Skip to main content

Diagnosing Environmental Controls on Vegetation Greening and Browning Trends Over Alaska and Northwest Canada Using Complementary Satellite Observations

  • Chapter
  • First Online:
Arctic Hydrology, Permafrost and Ecosystems

Abstract

Tundra and boreal forest regions have undergone extreme environmental changes in recent decades. Many studies have documented these changes and associated ecosystem impacts using a variety of methods including field measurements, remote sensing and biophysical modeling. Combined observations from satellite optical-infrared and microwave remote sensing have also been used for regional assessment and monitoring of environmental change, ecosystem processes and biogeochemical cycles in the Arctic. Remote sensing derived vegetation parameters range from relatively direct observations of vegetation greenness and chlorophyll fluorescence to higher-level vegetation productivity estimates. However, satellite remote sensing of land surface conditions is particularly challenging at high latitudes due to seasonal variations in solar illumination, snow cover, persistent cloud cover and atmospheric aerosol contamination. Here, we used satellite-derived observations of vegetation greenness (EVI), sun-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) to clarify regional patterns and recent variations in vegetation growth over the Arctic Boreal Vulnerability Experiment (ABoVE) domain. The annual non-frozen (NF) period and volumetric soil moisture (VSM) retrieved from satellite microwave remote sensing were used as proxies for growing season length and water supply controls to investigate the impacts of climate on vegetation growth. Positive trends in regional productivity generally coincide with a longer NF season. However, the benefit of a longer NF season to vegetation growth is reduced in soil moisture constrained regions, which have become more widespread in the recent decade over almost half (48.9%) of the domain. Our results document the influence of a changing environment on regional vegetation growth and the northern terrestrial carbon sink for atmospheric CO2.

A Chapter in Arctic hydrology, permafrost, and ecosystem: linkages and interactions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Abbreviations

ABoVE:

Arctic-Boreal Vulnerability Experiment

AMSR-E:

Advanced Microwave Scanning Radiometer for EOS

AMSR2:

AMSR follow-on instrument onboard the JAXA GCOM-W1 satellite

APAR:

Absorbed Photosynthetically Active solar Radiation

ASTER:

Advanced Spaceborne Thermal Emission and Reflection sensor

BPLUT:

Biome-Properties Look-Up Table

DEM:

Digital Elevation Model

ENSO:

El Niňo Southern Oscillation

EVI:

Enhanced Vegetation Index

FPAR:

Fraction of canopy-absorbed Photosynthetically Active Radiation

FR:

Frozen

FT:

Freeze/Thaw

FT-ESDR:

Freeze/Thaw Earth System Data Record

GDEM:

Global Digital Elevation Map

GFED:

Global Fire Emissions Database

GOME-2:

Global Ozone Mapping Experiment 2

GPP:

Gross Primary Productivity

HNL:

High Northern Latitudes

L4C:

Level 4 Carbon

LUE:

Light Use Efficiency

MODIS:

MODerate resolution Imaging Spectroradiometer

NASA:

National Aeronautics and Space Administration

NDVI:

Normalized Difference Vegetation Index

NF:

Non-frozen

PAR:

Photosynthetically Active Radiation

RZSM:

Root Zone Soil Moisture

SIF:

Solar-Induced chlorophyll Fluorescence

SMAP:

Soil Moisture Active Passive

SSM/I(S):

Special Sensor Microwave Imager (sounder)

Tb:

Brightness Temperature

VI:

Vegetation Index

VPD:

Vapor Pressure Deficit

VSM:

Volumetric Soil Moisture

References

  • Geruo A, Velicogna I, Kimball JS, Du J, Kim Y, Colliander A, Njoku E (2017) Satellite-observed changes in vegetation sensitivities to surface soil moisture and total water storage variations since the 2011 Texas drought. Environ Res Lett 12:054006

    Google Scholar 

  • Alexeev VA, Esau I, Polyakov IV, Byam SJ, Sorokina S (2012) Vertical structure of recent arctic warming from observed data and re-analysis products. Clim Change 111:215–239

    Google Scholar 

  • Baird AB, Verbyla D, Hollingsworth TN (2012) Browning of the landscape of interior Alaska based on 1986–2009 Landsat sensor NDVI. Can J For Res 42:1371–1382

    Google Scholar 

  • Baker NR (2008) Chlorophyll Fluorescence: a probe of photosynthesis in vito. Annu Rev Plant Biol 59(1):89–113

