Intraspecific Differences in Spectral Reflectance Curves as Indicators of Reduced Vitality in High-Arctic Plants

Remote sensing is a suitable candidate for monitoring rapid changes in Polar regions, offering high-resolution spectral, spatial and radiometric data. This paper focuses on the spectral properties of dominant plant species acquired during the first week of August 2015. Twenty-eight plots were selected, which could easily be identified in the field as well as on RapidEye satellite imagery. Spectral measurements of individual species were acquired, and heavy metal contamination stress factors were measured contemporaneously. As a result, a unique spectral library of dominant plant species, heavy metal concentrations and damage ratios were achieved with an indication that species-specific changes due to environmental conditions can best be differentiated in the 1401–2400 nm spectral region. Two key arctic tundra species, Cassiope tetragona and Dryas octopetala, exhibited significant differences in this spectral region that were linked to a changing health status. Relationships between field and satellite measurements were comparable, e.g., the Red Edge Normalized Difference Vegetation Index (RENDVI) showed a strong and significant relationship (R2 = 0.82; p = 0.036) for the species Dryas octopetala. Cadmium and Lead were below detection levels while manganese, copper and zinc acquired near Longyearbyen were at concentrations comparable to other places in Svalbard. There were high levels of nickel near Longyearbyen (0.014 mg/g), while it was low (0.004 mg/g) elsewhere.

[1]  G. Guyot,et al.  Utilisation de la Haute Resolution Spectrale pour Suivre L'etat des Couverts Vegetaux , 1988 .

[2]  Amanda M. Schwantes,et al.  Global satellite monitoring of climate-induced vegetation disturbances. , 2015, Trends in plant science.

[3]  K. Meuleman,et al.  Mapping vegetation communities of the Karkonosze National Park using APEX hyperspectral data and Support Vector Machines , 2014 .

[4]  A. Gitelson,et al.  Optical Properties and Nondestructive Estimation of Anthocyanin Content in Plant Leaves¶ , 2001, Photochemistry and photobiology.

[5]  Donald A. Walker,et al.  The Circumpolar Arctic vegetation map , 2005 .

[6]  Bogdan Zagajewski,et al.  Assessment of Imaging Spectroscopy for rock identification in the Karkonosze Mountains, Poland , 2016 .

[7]  Claus Weihs,et al.  klaR Analyzing German Business Cycles , 2005, Data Analysis and Decision Support.

[8]  Ranga B. Myneni,et al.  Temperature and vegetation seasonality diminishment over northern lands , 2013 .

[9]  Bernt Johansen,et al.  he relationship between phytomass , NDVI and vegetation ommunities on , 2013 .

[10]  T. Callaghan,et al.  Climatic and biotic extreme events moderate long‐term responses of above‐ and belowground sub‐Arctic heathland communities to climate change , 2015, Global change biology.

[11]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .

[12]  Zbigniew Bochenek,et al.  Understanding the drivers of extensive plant damage in boreal and Arctic ecosystems: Insights from field surveys in the aftermath of damage. , 2017, The Science of the total environment.

[13]  Thomas Maere,et al.  Determination of Leaf Area Index, Total Foliar N, and Normalized Difference Vegetation Index for Arctic Ecosystems Dominated by Cassiope tetragona , 2009 .

[14]  B. Rock,et al.  Detection of changes in leaf water content using Near- and Middle-Infrared reflectances , 1989 .

[15]  Nicholas C. Coops,et al.  Employing ground-based spectroscopy for tree-species differentiation in the Gulf Islands National Park Reserve , 2010 .

[16]  A. Gitelson,et al.  Assessing Carotenoid Content in Plant Leaves with Reflectance Spectroscopy¶ , 2002, Photochemistry and photobiology.

[17]  F. Vilella,et al.  Leaf area index, water index, and red : Far red ratio calculated by spectral reflectance and its relation to plant architecture and cut rose production , 2006 .

[18]  Hans T⊘mmervik,et al.  Vegetation damage monitoring in the Pasvik area, northern Norway, using airborne casi spatial mode data , 2000 .

[19]  Jana Albrechtová,et al.  Classification of Tundra Vegetation in the Krkonoše Mts. National Park Using APEX, AISA Dual and Sentinel-2A Data , 2017 .

[20]  Ranga B. Myneni,et al.  Use of unmanned aircraft systems (UAS) in a multi-scale vegetation index study of arctic plant communities in Adventdalen on Svalbard , 2014 .

[21]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[22]  C. Woodcock,et al.  Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation , 2013 .

[23]  Bo Elberling,et al.  Environmental Impact on an Arctic Soil–Plant System Resulting from Metals Released from Coal Mine Waste in Svalbard (78° N) , 2008 .

[24]  C. Tucker,et al.  Dynamics of aboveground phytomass of the circumpolar Arctic tundra during the past three decades , 2012 .

[25]  W. G. Rees,et al.  Reflectance spectra of subarctic lichens between 400 and 2400 nm , 2004 .

[26]  Bing Zhang,et al.  Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States , 2017 .

[27]  Christian Mielke,et al.  Subalpine and alpine vegetation classification based on hyperspectral APEX and simulated EnMAP images , 2017 .

