scholarly journals Biophysical Determinants of Shifting Tundra Vegetation Productivity in the Beaufort Delta Region of Canada

Ecosystems ◽  
2022 ◽  
Author(s):  
Jordan H. Seider ◽  
Trevor C. Lantz ◽  
Txomin Hermosilla ◽  
Michael A. Wulder ◽  
Jonathan A. Wang
Keyword(s):  
Random Forests ◽  
Climate Warming ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Future Research ◽  
Delta Region ◽  
Vegetation Productivity ◽  
Tundra Vegetation ◽  
Glaciofluvial Deposits ◽  
The Impact

AbstractTemperature increases across the circumpolar north have driven rapid increases in vegetation productivity, often described as ‘greening’. These changes have been widespread, but spatial variation in their pattern and magnitude suggests that biophysical factors also influence the response of tundra vegetation to climate warming. In this study, we used field sampling of soils and vegetation and random forests modeling to identify the determinants of trends in Landsat-derived Enhanced Vegetation Index, a surrogate for productivity, in the Beaufort Delta region of Canada between 1984 and 2016. This region has experienced notable change, with over 71% of the Tuktoyaktuk Coastlands and over 66% of the Yukon North Slope exhibiting statistically significant greening. Using both classification and regression random forests analyses, we show that increases in productivity have been more widespread and rapid at low-to-moderate elevations and in areas dominated by till blanket and glaciofluvial deposits, suggesting that nutrient and moisture availability mediate the impact of climate warming on tundra vegetation. Rapid greening in shrub-dominated vegetation types and observed increases in the cover of low and tall shrub cover (4.8% and 6.0%) also indicate that regional changes have been driven by shifts in the abundance of these functional groups. Our findings demonstrate the utility of random forests models for identifying regional drivers of tundra vegetation change. To obtain additional fine-grained insights on drivers of increased tundra productivity, we recommend future research combine spatially comprehensive time series satellite data (as used herein) with samples of high spatial resolution imagery and integrated field investigations.

scholarly journals Vegetation Dynamic Assessment by NDVI and Field Observations for Sustainability of China’s Wulagai River Basin

2021 ◽  
Vol 18 (5) ◽  
pp. 2528
Author(s):  
Panpan Chen ◽  
Huamin Liu ◽  
Zongming Wang ◽  
Dehua Mao ◽  
Cunzhu Liang ◽  
...  
Keyword(s):  
Species Diversity ◽  
River Basin ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Dynamic Assessment ◽  
Indicator System ◽  
Vegetation Changes ◽  
Vegetation Dynamic ◽  
Management Policies ◽  
The Impact

Accurate monitoring of grassland vegetation dynamics is essential for ecosystem restoration and the implementation of integrated management policies. A lack of information on vegetation changes in the Wulagai River Basin restricts regional development. Therefore, in this study, we integrated remote sensing, meteorological, and field plant community survey data in order to characterize vegetation and ecosystem changes from 1997 to 2018. The residual trend (RESTREND) method was utilized to detect vegetation changes caused by human factors, as well as to evaluate the impact of the management of pastures. Our results reveal that the normalized difference vegetation index (NDVI) of each examined ecosystem type showed an increasing trend, in which anthropogenic impact was the primary driving force of vegetation change. Our field survey confirmed that the meadow steppe ecosystem increased in species diversity and aboveground biomass; however, the typical steppe and riparian wet meadow ecosystems experienced species diversity and biomass degradation, therefore suggesting that an increase in NDVI may not directly reflect ecosystem improvement. Selecting an optimal indicator or indicator system is necessary in order to formulate reasonable grassland management policies for increasing the sustainability of grassland ecosystems.

scholarly journals Vegetation Dynamic Changes and Their Response to Ecological Engineering in the Sanjiangyuan Region of China

2020 ◽  
Vol 12 (24) ◽  
pp. 4035
Author(s):  
Xiaohui Zhai ◽  
Xiaolei Liang ◽  
Changzhen Yan ◽  
Xuegang Xing ◽  
Haowei Jia ◽  
...  
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Positive Impact ◽  
Ecological Engineering ◽  
Scientific Basis ◽  
Vegetation Dynamic ◽  
Vegetation Growth ◽  
The Impact