    Google Scholar 

  • Baldocchi D (2008) Breathing of the terrestrial biosphere: Lessons learned from a global network of carbon dioxide flux measurement systems. Aust J Bot 56(1):1–26

    Google Scholar 

  • Barichivich J, Briffa KR, Myneni R, Schrier G, Dorigo W, Tucker CJ, Osborn TJ, Melvin TM (2014) Temperature and snow-mediated moisture controls of summer photosynthetic activity in northern terrestrial ecosystems between 1982 and 2011. Remote Sens 6:1390–1431

    Google Scholar 

  • Barnett TP, Adam JC, Lettenmainer DP (2005) Potential impacts of a warming climate water availability in snow-dominated regions. Nature 438:303–309

    Google Scholar 

  • Bastos A, Ciais P, Park T, Zscheischler J, Yue C, Barichivich J, Myneni RB, Peng S, Piao S, Zhu Z (2017) Was the extreme Northern Hemisphere greening in 2015 predictable? Environ Res Lett 12:044016

    Google Scholar 

  • Beck PSA, Goetz SJ (2011) Satellite observations of high northern latitude vegetation productivity changes between 1982 and 2008: ecological variability and regional differences. Environ Res Lett 6:045501

    Google Scholar 

  • Beer C, Reichstein M, Tomelleri E et al (2010) Terrestrial gross carbon dioxide update: global distribution and covariation with climate. Science 329:834–838

    Google Scholar 

  • Berner LT, Beck PSA, Gunn AG, Lloyd AH, Goetz SJ (2011) High-latitude tree growth and satellite vegetation indices: Correlations and trends in Russia and Canada (1982-2008). J Geophys Res-Biogeosci 116:G01015

    Google Scholar 

  • Bjorkman AD, Vellend M, Frei ER, Henry GHR (2017) Climate adaptation is not enough: warming does not facilitate success of southern tundra plant populations in the high Arctic. Glob Change Biol 23:1540–1551

    Google Scholar 

  • Brodzik MJ, Knowles KW (2002) EASE-grid: a versatile set of equal area projections and grids in discrete global grids, Goodchild M (ed) Santa Barbara, CA: Nat. Center Geographic Inf. Anal.

    Google Scholar 

  • Brodzik MJ, Billingsley B, Haran T, Raup B, Savoie MH (2014) Correction: Brodzik MJ et al (2012) EASE-Grid 2.0: Incremental but significant improvements for Earth-Gridded Data Sets. ISPRS Int J Geo-Inf 1:32–45; ISPRS Int J Geo-Inf 3(3):1154–1156. https://doi.org/10.3390/ijgi3031154

  • Buermann W, Bikash PR, Jung M, Burn DH, Reichstein M (2013) Earlier Springs Decrease Peak Summer Productivity in North American Boreal Forests. Environ Res Letters 8(2):024027. https://doi.org/10.1088/1748–9326/8/2/024027

  • Chu T, Guo X (2014) Remote sensing techniques in monitoring post-fire effects and patterns of forest recovery in boreal forest regions: a review. Remote Sens 6(1):470–520

    Google Scholar 

  • Commane R, Lindaas J, Benmergui J, Luus KA, Chang RYW, Daube BC, Euskirchen ES, Henderson JM, Karion A, Miller JB, Miller SM, Parazoo NC, Randerson JT, Sweeney C, Tans P, Thoning K, Veraverbeke S, Miller CE, Wofsy SC (2017) Carbon dioxide sources from Alaska driven by increasing early winter respiration from Arctic tundra. Proc Natl Acad Sci USA 114(21):5361–5366

    Google Scholar 

  • Cowtan K, Way RG (2014) Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends. Q J R Meteorol Soc Wiley. http://dx.doi.org/10.1002/qj.2297

  • Dass P, Rawlins MA, Kimball JS, Kim Y (2016) Environmental controls on the increasing GPP of terrestrial vegetation across northern Eurasia. Biogeosciences 13:45–62

    Google Scholar 

  • de Beurs KM, Henebry GM (2010) A land surface phenology assessment of the northern polar regions using MODIS reflectance time series. Can J Remote Sens 36(Suppl 1):S87–S110

