Capturing species-level drought responses in a temperate deciduous forest using ratios of photochemical reflectance indices between sunlit and shaded canopies

To classify trees along a spectrum of isohydric to anisohydric behavior is a promising new framework for identifying tree species' sensitivities to drought stress, directly related to the vulnerability of carbon uptake of terrestrial ecosystems with increased hydroclimate variability. Trees with isohydric strategies regulate stomatal conductance to maintain stationary leaf water potential, while trees with anisohydric strategies allow leaf water potential to fall, which in the absence of significant hydraulic cavitation will facilitate greater rates of carbon uptake. Despite the recognition of the gas exchange consequences of isohydric and anisohydric strategies for individual tree species, there have been few studies regarding whether isohydric trees produces distinct spectral signatures under drought stress that can be remotely sensed. Here, we examined the capability of four vegetation indices (PRI, NDVI, NDVI705, and EVI) to capture the differences in spectral responses between isohydric and anisohydric trees within a deciduous forest in central Indiana, USA. Both leaf-level spectral measurements and canopy-scale satellite observations were used to compare peak growing-season spectral signatures between a drought and a non-drought year. At the leaf scale, two vegetation indices (NDVI and NDVI705) failed to capture the drought signal or the divergent isohydric/anisohydric behavior. EVI successfully captured the drought signal at both leaf and canopy scales, but failed to capture the divergent behavior between isohydric and anisohydric tree species during the drought. PRI captured both drought signals and divergent isohydric/anisohydric behavior at both leaf and canopy scales once normalized between sunlit (backward direction images) and shaded (forward direction images) portions of canopy, which indicates drought stress and subsequent photosynthetic downregulation are greater in the sunlit portion of canopy. This study presents a significant step forward in our ability to directly mapping emergent isohydricity at different scales based on divergent spectral signatures between sunlit and shaded canopies.

[1]  John A Gamon,et al.  Three causes of variation in the photochemical reflectance index (PRI) in evergreen conifers. , 2015, The New phytologist.

[2]  J. Vose,et al.  Quantifying structural and physiological controls on variation in canopy transpiration among planted pine and hardwood species in the southern Appalachians , 2011 .

[3]  N. McDowell,et al.  Darcy's law predicts widespread forest mortality under climate warming , 2015 .

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

[5]  Alan H. Strahler,et al.  Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: effect of crown shape and mutual shadowing , 1992, IEEE Trans. Geosci. Remote. Sens..

[6]  A. Nardini,et al.  Global convergence in the vulnerability of forests to drought , 2012, Nature.

[7]  Pablo J. Zarco-Tejada,et al.  Assessing Canopy PRI for Water Stress detection with Diurnal Airborne Imagery , 2008 .

[8]  Josep Peñuelas,et al.  The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: A review and meta-analysis , 2011 .

[9]  L. Band,et al.  Energy, water, and carbon fluxes in a loblolly pine stand: Results from uniform and gappy canopy models with comparisons to eddy flux data , 2009 .

[10]  J. Peñuelas,et al.  Assessment of photosynthetic radiation‐use efficiency with spectral reflectance , 1995 .

[11]  Guoqing Li,et al.  Effect of drought on pigments, osmotic adjustment and antioxidant enzymes in six woody plant species in karst habitats of southwestern China , 2011 .

[12]  S. Wofsy,et al.  Midday values of gross CO2 flux and light use efficiency during satellite overpasses can be used to directly estimate eight-day mean flux , 2005 .

[13]  K. Soudani,et al.  Relationships between photochemical reflectance index and light-use efficiency in deciduous and evergreen broadleaf forests , 2014 .

[14]  Amit Angal,et al.  Characterization of Terra and Aqua MODIS VIS, NIR, and SWIR Spectral Bands' Calibration Stability , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[15]  Lawrence A. Corp,et al.  The Photochemical Reflectance Index from Directional Cornfield Reflectances: Observations and Simulations , 2012 .

[16]  T. Hwang,et al.  Optical remote sensing of terrestrial ecosystem primary productivity , 2013 .

[17]  Hans Peter Schmid,et al.  Measurements of CO2 and energy fluxes over a mixed hardwood forest in the mid-western United States , 2000 .

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

[19]  Moon S. Kim,et al.  Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance , 2000 .

[20]  T. Scanlon,et al.  Comparing methods for partitioning a decade of carbon dioxide and water vapor fluxes in a temperate forest , 2016 .

