scholarly journals Estimating Frost during Growing Season and Its Impact on the Velocity of Vegetation Greenup and Withering in Northeast China

2020 ◽  
Vol 12 (9) ◽  
pp. 1355
Author(s):  
Guorong Deng ◽  
Hongyan Zhang ◽  
Lingbin Yang ◽  
Jianjun Zhao ◽  
Xiaoyi Guo ◽  
...  
Keyword(s):  
Global Climate Change ◽  
Northeast China ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Global Climate ◽  
Growing Season ◽  
Vegetation Phenology ◽  
Spatiotemporal Variations ◽  
The Past ◽  
Global Inventory

Vegetation phenology and photosynthetic primary production have changed simultaneously over the past three decades, thus impacting the velocity of vegetation greenup (Vgreenup) and withering (Vwithering). Although climate warming reduces the frequency of frost events, vegetation is exposed more frequently to frost due to the extension of the growing season. Currently, little is known about the effect of frost during the growing season on Vgreenup and Vwithering. This study analyzed spatiotemporal variations in Vgreenup and Vwithering in Northeast China between 1982 to 2015 using Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS 3g NDVI) data. Frost days and frost intensity were selected as indicators to investigate the influence of frost during the growing season on Vgreenup and Vwithering, respectively. Increased frost days during the growing season slowed Vgreenup and Vwithering. The number of frost days had a greater impact on Vwithering compared to Vgreenup. In addition, Vgreenup and Vwithering of forests were more vulnerable to frost days, while frost days had a lesser effect on grasslands. In contrast to frost days, frost intensity, which generally decreased during the growing season, accelerated Vgreenup and Vwithering for all land cover types. Changes in frost intensity had less of an impact on forests, whereas the leaf structure of grasslands is relatively simple and thus more vulnerable to frost intensity. The effects of frost during the growing season on Vgreenup and Vwithering in Northeast China were highlighted in this study, and the results provide a useful reference for understanding local vegetation responses to global climate change.

scholarly journals Changes in Vegetation Phenology and Productivity in Alaska Over the Past Two Decades

2020 ◽  
Vol 12 (10) ◽  
pp. 1546 ◽  
Author(s):  
Christopher Potter ◽  
Olivia Alexander
Keyword(s):  
Time Series ◽  
Coastal Plain ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Data Sets ◽  
Vegetation Phenology ◽  
Vegetation Growth ◽  
The Past ◽  
Moderate Resolution Imaging Spectroradiometer

Understanding trends in vegetation phenology and growing season productivity at a regional scale is important for global change studies, particularly as linkages can be made between climate shifts and the vegetation’s potential to sequester or release carbon into the atmosphere. Trends and geographic patterns of change in vegetation growth and phenology from the MODerate resolution Imaging Spectroradiometer (MODIS) satellite data sets were analyzed for the state of Alaska over the period 2000 to 2018. Phenology metrics derived from the MODIS Normalized Difference Vegetation Index (NDVI) time-series at 250 m resolution tracked changes in the total integrated greenness cover (TIN), maximum annual NDVI (MAXN), and start of the season timing (SOST) date over the past two decades. SOST trends showed significantly earlier seasonal vegetation greening (at more than one day per year) across the northeastern Brooks Range Mountains, on the Yukon-Kuskokwim coastal plain, and in the southern coastal areas of Alaska. TIN and MAXN have increased significantly across the western Arctic Coastal Plain and within the perimeters of most large wildfires of the Interior boreal region that burned since the year 2000, whereas TIN and MAXN have decreased notably in watersheds of Bristol Bay and in the Cook Inlet lowlands of southwestern Alaska, in the same regions where earlier-trending SOST was also detected. Mapping results from this MODIS time-series analysis have identified a new database of localized study locations across Alaska where vegetation phenology has recently shifted notably, and where land cover types and ecosystem processes could be changing rapidly.

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 Vegetation Phenological Changes in Multiple Landforms and Responses to Climate Change

2020 ◽  
Vol 9 (2) ◽  
pp. 111 ◽  
Author(s):  
Hongzhu Han ◽  
Jianjun Bai ◽  
Gao Ma ◽  
Jianwu Yan
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Growing Season ◽  
Vegetation Phenology ◽  
The South ◽  
Response Characteristics ◽  
The North ◽  
Spatio Temporal