    Google Scholar 

  • Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg I, Biblot J, Bormann N, Delsol C, Dragani R, Fuentes M, Greer AJ, Haimberger L, Healy SB, Hersbach H, Holm EV, Isaksen L, Kallberg P, Kohler M, Matricardi M, McNally AP, Mong-Sanz BM, Morcette JJ, Park BK, Peubey C, de Rosnay P, Tavolato C, Thepaut JN, Vitart F (2011) The ERAInterim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597

    Google Scholar 

  • Delbart N, Toan T, Kergoat L, Fedotova V (2006) Remote sensing of spring phenology in boreal regions: a free of snow-effect method using NOAA-AVHRR and SPOT-VGT data (1982-2004). Remote Sens Environ 101(1):52–62

    Google Scholar 

  • Derksen C, Xu X, Dunbar RS, Colliander A, Kim Y, Kimball JS, Black TA, Euskirchen E, Langlois A, Loranty MM, Marsh P, Rautiainen K, Roy A, Royer A Stephens J (2017) Retrieving landscape freeze/thaw state from soil moisture active passive (SMAP) radar and radiometer measurements. Remote Sens Environ 194:48–62

    Google Scholar 

  • Didan K, Munoz AB, Solano R, Huete A (2015) MODIS Vegetation Index User’s Guide (MOD13 Series) Version 3.0 June 2015 Collection 6. https://vip.arizona.edu/documents/MODIS/MODIS_VI_UsersGuide_June_2015_C6.pdf

  • Du J, Kimball JS, Jones LA, Kim Y, Glassy J, Watts JD (2017a) A global satellite environmental data record derived from AMSR-E and AMSR2 microwave earth observations. Earth Syst Sci Data 9:791–808

    Google Scholar 

  • Du J, Jones LA, Kimball JS (2017b) Daily global land parameters derived from AMSR-E and AMSR2, Version 2. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi:https://doi.org/10.5067/RF8WPYOPJKL2. [Date Accessed]

  • Du J, Kimball JS, Jones LA (2016) Passive microwave remote sensing of soil moisture based on dynamic vegetation scattering properties for AMSR-E. IEEE Trans Geosci Remote Sens 54:597–608

    Google Scholar 

  • Du J, Kimball JS, Shi J, Jones LA, Wu S, Sun R, Yang H (2014) Inter-calibration of satellite passive microwave land observations from AMSR-E and AMSR2 using overlapping FY3B-MWRI sensor measurements. Remote Sens 6:8594–8616

    Google Scholar 

  • Emmerton CA, Louis VL, Humphreys ER, Gamon JA, Barker JD, Pastorello GZ (2016) Net ecosystem exchange of CO2 with rapidly changing high Arctic landscapes. Glob Change Biol 22:1185–1200

    Google Scholar 

  • Flexas J, Escalona J, Evain S, Gulias J, Moya I, Osmond C, Medrano H (2002) Steafy-state chlorophyll fluorescence (Fs) measurements as a tool to follow variations of net CO2 assimilation and stomatal conductance during water-stress in C3 plant. Physiol Plant 114:231–240

    Google Scholar 

  • Friedl MA, McIver DK, Hodges JCF, Zhang XY, Muchoney D, Strahler AH, Woodcock CE, Gopal S, Schneider A, Cooper A, Baccini A, Gao F, Schaaf C (2002) Global land cover mapping from MODIS: algorithms and early results. Remote Sens Environ 83:287–302

    Google Scholar 

  • Gamon JA, Huemmrich KF, Stone RS, Tweedie CE (2013) Spatial and temporal variation in primary productivity (NDVI) of coastal Alaska tundra: Decreased vegetation growth following earlier snowmelt. Remote Sens Environ 129:144–153

    Google Scholar 

  • Giglio L, Randerson JT, van der Werd GR (2013) Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4). J Geophys Res 118:317–328

    Google Scholar 

  • Girardin MP, Hogg EH, Bernier PY, Kurz WA, Guo Z, Cyr G (2016) Negative impacts of high temperatures on growth of black spruce forests intensify with the anticipated climate warming. Glob Change Biol 22(2):627–643

    Google Scholar 

  • Goetz S, Kimball JS, Mack M, Kasischke E (2011) Scoping completed for an experiment to assess vulnerability of Arctic and Boreal ecosystems. EOS 92(18)

    Google Scholar 

  • Guanter L et al (2014) Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence. Proc Natl Acad Sci USA 111(14):E1327–E1333

