Engineering topics

Kristen Nicole Dennis

Publications and source records attributed to Kristen Nicole Dennis.

2 records

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Mapping Wetland and Riparian Areas to Support Rio Grande Cutthroat Trout Habitat Restoration

The Rio Grande cutthroat trout (Oncorhynchus clarki virginalis; RGCT) population has declined significantly over the last century due to habitat loss, competition, and hybridization with non-native trout species. The species currently occupies roughly 11% of its historic habitat. Conservation efforts led by government and private actors have succeeded in increasing RGCT populations since the early 2000s. State, federal, and private partners began the largest native trout restoration initiative in North America. Since 2002, these efforts have included wetland and riparian area restoration and RGCT reintroduction. Current restoration efforts focus on restoring the Costilla Creek Watershed located in Colorado and New Mexico to provide cool water temperatures, improve water quality, and maintain suitable habitat for the trout species. To guide these restoration efforts, the team conducted a rapid assessment to locate and characterize wetland and riparian areas in the Costilla Creek watershed. The team utilized NASA data from the Landsat 8 Operational Land Imager (OLI), as well as the Sentinel-2 MultiSpectral Instrument (MSI), and the Sentinel-1 Synthetic Aperture Radar (SAR) for May 2016 to October 2019. To produce probability maps of wetland presence, the team used the Software for Assisted Habitat Modeling (SAHM) incorporating predictor variables generated from topographic indices, spectral indices, and radar. The top three models (General Wetland model, Stream and Wetland Connectivity model, and Inclusive Wetland model) showed a strong ability to detect wetlands. They all had AUC values greater than 0.9 and had high overlap with wetland areas during visual assessment over high-resolution imagery. The General Wetland model output was converted into a wetland polygon dataset and polygons were classified by wetland type. The resulting maps and datasets will support partners in determining the extent of possible RGCT habitat and identifying where habitat restoration efforts may be needed.

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Quantifying Post-fire Vegetation Recovery on the Colorado Front Range

Forest composition and structure in the Colorado Front Range has been altered by changing wildfire regimes, particularly in response to increased fire severity. Subsequent reductions in post-fire tree regeneration can result in chronic impacts to ecological function and water quality. This project partnered with the U.S. Forest Service to estimate tree canopy recovery from 15 to 21 years after four Colorado Front Range fires that burned between 1996 and 2002— the Bobcat, Buffalo Creek, Hayman, and High Meadows fires—using Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI). First, we evaluated relationships between recovery metrics derived from spectral vegetation indices (i.e. post-fire vegetation, normalized burn ratio, percent unrecovered vegetation) and field-collected counts of post-fire tree seedling regeneration. Then, we used high-resolution imagery paired with Landsat timeseries spectral and geomorphometric data to map forest canopy cover 15-21 years post-fire. Finally, we assessed ecological drivers of recovery including topography, climate, soils, and fire severity using Random Forest. While we found that basic vegetation index metrics failed to distinguish field-measured tree regeneration, our data showed that both aspect and burn severity were important drivers of vegetation recovery. North-facing aspects tended to have higher pre-fire Normalized Difference Vegetation Index (NDVI) and thus higher burn severities. However, areas that burned at high severity experienced slower vegetation recovery, regardless of aspect suggesting that high severity fire can mute favorable site conditions on north-facing aspects (i.e. moister, more developed soils). While this work propels our understanding of variables that influence vegetative recovery, vegetation type, forest conversion, and watershed function, more work should focus on what vegetation indices identifying areas of recovery indicate across different forest types and burn severities.

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