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Lecture to the Masaryk Univ. Botany and Zoology Department (not one of the 6 Arctic Ecology lectures).

Lecture to the Masaryk Univ. Botany and Zoology Department (not one of the 6 Arctic Ecology lectures).

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  • This talk focus on factors that affect small patterned-ground forms and their interactions across a bioclimate gradient in northern Alaska and the western Canadian Arctic. This is a collaborative effort by team members of an NSF-funded biocomplextiy project.
  • Ground observations were conducted along two transects through all 5 Arctic bioclimate subzones as defined by the Circumpolar Arctic Vegetation Map (Walker et al. 2005). The subzones are defined by difference in the dominant plant growth forms on zonal sites and by the mean July temperatures.
  • The focus of this talk is the ground measurements of biomass, NDVI, and leaf area index and their correlations with observations from space mainly with the Advanced Very High Resolution Radiometer measurements.
  • This view of the Arctic was reconstructed from SSMI satellite imagery taken during the minimum sea ice event in September 2007, which was by far the least .extemt of ice recorded. It shows a large ice free area north of Alaska and much of eastern Russia in the Beaufort, East Siberia and Laptev Seas . Joey Comiso at NASA-Goddard has traced the extent of perennial ice since the beginning of satellite observations in 1980 and shows a -10.1% / decade decline in the extent of sea ice and an 11.4% decline in the area.
  • If the melting of the sea ice continues, we may see an ice free Arctic Ocean in late summer within our life times as portrayed on this vegetation map of the Arctic Tundra. What is striking in this polar view of the Arctic Tundra Biome is the close proximity of all the biome to the Arctic Ocean or seasonally frozen sea water. It really is a maritime biome. This map gives a good impression of just how closely tied the tundra biome is to the ocean. 61% of the tundra is within 50 km of sea ice (blue buffer), 80% is within 100 km (magenta and blue buffers), and 100% is within 350 km. Upland areas above 333 m (gray areas) were excluded from the analysis because these area experience sufficient adiabatic cooling to shift to colder elevation belts.
  • (Left) The best tools we have for looking at Arctic wide vegetation change are the multi-channel sensors aboard earth orbiting satellites that sense in the visible and near infrared portions of the electromagnetic spectrum. This graph shows the reflectance of several common ground cover types. Those types with a lot of chlorophyll have spectra similar to those shown by the red and green lines (alfalfa and maple trees). Green vegetation in general tends to reflect strongly in the near infrared portion of the spectrum apparently due to light scattering at the cell level within the leaves, and the amount of reflectance in the NIR varies considerably between species and can be used to help identify species. Chlorophyll also strongly absorbs light in the red portion of the spectrum. And the difference in the reflectance in the Infrared and Visible is an index of the amount of green vegetation in a given pixel. Normalizing by the sum of the NIR and VIS channel helps to account for the affects of shadows and the affects of different lighting on slopes. (Right) This circumpolar view of NDVI focuses on the tundra region. It was derived from images taken during two relatively warm years in the Arctic, and shows the Arctic a maximum greenness. Most other views have shown the tundra only as part of the global patterns, so variations within the tundra are minimized. This view shows the strong differences across the Arctic tundra zone. The blue colors a sparse vegetation generally found in the High Arctic, the greens and yellows indicate more peaty tundra types of the low arctic. The oranges and reds are the shrub tundras, many of which occur in permafrost free areas of the Arctic. As you can see there is a lot spatial variability in the NDVI. Some of these differences are caused by climate and some is caused by many other factors suc as areas of recent glaciation, mountain ranges, wetlands, and the influence of ocean and atmospheric circulation patterns. The greening of the Arctic project is focusing on the spatial variation of NDVI and “how has the patterned changed in recent years?”
  • This study by Jiong Jia prompted this interest in NDVI. The top graph traces the history of Maximum (Peak) NDVI values in the three major bioclimate subzones and the average for the entire Arctic Slope of Alaska. The bottom line in the top graph represents is the 20-yr record of MaxNDVI derived from AVHRR 8-km data in the coldest subzone near the coast and the top line is the warmest subzone in the foothills. The top blue line is the average Peak NDVI for the whole of the Arctic Slope. There is an average 17 ± 6% increase in NDVI across all of the Arctic Slope. Based on regressions of biomass vs. NDVI from the same study, this corresponds to about an average 170 g m-2 increase in biomass. The bottom graph shows the long-term temperature data from three stations in each of the subzones, Barrow in subzone C, Prudhoe Bay in subzone D, and Umiat in Subzone E. The shaded area corresponds to the same time interval shown in the top graph. And the red and blue arrows show positive and negative fluctuations in the yearly temperature which correspond to responses of the NDVI. These are the best data currently available that demonstrate a regional change in the vegetation over the past few decades. However, they are from only a small part of the Arctic, all of which is in the Low Arctic.
  • This study by Jiong Jia prompted this interest in NDVI. The top graph traces the history of Maximum (Peak) NDVI values in the three major bioclimate subzones and the average for the entire Arctic Slope of Alaska. The bottom line in the top graph represents is the 20-yr record of MaxNDVI derived from AVHRR 8-km data in the coldest subzone near the coast and the top line is the warmest subzone in the foothills. The top blue line is the average Peak NDVI for the whole of the Arctic Slope. There is an average 17 ± 6% increase in NDVI across all of the Arctic Slope. Based on regressions of biomass vs. NDVI from the same study, this corresponds to about an average 170 g m-2 increase in biomass. The bottom graph shows the long-term temperature data from three stations in each of the subzones, Barrow in subzone C, Prudhoe Bay in subzone D, and Umiat in Subzone E. The shaded area corresponds to the same time interval shown in the top graph. And the red and blue arrows show positive and negative fluctuations in the yearly temperature which correspond to responses of the NDVI. These are the best data currently available that demonstrate a regional change in the vegetation over the past few decades. However, they are from only a small part of the Arctic, all of which is in the Low Arctic.