    Google Scholar 

  • Guay KC, Beck PSA, Berner LT, Goetz SJ, Baccini AL, Buermann W (2014) Vegetation productivity patterns at high northern latitudes: a multi-sensor satellite data assessment. Glob Change Biol 20:3147–3158

    Google Scholar 

  • Guo W, Liu H, Wu X (2018) Vegetation greening despite weakening coupling between vegetation growth and temperature over the boreal region. J Geophys Res. https://doi.org/10.1029/2018JG004486

    Article  Google Scholar 

  • Heinsch FA, Zhao M, Running SW, Kimball JS, Nemani RR, Davis KJ, Bolstad PV, Cook BD, Desai AR, Ricciuto DM, Oechel WC, Kwon HJ, Luo H, Wofsy S, Dunn AL, Munger W, Baldocchi D, Xu L, Hollinger DY, Richardson AD, Stoy PC, Siqueira MBS, Monson R, Burns SP, Flanagan LB (2006) Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE Trans Geosci Remote Sens 44(7):1908–1925

    Google Scholar 

  • Hellmann L, Agafonov L, Ljungqvist FC, Churakova O, Duthorn E, Esper J, Hulsmann L, Kirdyanov AV, Moiseev P, Myglan VS, Nikolaev AN, Reinig F, Schweingruber FH, Solomina O, Tegel W, Buntgen U (2016) Diverse growth trends and climate responses across Eurasia’s boreal forest. Environ Res Lett 11:074021

    Google Scholar 

  • Hoy EE, Turetsky MR, Kasischke ES (2016) More frequent burning increases vulnerability of Alaska boreal black spruce forests. Environ Res Lett 11:095001

    Google Scholar 

  • Huete A, Dinan K, Miura T, Rodriguez EP, Gao X, Ferreira LG (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ 83:195–213

    Google Scholar 

  • Jeganathan C, Dash J, Atkinson PM (2014) Remotely sensed trends in the phenology of northern high latitude terrestrial vegetation, controlling for land cover change and vegetation type. Remote Sens Environ 143:154–170

    Google Scholar 

  • Jia GJ, Epstein HE, Walker DA (2009) Vegetation greening in the Canadian arctic related to decadal warming. J Environ Monit 11:2231–2238

    Google Scholar 

  • John R, Chen J, Kim Y, Ou-yang Z, Xiao J, Park H, Shao C, Zhang Y, Amarjargal A, Batkhshig O, Qi J (2016) Differentiating anthropogenic modification and precipitation-driven change on vegetation productivity on the Mongolian Plateau. Landscape Ecol 31:547–566

    Google Scholar 

  • Joiner JL et al (2014) The seasonal cycle of satellite chlorophyll fluorescence observations and its relationship to vegetation phenology and ecosystem atmosphere carbon exchange. Remote Sens Environ 152:375–391

    Google Scholar 

  • Joiner J, Guanter L, Lindstrot R, Voigt M, Vasilkov AP, Middleton EM, Huemmrich KF, Yoshida Y, Frankenberg C (2013) Global monitoring of terrestrial chlorophyll fluorescence from moderate spectral resolution near-infrared satellite measurements: methodology, simulation, and application to GOME-2. Atmos Meas Tech 5:809–829

    Google Scholar 

  • Jones LA, Kimball JS, Reichle RH, Madani N, Glassy J, Ardizzone JV, Colliander A, Cleverly J, Desai AR, Eamus D, Euskirchen E, Hutley L, Macfarlane C, Scott RL (2017) The SMAP Level 4 carbon product for monitoring ecosystem land-atmosphere CO2 exchange. IEEE Trans Geosci Remote Sens 55(11):6517–6532

    Google Scholar 

  • Jones MO, Kimball JS, Jones LA (2013) Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada. Glob Change Biol 19:3113–3122

    Google Scholar 

  • Jones LA, Ferguson CR, Kimball JS, Zhang K, Chan STK, McDonald KC, Njoku EG, Wood EF (2010) Satellite microwave remote sensing of daily land surface air temperature minima and maxima from AMSR-E. IEEE J Sel Top Appl Earth Obs Remote Sens 3(1):111–123

    Google Scholar 

  • Karkauskaite P, Tagesson T, Fensholt R (2017) Evaluation of the plant phenology index (PPI), NDVI and EVI for start-of-season trend analysis of the northern hemisphere boreal zone. Remote Sens 9(5):485

