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Title: Coupling fine-scale root and canopy structure using ground-based remote sensing

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatial scales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Lastly, our study highlights the potential,more » and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.« less
ORCiD logo [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [4]
  1. Purdue Univ., West Lafayette, IN (United States); The Ohio State Univ., Columbus, OH (United States)
  2. Virginia Commonwealth Univ., Richmond, VA (United States)
  3. USDA Forest Service, Burlington, VT (United States)
  4. The Ohio State Univ., Columbus, OH (United States)
  5. Smithsonian Tropical Research Institute, Miami, FL (United States)
Publication Date:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Remote Sensing
Additional Journal Information:
Journal Volume: 9; Journal Issue: 2; Journal ID: ISSN 2072-4292
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
09 BIOMASS FUELS; canopy; root; biomass; spatial wavelet coherence; radar; LiDAR
OSTI Identifier: