No trends in spring and autumn phenology during the global warming hiatus

Cascading environmental, phenological, and physiological influences on spatial variability of annual gross primary productivity in the Northern Hemisphere

Accurately assessing spatiotemporal variations in terrestrial gross primary productivity (GPP) is crucial for understanding the interactions between the terrestrial carbon cycle and climate change. Environmental factors influence annual GPP (AGPP) either directly or indirectly through plant phenology and physiology. However, it remains unclear how environment, plant phenology, and physiology interact to influence the spatial patterns of global AGPP. In this study, we analyzed the geographic patterns and primary controls of the phenological and physiological properties of GPP using 827 site-years of eddy covariance data from 101 sites in the Northern Hemisphere. Specifically, the cascading relationships among environmental, phenological, and physiological factors that contribute to the spatial patterns of AGPP were tested. While the majority of ecosystems across different biomes displayed unimodal GPP seasonal patterns, significant geographical variations were observed in their phenological and physiological properties. The growing season length (GSL) decreased with increasing latitude (P < 0.001), while the maximum photosynthetic capacity (GPPmax) increased from 20°N to 70°N (P < 0.001). The foremost drivers of the spatial variation in the start date of the growing season (SGS), the end date of the growing season (EGS), and GPPmax were winter air temperature, summer precipitation, and spring solar radiation, respectively, which in turn influenced the spatial variation in AGPP. The cascade effects (0.95) of environmental factors on AGPP were larger than the direct effects (0.28). The cascading relationships among environmental factors, SGS, EGS, and GPPmax explained 93 % of the spatial pattern in AGPP. GPPmax exerted the strongest direct influence (0.60) on AGPP, followed by SGS (0.33). Environmental factors influenced the spatial variability of AGPP through cascading effects mediated by plant phenology and physiology. These findings not only provide fundamental parameters for model validation but also enhance our understanding of the intricate environmental and biotic controls governing the spatial pattern of AGPP.

Climate change influences on vegetation photosynthesis in the Northern Hemisphere

Changes in ecosystem productivity affect terrestrial carbon sequestration. In previous research on the effects of climate change, it has been determined that prolonged growing season length (LOS) increases vegetation productivity in ecosystems. In addition to the duration of vegetation growth, the intensity of photosynthesis is another factor influencing the annual accumulated vegetation productivity. Nevertheless, the impact of climate change on productivity through photosynthetic intensity of vegetation remains uncertain. Here, we utilized the photosynthetic phenology extracted from solar-induced chlorophyll fluorescence (SIF) to investigate the influence of climate change on the annual peak value of vegetation photosynthesis (SIFmax), as well as the contribution of SIFmax to annual accumulated gross primary productivity (GPPann) in the Northern Hemisphere (>30° N). Furthermore, the influence of changes in LOS and SIFmax on GPPann were compared. The results showed that vegetation SIFmax increased in 73.0% of the areas, and that different climatic factors (radiation, precipitation and temperature), and the advanced start of the growing season (SOS) contributed to an increase in SIFmax. GPPann was more sensitive to the peak of photosynthesis than LOS, with SIFmax being the dominant factor affecting GPPann in 39.9% of the study area, compared to 13.7% of the area dominated by LOS. Our results demonstrated that climate change increases GPPann primarily by increasing SIFmax rather than by extending LOS. While temperature was the largest contributor to GPPann among all climate factors, precipitation and radiation can also have an obvious effect on GPPann through SIFmax. Our study highlights the important mediating role of peak photosynthesis in the influence of climatic factors on the annual accumulated productivity of vegetation. The results provide implications for understanding the characteristics of vegetation response to climate change, and for the development of ecosystem restoration and carbon management strategies.

Winter climate change mediates the sensitivity of vegetation leaf-out to spring warming in high latitudes in China

Global warming has significantly altered plant phenology by advancing the timing of leaf emergence, impacting vegetation productivity and adaptability. Winter and spring temperatures have commonly been used to explain spring phenology shifts, but we still lack a solid understanding of the effects of interactions between conditions in different seasons. This study utilizes normalized difference vegetation index (NDVI) and meteorological data to examine the effects of changes in winter and spring temperatures and precipitation on the start of the vegetation growing season (SOS) at high latitudes in China from 1982 to 2015. We found that SOS in Northeast China, as a whole, showed a weak advancing trend (moving earlier in the year), but with obvious regional differences. Even within the same vegetation type, changes in SOS were faster in the cold north (1.9 days/decade) and the cold and dry northwest (1.6 days/decade) than the regional averages for deciduous needleleaf forests (DNF; 1.2 days/decade) and grasslands (0.6 days/decade). Increases in spring temperatures dominate forest SOS advancement, while grassland SOS is mainly influenced by winter and spring precipitation. Decreases in winter minimum temperature (Tmin) enhance the spring temperature sensitivity of SOS. The way that winter precipitation regulates the spring temperature sensitivity of SOS differs among vegetation types: increasing sensitivity in grasslands but suppressing it in DNF. The moderating effects of winter conditions account for the greatest part of the regional differences in the magnitude of change in SOS. Our findings highlight that, although rising spring temperatures significantly affect SOS, winter Tmin and precipitation are crucial for understanding spatial SOS differences, particularly in cold, arid high-latitude regions. Winter conditions play an essential role in regulating the response of vegetation SOS to spring climate at high latitudes. These results suggest that considering the moderating effect of winter climate can facilitate more accurate predictions of temperature-driven phenological changes under future climate change.

Resistance of grassland productivity to drought and heatwave over a temperate semi-arid climate zone

Drought and heatwave are the primary climate extremes for vegetation productivity loss in the global temperate semi-arid grassland, challenging the ecosystem productivity stability in these areas. Previous studies have indicated a significant decline in the resistance of global grassland productivity to drought, but we still lack a systematic understanding of the mechanisms determining the spatiotemporal variations in grassland resistance to drought and heatwave. In this study, we focused on temperate semi-arid grasslands of China (TSGC) to assess the spatiotemporal variations of grassland productivity resistance to different climate extremes: compound dry-hot events, individual drought events, and individual heatwave events that occurred during 2000-2019. Based on the explainable machine learning model, we explored the resistance to the interaction of drought and heatwave and identify the dominant factors determining the spatiotemporal variations in resistance. The results revealed that grassland resistance to climate extremes had decreased in Xilingol Grassland and Mu Us Sandy Land, and had a not significant increase in Otindag Desert during 2000-2019. Human activities and the increase in CO2 concentration causes a decline in resistance in Mu Us Sandy Land, and the increase of VPD and shift of vegetation loss event timing caused a decline in resistance in Xilingol Grassland, while the weakening of climate extremes, especially the shortening of drought duration, increase the resistance in Otindag Desert. Mean annual temperature dominates the spatial differences in resistance among different grasslands. When drought and heatwave occur simultaneously, there is an additive effect on resistance and causes lower resistance to compound dry-hot events compared to individual drought and heatwave events. Our analysis provides crucial insights into understanding the impact of climate extremes on the temperate semi-arid grasslands of China.

Asymmetric temperature effect on leaf senescence and its control on ecosystem productivity

Widespread autumn cooling occurred in the northern hemisphere (NH) during the period 2004-2018, primarily due to the strengthening of the Pacific Decadal Oscillation and Siberian High. Yet, while there has been considerable focus on the warming impacts, the effects of natural cooling on autumn leaf senescence and plant productivity have been largely overlooked. This gap in knowledge hinders our understanding of how vegetation adapts and acclimates to complex climate change. In this study, we utilize over 36,000 in situ phenological time series from 11,138 European sites dating back to the 1950s, and 30 years of satellite greenness data (1989-2018), to demonstrate that leaf senescence dates (LSD) in northern forests responded more strongly to warming than to cooling in autumn. Specifically, a 1 °C increase in temperature caused 7.5 ± 0.2 days' delay in LSD, whereas a 1 °C decrease led to an advance of LSD with 3.3 ± 0.1 days (P < 0.001). This asymmetry in temperature effects on LSD is attributed to greater preoverwintering plant-resource acquisition requirements, lower frost risk, and greater water availability under warming than cooling conditions. These differential LSD responses highlight the nonlinear impact of temperature on autumn plant productivity, which current process-oriented models fail to accurately capture. Our findings emphasize the need to account for the asymmetric effects of warming and cooling on leaf senescence in model projections and in understanding vegetation-climate feedback mechanisms.