[28]  Bisun Datt,et al.  A New Reflectance Index for Remote Sensing of Chlorophyll Content in Higher Plants: Tests using Eucalyptus Leaves , 1999 .

[29]  Morten Tomter Store Norske Spitsbergen Kullkompani og samfunnsansvar : institusjonalisert praksis eller strategisk utviklingsarbeid : en case studie av hvordan Store Norske Spitsbergen Kullkompani forvalter samfunnsansvar , 2008 .

[30]  Marti J. Anderson,et al.  A new method for non-parametric multivariate analysis of variance in ecology , 2001 .

[31]  O. Mutanga,et al.  Spectral discrimination of papyrus vegetation (Cyperus papyrus L.) in swamp wetlands using field spectrometry , 2009 .

[32]  D. Sims,et al.  Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages , 2002 .

[33]  D. Roberts,et al.  Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales , 2005 .

[34]  Eirik Malnes,et al.  Record-low primary productivity and high plant damage in the Nordic Arctic Region in 2012 caused by multiple weather events and pest outbreaks , 2014 .

[35]  Zbigniew Bochenek,et al.  The Origin of Heavy Metals and Radionuclides Accumulated in the Soil and Biota Samples Collected in Svalbard, Near Longyearbyen , 2017 .

[36]  Scott J. Goetz,et al.  Satellite observations of high northern latitude vegetation productivity changes between 1982 and 2008: ecological variability and regional differences , 2011 .

[37]  Lennart Nilsen,et al.  Using Ordinary Digital Cameras in Place of Near-Infrared Sensors to Derive Vegetation Indices for Phenology Studies of High Arctic Vegetation , 2016, Remote. Sens..

[38]  Hans Tømmervik,et al.  Monitoring vegetation changes in Pasvik (Norway) and Pechenga in Kola Peninsula (Russia) using multitemporal Landsat MSS/TM data , 2003 .

[39]  P. Thenkabail,et al.  Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics , 2000 .

[40]  A. Gitelson,et al.  Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation , 1994 .

[41]  G. Birth,et al.  Measuring the Color of Growing Turf with a Reflectance Spectrophotometer1 , 1968 .

[42]  Lee A. Vierling,et al.  Differences in arctic tundra vegetation type and phenology as seen using bidirectional radiometry in the early growing season , 1997 .

[43]  Eric Hulten,et al.  Atlas of North European vascular plants : north of the Tropic of Cancer , 1987 .

[44]  J. Randerson,et al.  The impacts and implications of an intensifying fire regime on Alaskan boreal forest composition and albedo , 2011 .

[45]  G. Schmuck,et al.  Application of chlorophyll fluorescence in ecophysiology , 1986, Radiation and environmental biophysics.

[46]  Zbigniew Bochenek,et al.  The Use Of Mosses In Biomonitoring Of Selected Areas In Poland And Spitsbergen In The Years From 1975 To 2014 , 2015 .

[47]  Lucie Kupková,et al.  Laboratory and image spectroscopy for evaluating the biophysical state of meadow vegetation in the Krkonoše National Park , 2014 .

[48]  Christina Gloeckner,et al.  Modern Applied Statistics With S , 2003 .

[49]  G. Andreoli,et al.  Measurement and Modeling of the Spectral and Directional Reflection Properties of Lichen and Moss Canopies , 2000 .

[50]  Stein Rune Karlsen,et al.  Vegetation mapping of Svalbard utilising Landsat TM/ETM+ data , 2011, Polar Record.

[51]  W. R. Windham,et al.  Exploring the relationship between reflectance red edge and chlorophyll concentration in slash pine leaves. , 1995, Tree physiology.

[52]  René van der Wal,et al.  High-arctic plants like it hot: a long-term investigation of between-year variability in plant biomass , 2014 .

[53]  Jerzy Cierniewski,et al.  Assessment of Hyperspectral Remote Sensing for Analyzing the Impact of Human Trampling on Alpine Swards , 2017, Mountain Research and Development.

[54]  Bogdan Zagajewski,et al.  Variability in spectral characteristics of trampled high-mountain grasslands , 2014 .

[55]  Hankui K. Zhang,et al.  Examination of Sentinel-2A Multi-spectral Instrument (MSI) Reflectance Anisotropy and the Suitability of a General Method to Normalize MSI Reflectance to Nadir BRDF Adjusted Reflectance , 2017 .

[56]  Marcel Schwieder,et al.  Ground-Based Hyperspectral Characterization of Alaska Tundra Vegetation along Environmental Gradients , 2013, Remote. Sens..

[57]  Rasmus E. Benestad,et al.  Warmer and wetter winters: characteristics and implications of an extreme weather event in the High Arctic , 2014 .

[58]  D. Walker,et al.  Greening of arctic Alaska, 1981–2001 , 2003 .

[59]  Bogdan Zagajewski,et al.  The application of APEX images in the assessment of the state of non-forest vegetation in the Karkonosze Mountains , 2016 .

[60]  Terry V. Callaghan,et al.  Winter warming events damage sub‐Arctic vegetation: consistent evidence from an experimental manipulation and a natural event , 2009 .

[61]  A. Gitelson,et al.  Non‐destructive optical detection of pigment changes during leaf senescence and fruit ripening , 1999 .