Search Results (167)

Drought disturbances are becoming more frequent with global warming. Accurately assessing the regulatory effect of drought on vegetation phenology is key to understanding terrestrial ecosystem response mechanisms in the context of climate change. Previous studies on cumulative and lagged effects of drought on vegetation growth have mostly focused on a single vegetation type or the overall vegetation NDVI, overlooking the possible influence of different adaptation strategies of different vegetation types and differences in drought effects on different phenological nodes. This study investigates the cumulative and lagged effects of drought on vegetation phenology across a region of East Asia from 2001 to 2020 using NDVI data and the Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the start of growing season (SOS) and end of growing season (EOS) responses to drought across four vegetation types: deciduous needleleaf forests (DNFs), deciduous broadleaf forests (DBFs), shrublands, and grasslands. Results reveal contrasting phenological responses: drought delayed SOS in grasslands through a “drought escape” strategy but advanced SOS in forests and shrublands. All vegetation types showed earlier EOS under drought stress. Cumulative drought effects were strongest on DNFs, SOS, and shrubland SOS, while lagged effects dominated DBFs and grassland SOS. Drought impacts varied with moisture conditions: they were stronger in dry regions for SOS but more pronounced in humid areas for EOS. By confirming that drought effects vary by vegetation type and phenology node, these findings enhance our understanding of vegetation adaptation strategies and ecosystem responses to climate stress. Full article

Rubber Tree (Hevea brasiliensis) phenology critically influences tropical plantation productivity and carbon cycling, yet topography and climate impacts remain unclear. By integrating multi-sensor remote sensing (2001–2020) and Google Earth Engine, this study analyzed spatiotemporal dynamics in Hainan Island, China. Results reveal that both the start (SOS occurred between early and late March: day of year, DOY 60–81) and end (EOS occurred late January to early February: DOY 392–406, counted from the previous year) of the growing season exhibit progressive delays from the southeast to northwest, yielding a 10–11 month growing season length (LOS). Significantly, LOS extended by 4.9 days per decade (p < 0.01), despite no significant trends in SOS advancement (−1.1 days per decade) or EOS delay (+3.7 days per decade). Topographic modulation was evident: the SOS was delayed by 0.27 days per 100 m elevation rise (p < 0.01), while the EOS was delayed by 0.07 days per 1° slope increase (p < 0.01). Climatically, a 100 mm precipitation increase advanced SOS/EOS by approximately 1.0 day (p < 0.05), preseasonally, a 1 °C February temperature rise advanced the SOS and EOS by 0.49 and 0.53 days, respectively, and a 100 mm January precipitation increase accelerated EOS by 2.7 days (p < 0.01). These findings advance our mechanistic understanding of rubber phenological responses to climate and topographic gradients, providing actionable insights for sustainable plantation management and tropical forest ecosystem adaptation under changing climatic conditions. Full article

Plant phenology is closely related to plant function, ecosystem services, and climate balance. Solar-induced chlorophyll fluorescence (SIF) offers new perspectives on plant phenology at regional and global scales. However, the effect of SIF products at different scales on phenology extraction is still unclear. Understanding of the mechanisms underlying phenological responses to environmental factors remains incomplete. Therefore, in this study, two phenological metrics for the Start of Growing Season (SOS) and the End of Growing Season (EOS) were extracted from the phenology of deciduous forests in the middle and high latitudes of the Northern Hemisphere, utilizing SIF products at scales of 1 km, 5 km, and 50 km, and applying the Savitzky-Golay filtering method along with the dynamic threshold method. Our results showed that the 1-km resolution SIF had a significant advantage over the 5-km and 50-km resolution SIFs in terms of consistency with the extracted phenology results from the Gross Primary Productivity (GPP) sites, with mean absolute errors (MAEs) of 4.48 and 15.49 days for SOS and EOS, respectively. For the 5-km resolution SIF, the MAEs for the same phenological metrics were 9.2 and 21.07 days. For the 50-km resolution SIF, the MAEs were 58.94 and 42.73 days. Meanwhile, this study analyzed the trends of phenology utilizing the three scales of SIF products and found a general trend of advancement. The coarser spatial resolution of the SIF data made the trend of advancement more obvious. Using SHapley Additive exPlanations (SHAP) analysis, we investigated the phenological responses to environmental factors at different scales. We found that SOS/EOS were mainly regulated by soil and air temperature, whereas the scale effect on this analysis’ results was not significant. This study has implications for optimizing the use of data, understanding ecosystem changes, predicting vegetation dynamics under global change, and developing adaptive management strategies. Full article