Precipitation controls the time-lag and cumulative effects of hydrothermal factors on the end of the growing season in a semi-arid region of China

Climate change has a substantial influence on the end of the growing season (EOS). The time-lag and cumulative effects are non-negligible phenomena when studying the interactions between climate and vegetation. However, quantification of the temporal effects of climatic factors on the EOS in the context of changing hydrothermal patterns remains scarce. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) fraction of absorbed photosynthetically active radiation (FPAR), this study first inverted the EOS of typical steppe vegetation in a semi-arid region of China and then quantified the time-lag and cumulative effects of monthly total precipitation (PRE) and monthly average temperature (TEM) on the EOS during 2003-2022. The results showed that a turning point occurred in 2011, when the EOS displayed an advancing trend until 2011, followed by a delayed trend. Accordingly, the climatic background has changed from warming and drying conditions during 2003-2011 to warming and wetting conditions during 2011-2022. The time-lag scales of PRE and TEM on the EOS decreased from 2- and 4-month scales during 2003-2011, respectively, to 1- and 2-month scales during 2011-2022, respectively. The time-lag degree of the hydrothermal factors on the EOS weakened with increased precipitation. The cumulative time scales of the EOS response to PRE and TEM were mainly concentrated within 1-month during different time periods, but the EOS was more sensitive to short-term precipitation. The time lag and cumulative partial correlation coefficient of PRE to EOS changed from mainly negative regulation during 2003-2011 (39.2% and 50.0%, respectively) to mainly positive regulation during 2011-2022 (67.8% and 93.7%, respectively). The time-lag and cumulative effects of TEM on the EOS were positive with the precipitation and temperature gradient under a warming and wetting climate, which indicated that increased precipitation was a prerequisite for temperature to induce a delayed EOS in the semi-arid study region. This study emphasizes the important role of precipitation in regulating the EOS response to hydrothermal factors in semi-arid regions.

Assessment of Phenological Dynamics of Different Vegetation Types and Their Environmental Drivers with Near-Surface Remote Sensing: A Case Study on the Loess Plateau of China

Plant phenology is an important indicator of the impact of climate change on ecosystems. We have continuously monitored vegetation phenology using near-surface remote sensing, i.e., the PhenoCam in a gully region of the Loess Plateau of China from March 2020 to November 2022. In each image, three regions of interest (ROIs) were selected to represent different types of vegetation (scrub, arbor, and grassland), and five vegetation indexes were calculated within each ROI. The results showed that the green chromatic coordinate (GCC), excess green index (ExG), and vegetation contrast index (VCI) all well-captured seasonal changes in vegetation greenness. The PhenoCam captured seasonal trajectories of different vegetation that reflect differences in vegetation growth. Such differences may be influenced by external abiotic environmental factors. We analyzed the nonlinear response of the GCC series to environmental variables with the generalized additive model (GAM). Our results suggested that soil temperature was an important driver affecting plant phenology in the Loess gully region, especially the scrub showed a significant nonlinear response to soil temperature change. Since in situ phenology monitoring experiments of the small-scale on the Loess Plateau are still relatively rare, our work provides a reference for further understanding of vegetation phenological variations and ecosystem functions on the Loess Plateau.

Estimating global annual gross primary production based on satellite-derived phenology and maximal carbon uptake capacity

The high uncertainty regarding global gross primary production (GPP) remains unresolved. This study explored the relationships between phenology, physiology, and annual GPP to provide viable alternatives for accurate estimation. A statistical model of integrated phenology and physiology (SMIPP) was developed using GPP data from 145 FLUXNET sites to estimate the annual GPP for various vegetation types. By employing the SMIPP model driven by satellite-derived datasets of the global carbon uptake period (CUP) and maximal carbon uptake capacity (GPPmax), the global annual GPP was estimated for the period from 2001 to 2018. The results demonstrated that the SMIPP model accurately predicted annual GPP, with relative root mean square error values ranging from 11.20 to 19.29% for forest types and 20.49-35.71% for non-forest types. However, wetlands, shrublands, and evergreen forests exhibited relatively low accuracies. The average, trend, and interannual variation of global GPP during 2001-2018 were 132.6 Pg C yr-1, 0.25 Pg C yr-2, and 1.57 Pg C yr-1, respectively. They were within the ranges estimated in other global GPP products. Sensitivity analysis revealed that GPPmax had comparable effects to CUP in high-latitude regions but significantly greater impacts at the global scale, with sensitivity coefficients of 0.85 ± 0.23 for GPPmax and 0.46 ± 0.28 for CUP. This study provides a simple and practical method for estimating global annual GPP and highlights the influence of GPPmax and CUP on global-scale annual GPP.

Revisiting the hydrological legacy of revegetation on China's Loess Plateau using Eagleson's ecohydrological perspective

Revegetation has resulted in a trend of increasing vegetation greenness on the Chinese Loess Plateau. However, it remains unclear whether the regional vegetation coverage exceeds hydroclimatic limitations in the context of revegetation, and the hydrological effects of greening are controversial. Eagleson's optimality hypothesis can explain some of the hydrological effects on the Loess Plateau. Here, building on previous research, the geospatial vegetation states were estimated for pre- and post-revegetation periods on the Loess Plateau from 1982 to 2015 using Eagleson's ecological optimality theory. Additionally, a drought composite analysis approach was utilized to investigate the hydrological effects related to drought (including sensitivity and partitioning) under various vegetation states. It was found that revegetation increased the proportion of catchments in the equilibrium state and decreased the proportion in the disturbed state, owing to a wetter climate compared with the pre-revegetation period. Root-zone soil drought, driven by precipitation (P) deficit, asymmetrically triggered hydrological effects for both the pre- and post-revegetation periods, with reduced runoff (Q) for both periods and a decrease in evapotranspiration (ET) during the pre-revegetation period but an increase in ET during the post-revegetation period. Moreover, catchments in an equilibrium state exhibited lower sensitivity between ET and P, and more stable partitioning of ET with regards to P, compared with those in a disturbed state. These results underscore the theoretical framework that an equilibrium state is crucial for maintaining ecosystem ET. Our results highlight the necessity of considering the hydrologic regulation of vegetation states when assessing the hydrological effects of vegetation change.

Extreme low air temperature and reduced moisture jointly inhibit respiration in alpine grassland on the Qinghai-Tibetan Plateau

Alpine grassland is the main vegetation on the Qinghai-Tibetan Plateau (QTP) and exhibits high sensitivity to extreme weather events. With global warming, extreme weather events are projected to become more frequent on the QTP. However, the impact of these extreme weather events on the carbon cycle of alpine grassland remains unclear. The long-term in-situ carbon fluxes data was collected from 2013 to 2022 at an alpine grassland site to examine the impact of extreme low air temperature (ELT) and reduced moisture (including air and soil) on carbon fluxes during the growing season. Our findings indicated that a significant increase in net ecosystem production (NEP) after 2019, with the average NEP increasing from 278.91 ± 43.27 g C m-2 year-1 during 2013-2018 to 415.45 ± 45.29 g C m-2 year-1 during 2019-2022. The ecosystem carbon use efficiency (CUE) increased from 0.38 ± 0.06 during 2013-2018 to 0.62 ± 0.11 during 2019-2022. By combining concurrently measured environmental factors and remote sensing data, we identified the factors responsible for the abrupt change in the NEP after 2019. This phenomenon was caused by an abrupt decrease in ecosystem respiration (Reco) after 2019, which resulted from the inhibition imposed by ELT and reduced moisture. In contrast, gross primary production (GPP) remained stable from 2013 to 2022, which was confirmed by the remotely sensed vegetation index. This study highlights that combined extreme weather events associated with climate change can significantly impact the NEP of alpine grassland, potentially affecting different carbon fluxes at different rates. These findings provide new insights into the mechanisms governing the carbon cycle of alpine grassland.

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.