In recent decades, the vegetation of the Sanjiangyuan region has undergone a series of changes under the influence of climate change, and ecological restoration projects have been implemented. In this paper, we analyze the spatiotemporal dynamics of vegetation in this region using the satellite-retrieved normalized difference vegetation index (NDVI) from the global inventory modeling and mapping studies (GIMMS) and moderate resolution imaging and spectroradiometer (MODIS) datasets during the past 34 years. Specifically, the characteristics of vegetation changes were analyzed according to the stage of implementation of different ecological engineering programs. The results are as follows. (1) The vegetation in 65.6% of the study area exhibited an upward trend, and in 53.0% of the area, it displayed a large increase, which was mainly distributed in the eastern part of the study area. (2) The vegetation NDVI increased to differing degrees during stages of ecological engineering. (3) The NDVI in the western part of the Sanjiangyuan region is mainly affected by temperature, while in the northeastern part, the NDVI is affected more by precipitation. In the southern part, however, vegetation growth is affected neither by temperature nor by precipitation. On the whole region, vegetation growing is more affected by temperature than by precipitation. (4) The impacts of human activities on vegetation change are both positive and negative. In recent years, ecological engineering projects have had a positive impact on vegetation growth. This study can help us to correctly understand the impact of climate change on vegetation growth, so as to provide a scientific basis for the evaluation of regional ecological engineering effectiveness and the formulation of ecological protection policies.

scholarly journals Spatiotemporal Assessment of Vegetation Indices and Land Cover for Erbil City and Its Surrounding Using Modis Imageries

2017 ◽  
Vol 10 (1-2) ◽  
pp. 31-39 ◽  
Author(s):  
Shwan O. Hussein ◽  
Ferenc Kovács ◽  
Zalán Tobak
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Natural Vegetation ◽  
Visual Interpretation ◽  
Surrounding Areas ◽  
The Impact

Abstract The rate of global urbanization is exponentially increasing and reducing areas of natural vegetation. Remote sensing can determine spatiotemporal changes in vegetation and urban land cover. The aim of this work is to assess spatiotemporal variations of two vegetation indices (VI), the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), in addition land cover in and around Erbil city area between the years 2000 and 2015. MODIS satellite imagery and GIS techniques were used to determine the impact of urbanization on the surrounding quasi-natural vegetation cover. Annual mean vegetation indices were used to determine the presence of a spatiotemporal trend, including a visual interpretation of time-series MODIS VI imagery. Dynamics of vegetation gain or loss were also evaluated through the study of land cover type changes, to determine the impact of increasing urbanization on the surrounding areas of the city. Monthly rainfall, humidity and temperature changes over the 15-year-period were also considered to enhance the understanding of vegetation change dynamics. There was no evidence of correlation between any climate variable compared to the vegetation indices. Based on NDVI and EVI MODIS imagery the spatial distribution of urban areas in Erbil and the bare around it has expanded. Consequently, the vegetation area has been cleared and replaced over the past 15 years by urban growth.

scholarly journals Topographic Controls on Vegetation Changes in Alpine Tundra of the Changbai Mountains

Forests ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 756 ◽  
Author(s):  
Miaomiao Wu ◽  
Hong He ◽  
Shengwei Zong ◽  
Xinyuan Tan ◽  
Haibo Du ◽  
...  
Keyword(s):  
High Altitude ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Scale Effects ◽  
Alpine Tundra ◽  
Changbai Mountains ◽  
Vegetation Changes ◽  
Tundra Vegetation ◽  
Topographic Controls ◽  
Low Altitude

The vegetation of alpine tundra is undergoing significant changes and topography has played a significant role in mediating such changes. The roles of topography varied at different scales. In this study, we intended to identify topographic controls on tundra vegetation changes within the Changbai Mountains of Northeast China and reveal the scale effects. We delineated the vegetation changes of the last three decades using the normalized difference vegetation index (NDVI) time series. We conducted a trend analysis for each pixel to reveal the spatial change and used binary logistic regression models to analyze the relationship between topographic controls at different scales and vegetation changes. Results showed that about 30% of tundra vegetation experienced a significant (p < 0.05) change in the NDVI, with 21.3% attributable to the encroachment of low-altitude plants resulting in a decrease in the NDVI, and 8.7% attributable to the expansion of tundra endemic plants resulting in an increase in the NDVI. Plant encroachment occurred more severely in low altitude than in high altitude, whereas plant expansion mostly occurred near volcanic ash fields at high altitude. We found that plant encroachment tended to occur in complex terrains and the broad-scale mountain aspect had a greater effect on plant encroachment than the fine-scale local aspect. Our results suggest that it is important to include the mountain aspect in mountain vegetation change studies, as most such studies only use the local aspect.

