An improved approach for remotely sensing water stress impacts on forest C uptake

Given that forests represent the primary terrestrial sink for atmospheric CO2 , projections of future carbon (C) storage hinge on forest responses to climate variation. Models of gross primary production (GPP) responses to water stress are commonly based on remotely sensed changes in canopy 'greenness' (e.g., normalized difference vegetation index; NDVI). However, many forests have low spectral sensitivity to water stress (SSWS) - defined here as drought-induced decline in GPP without a change in greenness. Current satellite-derived estimates of GPP use a vapor pressure deficit (VPD) scalar to account for the low SWSS of forests, but fail to capture their responses to water stress. Our objectives were to characterize differences in SSWS among forested and nonforested ecosystems, and to develop an improved framework for predicting the impacts of water stress on GPP in forests with low SSWS. First, we paired two independent drought indices with NDVI data for the conterminous US from 2000 to 2011, and examined the relationship between water stress and NDVI. We found that forests had lower SSWS than nonforests regardless of drought index or duration. We then compared satellite-derived estimates of GPP with eddy-covariance observations of GPP in two deciduous broadleaf forests with low SSWS: the Missouri Ozark (MO) and Morgan Monroe State Forest (MMSF) AmeriFlux sites. Model estimates of GPP that used VPD scalars were poorly correlated with observations of GPP at MO (r(2) = 0.09) and MMSF (r(2) = 0.38). When we included the NDVI responses to water stress of adjacent ecosystems with high SSWS into a model based solely on temperature and greenness, we substantially improved predictions of GPP at MO (r(2) = 0.83) and for a severe drought year at the MMSF (r(2) = 0.82). Collectively, our results suggest that large-scale estimates of GPP that capture variation in SSWS among ecosystems could improve predictions of C uptake by forests under drought.

[1]  James A. Westfall,et al.  NACP Aboveground Biomass and Carbon Baseline Data, V.2 (NBCD 2000), U.S.A., 2000 , 2013 .

[2]  C. Roumet,et al.  Tradeoffs between functional strategies for resource-use and drought-survival in Mediterranean rangeland species , 2013 .

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

[4]  J. Grace,et al.  Responses of Plants to Environmental Stresses. Volume II. Water, Radiation, Salt, and other Stresses. , 1980 .

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

[6]  F. Lelièvre,et al.  Survival and recovery of perennial forage grasses under prolonged Mediterranean drought: I. Growth, death, water relations and solute content in herbage and stubble. , 1998, The New phytologist.

[7]  P. Hanson,et al.  A six-year study of sapling and large-tree growth and mortality responses to natural and induced variability in precipitation and throughfall. , 2001, Tree physiology.

[8]  M. Palecki,et al.  THE DROUGHT MONITOR , 2002 .

[9]  T. Meyers,et al.  Environmental controls on water use efficiency during severe drought in an Ozark Forest in Missouri, USA , 2009 .

[10]  A. Huete,et al.  Amazon Forests Green-Up During 2005 Drought , 2007, Science.

[11]  Eric A Davidson,et al.  Drought effects on litterfall, wood production and belowground carbon cycling in an Amazon forest: results of a throughfall reduction experiment , 2008, Philosophical Transactions of the Royal Society B: Biological Sciences.

[12]  J. Moutinho-Pereira,et al.  Water Use Strategies of Plants Under Drought Conditions , 2012 .

[13]  R. Oren,et al.  Water deficits and hydraulic limits to leaf water supply. , 2002, Plant, cell & environment.

[14]  R. Marchin,et al.  Hydraulic failure and tree dieback are associated with high wood density in a temperate forest under extreme drought , 2011 .

[15]  S. Ganguly,et al.  Amazon forests did not green‐up during the 2005 drought , 2009 .

[16]  T. Huntington.  Evidence for intensification of the global water cycle: Review and synthesis , 2006 .

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

[18]  Sergi Munné-Bosch,et al.  Die and let live: leaf senescence contributes to plant survival under drought stress. , 2004, Functional plant biology : FPB.

[19]  Thomas Wohlgemuth,et al.  Precipitation manipulation experiments--challenges and recommendations for the future. , 2012, Ecology letters.

[20]  J. Flexas,et al.  Drought-inhibition of photosynthesis in C3 plants: stomatal and non-stomatal limitations revisited. , 2002, Annals of botany.

[21]  T. McKee,et al.  THE RELATIONSHIP OF DROUGHT FREQUENCY AND DURATION TO TIME SCALES , 1993 .

[22]  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.

[23]  Eileen H. Helmer,et al.  Root biomass allocation in the world's upland forests , 1997, Oecologia.

[24]  Alan H. Strahler,et al.  Global land cover mapping from MODIS: algorithms and early results , 2002 .

[25]  C. Justice,et al.  High-Resolution Global Maps of 21st-Century Forest Cover Change , 2013, Science.

[26]  L. Ji,et al.  Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices , 2003 .

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

[28]  R. Barthelmie,et al.  High-resolution projections of climate-related risks for the Midwestern USA , 2013 .

[29]  W. Cohen,et al.  Evaluation of MODIS NPP and GPP products across multiple biomes. , 2006 .

[30]  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 .

[31]  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 .

[32]  H. A. Mooney,et al.  Maximum rooting depth of vegetation types at the global scale , 1996, Oecologia.

[33]  Jonas Ardö,et al.  Evaluation of MODIS gross primary productivity for Africa using eddy covariance data , 2013 .

[34]  R. B. Jackson,et al.  A global analysis of root distributions for terrestrial biomes , 1996, Oecologia.

[35]  Sergio M. Vicente-Serrano,et al.  Response of vegetation to drought time-scales across global land biomes , 2012, Proceedings of the National Academy of Sciences.

[36]  Atul K. Jain,et al.  A model-data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis , 2012 .

[37]  J. Passioura.  Water in the Soil-Plant-Atmosphere Continuum , 1982 .

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

[39]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

[40]  B. E. Mahall,et al.  Drought and changes in leaf orientation for two California chaparral shrubs: Ceanothus megacarpus and Ceanothus crassifolius , 1985, Oecologia.

[41]  Andrew E. Suyker,et al.  Assessing net ecosystem carbon exchange of U.S. terrestrial ecosystems by integrating eddy covariance flux measurements and satellite observations , 2011 .