Understanding vegetation phenology responses to easily ignored climate factors in china's mid-high latitudes

Previous studies have primarily focused on the influence of temperature and precipitation on phenology. It is unclear if the easily ignored climate factors with drivers of vegetation growth can effect on vegetation phenology. In this research, we conducted an analysis of the start (SOS) and end (EOS) of the growing seasons in the northern region of China above 30°N from 1982 to 2014, focusing on two-season vegetation phenology. We examined the response of vegetation phenology of different vegetation types to preseason climatic factors, including relative humidity (RH), shortwave radiation (SR), maximum temperature (Tmax), and minimum temperature (Tmin). Our findings reveal that the optimal preseason influencing vegetation phenology length fell within the range of 0-60 days in most areas. Specifically, SOS exhibited a significant negative correlation with Tmax and Tmin in 44.15% and 42.25% of the areas, respectively, while EOS displayed a significant negative correlation with SR in 49.03% of the areas. Additionally, we identified that RH emerged as the dominant climatic factor influencing the phenology of savanna (SA), whereas temperature strongly controlled the SOS of deciduous needleleaf forest (DNF) and deciduous broadleaf forest (DBF). Meanwhile, the EOS of DNF was primarily influenced by Tmax. In conclusion, this study provides valuable insights into how various vegetation types adapt to climate change, offering a scientific basis for implementing effective vegetation adaptation measures.

Impacts of mining on vegetation phenology and sensitivity assessment of spectral vegetation indices to mining activities in arid/semi-arid areas

Measuring the impact of mining activities on vegetation phenology and assessing the sensitivity of vegetation indices (VIs) to it are crucial for understanding land degradation in mining areas and enhancing the carbon sink capacity following the ecological restoration of mines. To this end, we have developed a novel technical framework to quantify the impact of mining activities on vegetation, and applied it to the Bainaimiao copper mining area in Inner Mongolia. Phenological indices are extracted based on the VI time series data of Sentinel-2, and changes in phenological differences in various directions are used to quantify the impact of mining activities on vegetation. Finally, indicators such as mean difference, standard deviation, index value distribution interval, and concentration of index value distribution were selected to assess the sensitivity of the Enhanced Vegetation Index (EVI), Green Chlorophyll Index (GCI), Global Environmental Monitoring Index (GEMI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Difference Vegetation Index (NDVI), Renormalized Difference Vegetation Index (RDVI), Red-Edge Chlorophyll Index (RECI), and Soil-Adjusted Vegetation Index (SAVI) to mining activities. The results of the study show that the impact of mining activities on surrounding vegetation extends to an area three times larger than the actual mining activity area. When compared with the reference and unaffected areas, the affected area experienced a delay of approximately 10 days in seasonal vegetation development. Environmental pollution caused by the tailings pond was identified as the primary factor influencing this delay. Significant variations in the sensitivity of each VI to assess mining activities in arid/semi-arid areas were observed. Notably, GCI, GNDVI and RDVI displayed relatively high sensitivity to discrepancies in the spectral attributes of vegetation within the affected area, while SAVI reflected the overall spectral stability of the vegetation in the affected area. The research findings have the potential to provide valuable technical guidance for holistic environmental management in mining areas and hold great significance in preventing further land degradation and supporting ecological restoration in mining areas.

Vegetation canopy structure mediates the response of gross primary production to environmental drivers across multiple temporal scales

Gross primary production (GPP) is a critical component of the global carbon cycle and plays a significant role in the terrestrial carbon budget. The impact of environmental factors on GPP can occur through both direct (by influencing photosynthetic efficiency) and indirect (through the modulation of vegetation structure) pathways, but the extent to which these mechanisms contribute has been seldom quantified. In this study, we used structural equation modeling and observations from the FLUXNET network to investigate the direct and indirect effects of environmental factors on terrestrial ecosystem GPP at multiple temporal scales. We found that canopy structure, represented by leaf area index (LAI), is a crucial intermediate factor in the GPP response to environmental drivers. Environmental factors affect GPP indirectly by altering canopy structure, and the relative proportion of indirect effects decreased with increasing LAI. The study also identified different effects of environmental factors on GPP across time scales. At the half-hourly time scale, radiation was the primary driver of GPP. In contrast, the influences of temperature and vapor pressure deficit took on greater prominence at longer time scales. About half of the total effect of temperature on GPP was indirect through the regulation of canopy structure, and the indirect effect increased with increasing time scale (GPPNT-based models: 0.135 (half-hourly) vs. 0.171 (daily) vs. 0.189 (weekly) vs. 0.217 (monthly); GPPDT-based models: 0.139 vs. 0.170 vs. 0.187 vs. 0.215; all values were reported in gC m-2 d-1 °C-1, P < 0.001); while the indirect effect of radiation on GPP was comparatively lower, accounting for less than a quarter of the total effect. Furthermore, we observed a direct, negative-to-positive impact of precipitation on GPP across timescales. These findings provide crucial information on the interplay between environmental factors and LAI on GPP and enable a deeper understanding of the driving mechanisms of GPP.

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.

Spatial Variation in Responses of Plant Spring Phenology to Climate Warming in Grasslands of Inner Mongolia: Drivers and Application

Plant spring phenology in grasslands distributed in the Northern Hemisphere is highly responsive to climate warming. The growth of plants is intricately influenced by not only air temperature but also precipitation and soil factors, both of which exhibit spatial variation. Given the critical impact of the plant growth season on the livelihood of husbandry communities in grasslands, it becomes imperative to comprehend regional-scale spatial variation in the response of plant spring phenology to climate warming and the effects of precipitation and soil factors on such variation. This understanding is beneficial for region-specific phenology predictions in husbandry communities. In this study, we analyzed the spatial pattern of the correlation coefficient between the start date of the plant growth season (SOS) and the average winter-spring air temperature (WST) of Inner Mongolia grassland from 2003 to 2019. Subsequently, we analyzed the importance of 13 precipitation and soil factors for the correlation between SOS and average WST using a random forest model and analyzed the interactive effect of the important factors on the SOS using linear mixing models (LMMs). Based on these, we established SOS models using data from pastoral areas within different types of grassland. The percentage of areas with a negative correlation between SOS and average WST in meadow and typical grasslands was higher than that in desert grasslands. Results from the random forest model highlighted the significance of snow cover days (SCD), soil organic carbon (SOC), and soil nitrogen content (SNC) as influential factors affecting the correlation between SOS and average WST. Meadow grasslands exhibited significantly higher levels of SCD, SOC, and SNC compared to typical and desert grasslands. The LMMs indicated that the interaction of grassland type and the average WST and SCD can effectively explain the variation in SOS. The multiple linear models that incorporated both average WST and SCD proved to be better than models utilizing WST or SCD alone in predicting SOS. These findings indicate that the spatial patterns of precipitation and soil factors are closely associated with the spatial variation in the response of SOS to climate warming in Inner Mongolia grassland. Moreover, the average WST and SCD, when considered jointly, can be used to predict plant spring phenology in husbandry communities.

Drier August and colder September slow down the delaying trend of leaf senescence in herbaceous plants on the Qinghai-Tibetan Plateau

Plant phenological shifts on the Qinghai-Tibetan Plateau (QTP) have gained considerable attention over the last few decades. However, temporal changes in plant autumn phenology and the main driving factors remain uncertain. Most previous studies used satellite-derived phenological transition dates and climatic statistics during the preseason, which have relatively large uncertainties and may mask some important climate change characteristics at the intra-annual scale, thus affecting exploration of the underlying phenological change causes. This study collected 1685 phenological records at 27 ground stations on the QTP during 1983-2017. Temporal change trends and break points in leaf senescence date (LSD) of 23 herbaceous species were assessed using least squares regression, a meta-analysis procedure, and the Pettitt test. The main drivers and causes were investigated through correlation analysis and contribution calculation based on LSD observations and monthly climatic data. Results showed that, LSD of QTP herbaceous plants was significantly delayed at a rate of 4.45 days/decade during 1983-2017. Break points were concentrated during 1999-2003, with an overall mean in 2001. After 2001, the delay trend in LSD decreased, falling from 5.26 days/decade to 2.54 days/decade. Air temperature and precipitation were the most important climatic factors that showed closer and more extensive correlations with LSD and greater contributions to the inter-annual variations in LSD. August and September were the most critical period during which climatic factors had higher contributions to the LSD shifts. However, August was drier, with precipitation significantly decreasing and temperature increasing, and September was colder after 2001. Therefore, the declining trend in LSD may be attributed to the drier August and colder September. This study has not only provided reliable field evidence on temporal changes in autumn phenology on the QTP, but has also provided valuable insights into autumn phenological modelling and regional carbon cycling in alpine regions.

