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The Ecosystem Modelling and Decision Support Project seeks to understand how drivers of ecosystem change like wildfire, drought, and land use affected past spatial and temporal patterns of vegetation communities and wildlife. Research methods involve 1) analyzing field-collected information (e.g. long-term plot/transect data, repeat photography) on soils, vegetation, and/or wildlife with multitemporal satellite data, 2) and the development and use of spatial and temporal statistical models, landscape metrics, and ecological indicators to inform management actions.
The borderland region of the United States and northern Mexico is expected to undergo both extended periods of drought and longer wildfire seasons under forecasted global climate change; it is important to understand how these disturbances interact and affect recovery trajectories and potentially shift plant community composition. This research leverages satellite imagery to map and analyze recent fire patterns, to measure post-fire recovery relative to drought, and to assess how ecosystem management may influence factors like burn severity and timing, the spread of exotic plants, and the cover of trees and shrubs. Two studies are highlighted here.
The first study focuses on reconstructing recent fire history in forests of the transboundary Madrean Archipelego of the southwestern United States and northern Mexico (Figure 1). Mountain ranges in the Madrean ecoregion have similar species assemblages and topographic characteristics, but have been managed in strikingly different ways since the mid-1800s. Differences in land use and forest management, particularly active wildfire suppression in the U.S. and lack thereof in Mexico, have led to contrasting fire regimes which may provide information to help guide forest restoration in the U.S. and inform Mexico’s fire management plans.
In the U.S., federal scientists developed the Monitoring Trends in Burn Severity (MTBS) national database of fire location and burn severity, however similar data for many remote areas outside of the U.S. are generally sparse. To help fill this data gap, we developed a semi-automated process to identify historical wildfire occurrence in Mexico using Landsat Thematic Mapper data time series from 1985-2011. We circumvented the need for a priori knowledge of fire occurrence by combining differenced Normalized Burn Ratio (dNBR) images covering sequential and overlapping seasonal blocks, identifying 83 large (> 1,000 acre) wildfires in northern Mexico during the period. This trans-boundary burn severity dataset will be used to assess differences in fire severity, timing and pattern relative to management and climate.
The second study uses satellite time-series to monitor changes in rangeland vegetation cover and greenness caused by prescribed fire and drought. Using a 25-year fire atlas of prescribed fire and wildfire locations, we paired sites with multiple fires with unburned control areas and compared satellite and field-based estimates of vegetation cover over time (Figure 2). To identify post-fire shifts in native, non-native and annual plant cover, we analyze vegetation cover and greenness estimated from Landsat Thematic Mapper satellite data (Figure 3). The data highlighted anomalous greening during drought periods that was related to increased annual and non-native plant cover (Figure 4). Satellite and field-data suggest that aggressive application of prescribed fire effectively reduces woody plant cover as intended, but may also encourage the spread of non-native grasses and annual plant cover, especially during drought periods. These observations can inform management restoration activities, including optimal timing relative to season and climate, to produce desired ecosystem outcomes.
Villarreal, M.L., Cortés Montaño, C. and Prickett, J. 2015. Recent patterns of wildfire severity across a transboundary ecoregion of the United States-Mexico borderlands. 9th IALE World Congress, July 5-10, 2015, Portland, OR.
Prickett, J.K. and Villarreal, M.L. 2014. Integrating Remote Sensing and GIS for retrospective wildfire mapping in remote areas. GeCo in the Rockies, September 22-26, 2014. Grand Junction, CO.
Villarreal, M.L., Wallace, C.S.A., Norman, L.M. and Coe, M. 2014. Effects of climate, soils and species composition on multitemporal satellite estimates of desert grassland cover. Association of American Geographers Annual Meeting, April 8-12, 2014, Tampa, FL.
Villarreal, M.L., Wallace, C.S.A., Buckley, S., Norman, L.M. and Coe, M. 2013. Measuring the interacting effects of drought and fire on grassland cover and phenology with a 30 year time-series of Landsat data. 12th Biennial Conference of Science and Management on the Colorado Plateau. September 16-19, 2013, Northern Arizona University, Flagstaff, AZ.
Below are publications associated with this project.