Iab2008 goa0811120(1)

Greening of the Arctic: an IPY initiative Skip Walker University of Alaska Fairbanks IAB Seminar, November 21, 2008 Does the the loss of sea ice affect the tundra and those who depend on it? Sep 1979 Sep 2007

Outline of talk Rationale and overview of the GOA initiative. North American Arctic Transect. Yamal Russia Transect. Circumpolar analysis of 28-year trends of sea-ice concentration, land-surface temperatures and greening patterns.

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 km 2 . NSIDC. Comiso et al. 2008, Geophysical Research Letters 35: L01703.

2008 sea-ice 2008 was the second lowest minimum. The Arctic coasts of North America and Asia were simultaneously ice free for the first time on record. 2007! NSIDC: http://nsidc.org/data/virtual_globes/images/seaice_2008_climatology_lr.mov Sep 2007 Sep 2008

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. The Arctic tundra is a maritime biome 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

There 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.

Uncertainties and needed research There are virtually no long-term biomass data to support or dispute the trends shown by NDVI. “ 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) Causes of variation of NDVI within the Arctic as well as seasonality of NDVI have 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? Other NDVI issues: Variation with latitude and different sun angles in tundra. Calibration problems between different satellites. Greenness changes in the Arctic need to be more clearly linked to issues relevant to man (e.g., wildlife habitat, links to other elements of the Arctic system, feedbacks to global system).

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

North American Arctic Transect (NAAT) 1800-km transect through five Arctic bioclimate subzones in North America. Initiated in 2002-06 as part of NSF Biocomplexity of Patterned-Ground Project. Numerous other IPY studies are coordinated with this effort (e.g. CALM, TSP, Lee Taylor’s mycorrhizae transect). 7 sites in AK and 4 in Canada. 7.111 (100%) Total Arctic 1.975 (28%) Glaciers 1.840 (26%) 9-12˚C E 1.564 (22%) 7-9˚ C D 1.179 (17%) 5-7˚ C C 0.450 (6%) 3-5˚ C B 0.114 (2%) 1-3˚ C A Circumpolar Area (km 2 x 10 6 ) Mean July Temp (˚C) Subzone

Central Questions of Biocomplexity 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

Summer warmth index along the NAAT > 10x increase in total air summer warmth (white bars). Surface temperatures are warmer than air temperatures (especially in High Arctic) Barren patterned ground features are warmer than the adjacent tundra. Courtesy V. Romanovsky and R. Daanen Sub- zone : I A I B I C I D I E I BF I Climate data: V.E. Romanovsky

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

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

Biomass along the NAAT Zonal vegetation Sub- zone : I A I B I C I D I E I 5-fold increase on zonal sites. 30-fold increase on patterned-ground features. Shift in dominant growth forms with temperature on zonal sites. Different suite of plant growth forms on the patterned-ground features. Biomass on patterned-ground features and zonal areas Walker 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

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

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: Conceptual nonnumeric approach that incorporates cracking and frost heave (Shur et al 2008). Self-organization model for initinvolving linear instability of top-down freezing in soils (Peterson and Krantz 2008). Linked hydrology-vegetation succession model at a landscape scale (Daanen et al. 2008). Detailed physical processes model of thermal, hydrology, and heave processes within a single non-sorted circle (Nickolsy, Romanovsky et al. 2008).

In the Russian literature, subzone A is treated as an entirely separate bioclimate “Zone” -- the true “polar desert” of Gorodkov, Alexandrova and others. If the Tundra Zone is defined by its proximity to the Arctic Ocean, subzone A is defined by its proximity to perennial sea ice. Isachsen, Nunuvut, Canada Barren sea cliffs at Isachsen coast Special significance of the Subzone A site at Isachsen

Subzone A is a very cool place. Ellef Ringnes Island Photo: D.A. Walker Very cold summers (mean July temperature < 3 ˚C). Very small vascular-plant flora (50 species). No woody plants. No sedges. Enhanced role of lichens and mosses. No peat deposits. Very little published ecosystem information from this subzone.

Small differences in microclimate or moisture make a huge difference in vegetation production. A warming of only 2 ˚C will convert this to Subzone B climate with a potential doubling of the vascular-plant species that could colonize the area. Vegetation at base of snow bed, Isachsen Papaver polare on dry zonal sites Vegetation on warmer mesic site, Isachsen Subzone A: “the Poppy zone”

Lessons from 2007 minimum sea-ice event : Modeled predictions of sea-ice ages in Arctic Basin indicate that the oldest ice is in the vicinity of the western Canadian Archipelago and will be the last to melt in the Arctic. This is also the region of bioclimate subzone A. The terrestrial ecosystems in this region are dependent on the summer sea ice to maintain the cold temperatures. If summer arctic ice vanishes, so does Subzone A. Subzone A is a rare and endangered bioclimate subzone! Modified from Nghiem et al. 2008. Minimum Summer Sea Ice Extent Modeled Observed Isachsen Mould Bay

Legacy from the Biocomplexity Project Datasets from the NAAT provide an important baseline of information for future climate change studies across the complete Arctic climate gradient. Macroscale Mesoscale Microscale Climate Permafrost Geology/ Geomorph. Soils Microflora/ fauna Vegetation Microscale (plots) Mesoscale (Regional to toposequence) Macroscale (panArctic) Multi-scale Databases from the NAAT

Synthesis of information from the North American Arctic Transect Synthesis of the project recently 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 including the following from UAF: Ronnie Daanen, Anja Kade, Patrick Kuss, Gary Michaelson, Corinne Munger, Dmitri Nickolski, Rorik Peterson, Chien-Lu Ping, Martha Raynolds, Vladimir Romanovsky, Ina Timling, Yuri Shur, Corinne Vonlanthen, Skip Walker 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.