Detection and attribution of the start of the growing season changes in the Northern Hemisphere

Global climate change has led to significant changes in land surface phenology. At present, research on the factors influencing the start of the growing season (SOS) mainly focuses on single factor effects, such as temperature and precipitation, ignoring the combined action of multiple factors. The impact of multiple factors on the spatial and temporal patterns of the SOS in the Northern Hemisphere is not clear, and it is necessary to combine multiple factors to quantify the degrees of influence of different factors on the SOS. Based on the GIMMS3g NDVI dataset, CRU climate data and other factor data, we used geographic detector model, random forest regression model, multiple linear regression, partial correlation analysis and Sen + Mann-Kendall trend analysis to explore the variation of the SOS in the Northern Hemisphere to reveal the main driving factors and impact threshold of 17 influencing factors on the SOS. The results showed that (1) during the past 34 years (1982-2015), the SOS in Europe and Asia mainly showed an advancing trend, whereas the SOS in North America mainly showed a delaying trend. (2) The SOS was mainly controlled by frost frequency, temperature and humidity. Increasing frost frequency inhibited the advancement of the SOS, and increasing temperature and humidity promoted the advancement of the SOS. (3) There were thresholds for the influences of the driving factors on the SOS. Outside the threshold ranges, the response mechanism of the SOS to driving factors changed. The results are important for understanding the response of the SOS to global climate change.

Warming-induced vapor pressure deficit suppression of vegetation growth diminished in northern peatlands

Recent studies have reported worldwide vegetation suppression in response to increasing atmospheric vapor pressure deficit (VPD). Here, we integrate multisource datasets to show that increasing VPD caused by warming alone does not suppress vegetation growth in northern peatlands. A site-level manipulation experiment and a multiple-site synthesis find a neutral impact of rising VPD on vegetation growth; regional analysis manifests a strong declining gradient of VPD suppression impacts from sparsely distributed peatland to densely distributed peatland. The major mechanism adopted by plants in response to rising VPD is the "open" water-use strategy, where stomatal regulation is relaxed to maximize carbon uptake. These unique surface characteristics evolve in the wet soil‒air environment in the northern peatlands. The neutral VPD impacts observed in northern peatlands contrast with the vegetation suppression reported in global nonpeatland areas under rising VPD caused by concurrent warming and decreasing relative humidity, suggesting model improvement for representing VPD impacts in northern peatlands remains necessary.

Accelerating effects of growing-season warming on tree seasonal activities are progressively disappearing

The phenological changes induced by climate warming have profound effects on water, energy, and carbon cycling in forest ecosystems. In addition to pre-season warming, growing-season warming may drive tree phenology by altering photosynthetic carbon uptake. It has been reported that the effect of pre-season warming on tree phenology is decreasing. However, temporal change in the effect of growing-season warming on tree phenology is not yet clear. Combining long-term ground observations and remote-sensing data, here we show that spring and autumn phenology were advanced by growing-season warming, while the accelerating effects of growing-season warming on tree phenology were progressively disappearing, manifesting as phenological events converted from being advanced to being delayed, in the temperate deciduous broadleaved forests across the Northern Hemisphere between 1983 and 2014. We further observed that the effect of growing-season warming on photosynthetic productivity showed a synchronized decline over the same period. The responses of phenology and photosynthetic productivity had a strong linear relationship with each other, and both showed significant negative correlations with the elevated temperature and vapor pressure deficit during the growing season. These findings indicate that warming-induced water stress may drive the observed decline in the responses of tree phenology to growing-season warming by decelerating photosynthetic productivity. Our results not only demonstrate a close link between photosynthetic carbon uptake and tree seasonal activities but also provide a physiological perspective of the nonlinear phenological responses to climate warming.

Non-symmetric responses of leaf onset date to natural warming and cooling in northern ecosystems

The northern hemisphere has experienced regional cooling, especially during the global warming hiatus (1998-2012) due to ocean energy redistribution. However, the lack of studies about the natural cooling effects hampers our understanding of vegetation responses to climate change. Using 15,125 ground phenological time series at 3,620 sites since the 1950s and 31-year satellite greenness observations (1982-2012) covering the warming hiatus period, we show a stronger response of leaf onset date (LOD) to natural cooling than to warming, i.e. the delay of LOD caused by 1°C cooling is larger than the advance of LOD with 1°C warming. This might be because cooling leads to larger chilling accumulation and heating requirements for leaf onset, but this non-symmetric LOD response is partially offset by warming-related drying. Moreover, spring greening magnitude, in terms of satellite-based greenness and productivity, is more sensitive to LOD changes in the warming area than in the cooling. These results highlight the importance of considering non-symmetric responses of spring greening to warming and cooling when predicting vegetation-climate feedbacks.

Temporal and spatial analysis of vegetation cover change in the Yellow River Delta based on Landsat and MODIS time series data

Based on the Landsat normalized difference vegetation index (NDVI) and the NDVI product of MODIS, this study synthesized two kinds of time-series images. The features were selected according to the characteristics of the time series, and the random forest algorithm was used for classification. Based on the classification results and GIS spatial analysis, the temporal and spatial changes in vegetation cover in the Yellow River Delta from 2000 to 2020 were studied. The results showed that from 2000 to 2020, the vegetation first increased and then decreased, and the dynamic degree of land cover change was generally low. The monthly average minimum NDVI values during the vegetation growth period mostly occurred before 2010, and the maximum values occurred after 2010. From the spatial perspective, the average vegetation area of the Yellow River Delta accounted for 31.54% of the total study area; specifically, the spatial pattern of vegetation distribution was relatively fixed, and the fixed vegetation area accounted for 63.90% of the total vegetation area. The spatial distribution had significant differences, and the vegetation was distributed radially from the center of the Yellow River to the periphery, with significant fragmentation found outside the watershed. The Yellow River had a strong interference with vegetation growth, and the stable vegetation distribution areas were concentrated near the Yellow River. The correlation coefficient between vegetation distribution and the location of the Yellow River was - 0.9964.

Vegetation photosynthetic phenology dataset in northern terrestrial ecosystems

Vegetation phenology can profoundly modulate the climate-biosphere interactions and thus plays a crucial role in regulating the terrestrial carbon cycle and the climate. However, most previous phenology studies rely on traditional vegetation indices, which are inadequate to characterize the seasonal activity of photosynthesis. Here, we generated an annual vegetation photosynthetic phenology dataset with a spatial resolution of 0.05 degrees from 2001 to 2020, using the latest gross primary productivity product based on solar-induced chlorophyll fluorescence (GOSIF-GPP). We combined smoothing splines with multiple change-point detection to retrieve the phenology metrics: start of the growing season (SOS), end of the growing season (EOS), and length of growing season (LOS) for terrestrial ecosystems above 30° N latitude (Northern Biomes). Our phenology product can be used to validate and develop phenology or carbon cycle models and monitor the climate change impacts on terrestrial ecosystems.

Advances in spring leaf phenology are mainly triggered by elevated temperature along the rural-urban gradient in Beijing, China

Urbanization-induced phenological changes have received considerable attention owing to their implications for determining urban ecosystem productivity and predicting the response of plants and ecosystem carbon cycles to future climate change. However, inconsistent rural-urban gradients in plant phenology remain, and phenological drivers other than temperature are poorly understood. In this study, we simultaneously observed the micro-climate and spring leaf phenology of seven woody plant species at 13 parks along a rural-urban gradient in Beijing, China. The minimum (T_min) and mean (T_mean) air temperature and the minimum (VPD_min) and mean (VPD_mean) vapor pressure deficit increased significantly along the rural-urban gradient, but the maximum air temperature (T_max) and maximum vapor pressure deficit (VPD_max) did not. All observed leaf phenological phases for the seven species were significantly advanced along the rural-urban gradient by 0.20 to 1.02 days/km. Advances in the occurrence of leaf phenological events were significantly correlated with increases in T_mean (accounting for 57-59% variation), T_min (21-26%), VPD_min (12-16%), and VPD_mean (3-5%), but not with changes in T_max or VPD_max. Advances in spring leaf phenology along the rural-urban gradient differed between non-native species and native species and between shrubs and trees. The reason may be mainly that the sensitivities of spring leaf phenology to micro-climate differ with species origin and growth form. This study highlights that urbanization-induced increases in T_mean and T_min are the major contributors to advances in spring leaf phenology along the rural-urban gradient, exerting less influence on native species than on non-native species.

