Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements.

Leaf aging is a fundamental driver of changes in leaf traits, thereby regulating ecosystem processes and remotely sensed canopy dynamics. We explore leaf reflectance as a tool to monitor leaf age and develop a spectra-based partial least squares regression (PLSR) model to predict age using data from a phenological study of 1099 leaves from 12 lowland Amazonian canopy trees in southern Peru. Results demonstrated monotonic decreases in leaf water (LWC) and phosphorus (Pmass ) contents and an increase in leaf mass per unit area (LMA) with age across trees; leaf nitrogen (Nmass ) and carbon (Cmass ) contents showed monotonic but tree-specific age responses. We observed large age-related variation in leaf spectra across trees. A spectra-based model was more accurate in predicting leaf age (R2  = 0.86; percent root mean square error (%RMSE) = 33) compared with trait-based models using single (R2  = 0.07-0.73; %RMSE = 7-38) and multiple (R2  = 0.76; %RMSE = 28) predictors. Spectra- and trait-based models established a physiochemical basis for the spectral age model. Vegetation indices (VIs) including the normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), normalized difference water index (NDWI) and photosynthetic reflectance index (PRI) were all age-dependent. This study highlights the importance of leaf age as a mediator of leaf traits, provides evidence of age-related leaf reflectance changes that have important impacts on VIs used to monitor canopy dynamics and productivity and proposes a new approach to predicting and monitoring leaf age with important implications for remote sensing.

[1]  Clayton C. Kingdon,et al.  Spectroscopic determination of leaf morphological and biochemical traits for northern temperate and boreal tree species. , 2014, Ecological applications : a publication of the Ecological Society of America.

[2]  Roberta E. Martin,et al.  Quantifying forest canopy traits: Imaging spectroscopy versus field survey , 2015 .

[3]  Roberta E. Martin,et al.  Amazonian functional diversity from forest canopy chemical assembly , 2014, Proceedings of the National Academy of Sciences.

[4]  J. Mustard,et al.  Beyond leaf color: Comparing camera‐based phenological metrics with leaf biochemical, biophysical, and spectral properties throughout the growing season of a temperate deciduous forest , 2014 .

[5]  David J. Harding,et al.  Amazon forests maintain consistent canopy structure and greenness during the dry season , 2014, Nature.

[6]  O. Phillips,et al.  The productivity, metabolism and carbon cycle of two lowland tropical forest plots in south-western Amazonia, Peru , 2014 .

[7]  K. Hufkens,et al.  Seasonal patterns of foliar reflectance in relation to photosynthetic capacity and color index in two co-occurring tree species, Quercus rubra and Betula papyrifera , 2012 .

[8]  Liana Anderson,et al.  Biome-Scale Forest Properties in Amazonia Based on Field and Satellite Observations , 2012, Remote. Sens..

[9]  Roberta E. Martin,et al.  Spectroscopy of canopy chemicals in humid tropical forests , 2011 .

[10]  R. Dickinson,et al.  Seasonal changes in leaf area of Amazon forests from leaf flushing and abscission , 2011 .

[11]  D. Roberts,et al.  On intra-annual EVI variability in the dry season of tropical forest A case study with MODIS and hyperspectral data , 2011 .

[12]  R. B. Jackson,et al.  A Large and Persistent Carbon Sink in the World’s Forests , 2011, Science.

[13]  Nicolas Barbier,et al.  Relationships between phenology, radiation and precipitation in the Amazon region , 2011 .

[14]  O. Phillips,et al.  The 2010 Amazon Drought , 2011, Science.

[15]  A. Huete,et al.  Fraction images for monitoring intra-annual phenology of different vegetation physiognomies in Amazonia , 2011 .

[16]  A. Escudero,et al.  Morphological and chemical leaf composition of Mediterranean evergreen tree species according to leaf age , 2011, Trees.

[17]  Roberta E. Martin,et al.  Taxonomy and remote sensing of leaf mass per area (LMA) in humid tropical forests. , 2011, Ecological applications : a publication of the Ecological Society of America.

[18]  Scott J Goetz,et al.  Seasonal and interannual variability of climate and vegetation indices across the Amazon , 2010, Proceedings of the National Academy of Sciences.