Other publications Carbon is sequestered by patterned-ground formation processes deep in the active layer and permafrost, contributing to the high carbon stocks in Arctic soils.

Other publications from the Biocomplexity project and North American Arctic Transect Ninth International Permafrost Conference papers (6): Other journal publications (30 + 2 in prep): Data reports (9):

The Yamal Peninsula Transect: Cumulative effects of resource development, reindeer herding, and climate change on the Yamal Peninsula, Russia Funded by NASA Photo: Bryan and Cherry Alexander

Yamal Transect 2007 Nadym Laborovaya Vaskiny Dachi 2008 Kharasavey 2010 (proposed) Ostrov Belyy Russkaya Gavan (or Franz Josef Land) Marresale (or site in N. Yamal)

Collaborators NASA: Land Cover Land-Use Change program Examines the linkages between greening trends, the range and forage for the reindeer of the Nenets people, and the regional sea-ice conditions. Field research and modeling in all 5 arctic bioclimate subzones. Linked to the Circumpolar Arctic Rangifer Monitoring and Assessment (CARMA) project, and the Cold Land Process in NEESPI (CLPN), and the (Environmental and Social Impacts of Industrial Development in Northern Russia ( ENSINOR ). NEESPI = Northern Eurasia Earth Science Partnership Initiative. Uma Bhatt, Gary Kofinas, Jozsef Geml, Martha Raynolds, Vladimir Romanovsky, Lee Taylor, Skip Walker: University of Alaska Fairbanks Marina Liebman, Nataliya Moskalenko, Pavel Orekov, Artem Khomotov, Anatoly Gubarkov: Earth Cryosphere Laboratory, Moscow, Russia Bruce Forbes, Florian Stammler, Timo Kumpula, Elina Karleja ärvi : Arctic Centre, Rovaniemi, Finland Howie Epstein: University of Virginia Jiong Jia: REC-TEA, Chinese Academy of Science Joey Comiso: NASA Goddard

Working with permafrost experts, sociologists, biologists, and soil scientists with long experience on the Yamal Peninsula Elina Karleja ärvi (Arctic Centre, graduate student, botanist), Nataliya Moskalenko (ECI, ecologist), Howie Epstein (U Va Co-PI, ecosystem ecologist), Marina Leibman (ECI, Permafrost, geomorphologist), Patrick Kuss (UAF, Post Doc, botanist), Anatoly Gubarkov (ECI, graduate student, permafrost, industrial impacts), Artem Khumotov (ECI, graduate student, GIS), George Mateyshak (MSU, Soil Scientist) Photo: D.A. Walker Earth Cryosphere Institute, Russian Academy of Science, Moscow organized the expeditions. Led by Marina Liebman and Nataliya Moskalenko.

Florian Stammler interviewing members of Nenets brigade . Combining remote sensing and traditional knowledge. Photo: Bruce Forbes Environmental and Social Impacts of Industrial Development in Northern Russia (ENSINOR) Bruce Forbes, Arctic Centre, Rovaniemi, PI of the ENSINOR Project.

Goal : Develop tools using remote sensing and modeling to better predict the cumulative effects of resource development, climate change, reindeer herding, and the role of terrain factors in affecting changes in tundra regions. The Yamal Typical of the sorts of changes that are likely to become much more common in tundra areas of Russia and the circumpolar region within the next decade. Currently, large areas of wilderness with no roads or development, but… large-scale gas and oil potential, extraordinarily sensitive permafrost environment traditional pasturelands for the nomadic Yamal Nenets people, rapid changes in climate.

The Yamal has very different landscapes from North American Arctic Transect Extraordinarily sensitive permafrost landscapes. Extensive human use of the land by nomadic Nentsy and by industry. Relatively lax regulatory control over hydrocarbon exploration and development. Heavy impact by reindeer.