Increasing temperature regulates the advance of peak photosynthesis timing in the boreal ecosystem

The shift in vegetation phenology is an essential indicator of global climate change. Numerous researches based on reflectance-based vegetation index data have explored the changes in the start (SOS) and end (EOS) of vegetation life events at long time scales, while a huge discrepancy existed between the phenological metrics of vegetation structure and function. The peak photosynthesis timing (PPT), which is crucial in regulating terrestrial ecosystem carbon balance, has not received much attention. Using two global reconstructed solar-induced chlorophyll fluorescence data (CSIF and GOSIF) directly associated with vegetation photosynthesis, the spatio-temporal dynamics in PPT as well as the key environmental controls across the boreal ecosystem during 2001-2019 were systematically explored. Multi-year mean pattern showed that PPT mainly appeared in the first half of July. Compared to the northern Eurasia, later PPT appeared in the northern North America continent for about 4-5 days. Meanwhile, spatial trend in PPT exhibited an advanced trend during the last two decades. Especially, shrubland and grassland were obvious among all biomes. Spatial partial correlation analysis revealed that preseason temperature was the dominant environmental driver of PPT trends, occupying 81.32% and 78.04% of the total pixels of PPT_CSIF and PPT_GOSIF, respectively. Attribution analysis by ridge regression again emphasized the largest contribution of temperature to PPT dynamics in the boreal ecosystem by 52.22% (PPT_CSIF) and 46.59% (PPT_GOSIF), followed by radiation (PPT_CSIF: 24.44%; PPT_GOSIF: 28.66%) and precipitation (PPT_CSIF: 23.34%; PPT_GOSIF: 24.75%). These results have significant implications for deepening our understanding between vegetation photosynthetic phenology and carbon cycling with respect to future climate change in the boreal ecosystem.

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.

Modelling Fagus sylvatica stem growth along a wide thermal gradient in Italy by incorporating dendroclimatic classification and land surface phenology metrics

Calibrating land surface phenology (LSP) with tree rings is important to model spatio-temporal variations in forest productivity. We used MODIS (resolution: 250 m) NDVI, WDRVI and EVI series 2000-2014 to derive LSP metrics quantifying phenophase timing and canopy photosynthetic rates of 26 European beech forests covering a large thermal gradient (5-16 °C) in Italy. Average phenophase timing changed greatly with site temperature (e.g. growing season 70 days longer at low- than high-elevation); average VI values were affected by precipitation. An annual temperature about 12 °C (c. 1100 m asl) represented a bioclimatic threshold dividing warm from cold beech forests, distinguished by different phenology-BAI (basal area increment) relationships and LSP trends. Cold forests showed decreasing VI values (browning) and delayed phenophases and had negative BAI slopes. Warmer forests tended to increase VI (greening), and positive BAI slopes. NDVI peak, commonly used in global trend assessments, changed with elevation in agreement with changes in wood production. A cross-validation modelling approach demonstrated the ability of LSP to predict average BAI and its interannual variability. Merging sites into bioclimatic groups improved models by amplifying the signal in growth or LSP. NDVI had highest performances when informing on BAI trends; WDRVI and EVI were mostly selected for modelling mean and interannual BAI. WDRVI association with tree rings, tested in this study for the first time, showed that this VI is highly promising for studying forest dynamics. MODIS LSP can quantify forest functioning changes across landscapes and model interannual spatial variations and trends in productivity dynamics under climate change.

Continued spring phenological advance under global warming hiatus over the Pan-Third Pole

The global surface temperature has witnessed a warming hiatus in the first decade of this century, but how this slowing down of warming will impact spring phenology over Pan-Third Pole remains unclear. Here, we combined multiple satellite-derived vegetation indices with eddy covariance datasets to evaluate the spatiotemporal changes in spring phenological changes over the Pan-Third Pole. We found that the spring phenology over Pan-Third Pole continues to advance at the rate of 4.8 days decade^-1 during the warming hiatus period, which is contrasted to a non-significant change over the northern hemisphere. Such a significant and continued advance in spring phenology was mainly attributed to an increase in preseason minimum temperature and water availability. Moreover, there is an overall increasing importance of precipitation on changes in spring phenology during the last four decades. We further demonstrated that this increasingly negative correlation was also found across more than two-thirds of the dryland region, tentatively suggesting that spring phenological changes might shift from temperature to precipitation-controlled over the Pan-Third Pole in a warmer world.

Climate Controls on the Spatial Variability of Vegetation Greenup Rate across Ecosystems in Northern Hemisphere

Variations in individual phenological events in response to global change have received considerable attentions. However, the development of phenological stages is relatively neglected, especially based on in situ observation data. In this study, the rate of vegetation greenup (Vgreenup) across the Northern Hemisphere was examined for different plant functional types (PFTs) by using eddy covariance flux data from 40 sites (417 site-years). Then, the controls of climatic variables on the spatial distribution of Vgreenup across PFTs were further investigated. The mean Vgreenup was 0.22 ± 0.11 g C m^-2 day^-2 across all sites, with the largest and lowest values observed in cropland and evergreen needle-leaf forest, respectively. A strong latitude dependence by Vgreenup was observed in both Europe and North America. The spatial variations of Vgreenup were jointly regulated by the duration of greenup (Dgreenup) and the amplitude of greenup (Agreenup). However, the predominant factor was Dgreenup in Europe, which changed to Agreenup in North America. Spring climatic factors exerted significant influences on the spatial distribution of Vgreenup across PFTs. Specifically, increasing temperature tended to shorten Dgreenup and promote Agreenup simultaneously, resulting in an acceleration of Vgreenup. Dryness had a depression effect on Vgreenup for the whole study area, as exhibited by a lower Vgreenup with increasing vapor pressure deficit or decreasing soil moisture. However, Vgreenup in North America was only significantly and positively correlated with temperature. Without the limitation of other climatic factors, the temperature sensitivity of Vgreenup was higher in North America (0.021 g C m^-2 day^-2 °C^-1) than in Europe (0.015 g C m^-2 day^-2 °C^-1). This study provides new cognitions for Vgreenup dynamics from in situ observations in complement to satellite observations, which can improve our understanding of terrestrial carbon cycles.

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.

Phenological Shifts of the Deciduous Forests and Their Responses to Climate Variations in North America

Forests play a vital role in sequestering carbon dioxide from the atmosphere. Vegetation phenology is sensitive to climate changes and natural environments. Exploring the patterns in phenological events of the forests can provide useful insights for understanding the dynamics of vegetation growth and their responses to climate variations. Deciduous forest in North America is an important part of global forests. Here we apply time-series remote sensing imagery to map the critical dates of vegetation phenological events, including the start of season (SOS), end of season (EOS), and growth length (GL) of the deciduous forests in North America during the past two decades. The findings show that the SOS and EOS present considerable spatial and temporal variations. Earlier SOS, delayed EOS, and therefore extended GL are detected in a large part of the study area from temporal trend analysis over the years, though the magnitude of the trend varies at different locations. The phenological events are found to correlate to the environmental factors and the impact on the vegetation phenology from the factors is location-dependent. The findings confirm that the phenology of the deciduous forests in North America is updated such as advanced SOS and delayed EOS in the last two decades and the climate variations are likely among the driving forces for the updates. Considering that previous studies warn that shifts in vegetation phenology could reverse the role of forests as net emitters or net sinks, we suggest that forest management should be strengthened to forests that experience significant changes in the phenological events.

Impact of Snowpack on the Land Surface Phenology in the Tianshan Mountains, Central Asia

The accumulation and ablation processes of seasonal snow significantly affect the land surface phenology in a mountainous ecosystem. However, the ability of snow to regulate the alpine land surface phenology in the arid regions is not well described in the context of climate change. The impact of snowpack changes on land surface phenology and its driving factors were investigated in the Tianshan Mountains using the land surface phenology metrics derived from satellited products and a snow dataset from downscaled regional climate model simulations covering the period from 1983 to 2015. The results demonstrated that the annual mean start of growing season (SOS) and length of growing season (LOS) experienced a significant (p < 0.05) decrease and increase with a rate of −2.45 days/decade and 2.98 days/decade, respectively. The significantly advanced SOS and increased LOS were mainly seen in the Western Tianshan Mountains and Ili Valley regions with elevations from 2500 to 3500 m a.s.l and below 3000 m a.s.l, respectively. During the early spring, the significant decline in snow cover fraction (SCF) could advance the SOS. In contrast, snowmelt amount and annual maximum snow water equivalent (SWE) have an almost equally substantial positive correlation with annual maximum vegetation greenness. In particular, the SOS of grassland was the most sensitive to variations of snow cover fraction during early spring than that of other vegetation types, and their strong relationship was mainly located at elevations from 1500 to 2500 m a.s.l. Its greenness was significantly controlled by the annual maximum snow water equivalent in all elevation bands. Both decreased SCF and increased temperature in the early spring caused a significant advance of the SOS, consequently prolonging the LOS. Meanwhile, more SWE and snowmelt amount could significantly promote vegetation greenness by regulating the soil moisture. The results can improve the understanding of the snow ecosystem services in the alpine regions under climate change.

