Relationship between Spatiotemporal Variations of Climate, Snow Cover and Plant Phenology over the Alps - An Earth Observation-Based Analysis

Alpine ecosystems are particularly sensitive to climate change, and therefore it is of significant interest to understand the relationships between phenology and its seasonal drivers in mountain areas. However, no alpine-wide assessment on the relationship between land surface phenology (LSP) patterns and its climatic drivers including snow exists. Here, an assessment of the influence of snow cover variations on vegetation phenology is presented, which is based on a 17-year time-series of MODIS data. From this data snow cover duration (SCD) and phenology metrics based on the Normalized Difference Vegetation Index (NDVI) have been extracted at 250 m resolution for the entire European Alps. The combined influence of additional climate drivers on phenology are shown on a regional scale for the Italian province of South Tyrol using reanalyzed climate data. The relationship between vegetation and snow metrics strongly depended on altitude. Temporal trends towards an earlier onset of vegetation growth, increasing monthly mean NDVI in spring and late summer, as well as shorter SCD were observed, but they were mostly non-significant and the magnitude of these tendencies differed by altitude. Significant negative correlations between monthly mean NDVI and SCD were observed for 15-55% of all vegetated pixels, especially from December to April and in altitudes from 1000-2000 m. On the regional scale of South Tyrol, the seasonality of NDVI and SCD achieved the highest share of correlating pixels above 1500 m, while at lower elevations mean temperature correlated best. Examining the combined effect of climate variables, for average altitude and exposition, SCD had the highest effect on NDVI, followed by mean temperature and radiation. The presented analysis allows to assess the spatiotemporal patterns of earth-observation based snow and vegetation metrics over the Alps, as well as to understand the relative importance of snow as phenological driver with respect to other climate variables

[1]  Jing M. Chen,et al.  Land surface phenology from optical satellite measurement and CO2 eddy covariance technique , 2012 .

[2]  Sergio M. Vicente-Serrano,et al.  The impact of snow depth and snowmelt on the vegetation variability over central Siberia , 2005 .

[3]  Pim Martens,et al.  The European Phenology Network , 2003, International journal of biometeorology.

[4]  G. Yohe,et al.  A globally coherent fingerprint of climate change impacts across natural systems , 2003, Nature.

[5]  Ramakrishna R. Nemani,et al.  Real-time monitoring and short-term forecasting of land surface phenology , 2006 .

[6]  A. Strahler,et al.  Monitoring vegetation phenology using MODIS , 2003 .

[7]  M. Schaepman,et al.  Relative Influence of Timing and Accumulation of Snow on Alpine Land Surface Phenology , 2018 .

[8]  Ottar Michelsen,et al.  Continent-wide response of mountain vegetation to climate change , 2012 .

[9]  Stefan Wunderle,et al.  Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements , 2008, Sensors.

[10]  C. Defila,et al.  Phytophenological trends in Switzerland , 2001, International journal of biometeorology.

[11]  Annette Menzel,et al.  Growing season extended in Europe , 1999, Nature.

[12]  C. Appenzeller,et al.  A comparative study of satellite and ground-based phenology , 2007, International journal of biometeorology.

[13]  G. Grabherr,et al.  Climate effects on mountain plants , 1994, Nature.

[14]  A. Denning,et al.  Remote sensing data assimilation for a prognostic phenology model , 2008 .

[15]  Jürgen Symanzik,et al.  On the use of the advanced very high resolution radiometer for development of prognostic land surface phenology models , 2007 .

[16]  S. Kotlarski,et al.  21st century climate change in the European Alps--a review. , 2014, The Science of the total environment.

[17]  David W. Inouye,et al.  High Altitude Climates , 2003 .

[18]  Rogier de Jong,et al.  Variability and evolution of global land surface phenology over the past three decades (1982–2012) , 2016, Global change biology.

[19]  Jan Verbesselt,et al.  Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology , 2013, Remote. Sens..

[20]  Min Feng,et al.  Assessment of MODIS BRDF/Albedo Model Parameters (MCD43A1 Collection 6) for Directional Reflectance Retrieval , 2017, Remote. Sens..