[21]  Josep Peñuelas,et al.  Leaf and stand-level carbon uptake of a Mediterranean forest estimated using the satellite-derived reflectance indices EVI and PRI , 2012 .

[22]  Hans Peter Schmid,et al.  Potential of MODIS ocean bands for estimating CO2 flux from terrestrial vegetation: A novel approach , 2004 .

[23]  Danielle E. Marias,et al.  Stomatal kinetics and photosynthetic gas exchange along a continuum of isohydric to anisohydric regulation of plant water status. , 2017, Plant, cell & environment.

[24]  T. A. Black,et al.  Global parameterization and validation of a two‐leaf light use efficiency model for predicting gross primary production across FLUXNET sites , 2016 .

[25]  J. Vose,et al.  Drought limitations to leaf-level gas exchange: results from a model linking stomatal optimization and cohesion-tension theory. , 2016, Plant, cell & environment.

[26]  Peter A. Troch,et al.  Temperature sensitivity of drought-induced tree mortality portends increased regional die-off under global-change-type drought , 2009, Proceedings of the National Academy of Sciences.

[27]  N. McDowell,et al.  Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought? , 2008, The New phytologist.

[28]  G. Asner,et al.  Drought stress and carbon uptake in an Amazon forest measured with spaceborne imaging spectroscopy. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[29]  Pierre Gentine,et al.  Global variations in ecosystem‐scale isohydricity , 2017, Global change biology.

[30]  Thomas Hilker,et al.  Data assimilation of photosynthetic light-use efficiency using multi-angular satellite data: I. Model formulation , 2011 .

[31]  D. Chittleborough,et al.  The potential for deep groundwater use by Acacia papyrocarpa (Western myall) in a water‐limited environment , 2017 .

[32]  J. Peñuelas,et al.  PRI assessment of long-term changes in carotenoids/chlorophyll ratio and short-term changes in de-epoxidation state of the xanthophyll cycle , 2009 .

[33]  Jing M. Chen,et al.  Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications , 1999 .

[34]  Hans Peter Schmid,et al.  Chronic water stress reduces tree growth and the carbon sink of deciduous hardwood forests , 2014, Global change biology.

[35]  P. O'Gorman,et al.  The physical basis for increases in precipitation extremes in simulations of 21st-century climate change , 2009, Proceedings of the National Academy of Sciences.

[36]  S. Running,et al.  Satellite detection of soil moisture related water stress impacts on ecosystem productivity using the MODIS-based photochemical reflectance index , 2016 .

[37]  C. Field,et al.  Allocating leaf nitrogen for the maximization of carbon gain: Leaf age as a control on the allocation program , 1983, Oecologia.

[38]  A. Dai.  Increasing drought under global warming in observations and models , 2013 .

[39]  D. Pury,et al.  Simple scaling of photosynthesis from leaves to canopies without the errors of big‐leaf models , 1997 .

[40]  W. Oechel,et al.  Parallel adjustments in vegetation greenness and ecosystem CO2 exchange in response to drought in a Southern California chaparral ecosystem , 2006 .

[41]  D. Dragoni,et al.  Dynamics of stem water uptake among isohydric and anisohydric species experiencing a severe drought , 2017, Tree physiology.

[42]  D. Baldocchi,et al.  Seasonal trends in photosynthetic parameters and stomatal conductance of blue oak (Quercus douglasii) under prolonged summer drought and high temperature. , 2003, Tree physiology.

[43]  Thomas Hilker,et al.  Linking stand architecture with canopy reflectance to estimate vertical patterns of light-use efficiency , 2017 .

[44]  John A. Gamon,et al.  Effects of irradiance and photosynthetic downregulation on the photochemical reflectance index in Douglas-fir and ponderosa pine , 2013 .

[45]  Rafael Poyatos,et al.  A new look at water transport regulation in plants. , 2014, The New phytologist.

[46]  Bryan A. Franz,et al.  Moderate Resolution Imaging Spectroradiometer on Terra: limitations for ocean color applications , 2008 .

[47]  A. Oishi,et al.  On the difference in the net ecosystem exchange of CO2 between deciduous and evergreen forests in the southeastern United States , 2015, Global change biology.

[48]  B. Demmig‐Adams,et al.  Xanthophyll cycle and light stress in nature: uniform response to excess direct sunlight among higher plant species , 1996, Planta.