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. Extraordinarily Sensitive Permafrost Landscapes Photos: D.A. Walker and M. Liebman (upper right)

Yamal: Center of future gas production in Russia Courtesy of A. Gubarkov

Courtesy of A. Gubarkov Large-scale development will occur once road, railroad and pipeline links to the south are built. Yamal Peninsula Yamal Peninsula

Relaxed Regulatory Environment Photos: D.A. Walker

Extent of infrastructure of Bovanenkova Field compared to Prudhoe Bay 448 km 2 Area of infrastructure (km 2 ) Bovanenkovo, RU North Slope, AK (Kumpula 2007) (NRC, 2003) Construction pads 2.1 24.2 Quarries 4.3 25.8 Roads (all types) 2.9 (79 km) 12.2 (954 km) Air strips 0 1.2 Total infrastructure 9.3 km 2 63.4 km 2 Other affected areas (major ORV trails, debris) 24 km 2 7.14 km 2 TOTAL DETECTIBLE CHANGED AREA 33.3 km 2 70.5 km 2 Approximate total extent of infrastructure (perimeter, including currently enclosed unimpacted areas no longer accessible to herders) 448 km 2 2,600 km 2 T. Kumpula: Yamal LCLUC Workshop, Moscow, 28-30 Jan 2008. Extent of Bovanenkovo Gas Field (2001) NRC, 2003. Cumulative Environmental Effects of the Oil and Gas Development on the Alaska North Slope. Extent of the North Slope, AK development (2001) 2,600 km 2

Graphics: Florian Stammler: Yamal LCLUC Workshop, Moscow, 28-30 Jan 2008. Photos: D.A. Walker The Nentsy and their reindeer

Effects of reindeer herding Photos: Bruce Forbes . Overgrazing Trampling Grassification Wind erosion

The Nentsy use the entire Yamal Peninsula. Photos: D.A. Walker . Photos: D.A. Walker

Analysis of impacts of resource extraction to pasturelands Brigade migration corridors VIII and IV

Brigade 4: 225 km 2 out of total 1019 km 2 summer pasture Brigade 8: 200 km 2 out of total 796 km 2 summer pasture Timo Kumpula: Yamal LCLUC Workshop, Moscow, 28-30 Jan 2008. Impacts of Bovanenkovo gas field to summer pasture of Brigades 4 and 8

Threats from industrial development much greater than threats from climate change. However, they currently generally view the gas development positively because of increased economic opportunities (e.g. markets for reindeer, some perks from the industry). Moderate demands: Complete and timely reclamation of lands used during the technical work that are not industrial and have no facilities on them. Establishing and protecting corridors for movement between camps by people and reindeer herders. (Zen’ko 2004, Stammler 2005). Herders view: Photo: D.A. Walker Stammler, F. 2005. Reindeer Nomads Meet the Market: Culture, Property and Globalisation at the End of the Land. Litverlag-Halle Studies in the Antrhopology of Eurasia, Muenster. Zen'ko, M. A. 2004. Contemporary Yamal: ethnoecological and ethnosocial problems. Anthropology & Archeology of Eurasia 42:7-63.

Pavel Orekhov and Nenets herder . Photo: D.A. Walker Despite an amazing ability to adapt to past climate, social, economic, and political upheavals in Russia, the Nentsy face difficult challenges with respect to adapting to industrial change because they lack title to their land. In Alaska and Canada, indigenous groups gained legal land claims. No such legal land rights exist for the Nentsy. Bruce Forbes. 2008. Equity, vulnerability and resilience in social-ecological systems: A contemporary example from the Russian Arctic. Research in Social Problems and Public Policy, 15: 203-236. However, there is a lack of equity in discussions regarding land-use.

Effects of climate change: Analysis of biomass and NDVI trends across the climate gradient Plant Cover NDVI & LAI Active layer Soils Field data collected: Plant Biomass Ground temperatures Data Report http://www.geobotany.uaf.edu/yamal/documents/yamal_2007_dr080211

Typical sampling strategy 5 50-m transects 5 5 x 5-m plots 1 x 3-m soil pit soil pit

Biomass along the Yamal transect n,s n,s s s n = no reindeer s = sand n Climate trend: 2000-2300 g m -2 at Nadym to about 1000-1300 g m -2 at Vaskiny Dachi. Effect of sandy soils: Sandy soils have 250-350 g m -2 less biomass than comparable clayey sites Much more lichen biomass and less mosses and graminoids. Effect of reindeer: Ungrazed sandy areas near Nadym – over 900 g m -2 of lichen Less than 200 g m -2 in sandy areas where reindeer grazing has occurred annually. Epstein et al: NASA LCLUC meeting 2008.

Modeled productivity of PFTs on the Yamal ArcVeg model (Epstein et al. 2002) Examines succession of biomass for seven Arctic plant functional types. Five climate scenarios. Warming vs. non-warming treatments. Three grazing intensities. Next steps will incorporate soil type and disturbance regimes (dust and complete removal of vegetation), relate to NDVI and develop regional extrapolations. Yu and Epstein : 2008, NASA LCLUC conference.

Some problems with existing arctic biomass data in the literature Although trends in NDVI are clear, there are still no convincing ground-based studies of changes in Arctic plant biomass. Real vegetation type is often unknown. Soil and site factor information missing. Harvest methods not documented. Not georeferenced. Replication not documented. Not linked to NDVI, LAI, or other cover properties of the vegetation. Definitions of biomass components unclear. “ What is above-ground biomass?”