[21]  C. Frei,et al.  The climate of daily precipitation in the Alps: development and analysis of a high‐resolution grid dataset from pan‐Alpine rain‐gauge data , 2014 .

[22]  Amanda S. Gallinat,et al.  Autumn, the neglected season in climate change research. , 2015, Trends in ecology & evolution.

[23]  N. Delbart,et al.  Determination of phenological dates in boreal regions using normalized difference water index , 2005 .

[24]  Peter M. Cox,et al.  Description of the "TRIFFID" Dynamic Global Vegetation Model , 2001 .

[25]  Lars Eklundh,et al.  Annual changes in MODIS vegetation indices of Swedish coniferous forests in relation to snow dynamics and tree phenology , 2010 .

[26]  Zhiyong Wang,et al.  Snow effects on alpine vegetation in the Qinghai-Tibetan Plateau , 2015, Int. J. Digit. Earth.

[27]  David M. Lawrence,et al.  An annual cycle of vegetation in a GCM. Part I: implementation and impact on evaporation , 2004 .

[28]  Günther Klonner,et al.  A dynamic eco-evolutionary model predicts slow response of alpine plants to climate warming , 2017, Nature Communications.

[29]  R. Dickinson,et al.  Evaluation of the Utility of Satellite-Based Vegetation Leaf Area Index Data for Climate Simulations , 2001 .

[30]  Stein Rune Karlsen,et al.  Spatial and Temporal Variability in the Onset of the Growing Season on Svalbard, Arctic Norway - Measured by MODIS-NDVI Satellite Data , 2014, Remote. Sens..

[31]  N. Delbart,et al.  Comparing land surface phenology with leafing and flowering observations from the PlantWatch citizen network , 2015 .

[32]  M. Coleman Views from the alps: Regional perspectives on climate change , 1999 .

[33]  Guiling Wang,et al.  Modeling seasonal vegetation variation and its validation against Moderate Resolution Imaging Spectroradiometer (MODIS) observations over North America , 2005 .

[34]  J. Mustard,et al.  Green leaf phenology at Landsat resolution: Scaling from the field to the satellite , 2006 .

[35]  J. Fox,et al.  Applied Regression Analysis and Generalized Linear Models , 2008 .

[36]  N. Delbart,et al.  Remote sensing of spring phenology in boreal regions: A free of snow-effect method using NOAA-AVHRR and SPOT-VGT data (1982-2004) , 2006 .

[37]  S. Schneider,et al.  Fingerprints of global warming on wild animals and plants , 2003, Nature.

[38]  Vivek K. Arora,et al.  A parameterization of leaf phenology for the terrestrial ecosystem component of climate models , 2005 .

[39]  Marcel Abendroth Physiological Plant Ecology Ecophysiology And Stress Physiology Of Functional Groups , 2016 .

[40]  A. Guisan,et al.  Potential Impact of Climate Change on Vegetation in the European Alps: A Review , 2001 .

[41]  Rik Leemans,et al.  Faculty Opinions recommendation of European phenological response to climate change matches the warming pattern. , 2006 .

[42]  Niklaus E. Zimmermann,et al.  Accelerated increase in plant species richness on mountain summits is linked to warming , 2018, Nature.

[43]  S. Running,et al.  A continental phenology model for monitoring vegetation responses to interannual climatic variability , 1997 .

[44]  Claudia Notarnicola,et al.  Altitude‐dependent influence of snow cover on alpine land surface phenology , 2017 .

[45]  Niklaus E. Zimmermann,et al.  Divergent vegetation growth responses to the 2003 heat wave in the Swiss Alps , 2005 .

[46]  Wentao Cai,et al.  Alpine vegetation phenology dynamic over 16years and its covariation with climate in a semi-arid region of China. , 2016, The Science of the total environment.

[47]  Per Jönsson,et al.  Seasonality extraction by function fitting to time-series of satellite sensor data , 2002, IEEE Trans. Geosci. Remote. Sens..

[48]  I. C. Prentice,et al.  An integrated biosphere model of land surface processes , 1996 .

