Validation of a remote sensing based index of forest disturbance
using streamwater nitrogen data
Keith
N
Eshleman, University of Maryland Center for Environmental Science, eshleman@al.umces.edu
(Presenting)
Philip
A
Townsend, University of Wisconsin, Madison, ptownsend@wisc.edu
Brenden
E
McNeil, West Virginia University, brenden.mcneil@mail.wvu.edu
Vegetation disturbances are known to alter the functioning of forested ecosystems by contributing to export (“leakage”) of dissolved nitrogen (N), typically nitrate-N, from watersheds that can contribute to acidification of acid-sensitive streams, leaching of base cations, and eutrophication of downstream receiving waters. Yet, at a landscape scale, direct evaluation of how disturbance is linked to spatial variability in N leakage is complicated by the fact that disturbances operate at different spatial scales, over different timescales, and at different intensities. In this paper we explore whether data from synoptic streamwater surveys conducted in an Appalachian oak-dominated forested river basin in western Maryland (USA) can be used to test and validate a scalable, synthetic, and integrative forest disturbance index (FDI) derived from Landsat imagery. In particular, we found support for the hypothesis that the interannual variation in spring baseflow total dissolved nitrogen (TDN) and nitrate-N concentrations measured at 35 randomly-selected stream stations varied as a linear function of the change in FDI computed for the corresponding set of subwatersheds. Our results demonstrate that the combined effects of forest disturbances can be detected using synoptic water quality data. It appears that careful timing of the synoptic baseflow sampling under comparable phenological and hydrometeorological conditions increased our ability to identify a forest disturbance signal.
Presentation Type: Poster
Poster Session: Ecosystems Science
NASA TE Funded Awards Represented:
NONE: Related Activity or Previously Funded TE Award