Soil Drought Anomalies in MODIS GPP of a Mediterranean Broadleaved Evergreen Forest

The Moderate Resolution Imaging Spectroradiometer (MODIS) yields global operational estimates of terrestrial gross primary production (GPP). In this study, we compared MOD17A2 GPP with tower eddy flux-based estimates of GPP from 2001 to 2010 over an evergreen broad-leaf Mediterranean forest in Southern France with a significant summer drought period. The MOD17A2 GPP shows seasonal variations that are inconsistent with the tower GPP, with close-to-accurate winter estimates and significant discrepancies for summer estimates which are the least accurate. The analysis indicated that the MOD17A2 GPP has high bias relative to tower GPP during severe summer drought which we hypothesized caused by soil water limitation. Our investigation showed that there was a significant correlation (R2 = 0.77, p < 0.0001) between the relative soil water content and the relative error of MOD17A2 GPP. Therefore, the relationship between the error and the measured relative soil water content could explain anomalies in MOD17A2 GPP. The results of this study indicate that careful consideration of the water conditions input to the MOD17A2 GPP algorithm on remote sensing is required in order to provide accurate predictions of GPP. Still, continued efforts are necessary to ascertain the most appropriate index, which characterizes soil water limitation in water-limited environments using remote sensing.

[1]  Y. Kerr,et al.  Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations , 2012 .

[2]  F. Giorgi,et al.  Climate change projections for the Mediterranean region , 2008 .

[3]  T. Lenton.  Early warning of climate tipping points , 2011 .

[4]  S. Dobrowski,et al.  Steady-state chlorophyll a fluorescence detection from canopy derivative reflectance and double-peak red-edge effects , 2003 .

[5]  T. Lenton,et al.  Integrating tipping points into climate impact assessments , 2013, Climatic Change.

[6]  Lawrence E. Band,et al.  Evaluating drought effect on MODIS Gross Primary Production (GPP) with an eco‐hydrological model in the mountainous forest, East Asia , 2008 .

[7]  T. Vesala,et al.  On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm , 2005 .

[8]  Damian Barrett,et al.  On the efficacy of combining thermal and microwave satellite data as observational constraints for root-zone soil moisture estimation. , 2009 .

[9]  Ramakrishna R. Nemani,et al.  Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[10]  C. Frankenberg,et al.  Linking chlorophyll a fluorescence to photosynthesis for remote sensing applications: mechanisms and challenges. , 2014, Journal of experimental botany.

[11]  K. Soudani,et al.  Ground-based Network of NDVI measurements for tracking temporal dynamics of canopy structure and vegetation phenology in different biomes , 2012 .

[12]  S. Rambal.  Les transferts d'eau dans le systeme sol-plante en region mediterraneenne karstique : une approche hierarchique , 1990 .

[13]  Federico Magnani,et al.  Let’s exploit available knowledge on vegetation fluorescence , 2014, Proceedings of the National Academy of Sciences.

[14]  J. Pal,et al.  Projected changes in mean and extreme precipitation over the Mediterranean region from a high resolution double nested RCM simulation , 2006 .

[15]  M. Lawes,et al.  The 10 Australian ecosystems most vulnerable to tipping points , 2011 .

[16]  M. S. Moran,et al.  Reply to Magnani et al.: Linking large-scale chlorophyll fluorescence observations with cropland gross primary production , 2014, Proceedings of the National Academy of Sciences.

[17]  Kasturi Devi Kanniah,et al.  Evaluation of Collections 4 and 5 of the MODIS Gross Primary Productivity product and algorithm improvement at a tropical savanna site in northern Australia , 2009 .

[18]  A. Arneth,et al.  Fluxes of carbon and water in a Pinus radiata forest subject to soil water deficit , 1998 .

[19]  S. Frolking,et al.  Satellite-based modeling of gross primary production in a seasonally moist tropical evergreen forest , 2005 .

[20]  Cristina Milesi,et al.  User's Guide GPP and NPP (MOD17A2/A3) Products NASA MODIS Land Algorithm , 2003 .

[21]  Markus Reichstein,et al.  Drought controls over conductance and assimilation of a Mediterranean evergreen ecosystem: scaling from leaf to canopy , 2003 .

[22]  Andrew E. Suyker,et al.  Estimation of crop gross primary production (GPP): I. impact of MODIS observation footprint and impact of vegetation BRDF characteristics , 2014 .

[23]  S. Rambal,et al.  Functional changes in the control of carbon fluxes after 3 years of increased drought in a Mediterranean evergreen forest? , 2009 .

[24]  D. Riaño,et al.  Estimation of live fuel moisture content from MODIS images for fire risk assessment , 2008 .

[25]  S. Tarantola,et al.  Detecting vegetation leaf water content using reflectance in the optical domain , 2001 .

[26]  R. Leuning,et al.  Carbon and water fluxes over a temperate Eucalyptus forest and a tropical wet/dry savanna in Australia: measurements and comparison with MODIS remote sensing estimates , 2005 .