Understanding vegetation phenology dynamics is essential for evaluating ecosystem responses to environmental changes. While previous studies have primarily focused on the correlation between vegetation phenology and climate variables, the integrated effects of meteorological factors, topography, and greenhouse gas (GHG) have often been overlooked. This study aims to analyze the spatiotemporal variations in grassland phenology on the southern slopes of the Qilian Mountains from 2002 to 2022, investigating the combined effects of these environmental factors. Our findings reveal significant spatial heterogeneity in vegetation phenology during the study period. Specifically, the start of the growing season (SOS), length of growing season (LOS), and end of the growing season (EOS) advanced, lengthened, and delayed by 0.35, 0.55, and 0.20 days per year, respectively. Climate factors were the primary drivers of phenological changes, with annual precipitation being the main determinant of SOS and LOS, while annual minimum temperature significantly influenced EOS. Topography and GHG had indirect effects on phenology, influencing both annual precipitation and temperature. Additionally, topography affected phenology through its impact on N₂O and CO₂ emissions. This study highlights the complex interactions between climate, topography, and GHG in shaping vegetation phenology, providing new insights into the driving mechanisms behind phenological changes in semi-arid grassland ecosystems. Full article

The carbon cycle of forest ecosystems is a component of the global terrestrial ecosystem carbon cycle, and the productivity of forest ecosystems is significantly influenced by vegetation phenology. In this investigation, we simulated the spatiotemporal trends of the carbon cycle in forest ecosystems in Hangzhou between 2001 and 2020 by means of the phenology-driven InTEC model and analyzed the mechanisms of carbon cycle changes in response to phenological changes. The results of this study suggested that the gross primary productivity (GPP), the net primary production (NPP), and the net ecosystem productivity (NEP) have obvious heterogeneity in spatiotemporal distribution, and the tendency of the start of the growing season (SOS) advancement, the end of the growing season (EOS) postponement, and the length of the growing season (LOS) lengthening is significant for a GPP increase with positive effects. Both phenology and climate have direct impacts on carbon cycle changes, while climate change indirectly affects carbon cycle changes through phenology changes. Full article

Monitoring vegetation phenology is crucial for understanding how plants respond to climate change and how the latter affects the role of vegetated ecosystems in biosphere cycles. It has been reported that the growing season has been extended, leading to an increase in global terrestrial productivity, but not much attention has been given to how different climatic variables affect specific tree species’ phenology. This study focuses on the main phenological events (SOS, Start Of Season; EOS, End Of Season; and LOS, Length Of Season) of two deciduous species (Fagus sylvatica L. and Castanea sativa Mill.) and the effects of temperature and precipitation on them. The analysis concerns a 23-year period (2000–2022) of various sites across southern Europe. The dates for each phenological event are estimated based on NDVI timeseries from MODIS satellite sensor. Both species show an elongation of their growing season, with SOS occurring 2.09 and 1.63 days/decade earlier and EOS 2.97 and 3.03 days/decade later for Fagus sylvatica and Castanea sativa, respectively, with this trend appearing more intense at lower altitudes. Temperature seems to be the major driver for these changes for both species, with higher temperatures before each phenological event leading to earlier SOS and delayed EOS. The effects of precipitation are less homogenous, showing different trends between sites and species. Full article

In desertified regions, monitoring vegetation phenology and elucidating its relationship with climatic factors are of crucial significance for understanding how desertification responds to climate change. This study aimed to extract the spatial-temporal evolution of land surface phenology metrics from 2001 to 2020 using MODIS NDVI products (NASA, Greenbelt, MD, USA) and explore the potential impacts of climate change on land surface phenology through partial least squares regression analysis. The key results are as follows: Firstly, regionally the annual mean start of the growing season (SOS) ranged from day of year (DOY) 130 to 170, the annual mean end of the growing season (EOS) fell within DOY 270 to 310, and the annual mean length of the growing season (LOS) was between 120 and 180 days. Most of the desertified areas demonstrated a tendency towards an earlier SOS, a delayed EOS, and a prolonged LOS, although a small portion exhibited the opposite trends. Secondly, precipitation prior to the SOS period significantly influenced the advancement of SOS, while precipitation during the growing season had a marked impact on EOS delay. Thirdly, high temperatures in both the pre-SOS and growing seasons led to moisture deficits for vegetation growth, which was unfavorable for both SOS advancement and EOS delay. The influence of temperature on SOS and EOS was mainly manifested during the months when SOS and EOS occurred, with the minimum temperature having a more prominent effect than the average and maximum temperatures. Additionally, the wind in the pre-SOS period was found to adversely impact SOS advancement, potentially due to severe wind erosion in desertified areas during spring. The findings of this study reveal that the delayed spring phenology, precipitated by the occurrence of a warm and dry spring in semi-arid desertified areas of northern China, has the potential to heighten the risk of desertification. Full article