    Google Scholar 

  • Kasischke ES, Verbyla DL, Rupp TS, McGuire AD, Murphy KA, Chapin FS III, Calef M, Allen JL, Duffy PA, Hoy EE, Jandt R, Turetsky MR (2010a) Alaska’s changing fire regime: implications for the vulnerability of its boreal forest. Canadian J Forest Res 40:1313–1324

    Google Scholar 

  • Kasischke ES, Goetz SJ, Kimball JS, Mack MM (2010b) The Arctic-Boreal Vulnerability Experiment (ABoVE): A Concise plan for a NASA-Sponsored Field Campaign Available online: http://cce.nasa.gov/terrestrial_ecology/pdfs/ABoVE%20Final%20Report.pdf. (Accessed 16 July 2018)

  • Keane RE, McKenzie D, Falk DA, Smithwick EAH, Miller C, Kellogg LB (2015) Representing climate, disturbance, and vegetation interactions in landscape models. Ecol Model 309–310:33–47

    Google Scholar 

  • Keith H, Mackey B, Berry S, Lindenmayer Gibbons P (2010) Estimating carbon carrying capacity in natural forest ecosystems across heterogeneous landscapes: addressing sources of error. Glob Change Biol 16:2971–2989

    Google Scholar 

  • Kim Y, Kimball JS, Glassy J, Du J (2017a) An extended global earth system data record on daily landscape freeze-thaw status determined from satellite passive microwave remote sensing. Earth Syst Sci Data 9:133–147

    Google Scholar 

  • Kim Y, Kimball JS, Glassy J, McDonald K C (2017b) Measures global record of daily landscape freeze/thaw status, Version 4. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi:https://doi.org/10.5067/MEASURES/CRYOSPHERE/nsidc-0477.004. [Date Accessed]

  • Kim Y, Kimball JS, Zhang K, Didan K, Velicogna I, McDonald KC (2014) Attribution of divergent northern vegetation growth responses to lengthening non-frozen seasons using satellite optical-NIR and microwave remote sensing. Int J Remote Sens 35(10):3700–3721

    Google Scholar 

  • Kim Y, Kimball JS, Zhang K, McDonald KC (2012) Satellite detection of increasing northern hemisphere non-frozen seasons from 1979 to 2008: Implications for regional vegetation growth. Remote Sens Environ 121:472–487

    Google Scholar 

  • Kim Y, Kimball JS, McDonald KC, Glassy J (2011) Developing a global data record of daily landscape freeze/thaw status using satellite passive microwave remote sensing. IEEE Trans Geosci Remote Sens 49(3):949–960

    Google Scholar 

  • Kim Y, Huete AR, Miura T, Jiang Z (2010) Spectral compatibility of vegetation indices across sensors: band decomposition analysis with Hyperion data. J Appl Remote Sens 4:043520

    Google Scholar 

  • Kimball J S, Jones L A, Glassy J, Reichle R (2017) SMAP L4 Global Daily 9 km Carbon Net Ecosystem Exchange, Version 3. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi:https://doi.org/10.5067/O4HAQJEWWUU8. [Date Accessed]

  • Kimball JS, Jones LA, Glassy J, Stavros EN, Madani N, Reichle RH, Jackson T, Colliander A (2016) Soil moisture active passive mission L4_C data product asssessment (version 2 validated release), Greenbelt, MD, NASA Goddard Space Flight Center, USA. [online] Available: https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20160008108.pdf

  • Kimball JS, Jones LA, Zhang K, Heinsch FA, McDonald KC, Oechel WC (2009) A satellite approach to estimate land-atmosphere CO2 exchange for boreal and arctic biomes using MODIS and AMSR-E. IEEE Trans Geosci Remote Sens 47(2):569–587

    Google Scholar 

  • Kolk H, Heijmans MMPD, Huissteden J, Pullens JWM, Berendse F (2016) Potential arctic tundra vegetation shifts in response to changing temperature, precipitation and permafrost thaw. Biogeosciences 13:6229–6245

    Google Scholar 

  • Liljedahl AK, Boike J, Daanen RP, Fedorov AN, Frost GV, Grosse G, Hinzman LD, Iijma Y, Jorgenson JC, Matveyeva N, Necsoiu M, Raynolds MK, Romanovsky VE, Schulla J, Tape KD, Walker DA, Wilson CJ, Yabuki H, Zona D (2016) Pan-Arctic ice-wedge degradation in warming permafrost and its influence on tundra hydrology. Nat Geosci 9:312–318