  • There are no replicated long-term studies of tundra biomass or community composition that can be directly linked to the NDVI changes. Permanent vegetation study areas need to be established where the structure, composition, and biomass of the natural vegetation are sampled on a regular basis. Sampling areas need to be established across the Arctic with the focus on zonal vegetation, but also with consideration of other regionally important factors such as soil moisture and soil texture. These could be done in conjunction with ongoing studies of the International Tundra Experiment (ITEX), the Circumpolar Active Layer Monitoring (CALM) program, or other terrestrial research projects that are global in scale. . Greenness of the circumpolar tundra region, as mapped with the NDVI (Fig. 7), shows clear but complex patterns related to bioclimate zonation, mountains, soils, abundance of lakes, bedrock geology, and permafrost regimes. The relative roles of these interacting factors in affecting present-day NDVI patterns and patterns of temporal NDVI change need to be better understood. 3. It is not entirely clear how much of the change in NDVI has been due to calibration problems and/or changes in the atmosphere that would affect the NDVI. NASA has produced a new time series of global NDVI data from 1981-2003 that has been recalibrated and should be used to repeat the analyses conducted earlier. Other approaches would be to examine the historical NDVI records in regions that have been showing warming and cooling trends during the length of satellite-based observations. 4. Numerous lines of evidence point to recent greening and expansion of shrubs in northern Alaska, but the short-term of both the NDVI record (20 years) and the photographic record (50 years) make it impossible to determine if this is an extension of long-term changes that have been going on through the Holocene, or if the changes have been greater during the past few years. Studies linking NDVI to the paleo-record of change in the Arctic (e.g., Bigelow et al. 2003) would help in understanding the likely historic trends of NDVI. Models of predicted future changes to NDVI in response to climate change need to be developed based on past response and knowledge of how these responses vary regionally, particularly along the north-south Arctic bioclimate gradient, but also with respect to soil moisture gradients and other terrain variables mentioned above. 5. Changes in global patterns of tundra greenness are linked to a variety of geophysical and biological properties, such as changes to soil temperature regimes, snow regimes, changes to hydrological regimes, and decomposition rates. Continued experimental studies of the mechanisms involved in vegetation change such as those of the ITEX program (e.g. Hollister et al. 2005, Wahren et al. 2005, Walker, M.D. et al. 2005 in press) need to be closely linked to studies of NDVI, vegetation structure, and species composition. Finally, returning to the themes introduced at the beginning of this paper, in order to understand the relevance of these changes to the broader system, we need to link the observed changes in the patterns of NDVI to such things as the distribution and abundance of wildlife (e.g. Griffith et al. 2002), runoff to the Arctic Ocean, the active layer (e.g., Nelson et al. 1987), and the nature of the permafrost. We also need to specifically analyze and quantify the linkages between ongoing change in the arctic ocean, sea-ice, and terrestrial systems.
  • Much of the change in the Alaska is thought to be due to changes in shrub cover. Ken Tape, Matthew Sturm and Chuck Racine have shown Over 30% increase in shrub cover on stable valley slopes dramatic increase in shrub cover on river terraces, colonization by new alders. less cover of sandbars, more vegetation in river floodplains
  • We had these two primary questions: How do biological and physical processes interact to form the patterned ground ecosystems? How do these systems change across the Arctic climate gradient?
  • Why focus on small patterned-ground features? The processes involved in the formation of patterned-ground landscapes are not well understood. The importance of patterned ground with respect to biogeochemical cycling, carbon sequestration and other ecosystem processes is poorly known. They are an ideal natural system to to help predict the consequences of climate change of disturbed and undisturbed tundra.
  • Why focus on small patterned-ground features? The processes involved in the formation of patterned-ground landscapes are not well understood. The importance of patterned ground with respect to biogeochemical cycling, carbon sequestration and other ecosystem processes is poorly known. They are an ideal natural system to to help predict the consequences of climate change of disturbed and undisturbed tundra.
  • The patterned ground forms change along the transect in a predictable way. This diagram of the changes on zonal surfaces along the climate gradient is adapted from Nadya Matveyeva’s work that described the transitions on the Taimyr Peninsula in Russia. Her conceptual model also fits the situation in North America quite well. Generally, at the northern end of the transect we see a dominance of small non-sorted polygons formed by cracking processes. Toward the middle of the transect, we see larger features that are formed by differential frost heaving with a strong increase in the amount of vegetation particularly around the margins of the heave features. And in the southern part of the gradient, vegetation overtops the features.
  • Plant cover: Insulates the surface decreasing the heat flux and summer soil temperatures. stabilizes cryoturbation and limits needle-ice formation. Promotes nitrogen and carbon inputs to the soil. The effect of vegetation on patterned ground morphology increases toward the south.
  • These are maps of three of the grids that show the vegetation, active layer and snow depths There are two posters that will be presented tomorrow that show the trends in the vegetation and morphology of patterned ground along the transect. Corinne Munger’s poster presents the maps and analysis. Martha Raynolds poster presents many photographs of the patterned ground forms along the temperature and moisture gradients.
  • Biomass affects NDVI along the transect. The NDVI is a measure of vegetation greenness that is derived from the difference in the reflectance of plants in the red and near-infrared portions of the electromagnetic spectrum. More dense vegetation generally has higher NDVI values. These graphs show some of the work of Howie Epstein and Alexia Kelley: T he upper graph shows that there is about a 2-fold increase in the average NDVI of vegetation on zonal surfaces along the transect, with quite a bit of scatter. Much of the scatter is due to small-scale variations caused by patterned ground. The lower graph shows the NDVI on and between patterned ground features. The contrast in NDVI on patterned ground features (gray bars) vs. the tundra between features (green bars) decreases toward the south.
  • Plant cover affects the morphology of patterned ground in two primary ways: 1. Insulates the surface decreasing the heat flux and summer soil temperatures. 2. Stabilizes the soils and limits cryoturbation and needle-ice formation. Promotes nitrogen and carbon inputs to the soil. The effect of vegetation on patterned ground morphology increases toward the south.
  • Extraordinarily Sensitive Permafrost Landscapes: Extensive nutrient-poor surface sands with lichens that are easily overgrazed by reindeer. Underlain by permafrost with massive pure ice. Extensive landslides are rapidly eroding the landscape. This exposes salt-rich and nutrient-rich clays. Complex vegetation succession process that results in willow-shrub tundra in the interior parts of the peninsula.
  • Willow communities on old landslides at Vaskiny Dachi Low-willow shrublands develop on landslides during 200-yr succession, greatly changing biomass and NDVI.
  • SnowDrainageNetwork: d9009DSC_0755.jpg Small drainage with snow and willows: d9009DSC_0457.jpg Green drainage networks: d9009DSC_0976.jpg Detail of Russian satellite image with snow in drainages: DetailRussianSatellite imageWithSnowInDrainages.png (GOA/NASA_LCLUC_NEESPI/2010RovaniemiWorkshop/SkipRovaniemiTalk/RovaniemiTalkPhotos/DisturbedAreas
  • There are numerous effects of all these animals, including Overgrazing and Trampling of the vegetation Transformation of previous sedge and shrub-dominated tundra vegetation into grasslands Wind erosion of the some of he trampled areas. Some of these effects are be quantified using remote sensing tools by Timo Kumpula
  • The changes in willow growth are affecting reindeer management. If they grow over ≈ 2 m high, herders can lose sight of animals. Extensive willow shrublands are avoided during migration..
  • A large portion of the summer pastureland land of both of these brigades is no longer available to them. In general the Nenets see the changes going on due to both resource extraction and climate change. They recognize the threat of resource extraction to be a much greater threat than that of climate change. But there are also positive aspects of the resource development. In general the herders view the gas field activity positively because the influx of gas field workers provide a market for their reindeer that did not previously exist.
