Scale dependence of canopy trait distributions along a tropical forest elevation gradient.

Average responses of forest foliar traits to elevation are well understood, but far less is known about trait distributional responses to elevation at multiple ecological scales. This limits our understanding of the ecological scales at which trait variation occurs in response to environmental drivers and change. We analyzed and compared multiple canopy foliar trait distributions using field sampling and airborne imaging spectroscopy along an Andes-to-Amazon elevation gradient. Field-estimated traits were generated from three community-weighting methods, and remotely sensed estimates of traits were made at three scales defined by sampling grain size and ecological extent. Field and remote sensing approaches revealed increases in average leaf mass per unit area (LMA), water, nonstructural carbohydrates (NSCs) and polyphenols with increasing elevation. Foliar nutrients and photosynthetic pigments displayed little to no elevation trend. Sample weighting approaches had little impact on field-estimated trait responses to elevation. Plot representativeness of trait distributions at landscape scales decreased with increasing elevation. Remote sensing indicated elevation-dependent increases in trait variance and distributional skew. Multiscale invariance of LMA, leaf water and NSC mark these traits as candidates for tracking forest responses to changing climate. Trait-based ecological studies can be greatly enhanced with multiscale studies made possible by imaging spectroscopy.

[1]  regory,et al.  Controls Over Foliar N:P Ratios in Tropical Rain Forests , 2019 .

[2]  Duncan Harding,et al.  A framework of understanding , 2018, Oxford Medicine Online.

[3]  Roberta E. Martin,et al.  Convergent elevation trends in canopy chemical traits of tropical forests , 2016, Global change biology.

[4]  M. Schildhauer,et al.  Monitoring plant functional diversity from space , 2016, Nature Plants.

[5]  D. Coomes,et al.  Landscape-scale changes in forest canopy structure across a partially logged tropical peat swamp , 2015 .

[6]  Joseph R. Stinziano,et al.  Non-structural carbohydrates in woody plants compared among laboratories. , 2015, Tree physiology.

[7]  C. Field,et al.  Projections of future meteorological drought and wet periods in the Amazon , 2015, Proceedings of the National Academy of Sciences.

[8]  R. Green,et al.  An introduction to the NASA Hyperspectral InfraRed Imager (HyspIRI) mission and preparatory activities , 2015 .

[9]  Roberta E. Martin,et al.  Landscape biogeochemistry reflected in shifting distributions of chemical traits in the Amazon forest canopy , 2015 .

[10]  Anja Rammig,et al.  Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model , 2015, Global change biology.

[11]  Gregory Asner,et al.  Spectroscopic Remote Sensing of Non-Structural Carbohydrates in Forest Canopies , 2015, Remote. Sens..

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

[13]  Roberta E. Martin,et al.  Amazonian landscapes and the bias in field studies of forest structure and biomass , 2014, Proceedings of the National Academy of Sciences.

[14]  Elise S Gornish,et al.  Foliar functional traits that predict plant biomass response to warming , 2014 .

[15]  R. Vargas,et al.  Nonstructural carbon in woody plants. , 2014, Annual review of plant biology.

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

[17]  Yadvinder Malhi,et al.  Spatial patterns of above-ground structure, biomass and composition in a network of six Andean elevation transects , 2014 .

[18]  Roberta E. Martin,et al.  Herbivory makes major contributions to ecosystem carbon and nutrient cycling in tropical forests. , 2013, Ecology letters.

[19]  B. Enquist,et al.  Revisiting Darwin's hypothesis: Does greater intraspecific variability increase species' ecological breadth? , 2014, American journal of botany.

[20]  Roberta E. Martin,et al.  Landscape-scale changes in forest structure and functional traits along an Andes-to-Amazon elevation gradient , 2013 .

[21]  Gregory P. Asner,et al.  Observing Changing Ecological Diversity in the Anthropocene , 2013 .

[22]  P. Meir,et al.  Soil properties in tropical montane cloud forests influence estimates of soil CO2 efflux , 2012 .

[23]  Joshua B. Fisher,et al.  Nutrient limitation in rainforests and cloud forests along a 3,000-m elevation gradient in the Peruvian Andes , 2012, Oecologia.

[24]  Gregory Asner,et al.  Mapping Savanna Tree Species at Ecosystem Scales Using Support Vector Machine Classification and BRDF Correction on Airborne Hyperspectral and LiDAR Data , 2012, Remote. Sens..

[25]  Roberta E. Martin,et al.  Carnegie Airborne Observatory-2: Increasing science data dimensionality via high-fidelity multi-sensor fusion , 2012 .

[26]  Stephen Porder,et al.  Relationships among net primary productivity, nutrients and climate in tropical rain forest: a pan-tropical analysis. , 2011, Ecology letters.

[27]  R. Leigh,et al.  Calcium delivery and storage in plant leaves: exploring the link with water flow. , 2011, Journal of experimental botany.

[28]  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.

[29]  Roberta E. Martin,et al.  Brightness-normalized Partial Least Squares Regression for hyperspectral data , 2010 .

[30]  S. Abad.  Introduction: Elevation gradients in the tropics: laboratories for ecosystem ecology and global change research , 2010 .

[31]  H. Kaufmann,et al.  Hyperspectral imaging—An advanced instrument concept for the EnMAP mission (Environmental Mapping and Analysis Programme) , 2009 .