Exploring the phenological divergences in vegetation caused by global climate change is of great significance for gaining a deeper understanding of the carbon cycling process in natural ecosystems. However, in many existing studies, the response of the start of the growing season (SOS) and the end of the growing season (EOS) to temperature exhibited multi-scale inconsistencies. In view of this, we took 259 Chinese urban agglomerations and their rural regions as the study areas, using MODIS phenological products (MCD12Q2), land surface temperature (LST) datasets, altitude, and latitude as data, and explored the phenological divergences in vegetation with LST changes in different geographical zones through box plots, linear regression models, and Spearman’s correlation analysis. The mean SOS and EOS in urban areas were both the earliest on approximately the 100.06th day and 307.39th day, respectively, and were then gradually delayed and advanced separately along an urban–rural gradient of 0–25 km. The divergences in vegetation phenology were no longer significant in rural areas 10 km away from urban boundaries, with change amplitudes of less than 0.4 days. In high latitude (40–50° N) regions, the correlation coefficients between the SOS and EOS of various urban agglomerations and LST were −0.627 and 0.588, respectively, whereas in low latitude (18–25° N) regions, the correlation coefficients appeared to be the opposite, being 0.424 and −0.426, respectively. In mid- to high-altitude (150–400 m) areas, LST had a strong advanced effect on SOS, while in high-altitude (above 1200 m) areas, LST had a strong delayed effect on EOS, with the R² values all being above 0.7. In summary, our study has revealed that within the context of varying geographical zones, the effects of LST on phenology exhibited significant spatial heterogeneity. This may provide strong evidence for the inconsistencies in the trends of phenology observed across previous studies and more relevant constraints for improving vegetation phenology prediction models. Full article

Frequent droughts pose a severe threat to the ecological health and sustainable development of the Loess Plateau (LP). The accurate assessment of the impact of drought on vegetation is crucial for diagnosing ecological health. Traditional drought assessment methods often rely on coarse estimations based on averages of vegetation drought indices, overlooking the spatial differentiation of complex vegetation phenology. This study proposes a vegetative drought assessment method that considers vegetation phenological characteristics using MODIS EVI and LST data products. First, the start and end of the growing season timepoints were extracted from the Enhanced Vegetation Index (EVI) using Savitzky–Golay (S–G) filtering and the dynamic threshold method, determining the growing-time window for each pixel. Next, the Vegetation Health Index (VHI) series was calculated and extracted for each pixel within the growing season. The mean value of the VHI series was then used to construct the Growing Season Health Index (GSHI). Based on the GSHI, the long-term vegetation drought characteristics at LP were revealed. Finally, we integrated the Optimal Parameters-based Geographical Detector (OPGD) to identify and quantify the multiple driving forces of vegetation drought. The results showed that: (1) the spatio-temporal difference of vegetation phenology on the LP was significant, exhibiting distinct zonal characteristics; (2) the spatial distribution of growing season drought on the LP presented a “humid southeast, arid northwest” pattern, with the early 21st century being a period of high drought occurrence; (3) drought has been alleviated in large-scale natural areas, but the local drought effect under urbanization is intensifying; and (4) meteorology and topography influence vegetation drought by regulating water redistribution, while the drought effect of human activities is intensifying. Full article