  • The results from the expedition were summarized in a data report that is available on line.
  • Especially our Russian colleagues who have made the Eurasia transect possible. In August 2010 we completed the second of the transects with an expedition to Franz Josef Land in northern Russia. This gave us observations from Bioclimate subzone A in Eurasia to compare with results from the same subzone in Canada. Other members of the team also drilled the northernmost permafrost borehole at 80˚ 37’ N.
  • The map in the lower left shows the location of the North America and Eurasia Arctic transects. North America Arctic Transect: Completed in 2006 as part of the Biocomplexity of Arctic Patterned Ground Ecosystems Project (NSF). Eurasian Arctic Transect: Field seasons in 2007-2010 (NASA).
  • The areas that we looked at on the ground were mainly zonal sites, those where the soils and vegetation correspond to the long-term climatic climax. These photos show representative sites along the Eurasia and North America transects in each bioclimate subzone.
  • Our goal was to correlate the NDVI patterns with other remote sensing data such as the summer warmth index derived from the AVHRR thermal bands and a variety of the other information such as that contained in the Circumpolar Arctic Vegetation Map GIS data base.
  • The biomass data from the transects were examined in a couple of ways. The first is a plot-level determination, which is the of the clip harvest data from the zonal plots at each sample location. Both transects show the general expected pattern of increased biomass along the bioclimate gradient, but there are also major differences related to differences in substrate, precipitation, and relative position of the locations within each subzone.
  • Some of the most important differences appear to be related to differences in disturbance regimes. For example, along the NAAT there is much more evergreen-shrub and lichen biomass. This could be the result of the much more intensive grazing pressure by reindeer along the the EAT. This phenomenon occurs across most of the Russian Arctic causing major differences in the structure of the vegetation.
  • Hand-held measurements of NDVI also had different values for equivalent levels of biomass and LAI along both transects, probably reflecting the the different structure of the vegetation.
  • These differences in structure are also evident in the LAI-Biomass relationship along both transects. An equivalent amount of biomass has consistently much higher LAI values along the NAAT than along the EAT and the difference increases at higher biomass values
  • These differences are reflected in graphs of the AVHRR-NDVI and biomass vs. summer warmth. The biomass shown here is a slightly different number which is a landscape-level of biomass that is derived from the biomass data in combination with detailed vegetation maps. In general the EAT is greener than the NAAT in equivalent climates.
  • In spite of the structural and composition differences between the transects, there is overall a very strong relationship between 1-km AVHRR NDVI values and biomass along both transects and in the combined data set.
  • This gives us quite a bit of confidence that we can extrapolate the the zonal landscape-level biomass values from the transect to the broader Arctic using the AVHRR data.
  • We have also examined the temporal relationships of the AVHRR NDVI compared to the coastal sea ice trends and summer land surface temperature trends. Uma Bhatt published a key paper this year that showed the strong year-to-year circumpolar correlations between coastal sea-ice, land temperatures, and NDVI values. This has now been updated with a new NDVI data set provided by Jorge Pinzon and Jim Tucker at NASA-Goddard. The two graphs in the lower right show the 1982-2010 trends in NDVI along the two transects. Several things are worth noting: The trend in tundra NDVI peaked in 1989 along the Yamal transect and 2004 along the North America Transect. Since 2004 it has been declining along both transects. A particular strong dip occurred in 2009. This occurred in every area of the Arctic. In western Eurasia, a further dip occurred in 2010. The trend along the Kara has been almost flat especially since 1990, when it reached its highest value, whereas the trend in North America has been a remarkable 24%.
  • Broad similarities in biomass between North America and Eurasia along Arctic temperature gradient, but also major differences likely related to different disturbance regimes, geology, and precipitation patterns. Very good correlation between AVHRR NDVI and zonal landscape-level biomass. Analysis of Landsat-derived NDVI trends for a similar period did not provide corroboration for magnitude of 1982-2010 NDVI change indicated by GIMMS 3g. AVHRR NDVI is still one of the best tools we presently have for looking at long-term terrestrial response to climate change. It is highly correlated with a wide variety of the biophysical properties, but we need better calibration of remote sensing data sets and ground measurements to give us confidence in the indicated temporal trends.
  • This project is a joint collaboration by three groups of institutions in the U.S., Russia and Finland. Five funded projects were collaborating in the project including. The primary logistic funding came from NASA and NSF in the U.S. and the Russian Academy of Science in Russia.

Bot deptlecture20110310(1) Bot deptlecture20110310(1) Presentation Transcript

  • Arctic vegetation along two long bioclimatic transects in North America and Russia Prof. D.A. (Skip) Walker, Fulbright Scholar Alaska Geobotany Center, Institute of Arctic Biology, University of Alaska Fulbright Lecture Masaryk University, 10 March 2011
  • Overview of talk
    • Introduction:
    • Rationale for the two transects: The international Polar Year and the Greening of the Arctic IPY project.
    • Overview of the two transects:
    • The North America Arctic Transect and the Biocomplexity of Patterned Ground project.
    • The Eurasia Arctic Transect the remote sensing objectives.
    • Toward a synthesis of results from the two projects:
    • Spatial and temporal patterns of circumpolar NDVI and biomass.
  • The International Polar Year (2007-2009)
    • The International Polar Year is a large scientific programme focused on the Arctic and the Antarctic from March 2007 to March 2009, currently still in its synthesis phase.
    • Organized through the International Council for Science (ICSU) and the World Meteorological Organization (WMO)
    • The fourth polar year. Others were in 1882-3, 1932-3, and 1957-8.
  • IPY goals
    • An intense scientific campaign to explore new frontiers in polar science.
    • Improve our understanding of the critical role of the polar regions in global processes.
    • Educate the public about the polar regions.
    • Projects were expected to be interdisciplinary in scope; involve a pulse of activity during the IPY period; leave a legacy of infrastructure and data; expand international cooperation; engage the public in polar discovery; and help attract the next generation of scientists and engineers. 
  • Research supported
    • Understanding Environmental Change: Research that advances the understanding of the physical, geological, chemical, human, and biological drivers of environmental change at the poles, their relationship to the climate system, their impact on ecosystems, and their linkages to global processes.
    • Human and Biotic Systems in Polar Regions: Research to address fundamental questions about social, behavioral, and/or natural systems that will increase our understanding of how humans and other organisms function in the extreme environments of the polar regions.
    • 60 countries involved: Czech Republic was one!
  • Honeycomb chart of IPY projects
    • Over 200 projects, with thousands of scientists from over 60 nations examining a wide range of physical, biological and social research topics at both poles.
    Greening of the ArctIc
  • Greening of the Arctic IPY intiative
    • Documenting, mapping and understanding the rapid and dramatic changes to terrestrial vegetation expected across the circumpolar Arctic as a result of a changing climate.
