Above-ground carbon loss from the 2015 Soda Fire Andrew Poley, Nancy Glenn, Aihua Li Department of Geosciences, Boise State University, Boise, ID, USA; contact: andewpoley@boisestate.edu Introduction DATA and MethodS Next steps In August 2015, the Soda Fire burned approximately 280,000 acres. The Bureau of Land Management (BLM) has implemented an emergency stabilization and burn area rehabilitation plan in order to preserve the sagebrush-steppe ecosystem that was lost from the fire. Remote sensing imagery are used to estimate pre-fire vegetation communities and biomass, burn severity of the fire, and post-fire vegetation recovery. We used Landsat data to estimate burn severity and AVIRIS hyperspectral imagery to estimate the pre-fire vegetation communities. We will use terrestrial laser scanning (TLS) to estimate post-fire vegetation recovery. We are currently refining the pre-fire vegetation classification, estimating vegetation biomass, and establishing a monitoring program for quantifying vegetation regrowth. Vegetation recovery is vital to restoring local habitats, as well as protecting the area from soil erosion causing further habitat degradation (Johansen et al., 2001). The objectives of this study are to measure the loss of vegetation from the Soda Fire using remote sensing techniques, and to use this baseline information to track vegetation recovery. Biomass Estimation Percent cover of the vegetation species present in the burned area of RCEW will be calculated from the AVIRIS classification Combining this data with available airborne and terrestrial lidar data for RCEW, biomass for each vegetation class will be estimated following the methods of: Li et al. 2015, Mirik et al. 2005, and Mirik et al. 2013. Landsat Imagery Pre-fire Landsat 8 imagery collected on July 29th 2015 Post-fire Landsat 7 imagery collected on August 22nd 2015 Pre-fire vegetation cover was estimated with equation 1 𝑀𝑆𝐴𝑉𝐼2= 1 2 2∗𝑁𝐼𝑅+1 − 2∗𝑁𝐼𝑅+1 2 −8 𝑁𝐼𝑅−𝑅𝑒𝑑 Burn severity was estimated based on the differences in pre and post-fire vegetation (MSAVI2Pre-fire – MSAVI2Post-fire ) We are particularly interest in: What vegetation communities re-establish within 1-2 years after the fire in the BLM treated and non-treated areas? How are these communities distributed throughout the burned area, and what is the change in carbon estimates over time? N N Study area Figure 3: Pre-fire vegetation cover (Left). Burn severity of Soda Fire (Right) We are studying vegetation loss from the Soda Fire within the Reynolds Creek Experimental Watershed (RCEW). RCEW is located within the Owyhee Mountain Range, Southwest ID Area: approximately 239 km2 Ecosystem: semiarid sagebrush-steppe Figure 5: Li et al. 2015, biomass estimation workflow for sagebrush Vegetation Monitoring Stratified sampling in 10 meter plots will be used to determine how much carbon has returned a year following the fire. These plots include existing biomass monitoring plots by terrestrial laser scanning. The BLM has implemented the following vegetation treatments in RCEW: Drill seeding (native), aerial seeding (sagebrush and grasses), sagebrush and forb seedlings Field measurements will be taken in spring/early summer 2016 during vegetation peak greenness AVIRIS Imagery Airborne Visible/ Infrared Imaging Spectrometer data were collected over RCEW in September 2014 with a 2.5 m resolution. Imagery was converted to top surface reflectance, atmospherically corrected, georeferenced, and mosaicked. Vegetation classification was performed using ENVI’s Spectral Information Divergence classification (SID) based on training data collected in the field (Chang, 1999). Vegetation classes were chosen based on the highest biomass contributors in the burned area. Grasses and forbs with spectral contributions too small to be recorded by the sensor were neglected. Figure 1: Percent vegetation cover across Reynolds Creek Experimental Watershed, ID (Li et al. 2015). Common Vegetation: Artemisia tridentate (Sagebrush) Figure 6: BLM Vegetation Treatments Purshia tridentate (Bitterbrush) Juniperus occidentalis (Western Juniper) Salix lasiandra (Willow). Impacts of vegetation loss from the Soda Fire: Loss of habitat for hundreds of different species (Blaisdell et al., 1982) Main source for SOC content (Lal, 2004) Disruption of the hydrologic cycle within the watershed (Schlaepfer et al., 2011) REFERENCES SID Classification Blaisdell, J. P., Murray, R. B., and McArthur, E. D. (1982). Managing Intermountain rangelands- sagebrush-grass ranges. Intermount. For. and Range Exp. Sta. Gen. Tech. Rep. INT-134. 41. Chang, C. (1999). Spectral information divergence for hyperspectral image analysis. Geoscience and Remote Sensing Symposium. IGARSS '99 Proceedings. IEEE 1999 International , Vol.1: 509-511 Johansen, M. P., Hakonson, T. E. and Breshears, D. D. (2001), Post-fire runoff and erosion from rainfall simulation: contrasting forests with shrublands and grasslands. Hydrol. Process., Vol. 15: 2953–2965. Lal, R., 2004. Soil carbon sequestration impacts on global climate change and food scarcity. Science 304, 1623-1628. Li, A., Glenn, N. F., Olsoy, P. J., Mitchell, J. J., and Shrestha, R. (2015). Aboveground biomass estimates of sagebrush using terrestrial and airborne LiDAR data in a dryland ecosystem. Agricultural and Forest Meteorology, Vol. 213: 138-147. Mirik, M., Norland, J.E., Crabtree, R.L., Biondini, M.E. (2005). Hyperspectral One-Meter-Resolution Remote Sensing in Yellowstone National Park, Wyoming: II. Biomass, Rangeland Ecology & Management, Vol. 58, Issue 5: 459-465. Mirik, M., Chaudhuri, S., Surber, B., Ale, S., and Ansley, R. (2013). Evaluating Biomass of Juniper Trees (Juniperus pinchotii) from Imagery-Derived Canopy Area Using the Support Vector Machine Classifier. Advances in Remote Sensing, Vol. 2 No. 2: 181-192. Schlaepfer, D. R., Lauenroth, W. K., and Bradford, J. B. (2012). Ecohydrological niche of sagebrush ecosystems. Ecohydrol., Vol. 5: 453–466. Figure 4: Unclassified AVIRIS hyperspectral imagery (Left). SID vegetation classification (Right) Acknowledgments: Funding for this project is provided by NOAA, NA10OAR4680240; NASA Terrestrial Ecology, NNX14AD81G; and NASA EPSCoR, NNX14AN39A. Figure 2: Area of RCEW burned by the Soda Fire