[49]  Andrew Jarvis,et al.  Hole-filled SRTM for the globe Version 4 , 2008 .

[50]  Rasmus Fensholt,et al.  Evaluation of the Plant Phenology Index (PPI), NDVI and EVI for Start-of-Season Trend Analysis of the Northern Hemisphere Boreal Zone , 2017, Remote. Sens..

[51]  R. Barry PAST AND POTENTIAL FUTURE CHANGES IN MOUNTAIN ENVIRONMENTS , 1994 .

[52]  Michele Meroni,et al.  Phenological monitoring of grassland and larch in the Alps from Terra and Aqua MODIS images , 2011 .

[53]  H. Mooney,et al.  Shifting plant phenology in response to global change. , 2007, Trends in ecology & evolution.

[54]  Ramakrishna R. Nemani,et al.  A generalized, bioclimatic index to predict foliar phenology in response to climate , 2004 .

[55]  R. Rickli,et al.  Global climate change and variability and its influence on Alpine climate — concepts and observations , 1997 .

[56]  M. Schardt,et al.  Drought Impact on Phenology and Green Biomass Production of Alpine Mountain Forest—Case Study of South Tyrol 2001–2012 Inspected with MODIS Time Series , 2018 .

[57]  Geoffrey M. Henebry,et al.  Spatio-Temporal Statistical Methods for Modelling Land Surface Phenology , 2010 .

[58]  W. J. Shuttleworth,et al.  Incorporating NDVI-Derived LAI into the Climate Version of RAMS and Its Impact on Regional Climate , 2002 .

[59]  M. Bordoni,et al.  Climate change impacts on the Alpine ecosystem: an overview with focus on the soil - a review , 2016 .

[60]  P. Beck,et al.  Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI , 2006 .

[61]  C. Plutzar,et al.  Extinction debt of high-mountain plants under twenty-first-century climate change , 2012 .

[62]  J. von Hardenberg,et al.  Elevation-dependent warming in global climate model simulations at high spatial resolution , 2018, Climate Dynamics.

[63]  L. Eklundh,et al.  A physically based vegetation index for improved monitoring of plant phenology , 2014 .

[64]  David Paull,et al.  Using phase-spaces to characterize land surface phenology in a seasonally snow-covered landscape , 2015 .

[65]  Jean-Louis Roujean,et al.  Ability of the land surface model ISBA‐A‐gs to simulate leaf area index at the global scale: Comparison with satellites products , 2006 .

[66]  Michael D. Dettinger,et al.  Implementing a U.S. national phenology network , 2005 .

[67]  A. Menzel,et al.  Trends in phenological phases in Europe between 1951 and 1996 , 2000, International journal of biometeorology.

[68]  J. L. Kellermann,et al.  Snowmelt timing, phenology, and growing season length in conifer forests of Crater Lake National Park, USA , 2018, International Journal of Biometeorology.

[69]  C. Körner The Green Cover of Mountains in a Changing Environment , 2005 .

[70]  Bradley C. Reed,et al.  Remote Sensing Phenology , 2009 .

[71]  Cynthia Rosenzweig,et al.  Assessment of observed changes and responses in natural and managed systems , 2007 .

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

[73]  Dylan Keon,et al.  Equations for potential annual direct incident radiation and heat load , 2002 .

[74]  Annette Menzel,et al.  Effects of Different Methods on the Comparison between Land Surface and Ground Phenology - A Methodological Case Study from South-Western Germany , 2016, Remote. Sens..

[75]  P. Jarvis The Interpretation of the Variations in Leaf Water Potential and Stomatal Conductance Found in Canopies in the Field , 1976 .

[76]  G. Dedieu,et al.  Global-Scale Assessment of Vegetation Phenology Using NOAA/AVHRR Satellite Measurements , 1997 .

[77]  Harald Bugmann,et al.  Global Change and Mountain Regions:: An Overview of Current Knowledge , 2005 .

[78]  Kirsten M. de Beurs,et al.  Land surface phenology of North American mountain environments using moderate resolution imaging spectroradiometer data , 2011 .