    Google Scholar 

  • Loranty MM, Lieberman-Cribbin W, Berner LT, Natali SM, Goetz SJ, Alexander HD, Kholodov AL (2016) Spatial variation in vegetation productivity trends, fire disturbance, and soil carbon across arctic-boreal permafrost ecosystems. Environ Res Lett 11(9):095008

    Google Scholar 

  • Luus KA, Commane R, Parazoo NC, Benmergui J, Euskirchen ES, Frankenberg C, Joiner J, Lindaas J, Miller CE, Oechel WC, Zona D, Wofsy S, Lin JC (2017) Tundra photosynthesis captured by satellite-observed solar-induced chlorophyll fluorescence. Geophys Res Lett 44:1564–1573

    Google Scholar 

  • Madani N, Kimball JS, Jones LA, Parazoo NC, Guan K (2017) Global analysis of bioclimate controls on ecosystem productivity using satellite observations of solar-induced chlorophyll fluorescence. Remote Sens 9:530

    Google Scholar 

  • Malnes E, Karlsen SR, Johansen B, Bjerke J, Tommervik H (2016) Snow season variability in a boreal-Arctic transition area monitored by MODIS data. Environ Res Lett 11:125005

    Google Scholar 

  • McGuire AD, Chapin FSIII, Ruess R (2010) The dynamics of change in Alaska’s boreal forests: resilience and vulnerability in response to climate warming. Can J For Res 40(7):1195–1196

    Google Scholar 

  • McGuire AD, Anderson LG, Christensen TR, Dallimore S, Guo L, Hayes DJ, Heimann M, Lorenson TD, Macdonald RW, Roulet N (2009) Sensitivity of the carbon cycle in the Arctic to climate change. Ecol Monogr 79(4):523–555

    Google Scholar 

  • Meroni M, Rossini M, Guanter L, Alonso L, Rascher U, Colombo R, Moreno J (2009) Remote sensing of solar-induced chlorophyll fluorescence: review of methods and applications. Remote Sens Environ 113:2037–2051

    Google Scholar 

  • Miles VV, Esau I (2016) Spatial heterogeneity of green and browning between and within bioclimatic zones in northern West Siberia. Environ Res Lett 11:115002

    Google Scholar 

  • Morton DC, Le Page Y, DeFries R, Collatz GJ, Hurtt GC (2013) Understorey fire frequency and the fate of burned forests in southern Amazonia. Phil Trans R Soc B 368: 20120163. http://dx.doi.org/10.1098/rstb.2012.0163

  • Mu Q, Heinsch FA, Zhao M, Running SW (2007) Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote Sens Environ 111:519–536

    Google Scholar 

  • Parazoo NC, Arneth A, Pugh TAM, Smith B, Steiner N, Luus K, Commane R, Benmergui J, Stofferahn E, Liu J, Rodenbeck C, Kawa R, Euskirchen E, Zona D, Arndt K, Oechel W, Miller C (2018) Spring photosynthetic onset and net CO2 uptake in Alaska triggered by landscape thawing. Glob Change Biol 24:3416–3435

    Google Scholar 

  • Parazoo CN, Bowman K, Fisher JB, Frankenberg C, Jones DBA, Cescatti A, Perez-Priego O, Wohlfahrt G, Montagnani L (2015) Terrestrial gross primary production inferred from satellite fluorescence and vegetation models. Glob Change Biol 20:3103–3121

    Google Scholar 

  • Park H, Kim Y, Kimball JS (2016a) Widespread permafrost vulnerability and soil active layer increases over the high northern latitudes inferred from satellite remote sensing and process model assessments. Remote Sens Environ 175:349–358

    Google Scholar 

  • Park H, Yoshikawa Y, Oshima K, Kim Y, Ngo-duc T, Kimball JS, Yang D (2016b) Quantification of warming climate-induced changes in terrestrial arctic river ice thickness and phenology. J Clim 29:1733–1754

    Google Scholar 

  • Pearson RG, Phillips SJ, Loranty MM, Beck Beck P S A, Damoulad T, Knight SJ, Goetz SJ (2013) Shifts in Arctic vegetation and associated feedbacks under climate change. Nat Clim Change 3:673–677

    Google Scholar 

  • Phoenix GK, Bjerke JW (2016) Arctic browning: extreme events and trends reversing arctic greening. Glob Change Biol 22:2960–2962