Impact of Vegetation Types on Surface Temperature Change

2008 ◽  
Vol 47 (2) ◽  
pp. 411-424 ◽  
Author(s):  
Young-Kwon Lim ◽  
Ming Cai ◽  
Eugenia Kalnay ◽  
Liming Zhou
Keyword(s):  
Surface Temperature ◽  
Temperature Change ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Research Unit ◽  
Vegetation Types ◽  
Surface Temperature Change ◽  
The Impact ◽  
Surface Vegetation

Abstract The impact of different surface vegetations on long-term surface temperature change is estimated by subtracting reanalysis trends in monthly surface temperature anomalies from observation trends over the last four decades. This is done using two reanalyses, namely, the 40-yr ECMWF (ERA-40) and NCEP–NCAR I (NNR), and two observation datasets, namely, Climatic Research Unit (CRU) and Global Historical Climate Network (GHCN). The basis of the observation minus reanalysis (OMR) approach is that the NNR reanalysis surface fields, and to a lesser extent the ERA-40, are insensitive to surface processes associated with different vegetation types and their changes because the NNR does not use surface observations over land, whereas ERA-40 only uses surface temperature observations indirectly, in order to initialize soil temperature and moisture. As a result, the OMR trends can provide an estimate of surface effects on the observed temperature trends missing in the reanalyses. The OMR trends obtained from observation minus NNR show a strong and coherent sensitivity to the independently estimated surface vegetation from normalized difference vegetation index (NDVI). The correlation between the OMR trend and the NDVI indicates that the OMR trend decreases with surface vegetation, with a correlation &lt; −0.5, indicating that there is a stronger surface response to global warming in arid regions, whereas the OMR response is reduced in highly vegetated areas. The OMR trend averaged over the desert areas (0 &lt; NDVI &lt; 0.1) shows a much larger increase of temperature (∼0.4°C decade−1) than over tropical forest areas (NDVI &gt; 0.4) where the OMR trend is nearly zero. Areas of intermediate vegetation (0.1 &lt; NDVI &lt; 0.4), which are mostly found over midlatitudes, reveal moderate OMR trends (approximately 0.1°–0.3°C decade−1). The OMR trends are also very sensitive to the seasonal vegetation change. While the OMR trends have little seasonal dependence over deserts and tropical forests, whose vegetation state remains rather constant throughout the year, the OMR trends over the midlatitudes, in particular Europe and North America, exhibit strong seasonal variation in response to the NDVI fluctuations associated with deciduous vegetation. The OMR trend rises up approximately to 0.2°–0.3°C decade−1 in winter and early spring when the vegetation cover is low, and is only 0.1°C decade−1 in summer and early autumn with high vegetation. However, the Asian inlands (Russia, northern China with Tibet, and Mongolia) do not show this strong OMR variation despite their midlatitude location, because of the relatively permanent aridity of these regions.

scholarly journals Social Inequities in Urban Heat and Greenspace: Analyzing Climate Justice in Delhi, India

2021 ◽  
Vol 18 (9) ◽  
pp. 4800
Author(s):  
Bruce C. Mitchell ◽  
Jayajit Chakraborty ◽  
Pratyusha Basu
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Risk Index ◽  
Agricultural Workers ◽  
Vulnerable Groups ◽  
Future Research ◽  
Rapid Urbanization ◽  
Social Inequities ◽  
Urban Heat ◽  
The Impact