The phenological characteristics of plants can reflect both their responses to environmental changes as well as an ecosystem’s sensitivity to climate change. Although there have been several phenological studies of plant species worldwide, there is minimal research on the phenology of vegetation found in extremely arid environments within the context of climate change. To address this research gap, this study investigated the effects of climate–hydrological factors, including temperature, precipitation, surface temperature, and surface humidity, on the phenological characteristics (start of the growing season [SOS] and end of the growing season [EOS]) of Populus euphratica in the Tarim Desert Oasis. Using Landsat 7/8 satellite imagery and field data, we analyzed the spatial and temporal variations in the SOS and EOS from 2004 to 2023. The availability of water, particularly changes in groundwater depth and surface water, directly played a key role in shaping the spatial distribution and temporal dynamics of P. euphratica phenology. The impact of increasing temperatures on P. euphratica phenology varied under different moisture conditions: in high-moisture environments, increased temperatures promoted earlier SOS and delayed EOS, with the opposite conditions occurring in low-moisture environments. This study highlights the profound influence of moisture conditions on P. euphratica phenology in the context of climate change, especially in extreme arid regions. To accurately predict the response of P. euphratica phenology to climate change, future ecological models should incorporate hydrological factors, particularly changes in soil moisture, in cold and dry regions. These findings provide important insights for developing effective ecological protection and management strategies. Full article

Monitoring mangrove phenology requires frequent, high-resolution remote sensing data, yet satellite imagery often suffers from coarse resolution and cloud interference. Traditional methods, such as denoising and spatiotemporal fusion, faced limitations: denoising algorithms usually enhance temporal resolution without improving spatial quality, while spatiotemporal fusion models struggle with prolonged data gaps and heavy noise. This study proposes an optimized mangrove phenology extraction approach (OMPEA), which integrates Landsat and MODIS data with a denoising algorithm (e.g., Gap Filling and Savitzky–Golay filtering, GF–SG) and a spatiotemporal fusion model (e.g., Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model, ESTARFM). The key of OMPEA is that GF–SG algorithm filled data gaps from cloud cover and satellite transit gaps, providing high-quality input to ESTARFM and improving its accuracy of NDVI imagery reconstruction in mangrove phenology extraction. By conducting experiments on the GEE platform, OMPEA generates 1-day, 30 m NDVI imagery, from which phenological parameters (i.e., the start (SoS), end (EoS), length (LoS), and peak (PoS) of the growing season) are derived using the maximum separation (MS) method. Validation in four mangrove areas along the coastal China shows that OMPEA significantly improves the potential to capture mangrove phenology in the presence of incomplete data. The OMPEA significantly increased usable data, adding 7–33 Landsat images and 318–415 MODIS images per region. The generated NDVI series exhibits strong spatiotemporal consistency with original data (R²: 0.788–0.998, RMSE: 0.007–0.253) and revealed earlier SoS and longer LoS at lower latitudes. Cross-correlation analysis showed a 2–3 month lagged effects of temperature on mangroves’ growth, with precipitation having minimal impact. The proposed OMPEA improves the possibility of capturing mangrove phenology under non-continuous and low-resolution data, providing valuable insights for large-scale and long-term mangrove conservation and management. Full article

Accurately assessing the carbon sink intensity of China’s ecosystem is crucial for achieving carbon neutrality. However, existing ecosystem process models have significant uncertainties in net ecosystem productivity (NEP) estimates due to the lack of or insufficient description of phenological regulation. Although plant developmental factors have been proven to significantly influence autumn phenology, they have not been systematically incorporated into autumn phenology models. In this study, we modified the autumn phenology model (cold-degree-day, CDD) by incorporating the growing-season gross primary productivity (GPP) and the start of growing season (SOS) and used it as a constraint to improve the CASA model for quantifying NEP across China from 2003 to 2021. Validation results showed that the CDD model incorporating developmental factors significantly improved the simulation accuracy at the end of the growing season (EOS). More importantly, compared with flux tower observations, the NEP derived from the improved CASA model based on the above phenology model showed a 15.34% reduction in root mean square error and a 74% increase in the coefficient of determination relative to the original model. During the study period, China’s multiyear average total NEP was 489.67 ± 38.27 Tg C/yr, with the highest found in evergreen broadleaf forests and the lowest detected in shrublands. Temporally, China’s NEP demonstrated an overall increasing trend with an average rate of 1.75 g C/m²/yr². However, the growth rate of NEP remained far below concurrent carbon emissions from fossil fuel combustion totally, especially for eastern China, while the northeastern regions performed relatively better. The improved regional carbon flux estimation framework proposed in this study will provide important support for developing future climate change mitigation strategies. Full article

