## 5 Conclusions  
The results from our study demonstrate that warming and hydrologic change lead to detectable changes in species composition and ecosystem productivity in boreal peatlands. We have further demonstrated the utility and efficacy of applying remotely sensed data toward characterizing and tracking changes in plant functional cover over time. Remote sensing is emerging as an effective tool to support ecological research, given its growing ability to characterize key elements of ecosystem structure and function such as leaf area, foliar chemistry, species diversity, and, more recently, the cover of different species and PFTs. We have shown that remote sensing can be used to detect the effects of a range of global change drivers on the productivity and functional composition of two types of peatland ecosystems representative of extensive areas of the northern boreal environment. We have also shown the feasibility of using hyperspectral remote sensing to map the distribution of PFTs over large spatial extents. In light of rapid global change, this approach could provide valuable insight into the changing ecology of the far north. **Supplementary Materials:** The following are available online at [[http://www.mdpi.com/2072-4292/11/14/1685/s1](http://www.mdpi.com/2072-4292/11/14/1685/s1)]([http://www.mdpi.com/2072-4292/11/14/1685/s1](http://www.mdpi.com/2072-4292/11/14/1685/s1)), Figure S1: Mean treatment reflectance spectra for the APEX site. Five plots are averaged in the control, and four are averaged in the lowered and raised plots. Each plot-level average is comprised of three scans taken in succession, Figure S2: Mean treatment reflectance spectra for the SPRUCE site. Each spectra represents six plots across two chambers. Each plot-level average is comprised of three scans taken in succession, Figure S3: Distribution of data included in the linear modeling of the relationship between hyperspectral and plot-level characteristics. We also performed Anderson-Darling tests to support our use of these data in our models. We were able to reject the null hypothesis that the data were uniformly distributed in all cases, Figure S4: Spectral response curves for the cover types represented in the aerial hyperspectral dataset to demonstrate differentiation among cover types. **Author Contributions:** Conceptualization, M.Y.M., M.J.F., E.S.K., M.R.T., T.A.D. and R.A.M. ; Data curation, M.Y.M., J.A. and J.D.E. ; Formal analysis, M.Y.M. and J.R.R. ; Funding acquisition, M.J.F., E.S.K., R.K., M.R.T., T.A.D., B.P. and R.A.M. ; Investigation, M.Y.M., M.J.F., E.S.K., J.A., J.D.E. and R.A.M. ; Methodology, M.Y.M., J.R.R and R.A.M. ; Project administration, M.Y.M; Resources, M.J.F., R.K., M.R.T., T.A.D., B.P. and R.A.M. ; Supervision, M.J.F.,E.S.K. and R.A.M. ; Visualization, M.Y.M. ; Writing - original draft, M.Y.M. ; Writing - review & editing, M.J.F., J.R.R., E.S.K., R.K., M.R.T., T.A.D., J.A., J.D.E., B.P. and R.A.M. **Funding:** This research was supported by the National Science Foundation grant #DEB LTREB 1354370 to (to E.S.K. and M.R.T.) and NASA grant #NNX14 AF96G to (M.J.F. and E.S.K. ), as well as cooperative agreements between the USDA Forest Service Northern Research Station and the University of Minnesota and Michigan Tech University. R.A.M. was supported by the Minnesota Agricultural Experiment Station project MIN-42-060. APEX is supported by funding for the Bonanza Creek LTER (funded jointly by National Science Foundation grant DEB-0423442 and USDA Forest Service, Pacific Northwest Research grant PNW01-JV11261952-231). SPRUCE is sponsored by the US Department of Energy Office of Science, by the Office of Biological and Environmental Research, and by the Oak Ridge National Laboratory. Generous funding for M.Y.M. was made possible by the University of Minnesota Department of Forest Resources. T.A.D. acknowledges the Engineer Research and Development Center Army Direct (6.1) Research Program and the Strategic Environmental Research and Development Program (projects RC-2110 and 18-1170).