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.

Understanding the Long-Term Vegetation Dynamics of North Korea and Their Impact on the Thermal Environment

In response to widespread deforestation, North Korea has restored forests through national policy over the past 10 years. Here, the entire process of forest degradation and restoration was evaluated through satellite-based vegetation monitoring, and its effects were also investigated. The vegetation dynamics of North Korea were characterized from 1986 to 2021 using the Landsat satellite 5–7, after which we evaluated the effect of vegetation shifts through changes in surface temperature since the 2000s. Vegetation greenness decreased significantly from the 1980s to the 2000s but increased in recent decades due to forest restoration. During the deforestation period, vegetation in all areas of North Korea tended to decrease, which was particularly noticeable in the provinces of Pyongannam-do and Hamgyongnam-do. During the forest restoration period, increases in vegetation greenness were evident in most regions except for some high-mountainous and developing regions, and the most prominent increase was seen in Pyongyang and Pyongannam-do. According to satellite-based analyses, the land surface temperature exhibited a clear upward trend (average slope = 0.13). However, large regional differences were identified when the analysis was shortened to encompass only the last 10 years. Particularly, the correlation between the area where vegetation improved and the area where the surface temperature decreased was high (−0.32). Moreover, the observed atmospheric temperature increased due to global warming, but only the surface temperature exhibited a decreasing trend, which could be understood by the effect of vegetation restoration. Our results suggest that forest restoration can affect various sectors beyond the thermal environment due to its role as an enhancer of ecosystem services.

Warming-induced increase in carbon uptake is linked to earlier spring phenology in temperate and boreal forests

Under global warming, advances in spring phenology due to rising temperatures have been widely reported. However, the physiological mechanisms underlying the advancement in spring phenology still remain poorly understood. Here, we investigated the effect of temperature during the previous growing season on spring phenology of current year based on the start of season extracted from multiple long-term and large-scale phenological datasets between 1951 and 2018. Our findings indicate that warmer temperatures during previous growing season are linked to earlier spring phenology of current year in temperate and boreal forests. Correspondingly, we observed an earlier spring phenology with the increase in photosynthesis of the previous growing season. These findings suggest that the observed warming-induced earlier spring phenology is driven by increased photosynthetic carbon assimilation in the previous growing season. Therefore, the vital role of warming-induced changes in carbon assimilation should be considered to accurately project spring phenology and carbon cycling in forest ecosystems under future climate warming.

The mechanisms underlying plant phenological shifts are debated. Here, based on phenological observations and ecosystem flux and climate data, Gu and colleagues provide evidence that warming-enhanced photosynthesis in a growing season contributes to earlier spring phenology in the following year in temperate and boreal forests.

Distribution and Attribution of Earlier Start of the Growing Season over the Northern Hemisphere from 2001–2018

The start of the growing season (SOS) is a vital ecological indicator for climate change and the terrestrial ecosystem. Previous studies have reported that the SOS over the Northern Hemisphere (NH) has experienced remarkable changes in the past few decades. However, because of the different spatial and temporal coverages of existing SOS studies, a coherent and robust account for SOS changes in the NH has been lacking. Using satellite-retrieved vegetation-phenology datasets, ground observations, and several auxiliary datasets, this study evaluated the performance of the latest MODIS vegetation-dynamics dataset (MCD12Q2-C6) and explored the distribution and attribution of the SOS to climate change over the NH for the period 2001–2018. The validation results using the Chinese Ecosystem Research Network (CERN) and Lilac-leafing observations (Lilac) displayed that the MCD12Q2-C6 has a good performance in SOS monitoring over the NH mid-latitudes. Meanwhile, evidence from MCD12Q2-C6 pointed out that the SOS was advanced by 2.08 days on average over the NH during 2001–2018, especially for Europe, China, and Alaska, United States. In addition, detailed-sensitivity analysis showed that the increased surface air temperature (Ts) (−1.21 ± 0.34 days °C−1) and reduced snow-cover fraction (Sc) (0.62 ± 0.29 days%−1) were the key driving factors of the observed SOS changes over the NH during 2001–2018. Compared with Ts and Sc, the role of total precipitation (Pt) was minor in dominating the spring vegetation-phenology changes at the same period. The findings of this study contribute to our understanding of the responses of SOS to the competing changes of Ts, Pt, and Sc over the NH.

Daytime and nighttime warming has no opposite effects on vegetation phenology and productivity in the northern hemisphere

Over the past 50 years, global land surface air temperature has been rising at a much higher rate at night than during the day. Understanding plant responses to the asymmetric daytime and nighttime warming in the context of climate change has been a hot topic in global change biology and global ecology. It has been debatable whether the asymmetric warming has opposite effects on vegetation activity (e.g., phenology, productivity). Here we settle the debate by scrutinizing the underpinnings of different statistical methods and revealing how the misuse or improper use of these methods could mischaracterize the effects of asymmetric warming with in situ and satellite observations. The use of the ordinary least square (OLS) methods including both daytime (T_max) and nighttime (T_min) temperature in the multiple regression models could overlook the multicollinearity problem and yield the misinterpretations that T_max and T_min had opposite effects on spring phenology, autumn phenology, gross primary production (GPP), and normalized difference vegetation index (NDVI). However, when the OLS methods were applied with T_max and T_min included in separate models or alternatively the ridge regression (RR) method with properly selected ridge parameter was used, the effects of T_max and T_min on vegetation activity were generally in the same direction. The use of the RR method with improperly selected ridge parameter could also mischaracterize the effects of asymmetric warming. Our findings show that daytime and nighttime warming has no opposite effects on vegetation phenology and productivity in the northern hemisphere, and properly dealing with the multicollinearity problem is critical for understanding the effects of asymmetric warming on vegetation activity.

Heatwaves Significantly Slow the Vegetation Growth Rate on the Tibetan Plateau

In recent years, heatwaves have been reported frequently by literature and the media on the Tibetan Plateau. However, it is unclear how alpine vegetation responds to the heatwaves on the Tibetan Plateau. This study aimed to identify the heatwaves using long-term meteorological data and examine the impact of heatwaves on vegetation growth rate with remote sensing data. The results indicated that heatwaves frequently occur in June, July, and August on the Tibetan Plateau. The average frequency of heatwaves had no statistically significant trends from 2000 to 2020 for the entire Tibetan Plateau. On a monthly scale, the average frequency of heatwaves increased significantly (p < 0.1) in August, while no significant trends were in June and July. The intensity of heatwaves indicated a negative correlation with the vegetation growth rate anomaly (ΔVGR) calculated from the normalized difference vegetation index (NDVI) (r = −0.74, p < 0.05) and the enhanced vegetation index (EVI) (r = −0.61, p < 0.1) on the Tibetan Plateau, respectively. Both NDVI and EVI consistently demonstrate that the heatwaves slow the vegetation growth rate. This study outlines the importance of heatwaves to vegetation growth to enrich our understanding of alpine vegetation response to increasing extreme weather events under the background of climate change.

Arctic amplification modulated by Atlantic Multidecadal Oscillation and greenhouse forcing on multidecadal to century scales

Enhanced warming in the Arctic (Arctic amplification, AA) in the last decades has been linked to several factors including sea ice and the Atlantic Multidecadal Oscillation (AMO). However, how these factors contributed to AA variations in a long-term perspective remains unclear. By reconstructing a millennial AA index combining climate model simulations with recently available proxy data, this work determines the important influences of the AMO and anthropogenic greenhouse gas forcing on AA variations in the last millennium, leading to identification of a significant downward trend of AA on top of a sustained strong AMO modulation at the multidecadal scales. The decreased AA during the industrial era was strongly associated with the anthropogenic forcing, proving the emerging role of the forcing in reducing the AA strength.

