scholarly journals Relationship between Winter Snow Cover Dynamics, Climate and Spring Grassland Vegetation Phenology in Inner Mongolia, China

2019 ◽  
Vol 8 (1) ◽  
pp. 42 ◽  
Author(s):  
Dejing Qiao ◽  
Nianqin Wang
Keyword(s):  
Snow Cover ◽  
Air Temperature ◽  
Inner Mongolia ◽  
Vegetation Index ◽  
Terrestrial Ecosystems ◽  
Onset Date ◽  
Vegetation Phenology ◽  
Grassland Vegetation ◽  
Spring Phenology ◽  
Winter Snow

The onset date of spring phenology (SOS) is regarded as a key parameter for understanding and modeling vegetation–climate interactions. Inner Mongolia has a typical temperate grassland vegetation ecosystem, and has a rich snow cover during winter. Due to climate change, the winter snow cover has undergone significant changes that will inevitably affect the vegetation growth. Therefore, improving our ability to accurately describe the responses of spring grassland vegetation phenology to winter snow cover dynamics would enhance our understanding of changes in terrestrial ecosystems due to their responses to climate changes. In this study, we quantified the spatial-temporal change of SOS by using the Advanced Very High Resolution Radiometer (AVHRR) derived Normalized Difference Vegetation Index (NDVI) from 1982 to 2015, and explored the relationships between winter snow cover, climate, and SOS across different grassland vegetation types. The results showed that the SOS advanced significantly at a rate of 0.3 days/year. Winter snow cover dynamics presented a significant positive correlation with the SOS, except for the start date of snow cover. Moreover, the relationship with the increasing temperature and precipitation showed a significant negative correlation, except that increasing Tmax (maximum air temperature) and Tavg (average air temperature) would lead a delay in SOS for desert steppe ecosystems. Sunshine hours and relative humidity showed a weaker correlation.

scholarly journals Soil moisture controls on patterns of grass green-up in Inner Mongolia: an index based approach

2013 ◽  
Vol 17 (2) ◽  
pp. 805-815 ◽  
Author(s):  
H. Liu ◽  
F. Tian ◽  
H. C. Hu ◽  
H. P. Hu ◽  
M. Sivapalan
Keyword(s):  
Soil Moisture ◽  
Water Availability ◽  
Inner Mongolia ◽  
Vegetation Index ◽  
Onset Date ◽  
Small Scale ◽  
Vegetation Phenology ◽  
Spring Phenology ◽  
Environmental Controls ◽  
Macro Scale

Abstract. Water availability is one of the most important environmental controls on vegetation phenology, especially in semi-arid regions. It is often represented in terms of soil moisture in small-scale studies, whereas it tends to be represented by precipitation in large-scale (e.g., regional) studies. Clearly, soil moisture is the more appropriate indicator for root water uptake and vegetation growth/phenology. Its potential advantage and applicability needs to be demonstrated at regional scales. The paper presents a data-based regional study of the effectiveness of novel water and temperature-based indices to predict spring vegetation green-up dates based on the Normalized Difference Vegetation Index (NDVI) observations in the grasslands of Inner Mongolia, China. The macro-scale hydrological model, VIC (Variable Infiltration Capacity), is employed to generate a soil moisture database across the region. In addition to a standard index based on temperature, two potential hydrology-based indices for prediction of spring onset dates are defined, based on the simulated soil moisture data as well as on observed precipitation data. Results indicate that the correspondence between the NDVI-derived green-up onset date and the soil-moisture-derived potential onset date exhibits a significantly better correlation as a function of increasing aridity compared to that based on precipitation. In this way the soil-moisture-based index is demonstrated to be superior to the precipitation-based index in terms of capturing grassland spring phenology. The results also showed that both of the hydrological (water-based) indices were superior to the thermal (temperature-based) index in determining the patterns of grass green-up in the Inner Mongolia region, indicating water availability to be the dominant control on average. The understanding about the relative controls on grassland phenology and the effectiveness of alternative indices to capture these controls are important for future studies of vegetation phenology change under climate change.

scholarly journals Soil moisture controls on patterns of grass green-up in Inner Mongolia: an index based approach