“ What does NDVI really mean in tundra systems… particularly for reindeer and caribou?” Some areas with low NDVI have high forage quality for reindeer. Bright green areas may be dominated by species such as alder or dwarf-birch, which have abundant toxic secondary plant compounds that protect them from grazing. Shrub tundra at Laborovaya Lichen-woodland at Nadym Photos: D.A. Walker

AVHRR-Derived NDVI of the Yamal Peninsula Martha Raynolds: Yamal LCLUC meeting, Moscow 28-31 Jan 2008. landschaft elevation lithology veget-id lake area SWI Analysis of NDVI in relation to GIS databases

Summer warmth index (SWI) of Yamal Peninsula, based on AVHRR satellite-derived land-surface temperatures (mean of 1982-2003, Comiso). Vaskiny Dachi Laborovaya Belyy Ostrov Marre Sale Kharasavey Novii Port YAMAL Martha Raynolds: Yamal LCLUC meeting, Moscow 28-31 Jan 2008. Land-surface summer warmth on the Yamal

Bioclimate subzones as mapped on the Circumpolar Arctic Vegetation Map Bioclimate subzones as mapped by SWI Reevaluation of circumpolar zonal boundaries using AVHRR LST data Colder coastal strips Interior areas warmer Mountains colder Martha Raynolds: Yamal LCLUC meeting, Moscow 28-31 Jan 2008.

Yamal y = 0.0036x + 0.358 R 2 = 0.2158 Circumpolar Arctic y = 0.0137x – 0.0204 R 2 = 0.5814 NDVI vs. Summer Warmth on the Yamal compared to the Circumpolar Arctic Arctic as a whole has much stronger correlations between NDVI and SWI. Martha Raynolds: Yamal LCLUC meeting, Moscow 28-31 Jan 2008.

Areas with less NDVI than expected are brown, areas with more NDVI than expected are green. Comparison of actual NDVI and predicted NDVI based on SWI/NDVI relationship for entire Arctic 0 < - 0.3 > + 0.3 Martha Raynolds: Yamal LCLUC meeting, Moscow 28-31 Jan 2008. Most of the peninsula is greener than we expected.

Extensive willow shrublands due to landslide disturbances

Circumpolar Data Sets Primary controls at pan-Arctic scale: Summer temp Lake cover Glacial history Soil type AVHRR Land-surface Temp Permafrost Soils Glacial Geology Vegetation Circumpolar Analysis of NDVI patterns: Martha Raynolds Ph.D. thesis NDVI Raynolds, M.K., D. A. Walker and H. A. Maier. 2006. NDVI patterns and phytomass distribution in the circumpolar Arctic. Remote Sensing of Environment 102:271-28 . Raynolds, M. K., J. C. Comiso, D. A. Walker, D. Verbyla. 2008. Relationship between satellite-derived land surface temperatures, arctic vegetation types, and NDVI. Remote Sensing of Environment 112:1884-1894. Raynolds, M. K. and Walker, D. A. 2008. Relationship of permafrost characteristics, NDVI, and arctic vegetation types. Proceedings of the Ninth International Conference on Permafrost : 1469-1474. Raynolds, M. K. and Walker, D. A. 2008 (submitted): The effects of deglaciation on circumpolar distribution of arctic vegetation. Canadian Journal of Remote Sensing . Raynolds, M.K. 2009 in prep. Synthesis of circumpolar controls on NDVI.

Analysis of sea-ice, land surface temperature and NDVI trends: Division of Arctic Ocean and associated land masses according to Russian Arctic Atlas Uma Bhatt, D.A. Walker, M.K. Raynolds, J. Comiso Analysis of 50-km buffers seaward and landward along each sea coast and also for entire tundra area below 330 m. 1982-2007 AVHRR data to analyze trends in sea ice concentration, LST, and NDVI.

Mid July Sea Ice percentage cover Summer warmth index (SWI) Max NDVI Integrated NDVI Bhatt et al: Yamal LCLUC Workshop, Moscow, 28-30 Jan 2008, and EGU 2008. Pan-Arctic trends: Sea ice, land temperatures and NDVI, 1980-2007

Mid July Sea Ice percentage cover Summer warmth index (SWI) Max NDVI Integrated NDVI Bhatt et al: Yamal LCLUC Workshop, Moscow, 28-30 Jan 2008, and EGU 2008. Focus on Kara/Yamal and Beaufort regions Pan-Arctic trends: Sea ice, land temperatures and NDVI, 1980-2007

Sea-ice and temperature trends in Beaufort Sea and Kara/Yamal region of Russia, 1982-2007 Beaufort Negative sea-ice trend (-29%) correlated with positive temperature trend (+16%) and very high inter-annual variability. Kara/Yamal Negative sea-ice trend (-25%) but nearly flat temperature trend (+4%). Bhatt et al.: NASA LCLUC Workshop, 2008. None of the trends are significant at p = 0.05 because of high interannual variability.

NDVI trends in Beaufort Sea and Kara/Yamal region of Russia Beaufort Kara/Yamal Greater change in Beaufort Region maximum NDVI (+ 24%) vs. Kara/Yamal (+ 3%) most likely due to more positive trend in ground surface temperatures in the Beaufort region during the period of record. Beaufort trends are significant at p = 0.05. Bhatt et al. EGU, Vienna, Proceedings, 2008.