Climate change and rapid urbanization currently pose major challenges for equitable development in megacities of the Global South, such as Delhi, India. This study considers how urban social inequities are distributed in terms of burdens and benefits by quantifying exposure through an urban heat risk index (UHRI), and proximity to greenspace through the normalized difference vegetation index (NDVI), at the ward level in Delhi. Landsat derived remote sensing imagery for May and September 2011 is used in a sensitivity analysis of varying seasonal exposure. Multivariable models based on generalized estimating equations (GEEs) reveal significant statistical associations (p < 0.05) between UHRI/NDVI and several indicators of social vulnerability. For example, the proportions of children (β = 0.922, p = 0.024) and agricultural workers (β = 0.394, p = 0.016) are positively associated with the May UHRI, while the proportions of households with assets (β = −1.978, p = 0.017) and households with electricity (β = −0.605, p = 0.010) are negatively associated with the May UHRI. In contrast, the proportions of children (β = 0.001, p = 0.633) and agricultural workers (β = 0.002, p = 0.356) are not significantly associated with the May NDVI, while the proportions of households with assets (β = 0.013, p = 0.010) and those with electricity (β = 0.008, p = 0.006) are positively associated with the May NDVI. Our findings emphasize the need for future research and policies to consider how socially vulnerable groups are inequitably exposed to the impact of climate change-related urban heat without the mitigating effects of greenspace.

scholarly journals Vegetation Change and Its Response to Climate Change in Yunnan Province, China

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Huaizhang Sun ◽  
Jiyan Wang ◽  
Junnan Xiong ◽  
Jinhu Bian ◽  
Huaan Jin ◽  
...  
Keyword(s):  
Climate Change ◽  
Yunnan Province ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Growing Season ◽  
Effect Of Temperature ◽  
Lag Effect ◽  
Different Seasons ◽  
The Impact

The impact of global climate change on vegetation has become increasingly prominent over the past several decades. Understanding vegetation change and its response to climate can provide fundamental information for environmental resource management. In recent years, the arid climate and fragile ecosystem have led to great changes in vegetation in Yunnan Province, so it is very important to further study the relationship between vegetation and climate. In this study, we explored the temporal changes of normalized difference vegetation index (NDVI) in different seasons based on MOD13Q1 NDVI by the maximum value composite and then analyzed spatial distribution characteristics of vegetation using Sen’s tendency estimation, Mann–Kendall significance test, and coefficient of variation model (CV) combined with terrain factors. Finally, the concurrent and lagged effects of NDVI on climate factors in different seasons and months were discussed using the Pearson correlation coefficient. The results indicate that (1) the temporal variation of the NDVI showed that the NDVI values of different vegetation types increased at different rates, especially in growing season, spring, and autumn; (2) for spatial patterns, the NDVI, CV, and NDVI trends had strong spatial heterogeneity owning to the influence of altitudes, slopes, and aspects; and (3) the concurrent effect of vegetation on climate change indicates that the positive effect of temperature on NDVI was mainly in growing season and autumn, whereas spring NDVI was mainly influenced by precipitation. In addition, the lag effect analysis results revealed that spring precipitation has a definite inhibition effect on summer and autumn vegetation, but spring and summer temperature can promote the growth of vegetation. Meanwhile, the precipitation in the late growing season has a lag effect of 1-2 months on vegetation growth, and air temperature has a lag effect of 1 month in the middle of the growing season. Based on the above results, this study provided valuable information for ecosystem degradation and ecological environment protection in the Yunnan Province.

scholarly journals Vegetation Change Detection in the Niger Delta Region of Nigeria using Remote Sensing and GIS Techniques from 2000 to 2020

2021 ◽  
pp. 181-188
Author(s):  
P. O. Phil-Eze ◽  
Wali Elekwachi ◽  
L. C. Bosco-Abiahu ◽  
H. Wizor Collins ◽  
Abdullahi Muktar ◽  
...  
Keyword(s):  
Urban Areas ◽  
Niger Delta ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Forest Cover ◽  
United States Geological Survey ◽  
Exploration And Exploitation ◽  
Delta Region ◽  
Niger Delta Region ◽  
Negative Change

Generally, vegetation change through the conversion of the world’s forest land to other uses has assumed an increasing scale due to the unprecedented growth of the human population which increases the demand for food and land. Some believed that decrease in vegetation in the area is attributed to oil exploration and exploitation activities only. This study aimed to find out the nature of the vegetation change in the region from 2000 to 2020. The data used was remotely sensed images as Enhanced Vegetation Index (EVI) observed by Terra-MODIS, downloaded via United States Geological Survey (USGS). The Simple Image Differencing was performed on two images (February 18, 2000 and February 18, 2020) using IDRISI software. The result shows that all the states in the Niger Delta region experience both positive and negative change in vegetation cover. The positive change was observed around locations where agricultural plantations exists and within urban areas followed by oil and gas exploration and exploitation that damage the natural forest cover, while negative change was observed around farms where intensive rainy season farming takes place. It was recommended that deforested areas in the region should be reclaimed by planting economic trees as plantation to enhance greenness and maintain balance of the ecosystem. If intensive farming is necessary, it should be practiced sustainably to save the environment.