[19]  Nicolas Barbier,et al.  Remote sensing detection of droughts in Amazonian forest canopies. , 2010, The New phytologist.

[20]  A. Arneth,et al.  Variations in chemical and physical properties of Amazon forest soils in relation to their genesis , 2010 .

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

[22]  R. Kokaly,et al.  Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies , 2009 .

[23]  Dar A. Roberts,et al.  The influence of epiphylls on remote sensing of humid forests , 2009 .

[24]  Luiz E. O. C. Aragão,et al.  Regional and seasonal patterns of litterfall in tropical South America , 2009 .

[25]  Roberta E. Martin,et al.  Airborne spectranomics: mapping canopy chemical and taxonomic diversity in tropical forests , 2009 .

[26]  L. Poorter,et al.  Causes and consequences of variation in leaf mass per area (LMA): a meta-analysis. , 2009, The New phytologist.

[27]  Regional and temporal patterns of litterfall in tropical South America , 2009 .

[28]  Roberta E. Martin,et al.  Leaf chemical and spectral diversity in Australian tropical forests. , 2009, Ecological applications : a publication of the Ecological Society of America.

[29]  Roberta E. Martin,et al.  Spectral and chemical analysis of tropical forests: Scaling from leaf to canopy levels , 2008 .

[30]  Michael L. Goulden,et al.  Seasonal patterns of tropical forest leaf area index and CO2 exchange , 2008 .

[31]  G. Arturo Sanchez-Azofeifa,et al.  Changes in Spectral Properties, Chlorophyll Content and Internal Mesophyll Structure of Senescing Populus balsamifera and Populus tremuloides Leaves , 2008, Sensors.

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

[33]  O. Phillips,et al.  A calibration method for the crown illumination index for assessing forest light environments , 2007 .

[34]  D. Roy,et al.  Large seasonal swings in leaf area of Amazon rainforests , 2007, Proceedings of the National Academy of Sciences.

[35]  Hendrik Poorter,et al.  Differences in construction costs and chemical composition between deciduous and evergreen woody species are small as compared to differences among families. , 2006, Plant, cell & environment.

[36]  Frans Bongers,et al.  Leaf traits are good predictors of plant performance across 53 rain forest species. , 2006, Ecology.

[37]  A. Huete,et al.  Amazon rainforests green‐up with sunlight in dry season , 2006 .

[38]  A. Cescatti,et al.  Leaf internal diffusion conductance limits photosynthesis more strongly in older leaves of Mediterranean evergreen broad‐leaved species , 2005 .

[39]  A. Sõber,et al.  Leaf hydraulic conductance in relation to anatomical and functional traits during Populus tremula leaf ontogeny. , 2005, Tree physiology.

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

[41]  J. Tenhunen,et al.  Spatial and age-dependent modifications of photosynthetic capacity in four Mediterranean oak species. , 2004, Functional plant biology : FPB.

[42]  Sean C. Thomas,et al.  The worldwide leaf economics spectrum , 2004, Nature.

[43]  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.

[44]  Christopher Uhl,et al.  Leaf demography and phenology in Amazonian rain forest : a census of 40,000 leaves of 23 tree species , 2004 .

[45]  P. Reich,et al.  Leaf lifespan as a determinant of leaf structure and function among 23 amazonian tree species , 1991, Oecologia.

[46]  H. Mooney,et al.  Leaf age and seasonal effects on light, water, and nitrogen use efficiency in a California shrub , 1983, Oecologia.

[47]  T. Mulroy,et al.  Spectral properties of heavily glaucous and non-glaucous leaves of a succulent rosette-plant , 2004, Oecologia.

[48]  M. Keller,et al.  Carbon in Amazon Forests: Unexpected Seasonal Fluxes and Disturbance-Induced Losses , 2003, Science.

[49]  A. Escudero,et al.  Decline in photosynthetic nitrogen use efficiency with leaf age and nitrogen resorption as determinants of leaf life span , 2003 .

[50]  Ü. Niinemets,et al.  Leaf structure vs. nutrient relationships vary with soil conditions in temperate shrubs and trees , 2003 .

[51]  D. Sims,et al.  Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features , 2003 .

[52]  Stephen J. Wright,et al.  Decline of photosynthetic capacity with leaf age and position in two tropical pioneer tree species. , 2002, American journal of botany.

