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Does Tree Crown Architecture Differ by Tree Species? A test with NEON data
  • +6
  • Yiting Fan,
  • Ethan R Cade,
  • Conner W Channels,
  • G Burch Fisher,
  • Steven M Guinn,
  • Christopher Hughes,
  • Lydia R Nicolai,
  • Andrew J Elmore,
  • Brenden E Mcneil
Yiting Fan
Department of Geology and Geography, West Virginia University

Corresponding Author:[email protected]

Author Profile
Ethan R Cade
Department of Geology and Geography, West Virginia University, Department of Geology and Geography, West Virginia University
Conner W Channels
Department of Geology and Geography, West Virginia University
G Burch Fisher
University of Maryland Center for Environmental Science
Steven M Guinn
University of Maryland Center for Environmental Science
Christopher Hughes
Department of Geology and Geography, West Virginia University
Lydia R Nicolai
Department of Geology and Geography, West Virginia University
Andrew J Elmore
University of Maryland Center for Environmental Science
Brenden E Mcneil
Department of Geology and Geography, West Virginia University

Abstract

Tree crown architecture, which we define as the 3-D arrangement and orientation of leaves within a tree crown, influences the rates of photosynthesis, evapotranspiration, and spectral reflectance that affect tree and forest responses to climate change. As part of their adaptive and acclimation strategies for responding to environmental variability, trees are likely to differ in their tree crown architectures, but these differences remain poorly described. We use measurements from 11 deciduous forest locations within the National Ecological Observatory Network (NEON) to quantify traits that can define key dimensions of variability in crown architecture. Specifically, we: (1) measure seasonal trends in mean leaf angle (MLA) from tower-based time-lapse photography, (2) quantify traits describing the density and distribution of leaves in tree crowns from NEON Airborne Observation Platform (AOP) LiDAR data, and (3) infer crown functioning from multi-scale data on near-infrared reflectance of vegetation (NIRv), as obtained from phenocams, the NEON AOP imaging spectrometer, and Harmonized Landsat Sentinel-2 (HLS). From these data, we test for trait covariations (e.g., among MLA, the vertical distribution of plant area index, and the seasonal peak of NIRv) that can suggest fundamental tradeoffs governing how each species arranges and orients leaves in their crowns. In describing how these crown architectural traits covary across the diverse tree species and wide environmental gradients within 11 NEON sites, we highlight implications for tree ecophysiology and remote sensing-based studies on the interactions of trees, forests and climate change.
02 Dec 2023Submitted to ESS Open Archive
03 Dec 2023Published in ESS Open Archive