Vegetation Phenology in Permafrost Regions of Northeastern China Based on MODIS and Solar-induced Chlorophyll Fluorescence

Vegetation phenology is an indicator of vegetation response to natural environmental changes and is of great significance for the study of global climate change and its impact on terrestrial ecosystems.The normalized difference vegetation index(NDVI)and enhanced vegetation index(EVI),extracted from the Moderate Resolution Imaging Spectrometer(MODIS),are widely used to monitor phenology by calculating land surface reflectance.However,the applicability of the vegetation index based on‘greenness'to monitor photosynthetic activity is hindered by poor observation conditions(e.g.,ground shadows,snow,and clouds).Recently,satellite measurements of solar-induced chlorophyll fluorescence(SIF)from OCO-2 sensors have shown great potential for studying vegetation phenology.Here,we tested the feasibility of SIF in extracting phenological metrics in permafrost regions of the northeastern China,exploring the characteristics of SIF in the study of vegetation phenology and the differences between NDVI and EVI.The results show that NDVI has obvious SOS advance and EOS lag,and EVI is closer to SIF.The growing season length based on SIF is often the shortest,while it can represent the true phenology of vegetation because it is closely related to photosynthesis.SIF is more sensitive than the traditional remote sensing indices in monitoring seasonal changes in vegetation phenology and can compensate for the shortcomings of traditional vegetation indices.We also used the time series data of MODIS NDVI and EVI to extract phenological metrics in different permafrost regions.The results show that the length of growing season of vegetation in predominantly continuous permafrost(zone I)is longer than in permafrost with isolated taliks(zone II).Our results have certain significance for understanding the response of ecosystems in cold regions to global climate change.

Phenology of different types of vegetation and their response to climate change in the Qilian Mountains,China

The Qilian Mountains(QM)possess a delicate vegetation ecosystem,amplifying the evident response of vegetation phenology to climate change.The relationship between changes in vegetation growth and climate remains complex.To this end,we used MODIS NDVI data to extract the phenological parameters of the vegetation including meadow(MDW),grassland(GSD),and alpine vegetation(ALV))in the QM from 2002 to 2021.Then,we employed path analysis to reveal the direct and indirect impacts of seasonal climate change on vegetation phenology.Additionally,we decomposed the vegetation phenology in a time series using the trigonometric seasonality,Box-Cox transformation,ARMA errors,and Trend Seasonal components model(TBATS).The findings showed a distinct pattern in the vegetation phenology of the QM,characterized by a progressive shift towards an earlier start of the growing season(SOS),a delayed end of the growing season(EOS),and an extended length of the growing season(LOS).The growth cycle of MDW,GSD,and ALV in the QM species is clearly defined.The SOS for MDW and GSD occurred earlier,mainly between late April and August,while the SOS for ALVs occurred between mid-May and mid-August,a one-month delay compared to the other vegetation.The EOS in MDW and GSD were concentrated between late August and April and early September and early January,respectively.Vegetation phenology exhibits distinct responses to seasonal temperature and precipitation patterns.The advancement and delay of SOS were mainly influenced by the direct effect of spring temperatures and precipitation,which affected 19.59%and 22.17%of the study area,respectively.The advancement and delay of EOS were mainly influenced by the direct effect of fall temperatures and precipitation,which affected 30.18%and 21.17%of the area,respectively.On the contrary,the direct effects of temperature and precipitation in summer and winter on vegetation phenology seem less noticeable and were mainly influenced by indirect effects.The indirect effect of winter precipitation is the main factor affecting the advance or delay of SOS,and the area proportions were 16.29%and 23.42%,respectively.The indirect effects of fall temperatures and precipitation were the main factors affecting the delay and advancement of EOS,respectively,with an area share of 15.80%and 21.60%.This study provides valuable insight into the relationship between vegetation phenology and climate change,which can be of great practical value for the ecological protection of the Qinghai-Tibetan Plateau as well as for the development of GSD ecological animal husbandry in the QM alpine pastoral area.