    Google Scholar 

  • Piedallu C, Gégout J (2008) Efficient assessment of topographic solar radiation to improve plant distribution models. Agric For Meteorol 148(11):1696–1706

    Google Scholar 

  • Potter C (2014) Regional analysis of NASA satellite greenness trends for ecosystems of Arctic Alaska. Int J Geosci 5:997–1006

    Google Scholar 

  • Reichle R, De Lannoy G, Koster RD, Crow WT, Kimball JS, Liu Q (2018) SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data, Version 4. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/KPJNN2GI1DQR

  • Rogers BM, Solvik K, Hogg EH, Ju J, Masek JG, Michaelian M, Berner LT, Goetz SJ (2018) Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data. Glob Change Biol 24:2284–2304

    Google Scholar 

  • Rogers BM, Soya AJ, Goulden ML, Randerson JT (2015) Influence of tree species on continental differences in boreal fires and climate feedbacks. Nat Geosci 8:228–234

    Google Scholar 

  • Schimel D, Pavlick R, Fisher JB, Asner GP, Saatchi S, Townsend P, Miller C, Frankenberg C, Hibbard K, Cox P (2015) Observing terrestrial ecosystems and the carbon cycle from space. Glob Change Biol 21(5):1762–1776. https://doi.org/10.1111/gcb.12822

  • Screen JA (2017) Far-flung effects of Arctic warming. Nat Geosci 10:253–254

    Google Scholar 

  • Shabanov N, Vargas M, Miura T, Sei A, Danial A (2015) Evaluation of the performance of Suomi NPP VIIRS top of canopy vegetation indices over AERONET sites. Remote Sens Environ 162:29–44

    Google Scholar 

  • Shi H, Li L, Eamus D, Huete A, Cleverly J, Tian X, Yu Q, Wang S, Montagnani L, Magliulo V, Rotenberg E, Pavelka M, Carrara A (2017) Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of multiple land cover types. Ecol Ind 72:153–164

    Google Scholar 

  • Sitch S, McGuire AD, Kimball J, Gedney N, Gamon J, Engstrom R, Wolf A, Zhuang Q, Clein J, McDonald KC (2007) Assessing the carbon balance of circumpolar arctic tundra using remote sensing and process modeling. Ecol Appl 17(1):213–234

    Google Scholar 

  • SNAP (2012) Predicting Future Potential Climate-Biomes for the Yukon, Northwest Territories, and Alaska (https://www.snap.uaf.edu/attachments/Cliomes-FINAL.pdf)

  • Sulla-Menashe D, Woodcock CE, Friedl MA (2018) Canadian boreal forest greening and browning trends: an analysis of biogeographic patterns and the relative roles of disturbance versus climate drivers. Environ Res Lett 13:014007

    Google Scholar 

  • Tachikawa T, Hato M, Kaku M, Iwasaki A (2011) The characteristics of ASTER GDEM version 2, IGARSS

    Google Scholar 

  • Tape K, Sturm M, Racine C (2006) The evidence for shrub expansion in Northern Alaska and the Pan-Arctic. Glob Change Biol 12:686–702. https://doi.org/10.1111/j.1365-2486.2006.01128.x

  • Ueyama M, Iwata H, Harazono Y, Euskirchen ES, Oechel WC, Zona D (2013) Growing season and spatial variations of carbon fluxes of Arctic and boreal ecosystems in Alaska (USA). Ecol Appl 23(8):1798–1816

    Google Scholar 

  • Verbyla D (2015) Remote sensing of interannual boreal forest NDVI in relation to climatic conditions in interior Alaska. Environ Res Lett 10:125016

    Google Scholar 

  • Vermote EF, El Saleous NZ, Justice CO (2002) Atmospheric correction of MODIS data in the visible to middle infrared: first results. Remote Sens Environ 83:97–111

    Google Scholar 

  • Vickers H, Hogda KA, Solbo S, Karlsen SR, Tommervik H, Aanes R, Hansen BB (2016) Changes in green in the high Arctic: insights from a 30 year AVHRR max NDVI dataset for Svalbard. Environ Res Lett 11:105004

    Google Scholar 

  • Wagle P, Zhang Y, Jin C, Xiao X (2016) Comparison of solar-induced chlorophyll fluorescence, light-use efficiency, and process-based GPP models in maize. Ecol Appl 26(4):1211–1222

