Geology topics
Publications and source records attributed to Steven Bekedam.
This study provides data on management actions aiming to reduce invasive annual grass abundance in National Park Service units of the northern Great Plains. This report provides an annual status update on the study at Wind Cave National Park.
The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains (NGP) working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.” The original ABAM model has little information about the effects of the herbicide indaziflam (Esplanade or Rejuvra, Bayer Environmental Sciences) on target invasive annual grasses and other components of the vegetation in conditions like those that frequently occur in ABAM parks (i.e., ungrazed). The purpose of this study is to provide some of that information in order to accelerate the rate of learning accomplished in the adaptive management cycle. This annual report to the partner provides that information as collected in 2022 in 3 plots at Little Bighorn Battlefield National Monument.
National Park Service (NPS) units in the northern Great Plains (NGP) were established to preserve and interpret the history of America, protect and showcase unusual geology and paleontology, and provide a home for vanishing large wildlife. A unifying feature among these national parks, monuments, and historic sites is mixed-grass prairie, which not only provides background scenery but is the very foundation of many park missions. As recognition of the prairie’s importance to park fundamental resources and values has grown, so too has the realization that invasive plants threaten these values by reducing native species diversity, altering food webs, and marring the visitor experience. Parks manage invasive species despite uncertainties in treatment effectiveness because management cannot wait for research to provide definitive answers. Under these circumstances, adaptive management (AM) is an appropriate approach. In the NGP, we formed a collaborative adaptive vegetation management team to apply AM towards reducing invasive species (with a focus on exotic annual grasses) and improving native vegetation conditions. In our AM framework, the team uses a Bayesian model built from NPS Inventory & Monitoring and Fire Effects monitoring data and experimental results to predict the effects of management actions on park management units, according to those units’ vegetation condition and management history. These predictions inform management decisions, which are then applied.