Reconstructed Arctic amplification shows a significant downward trend over the past millennium which can to a large part be explained by the strength of the Atlantic Multidecadal Oscillation and recent anthropogenic greenhouse gas forcing.

Inter-Annual Variations of Precipitation Modulate the Dry Spell Length

Dry spell length (DSL), consecutive non-rainy days between two precipitation events, play an important role in regulating soil moisture dynamics, terrestrial energy exchange as well as vegetation growth. According to the Clausius-Clapeyron (C-C) relationship, global warming can result in prolonged DSL. However, usually the amount of precipitation and its characteristics coincidentally varied with the changes of DSL under global warming, it remains unclear how the inter-annual variation of precipitation interacts with the evolution of dry spells. In this study, the global long-term in-situ observation data set of daily precipitation during 1976-2019 was used to examine the spatiotemporal trends of growing season DSL and precipitation. Our results showed that the global mean growing season DSL significantly increased by 0.3 days decade-1 during 1976-1998 while no significant trend of that was observed during 1999-2019. In contrast, the growing season precipitation (Prec_GS) showed no significant trend in 1976-1998 whereas significant increase trend of that was observed in 1999-2019. To explore the impacts of precipitation on the evolution of dry spells, we examined the relationship between the growing season DSL and Prec_GS. We found that prevalent negative relationship was observed between growing season DSL and Prec_GS in 88% and 86% stations during the period of 1976-1998 and 1999-2019, respectively. Spatially, the mean annual Prec_GS and DSL showed significantly negative relationship, that is, the stations with more precipitation showed shorter DSL in growing season, and vice versa. The changes of mean annual Prec_GS explained 81% spatial variation of growing season DSL. Moreover, during the period of 1999-2019 significant increase of precipitation frequency and decrease of dry day frequency were also observed in addition to the increase of Prec_GS in this period. The decreased dry day frequency further resulted in the decrease of growing season DSL. By excluded the impacts of precipitation, the DSL/Prec_GS ratio showed significant decreasing trend during 1999-2019. Our study suggested that the spatiotemporal variations of DSL were modulated by the variation of precipitation. The impacts of precipitation changes on ecosystem by altering the dry spell evolution should be considered in modeling the terrestrial carbon and hydrological cycling in response to climate changes.

An earlier start of the thermal growing season enhances tree growth in cold humid areas but not in dry areas

Climatic warming alters the onset, duration and cessation of the vegetative season. While previous studies have shown a tight link between thermal conditions and leaf phenology, less is known about the impacts of phenological changes on tree growth. Here, we assessed the relationships between the start of the thermal growing season and tree growth across the extratropical Northern Hemisphere using 3,451 tree-ring chronologies and daily climatic data for 1948-2014. An earlier start of the thermal growing season promoted growth in regions with high ratios of precipitation to temperature but limited growth in cold-dry regions. Path analyses indicated that an earlier start of the thermal growing season enhanced growth primarily by alleviating thermal limitations on wood formation in boreal forests and by lengthening the period of growth in temperate and Mediterranean forests. Semi-arid and dry subalpine forests, however, did not benefit from an earlier onset of growth and a longer growing season, presumably due to associated water loss and/or more frequent early spring frosts. These emergent patterns of how climatic impacts on wood phenology affect tree growth at regional to hemispheric scales hint at how future phenological changes may affect the carbon sequestration capacity of extratropical forest ecosystems.

A Decrease in the Daily Maximum Temperature during Global Warming Hiatus Causes a Delay in Spring Phenology in the China–DPRK–Russia Cross-Border Area

Spring phenology is the most sensitive indicator of climate change and exploring its response to climate change has important implications for ecosystem processes in the study area. The temperature changes before and after the global warming hiatus may affect the spatiotemporal pattern of land surface phenology. In this paper, taking the China–DPRK (Democratic People’s Republic of Korea)–Russia cross-border region as an example, based on GIMMS NDVI data, the Polyfit-Maximum method was used to extract the start date of the vegetation growing season (SOS). The variation trend of SOS and its response to climate change were analyzed in the early (1982–1998) and late (1998–2015) periods of the warming hiatus. At the regional scale, the spatial distribution of the SOS in the China–DPRK–Russia (CDR) cross-border area presents an elevation gradient, which is earlier in high-elevation areas and later in low-elevation areas. The temporal and spatial trend of SOS is mainly correlated by daytime maximum temperature (Tmax). The significant increase in Tmax in the early period promoted the advance of SOS (0.47 days/year), and the decrease in Tmax in the later period caused the delay of SOS (0.51 days/year). While the main influencing factor of the SOS changes in the region in the early and late periods was Tmax, the response of the SOS changes in China, DPRK and Russia to climate change also changed with the dramatic temperature changes during the warming hiatus. The Chinese side is increasingly responding to Tmax, while the North Korean side is becoming less responsive to climatic factors, and precipitation and radiation on the Russian side are driving the advance of the SOS.

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.

Vegetation Browning Trends in Spring and Autumn over Xinjiang, China, during the Warming Hiatus

Satellite-derived vegetation records (GIMMS3g-NDVI) report that climate warming promotes vegetation greening trends; however, the climate impacts on vegetation growth during the global warming hiatus period (1998–2012) remain unclear. In this study, we focused on the vegetation change trend in Xinjiang in spring and autumn before and during the recent warming hiatus period, and their climate-driving mechanisms, which have not been examined in previous studies. Based on satellite records, our results indicated that the summer normalized difference vegetation index (NDVI) in Xinjiang experienced a greening trend, while a browning trend existed in spring and autumn during this period. The autumn NDVI browning trend in Xinjiang was larger than that in spring; however, the spring NDVI displayed a higher correlation with climatic factors than did the autumn NDVI. During the warming hiatus, spring climatic factors were the main controlling factors of spring NDVI, and spring vapor pressure deficit (VPD) had the highest positive correlation with spring NDVI, followed by spring temperature. The larger increase in air temperature in spring than in autumn resulted in increased VPD differences in spring and autumn. In autumn, summer climatic factors (e.g., VPD, WS, RH, and precipitation) were significantly correlated with the autumn NDVI during the warming hiatus. However, the autumn temperature was weakly correlated with the autumn NDVI. Our results have significant implications for understanding the response of vegetation growth to recent and future climatic conditions.

Climate Warming-Induced Changes in Plant Phenology in the Most Important Agricultural Region of Romania

Changes in plant phenology are a direct indicator of climate change and can produce important consequences for agricultural and ecological systems. This study analyzes changes in plant phenology in the 1961–2010 period (for both the entire interval and in three successive multi-decades: 1961–1990, 1971–2000 and 1981–2010) in southern and southeastern Romania, the country’s most important agricultural region. The analysis is based on mean monthly air temperature values collected from 24 regional weather stations, which were used for extracting the length (number of days) of phenophases (growing season onset, budding–leafing, flowering, fruiting, maturing, dissemination of seeds, start of leaf loss, end of leaf loss) and of the overall climatic growing season (CGS, which includes all phenophases), by means of the histophenogram method. Using a number of reliable statistical tools (Mann–Kendall test, Sen’s slope estimator and the regression method) for exploring annual trends and net (total) changes in the length of the phenological periods, as well as for detecting the climate—growing season statistical relationships, our results revealed complex phenology changes and a strong response in phenological dynamics to climate warming. Essentially, a lengthening of all phenophases (maximal in the maturing period, in terms of statistical significance and magnitude of trends—on average 0.48 days/yr/24 days net change in the 1961–2010 period, or even 0.94 days/yr/28 days net change in the 1971–2000 sub-period) was noticed, except for the fruiting and dissemination phenophases, which were dominated by negative trends in the number of days, but partially statistically significant (at a confidence level threshold of at least 90%). The CGS exhibited overall increasing trends, with an average of 0.21 days/yr/11 days net change in the 1961–2010 interval, and even of 0.90 days/yr/27 days net change in the 1981–2010 sub-period. Moreover, based on the slope values obtained upon application of a linear regression to mean temperature and CGS, we discovered that a 1 °C increase in climate warming accounted for a remarkable lengthening of the CGS, on average of 14 days between 1961 and 2010, and of 16 days between 1981 and 2010. Our results can help improve the adaptation of agroecological systems to future climate change.