Summary of trends Sea ice is strongly decreasing throughout the Arctic except the Greenland Sea. The strongest most significant trends are in the E. Siberian to E. Chukchi region. Summer warmth is increasing most strongly in the Beringian region between the E. Siberian Sea and the E. Chukchi and also in the Greenland Sea and Baffin Bay. Relatively small increases are seen between the W. Kara and Laptev seas. NDVI is increasing most strongly in the E. Chukchi and Beaufort regions, and also Davis Straight. Negative trends are occurring in several areas, most notable along the E. Kara Sea and Laptev Sea. Bhatt et al., in progress, 2008.

Bhatt et al., in progress, 2008. Sea ice is generally negatively correlated with the Arctic Oscillation and positively correlated with the Pacific Decadal Oscillation. SWI and NDVI are generally positively correlated with the AO and negatively correlated with the PDO. Correlations require more thought in terms of mechanisms. Analysis of wind correlations with NDVI and SWI are in progress. NPI AO PDO NPI AO PDO NPI AO PDO NAO NAO NAO Climate index 0 0 0 .24 0 0 .10 0 0 .15 -.16 .14 .22 -.25 .10 .15 0 0 0 -.22 0 .25 -.26 0 .49 -.63 .45 .27 -.41 .41 .16 0 -.13 .40 -.29 .14 .23 .20 -.24 0 0 .26 -.17 .15 0 -.11 0 0 0 0 0 .16 -.27 0 0 .10 -.25 0 .14 -.24 -.11 .20 -.26 -.26 .49 -.56 -.17 .43 -.53 0 0 0 -.34 .48 -.57 -.20 -.3 .42 .19 -.10 .14 .16 -.15 0 .15 0 0 0 0 .13 .11 0 .40 .22 -.11 0 .13 -.26 0 .37 -.28 .12 .32 -.43 .33 .15 -.31 .19 -.2 -.14 -.40 .14 0 .12 .14 .3 0 Correlations with climate indices 50-km zones with climate indices during preceding winter (DJFM) Red values are positive correlations, blue are negative. Bold values are significant at 90% level or greater. .13 .43 -.1 Grnland Sea 0 0 0 Baffin Sea -.31 .18 -.2 Davis Straits 0 .14 .19 Canadian Arch -.12 0 .48 Beaufort 0 0 0 E. Bering 0 -.11 0 W. Bering -.17 .19 -.1 Chukchi 0.19 -.27 .14 E.Siberian 0.60 -.56 .33 Laptev 0 0 - .2 Kara-East 0 -.54 .27 Kara-Yamal .11 -0.2 .38 Barents Integrated NDVI Sea Ice SWI

Seasonality trends NDVI Sea-ice concentration Jia et al. in press, JGR-Biogeosciences Bhatt et al. in prep., Earth Interactions

Controls on seasonality Biweekly sea-ice concentration in Arctic Alaska Seas Jun-Aug Wind patterns Bhatt et al. in prep., Atmospheric Research Beaufort East Chukchi East Bering Beaufort East Chukchi East Bering NARR long term climatological 10-m vector winds (1979-2000) averaged for June-August in m s- 1 . Data for image provided by the NOAA-ESRL Physical Sciences Division, Boulder Colorado from their Web site at http://www.cdc.noaa.gov . Weekly climatological sea ice based on the 1982-2007 period for the 50-km coastal ocean domain. Future analyses will examine the controls of sea-ice, winds, snow, atmospheric circulation and ocean circulation on seasonal patterns of NDVI. Proposed to NSF by Epstein, Bhatt, Walker, and Steele.

Cumulative effects on the Yamal Resource development: Indirect (unplanned) impacts (such as ORV trails, flooding from roads) are greater than the direct (planned) impacts (infrastructure). Roads and pipelines: serious barriers to migration corridors. Effects will increase as new field are developed. Landscape factors and terrain sensitivity: High potential for extensive landscape effects due to unstable sandy soils, and extremely ice-rich permafrost near the surface. Reindeer herding: Land withdrawals by industry, increasing Nenets population, and larger reindeer herds are all increasing pressure on the rangelands. Herders view: Threats from industrial development much greater than threats from climate change. Big concern is lack of power during negotiations. They currently generally view the gas development positively because of increased economic opportunities. Climate change: Satellite data suggest that there has been only modest summer land-surface warming and only slight greening changes across the Yamal during the past 24 years. (Trend is much stronger in other parts of the Arctic, e.g. Beaufort Sea.) Kara-Yamal: negative sea ice, positive summer warmth and positive NDVI are correlated with positive phases of the North Atlantic Oscillation and Arctic Oscillation.

