Will borealization of Arctic tundra herbivore communities be driven by climate warming or vegetation change?

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.

Download Full-text

Remote sensing assessment of glacial loss and vegetation change from 1989 to 2016: Pond Inlet, Nunavut

10.32920/ryerson.14667960.v1 ◽

2021 ◽

Author(s):

Ruby R. Pennell

Keyword(s):

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Relevant Literature ◽

Arctic Tundra ◽

The Arctic ◽

Landscape Changes ◽

Storm Events ◽

Time Period ◽

Induced Changes

The climate change phenomenon occurring across the globe is having an increasingly alarming effect on Canada’s Arctic. Warming temperatures can have wide spanning impacts ranging from more rain and storm events, to increasing runoff, thawing permafrost, sea ice decline, melting glaciers, ecosystem disruption, and more. The purpose of this MRP was to assess the climate-induced landscape changes, including glacial loss and vegetation change, in Pond Inlet, Nunavut. A time series analysis was performed using the intervals 1989-1997, 1997-2005, and 2005-2016. The two methods for monitoring change were 1) the Normalized Difference Snow Index (NDSI) to detect glacial change, and 2) the Normalized Difference Vegetation Index (NDVI) to detect vegetation change, both utilizing threshold and masking techniques to increase accuracy. It was found that the percent of glacial loss and vegetation change in Pond Inlet had consistently increased throughout each time period. The area of glacial loss grew through each period to a maximum of 376 km2 of glacial loss in the last decade. Similarly, the area of the Arctic tundra that experienced vegetation change increased in each time period to a maximum of 660 km2 in the last decade. This vegetation change was characterized by overall increasing values of NDVI, revealing that many sections of the Arctic tundra in Pond Inlet were increasing in biomass. However, case study analysis revealed pixel clustering around the lower vegetation class thresholds used to classify change, indicating that shifts between these vegetation classes were likely exaggerated. Shifts between the higher vegetation classes were significant, and were what contributed to the most change in the last decade. The observations of higher glacial melt and increases in biomass are occurring in parallel with the increasing temperatures in Pond Inlet. Relevant literature in the Arctic agrees with the findings of this MRP that there are significant trends of glacial loss and vegetation greening and many studies attribute this directly to climate warming. The results of this study provide the necessary background with regards to landscape changes which could be used in future field studies investigating the climate induced changes in Pond Inlet. This study also demonstrates that significant landscape modifications have occurred in the recent decades and there is a strong need for continued research and monitoring of climate induced changes.

Download Full-text

Does Climate Warming Stimulate or Inhibit Soil Protist Communities? A Test on Testate Amoebae in High-Arctic Tundra with Free-Air Temperature Increase

Protist ◽

10.1016/j.protis.2010.04.006 ◽

2011 ◽

Vol 162 (2) ◽

pp. 237-248 ◽

Cited By ~ 21

Author(s):

Andrey N. Tsyganov ◽

Ivan Nijs ◽

Louis Beyens

Keyword(s):

Air Temperature ◽

Climate Warming ◽

Temperature Increase ◽

Arctic Tundra ◽

Testate Amoebae ◽

High Arctic ◽

Free Air

Download Full-text

Links between spring snow cover and long-term alpine vegetation change

10.5194/egusphere-egu2020-8737 ◽

2020 ◽

Author(s):

Shengwei Zong ◽

Christian Rixen

Keyword(s):

Remote Sensing ◽

Snow Cover ◽

Plant Species ◽

Climate Warming ◽

Vegetation Change ◽

Alpine Vegetation ◽

Alpine Ecosystems ◽

Snow Cover Extent ◽

The Relationship

Snow is an important environmental factor determining distributions of plant species in alpine ecosystems. During the past decades, climate warming has resulted in significant reduction of snow cover extent globally, which led to remarkable alpine vegetation change. Alpine vegetation change is often caused by the combined effects of increasing air temperature and snow cover change, yet the relationship between snow cover and vegetation change is currently not fully understood. To detect changes in both snow cover and alpine vegetation, a relatively fine spatial scales over long temporal spans is necessary. In this study in alpine tundra of the Changbai Mountains, Northeast China, we (1) quantified spatiotemporal changes of spring snow cover area (SCA) during half a century by using multi-source remote sensing datasets; (2) detected long-term vegetation greening and browning trends at pixel level using Landsat archives of 30 m resolution, and (3) analyzed the relationship between spring SCA change and vegetation change. Results showed that spring SCA has decreased significantly during the last 50 years in line with climate warming. Changes in vegetation greening and browning trend were related to distributional range dynamics of a dominant indigenous evergreen shrub Rhododendron aureum, which extended at the leading edge and retracted at the trailing edge. Changes in R. aureum distribution were probably related to spring snow cover changes. Areas with decreasing R. aureum cover were often located in snow patches where probably herbs and grasses encroached from low elevations and adjacent communities. Our study highlights that spring SCA derived from multi-source remote sensing imagery can be used as a proxy to explore relationship between snow cover and vegetation change in alpine ecosystems. Alpine indigenous plant species may migrate upward following the reduction of snow-dominated environments in the context of climate warming and could be threatened by encroaching plants within snow bed habitats.