Vegetation phenology is highly sensitive to climate change, and the phenological responses of vegetation to climate factors vary over time and space. Research on the vegetation phenology in different climatic regimes will help clarify the key factors affecting vegetation changes. In this paper, based on a time-series reconstruction of Moderate-Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data using the Savitzky–Golay filtering method, the phenology parameters of vegetation were extracted, and the Spatio-temporal changes from 2001 to 2016 were analyzed. Moreover, the response characteristics of the vegetation phenology to climate changes, such as changes in temperature, precipitation, and sunshine hours, were discussed. The results showed that the responses of vegetation phenology to climatic factors varied within different climatic regimes and that the Spatio-temporal responses were primarily controlled by the local climatic and topographic conditions. The following were the three key findings. (1) The start of the growing season (SOS) has a regular variation with the latitude, and that in the north is later than that in the south. (2) In arid areas in the north, the SOS is mainly affected by the temperature, and the end of the growing season (EOS) is affected by precipitation, while in humid areas in the south, the SOS is mainly affected by precipitation, and the EOS is affected by the temperature. (3) Human activities play an important role in vegetation phenology changes. These findings would help predict and evaluate the stability of different ecosystems.

scholarly journals Reduced resilience of terrestrial ecosystems locally is not reflected on a global scale

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Yuhao Feng ◽  
Haojie Su ◽  
Zhiyao Tang ◽  
Shaopeng Wang ◽  
Xia Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Vegetation Index ◽  
Global Climate ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Ecological Resilience ◽  
Terrestrial Vegetation ◽  
Ecosystem Resilience

AbstractGlobal climate change likely alters the structure and function of vegetation and the stability of terrestrial ecosystems. It is therefore important to assess the factors controlling ecosystem resilience from local to global scales. Here we assess terrestrial vegetation resilience over the past 35 years using early warning indicators calculated from normalized difference vegetation index data. On a local scale we find that climate change reduced the resilience of ecosystems in 64.5% of the global terrestrial vegetated area. Temperature had a greater influence on vegetation resilience than precipitation, while climate mean state had a greater influence than climate variability. However, there is no evidence for decreased ecological resilience on larger scales. Instead, climate warming increased spatial asynchrony of vegetation which buffered the global-scale impacts on resilience. We suggest that the response of terrestrial ecosystem resilience to global climate change is scale-dependent and influenced by spatial asynchrony on the global scale.

scholarly journals Modelling the productivity of Siberian larch forests from Landsat NDVI time series in fragmented forest stands of the Mongolian forest-steppe

2021 ◽  
Vol 193 (4) ◽  
Author(s):  
Stefan Erasmi ◽  
Michael Klinge ◽  
Choimaa Dulamsuren ◽  
Florian Schneider ◽  
Markus Hauck
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Global Climate Change ◽  
Global Climate ◽  
Siberian Larch ◽  
Growing Season ◽  
Forest Productivity ◽  
Forest Steppe ◽  
Fragmented Forest ◽  
Southern Fringe

AbstractThe monitoring of the spatial and temporal dynamics of vegetation productivity is important in the context of carbon sequestration by terrestrial ecosystems from the atmosphere. The accessibility of the full archive of medium-resolution earth observation data for multiple decades dramatically improved the potential of remote sensing to support global climate change and terrestrial carbon cycle studies. We investigated a dense time series of multi-sensor Landsat Normalized Difference Vegetation Index (NDVI) data at the southern fringe of the boreal forests in the Mongolian forest-steppe with regard to the ability to capture the annual variability in radial stemwood increment and thus forest productivity. Forest productivity was assessed from dendrochronological series of Siberian larch (Larix sibirica) from 15 plots in forest patches of different ages and stand sizes. The results revealed a strong correlation between the maximum growing season NDVI of forest sites and tree ring width over an observation period of 20 years. This relationship was independent of the forest stand size and of the landscape’s forest-to-grassland ratio. We conclude from the consistent findings of our case study that the maximum growing season NDVI can be used for retrospective modelling of forest productivity over larger areas. The usefulness of grassland NDVI as a proxy for forest NDVI to monitor forest productivity in semi-arid areas could only partially be confirmed. Spatial and temporal inconsistencies between forest and grassland NDVI are a consequence of different physiological and ecological vegetation properties. Due to coarse spatial resolution of available satellite data, previous studies were not able to account for small-scaled land-cover patches like fragmented forest in the forest-steppe. Landsat satellite-time series were able to separate those effects and thus may contribute to a better understanding of the impact of global climate change on natural ecosystems.

scholarly journals Analysis of Drought Characteristics in Xilingol Grassland of Northern China Based on SPEI and Its Impact on Vegetation