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

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

[55]  O. Phillips,et al.  An international network to monitor the structure, composition and dynamics of Amazonian forests (RAINFOR) , 2002 .

[56]  R. Borchert,et al.  Modification of Vegetative Phenology in a Tropical Semi‐deciduous Forest by Abnormal Drought and Rain 1 , 2002 .

[57]  M. Lewis,et al.  Spectral characterization of Australian arid zone plants , 2002 .

[58]  S. Wold,et al.  PLS-regression: a basic tool of chemometrics , 2001 .

[59]  E. Hunt,et al.  Estimating near-infrared leaf reflectance from leaf structural characteristics. , 2001, American journal of botany.

[60]  G. Asner,et al.  Satellite observation of El Niño effects on Amazon Forest phenology and productivity , 2000 .

[61]  Ülo Niinemets,et al.  Variability in Leaf Morphology and Chemical Composition as a Function of Canopy Light Environment in Coexisting Deciduous Trees , 1999, International Journal of Plant Sciences.

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

[63]  J. Randerson,et al.  Primary production of the biosphere: integrating terrestrial and oceanic components , 1998, Science.

[64]  G. Carter,et al.  Variability in leaf optical properties among 26 species from a broad range of habitats. , 1998, American journal of botany.

[65]  D. Roberts,et al.  Spectral changes with leaf aging in Amazon caatinga , 1998, Trees.

[66]  K. Kitajima,et al.  Decline of photosynthetic capacity with leaf age in relation to leaf longevities for five tropical canopy tree species. , 1997, American journal of botany.

[67]  F. Baret,et al.  Leaf optical properties with explicit description of its biochemical composition: Direct and inverse problems , 1996 .

[68]  B. Biswal,et al.  Carotenoid catabolism during leaf senescence and its control by light , 1995 .

[69]  B. Gao,et al.  Retrieval of equivalent water thickness and information related to biochemical components of vegetation canopies from AVIRIS data , 1995 .

[70]  J. Terborgh,et al.  The Phenology of Tropical Forests: Adaptive Significance and Consequences for Primary Consumers* , 1993 .

[71]  David B. Clark,et al.  LIFE HISTORY DIVERSITY OF CANOPY AND EMERGENT TREES IN A NEOTROPICAL RAIN FOREST , 1992 .

[72]  C. Levenstein.  An International Network , 1991, New solutions : a journal of environmental and occupational health policy : NS.

[73]  Jiyou Wu,et al.  Seasonal patterns in leaf reflectance red-edge characteristics , 1991 .

[74]  C. Elvidge.  Visible and near infrared reflectance characteristics of dry plant materials , 1990 .

[75]  F. Boochs,et al.  Shape of the red edge as vitality indicator for plants , 1990 .

[76]  P. Curran.  Remote sensing of foliar chemistry , 1989 .

[77]  Gregory A. Carter,et al.  Effect of competition and leaf age on visible and infrared reflectance in pine foliage , 1989 .

[78]  B. Kowalski,et al.  Partial least-squares regression: a tutorial , 1986 .

[79]  D. Horler,et al.  The red edge of plant leaf reflectance , 1983 .

[80]  M. Lowman,et al.  Variation in leaf toughness and phenolic content among five species of Australian rain forest trees , 1983 .

[81]  D A Reicosky,et al.  Physiological Effects of Surface Waxes: I. Light Reflectance for Glaucous and Nonglaucous Picea pungens. , 1978, Plant physiology.

[82]  J. Woolley.  Reflectance and transmittance of light by leaves. , 1971, Plant physiology.

[83]  E. B. Knipling.  Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation , 1970 .

[84]  H. Gausman,et al.  Relation of light reflectance to histological and physical evaluations of cotton leaf maturity. , 1970, Applied optics.

[85]  W. D. Billings,et al.  REFLECTION OF VISIBLE AND INFRARED RADIATION FROM LEAVES OF DIFFERENT ECOLOGICAL GROUPS , 1951 .

[86]  Bronx Park.  REFLECTION OF VISIBLE AND INFRARED RADIATION FROM LEAVES OF DIFFERENT ECOLOGICAL GROUPS , 1951 .