Download Full-text

Roots in the tundra : relations between climate warming and root biomass and implications for vegetation change and carbon dynamics

10.18174/385684 ◽

2016 ◽

Author(s):

Peng Wang

Keyword(s):

Climate Warming ◽

Root Biomass ◽

Vegetation Change ◽

Carbon Dynamics

Download Full-text

Using Long-Term SAR Backscatter Data to Monitor Post-Fire Vegetation Recovery in Tundra Environment

Remote Sensing ◽

10.3390/rs11192230 ◽

2019 ◽

Vol 11 (19) ◽

pp. 2230 ◽

Cited By ~ 1

Author(s):

Zhiwei Zhou ◽

Lin Liu ◽

Liming Jiang ◽

Wanpeng Feng ◽

Sergey V. Samsonov

Keyword(s):

Vegetation Change ◽

Vegetation Index ◽

Arctic Tundra ◽

Optical Observations ◽

Vegetation Recovery ◽

Vegetation Coverage ◽

Burned Area ◽

Strong Impact ◽

L Band ◽

Surface Vegetation

Wildfires could have a strong impact on tundra environment by combusting surface vegetation and soil organic matter. For surface vegetation, many years are required to recover to pre-fire level. In this paper, by using C-band (VV/HV polarization) and L-band (HH polarization) synthetic aperture radar (SAR) images acquired before and after fire from 2002 to 2016, we investigated vegetation change affected by the Anaktuvuk River Fire in Arctic tundra environment. Compared to the unburned areas, C- and L-band SAR backscatter coefficients increased by up to 5.5 and 4.4 dB in the severely burned areas after the fire. Then past 5 years following the fire, the C-band SAR backscatter differences decreased to pre-fire level between the burned and unburned areas, suggesting that vegetation coverage in burned sites had recovered to the unburned level. This duration is longer than the 3-year recovery suggested by optical-based Normalized Difference Vegetation Index (NDVI) observations. While for the L-band SAR backscatter after 10-year recovery, about 2 dB higher was still found in the severely burned area, compared to the unburned area. The increased roughness of the surface is probably the reason for such sustained differences. Our analysis implies that long records of space-borne SAR backscatter can monitor post-fire vegetation recovery in Arctic tundra environment and complement optical observations.

Download Full-text

Four decades of plant community change along a continental gradient of warming

10.1101/313379 ◽

2018 ◽

Author(s):

Antoine Becker-Scarpitta ◽

Steve Vissault ◽

Mark Vellend

Keyword(s):

Climate Warming ◽

Vegetation Change ◽

High Sensitivity ◽

Warming Trend ◽

Community Change ◽

Individual Species ◽

Eastern Canada ◽

Recent Warming ◽

Temperature Indices ◽

Distribution Shifts

AbstractMany studies of individual sites have revealed biotic changes consistent with climate warming (e.g., upward elevational distribution shifts), but our understanding of the tremendous variation among studies in the magnitude of such biotic changes is minimal. In this study we re-surveyed forest vegetation plots 40 years after the initial surveys in three protected areas along a west-to-east gradient of increasingly steep recent warming trends in eastern Canada (Québec). Consistent with the hypothesis that climate warming has been an important driver of vegetation change, we found an increasing magnitude of changes in species richness and composition from west to east among the three parks. For the two mountainous parks, we found no changes in elevational species’ distributions in the eastern most park where warming has been minimal (Forillon Park), and significant upward distribution shifts in the centrally located park where the recent warming trend has been marked (Mont-Mégantic). Community temperature indices (CTI), reflecting the average affinities of locally co-occurring to temperature conditions across their geographic ranges (“species temperature indices”), did not change over time as predicted. However, close examination of the underpinnings of CTI values suggested a high sensitivity to uncertainty in individual species’ temperature indices, and so a potentially limited responsiveness to warming. Overall, by testing a priori predictions concerning variation among parks in the direction and magnitude of vegetation changes, we have provided stronger evidence for a link between climate warming and biotic responses than otherwise possible, and provided a potential explanation for large variation among studies in warming-related biotic changes.