scholarly journals Long-term variability in vegetation productivity in relation to rainfall, herbivory and fire in Tswalu Kalahari Reserve

Koedoe ◽  
2018 ◽  
Vol 60 (1) ◽  
Author(s):  
Wataru Tokura ◽  
Sam L. Jack ◽  
Tania Anderson ◽  
Michael T. Hoffman
Keyword(s):  
Vegetation Change ◽  
Vegetation Index ◽  
Woody Species ◽  
Plant Productivity ◽  
Rainfall Regime ◽  
Positive Trend ◽  
Vegetation Types ◽  
Vegetation Productivity ◽  
Spatio Temporal

Exploring the long-term influence of climate and land use on vegetation change allows for a more robust understanding of how vegetation is likely to respond in the future. To inform management, this study investigated the relationship between vegetation productivity trends and potential drivers of change in the 110 000 ha of the Tswalu Kalahari Reserve between 2000 and 2015, using the Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index (EVI, MOD13Q1). Spatio-temporal variability of the EVI was mapped and then related to the historical records of precipitation, animal numbers and fire occurrences. Long-term trends in productivity were analysed by residual trend analysis (RESTREND). Significantly different EVI profiles were found between vegetation types, and this was related to the structure and function of the vegetation, as well as the effects of soil reflectance. The EVI time-series signalled spatial and temporal heterogeneity in plant productivity, which was strongly correlated with rainfall, although fire and especially herbivory had noteworthy localised effects on productivity. The RESTREND identified a significant positive trend in plant productivity in shrub-dominated vegetation types, providing evidence for the ongoing thickening of woody species. Significant negative trends in productivity were associated with artificial water points and more heavily stocked areas, leading to degradation.Conservation implications: The southern Kalahari has a highly variable rainfall regime, which is tied to a dynamic vegetation response. This variability should be taken into account when making management decisions. Field-based monitoring together with adaptive management approaches are needed in the face of an uncertain future in which significant warming is expected.

scholarly journals Remote sensing evaluation of High Arctic wetland depletion following permafrost disturbance by thermo-erosion gullying processes

2017 ◽  
Vol 3 (2) ◽  
pp. 237-253 ◽  
Author(s):  
Naïm Perreault ◽  
Esther Lévesque ◽  
Daniel Fortier ◽  
Denis Gratton ◽  
Laurent J. Lamarque
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Effective Means ◽  
Wetland Hydrology ◽  
High Arctic ◽  
Permafrost Degradation ◽  
Wetland Area ◽  
Tundra Vegetation ◽  
The Impact

Northern wetlands and their productive tundra vegetation are of prime importance for Arctic wildlife by providing high-quality forage and breeding habitats. However, many wetlands are becoming drier as a function of climate-induced permafrost degradation. This phenomenon is notably the case in cold, ice-rich permafrost regions such as Bylot Island, Nunavut, where degradation of ice wedges and thermo-erosion gullying have already occurred throughout the polygon-patterned landscape resulting in a progressive shift from wet to mesic tundra vegetation within a decade. This study reports on the application of the normalized difference vegetation index to determine the extent of permafrost ecosystem disturbance on wetlands adjacent to thermo-erosion gullies. The analysis of a GeoEye-1 image of the Qarlikturvik valley, yielding a classification with five classes and 62% accuracy, resulted in directly identifying affected areas when compared to undisturbed baseline of wet and mesic plant communities. The total wetland area lost by drainage around the three studied gullies approximated to 95 430 m2, which already represents 0.5% of the total wetland area of the valley. This is worrisome considering that 36 gullies have been documented in a single valley since 1999 and that permafrost degradation by thermal erosion gullying is significantly altering landscape morphology, modifying wetland hydrology, and generating new fluxes of nutrients, sediments, and carbon in the watershed. This study demonstrates that remote sensing provides an effective means for monitoring spatially and temporally the impact of permafrost disturbance on Arctic wetland stability.

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