Tundra vegetation change and impacts on permafrost

AbstractLate Weichselian litho-, bio-, and chronostratigraphy (14C and varves) in southeastern Sweden provide a detailed picture of the deglaciation pattern and dynamics, shore displacement, late-glacial sedimentation, and history of the landscape, vegetation, and climate. Two plausible glacial models were tested against lithologic, chronologic, and climatic data. Permafrost at and outside the ice margin and topographic conditions beneath the ice apparently caused inward spread of frozen glacier-bed conditions. This led to a buildup of a large zone of debris-rich basal ice. A climatic amelioration about 12,700 yr B.P. changed the temperature profile in the ice sheet. Deposition of basal melt-out till began at the previously frozen glacier bed, and a rapid recession of the clean ice set in; thin exposed debris-rich basal ice which was separated from the active ice margin about 150 yr later. In this zone of stagnant ice there followed a 200– 300-yr period marked by subglacial and supraglacial melt-out and resedimentation, forming a large hummocky/transverse moraine. The mild climate favored rapid plant immigration, and a park-tundra was established. The gradual closing of the landscape was interrupted by a 100- to 150-yr period of tundra vegetation and a cool, dry climate, with local vegetational differences caused by differences in soil moisture. About 12,000 yr B.P. a second climatic amelioration set in, and during the next 1000 yr a birch (and pine) woodland gradually developed. Soils stabilized and Empetrum heaths became abundant as the climate gradually deteriorated at the end of this period. By 11,000 yr B.P. the area had become a tundra again with scattered birch stands, dominated by herbs such as Artemisia, Chenopodiaceae, grasses, and sedges. Some 500 yr later a birch/pine woodland again succeeded, and within about 500 yr the vegetation changed to a rather closed woodland as the climate ameliorated further. However, the time lag between climatic and vegetation change was considerable.

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

Forests ◽

10.3390/f9120756 ◽

2018 ◽

Vol 9 (12) ◽

pp. 756 ◽

Cited By ~ 3

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.

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

Ecosystems ◽

10.1007/s10021-021-00725-6 ◽

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.

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Plot-scale evidence of tundra vegetation change and links to recent summer warming

Nature Climate Change ◽

10.1038/nclimate1465 ◽

2012 ◽

Vol 2 (6) ◽

pp. 453-457 ◽

Cited By ~ 473

Author(s):

Sarah C. Elmendorf ◽

Gregory H. R. Henry ◽

Robert D. Hollister ◽

Robert G. Björk ◽

Noémie Boulanger-Lapointe ◽

...

Keyword(s):

Vegetation Change ◽

Tundra Vegetation ◽

Summer Warming

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Tundra vegetation change near Barrow, Alaska (1972–2010)

Environmental Research Letters ◽

10.1088/1748-9326/7/1/015508 ◽

2012 ◽

Vol 7 (1) ◽

pp. 015508 ◽

Cited By ~ 35

Author(s):

S Villarreal ◽

R D Hollister ◽

D R Johnson ◽

M J Lara ◽

P J Webber ◽

...

Keyword(s):

Vegetation Change ◽

Tundra Vegetation

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Models of vegetation change for landscape planning: a comparison of FETM, LANDSUM, SIMPPLLE, and VDDT

10.2737/rmrs-gtr-76 ◽

2001 ◽

Cited By ~ 18

Author(s):

T. M. Barrett

Keyword(s):

Vegetation Change ◽

Landscape Planning

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Vegetation structure of tundra and taiga on the map of the natural vegetation of Europe

Geobotanical mapping ◽

10.31111/geobotmap/2007.13 ◽

2007 ◽

pp. 13-22 ◽

Cited By ~ 1

Author(s):

T. K. Yurkovskaya

Keyword(s):

Vegetation Cover ◽

Abiotic Factors ◽

Self Regulation ◽

Space Structure ◽

Middle Taiga ◽

Russian Plain ◽

Forest Communities ◽

The North ◽

Tundra Vegetation ◽

Starting Point

I have focused only on some features of structure in the taiga vegetation cover. In conclusion I would like to tell some words about the causes of complicated space structure of the taiga and tundra vegetation cover. The causes of latitudinal differentiation are climatic undoubtedly, but heterogeneity of vegetation cover within the limits of tundra and taiga subzones is accounted for different factors. In tundra abiogenic factors prevail, first of all the permafrost processes. That is the reason why tundra vegetation cover is so sensible to any disturbances and so hard regenerates after various transformations. In taiga the space structure is mostly the result of self-regulation and self- restoration of biota. The abiotic factors, certainly, play significant role, but they recede to the second plan. So we showed that in the north and middle taiga the structure of vegetation cover, during the Holocene up to present time, is determined in many respects by the increasing role of mires. Suffice it to look at the map of distribution of mires in order to estimate their role in vegetation cover of the easteuropean taiga (Yurkovskaya, 1980). So, the increase of mire area on the Russian Plain in m2/year per 1000 ha varies between 200 and 700, the average increas is ca 300—400 m2/year (Elina et all., 2000). The mires favour peniplenization and unite the separate areas of forest communities into the whole by means of forming the buffer paludificated territories (various hydrophilous variants of forest communities). But if mires, at all their stability, after destroying practically don't restore, the forests even after continuous cuttings restore their structure and composition through the series of successional stages unless an ecotope is damaged completely. Hence the space structure of taiga is the result, first of all, self development and self regulation of its vegetation cover. But, as it is known, at present time the process of destruction of natural biota has gone too far that the question arises not only about supporting its state and structure but also about the survival of the mankind itself. In this regard the vegetation map of Europe is the invaluable basis, which gives the starting point for all conservational, ecological and economical measures. But it is important to learn reading and using the map. And this is one of our actual goals.

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

Geobotanical mapping ◽

10.31111/geobotmap/1998-2000.26 ◽

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.

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