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

[33]  Michael E. Schaepman,et al.  Retrieval of foliar information about plant pigment systems from high resolution spectroscopy , 2009 .

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

[35]  Yadvinder Malhi,et al.  Regional and large-scale patterns in Amazon forest structure and function are mediated by variations in soil physical and chemical properties , 2009 .

[36]  J. Terborgh,et al.  Drought Sensitivity of the Amazon Rainforest , 2009, Science.

[37]  David D. Ackerly,et al.  Community assembly and shifts in plant trait distributions across an environmental gradient in coastal California , 2009 .

[38]  Gregory P Asner,et al.  The biogeochemical heterogeneity of tropical forests. , 2008, Trends in ecology & evolution.

[39]  A. Agrawal.  Macroevolution of plant defense strategies. , 2007, Trends in ecology & evolution.

[40]  Anne-Laure Boulesteix,et al.  Partial least squares: a versatile tool for the analysis of high-dimensional genomic data , 2006, Briefings Bioinform..

[41]  Roberta E. Martin,et al.  Carnegie Airborne Observatory: in-flight fusion of hyperspectral imaging and waveform light detection and ranging for three-dimensional studies of ecosystems , 2007 .

[42]  Mark Westoby,et al.  Land-plant ecology on the basis of functional traits. , 2006, Trends in ecology & evolution.

[43]  D. Roberts,et al.  Using Imaging Spectroscopy to Study Ecosystem Processes and Properties , 2004 .

[44]  D. Roberts,et al.  Spectral and Structural Measures of Northwest Forest Vegetation at Leaf to Landscape Scales , 2004, Ecosystems.

[45]  Sheng Chen,et al.  Sparse modeling using orthogonal forward regression with PRESS statistic and regularization , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[46]  C. Körner,et al.  Altitudinal variation in stomatal conductance, nitrogen content and leaf anatomy in different plant life forms in New Zealand , 1986, Oecologia.

[47]  C. Körner,et al.  A global survey of carbon isotope discrimination in plants from high altitude , 2004, Oecologia.

[48]  P. Reich,et al.  A handbook of protocols for standardised and easy measurement of plant functional traits worldwide , 2003 .

[49]  Stephen G. Ungar,et al.  Overview of the Earth Observing One (EO-1) mission , 2003, IEEE Trans. Geosci. Remote. Sens..

[50]  Marie-Louise Smith,et al.  Analysis of hyperspectral data for estimation of temperate forest canopy nitrogen concentration: comparison between an airborne (AVIRIS) and a spaceborne (Hyperion) sensor , 2003, IEEE Trans. Geosci. Remote. Sens..

[51]  G. Asner,et al.  Unexpected changes in soil phosphorus dynamics along pasture chronosequences in the humid tropics , 2002 .

[52]  Jane R. Foster,et al.  Comparison of EO-1 Hyperion to AVIRIS for mapping forest composition in the Appalachian Mountains, USA , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[53]  K. Hikosaka,et al.  Photosynthesis–nitrogen relationships in species at different altitudes on Mount Kinabalu, Malaysia , 2002, Ecological Research.

[54]  Harald Martens,et al.  Reliable and relevant modelling of real world data: a personal account of the development of PLS Regression , 2001 .

[55]  P. Reich,et al.  Strategy shifts in leaf physiology, structure and nutrient content between species of high‐ and low‐rainfall and high‐ and low‐nutrient habitats , 2001 .

[56]  P. Matson,et al.  Net primary productivity and nutrient cycling across a mesic to wet precipitation gradient in Hawaiian montane forest , 2001, Oecologia.

[57]  I. Noble,et al.  A framework for understanding the relationship between environment and vegetation based on the surface area to volume ratio of leaves , 2000 .

[58]  Michael F. Thomashow,et al.  PLANT COLD ACCLIMATION: Freezing Tolerance Genes and Regulatory Mechanisms. , 1999, Annual review of plant physiology and plant molecular biology.

[59]  G. Goldstein,et al.  Physiological and morphological variation in Metrosideros polymorpha, a dominant Hawaiian tree species, along an altitudinal gradient: the role of phenotypic plasticity , 1998, Oecologia.

[60]  E. Beck.  Tropical Alpine Environments: Cold tolerance in tropical alpine plants , 1994 .

[61]  Fred A. Kruse,et al.  The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data , 1993 .

[62]  W. Schlesinger.  Biogeochemistry: An Analysis of Global Change , 1991 .

[63]  R. Myneni,et al.  A review on the theory of photon transport in leaf canopies , 1989 .

[64]  David M. Haaland,et al.  Partial least-squares methods for spectral analyses. 2. Application to simulated and glass spectral data , 1988 .

[65]  E. V. Thomas,et al.  Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information , 1988 .

[66]  A. Gentry,et al.  Changes in Plant Community Diversity and Floristic Composition on Environmental and Geographical Gradients , 1988 .

[67]  Maurice Demarty,et al.  Calcium and the cell wall , 1984 .

[68]  Peter M. Vitousek,et al.  Nutrient Cycling and Nutrient Use Efficiency , 1982, The American Naturalist.

[69]  A. Humboldt,et al.  Aspects of Nature, in Different Lands and Different Climates , 1849 .