    Google Scholar 

  • Walker X, Johnstone JF (2014) Widespread negative correlations between black spruce growth and temperature across topographic moisture gradients in the boreal forest

    Google Scholar 

  • Walther S, Guanter L, Heim B, Jung M, Duveiller G, Wolanin A, Sachs T (2018) Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis. Biogeosciences https://doi.org/10.5194/bg-2018-196

  • Wang C, Chen J, Wu J, Tang Y, Shi P, Black TA, Zhu K (2017) A now-free vegetation index for improved monitoring of vegetation spring green-up date in deciduous ecosystems. Remote Sens Environ 196:1–12

    Google Scholar 

  • Xu L, Myneni RB, Chapin FS III, Callaghan TV, Pinzon JE, Tucker CJ, Zhu Z, Bi J, Ciais P, Tommervik H, Euskirchen ES, Forbes BC, Piao SL, Anderson BT, Ganguly S, Nemani RR, Goetz SJ, Beck PSA, Bunn AG, Cao C, Stroeve JC (2013) Temperature and vegetation seasonality diminishment over northern lands. Nat Clim Change 3:581–586

    Google Scholar 

  • Yang X, Tang J, Mustard JF, Lee JE, Rossini M, Joiner J, Munger JW, Kornfeld A, Richardson AD (2015) Solar-induced chlorophyll fluorescence that correlates with canopy photosynthesis on diurnal and seasonal scales in a temperate deciduous forest. Geophys Res Lett 42:2977–2987

    Google Scholar 

  • Yi Y, Kimball JS, Rawlins MA, Moghaddam M, Euskirchen ES (2015) The role of snow cover affecting boreal-arctic soil freeze-thaw and carbon dynamics. Biogeosciences 12:5811–5829

    Google Scholar 

  • Yi Y, Kimball JS, Reichle RH (2014) Spring hydrology determines summer net carbon uptake in northern ecosystems. Environ Res Lett 9:046003

    Google Scholar 

  • Yi Y, Kimball JS, Jones LA, Reichle RH, Nemani R, Margolis HA (2013) Recent climate and fire disturbance impacts on boreal and arctic ecosystem productivity estimated using a satellite-based terrestrial carbon flux model. J Geophys Res-Biogeosci 118:606–622

    Google Scholar 

  • Zhang K, Kimball JS, Kim Y, McDonald KC (2011) Changing freeze-thaw seasons in northern high latitudes and associated influences on evapotranspiration. Hydrol Process 25(26):4142–4151

    Google Scholar 

  • Zhang K, Kimball JS, Hogg EH, Zhao M, Oechel WC, Cassano JJ, Running SW (2008) Satellite-based model detection of recent climate-driven changes in northern high-latitude vegetation productivity. J Geophys Res-Biogeosci 113:G03033

    Google Scholar 

  • Zhang Y, Xiao X, Wu X, Zhang G, Qin Y, Dong J (2017) Data descriptor: a global moderate resolution dataset of gross primary production of vegetation for 2000–2016. Sci Data 4:170165

    Google Scholar 

  • Zhao M, Running SW, Heinsch FA, Nemani RR (2011) MODIS derived terrestrial primary production. In: Land remote sensing and global environmental change. Springer, New York, pp 635–660. http://dx.doi.org/10.1007/978-1-4419-6749-7_28

Download references

Acknowledgments

This work was conducted at the University of Montana under contract to NASA (NNX14AB20A, NNX15AT74A, NNX14AI50G). The GOME-2 SIF data used in this study are available at (https://acd-ext.gsfc.nasa.gov/People/Joiner/my_gifs/GOME_F/GOME-F.htm), while the GFED4 data record is available at (http://www.globalfiredata.org/). The SMAP L4C, AMSR VSM and FT-ESDR data were obtained from the National Snow and Ice Data Center (NSIDC), while the MODIS VI records were obtained from the NASA LP DAAC (https://modis.gsfc.nasa.gov/data/dataprod/mod13.php).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Youngwook Kim .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Kim, Y., Kimball, J.S., Parazoo, N., Kirchner, P. (2021). Diagnosing Environmental Controls on Vegetation Greening and Browning Trends Over Alaska and Northwest Canada Using Complementary Satellite Observations. In: Yang, D., Kane, D.L. (eds) Arctic Hydrology, Permafrost and Ecosystems. Springer, Cham. https://doi.org/10.1007/978-3-030-50930-9_20

Download citation

Publish with us

Policies and ethics