[79]  C. Justice,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part II: The Generation of Global Fields of Terrestrial Biophysical Parameters from Satellite Data , 1996 .

[80]  Michael Lehning,et al.  Scale‐dependent effects of solar radiation patterns on the snow‐dominated hydrologic response , 2015 .

[81]  Jan Dick,et al.  Recent Plant Diversity Changes on Europe’s Mountain Summits , 2012, Science.

[82]  R. Ahas,et al.  Atmospheric mechanisms governing the spatial and temporal variability of phenological phases in central Europe , 2002 .

[83]  H. Fowler,et al.  Elevation-dependent warming in mountain regions of the world , 2015 .

[84]  Claudia Notarnicola,et al.  Snow Cover Maps from MODIS Images at 250 m Resolution, Part 2: Validation , 2013, Remote. Sens..

[85]  Michele Brunetti,et al.  HISTALP—historical instrumental climatological surface time series of the Greater Alpine Region , 2007 .

[86]  Annette Menzel,et al.  Recent spring phenology shifts in western Central Europe based on multiscale observations , 2014 .

[87]  R. Stöckli,et al.  European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset , 2004 .

[88]  Michele Meroni,et al.  Remote sensing of larch phenological cycle and analysis of relationships with climate in the Alpine region , 2010 .

[89]  Simon Ferrier,et al.  Space can substitute for time in predicting climate-change effects on biodiversity , 2013, Proceedings of the National Academy of Sciences.

[90]  O. Sonnentag,et al.  Climate change, phenology, and phenological control of vegetation feedbacks to the climate system , 2013 .

[91]  Linda O. Mearns,et al.  Investigating the Effect of Seasonal Plant Growth and Development in Three-Dimensional Atmospheric Simulations. Part I: Simulation of Surface Fluxes over the Growing Season , 2001 .

[92]  P. Marquet,et al.  A Significant Upward Shift in Plant Species Optimum Elevation During the 20th Century , 2008, Science.

[93]  S. Wipf,et al.  Enough space in a warmer world? Microhabitat diversity and small‐scale distribution of alpine plants on mountain summits , 2018 .

[94]  T. Vesala,et al.  Reduction of ecosystem productivity and respiration during the European summer 2003 climate anomaly: a joint flux tower, remote sensing and modelling analysis , 2007 .

[95]  Claudia Notarnicola,et al.  Area and volume loss of the glaciers in the Ortles-Cevedale group (Eastern Italian Alps): controls and imbalance of the remaining glaciers , 2013 .

[96]  Claudia Notarnicola,et al.  Remote Sensing Snow Cover Maps from Modis Images at 250 M Resolution, Part 1: Algorithm Description , 2022 .

[97]  David Riaño,et al.  Assessment of different topographic corrections in Landsat-TM data for mapping vegetation types (2003) , 2003, IEEE Trans. Geosci. Remote. Sens..

[98]  Martin Beniston,et al.  CLIMATIC CHANGE AT HIGH ELEVATION SITES: AN OVERVIEW , 1997 .

[99]  Liming Zhou,et al.  Dynamics of leaf area for climate and weather models , 2008 .

[100]  Mark D. Schwartz,et al.  Assessing satellite‐derived start‐of‐season measures in the conterminous USA , 2002 .

[101]  Conghe Song,et al.  Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index , 2011, Landscape Ecology.

[102]  I. Chuine,et al.  A unified model for budburst of trees. , 2000, Journal of theoretical biology.

[103]  M. Friedl,et al.  Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product , 2010 .

[104]  Michele Meroni,et al.  On the spatial and temporal variability of Larch phenological cycle in mountainous areas , 2009 .

[105]  S. Dech,et al.  The relationship between precipitation anomalies and satellite-derived vegetation activity in Central Asia , 2013 .

[106]  Nadine Gobron,et al.  Optical remote sensing of vegetation: Modeling, caveats, and algorithms , 1995 .

[107]  Mariana Vertenstein,et al.  The Community Land Model's Dynamic Global Vegetation Model (CLM-DGVM): Technical description and user's guide , 2004 .