An Inter-Andean Forest Relict: Vegetation Change on Pasochoa Volcano, Ecuador

1995 ◽  
Vol 15 (4) ◽  
pp. 339 ◽  
Author(s):  
Margaret J. Stern
Keyword(s):  
Vegetation Change ◽  
Relict Vegetation

Possible vegetation change in Mountain Altai under climate warming and compiling the prognosis maps

2000 ◽  
pp. 26-31
Author(s):  
E. I. Parfenova ◽  
N. M. Chebakova
Keyword(s):  
Climate Warming ◽  
Vegetation Change ◽  
Climate Change Scenario ◽  
Change Scenario ◽  
Forest Steppe ◽  
Vegetation Map ◽  
Climatic Indices ◽  
Bioclimatic Model ◽  
Open Woodland ◽  
Mountain Taiga

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.

Soil seed banks and the effects of meadow management on vegetation change in a 10-year meadow field trial

2002 ◽  
Vol 39 (2) ◽  
pp. 279-293 ◽  
Author(s):  
R.S. Smith ◽  
R.S. Shiel ◽  
D. Millward ◽  
P. Corkhill ◽  
R.A. Sanderson
Keyword(s):  
Field Trial ◽  
Vegetation Change ◽  
Seed Banks ◽  
Soil Seed Banks

Assessing the response of vegetation change to drought during 2009–2018 in Yunnan Province, China

2021 ◽  
Author(s):  
Yuanhe Yu ◽  
Yuzhen Shen ◽  
Jinliang Wang ◽  
Yuchun Wei ◽  
Lanping Nong ◽  
...  
Keyword(s):  
Yunnan Province ◽  
Vegetation Change

scholarly journals Vegetation Change and Its Response to Climate Extremes in the Arid Region of Northwest China

2021 ◽  
Vol 13 (7) ◽  
pp. 1230
Author(s):  
Simeng Wang ◽  
Qihang Liu ◽  
Chang Huang
Keyword(s):  
Arid Region ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Time Lag ◽  
Climate Extremes ◽  
Northwest China ◽  
Precipitation Extremes ◽  
Temperature Extremes ◽  
Increasing Trend

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.

A lake sediment–based paleoecological reconstruction of late Holocene fire history and vegetation change in Great Basin National Park, Nevada, USA

2021 ◽  
pp. 1-15
Author(s):  
Christopher S. Cooper ◽  
David F. Porinchu ◽  
Scott A. Reinemann ◽  
Bryan G. Mark ◽  
James Q. DeGrand
Keyword(s):  
Great Basin ◽  
Relative Abundance ◽  
Vegetation Change ◽  
Fire History ◽  
Ice Age ◽  
Sediment Geochemistry ◽  
Catchment Scale ◽  
Composition And Structure ◽  
Hydroclimate Variability ◽  
Late Fifteenth

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.

scholarly journals Impacts of vegetation and palaeohydrological changes on the n-alkane composition of a Holocene peat sequence from the Upper Vistula Valley (southern Poland)

2021 ◽  
Author(s):  
Sylwia Skreczko ◽  
Artur Szymczyk ◽  
Weronika Nadłonek
Keyword(s):  
Vegetation Change ◽  
Higher Plants ◽  
Large River ◽  
Gas Chromatography Mass Spectrometry ◽  
Botanical Composition ◽  
Central European ◽  
Plant Macrofossil ◽  
Southern Poland ◽  
River Valleys ◽  
Palaeoenvironmental Conditions

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.

scholarly journals Short-Term Effects of Fire Severity on Vegetation Based on Sentinel-2 Satellite Data

2021 ◽  
Vol 13 (1) ◽  
pp. 432
Author(s):  
Aru Han ◽  
Song Qing ◽  
Yongbin Bao ◽  
Li Na ◽  
Yuhai Bao ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Vegetation Change ◽  
Fire Severity ◽  
Dynamic Change ◽  
Burned Area ◽  
Fire Event ◽  
Vegetation Dynamic ◽  
Area Index ◽  
Sentinel 2

An important component in improving the quality of forests is to study the interference intensity of forest fires, in order to describe the intensity of the forest fire and the vegetation recovery, and to improve the monitoring ability of the dynamic change of the forest. Using a forest fire event in Bilahe, Inner Monglia in 2017 as a case study, this study extracted the burned area based on the BAIS2 index of Sentinel-2 data for 2016–2018. The leaf area index (LAI) and fractional vegetation cover (FVC), which are more suitable for monitoring vegetation dynamic changes of a burned area, were calculated by comparing the biophysical and spectral indices. The results showed that patterns of change of LAI and FVC of various land cover types were similar post-fire. The LAI and FVC of forest and grassland were high during the pre-fire and post-fire years. During the fire year, from the fire month (May) through the next 4 months (September), the order of areas of different fire severity in terms of values of LAI and FVC was: low > moderate > high severity. During the post fire year, LAI and FVC increased rapidly in areas of different fire severity, and the ranking of areas of different fire severity in terms of values LAI and FVC was consistent with the trend observed during the pre-fire year. The results of this study can improve the understanding of the mechanisms involved in post-fire vegetation change. By using quantitative inversion, the health trajectory of the ecosystem can be rapidly determined, and therefore this method can play an irreplaceable role in the realization of sustainable development in the study area. Therefore, it is of great scientific significance to quantitatively retrieve vegetation variables by remote sensing.

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