    • Comprised of four projects:
      • North America Arctic Transect
      • Land-cover and land-use changes on the Yamal Peninsula
      • Synthesis of Arctic System Science: Greening of the Arctic
      • Toolik-Arctic Geobotanical Atlas
  • Two transects through all 5 Arctic bioclimate subzones Bioclimate subzones Sub- Zone MJT Shrubs A 1-3 ˚C none B 3-5 ˚C prostrate dwarf-shrubs C 5-7 ˚C hemi-prostrate dwarf shrubs D 7-9 ˚C erect dwarf-shrubs E 9-12 ˚C low-shrubs
    • Along the tundra bioclimate gradient :
      • 10˚ C change in the MJT,
      • 10-fold change in zonal biomass,
      • 10-fold change in productivity,
      • 5 to 10-fold change in vascular-plant diversity.
    CAVM Team 2003
  • Major goal of the Greening of the Arctic project: Link spatial and temporal trends of NDVI observed on AVHRR satellite images to ground observations along both transects.
    • Climate
    • Vegetation
    • Soils
        • Permafrost
        • Spectral properties
    5 N-factor Biomass Plant species cover NDVI and LAI Active layer depth Soil characterization Site characterizatiion Permafrost boreholes
  • Focus of this talk
      • North America Arctic Transect
      • Land-cover and land-use changes on the Yamal Peninsula
  • Trend in Arctic sea-ice Since 1980, perennial sea ice extent in the Arctic has declined at the rate of 10.1% per decade, and area trend is -11.4% decade. 2007 2007 minimum sea-ice extent, 4.5 million km2. NSIDC. Comiso et al. 2008, Geophysical Research Letters 35: L01703.
  • The Arctic tundra is a maritime biome
    • 61% of the tundra is within 50 km of sea ice (blue buffer).
    • 80% is within 100 km (magenta and blue buffers).
    • 100% is within 350 km (all colors).
    • Changes in the Arctic ocean sea ice will very likely affect terrestrial ecosystems.
    Map by Hilmar Maier. Walker, D. A., 2005. The Circumpolar Arctic Vegetation Map. Journal of Vegetation Science.
  • Normalized Difference Vegetation Index (NDVI): An index of greenness CAVM Team. 2003 In general, land cover with high reflectance in the NIR and low reflectance in the visible portion of the spectrum has dense green vegetation. Reflectance spectra of common ground-cover types Normalized Difference Vegetation Index NDVI = (NIR - VIS) / (NIR + VIS) NIR = spectral reflectance in the near-infrared band (0.7 - 1.1µm), where light scattering from the cell-structure of the leaves dominates. VIS = reflectance in the visible, chlorophyll-absorbing portion of the spectrum (0.4 to 0.7µm). Circumpolar patterns of NDVI
  • Time series of peak NDVI for northern Alaska (1981-2001) Jia et al. 2003 Geophysical Research Letters. 30: 2067.
    • 17 ± 6% increase in peak NDVI from 1981-2001.
    • Available biomass data indicate that this increase in NDVI corresponds to about a 150 g m-2 increase in biomass.
    • Changes in NDVI show a long term increase and also some correspondence to yearly fluctuations in temperature.
    NDVI vs. Time in Bioclimate Subzones C, D, and E Temperature vs. Time in Subzones C, D, and E
  • Time series of peak NDVI anomalies in the tundra and boreal forest (1981-2005) Bunn et al. 2007. EOS. Northern high latitude ecosystems respond to climate change. 88: 333-335.
    • 88% of the region is shows no significant trends in NDVI. 3% have decreasing trends, and 9% have increasing trends.
    • Most of the positive changes are in tundra areas, particularly in North America.
    • Forest areas are showing an overall decline in NDVI.
    Green: increasing NDVI Red: decreasing NDVI White: no trend
  • Skepticism regarding the NDVI trends
        • “ Should we believe in the NDVI trend? There are no “ground truth” measurements of photosynthesis at northern high latitudes over the same period, and so the accuracy of the trend cannot be established unambiguously…. It will be a challenge for ecologists to explain how photosynthesis could possibly have increased by approximately 10% from 1981 to 1991.” (Inez Fung 1997)
        • At the time of Inez Fung’s statement the causes of variation of NDVI within the Arctic as well as seasonality of NDVI had not been examined.
        • The relative roles of interacting factors (e.g., climate, sea-ice distribution, elevation, glacial history, substrate chemistry, water regimes) need to be better understood. Is the current trend still partially a long-term response from the last glaciation?
        • There are virtually no long-term biomass data to support or dispute the trends shown by NDVI.
  • There still is not a lot of direct evidence for change in Arctic vegetation. Photo – M. K. Raynolds
    • Mostly experimental evidence;
      • Green-house experiments (Chapin et al.)
      • ITEX experiments
    • One long-term biomass study of Shaver at Toolik Lake that is suggestive of change but inconclusive.
    • Photo record of shrub cover change in northern AK (Matthew Sturm, Ken Tape, and Chuck Racine):
      • Over 30% increase in alders on some stable valley slopes in the warmest parts of the Arctic.
      • Dramatic increase in shrub cover on river terraces.
    This is changing. In the past year, there have been several major syntheses from international research projects that are examining change. And these will be published soon.
  • GOA studies are focused along two Arctic transects. CAVM Team. 2003 Transects in North America and Eurasia through all five bioclimate subzones as portrayed on the CAVM. Two Arctic Transects
  • NAAT was created during the Biocomplexity of Patterned-Ground project Howe Island, AK. Photo; D.A. Walker
    • How do biological and physical processes interact to form small patterned- ground ecosystems?
    • How do patterned-ground processes vary across the Arctic climate gradient?
    Walker et al. 2008, JGR
  • Why focus on these dumb spots?
    • WELL, BECAUSE:
    • The processes involved in the formation of patterned-ground landscapes are not well understood.
    • The importance of patterned ground with respect to biogeochemical cycling, carbon sequestration and other ecosystem processes is poorly known.
    • They are an ideal natural system to to help predict the consequences of climate change of disturbed and undisturbed tundra across the full Arctic climate gradient.
  • IPY objectives of the North America Arctic Transect
    • Create a legacy dataset of baseline information along the North American Arctic Transect (NAAT) that represents the full range of zonal vegetation types in the Arctic.
    • Communicate the results of the studies through a three-part education/outreach component that includes an Arctic Field Ecology course, contributions to a new “Arctic Geobotanical Atlas” web site, and a field trip for the 9th International Conference on Permafrost.
    Biomass, leaf-area, spectral data and other site information were collected from each site to provide a baseline against which to monitor future changes.