Under global climate change, fragmented urban vegetation is more susceptible to the external environment, and changes in vegetation phenology are one of the most apparent responses. In this study, phenological camera (phenocamera) photo data, Klosterman curve fitting, and a Gu model were employed to explore the phenological characteristics of an urban forest at different levels within different species. Differences between species and groups regarding the upturn date (UD), the stabilization date (SD), the downturn date (DD), the recession date (RD), and the length of the growing season (LOS) are displayed in detail. We found that the UD of Cinnamomum camphora groups began in late April (day of year 108th), the SD appeared in early May (121st), and the DD started in early October (283rd) and ended in late October (293rd), with an average LOS of 185 days. The phenological characteristics of the Cinnamomum camphora and Bischofia polycarpa groups differed significantly. The average LOS of Bischofia polycarpa was 47 days longer than that of Cinnamomum camphora. Between Cinnamomum camphora individuals and group levels, differences in the UD and the SD were not obvious, while differences in the DD, the RD, and the LOS were large (LOS > RD > DD). The LOS of Cinnamomum camphora was longer on the individual scale (209 days), while the average LOS on the group scale was 185 days. In conclusion, our results reflect the more refined quantitative results of urban vegetation phenology and will help to elucidate urban vegetation phenological changes, which has important theoretical and practical significance for future urban forest management practices. Full article

Increased tree species diversity can promote forest production by reducing intra-specific competition and promoting an efficient unitization of resources. However, questions remain on whether and how mixed stands affect the dynamics of intra–annual xylem formation in trees, especially in subtropical forests. In this study, we randomly selected 18 trees from a monoculture of 63-year-old Masson pine (Pinus massoniana) growing in pure stands and mixed them with 39-year-old Castanopsis hystrix in Pinxiang, southern China. A total of 828 microcores were collected biweekly throughout the growing season from 2022 to 2023 to monitor the intra-annual xylem formation. Cell production started in early March and ended in late December and lasted about 281 to 284 days. Xylem phenology was similar between mixed and pure stands. During both seasons, the Masson pine in mixed stands showed higher xylem production and growth rates than those in pure stands. The Masson pine in mixed stands produced 45–51 cells in 2022 (growth rate of 0.22 cells day⁻¹) and 35–41 cells in 2023 (0.17 cells day⁻¹). Growth rate, and not growth seasons, determined the superior xylem growth in the mixed stands. Our study shows that after 39 years of management, Masson pine and C. hystrix unevenly aged mixed stands have a significant positive mixing effect on Masson pine xylem cell production, which demonstrates that monitoring intra-annual xylem growth dynamics can be an important tool to evaluate the effect of species composition and reveal the mechanisms to promote tree growth behind the mixing effect. Full article

Exploring the relationship between leaf and xylem growth and nitrogen (N) deposition on tree growth helps us better understand how N deposition affects tree growth, but relevant studies are still limited. We tested if leaf and xylem growth and their relationship were affected by N deposition across multiple stages of leaf development. We studied two dominant tree species (Castanopsis chinensis and Schima superba) in a subtropical forest in South China, monitoring their leaf and xylem growth traits under canopy N addition of 0 (CK) and 50 kg N ha⁻¹ year⁻¹ (CAN) and compared these traits and their relationships across different treatments, periods, and species. We found that CAN significantly increased C. chinensis’s leaf carbon (C) content, while the same treatment reduced leaf C content in S. superba. Specific leaf area (SLA), specific leaf weight (SLW), leaf N content, and C:N ratio showed more variation between species and within species across developmental stages than in response to different N addition treatments. Nitrogen addition also significantly increased the xylem width in both species, but the weekly xylem increment before July was notably higher in S. superba than in C. chinensis. Moreover, the leaf C content during early leaf development (ELD) following N addition was significantly and negatively correlated with the start date of xylogenesis in C. chinensis but had no significant effect on the onset of xylogenesis in S. superba. Additionally, regardless of species, SLA in ELD was negatively correlated with xylem width at the end of the early growing season (EW) under CK. However, this relationship became insignificant under CAN, suggesting that N addition alleviated the trade-off between SLA in ELD and EW. These results demonstrated that the relationship between leaf and xylem growth is influenced by both the leaf developmental stage and N availability. Traditional analyses of the leaf–xylem relationship, based solely on mature leaf traits, might oversimplify the effects of N deposition on tree growth. Full article