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Article

Characterizing Boreal Peatland Plant Composition and Species Diversity with Hyperspectral Remote Sensing

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Department of Geography, Environment & Society, University of Minnesota, Minneapolis, MN 55455, USA
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Department of Forest Resources, University of Minnesota, Saint Paul, MN 55108, USA
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Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, USA
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School of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI 49931, USA
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Northern Research Station, USDA Forest Service, Houghton, MI 49931, USA
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Northern Research Station, USDA Forest Service, Grand Rapids, MN 55744, USA
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Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
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Cold Regions Research and Engineering Laboratory, U.S. Army, Fort Wainwright, AK 99703, USA
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Geospatial Research Lab, U.S. Army Corps of Engineers, Alexandria, VA 22315, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(14), 1685; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11141685
Received: 7 June 2019 / Revised: 3 July 2019 / Accepted: 5 July 2019 / Published: 16 July 2019
(This article belongs to the Special Issue Remote Sensing of Peatlands II)
Peatlands, which account for approximately 15% of land surface across the arctic and boreal regions of the globe, are experiencing a range of ecological impacts as a result of climate change. Factors that include altered hydrology resulting from drought and permafrost thaw, rising temperatures, and elevated levels of atmospheric carbon dioxide have been shown to cause plant community compositional changes. Shifts in plant composition affect the productivity, species diversity, and carbon cycling of peatlands. We used hyperspectral remote sensing to characterize the response of boreal peatland plant composition and species diversity to warming, hydrologic change, and elevated CO2. Hyperspectral remote sensing techniques offer the ability to complete landscape-scale analyses of ecological responses to climate disturbance when paired with plot-level measurements that link ecosystem biophysical properties with spectral reflectance signatures. Working within two large ecosystem manipulation experiments, we examined climate controls on composition and diversity in two types of common boreal peatlands: a nutrient rich fen located at the Alaska Peatland Experiment (APEX) in central Alaska, and an ombrotrophic bog located in northern Minnesota at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment. We found a strong effect of plant functional cover on spectral reflectance characteristics. We also found a positive relationship between species diversity and spectral variation at the APEX field site, which is consistent with other recently published findings. Based on the results of our field study, we performed a supervised land cover classification analysis on an aerial hyperspectral dataset to map peatland plant functional types (PFTs) across an area encompassing a range of different plant communities. Our results underscore recent advances in the application of remote sensing measurements to ecological research, particularly in far northern ecosystems. View Full-Text
Keywords: hyperspectral; remote sensing; peatlands; boreal; arctic; species diversity; land cover hyperspectral; remote sensing; peatlands; boreal; arctic; species diversity; land cover
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MDPI and ACS Style

McPartland, M.Y.; Falkowski, M.J.; Reinhardt, J.R.; Kane, E.S.; Kolka, R.; Turetsky, M.R.; Douglas, T.A.; Anderson, J.; Edwards, J.D.; Palik, B.; Montgomery, R.A. Characterizing Boreal Peatland Plant Composition and Species Diversity with Hyperspectral Remote Sensing. Remote Sens. 2019, 11, 1685. https://0-doi-org.brum.beds.ac.uk/10.3390/rs11141685

AMA Style

McPartland MY, Falkowski MJ, Reinhardt JR, Kane ES, Kolka R, Turetsky MR, Douglas TA, Anderson J, Edwards JD, Palik B, Montgomery RA. Characterizing Boreal Peatland Plant Composition and Species Diversity with Hyperspectral Remote Sensing. Remote Sensing. 2019; 11(14):1685. https://0-doi-org.brum.beds.ac.uk/10.3390/rs11141685

Chicago/Turabian Style

McPartland, Mara Y., Michael J. Falkowski, Jason R. Reinhardt, Evan S. Kane, Randy Kolka, Merritt R. Turetsky, Thomas A. Douglas, John Anderson, Jarrod D. Edwards, Brian Palik, and Rebecca A. Montgomery. 2019. "Characterizing Boreal Peatland Plant Composition and Species Diversity with Hyperspectral Remote Sensing" Remote Sensing 11, no. 14: 1685. https://0-doi-org.brum.beds.ac.uk/10.3390/rs11141685

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