Circumpolar Summary Temperature - sea ice linkages: Strong linkages have been demonstrated between reduced sea-ice concentrations and increased land-surface temperatures. NDVI trends: Large regional differences in the NDVI trends: Strongly positive trend in the northern Beringia region of E. Siberia, Chukchi, and Beaufort seas. This is the region with the strongest recent reductions in sea-ice concentrations. Slight negative trend in northern Eurasia (E. Kara, Laptev seas). NDVI controls: Ground-based and remote-sensing studies along climate transects in North America and Yamal have very different spatial patterns of NDVI and factors affecting the NDVI in each region: North America : age of glacial surfaces, differences in substrates (acidic vs. nonacidic soils), strong temperature controls. Yamal : Large effect of natural disturbance, sandy vs. clayey substrates, heavily grazed systems (but still unknown what the actual effect of reindeer on NDVI is), weaker temperature control. Climate drivers: Throughout the Arctic including the Beaufort and Yamal, the general trend is positive summer warmth and NDVI with positive phases of the North Atlantic Oscillation and Arctic Oscillation, and negative correlations with positive phases of the Pacific Decadal Oscillation. The positive phase of NAO and AO is consistent with a warmer winter Arctic, reduced summer sea ice, increased SWI and increased integrated NDVI. Replicated long-term vegetation studies and standardized protocols: Needed across the Arctic and coordinated with other terrestrial monitoring of climate, permafrost, active layers, ITEX etc. — especially in areas currently surrounded by perennial sea ice and other areas where the changes are occurring most rapidly (e.g. Beringia region).

Collaborators NASA: Land Cover Land-Use Change program Examines the linkages between greening trends, the range and forage for the reindeer of the Nenets people, and the regional sea-ice conditions. Field research and modeling in all 5 arctic bioclimate subzones. Linked to the Circumpolar Arctic Rangifer Monitoring and Assessment (CARMA) project, and the Cold Land Process in NEESPI (CLPN). NEESPI = Northern Eurasia Earth Science Partnership Initiative. Uma Bhatt, Gary Kofinas, Jozsef Geml, Martha Raynolds, Vladimir Romanovsky, Lee Taylor, Skip Walker: University of Alaska Fairbanks Marina Liebman, Nataliya Moskalenko, Pavel Orekov, Artem Khomotov, Anatoly Gubarkov: Earth Cryosphere Laboratory, Moscow, Russia Bruce Forbes, Florian Stammler, Timo Kumpula, Elina Karleja ärvi : Arctic Centre, Rovaniemi, Finland Howie Epstein: University of Virginia Jiong Jia: REC-TEA, Chinese Academy of Science Joey Comiso: NASA Goddard

The Yamal has very different landscapes from North American Arctic Transect Extensive human use of the land by nomadic Nentsy and by industry. Extraordinarily sensitive permafrost landscapes. Relatively lax regulatory control over hydrocarbon exploration and development. Heavy impact by reindeer.

Extensive nutrient-poor surface sands. Underlain by massive pure ice, Subject to erosion and landslides, That expose salt-rich and nutrient-rich clays, leading to Complex successional process that results in willow-shrub tundra in the interior parts of the peninsula. Extraordinarily Sensitive Permafrost Landscapes Photos: D.A. Walker and M. Liebman (upper right)

: Florian Stammler interviewing members of Nenets brigade . Combining remote sensing and traditional knowledge. Photo: Bruce Forbes Working with sociologists Herders view: Land withdrawals by industry, increasing Nenets population, and larger reindeer herds are all increasing pressure on the rangelands. Threats from industrial development much greater than threats from climate change. They generally view the gas development positively because of increased economic opportunities.

Pavel Orekhov discussing parka technology with Nenets herder . Photo: D.A. Walker

Analysis of biomass and NDVI trends across the climate gradient Plant Cover NDVI & LAI Active layer Soils Field data collected: Plant Biomass Ground temperatures Data Report http://www.geobotany.uaf.edu/yamal/documents/yamal_2007_dr080211

Biomass along the Yamal transect n,s n,s s s n = no reindeer s = sand n Climate trend: 2000-2300 g m -2 at Nadym to about 1000-1300 g m -2 at Vaskiny Dachi. Effect of sandy soils: Sandy soils have 250-350 g m -2 less biomass than comparable clayey sites Much more lichen biomass and less mosses and graminoids. Effect of reindeer: Ungrazed sandy areas near Nadym – over 1000 g m -2 Less than 250 g m -2 in sandy areas where reindeer grazing has occurred annually. Epstein et al: NASA LCLUC meeting 2008.

AVHRR-Derived NDVI of the Yamal Peninsula Martha Raynolds: Yamal LCLUC meeting, Moscow 28-31 Jan 2008. landschaft elevation lithology veget-id lake area SWI Analysis of remotely sensed data and regional data in GIS databases

Summer warmth index (SWI) of Yamal Peninsula, based on satellite-derived land-surface temperatures (mean of 1982-2003, Comiso). Vaskiny Dachi Laborovaya Belyy Ostrov Marre Sale Kharasavey Novii Port YAMAL Martha Raynolds: Yamal LCLUC meeting, Moscow 28-31 Jan 2008.