[27]  M. Vanclooster,et al.  Improving soil moisture profile reconstruction from ground-penetrating radar data: a maximum likelihood ensemble filter approach , 2013 .

[28]  P. Quézel,et al.  Ecologie et biogéographie des forêts du bassin méditerranéen , 2003 .

[29]  Marco Bindi,et al.  Climatic changes and associated impacts in the Mediterranean resulting from a 2°C global warming , 2009 .

[30]  Nicholas C. Coops,et al.  Incorporation of a soil water modifier into MODIS predictions of temperate Douglas-fir gross primary productivity: Initial model development , 2007 .

[31]  S. Rambal,et al.  Simulating climate change impacts on fire frequency and vegetation dynamics in a Mediterranean‐type ecosystem , 2002 .

[32]  G. Bonan.  Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests , 2008, Science.

[33]  W. Oechel,et al.  A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS , 2008 .

[34]  S. Running,et al.  Contrasting Climatic Controls on the Estimated Productivity of Global Terrestrial Biomes , 1998, Ecosystems.

[35]  Maosheng Zhao,et al.  Improvements of the MODIS terrestrial gross and net primary production global data set , 2005 .

[36]  S. Rambal.  Hierarchy and Productivity of Mediterranean-Type Ecosystems , 2001 .

[37]  Michel Crépon,et al.  21st century climate change scenario for the Mediterranean using a coupled atmosphere–ocean regional climate model , 2008 .

[38]  Bo-Cai Gao,et al.  Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll $(\hbox{fAPAR}_{\rm chl})$ and Leaf Water Content (LWC) , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[39]  Jadunandan Dash,et al.  An algorithm to derive the fraction of photosynthetically active radiation absorbed by photosynthetic elements of the canopy (FAPAR(ps)) from eddy covariance flux tower data. , 2013, The New phytologist.

[40]  N. Breda,et al.  A generic model of forest canopy conductance dependent on climate, soil water availability and leaf area index , 2000 .

[41]  Elizabeth M. Middleton,et al.  Variations of Foliage Chlorophyll fAPAR and Foliage Non-Chlorophyll fAPAR (fAPAR$_{\rm chl}$, fAPAR$_{\rm non\mathchar "702D chl}$) at the Harvard Forest , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[42]  S. Wofsy,et al.  Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data , 2004 .

[43]  E. Fischer,et al.  Consistent geographical patterns of changes in high-impact European heatwaves , 2010 .

[44]  Maosheng Zhao,et al.  Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009 , 2010, Science.

[45]  Rasmus Fensholt,et al.  Estimation of Herbaceous Fuel Moisture Content Using Vegetation Indices and Land Surface Temperature from MODIS Data , 2013, Remote. Sens..

[46]  S. Running,et al.  Regional evaporation estimates from flux tower and MODIS satellite data , 2007 .

[47]  S. Rambal,et al.  Identifying spatial patterns of Mediterranean landscapes from geostatistical analysis of remotely-sensed data , 1994 .

[48]  W. Oechel,et al.  A continuous measure of gross primary production for the conterminous United States derived from MODIS and AmeriFlux data , 2010, Remote Sensing of Environment.

[49]  Serge Rambal,et al.  Simulating carbon and water flows and growth in a Mediterranean evergreen Quercus ilex coppice using the FOREST-BGC model , 2002 .

[50]  Maosheng Zhao,et al.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production , 2004 .

[51]  F. Giorgi,et al.  Increased aridity in the Mediterranean region under greenhouse gas forcing estimated from high resolution simulations with a regional climate model , 2008 .

[52]  J. Monteith.  Climate and the efficiency of crop production in Britain , 1977 .

[53]  D. Guyon,et al.  Quality analysis applied on eddy covariance measurements at complex forest sites using footprint modelling , 2005 .

[54]  K. Davis,et al.  Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data , 2010 .

[55]  Marco Bindi,et al.  Potential impact of climate change on fire risk in the Mediterranean area , 2006 .

[56]  F. Baret,et al.  Estimating light absorption by chlorophyll, leaf and canopy in a deciduous broadleaf forest using MODIS data and a radiative transfer model , 2005 .

[57]  Maosheng Zhao,et al.  Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses , 2006 .

[58]  S. Rambal.  The differential role of mechanisms for drought resistance in a Mediterranean evergreen shrub: a simulation approach , 1993 .

[59]  S. Rambal,et al.  Modelling the drought impact on monoterpene fluxes from an evergreen Mediterranean forest canopy , 2009, Oecologia.

[60]  Ü. Rannik,et al.  Estimates of the annual net carbon and water exchange of forests: the EUROFLUX methodology , 2000 .

[61]  Markus Reichstein,et al.  Tracking seasonal drought effects on ecosystem light use efficiency with satellite-based PRI in a Mediterranean forest. , 2009 .

[62]  Wolfgang Wagner,et al.  Inter-comparison of microwave satellite soil moisture retrievals over the Murrumbidgee Basin, southeast Australia , 2013 .

[63]  Damian Barrett,et al.  Multi-sensor model-data fusion for estimation of hydrologic and energy flux parameters , 2008 .