Divergent response of vegetation phenology to extreme temperatures and precipitation of different intensities on the Tibetan Plateau

Quantifying how climate factors affect vegetation phenology is crucial for understanding climate-vegetation interactions and carbon and water cycles under a changing climate.However,the effects of different intensities of extreme climatic events on vegetation phenology remain poorly understood.Using a long-term solar-induced chlorophyll fluorescence dataset,we investigated the response of vegetation phenology to extreme temperatures and precipitation events of different intensities across the Tibetan Plateau(TP)from 2000 to 2018.We found that the effect of maximum temperature exposure days(TxED)and minimum temperature exposure days(TnED)on the start of the growing season(SOS)was initially delayed and shifted to advance along the increasing temperature gradients.However,the response of the end of the growing season(EOS)to TxED and TnED shifted from an advance to a delay with increasing temperature gradients until the temperature thresholds were reached,above which thresholds produced an unfavorable response to vegetation growth and brought the EOS to an early end.The corresponding maximum and minimum temperature thresholds were 10.12 and 2.54℃,respectively.In contrast,cumulative precipitation(CP)was more likely to advance SOS and delay EOS as the precipitation gradient increased,but the advance of SOS is gradually weakening.Four vegetation types(i.e.,forest,shrubland,meadow,and steppe)showed similar trends in response to different climates,but the optimal climatic conditions varied between the vegetation types.Generally,meadow and steppe had lower optimal temperatures and precipitation than forest and shrubland.These findings revealed the divergent responses of vegetation phenology to extreme climate events of different intensities,implying that the SOS will continue to advance with warming,whereas the EOS may undergo a partial transformation from delayed areas to advanced areas with continued warming.

Reconstructing landscapes of ungulate parturition and predation using vegetation phenology

Enhanced vegetation index(EVI)data can be used to identify and define the space in which ungulates practice parturition and encounter predation.This study explores the use of EVI data to identify landscapes linked to ungulate parturition and predation events across space,time,and environmental conditions.As a case study,we used the moose population(Alces alces)of northern Minnesota in the USA.Using remotely sensed EVI data rasters and global positioning system collar data,we quantified how vegetation phenology and moose movement shaped the births and predation of 52 moose calves from 2013 to 2020 on or adjacent to the Grand Portage Indian Reservation.The known sources of predation were American black bears(Ursus americanus,n=22)and gray wolves(Canis lupus,n=28).Satellite-derived data summarizing seasonal landscape features at the local level revealed that landscape heterogeneity use by moose can help to quantitatively identify landscapes of parturition and predation in space and time across large areas.Vegetation phenology proved to be differentiable between adult moose ranges,sites of cow parturition,and sites of calf predation.Landscape characteristics of each moose group were consistent and tractable based on environment,suggesting that sites of parturition and predation of moose are predictable in space and time.It is possible that moose selected specific landscapes for parturition despite risk of increased predation of their calves,which could be an example of an"ecological trap."This analytical framework can be employed to identify areas for future ungulate research on the impacts of landscape on parturition and predation dynamics.

Alpine vegetation responses to snow phenology in the Chinese Tianshan mountainous region

Investigating the interrelation between snow and vegetation is essential to explain the response of alpine ecosystems to climate change.Based on the MOD10 A1 daily cloud-free snow product and MOD13 A1 NDVI(normalized difference vegetation index)data,this study analysed the spatial and temporal patterns of snow phenology including snow onset date,snow end date,snow cover days,and vegetation phenology including the start of growing season,the end of growing season and the length of growing season in the Chinese Tianshan Mountainous Region(CTMR)from 2002 to 2018,and then investigated the snow phenological effects on the vegetation phenology among different ecogeographic zones and diverse vegetation types.The results indicated that snow onset date was earlier at higher elevations and later at lower elevations,while snow end date showed opposite spatial distribution characteristics.The end of growing season occurred later on the northwest slope of the CTMR and the Yili Valley.The earliest end of growing season was in the middle part of the CTMR.A long growing season was mainly distributed along the northern slope and the Yili Valley,while a short growing season was concentrated in the middle part of the CTMR.The response of vegetation phenology to changes in snow phenology varied among vegetation types and ecogeographic zones.The effect of snow phenology on vegetation phenology was more significant in IID5(Yili Valley)than in the other ecogeographic zones.A negative correlation was observed between the start of growing season and snow end date in nearly 54.78%of the study area,while a positive correlation was observed between the start of growing season and the snow end date in 66.85%of the study area.The sensitivity of vegetation phenology to changes in snow cover varied among different vegetation types.Snow onset date had the greatest effect on the start of growing season in the four vegetation cover types(alpine meadows,alpine steppes,shrubs,and alpine sparse vegetation),whereas the snow cover days had the least impact.Snow end date had the greatest impact on the end of growing season in the alpine steppes and shrub areas.The study results are helpful for understanding the vegetation dynamics under ongoing climate change,and can benefit vegetation management and pasture development in the CTMR.