  • North American Arctic Transect Dalton Highway (7 locations) Arctic Bioclimate Subzones Canada Sub-zone MJT (˚C) SWI (˚C mo) A <3 <6 B 3-5 6-9 C 5-7 9-12 D 7-9 12-20 E 9-12 20-35 Forest >12 >35
  • North American Arctic Transect Activities
    • CALM Grids
      • Active layer
      • Vegetation
      • Snow
    • Climate /permafrost
      • Met station
      • Soil temperatures
      • Frost heave
    • Soils
      • Characterization
      • Nitrogen mineralization
      • Decomposition
    • Vegetation
      • Classification
      • Biomass
      • Mapping
    • Remote sensing
      • NDVI
      • Mapping
    • Modeling
    • Education
    Isachsen Grid, Subzone A Photo D.A. Walker
  • Biocomplexity grids
    • Subzone A:
    • Satellite Bay, Canada - 1
    • Isachsen, Canada - 3 planned
    • Subzone B:
    • Mould Bay, Canada - 2
    • Subzone C:
      • Howe Island, Alaska - 1
      • West Dock, Alaska - 1
      • Green Cabin, Canada - 3
    Happy Valley Grid
    • Subzone D:
      • Deadhorse, Alaska - 1
      • Franklin Bluffs, Alaska - 3
      • Sagwon MNT, Alaska- 2
      • Ambarchik, Russian - 1
    • Subzone E:
      • Sagwon MAT, Alaska - 1
      • Happy Valley, Alaska - 3
      • Kurishka, Russia - 1
    • TOTAL 20 + (3 planned) = 23
  • Trend in patterned-ground along the Arctic bioclimate gradient Sub- zone: A B C D E Drawings modified from Chernov and Matveyeva 1997 Small non-sorted polygons Non-sorted circles Earth hummocks
  • Subzone A Isachsen, Ellef Ringnes Island, mean July temperature = 3 ˚C, SWI = 4 ˚C mo
  • Subzone C Howe Island, Ak and Green Cabin, Banks Island, MJT, 8 ˚C, SWI = 16 ˚C mo
  • Subzone E Tuktuyaktuk, NWT, Happy Valley, AK, MJT = 12 ˚C, SWI = 30 ˚C mo
  • Vegetation component
  • The roles of vegetation in patterned formation
    • Plant cover:
    • Insulates the surface decreasing the heat flux and summer soil temperatures.
    • stabilizes cryoturbation and limits needle-ice formation.
    • Promotes nitrogen and carbon inputs to the soil.
    Bill Steere collecting Bryum wrightii on a frost boil at Prudhoe Bay, July, 1971. N, Matveyeva - Map and drawing of frost boil vegeation on the Taimyr Peninsula, Russia.
  • Martha Raynolds Anja Kade Vegetation mapping and analysis of of active-layer/heave/vegetation relationships
  • Maps of vegetation, biomass, active layer and snow depth
    • Raynolds et al. 2008 JGR -Biogeosciences
    • Maps are from representative zonal sites in each bioclimate subzone.
  • Trends in biomass, snow depth, and thaw on zonal grids Subzone Biomass Active Layer Snow depth Active Layer Subzone
    • Both biomass and snow depth depth increase toward the south and both have major effects on soil temperature regimes.
    Raynolds et al. 2008, JGR-Biogeosciences
  • NDVI along the NAAT
    • 2-fold increase of the NDVI on zonal surfaces.
    • 6-fold difference in NDVI on PGFs.
    • 2-fold difference in NDVI between PGFs.
    Random hand-held NDVI on zonal surfaces along the temperature gradient (no attention to PGFs) NDVI of patterned-ground features and nearby tundra along the gradient Courtesy of Howie Epstein and Alexia Kelley I A I B I C I D I E I
  • Classification of patterned-ground vegetation along the NAAT
    • Used the Braun-Blanquet appraoch.
    • Low Arctic: Kade, A., Walker, D.A., and Raynolds, M.K., 2005, Plant communities and soils in cryoturbated tundra along a bioclimate gradient in the Low Arctic, Alaska: Phytocoenologia, v. 35, p. 761-820.
    • High Arctic: Vonlanthen, C.M., Walker, D.A., Raynolds, M.K., Kade, A., Kuss, H.P., Daniëls, F.J.A., and Matveyeva, N.V., 2008, Patterned-ground plant communities along a bioclimate gradient in the High Arctic, Canada: Phytocoenologia, v. 38, p. 23-63.
    Plant communities Soil and site data
  • Plant species and cover information for each plant community Kade et al. 2005, Plant communities and soils in cryoturbated tundra along a bioclimate gradient in the Low Arctic, Alaska. Phytocoenologia , 35: 761-820. Plant community table (cover) Classification according to Braun-Blanquet approach
  • Frost-boil plant communities, soil and site information Kade et al. 2005, Plant communities and soils in cryoturbated tundra along a bioclimate gradient in the Low Arctic, Alaska. Phytocoenologia , 35: 761-820. Plant communities Soil and site data
  • Landscapes in the Low Arctic examined by Anja Kade et al. (2005) Photos by A. Kade Howe Island Subzone C Deadhorse Subzone D Happy Valley Subzone E
  • Summary of plant communities for the Low Arctic part of the transect Kade et al. (2005) Of these, Anja described 5 communities occurring on patterned-ground features and 4 zonal communities occurring between patterned-ground features or on sites without patterned ground.
  • Somewhat different approach than previous studies
    • Matveyeva (1998) considered the patterned-ground features and areas between patterned-ground features as part of the same associations.
    • We felt that this violates the site homogeneity requirement of the Braun-Blanquet approach.
    • Besides, we needed to examine the plant community and site characteristics of the patterned-ground features separately to determine biomass, the effects on the microclimate, thermal properties of the soils, and effects on the soils, and permafrost regimes.
  • Contrast in vegetation on and between frost features Kade et al 2005 Deadhorse Subzone C Braya purpurascens-Puccinellia angustata community Dryas integrifolia-Salix arctica community Nonsorted Circle Between Circles
  • Contrast in vegetation on and between frost features Kade et al 2005 Franklin Bluffs Subzone D Junco biglumis-Dryadetum integrifoliae typicum subass. nov. Dryado integrifoliae-Caricetum bigelowii Walker et al. 1994 Nonsorted Circle Between Circles
  • Contrast in vegetation on and between frost features Kade et al 2005 Happy Valley Subzone E Nonsorted Circle Between Circles Cladino-Vaccinietum vitis-idaeae ass. nov. Sphagno-Eriophoretum vaginati Walker et al. 1994
  • Plant species and cover information for each plant community Kade et al. 2005, Plant communities and soils in cryoturbated tundra along a bioclimate gradient in the Low Arctic, Alaska. Phytocoenologia , 35: 761-820. Plant community table (cover) Classification according to Braun-Blanquet approach
  • DCA ordination and biplot of Low Arctic vegetation plots Subzone C Subzone E ∂ Subzone D ∂ ∂ ∂ Patterned-ground features Between pgf Kade et al 2005
  • Species richness and cover Kade et al 2005
    • Species richness peaks in subzone D in both micro-habitats (155 species in zonal sites and 165 on the pattterned ground features).
