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Northern Rocky Mountain Science Center
Northern Rocky Mountain Science Center scientists work throughout the U.S. and the world on a diverse set of issues to support the safeguarding, understanding, and management of our public lands.
Featured Research
Featured Research
READI-Net—A network of robotic environmental DNA samplers to enhance the early detection of aquatic biological threats
Featured Research
Featured Research
NOROCK is developing drought early warning systems for fisheries and water management
NOROCK Quick Links
NOROCK Quick Links
Check out our most up-to-date data & science, and learn about any upcoming NOROCK opportunities .
News
USGS and BLM publish a science synthesis on risks of spreading invasive annual grasses in MT, ND & SD through vegetation treatments
USGS and BLM publish a science synthesis on risks of spreading invasive annual grasses in MT, ND & SD through vegetation treatments
Kathryn M. Irvine, Northern Rocky Mountain Science Center Research Statistician, Receives Distinguished Achievement Award
Kathryn M. Irvine, Northern Rocky Mountain Science Center Research Statistician, Receives Distinguished Achievement Award
Fiscal Year 2025 Highlights from EESC’s Disease Decision Analysis and Research Group
Fiscal Year 2025 Highlights from EESC’s Disease Decision Analysis and Research Group
Publications
A summary of grizzly bear distribution in the lower-48 US states in 2024 A summary of grizzly bear distribution in the lower-48 US states in 2024
Understanding the distribution of grizzly bear populations in the lower-48 states, is important for their conservation and management, and for public safety. Previously, our research teams working in grizzly bear ecosystems in the lower-48 states used varying methods to estimate distribution of grizzly bear populations. In the Greater Yellowstone Ecosystem (GYE) and Northern Continental...
Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data Leveraging an observed-data likelihood improves the use of machine learning labels in a Bayesian hierarchical model for bioacoustic data
Classification of massive datasets by machine learning (ML) algorithms is promising for many scientific domains, especially wildlife monitoring programs that rely on passive acoustic surveys for detecting species. However, treating ML-predicted class labels (e.g., species identity) as truth biases inferences of focal parameters within common modeling frameworks. One solution is to model...
Groundwater structures fish growth and production across a riverscape Groundwater structures fish growth and production across a riverscape
Landscapes are composed of habitat patches and conditions that vary across space and time. While habitat variability and complexity can support important ecological processes and ecosystem services, the dynamic nature of habitats can also constrain organismal growth and production as optimal conditions are fleeting. In riverine ecosystems, groundwater discharge to streams stabilises...
Science
USGS Science Syntheses for Public Lands Management
Scientific information is fundamental to understanding how proposed actions on public lands may impact the environment. Development of new science is occurring at rates that can make it challenging for biologists, resource managers, decision makers, private landowners, and other stakeholders to ensure they are using up-to-date, high-quality science information to inform their decisions. Further...
eDNA and the Efficacy of Management Actions
Environmental DNA (eDNA) is a powerful feedback tool, giving managers fast, clear, and cost-effective evidence to guide decisions and improve conservation outcomes.
By
Ecosystems Mission Area, Biological Threats and Invasive Species Research Program, Environmental Health Program, Species Management Research Program, Alaska Science Center, Columbia Environmental Research Center, Eastern Ecological Science Center, Forest and Rangeland Ecosystem Science Center, Fort Collins Science Center, Great Lakes Science Center, National Wildlife Health Center, Northern Prairie Wildlife Research Center, Northern Rocky Mountain Science Center, Pacific Island Ecosystems Research Center, Southwest Biological Science Center, Upper Midwest Environmental Sciences Center, Western Ecological Research Center (WERC), Western Fisheries Research Center, Wetland and Aquatic Research Center , Pacific Northwest Environmental DNA Laboratory
eDNA for Water-Quality Monitoring and Public Health Protection
By analyzing genetic traces left behind in water, eDNA provides early warning signs of problems—helping managers respond faster, protect public health, and keep freshwater ecosystems resilient.
By
Ecosystems Mission Area, Biological Threats and Invasive Species Research Program, Environmental Health Program, Alaska Science Center, Columbia Environmental Research Center, Eastern Ecological Science Center, Forest and Rangeland Ecosystem Science Center, Fort Collins Science Center, Great Lakes Science Center, National Wildlife Health Center, Northern Prairie Wildlife Research Center, Northern Rocky Mountain Science Center, Pacific Island Ecosystems Research Center, Upper Midwest Environmental Sciences Center, Western Ecological Research Center (WERC), Western Fisheries Research Center, Wetland and Aquatic Research Center , Pacific Northwest Environmental DNA Laboratory