Spatiotemporal variation in snow cover and its effects on grassland phenology on the Mongolian Plateau

Snow cover is an important water source for vegetation growth in arid and semi-arid areas,and grassland phenology provides valuable information on the response of terrestrial ecosystems to climate change.The Mongolian Plateau features both abundant snow cover resources and typical grassland ecosystems.In recent years,with the intensification of global climate change,the snow cover on the Mongolian Plateau has changed correspondingly,with resulting effects on vegetation growth.In this study,using MOD10A1 snow cover data and MOD13A1 Normalized Difference Vegetation Index(NDVI)data combined with remote sensing(RS)and geographic information system(GIS)techniques,we analyzed the spatiotemporal changes in snow cover and grassland phenology on the Mongolian Plateau from 2001 to 2018.The correlation analysis and grey relation analysis were used to determine the influence of snow cover parameters(snow cover fraction(SCF),snow cover duration(SCD),snow cover onset date(SCOD),and snow cover end date(SCED))on different types of grassland vegetation.The results showed wide snow cover areas,an early start time,a late end time,and a long duration of snow cover over the northern Mongolian Plateau.Additionally,a late start,an early end,and a short duration were observed for grassland phenology,but the southern area showed the opposite trend.The SCF decreased at an annual rate of 0.33%.The SCD was shortened at an annual rate of 0.57 d.The SCOD and SCED in more than half of the study area advanced at annual rates of 5.33 and 5.74 DOY(day of year),respectively.For grassland phenology,the start of the growing season(SOS)advanced at an annual rate of 0.03 DOY,the end of the growing season(EOS)was delayed at an annual rate of 0.14 DOY,and the length of the growing season(LOS)was prolonged at an annual rate of 0.17 d.The SCF,SCD,and SCED in the snow season were significantly positively correlated with the SOS and negatively correlated with the EOS and LOS.The SCOD was significantly negatively correlated with the SOS and positively correlated with the EOS and LOS.The SCD and SCF can directly affect the SOS of grassland vegetation,while the EOS and LOS were obviously influenced by the SCOD and SCED.This study provides a scientific basis for exploring the response trends of alpine vegetation to global climate change.

Spatial variations in responses of vegetation autumn phenology to climate change on the tibetan Plateau

Aims Information about changes in the start and end of the vegetation growing season(SOS and EOS)is crucial for assessing ecosystem responses to climate change because of the high sensitivity of both to climate and their extensive influence on ecological processes in temperate and cold regions.climatic warming substantially advanced SOS on the tibetan Plateau from 1982 to 2011.However,it is unclear why EOS showed little delay despite increasing tem-perature over this period.Methods We used multiple methods to determine EOS from the satellite-observed normalized-difference vegetation index and investigated the relationships between EOS and its potential drivers on the tibetan Plateau over 1982-2011.Important findings We found a slight but non-significant delay in regionally averaged EOS of 0.7 day decade−1(P=0.18)and a widespread but weak delaying trend across the Plateau over this period.the inter-annual variations in regionally averaged EOS were driven mainly by pre-season temperature(partial R=0.62,P<0.01),and precipitation and insolation showed weak impact on EOS(P>0.10).Pre-season warming delayed EOS mainly in the eastern half and north-western area of the plateau.In the south-west,EOS was significantly and positively related to SOS,suggesting potentially indirect effects of winter weather conditions on the following autumn’s phenology through regulation of spring phenology.EOS was more strongly related with pre-season temperature in colder and wetter areas,reflecting vegetation adaptation to local climate.Interestingly,pre-season temperature had weaker delaying effects on EOS for vegeta-tion with a shorter growing season,for which SOS had a stronger control on inter-annual variations in EOS than for vegetation with a longer growing season.this indicates that shorter-season tibetan Plateau vegetation may have lower plasticity in adjusting the length of its growing season,whenever it begins,and that climate change is more likely to shift the growing season than extend it for that vegetation.