    • Cover values were greatest between the patterned ground features except in subzone E.
  • Selected soil physical properties
  • Selected soil chemical properties for
  • Ordination of zonal patterned ground vegetation: controlling environmental gradients along the full gradient
    • NMDS ordination.
    • Clear gradient of vegetation response to cryoturbation within each subzone and clear floristic separation between subzones.
    • But no clear overall controlling factors for the whole data set.
    • Floristic separation between Alaska and Canada portions of the gradient due to different floristic provinces, and substrate differences.
    Patterned-ground features Between patterned-ground features Intermediate Walker, D.A., Kuss, P., et al., 2011 (in revision), Vegetation and patterned-ground relationships along the Arctic bioclimate gradient in North America Applied Vegetation Science.
  • Four models of patterned ground formation Coupled Water-Ice-Temperature / ArcVeg model, Daanen et al. 2008 JGR Conceptual model of frost-boil and hummock formation, Shur et al. 2008, NICOP proceedings Differential frost-heave model Peterson and Krantz, JGR 2008 Thermo-mechanical model, Nicolsky et al., JGR 2008 Each provides a unique perspective.
  • Conclusions from the NAAT: Still a work in progress
    • The structure of the vegetation affects patterned-ground morphology on zonal sites in predictable ways that vary with differences in climate, soil-moistur and soil-texture.
    • Contrasts in the vegetation on and between patterned-ground features is best developed in Subzones C and D. These differences drive the movement of heat and water and the development of frost heave.
    • New and improved models are needed to better understand the interactions the physical and biological processes in patterned-gound formation.
    • More replication is needed and more sampling in different habitats, e.g. wetlands.
  • Synthesis of information from the North American Arctic Transect
    • Synthesis of the project published in special issue of Journal of Geophysical Research - Biogeosciences:
      • 9 papers from the North American Arctic Transect.
      • 5 papers from the Thule, Greenland biocomplexity project (Welker et al).
    • 21 collaborators.
    Walker, D. A. et al. 2008. Arctic patterned-ground ecosystems: a synthesis of field studies and models along a North American Arctic Transect. Journal of Geophysical Research - Biogeosciences 113:G03S01, doi10.1029/2007JG000504.
  • Expeditions and Timeline: Dalton Highway: 2001-2002 Green Cabin: 2003 Mould Bay: 2004 Isachsen: 2005 Synthesis: 2006-2008 2001-02 2003 2004 2005
  • Field Camp at Green Cabin, Banks Island
  • The Eurasia Arctic Transect: Vegetation Analysis and Mapping D.A. Walker, H.E. Epstein, H. A. Maier, G.V. Frost, M.K. Raynolds, U.S. Bhatt, J. Comiso, R. Daanen, D.S. Drozdov, B. Forbes, A.A. Gubarkov, G. Jia, E. Kaarlejarvi, O. Khitun, A.V. Khomutov, P. Kuss, M.O. Leibman, G. Matyshak, N.G. Moskalenko, P. Orekhov, J.E. Pinzon, V.E. Romanovsky, C.J. Tucker, N.G. Ukraintseva, Q. Yu Yamal Peninsula, Russia. Photo: D.A. Walker
  • Overview of EAT effort
    • Hierarchical mapping analysis
      • AVHRR (1 km 12.5 km and 50 km)
      • Landsat ETM+ (15 m and 30 m)
      • GeoEye(40-cm resolution)
      • Hand-held measurements of NDVI
    • Ground observations along the climate gradient
      • Data collected and data report
      • Vegetation analysis
    • Analysis of the linkages between climate change, sea-ice retreat and changes in the terrestrial vegetation.
  • The Eurasia Arctic Transect
    • About 2000 km from 65˚ 19’ N to 80˚ 38’.
    • Subzone A: Krenkel, Franz Josef Land
    • Subzone B: Ostrov Belyy
    • Subzone C: Kharasavey
    • Subzone D: Vaskiny Dachi
    • Subzone E: Laborovaya
    • Forest-tundra transition: Nadym and Kharp
    • Four expeditions (2007-10).
  • Much of project focuses on greenness patterns and change using the Normalized Difference Vegetation Index (NDVI)
    • Chlorophyll absorbs red light for photosynthesis and reflects near infrared light.
    • NDVI = (NIR-R)/(NIR + R) . The difference between the reflectance in the NIR and R portions of the spectrum is a measure of the photosynthetic capacity of the surface. The difference is divided by the sum of the reflectances to adjust for variations in the index due to slope and shadows.
    • NDVI is much greater in vegetation with high chlorophyll content.
    Plants absorb red light and reflect NIR radiation.
  • A hierarchical approach to examining greenness patterns and change
    • Plant- to plot-scale:
      • Ground measurements of 5 x 5 m plots.
      • Quickbird 60-cm pan-sharpened pixel size.
    • Landscape- to Regional-scale:
      • Yamal 1-km AVHRR data from CAVM.
      • Landsat ETM 30-m pixel size (USGS GLS 1990).
    • Global scale:
      • Global 12.5 km data: NDVI (Pinzon).
      • Global sea-ice, land-temperature and NDVI data: 25-km pixels based on Comiso sea-ice and temperature and cubic convolution of 8-km GIMMS NDVI.
  • Multiple-scale analysis of Yamal NDVI: 1-km AVHRR NDVI derived from CAVM data set
    • USGS data set used for the CAVM
    Circumpolar MaxNDVI
    • Calibrated NDVI to biomass using the zonal biomass values from the Yamal.
    • More biomass information is needed from shrublands and cryptogamic tundra areas.
    Courtesy of M.K. Raynolds. 2010.
  • Analysis of 1-km NDVI with Landschaft and CAVM map units
    • Loamy uplands have higher NDVI than sandy uplands. Landschaft does not delineate some known sandy areas (e.g. O. Belyy).
    • Broad river channels have highest NDVI despite large amount of lakes in the valleys.
    • 1-km data is not fine enough to resolve the greening patterns within the highly eroded upland areas.
    Courtesy of M.K. Raynolds. 2010. NDVI with Landschaft boundaries NDVI on marine terrace uplands and drainages of differing soil texture
  • Enhanced TM (15-m) derived maps of Ostrov Belyy
    • Maier and Walker. 2010. Poster at 2 nd Yamal LCLUC Workshop
    False-color image
    • 15-m resolution panchromatic band is used to enhance the 30-m resolution TM data.
    • Single ETM+ scene covers all of Ostrov Belyy.
    • Unsupervised classification used 15 spectral clusters. Salt marshes classified separately
    • NDVI map shows clear relationship of productivity with respect soil moisture (predominantly moist loamy soils in the north vs. dry sandy soils in the south).
    Land-cover map NDVI map
  • Land-cover mapping with 30-m Landsat TM data
    • Maier and Walker. 2010. Poster at 2nd Yamal LCLUC Workshop
    GLS-1990 mosaic Land-cover maps of Yamal study locations
    • Landsat mosaic provides intermediate-resolution terrain information of the whole peninsula.