2012 ◽  
Vol 9 (10) ◽  
pp. 11641-11675 ◽  
Author(s):  
H. Liu ◽  
F. Tian ◽  
H. Hu ◽  
H. Hu ◽  
M. Sivapalan
Keyword(s):  
Soil Moisture ◽  
Water Availability ◽  
Inner Mongolia ◽  
Vegetation Index ◽  
Onset Date ◽  
Small Scale ◽  
Vegetation Phenology ◽  
Spring Phenology ◽  
Environmental Controls ◽  
Macro Scale

Abstract. Water availability is one of the most important environmental controls on vegetation phenology, especially in semi-arid regions, and is often represented in terms of soil moisture in small-scale studies whereas it tends to be represented by precipitation in large-scale (e.g. regional) studies. Clearly, soil moisture is the more appropriate indicator for root water uptake and vegetation growth/phenology and therefore its potential advantage and applicability needs to be demonstrated at regional scales. This paper represents a data-based regional study of the effectiveness of alternative indices based on water and energy availability on space-time patterns of spring vegetation green-up onset dates estimated from Normalized Difference Vegetation Index (NDVI) datasets in the grasslands of Inner Mongolia, China. The macro-scale hydrological model, VIC, is employed to generate a soil moisture database across the region. In addition to standard index based on temperature, two potential hydrology based indices for prediction of spring onset dates are defined based on the simulated soil moisture data as well as on observed precipitation data. Results indicate that the correspondence between the NDVI-derived green-up onset date and the soil moisture derived potential onset date exhibits a significantly better correlation as a function of increasing aridity, compared to that based on precipitation. In this way the soil moisture based index is demonstrated to be superior to the precipitation based index in terms of capturing grassland spring phenology. The results also showed that both of the hydrological (water based) indices were superior to the thermal (temperature based) index in determining the patterns of grass green-up in the Inner Mongolia region, indicating water availability to be the dominant control, on average. The understanding about the relative controls on grassland phenology, and the effectiveness of alternative indices to capture these controls, are important for future studies and predictions of vegetation phenology change under climate change.

scholarly journals Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere

2015 ◽  
Vol 9 (5) ◽  
pp. 1879-1893 ◽  
Author(s):  
K. Atlaskina ◽  
F. Berninger ◽  
G. de Leeuw
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Air Temperature ◽  
Land Surface ◽  
Surface Albedo ◽  
Vegetation Index ◽  
Precipitation Amount ◽  
Snow Cover Fraction ◽  
Air Temperatures ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo data for the Northern Hemisphere during the spring months (March–May) were analyzed to determine temporal and spatial changes over snow-covered land surfaces. Tendencies in land surface albedo change north of 50° N were analyzed using data on snow cover fraction, air temperature, vegetation index and precipitation. To this end, the study domain was divided into six smaller areas, based on their geographical position and climate similarity. Strong differences were observed between these areas. As expected, snow cover fraction (SCF) has a strong influence on the albedo in the study area and can explain 56 % of variation of albedo in March, 76 % in April and 92 % in May. Therefore the effects of other parameters were investigated only for areas with 100 % SCF. The second largest driver for snow-covered land surface albedo changes is the air temperature when it exceeds a value between −15 and −10 °C, depending on the region. At monthly mean air temperatures below this value no albedo changes are observed. The Enhanced Vegetation Index (EVI) and precipitation amount and frequency were independently examined as possible candidates to explain observed changes in albedo for areas with 100 % SCF. Amount and frequency of precipitation were identified to influence the albedo over some areas in Eurasia and North America, but no clear effects were observed in other areas. EVI is positively correlated with albedo in Chukotka Peninsula and negatively in eastern Siberia. For other regions the spatial variability of the correlation fields is too high to reach any conclusions.

scholarly journals A systematic review of ecological responses to variation in seasonal snow cover

2020 ◽  
Author(s):  
Rachel Slatyer ◽  
Pieter Andrew Arnold
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Terrestrial Ecosystems ◽  
Ecosystem Change ◽  
Future Research ◽  
Snow Layer ◽  
Spring Phenology ◽  
Ecological Responses ◽  
Seasonal Snow ◽  
Snow Conditions

