, the mean SOS was delayed by 1.71 d (R2 = 0.93, p &lt; 0.01). There were no obvious trends in EOS variation within the study area altitude gradient. LOS decreased by 1.23 d for each 100 m increase in elevation (R2 = 0.90, p &lt; 0.01). Forests on steep slopes had an earlier SOS, a later EOS, and a longer LOS than forests on gentle slopes. For each degree increase in slope, SOS advanced by 0.12 d (R2 = 0.53, p = 0.04), EOS was delayed by 0.18 d (R2 = 0.82, p = 0.002), and the LOS increased by 0.28 d (R2 = 0.78, p = 0.004). The slope aspect had effects on the EOS and the LOS but had no effect on the SOS. The forest EOS of the south aspect was 3.15 d later than that of the north aspect, and the LOS was 6.47 d longer. Over the 10-year study period, the phenology differences between the north and south aspects showed that the LOS difference decreased by 0.85 d, the SOS difference decreased by 0.34 d, and the EOS difference decreased by 0.53 d per year. Our study illustrates the significance of the coupling mechanism between mountain topography and forest phenology, which will assist our future understanding of the response of mountain forest phenology to climate change, and provide a scientific basis for further research on temperate forest phenology.