Tree-mycorrhizal associations detected remotely from canopy spectral properties.
A central challenge in global ecology is the identification of key functional processes in ecosystems that scale, but do not require, data for individual species across landscapes. Given that nearly all tree species form symbiotic relationships with one of two types of mycorrhizal fungi - arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi - and that AM- and ECM-dominated forests often have distinct nutrient economies, the detection and mapping of mycorrhizae over large areas could provide valuable insights about fundamental ecosystem processes such as nutrient cycling, species interactions, and overall forest productivity. We explored remotely sensed tree canopy spectral properties to detect underlying mycorrhizal association across a gradient of AM- and ECM-dominated forest plots. Statistical mining of reflectance and reflectance derivatives across moderate/high-resolution Landsat data revealed distinctly unique phenological signals that differentiated AM and ECM associations. This approach was trained and validated against measurements of tree species and mycorrhizal association across ~130 000 trees throughout the temperate United States. We were able to predict 77% of the variation in mycorrhizal association distribution within the forest plots (P < 0.001). The implications for this work move us toward mapping mycorrhizal association globally and advancing our understanding of biogeochemical cycling and other ecosystem processes.
Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA, 91109, USA.|Joint Institute for Regional Earth System Science and Engineering, University of California at Los Angeles, 607 Charles E Young Drive East, Young Hall #4242, Los Angeles, CA, 90095-7228, USA.
Joshua B
JB
Fisher
Center for the Study of Institutions, Populations, and Environmental Change (CIPEC), Indiana University, Bloomington, Indiana, 47408, USA.
Sean
S
Sweeney
Department of Biology, West Virginia University, 53 Campus Drive, Morgantown, WV, 26506, USA.
Edward R
ER
Brzostek
Center for the Study of Institutions, Populations, and Environmental Change (CIPEC), Indiana University, Bloomington, Indiana, 47408, USA.|Department of Geography, Indiana University, Student Building 120, Bloomington, IN, 47405, USA.
Tom P
TP
Evans
Yale School of Forestry and Environmental Studies, Kroon Hall, 195 Prospect St., New Haven, CT, 06511, USA.
Daniel J
DJ
Johnson
Department of Biology, Washington University in St. Louis, Saint Louis, MO, 63130, USA.
Jonathan A
JA
Myers
Conservation Ecology Center, Smithsonian Conservation Biology Institute, National Zoological Park, 1500 Remount Road, Front Royal, VA, 22630, USA.|U.S. Geological Survey, National Research Program - Eastern Branch, 12201 Sunrise Valley Drive, Reston, VA, MS430, USA.
Norman A
NA
Bourg
Department of Natural and Applied Sciences and Cofrin Center for Biodiversity, University of Wisconsin-Green Bay, 2420 Nicolet Drive, Green Bay, WI, 54311, USA.
Amy T
AT
Wolf
Department of Natural and Applied Sciences and Cofrin Center for Biodiversity, University of Wisconsin-Green Bay, 2420 Nicolet Drive, Green Bay, WI, 54311, USA.
Robert W
RW
Howe
Department of Biology, Indiana University, 247 Jordan Hall, 1001 E. Third St., Bloomington, IN, 47405, USA.
Richard P
RP
Phillips
D004463:Ecology / Q000379:methods*; D065928:Forests; D038821:Mycorrhizae / Q000502:physiology*; D058998:Remote Sensing Technology; D063809:Satellite Imagery; D014197:Trees / Q000382:microbiology*
canopy; landscape; mycorrhizae; nutrients; remote sensing; species; spectral