Spatiotemporal nexus between vegetation change and extreme climatic indices and their possible causes of change

2021 ◽  
Vol 289 ◽  
pp. 112505
Author(s):  
Abu Reza Md Towfiqul Islam ◽  
H.M.Touhidul Islam ◽  
Shamsuddin Shahid ◽  
Mst Khadiza Khatun ◽  
Mir Mohammad Ali ◽  
...  
2000 ◽  
pp. 26-31
Author(s):  
E. I. Parfenova ◽  
N. M. Chebakova

Global climate warming is expected to be a new factor influencing vegetation redistribution and productivity in the XXI century. In this paper possible vegetation change in Mountain Altai under global warming is evaluated. The attention is focused on forest vegetation being one of the most important natural resources for the regional economy. A bioclimatic model of correlation between vegetation and climate is used to predict vegetation change (Parfenova, Tchebakova 1998). In the model, a vegetation class — an altitudinal vegetation belt (mountain tundra, dark- coniferous subalpine open woodland, light-coniferous subgolets open woodland, dark-coniferous mountain taiga, light-coniferous mountain taiga, chern taiga, subtaiga and forest-steppe, mountain steppe) is predicted from a combination of July Temperature (JT) and Complex Moisture Index (CMI). Borders between vegetation classes are determined by certain values of these two climatic indices. Some bioclimatic regularities of vegetation distribution in Mountain Altai have been found: 1. Tundra is separated from taiga by the JT value of 8.5°C; 2. Dark- coniferous taiga is separated from light-coniferous taiga by the CMI value of 2.25; 3. Mountain steppe is separated from the forests by the CMI value of 4.0. 4. Within both dark-coniferous and light-coniferous taiga, vegetation classes are separated by the temperature factor. For the spatially model of vegetation distribution in Mountain Altai within the window 84 E — 90 E and 48 N — 52 N, the DEM (Digital Elevation Model) was used with a pixel of 1 km resolution. In a GIS Package IDRISI for Windows 2.0, climatic layers were developed based on DEM and multiple regressions relating climatic indices to physiography (elevation and latitude). Coupling the map of climatic indices with the authors' bioclimatic model resulted into a vegetation map for the region of interest. Visual comparison of the modelled vegetation map with the observed geobotanical map (Kuminova, 1960; Ogureeva, 1980) showed a good similarity between them. The new climatic indices map was developed under the climate change scenario with summer temperature increase 2°C and annual precipitation increase 20% (Menzhulin, 1998). For most mountains under such climate change scenario vegetation belts would rise 300—400 m on average. Under current climate, the dark-coniferous and light-coniferous mountain taiga forests dominate throughout Mountain Altai. The chern forests are the most productive and floristically rich and are also widely distributed. Under climate warming, light-coniferous mountain taiga may be expected to transform into subtaiga and forest-steppe and dark-coniferous taiga may be expected to transform partly into chern taiga. Other consequences of warming may happen such as the increase of forest productivity within the territories with sufficient rainfall and the increase of forest fire occurrence over territories with insufficient rainfall.


2014 ◽  
Vol 25 (1-2) ◽  
pp. 101-107
Author(s):  
I. A. Tarakhkalo

The analysis on the effects of pyrogenic Lugansk region for the period from 2001 to 2005 was conducted using the service «FIRMS». Established seasonal dynamics of pyrogenic phenomena and specific influence of climatic factors on the pyrogenic effects in the Luhansk region.


2002 ◽  
Vol 39 (2) ◽  
pp. 279-293 ◽  
Author(s):  
R.S. Smith ◽  
R.S. Shiel ◽  
D. Millward ◽  
P. Corkhill ◽  
R.A. Sanderson

Author(s):  
Yuanhe Yu ◽  
Yuzhen Shen ◽  
Jinliang Wang ◽  
Yuchun Wei ◽  
Lanping Nong ◽  
...  