Seasonal snow is among the most important factors governing the ecology of many terrestrial ecosystems, but rising global temperatures are changing snow regimes and driving widespread declines in the depth and duration of snow cover. Loss of the insulating snow layer will fundamentally change the environment. Understanding how individuals, populations, and communities respond to different snow conditions is thus essential for predicting and managing future ecosystem change. We synthesized 365 studies that have examined ecological responses to variation in winter snow conditions. This research encompasses a broad range of methods (experimental manipulations, natural snow gradients, and long-term monitoring approaches), locations (35 countries), study organisms (plants, mammals, arthropods, birds, fish, lichen, and fungi), and response measures. Earlier snowmelt was consistently associated with advanced spring phenology in plants, mammals, and arthropods. Reduced snow depth also often increased mortality and/or physical injury in plants, although there were few clear effects on animals. Neither snow depth nor snowmelt timing had clear or consistent directional effects on body size of animals or biomass of plants. With 96% of studies from the northern hemisphere, the generality of these trends across ecosystems and localities is also unclear. We identified substantial research gaps for several taxonomic groups and response types, with notably scarce research on winter-time responses. We have developed an agenda for future research to prioritize understanding of the mechanisms underlying responses to changing snow conditions and the consequences of those responses for seasonally snow-covered ecosystems.

scholarly journals Driving Forces of the Changes in Vegetation Phenology in the Qinghai–Tibet Plateau

2021 ◽  
Vol 13 (23) ◽  
pp. 4952
Author(s):  
Xigang Liu ◽  
Yaning Chen ◽  
Zhi Li ◽  
Yupeng Li ◽  
Qifei Zhang ◽  
...  
Keyword(s):  
Air Temperature ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Driving Forces ◽  
Growing Season ◽  
Tibet Plateau ◽  
Vegetation Phenology ◽  
Climate Change Research ◽  
Temperature And Precipitation ◽  
Qinghai Tibet Plateau

Phenological change is an emerging hot topic in ecology and climate change research. Existing phenological studies in the Qinghai–Tibet Plateau (QTP) have focused on overall changes, while ignoring the different characteristics of changes in different regions. Here, we use the Global Inventory Modeling and Mapping Studies (GIMMS3g) normalized difference vegetation index (NDVI) dataset as a basis to discuss the temporal and spatial changes in vegetation phenology in the Qinghai–Tibet Plateau from 1982 to 2015. We also analyze the response mechanisms of pre-season climate factor and vegetation phenology and reveal the driving forces of the changes in vegetation phenology. The results show that: (1) the start of the growing season (SOS) and the length of the growing season (LOS) in the QTP fluctuate greatly year by year; (2) in the study area, the change in pre-season precipitation significantly affects the SOS in the northeast (p < 0.05), while, the delay in the end of the growing season (EOS) in the northeast is determined by pre-season air temperature and precipitation; (3) pre-season precipitation in April or May is the main driving force of the SOS of different vegetation, while air temperature and precipitation in the pre-season jointly affect the EOS of different vegetation. The differences in and the diversity of vegetation types together lead to complex changes in vegetation phenology across different regions within the QTP. Therefore, addressing the characteristics and impacts of changes in vegetation phenology across different regions plays an important role in ecological protection in this region.

scholarly journals Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Lingling Liu ◽  
Xiaoyang Zhang
Keyword(s):  
United States ◽  
Interannual Variation ◽  
Vegetation Index ◽  
Climate Modeling ◽  
Terrestrial Ecosystems ◽  
Spring Phenology ◽  
Warming Climate ◽  
Spring Temperatures ◽  
Term Data

Abstract Warming climate and its impact on vegetation phenological trends have been widely investigated. However, interannual variability in temperature is considerably large in recent decades, which is expected to trigger an increasing trend of variation in vegetation phenology. To explore the interannual phenological variation across the contiguous United States (CONUS), we first detected the onset of vegetation greenup using the time series of the daily two-band Enhanced Vegetation Index (EVI2) observed from the AVHRR Long-Term Data Record (1982–1999) and the MODIS Climate Modeling Grid (2000–2016). We then calculated the interannual variation in greenup onset during four decadal periods: 1982–1989, 1990–1999, 2000–2009 and 2010–2016. Further, the trend of interannual variation in greenup onset from 1982 to 2016 was analyzed at pixel and state levels. Extreme phenological events were also determined using a greenup onset anomaly for each pixel. Similar approaches were applied to spring temperatures to detect extreme years and to the temporal trend of interannual variation to explain the phenological variation. The results revealed that 62% of pixels show an increasing interannual variation in greenup onset, and in 44% of pixels, this variation could be explained by the temperature. Although extreme phenology occurred locally in different years, three nationwide extreme phenological years were distinguished. The extreme warm spring that occurred in 2012 resulted in the occurrence of greenup onset as much as 20 days earlier than normal in large parts of the CONUS. In contrast, greenup onset was much later (up to 30 days) in 1983 and 1996 due to cool spring temperatures. These findings suggest that interannual variation in spring phenology could be much stronger in the future in response to climate variation, which could have more significant impacts on terrestrial ecosystems than the regular long-term phenological trend.

