Geology topics

Eric Waller

Publications and source records attributed to Eric Waller.

3 recordsLinked to original sources

USGS2025

Stakeholders' priorities for management of a restored elk (Cervus canadensis) population in northeast Minnesota

Wildlife reintroduction projects are an important tool for restoring traditional wildlife heritage, increasing species diversity, providing subsistence and sport hunting and other recreational opportunities, and assisting ecosystem adaption to future climate change. In Minnesota, the Fond du Lac Band of Lake Superior Chippewa and some conservationists advocate for the expansion of existing elk range to other parts of the state. For reintroduction projects to be successful, it is helpful if managers understand stakeholders' preferences for management objectives. We used best-worst scaling (BWS) to assess residents' preferences for management objective alternatives. The University of Minnesota, in collaboration with the Fond du Lac Band of Lake Superior Chippewa and the Rocky Mountain Elk Foundation, conducted a mail-back questionnaire of landowners ( n = 4500) and the general public ( n = 4000) in northeastern Minnesota to determine their attitudes toward elk reintroduction. Results suggest that the most preferred objectives were minimizing negative impacts on existing wildlife populations and reintroducing native species. In contrast, the least important objectives were related to providing elk viewing opportunities or maximizing economic opportunities through elk-related tourism. These findings help inform management objectives related to the reintroduction proposal, provide insight to minimize potential conflict and help develop future communication material related to elk reintroduction.

Minnesota↗

USGS2022

DSWEmod - The production of high-frequency surface water map composites from daily MODIS images

Optical satellite imagery is commonly used for monitoring surface water dynamics, but clouds and cloud shadows present challenges in assembling complete water time series. To test whether the daily revisit rate of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery can reduce cloud obstruction and improve high-frequency surface water mapping, we compared map results derived from Landsat (30-m) and MODIS (250-m) data across the state of California for 2003–2019. We adapted the Dynamic Surface Water Extent (DSWE) model in Google Earth Engine to generate surface water map composites from MODIS imagery every 5, 10, 15, and 30 days, and compared products to monthly Landsat-based DSWE maps. Results for DSWEmod (DSWE MODIS) in California suggest that more than 5% data loss (cloud obstruction, etc.) was present in only 2% of the 15-day time series, as compared to 32% of the monthly Landsat DSWE time series. The five-day DSWEmod composites averaged 8.4% obscuration in the winter months. Area estimates derived from cloud-filtered MODIS and Landsat monthly products have the highest linear correlations compared to streamgage discharge records, suggesting that monthly scale analyses best explain the relationship between surface water area and general streamflow dynamics. Shorter-interval DSWEmod products have lower correlations but utility for understanding the timing of surface water peaks and past flood events.

Journal of the American Water Resources Associatio↗

USGS2019

Landsat time series assessment of invasive annual grasses following energy development

Invasive annual grasses are of concern in many areas of the Western United States because they tolerate resource variability and have high reproductive capacity, with propagules that are readily dispersed in disturbed areas like those created and maintained for energy development. Early-season invasive grasses “green up” earlier than the most native plants, producing a distinct pulse of greenness in the early spring that can be exploited to identify their location using multi-date imagery. To determine if invasive annual grasses increased around energy development areas after the construction phase, we calculated an invasive index using Landsat TM and ETM+ imagery for a 34-year time period (1985–2018) and assessed trends for 1755 wind turbines installed between 1988 and 2013 in the Southern California Desert. The index uses the maximum normalized difference vegetation index (NDVI) for early-season greenness (January–June) and mean NDVI (July–October) for the later dry season. We estimated the relative cover of invasive annuals each year at turbine locations and control sites, and tested for changes before and after each turbine was installed. The time series was also mapped across the region and temporal trends were assessed relative to seasonal precipitation. The results showed an increase in early-season invasives at turbine sites after installation, but also an increase in many of the surrounding control areas. Maps of the invasive index show a region-wide increase starting at around 1998, and a great deal of the increase occurred in areas surrounding wind development sites. These results suggest that invasions around the energy developments occurred within the context of a larger regional invasion, and while the development did not necessarily initiate the invasion, annual grasses were more prevalent around the development areas.

California↗