Detecting the Turning Points of Grassland Autumn Phenology on the Qinghai-Tibetan Plateau: Spatial Heterogeneity and Controls

Autumn phenology, commonly represented by the end of season (EOS), is considered to be the most sensitive and crucial productivity indicator of alpine and cold grassland in the Qinghai-Tibetan Plateau. Previous studies typically assumed that the rates of EOS changes remain unchanged over long time periods. However, pixel-scale analysis indicates the existence of turning points and differing EOS change rates before and after these points. The spatial heterogeneity and controls of these turning points remain unclear. In this study, the EOS turning point changes are extracted and their controls are explored by integrating long time-series remote sensing images and piecewise regression methods. The results indicate that the EOS changed over time with a delay rate of 0.08 days/year during 1982–2015. The rates of change are not consistent over different time periods, which clearly highlights the existence of turning points. The results show that temperature contributed most strongly to the EOS changes, followed by precipitation and insolation. Furthermore, the turning points of climate, human activities (e.g., grazing, economic development), and their intersections are found to jointly control the EOS turning points. This study is the first quantitative investigation into the spatial heterogeneity and controls of the EOS turning points on the Qinghai-Tibetan Plateau, and provides important insight into the growth mechanism of alpine and cold grassland.

Exploring the Applicability and Scaling Effects of Satellite-Observed Spring and Autumn Phenology in Complex Terrain Regions Using Four Different Spatial Resolution Products

The information on land surface phenology (LSP) was extracted from remote sensing data in many studies. However, few studies have evaluated the impacts of satellite products with different spatial resolutions on LSP extraction over regions with a heterogeneous topography. To bridge this knowledge gap, this study took the Loess Plateau as an example region and employed four types of satellite data with different spatial resolutions (250, 500, and 1000 m MODIS NDVI during the period 2001–2020 and ~10 km GIMMS3g during the period 1982–2015) to investigate the LSP changes that took place. We used the correlation coefficient (r) and root mean square error (RMSE) to evaluate the performances of various satellite products and further analyzed the applicability of the four satellite products. Our results showed that the MODIS-based start of the growing season (SOS) and end of the growing season (EOS) were highly correlated with the ground-observed data with r values of 0.82 and 0.79, respectively (p < 0.01), while the GIMMS3g-based phenology signal performed badly (r < 0.50 and p > 0.05). Spatially, the LSP that was derived from the MODIS products produced more reasonable spatial distributions. The inter-annual averaged MODIS SOS and EOS presented overall advanced and delayed trends during the period 2001–2020, respectively. More than two-thirds of the SOS advances and EOS delays occurred in grasslands, which determined the overall phenological changes across the entire Loess Plateau. However, both inter-annual trends of SOS and EOS derived from the GIMMS3g data were opposite to those seen in the MODIS results. There were no significant differences among the three MODIS datasets (250, 500, and 1000 m) with regard to a bias lower than 2 days, RMSE lower than 1 day, and correlation coefficient greater than 0.95 (p < 0.01). Furthermore, it was found that the phenology that was derived from the data with a 1000 m spatial resolution in the heterogeneous topography regions was feasible. Yet, in forest ecosystems and areas with an accumulated temperature ≥10 °C, the differences in phenological phase between the MODIS products could be amplified.

Specific Drivers and Responses to Land Surface Phenology of Different Vegetation Types in the Qinling Mountains, Central China

Land surface phenology (LSP), as a precise bio-indicator that responds to climate change, has received much attention in fields concerned with climate change and ecology. Yet, the dynamics of LSP changes in the Qinling Mountains (QMs)—A transition zone between warm-temperate and north subtropical climates with complex vegetation structure—under significant climatic environmental evolution are unclear. Here, we analyzed the spatiotemporal dynamics of LSP for different vegetation types in the QMs from 2001 to 2019 and quantified the degree of influence of meteorological factors (temperature, precipitation, and shortwave radiation), and soil (temperature and moisture), and biological factors (maximum of NDVI and middle date during the growing season) on LSP changes using random forest models. The results show that there is an advanced trend (0.15 days/year) for the start of the growing season (SOS), a delayed trend (0.24 days/year) for the end of the growing season (EOS), and an overall extended trend (0.39 days/year) for the length of the growing season (LOS) in the QMs over the past two decades. Advanced SOS and delayed EOS were the dominant patterns leading to a lengthened vegetation growing season, followed by a joint delay of SOS and EOS, and the latter was particularly common in shrub and evergreen broadleaved forests. The growth season length increased significantly in western QMs. Furthermore, we confirmed that meteorological factors are the main factors affecting the interannual variations in SOS and EOS, especially the meteorological factor of preseason mean shortwave radiation (SWP). The grass and crop are most influenced by SWP. The soil condition has, overall, a minor influence the regional LSP. This study highlighted the specificity of different vegetation growth in the QMs under warming, which should be considered in the accurate prediction of vegetation growth in the future.

Using Multi-Temporal Satellite Data to Analyse Phenological Responses of Rubber (Hevea brasiliensis) to Climatic Variations in South Sumatra, Indonesia

Land surface phenology derived from satellite data provides insights into vegetation responses to climate change. This method has overcome laborious and time-consuming manual ground observation methods. In this study, we assessed the influence of climate on phenological metrics of rubber (Hevea brasiliensis) in South Sumatra, Indonesia, between 2010 and 2019. We modelled rubber growth through the normalised difference vegetation index (NDVI), using eight-day surface reflectance images at 250 m spatial resolution, sourced from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua satellites. The asymmetric Gaussian (AG) smoothing function was applied on the model in TIMESAT to extract three phenological metrics for each growing season: start of season (SOS), end of season (EOS), and length of season (LOS). We then analysed the effect of rainfall and temperature, which revealed that fluctuations in SOS and EOS are highly related to disturbances such as extreme rainfall and elevated temperature. Additionally, we observed inter-annual variations of SOS and EOS associated with rubber tree age and clonal variability within plantations. The 10-year monthly climate data showed a significant downward and upward trend for rainfall and temperature data, respectively. Temperature was identified as a significant factor modulating rubber phenology, where an increase in temperature of 1 °C advanced SOS by ~25 days and EOS by ~14 days. These results demonstrate the capability of remote sensing observations to monitor the effects of climate change on rubber phenology. This information can be used to improve rubber management by helping to identify critical timing for implementation of agronomic interventions.

Trends in land surface phenology across the conterminous United States (1982-2016) analyzed by NEON domains

Tracking phenological change in a regionally explicit context is a key to understanding ecosystem status and change. The current study investigated long-term trends of satellite-observed land surface phenology (LSP) in the 17 National Ecological Observatory Network (NEON) domains across the conterminous United States (CONUS). Characterization of LSP trends was based on a high temporal resolution (3-d) time series of the two-band enhanced vegetation index (EVI2) derived from a long-term data record (LTDR) of the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS). We identified significant trend patterns in LSP and their seasonal climate and land use/land cover drivers for each NEON domain. Key findings include (1) the start of season (SOS) predominantly shifted later in 13 out of 17 domains (24.3% of CONUS by area) due potentially to both a lack of spring warming in the eastern United States and changes in agronomic practices over agricultural lands; (2) the end of season (EOS) became predominantly later in nine domains dominated by natural vegetation (14.1% of CONUS by area) in response to widespread warming in autumn; (3) the EOS predominantly shifted earlier in three domains (10.6% of CONUS by area) over primarily agricultural lands as potentially affected by changes in crop growth cycles; and (4) earlier shift in the SOS was mostly found in the Northwest (3.6% of CONUS by area) and was predominant only in the moist Pacific Northwest (27.7% of the domain by area) in response to more pronounced spring warming in the region. The overall patterns of SOS and EOS trends across CONUS appeared constrained by continental-scale temperature trends as characterized by a west-east dipole and the distribution of the nation's agricultural lands. In addition, seasonal trend analysis revealed that most NEON domains (15/17) became predominantly greener in part of or throughout the growing season, potentially contributed by both climate change-induced growth increase and improved agricultural productivity. The domain-wide LSP trends with their underlying drivers identified here provide important contextual information for NEON science as well as for investigations within CONUS using other distributed observatories (e.g., LTER, LTAR, FLUXNET, USA-NPN, etc.).