Yamal y = 0.0036x + 0.358 R 2 = 0.2158 Circumpolar Arctic y = 0.0137x – 0.0204 R 2 = 0.5814 NDVI vs. Summer Warmth on the Yamal compared to the Circumpolar Arctic Arctic as a whole has steeper increase of NDVI with SWI and much stronger correlations. Possibly due to a combination of factors: High disturbance regimes and abundance of shrubs on landslides. Effects of grazing. Nutrient poor soils on uplands. Increase in NDVI on better drained soils and higher elevations toward the south on the Yamal. Martha Raynolds: Yamal LCLUC meeting, Moscow 28-31 Jan 2008.

Areas with less NDVI than expected are brown, areas with more NDVI than expected are green. Comparison of actual NDVI and predicted NDVI based on SWI/NDVI relationship for entire Arctic 0 < - 0.3 > + 0.3 Martha Raynolds: Yamal LCLUC meeting, Moscow 28-31 Jan 2008.

Analysis of Circumpolar patterns of NDVI CAVM Team. 2003 Raynolds, M.K., D. A. Walker and H. A. Maier. 2006. NDVI patterns and phytomass distribution in the circumpolar Arctic. Remote Sensing of Environment 102:271-28 . Raynolds, M. K., J. C. Comiso, D. A. Walker, D. Verbyla. 2008. Relationship between satellite-derived land surface temperatures, arctic vegetation types, and NDVI. Remote Sensing of Environment 112:1884-1894. Raynolds, M. K. and Walker, D. A. 2008. Relationship of permafrost characteristics, NDVI, and arctic vegetation types. Proceedings of the Ninth International Conference on Permafrost: 1469-1474. Raynolds, M. K. and Walker, D. A. 2008 (submitted): The effects of deglaciation on circumpolar distribution of arctic vegetation. Canadian Journal of Remote Sensing. Martha Raynolds: Ph.D. Thesis

Circumpolar Data Sets Vegetation Land-Surface Temperature Precipitation Climate Peatlands Soil chemistry Substrate Landscape age Permafrost Primary controls at pan-Arctic scale: Summer temp Lake cover Glacial history Soil type NDVI AVHRR Land-surface Temp Permafrost Soils Glacial Geology Vegetation Controls on Circumpolar NDVI patterns M.K. Raynolds, Ph.D. Thesis

Summer land-surface temperature as shown by the summer warmth index(SWI) Summer Warm Index (SWI, ˚C mo) Area (km^2 x 100) Subzone E D C B A SWI derived from 20-yr mean AVHRR thermal data (Raynolds et al. 2008 Rem. Sens. Envir.)

Areas with less NDVI than expected are brown, areas with more NDVI than expected are green. Expected NDVI value as calculated by SWI regression equation

Mid July Sea Ice percentage cover Summer warmth index (SWI) Max NDVI Integrated NDVI Bhatt et al: Yamal LCLUC Workshop, Moscow, 28-30 Jan 2008, and EGU 2008. Focus on Kara/Yamal and Beaufort regions

Sea-ice and temperature trends in Beaufort Sea and Kara/Yamal region of Russia, 1982-2007 Beaufort Negative sea-ice trend (-29%) correlated with positive temperature trend (+16%) and very high interannual variability. Kara/Yamal Negative sea-ice trend (-25%) but nearly flat temperature trend (+4%). Bhatt et al.: NASA LCLUC Workshop, 2008. None of the trends are significant at p = 0.05 because of high interannual variability.

Correlations between trends Year to year variation in summer land surface temperature (SWI) is generally strongly negatively correlated with mid-July ice cover within 50-km of the coast. Correlations weaken at greater distances from the ocean (not shown). Integrated NDVI is positively correlated with trend in summer land temperatures and negatively correlated with the trend in sea-ice. Blue : Negative correlations. Red : Positive correlations. Bold : Significant at p = 0.05. Italics: Significant at p = 0.10. Bhatt et al., in progress, 2008.

Bhatt et al., in progress, 2008. NPI AO PDO NPI AO PDO NPI AO PDO NAO NAO NAO Climate index 0 0 0 .24 0 0 .10 0 0 .15 -.16 .14 .22 -.25 .10 .15 0 0 0 -.22 0 .25 -.26 0 .49 -.63 .45 .27 -.41 .41 .16 0 -.13 .40 -.29 .14 .23 .20 -.24 0 0 .26 -.17 .15 0 -.11 0 0 0 0 0 .16 -.27 0 0 .10 -.25 0 .14 -.24 -.11 .20 -.26 -.26 .49 -.56 -.17 .43 -.53 0 0 0 -.34 .48 -.57 -.20 -.3 .42 .19 -.10 .14 .16 -.15 0 .15 0 0 0 0 .13 .11 0 .40 .22 -.11 0 .13 -.26 0 .37 -.28 .12 .32 -.43 .33 .15 -.31 .19 -.2 -.14 -.40 .14 0 .12 .14 .3 0 Correlations with climate indices 50-km zones with climate indices during preceding winter (DJFM) Red values are positive correlations, blue are negative. Bold values are significant at 90% level or greater. .13 .43 -.1 Grnland Sea 0 0 0 Baffin Sea -.31 .18 -.2 Davis Straits 0 .14 .19 Canadian Arch -.12 0 .48 Beaufort 0 0 0 E. Bering 0 -.11 0 W. Bering -.17 .19 -.1 Chukchi 0.19 -.27 .14 E.Siberian 0.60 -.56 .33 Laptev 0 0 - .2 Kara-East 0 -.54 .27 Kara-Yamal .11 -0.2 .38 Barents Integrated NDVI Sea Ice SWI