    • Mosaic is composed of many scenes with different acquisition dates (May to September). Difficult to get consistent land-cover classification or MaxNDVI for the whole peninsula.
    • Land-cover maps produced separately for each LCLUC location.
    • May be possible to get consistent classification for whole area by combining all decadal and mid-decadal mosaics to get one coverage displaying MaxNDVI for all pixels.
  • 1. Extensive nutrient-poor surface sands with lichens that are easily overgrazed by reindeer. 2. Underlain by permafrost with massive pure ice. 3. Extensive landslides are rapidly eroding the landscape. 4. This exposes salt-rich and nutrient-rich clays. 5. Complex vegetation succession process that results in willow-shrub tundra and much greener vegetation in the eroded valleys. High-ice Permafrost Landscapes Photos: D.A. Walker and M. Liebman (upper right)
  • Extensive azonal willow shrublands due to landslide disturbances Greening associated with eroded sandy uplands
  • Landslides and cryogenic erosion Photos D.A. Walker Strong greening on landslide slopes cover extensive areas of the Yamal.
    • Large effect on patterns of greenness in many areas.
    • Need temporal series of high-resolution satellite images and/or photos in landslide areas to assess the rate of change.
    Key: A – stable areas B – shear surface C – landslide body Before landslides After landslides Low-willow shrublands develop on landslides during 200-yr succession, greatly changing biomass and NDVI. Ukraintseva and Leibman et al. 2000, 2007, 2008 Biomass 1 – young landslide 2 – old landslide 3 – very old landslide
  • Snow, hydrology, NDVI relationships in landslide areas RESURS-01 image, spring, unknown date
    • Expansion of the major river valleys and mosaic of smaller drainages is occurring very rapidly.
    • Need better understanding of the rate of growth of the drainage networks.
    • Need models and high-resolution imagery to address expansion of drainage networks
  • New High Resolultion GeoEye image of Vaskiny Dachi area clearly shows erosion patterns Vaskiny Dachi
    • 0.41 meter resolution!
  • Erosional patterns are clearly discernable on GeoEye scene. Vaskiny Dachi Should permit analysis of rate of erosion and related greening.
  • Other factors affecting greenness patterns: (1) 300,000 reindeer on the Yamal Photos: Bruce Forbes. Overgrazing Trampling Grassification Wind erosion
      • Effects on reindeer on NDVI are unknown at present because of lack of control areas to study the effects (exclosures).
      • Potential major effect in sandy areas.
  • Nenets camp on Yamal in Salix low shrub tundra Reindeer grazing Salix thickets in Nenets Okrug. If they grow over ≈ 2 m high, herders can lose sight of animals. The changes in willow growth are affecting reindeer management. Forbes et al. 2009 PNAS , ENSINOR project Photos courtesy of Bruce Forbes.
  • Other factors affecting greening patterns: (2) Impacts of gas development Timo Kumpula: Yamal LCLUC Workshop, Moscow, 28-30 Jan 2008 .
      • Locally important but still relatively small extent.
      • Need development scenario models to help predict and plan for expansion of road networks.
  • Analysis of biomass and NDVI trends across the climate gradient NDVI & LAI Soils Field data collected: Plant Biomass Ground temperatures Active layer Plant Cover
  • 2010 Expedition to Hayes Island, Franz Josef Land
    • Ground-based observations in Bioclimate Subzone A of the Eurasia Arctic Transect.
    • Northern-most permafrost borehole in Russia at 80˚ 37’ N.
    • Completed parallel transect studies in North America and Eurasia.
  • Typical layout of transects and plots at each site
    • Five 50-m transects
    • Five 5 x 5-m plots (relevés)
    • Biomass harvests in each plot (x)
    • iButtons for n-factor in corner of each plot (•)
    • Soil pit in SW corner
    Soil pit
  • EAT data reports
    • Descriptions of each study location
      • General description of the region and study sites
      • Physiography and geology
      • Climate summary
    • Transect data
      • Plant species cover
      • LAI
      • NDVI
      • Thaw depth
      • Photos of transects
    • Relevé data
      • Cover abundance of plant species
      • Soil chemical and physical data
      • Site factors
      • Biomass by plant functional type
      • Photos of relevés
    • Soil pits
      • Descriptions
      • Photos
  • Spatial patterns of biomass and NDVI: EAT transect biomass
    • Zonal sites show little variation across the peninsula, except in subzone E.
    • Biomass values for zonal site in subzone E is close to tussock tundra values for Alaska (≈ 750 g m^2).
    • Total live biomass values of zonal loamy sites in subzones C and D are close published values for mesic tundra Barrow and Prudhoe Bay (≈ 450 g m^2).
    Biomass (G m^2) Total live and dead above-ground biomass including trees Total live above-ground biomass Zonal loamy sites Subzone FT E D C B Understory only Zonal loamy sites
  • Vegetation Analysis: NMS Ordination of tundra study plots based on floristic similarity
    • Colors according to CAVM bioclimate subzones:
      • Blue : Subzone B
      • Green: Subzone C
      • Olive: Subzone D
      • Red : Subzone E
    • Shape of symbols represent soil texture:
      • Sandy
      • Loamy
    JJ Frost et al. 2010, Yamal LCLUC Workshop
  • Ordination with biplot arrows showing environmental relationships
    • Biplot arrows show direction and strength of correlations for each measured environmental variable. R^2 cutoff = 0.25.
    • Variables pointing in the horizontal direction are correlated with percent silt:
      • (+): soil nutrients, soil moisture
      • (-): sand, thaw depth.
    • Variables pointing in the vertical direction are more strongly correlated with latitude :
      • (-) Summer warmth, microrelief
    • X and Y axes are interpreted as complex environmental gradients with numerous variables covarying along each axis:
      • X axis: soil texture/ pH/ moisture gradient
      • Y axis: latitude/ climate/ microrelief gradient
    JJ Frost et al. 2010, Yamal LCLUC Workshop
  • Ordination space interpreted as an environmental space with clear bioclimate and soil texture gradients
    • First interpretation Subzones B to E:
      • Horizonal axis: Sand to Loams
      • Vertical axis: Warm to cold
    JJ Frost et al. 2010, Yamal LCLUC Workshop USDA Soil Texture Triangle Subzone E Subzone D Subzone C Subzone B Loamy Sandy
  • Ordination with bipolot plant-variables and NDVI correlations
    • Plant variables correlated with complex soil texture gradient
      • Pleurocarpous mosses (+)
      • Graminoid cover (+)
      • Crustose lichens (-)
      • Moss thickness
    • Variables correlated with the latitude (-temperature) gradient
      • Bare soil cover (+)
      • Liverwort cover (+)
      • Shrub biomass (-)
      • Evergreen shrubs (-)
      • LAI (-)
    • NDVI and plant production shows strong relationships to both gradients.
