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.
Resource for Advanced Modeling (RAM) - Principal Investigator - Catherine Jarnevich
Branch scientists have developed the Resource for Advanced Modeling (RAM), a modeling facility for collaborative research both within the U.S. Geological Survey (USGS) and with the wider research community. The facility provides a collaborative working environment for up to 20 scientists from within the USGS and the wider research community. There are networked, wireless computing facilities with the ability to run and test various models (e.g., Maxent, Boosted Regression Trees, Logistic Regression, MARS, Random Forest) for a variety of spatial scales (county, state, region, nation, or global). These techniques use predictor layers from MODIS time-series data as well as current and future climate layers (near- and long-term projections). The main purpose of the RAM is to bring together remote sensing and climate forecasting experts, habitat modelers, field ecologists, and land managers in a synergistic environment.
Developing Ecological Forecasting Models for Invasive Species - Principal Investigator - Catherine Jarnevich
Forecasts of where species might be and what impacts they may have are necessary for management of invasive species. Researchers at FORT are using various approaches to provided needed information to resource managers to combat invasive plants, animals, and disease organisms.
Below are other science projects associated with this project.
Resource for Advanced Modeling (RAM)
Developing Ecological Forecasting Models for Invasive Species
- Overview
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.
Resource for Advanced Modeling (RAM) - Principal Investigator - Catherine Jarnevich
Branch scientists have developed the Resource for Advanced Modeling (RAM), a modeling facility for collaborative research both within the U.S. Geological Survey (USGS) and with the wider research community. The facility provides a collaborative working environment for up to 20 scientists from within the USGS and the wider research community. There are networked, wireless computing facilities with the ability to run and test various models (e.g., Maxent, Boosted Regression Trees, Logistic Regression, MARS, Random Forest) for a variety of spatial scales (county, state, region, nation, or global). These techniques use predictor layers from MODIS time-series data as well as current and future climate layers (near- and long-term projections). The main purpose of the RAM is to bring together remote sensing and climate forecasting experts, habitat modelers, field ecologists, and land managers in a synergistic environment.
Sources/Usage: Public Domain.Cheatgrass turning red in the fall in the Squirrel Creek burn area, Medicine Bow National Forest. Photo by Amanda West, USGS. Public domain. Developing Ecological Forecasting Models for Invasive Species - Principal Investigator - Catherine Jarnevich
Forecasts of where species might be and what impacts they may have are necessary for management of invasive species. Researchers at FORT are using various approaches to provided needed information to resource managers to combat invasive plants, animals, and disease organisms.
- Science
Below are other science projects associated with this project.
Resource for Advanced Modeling (RAM)
Branch scientists have developed the Resource for Advanced Modeling (RAM), a modeling facility for collaborative research both within the U.S. Geological Survey (USGS) and with the wider research community. The facility provides a collaborative working environment for up to 20 scientists from within the USGS and the wider research community. There are networked, wireless computing facilities with...Developing Ecological Forecasting Models for Invasive Species
Forecasts of where species might be and what impacts they may have are necessary for management of invasive species. Researchers at FORT are using various approaches to provided needed information to resource managers to combat invasive plants, animals, and disease organisms. - Publications