Sea ice is generally negatively correlated with the Arctic Oscillation and positively correlated with the Pacific Decadal Oscillation. SWI and NDVI are generally positively correlated with the AO and negatively correlated with the PDO. Correlations require more thought in terms of mechanisms. Analysis of wind correlations with NDVI and SWI are in progress. NPI AO PDO NPI AO PDO NPI AO PDO NAO NAO NAO Climate index 0 0 0 .24 0 0 .10 0 0 .15 -.16 .14 .22 -.25 .10 .15 0 0 0 -.22 0 .25 -.26 0 .49 -.63 .45 .27 -.41 .41 .16 0 -.13 .40 -.29 .14 .23 .20 -.24 0 0 .26 -.17 .15 0 -.11 0 0 0 0 0 .16 -.27 0 0 .10 -.25 0 .14 -.24 -.11 .20 -.26 -.26 .49 -.56 -.17 .43 -.53 0 0 0 -.34 .48 -.57 -.20 -.3 .42 .19 -.10 .14 .16 -.15 0 .15 0 0 0 0 .13 .11 0 .40 .22 -.11 0 .13 -.26 0 .37 -.28 .12 .32 -.43 .33 .15 -.31 .19 -.2 -.14 -.40 .14 0 .12 .14 .3 0 Correlations with climate indices 50-km zones with climate indices during preceding winter (DJFM) Red values are positive correlations, blue are negative. Bold values are significant at 90% level or greater. .13 .43 -.1 Grnland Sea 0 0 0 Baffin Sea -.31 .18 -.2 Davis Straits 0 .14 .19 Canadian Arch -.12 0 .48 Beaufort 0 0 0 E. Bering 0 -.11 0 W. Bering -.17 .19 -.1 Chukchi 0.19 -.27 .14 E.Siberian 0.60 -.56 .33 Laptev 0 0 - .2 Kara-East 0 -.54 .27 Kara-Yamal .11 -0.2 .38 Barents Integrated NDVI Sea Ice SWI

Cumulative effects on the Yamal Resource development: Indirect (unplanned) impacts (such as ORV trails, flooding from roads) are greater than the direct (planned) impacts (infrastructure). Roads and pipelines: serious barriers to migration corridors. Effects will increase as new field are developed. Landscape factors and terrain sensitivity: High potential for extensive landscape effects due to unstable sandy soils, and extremely ice-rich permafrost near the surface. Reindeer herding: Land withdrawals by industry, increasing Nenets population, and larger reindeer herds are all increasing pressure on the rangelands. Herders view: Threats from industrial development much greater than threats from climate change. They generally view the gas development positively because of increased economic opportunities. Climate change: Satellite data suggest that there has been only modest summer land-surface warming and only slight greening changes across the Yamal during the past 24 years. (Trend is much stronger in other parts of the Arctic, e.g. Beaufort Sea.) Kara-Yamal: negative sea ice, positive summer warmth and positive NDVI are correlated with positive phases of the North Atlantic Oscillation and Arctic Oscillation.

Circumpolar Summary Temperature - sea ice linkages: Strong linkages have been demonstrated between reduced sea-ice concentrations and increased land-surface temperatures. NDVI trends: Large regional differences in the NDVI trends: Strongly positive trend in the northern Beringia region of E. Siberia, Chukchi, and Beaufort seas. This is the region with the strongest recent reductions in sea-ice concentrations. Slight negative trend in northern Eurasia (E. Kara, Laptev seas). NDVI controls: Ground-based and remote-sensing studies along climate transects in North America and Yamal have very different spatial patterns of NDVI and factors affecting the NDVI in each region: North America : age of glacial surfaces, differences in substrates (acidic vs. nonacidic soils), strong temperature controls. Yamal : Large effect of natural disturbance, sandy vs. clayey substrates, heavily grazed systems (but still unknown what the actual effect of reindeer on NDVI is), weaker temperature control. Climate drivers: Throughout the Arctic including the Beaufort and Yamal, the general trend is positive summer warmth and NDVI with positive phases of the North Atlantic Oscillation and Arctic Oscillation, and negative correlations with positive phases of the Pacific Decadal Oscillation. The positive phase of NAO and AO is consistent with a warmer winter Arctic, reduced summer sea ice (-), increased SWI (+) and increased integrated NDVI (+). Replicated long-term studies: Needed across the Arctic and coordinated with other terrestrial monitoring of climate, permafrost, active layers, ITEX etc. — especially in areas currently surrounded by perennial sea ice and other areas where the changes are occurring most rapidly (e.g. Beringia region). Standardized protocols: Need standardized protocols for biomass and vegetation monitoring at a network of sites for a coordinated Circumpolar Terrestrial Ecosystem Baseline .

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