Quantifying Early-Seral Forest Composition with Remote Sensing
Author(s) -
RaymaA. Cooley,
PeterT. Wolter,
BrianR. Sturtevant
Publication year - 2016
Publication title -
photogrammetric engineering and remote sensing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.483
H-Index - 127
eISSN - 2374-8079
pISSN - 0099-1112
DOI - 10.14358/pers.82.11.853
Subject(s) - seral community , geography , remote sensing , composition (language) , cartography , forestry , physical geography , environmental science , ecology , ecological succession , biology , linguistics , philosophy
Spatially explicit modeling of recovering forest structure within two years following wildfire disturbance has not been attempted, yet such knowledge is critical for determining successional pathways. We used remote sensing and field data, along with digital climate and terrain data, to model and map early-seral aspen structure and vegetation species richness following wildfire. Richness was the strongest model ( rmse = 2.47 species, Adj. R 2 = 0.60), followed by aspen stem diameter, basal area ( ba ), height, density, and percent cover (Adj. R 2 range = 0.22 to 0.53). Effects of pre-fire aspen ba and fire severity on post-fire aspen structure and richness were analyzed. Post-fire recovery attributes were not significantly related to fire severity, while all but percent cover and richness were sensitive to pre-fire aspen ba (Adj. R 2 range = 0.12 to 0.33, p
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