    JJ Frost et al. 2010, Yamal LCLUC Workshop NDVI
  • Significant relationships between hand-held NDVI measurements and other variables
    • Strongest NDVI relationships are with some plant cover variables (e.g. pct. cover of evergreen shrubs, acrocarpous mosses, deciduous shrubs, LAI, moss height, organic thickness).
    • Also strong environmental correlations (e.g. vol. soil moisture, pct. sand, latitude, SWI) mostly related to soil moisture and warmth gradients.
    Key variables
  • Toward a synthesis of the two transects
    • Although the research along the two transects had different objectives. There is a common primary data set from both transects:
      • Vegetation, soils, and site factors from zonal vegetation along the complete Arctic bioclimate gradient.
      • Ground measurements of key plant productivity variables: biomass, LAI, and NDVI.
      • A circumpolar remote-sensing data set that contains vegetation, land temperatures, and NDVI data for both transects and changes in NDVI since 1982.
    • This allows us to compare the spatial and temporal trends in vegetation, biomass, and NDVI between the two transects in response to ongoing changes in climate and land-use.
  • Field studies along two 1800-km Arctic transects
    • USGS 1-km AVHRR data set used for the CAVM.
    North America Arctic Transect: 2002-2006 Biocomplexity of Arctic Patterned Ground Ecosystems Project (NSF). Eurasian Arctic Transect: 2007-2010, Greening of Arctic (NASA). Both transects through all five Arctic bioclimate subzones.
  • Zonal vegetation along both transects Eurasia Transect A - Hayes Island B - Ostrov Belyy C – Kharasavey D - Vaskiny Dachi E - Laborovaya North America transect A - Isachsen B- Mould Bay C - Green Cabin D - Sagwon MNT E - Happy Valley
  • Summer Warmth Index Vegetation (CAVM Team 2003) Variation in summer land temperature and vegetation along the transects
  • Differences between the transects:
    • EAT has less biomass in subzone A (Wetter, much colder).
    • EAT has more biomass in subzone C, (Wetter, unglaciated, more nutrients?)
    • NAAT has much more biomass in subzone E (grazing effect?).
    Plot-level biomass trends along EAT and NAAT NAAT EAT
    • Fewer evergreen shrubs and lichens along the EAT especially in subzones D and E. (Reindeer?)
    NAAT EAT Differences between EAT and NAAT
  • Comparison of EAT and NAAT Hand-held NDVI vs. biomass, and LAI
    • For equivalent amounts of biomass and LAI, the HH-NDVI readings were much higher along the EAT.
  • Comparison of EAT and NAAT Leaf Area Index vs. Biomass
    • An equivalent amount of biomass has consistently much higher LAI values along the NAAT than along the EAT and the difference increases at higher biomass values.
    • Reflects the different structure of the vegetation along the two transects. Higher proportion of the total biomass is non-green along the NAAT (more wood, taller plants?).
  • Comparison of EAT and NAAT 1-km AVHRR NDVI & biomass, vs. summer warmth index
    • Greater biomass and NDVI for equivalent temperature along the EAT compared to NAAT.
    • Biomass values are landscape-level averages for zonal landscapes.
    • EAT is greener in equivalent summer climates.
  • Comparison of EAT and NAAT: 1-km AVHRR NDVI and zonal landscape-scale biomass
    • Very strong correlation between AVHRR NDVI and biomass along both transects and for combined data set.
  • Use of ground data to calibrate regional AVHRR-NDVI /biomass data
  • Circumpolar aboveground biomass derived from NDVI Raynolds et al. 2011 submitted, Geophysical Research Letters
  • Temporal analysis of NDVI change with respect to summer sea ice and land temperatures Arctic Tundra Vegetation March Sea-Ice Extent Sea Ice: http://www.arctic.noaa.gov/reportcard/figures/seaice2009fig1.jpg Vegetation and NDVI: http://www.arcticatlas.org/maps/themes/cp/cpvg
    • 80% of Arctic tundra is within 100 km of ice-covered seas (100% is within 350 km).
    • Models have shown that melting the sea ice will affect land temperatures and permafrost even at great distances from the Arctic Ocean.
    • Changes is summer sea-ice distribution should affect land temperatures and the productivity of tundra.
    Max NDVI
  • Study Framework: Division of Arctic Ocean and associated land masses Uma Bhatt, D.A. Walker, M.K. Raynolds, J. Comiso, H.E. Epstein, G.J., Jia, J. Pinzon, and C.J. Tucker, 2010, Earth Interactions.
    • Russian Arctic Atlas for seas.
    • CAVM Florist provinces for land masses.
    • Analysis of 50-km buffers seaward and landward along each sea coast and also for entire non-alpine tundra area.
  • Changes in summer land-surface temperature (1982-2010)
  • Temporal patterns of NDVI in relationship to changes in area of summer open water Walker et al. 2011. Bulletin American Meteorological Society. State of the Climate . New analysis based on new GIMMS 3g AVHRR NDVI data by Pinzon et al. 2010 (in progress) and sea ice data by Comiso et al. 2010. Pct. Change MaxNDVI (1982-2010) 26% increase +4% increase Beaufort Kara Beaufort Kara Oceans: % change of May-Aug open water (1982-2010) Tundra land areas: % change in TI-NDVI (1982-2010) From Bhatt et al. 2010, AGU Fall Meeting
  • Percentage change (based on least squares fit method) in coastal open water, land temperatures, and NDVI and significance of trends
    • In general, areas of enhanced NDVI patterns are corresponding to areas of warmer land temperatures.
    • The connections between land warming and more open water are less clear in 2010 than they were previously.
    • Cooling in the Kara region despite very large increases in open coastal water (more fog, more winter precip. Shorter growing seasson?)
    Walker et al. 2011, BAMS State of the Climate, in prep.
    • This study has shown:
    • The feasibility of studying and monitoring zonal landscape-level biomass and NDVI across the full Arctic bioclimate gradient at a circumpolar scale.
    • Broad similarities in biomass between North America and Eurasia along the Arctic temperature gradient, but also major differences related to different disturbance regimes, geology, and precipitation patterns. Very good correlation between AVHRR NDVI and zonal landscape-level biomass.
    • Strong linkages between change in NDVI and summer land temperatures, but weaker linkages with coastal sea-ice concentrations.
    • Good start, but more replication is needed for ground observations in all subzones along both gradients. And more long-term studies of biomass trends are needed.
  • Collaborations
    • Institutions:
      • University of Alaska
      • University of Virginia
      • Earth Cryosphere Institute (RAS),
      • Arctic Centre, Rovaniemi
    2
      • Funding
      • U.S.: NSF, NASA
      • Finland: ENSINOR
      • Russian Academy of Science
      • Members of 2010 Expedition to Hayes Island
    Děkuji!