Geology topics

Ann Rodman

Publications and source records attributed to Ann Rodman.

4 recordsLinked to original sources

USGS2025

UAS and high-resolution satellite imagery improve the accuracy of cheatgrass detection across an invaded Yellowstone landscape

Context Cheatgrass ( Bromus tectorum L.) is a problem across the western United States, where it outcompetes and replaces native grass species, alters habitats, and increases the risk of wildfires. Cheatgrass greens up earlier in the growing season compared to native grasses, making it classifiable with multi-temporal and multi-spectral remote sensing. Objectives We mapped cheatgrass at different scales in the Greater Yellowstone Ecosystem using 10-m Sentinel-2 imagery, 3-m PlanetScope, and 10-cm Uncrewed Aerial Systems (UAS) imagery. We compared these maps to field-collected data to address 1) variation in seasonal phenological signals of native and cheatgrass patches, 2) the influence of scale on detectability and map accuracy across our study area. Results Model accuracy to predict cheatgrass presence increased with imagery resolution and ranged from 83% using 10-m Sentinel-2 to 94% with the integration of PlanetScope and UAS imagery. While there was spatial agreement across models, the fusion of UAS data with satellite sources allowed the detection of small cheatgrass with more precision. Our novel use of NExR and dNExR (a redness and differenced redness index) data in the classification of cheatgrass capitalizes on the senescence of cheatgrass during peak summer periods where cloud free imagery is more prevalent. Conclusions Our satellite and UAS-based models of cheatgrass prediction compare the fusion of very high resolution imagery and phenological time differencing to identify infested areas. Tradeoffs between accuracy and expense lead to important questions for management applications.

Montana↗

USGS2016

Analyses of historical and projected climates to support climate adaptation in the northern Rocky Mountains: Chapter 4

Most of the western United States is experiencing the effects of rapid and directional climate change (Garfin et al. 2013). These effects, along with forecasts of profound changes in the future, provide strong motivation for resource managers to learn about and prepare for future changes. Climate adaptation plans are based on an understanding of historic climate variation and their effects on ecosystems and on forecasts of future climate trends. Frameworks for climate adaptation thus universally identify the importance of a summary of historical, current, and projected climates (Glick, Stein, and Edelson 2011; Cross et al. 2013; Stein et al. 2014). Trends in physical climate variables are usually the basis for evaluating the exposure component in vulnerability assessments. Thus, this chapter focuses on step 2 of the Climate-Smart Conservation framework (chap. 2): vulnerability assessment. We present analyses of historical and current observations of temperature, precipitation, and other key climate measurements to provide context and a baseline for interpreting the ecological impacts of projected climate changes.

Rocky Mountains↗

USGS2015

The shifting climate portfolio of the Greater Yellowstone Area

Knowledge of climatic variability at small spatial extents (< 50 km) is needed to assess vulnerabilities of biological reserves to climate change. We used empirical and modeled weather station data to test if climate change has increased the synchrony of surface air temperatures among 50 sites within the Greater Yellowstone Area (GYA) of the interior western United States. This important biological reserve is the largest protected area in the Lower 48 states and provides critical habitat for some of the world’s most iconic wildlife. We focused our analyses on temporal shifts and shape changes in the annual distributions of seasonal minimum and maximum air temperatures among valley-bottom and higher elevation sites from 1948–2012. We documented consistent patterns of warming since 1948 at all 50 sites, with the most pronounced changes occurring during the Winter and Summer when minimum and maximum temperature distributions increased. These shifts indicate more hot temperatures and less cold temperatures would be expected across the GYA. Though the shifting statistical distributions indicate warming, little change in the shape of the temperature distributions across sites since 1948 suggest the GYA has maintained a diverse portfolio of temperatures within a year. Spatial heterogeneity in temperatures is likely maintained by the GYA’s physiographic complexity and its large size, which encompasses multiple climate zones that respond differently to synoptic drivers. Having a diverse portfolio of temperatures may help biological reserves spread the extinction risk posed by climate change.

Montana, Wyoming↗

USGS2014

Pollinators in peril? A multipark approach to evaluating bee communities in habitats vulnerable to effects from climate change

In 2010, collaborators from the National Park Service (Ann Rodman, Yellowstone National Park), USGS (Sam Droege and Ralph Grundel), and Harvard University (Jessica Rykken) were awarded funding from the NPS Climate Change Response Program to launch just such an investigation in almost 50 units of the National Park System (fig. 1). The main objectives of this multiyear project were to: Compare bee communities in three “vulnerable” habitats (high elevation, inland arid, coastal) and paired “common” habitats, representative of the landscape matrix, in order to determine whether vulnerable habitats have a distinctive bee fauna that may be at higher risk under climate change scenarios. Inform natural resource managers at each park about the bee fauna at their paired sites, including the presence of rare and endemic species, and make suggestions for active management strategies to promote native bee habitat if warranted. Increase awareness among park natural resource staffs, interpreters, and visitors of native bee diversity and natural history, the essential role of bees in maintaining healthy ecosystems, and potential threats from climate change to pollinator-dependent ecosystems.

Park Science↗