2021 ◽  
Vol 13 (7) ◽  
pp. 1230
Author(s):  
Simeng Wang ◽  
Qihang Liu ◽  
Chang Huang

Changes in climate extremes have a profound impact on vegetation growth. In this study, we employed the Moderate Resolution Imaging Spectroradiometer (MODIS) and a recently published climate extremes dataset (HadEX3) to study the temporal and spatial evolution of vegetation cover, and its responses to climate extremes in the arid region of northwest China (ARNC). Mann-Kendall test, Anomaly analysis, Pearson correlation analysis, Time lag cross-correlation method, and Least absolute shrinkage and selection operator logistic regression (Lasso) were conducted to quantitatively analyze the response characteristics between Normalized Difference Vegetation Index (NDVI) and climate extremes from 2000 to 2018. The results showed that: (1) The vegetation in the ARNC had a fluctuating upward trend, with vegetation significantly increasing in Xinjiang Tianshan, Altai Mountain, and Tarim Basin, and decreasing in the central inland desert. (2) Temperature extremes showed an increasing trend, with extremely high-temperature events increasing and extremely low-temperature events decreasing. Precipitation extremes events also exhibited a slightly increasing trend. (3) NDVI was overall positively correlated with the climate extremes indices (CEIs), although both positive and negative correlations spatially coexisted. (4) The responses of NDVI and climate extremes showed time lag effects and spatial differences in the growing period. (5) Precipitation extremes were closely related to NDVI than temperature extremes according to Lasso modeling results. This study provides a reference for understanding vegetation variations and their response to climate extremes in arid regions.


2021 ◽  
pp. 1-15
Author(s):  
Christopher S. Cooper ◽  
David F. Porinchu ◽  
Scott A. Reinemann ◽  
Bryan G. Mark ◽  
James Q. DeGrand

Abstract Analyses of macroscopic charcoal, sediment geochemistry (%C, %N, C/N, δ13C, δ15N), and fossil pollen were conducted on a sediment core recovered from Stella Lake, Nevada, establishing a 2000 year record of fire history and vegetation change for the Great Basin. Charcoal accumulation rates (CHAR) indicate that fire activity, which was minimal from the beginning of the first millennium to AD 750, increased slightly at the onset of the Medieval Climate Anomaly (MCA). Observed changes in catchment vegetation were driven by hydroclimate variability during the early MCA. Two notable increases in CHAR, which occurred during the Little Ice Age (LIA), were identified as major fire events within the catchment. Increased C/N, enriched δ15N, and depleted δ13C values correspond with these events, providing additional evidence for the occurrence of catchment-scale fire events during the late fifteenth and late sixteenth centuries. Shifts in the vegetation community composition and structure accompanied these fires, with Pinus and Picea decreasing in relative abundance and Poaceae increasing in relative abundance following the fire events. During the LIA, the vegetation change and lacustrine geochemical response was most directly influenced by the occurrence of catchment-scale fires, not regional hydroclimate.


Author(s):  
Sylwia Skreczko ◽  
Artur Szymczyk ◽  
Weronika Nadłonek

Abstract Purpose The analysis of n-alkanes in palaeoenvironmental studies of peatlands is mainly limited to ombrogenous peatlands which are a rare feature in the environment. Using n-alkane and plant macrofossil analysis, we have tracked changes in the environment in the valley of a large Central European river. We tested the possibilities for applying such studies to low-moor bogs which are the most commonly occurring type of bog in the world. Materials and methods Representative peat samples were taken from two profiles in a peatland located in the Vistula Valley (southern Poland), and they were analysed for the occurrence and distribution of biomarkers. The distribution of n-alkanes was determined using gas chromatography-mass spectrometry (GC–MS). The botanical composition of the samples was determined by analysis of plant macrofossil remains, and the degree of peat decomposition was also determined. Results and discussion Samples of low-moor peat were characterised by a prevalence of medium- and long-chain n-alkane homologues, which is typical for higher plants. The variable values of the CPI, CPI (25–31), and the C23/C25 ratio have provided information on the stages of formation of the Zapadź bog. The source of n-alkane differentiation is vegetation change related to palaeohydrological dynamics and palaeoenvironmental conditions within the peatland. Conclusions We have shown that analysis of n-alkanes can be successfully used in low-moor bogs as a complement to palaeobotanical and palaeozoological methods. The bringing together of these types of research enables changes in the ecosystems of large river valleys to be tracked.


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