[64]  Nicholas C. Coops,et al.  Comparison of MODIS, eddy covariance determined and physiologically modelled gross primary production (GPP) in a Douglas-fir forest stand , 2007 .

[65]  Maosheng Zhao,et al.  Improvements to a MODIS global terrestrial evapotranspiration algorithm , 2011 .

[66]  E. Wood,et al.  Projected changes in drought occurrence under future global warming from multi-model, multi-scenario, IPCC AR4 simulations , 2008 .

[67]  M. S. Moran,et al.  Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence , 2014, Proceedings of the National Academy of Sciences.

[68]  S. Rambal,et al.  Long‐term transpiration change with rainfall decline in a Mediterranean Quercus ilex forest , 2009 .

[69]  K. Soudani,et al.  Remote sensing: A green illusion , 2014, Nature.

[70]  P. Ciais,et al.  Europe-wide reduction in primary productivity caused by the heat and drought in 2003 , 2005, Nature.

[71]  Markus Reichstein,et al.  Evidence for soil water control on carbon and water dynamics in European forests during the extremely dry year: 2003 , 2007 .

[72]  C. Schmullius,et al.  Remote sensing of ecosystem light use efficiency with MODIS-based PRI , 2011 .

[73]  T. Vesala,et al.  Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation , 2006 .

[74]  Arnaud Carrara,et al.  Biogeosciences Quality control of CarboEurope flux data – Part 1 : Coupling footprint analyses with flux data quality assessment to evaluate sites in forest ecosystems , 2008 .

[75]  Gaylon S. Campbell,et al.  A SIMPLE METHOD FOR DETERMINING UNSATURATED CONDUCTIVITY FROM MOISTURE RETENTION DATA , 1974 .

[76]  W. Cohen,et al.  Site‐level evaluation of satellite‐based global terrestrial gross primary production and net primary production monitoring , 2005 .

[77]  T. A. Black,et al.  Can a satellite-derived estimate of the fraction of PAR absorbed by chlorophyll (FAPARchl) improve predictions of light-use efficiency and ecosystem photosynthesis for a boreal aspen forest? , 2009 .

[78]  F. Giorgi,et al.  Climate change hot‐spots , 2006 .

[79]  James S. Clark,et al.  Coordinated approaches to quantify long‐term ecosystem dynamics in response to global change , 2011 .

[80]  Laurie A. Chisholm,et al.  Monitoring live fuel moisture content of heathland, shrubland and sclerophyll forest in south-eastern Australia using MODIS data , 2012 .

[81]  Jadunandan Dash,et al.  Developing a diagnostic model for estimating terrestrial vegetation gross primary productivity using the photosynthetic quantum yield and Earth Observation data , 2013, Global change biology.

[82]  Zhongbo Su,et al.  Soil moisture mapping over the central part of the Tibetan Plateau using a series of ASAR WS images , 2012 .

[83]  S. Rambal,et al.  Seasonal and annual variation of carbon exchange in an evergreen Mediterranean forest in southern France , 2008 .

[84]  Steven W. Running,et al.  Evaluating water stress controls on primary production in biogeochemical and remote sensing based models , 2007 .

[85]  John Hom,et al.  Improved estimates of net primary productivity from modis satellite data at regional and local scales. , 2006, Ecological applications : a publication of the Ecological Society of America.

[86]  Zirui Liu,et al.  Evaluating Parameter Adjustment in the MODIS Gross Primary Production Algorithm Based on Eddy Covariance Tower Measurements , 2014, Remote. Sens..

[87]  D. Hollinger,et al.  MODELING GROSS PRIMARY PRODUCTION OF AN EVERGREEN NEEDLELEAF FOREST USING MODIS AND CLIMATE DATA , 2005 .

[88]  S. Seneviratne,et al.  Hot days induced by precipitation deficits at the global scale , 2012, Proceedings of the National Academy of Sciences.

[89]  Kasturi Devi Kanniah,et al.  Response of savanna gross primary productivity to interannual variability in rainfall , 2013 .

[90]  Wolfgang Wagner,et al.  Evaluation of the predicted error of the soil moisture retrieval from C-band SAR by comparison against modelled soil moisture estimates over Australia , 2012, Remote sensing of environment.

[91]  J. Monteith.  SOLAR RADIATION AND PRODUCTIVITY IN TROPICAL ECOSYSTEMS , 1972 .

[92]  J. Peñuelas,et al.  Remote estimation of carbon dioxide uptake by a Mediterranean forest , 2008 .

[93]  Emanuele Santi,et al.  Soil moisture mapping using Sentinel-1 images: Algorithm and preliminary validation , 2013 .

[94]  N. Breda.  Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. , 2003, Journal of experimental botany.

[95]  Jadunandan Dash,et al.  Evaluation of the influence of two operational fraction of absorbed photosynthetically active radiation (FAPAR) products on terrestrial ecosystem productivity modelling , 2014 .

[96]  Tao Zhang,et al.  On the Increased Frequency of Mediterranean Drought , 2012 .

[97]  T. Meyers,et al.  Climate extremes and grassland potential productivity , 2012 .