A Decade of Ground–Air Temperature Tracking at Emigrant Pass Observatory, Utah

2006 ◽  
Vol 19 (15) ◽  
pp. 3722-3731 ◽  
Author(s):  
Marshall G. Bartlett ◽  
David S. Chapman ◽  
Robert N. Harris
Keyword(s):  
Solar Radiation ◽  
Snow Cover ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Incident Solar Radiation ◽  
Ground Temperatures ◽  
Temperature Tracking ◽  
Air Temperatures ◽  
Winter Snow ◽  
A Minor

Abstract Observations of air and ground temperatures collected between 1993 and 2004 from Emigrant Pass Geothermal Climate Observatory in northwestern Utah are analyzed to understand the relationship between these two quantities. The influence of surface air temperature (SAT), incident solar radiation, and snow cover on surface ground temperature (SGT) variations are explored. SAT variations explain 94% of the variance in SGT. Incident solar radiation is the primary variable governing the remaining variance misfit and is significantly more important during summer months than winter months. A linear relationship between the ground–air temperature difference (ΔTsgt-sat) and solar radiation exists with a trend of 1.21 K/(100 W m−2); solar radiation accounts for 1.3% of the variance in SGT. The effects of incident solar radiation also account for the 2.47-K average offset in ΔTsgt-sat. During the winter, snow cover plays a role in governing SGT variability, but exerts only a minor influence on the annual tracking of ground and air temperatures at the site, accounting for 0.5% of the variance in SGT. These observations of the tracking of SGT and SAT confirm that borehole temperature changes mimic changes in SAT at frequencies appropriate for climatic reconstructions.

scholarly journals Asymmetric Effects of Daytime and Nighttime Warming on Boreal Forest Spring Phenology

2019 ◽  
Vol 11 (14) ◽  
pp. 1651 ◽  
Author(s):  
Guorong Deng ◽  
Hongyan Zhang ◽  
Xiaoyi Guo ◽  
Yu Shan ◽  
Hong Ying ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Vegetation Index ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Maximum Temperature ◽  
Spring Phenology ◽  
Asymmetric Effects ◽  
Terrestrial Ecosystem Model ◽  
Diurnal Temperatures ◽  
Nighttime Warming

Vegetation phenology is the most intuitive and sensitive biological indicator of environmental conditions, and the start of the season (SOS) can reflect the rapid response of terrestrial ecosystems to climate change. At present, the model based on mean temperature neglects the role of the daytime maximum temperature (TMAX) and the nighttime minimum temperature (TMIN) in providing temperature accumulation and cold conditions at leaf onset. This study analyzed the spatiotemporal variations of spring phenology for the boreal forest from 2001 to 2017 based on the moderate-resolution imaging spectro-radiometer (MODIS) enhanced vegetation index (EVI) data (MOD13A2) and investigated the asymmetric effects of daytime and nighttime warming on the boreal forest spring phenology during TMAX and TMIN preseason by partial correlation analysis. The results showed that the spring phenology was delayed with increasing latitude of the boreal forest. Approximately 91.37% of the region showed an advancing trend during the study period, with an average advancement rate of 3.38 ± 0.08 days/decade, and the change rates of different land cover types differed, especially in open shrubland. The length of the TMIN preseason was longer than that of the TMAX preseason and diurnal temperatures showed an asymmetrical increase during different preseasons. The daytime and nighttime warming effects on the boreal forest are asymmetrical. The TMAX has a greater impact on the vegetation spring phenology than TMIN as a whole and the effect also has seasonal differences; the TMAX mainly affects the SOS in spring, while TMIN has a greater impact in winter. The asymmetric effects of daytime and nighttime warming on the SOS in the boreal forest were highlighted in this study, and the results suggest that diurnal temperatures should be added to the forest terrestrial ecosystem model.

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