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Siqin Tong ◽  
Yuhai Bao ◽  
Rigele Te ◽  
Qiyun Ma ◽  
Si Ha ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Pearson Correlation ◽  
Growing Season ◽  
Vegetation Coverage ◽  
Semiarid Region ◽  
Linear Regression Method ◽  
Upward Trend ◽  
Drought Effect ◽  
Positive Correlation

This research is based on the standardized precipitation evapotranspiration index (SPEI) and normalized difference vegetation index (NDVI) which represent the drought and vegetation condition on land. Take the linear regression method and Pearson correlation analysis to study the spatial and temporal evolution of SPEI and NDVI and the drought effect on vegetation. The results show that (1) during 1961–2015, SPEI values at different time scales showed a downward trend; SPEI-12 has a mutation in 1997 and the SPEI value significantly decreased after this year. (2) During 2000–2015, the annual growing season SPEI has an obvious upward trend in time and the apparent wetting spatially. (3) In the recent 16 years, the growing season NDVI showed an upward trend and more than 80% of the total area’s vegetation increased in Xilingol. (4) Vegetation coverage in Xilingol grew better in humid years and opposite in arid years. SPEI and NDVI had a significant positive correlation; 98% of the region showed positive correlation, indicating that meteorological drought affects vegetation growth more in arid and semiarid region. (5) The effect of drought on vegetation has lag effect, and the responses of different grassland types to different scales of drought were different.

Alpine sparsely vegetated areas in the eastern Qilian Mountains shrank with climate warming in the past 30 years

2018 ◽  
Vol 42 (4) ◽  
pp. 415-430 ◽  
Author(s):  
Biao Zeng ◽  
Fuguang Zhang ◽  
Taibao Yang ◽  
Jiaguo Qi ◽  
Mihretab G Ghebrezgabher
Keyword(s):  
Climate Change ◽  
Climate Warming ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Qilian Mountains ◽  
Visual Interpretation ◽  
Hydrothermal Conditions ◽  
The Past ◽  
Distribution Ranges

Alpine sparsely vegetated areas (ASVAs) in mountains are sensitive to climate change and rarely studied. In this study, we focused on the response of ASVA distribution to climate change in the eastern Qilian Mountains (EQLM) from the 1990s to the 2010s. The ASVA distribution ranges in the EQLM during the past three decades were obtained from the Thematic Mapper remote sensing digital images by using the threshold of normalized difference vegetation index (NDVI) and artificial visual interpretation. Results indicated that the ASVA shrank gradually in the EQLM and lost its area by approximately 11.4% from the 1990s to the 2010s. The shrunken ASVA with markedly more area than the expanded one was mainly located at altitudes from 3700 m to 4300 m, which were comparatively lower than the average altitude of the ASVA distribution ranges. This condition led to the low ASVA boundaries in the EQLM moving upwards at a significant velocity of 22 m/decade at the regional scale. This vertical zonal process was modulated by topography-induced differences in local hydrothermal conditions. Thus, the ASVA shrank mainly in its lower parts with mild and sunny slopes. Annual maximum NDVI in the transition zone increased significantly and showed a stronger positive correlation with significantly increasing temperature than insignificant precipitation variations during 1990–2015. The ASVA shrinkage and up-shifting of its boundary were attributed to climate warming, which facilitated the upper part of alpine meadow in the EQLM by releasing the low temperature limitation on vegetation growth.

scholarly journals Climate Change Patterns of Wild Blueberry Fields in Downeast, Maine over the Past 40 Years

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 594
Author(s):  
Rafa Tasnim ◽  
Francis Drummond ◽  
Yong-Jiang Zhang
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Potential Evapotranspiration ◽  
Growing Season ◽  
Spatial Average ◽  
Climate Variables ◽  
Threshold Values ◽  
The Past ◽  
Wild Blueberry ◽  
Crop Health