Response of water-use efficiency to phenology in the natural forest and grassland of the Loess Plateau in China

Ecosystem water use efficiency(WUE)is an integrated physiological metric for the coupling cycle between terrestrial carbon,water,and energy.How WUE responds to vegetation phenology(e.g.,SOS,EOS-start,end of growing season,and GSL-growing season length)shifting in temperate semi-arid regions is a hot spot in relative research fields.Based on remotesensing products and in-situ measured climate data,this study discussed how gross primary productivity(GPP),evapotranspiration(ET),and WUE(quantified by GPP/ET)would change with the altering vegetation phenology and climate in the untouched semi-arid forests and grasslands of the Chinese Loess Plateau during 2001–2020.Our results show that vegetation tended to green-up earlier and brown-down later from 2001 to 2020,causing an extended GSL.The forests had an earlier SOS,later EOS,and longer GSL than the grasslands,but the latter had a bigger variation amplitude.The WUE in the study area decreased significantly during spring and summer,while the grassland WUE increased in autumn;the annual mean reduction rate in grassland WUE was approximately twice that of woodland.Earlier SOS could increase forest WUE but reduce grassland WUE in spring,mainly because leaf unfolding has a more pronounced limitation on soil evaporation beneath the forest canopy.EOS had less impact on WUE,and no apparent difference existed between these two ecosystems.Climate change could affect WUE directly by changing GPP and ET and indirectly by regulating vegetation phenology.Warming can increase GPP and ET,causing an earlier SOS,further promoting GPP and ET(except forest ET).Precipitation significantly affected forest GPP and ET in spring,grassland GPP and ET in summer,and grassland ET in autumn;precipitation affects spring grassland WUE mainly via regulating SOS.Enhanced solar radiation could suppress grassland GPP in spring,promote forest ET in autumn,and regulate grassland WUE by affecting phenology.This study is meaningful for improving the process-based vegetation model and studying arid and semi-arid ecosystems’responses to a changing climate.

气候变化和物候变动对东北黑土区农业生产的协同作用及未来粮食生产风险

The black soil region of northeast China is a vital food base and is one of the most sensitive regions to climate change in China.However,the characteristics of the crop phenological response and the integrated impact of climate and phenological changes on agricultural productivity in the region under the background of climate change are not clear.The future agricultural risk assessment has been insufficiently quantified and the existing risk level formulation lacks a sound basis.Based on remote sensing products,climate data,and model simulations,this study integrated a logistic function fitting curvature derivation,multiple linear regression,and scenario simulation to investigate crop phenology dynamics and their climate response characteristics in the black soil region.Additionally,the compound effects of climate and phenology changes on agricultural production and possible future risks were identified.The key results were as follows:(1)From 2000 to 2017,29.76%of the black soil region of northeast China experienced a significant delay in the start of the growing season(SOS)and 16.71%of the total area displayed a trend for the end of the growing season(EOS)to arrive earlier.The time lagged effects of the SOS in terms of the crop response to climatic factors were site and climatic parameter dependent.The influence of temperature was widespread and its effect had a longer lag time in general;(2)Both climatic and phenological changes have had a significant effect on the inter-annual variability of crop production,and the predictive ability of both increased by 70.23%,while the predictive area expanded by 85.04%,as compared to that of climate change in the same period of the growing season;(3)Under the RCP8.5 scenario,there was a risk that the future crop yield would decrease in the north and increase in the south,and the risk area was constantly expanding.With a 2.0℃rise in global temperature,the crop yield of the southern Songnen black soil sub-region would reduce by almost 10%.This finding will improve our understanding of the mechanisms underlying climate change and vegetation productivity dynamics,and is also helpful in the promotion of the risk management of agrometeorological disasters.

A New Perspective on Understanding the Reduced Spring Dust Storm Frequency in Inner Mongolia, China

Spatiotemporal patterns of dust storms are affected by climate change through changes in convective instability, regional meteorological characteristics, and local sediment supply. Linking dust storm dynamics to climate change helps the understanding of what controls the initiation of dust storms, and assists the prediction of future dust storm occurrence. This study examines the temporal dynamics of spring dust storms in Inner Mongolia, a major dust source area in East Asia. We found that severe spring dust storms have significantly declined from1954 to 2007. Four dust storm types showed similar decreasing trends from 2001 to 2012. This change in spring dust storm dynamics is attributed to the shift in vegetation green-up dates based on the analysis of a satellite derived vegetation index. Earlier vegetation green-up has a dampening effect on spring dust storms. Suitable environmental conditions for vegetation green-up hinder the emergence of dust storms. This study expands our understanding of the dynamics of spring dust storms in the changing climate through a new perspective on vegetation phenology in the spring.