[49]  G. Bohrer,et al.  Contrasting strategies of hydraulic control in two codominant temperate tree species , 2017 .

[50]  S. Munné-Bosch,et al.  Drought‐induced senescence is characterized by a loss of antioxidant defences in chloroplasts , 2001 .

[51]  C. Allen,et al.  Climate‐induced forest dieback as an emergent global phenomenon , 2007 .

[52]  D. Dragoni,et al.  The role of isohydric and anisohydric species in determining ecosystem-scale response to severe drought , 2015, Oecologia.

[53]  Elizabeth M. Middleton,et al.  Regional mapping of gross light-use efficiency using MODIS spectral indices , 2008 .

[54]  R. Leuning,et al.  A two-leaf model for canopy conductance, photosynthesis and partitioning of available energy I:: Model description and comparison with a multi-layered model , 1998 .

[55]  Thomas Hilker,et al.  Estimation of Light-use Efficiency of Terrestrial Ecosystems from Space: A Status Report , 2010 .

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

[57]  D. Sims,et al.  An improved approach for remotely sensing water stress impacts on forest C uptake , 2014, Global change biology.

[58]  Josep Peñuelas,et al.  Affecting Factors and Recent Improvements of the Photochemical Reflectance Index (PRI) for Remotely Sensing Foliar, Canopy and Ecosystemic Radiation-Use Efficiencies , 2016, Remote. Sens..

[59]  Hans Peter Schmid,et al.  Evidence of increased net ecosystem productivity associated with a longer vegetated season in a deciduous forest in south‐central Indiana, USA , 2010 .

[60]  S. Heckathorn,et al.  Drought-induced nitrogen retranslocation in perennial C4 grasses of tallgrass prairie , 1994 .

[61]  Jennifer Nakamura,et al.  Drought in the Southeastern United States: Causes, Variability over the Last Millennium, and the Potential for Future Hydroclimate Change* , 2009 .

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

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

[64]  N. McDowell,et al.  Pragmatic hydraulic theory predicts stomatal responses to climatic water deficits. , 2016, The New phytologist.

[65]  H. Schmid,et al.  An initial intercomparison of micrometeorological and ecological inventory estimates of carbon exchange in a mid‐latitude deciduous forest , 2002 .

[66]  Jehn-Yih Juang,et al.  Separating the effects of climate and vegetation on evapotranspiration along a successional chronosequence in the southeastern US , 2006 .

[67]  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 .

[68]  A. Huete,et al.  A comparison of vegetation indices over a global set of TM images for EOS-MODIS , 1997 .

[69]  N. Buchmann,et al.  Towards an advanced assessment of the hydrological vulnerability of forests to climate change-induced drought. , 2014, The New phytologist.

[70]  C. Field,et al.  A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency , 1992 .

[71]  J. Gamon,et al.  The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels , 1997, Oecologia.

[72]  N. Coops,et al.  Multi-Angle Remote Sensing of Forest Light Use Efficiency , 2007 .

[73]  P. North,et al.  Remote sensing of canopy light use efficiency using the photochemical reflectance index , 2001 .

[74]  Hainian Zeng,et al.  Drought-deciduous behavior reduces nutrient losses from temperate deciduous trees under severe drought , 2010, Oecologia.

[75]  Danielle E. Marias,et al.  Mapping 'hydroscapes' along the iso- to anisohydric continuum of stomatal regulation of plant water status. , 2016, Ecology letters.

[76]  C. Tucker.  Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[77]  A. Zeileis,et al.  Remotely-sensed detection of effects of extreme droughts on gross primary production , 2016, Scientific Reports.

[78]  T. A. Black,et al.  Separating physiologically and directionally induced changes in PRI using BRDF models , 2008 .

[79]  Alan H. Strahler,et al.  A hybrid geometric optical-radiative transfer approach for modeling albedo and directional reflectance of discontinuous canopies , 1995, IEEE Transactions on Geoscience and Remote Sensing.

[80]  T. A. Black,et al.  A MODIS-derived photochemical reflectance index to detect inter-annual variations in the photosynthetic light-use efficiency of a boreal deciduous forest , 2005 .

[81]  P. Zarco-Tejada,et al.  A PRI-based water stress index combining structural and chlorophyll effects: Assessment using diurnal narrow-band airborne imagery and the CWSI thermal index , 2013 .

[82]  Josep Peñuelas,et al.  A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers , 2016, Proceedings of the National Academy of Sciences.