Maine, USA is the largest producer of wild blueberries (Vaccinium angustifolium Aiton), an important native North American fruit crop. Blueberry fields are mainly distributed in coastal glacial outwash plains which might not experience the same climate change patterns as the whole region. It is important to analyze the climate change patterns of wild blueberry fields and determine how they affect crop health so fields can be managed more efficiently under climate change. Trends in the maximum (Tmax), minimum (Tmin) and average (Tavg) temperatures, total precipitation (Ptotal), and potential evapotranspiration (PET) were evaluated for 26 wild blueberry fields in Downeast Maine during the growing season (May–September) over the past 40 years. The effects of these climate variables on the Maximum Enhanced Vegetation Index (EVImax) were evaluated using Remote Sensing products and Geographic Information System (GIS) tools. We found differences in the increase in growing season Tmax, Tmin, Tavg, and Ptotal between those fields and the overall spatial average for the region (state of Maine), as well as among the blueberry fields. The maximum, minimum, and average temperatures of the studied 26 wild blueberry fields in Downeast, Maine showed higher rates of increase than those of the entire region during the last 40 years. Fields closer to the coast showed higher rates of warming compared with the fields more distant from the coast. Consequently, PET has been also increasing in wild blueberry fields, with those at higher elevations showing lower increasing rates. Optimum climatic conditions (threshold values) during the growing season were explored based on observed significant quadratic relationships between the climate variables (Tmax and Ptotal), PET, and EVImax for those fields. An optimum Tmax and PET for EVImax at 22.4 °C and 145 mm/month suggest potential negative effects of further warming and increasing PET on crop health and productivity. These climate change patterns and associated physiological relationships, as well as threshold values, could provide important information for the planning and development of optimal management techniques for wild blueberry fields experiencing climate change.

scholarly journals Phenology-Based Residual Trend Analysis of MODIS-NDVI Time Series for Assessing Human-Induced Land Degradation

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3676 ◽  
Author(s):  
Hao Chen ◽  
Xiangnan Liu ◽  
Chao Ding ◽  
Fang Huang
Keyword(s):  
Trend Analysis ◽  
Land Degradation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growing Season ◽  
Practical Method ◽  
Large Area ◽  
Modis Ndvi ◽  
Daily Precipitation Data ◽  
Improved Model

Land degradation is a widespread environmental issue and an important factor in limiting sustainability. In this study, we aimed to improve the accuracy of monitoring human-induced land degradation by using phenological signal detection and residual trend analysis (RESTREND). We proposed an improved model for assessing land degradation named phenology-based RESTREND (P-RESTREND). This method quantifies the influence of precipitation on normalized difference vegetation index (NDVI) variation by using the bivariate linear regression between NDVI and precipitation in pre-growing season and growing season. The performances of RESTREND and P-RESTREND for discriminating land degradation caused by climate and human activities were compared based on vegetation-precipitation relationship. The test area is in Western Songnen Plain, Northeast China. It is a typical region with a large area of degraded drylands. The MODIS 8-day composite reflectance product and daily precipitation data during 2000–2015 were used. Our results showed that P-RESTREND was more effective in distinguishing different drivers of land degradation than the RESTREND. Degraded areas in the Songnen grasslands can be effectively detected by P-RESTREND. Therefore, this modified model can be regarded as a practical method for assessing human-induced land degradation.

scholarly journals Assessing Snow Phenology and Its Environmental Driving Factors in Northeast China

2022 ◽  
Vol 14 (2) ◽  
pp. 262
Author(s):  
Hui Guo ◽  
Xiaoyan Wang ◽  
Zecheng Guo ◽  
Siyong Chen
Keyword(s):  
Snow Cover ◽  
Northeast China ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Water Cycle ◽  
Water Source ◽  
Driving Factors ◽  
Change Rate ◽  
Mean Temperature ◽  
Forested Areas

Snow cover is an important water source and even an Essential Climate Variable (ECV) as defined by the World Meteorological Organization (WMO). Assessing snow phenology and its driving factors in Northeast China will help with comprehensively understanding the role of snow cover in regional water cycle and climate change. This study presents spatiotemporal variations in snow phenology and the relative importance of potential drivers, including climate, geography, and the normalized difference vegetation index (NDVI), based on the MODIS snow products across Northeast China from 2001 to 2018. The results indicated that the snow cover days (SCD), snow cover onset dates (SCOD) and snow cover end dates (SCED) all showed obvious latitudinal distribution characteristics. As the latitude gradually increases, SCD becomes longer, SCOD advances and SCED delays. Overall, there is a growing tendency in SCD and a delayed trend in SCED across time. The variations in snow phenology were driven by mean temperature, followed by latitude, while precipitation, aspect and slope all had little effect on the SCD, SCOD and SCED. With decreasing temperature, the SCD and SCED showed upward trends. The mean temperature has negatively correlation with SCD and SCED and positively correlation with SCOD. With increasing latitude, the change rate of the SCD, SCOD and SCED in the whole Northeast China were 10.20 d/degree, −3.82 d/degree and 5.41 d/degree, respectively, and the change rate of snow phenology in forested areas was lower than that in nonforested areas. At the same latitude, the snow phenology for different underlying surfaces varied greatly. The correlations between the snow phenology and NDVI were mainly positive, but weak correlations accounted for a large proportion.

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