Download Full-text

The role of inland freshwaters in summer CO2, CH4 and N2O emissions from northeast Siberian Arctic tundra

10.5194/egusphere-egu2020-20028 ◽

2020 ◽

Author(s):

Melanie Martyn ◽

Joshua Dean ◽

Han Dolman ◽

Jorien Vonk

Keyword(s):

Climate Warming ◽

Ghg Emissions ◽

Arctic Tundra ◽

The Arctic ◽

Inland Waters ◽

N2o Emissions ◽

Emission Rates ◽

Study Region ◽

Degradation Rates ◽

Siberian Arctic

Inland waters can be significant sources of greenhouse gases (GHGs; CO2, CH4 and N2O) to the atmosphere, yet they are often excluded from terrestrial GHG balances. Vast stocks of carbon stored in Arctic tundra permafrost soils are vulnerable to mobilisation due to permafrost thawing accelerated by the amplified effects of climate warming at high latitudes. The carbon that is released becomes available to (partial) degradation producing GHGs which inland waters emit to the atmosphere, thus forming a positive feedback to climate warming. Rising temperatures, longer summers and increased precipitation in the Arctic tundra are expected to increase permafrost thaw and degradation rates, therefore the contribution of inland waters to the tundra terrestrial GHG budgets needs to be better understood to assess the strength and timing of the feedback effect in the future.Field data from lakes, ponds and streams throughout the summer season of three years and from floodplain water present in one of the years was collected. This data was used to calculate CO2 equivalent diffusive fluxes from inland freshwaters, and combined with eddy covariance flux tower measurements and with satellite remote sensing to calculate total GHG emissions of the study area.The results indicate that ponds are the largest contributors to upscaled inland water GHG emissions (around 50%) followed by streams and finally lakes. Streams had the highest emission rates followed by lakes and ponds the lowest, however due to the large surface area coverage of ponds (15% of the study area) they become the largest contributor to the upscaled freshwater GHG emissions. Upscaling of CH4 and CO2 fluxes shows that while the study region remains a GHG sink, inclusion of freshwater emissions reduces its sink capacity by 28% during our reference month July. Assuming that 10% of the study area is flooded in this month, it reduces the terrestrial GHG sink estimate to 45% instead of 28%, partially due to N2O oversaturation in the flood water in relation to the atmosphere whereas N2O concentrations in lakes, streams and ponds are close to zero. Overall the results show that if the Siberian Arctic tundra becomes wetter or more frequently flooded due to climate warming it will significantly affect the total terrestrial GHG balance.

Download Full-text

Trophic interactions and abiotic factors drive functional and phylogenetic structure of vertebrate herbivore communities across the Arctic tundra biome

Ecography ◽

10.1111/ecog.04347 ◽

2019 ◽

Vol 42 (6) ◽

pp. 1152-1163 ◽

Cited By ~ 3

Author(s):

James D. M. Speed ◽

Ina Åsnes Skjelbred ◽

Isabel C. Barrio ◽

Michael D. Martin ◽

Dominique Berteaux ◽

...

Keyword(s):

Trophic Interactions ◽

Abiotic Factors ◽

Arctic Tundra ◽

The Arctic ◽

Phylogenetic Structure ◽

Herbivore Communities

Download Full-text

Phenology and vegetation change measurements from true colour digital photography in high Arctic tundra

Arctic Science ◽

10.1139/as-2014-0003 ◽

2016 ◽

Vol 2 (2) ◽

pp. 33-49 ◽

Cited By ~ 5

Author(s):

Alison L. Beamish ◽

Wiebe Nijland ◽

Marc Edwards ◽

Nicholas C. Coops ◽

Greg H.R. Henry

Keyword(s):

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Image Data ◽

Arctic Tundra ◽

Digital Photography ◽

High Arctic ◽

Permanent Plots ◽

Moisture Conditions ◽

And Control

Manual collection of accurate phenology data is time-consuming and expensive. In this study, we investigate whether repeat colour digital photography can be used (1) to identify phenological patterns, (2) to identify differences in vegetation due to experimental warming and site moisture conditions, and (3) as a proxy for biomass. Pixel values (RGB) were extracted from images taken of permanent plots in long-term warming experiments in three tundra communities at a high Arctic site during one growing season. The Greenness Excess Index (GEI) was calculated from image data at the plot scale (1 × 1 m) as well as for two species, Dryas integrifolia and Salix arctica. GEI values were then compared to corresponding field-based phenology observations. GEI and Normalized Difference Vegetation Index (NDVI) values from a paired set of true colour and infrared images were compared with biomass data. The GEI values followed seasonal phenology at the plot and species scale and correlated well with standardized observations. GEI correlated well with biomass and was able to detect quantitative differences between warmed and control plots and the differences between communities due to site-specific moisture conditions. We conclude that true colour images can be used effectively to monitor phenology and biomass in high Arctic tundra. The simplicity and affordability of the photographic method represents an opportunity to expand observations in tundra ecosystems.

Download Full-text