Quantitative Modeling
Quantitative Modeling
A requirement for managing a species, be it a common native species, a species of conservation concern, or an invasive species, is having some information on its distribution and potential drivers of distribution. Branch scientists have been tackling the question of where these types of species are and where they might be in the future. Focus species are as varied as the invasive tamarisk, Russian olive, Africanized honey bee and nutria to the federally threatened Lesser Prairie chicken and others. These and other species are modeled at a variety of spatial scales, from park or wildlife refuge to global levels. Models use various predictor layers that can include current and future climate layers (near- and long-term projections), remote-sensing derivatives (such as MODIS phenology metrics), land cover, topography, and anthropogenic features.
Filter Total Items: 43
Using Long-Term Remote Sensing and an Automated Reference Toolset To Estimate and Predict Post-Development Recovery Potential
USGS scientists are using a time-varying approach to monitor and predict recovery of sagebrush ecosystems following disturbance.
Evaluating Trends in Greater Sage-Grouse Populations With Quantile Regression
USGS scientists are evaluating the use of quantile regression to develop models of sage-grouse population changes across the United States.
Developing Broad Scale Indicators for Monitoring Ecosystems and Landscapes
Many issues currently facing the Bureau of Land Management (BLM) and other large land managers span large landscapes, including sage-grouse conservation, wildfires, and energy development. Such challenges involve changes at both local and broad scales, but monitoring has typically focused at the scale of individual sites. The USGS is working to develop broad-scale indicators for monitoring...
Species Distribution Modeling
A requirement for managing a species, be it a common native species, a species of conservation concern, or an invasive species, is having some information on its distribution and potential drivers of distribution. Branch scientists have been tackling the question of where these types of species are and where they might be in the future.
Documenting, Mapping, and Predicting Invasive Species Using the Fort Collins Science Center's RAM (Resource for Advanced Modeling)
The Resource for Advanced Modeling room provides a collaborative working environment for up to 20 scientists, supported with networked, wireless computing capability for running and testing various scientific models (e.g., Maxent, Boosted Regression Trees, Logistic Regression, MARS, Random Forest) at a variety of spatial scales, from county to global levels. Models use various predictor layers...
Non-invasive Genetic Sampling of Free-roaming Horses to Estimate Population Size, Genetic Diversity, and Consumption of Invasive Species
Molecular tagging is a new application of molecular genetic techniques to traditional mark-recapture methodology designed to address situations where traditional methods fail. In such studies, non-invasively collected samples (such as feces, feathers, or fur) are used as a source of DNA that is then genotyped at multiple loci such that each individual animal can be uniquely identified. Thus, each...
Counting America’s Wild Horses and Burros: Better Estimates for Population Management
The Wild Free-Roaming Horses and Burros Act of 1971, as amended, states that, "It is the policy of Congress that wild free-roaming horses and burros shall be protected from capture, branding, harassment, or death; and to accomplish this they are to be considered in the area where presently found, as an integral part of the natural system of the public lands (PL 92-195, Sec. 1331, Congressional...
Incorporating Genetic Data into Spatially-explicit Population Viability Models for Gunnison Sage-grouse
This goal of this study is to develop a spatially explicit habitat-population modeling framework to assess the viability of Gunnison Sage-grouse and each of the seven populations (Gunnison Basin and six satellite populations).
Landscape Genetics
Landscape genetics is a recently developed discipline that involves the merger of molecular population genetics and landscape ecology. The goal of this new field of study is to provide information about the interaction between landscape features and microevolutionary processes such as gene flow, genetic drift, and selection allowing for the understanding of processes that generate genetic...
Population Models
Population models can incorporate genetic data to assess potential impacts of different management strategies on connectivity, effective population size, and genetic diversity.
Biometrics
Mathematical and statistical methods used to analyze biological data are powerful research tools that play several important roles in conceptualizing and understanding the structure and dynamics of ecological systems. Through the development of specialized and sophisticated quantitative tools and models, the complex nature of data arising from studies of ecological systems can be understood.
Using Quantile Regression to Investigate Ecological Limiting Factors
Unexplained heterogeneity in statistical models of animal responses to their physical environment is reasonable to expect because the measured habitat resources are a constraint on—but not the sole determinant of—abundance, survival, fecundity, or fitness. The ecological understanding and reliability of management predictions based on animal habitat models can be improved by shifting focus from...