Catherine S. Jarnevich, PhD
Catherine began working for the USGS while obtaining her doctorate in ecology in 2000. She gained skills in integrating disparate datasets of species’ location data and using these to generate spatially explicit models of species occurrence and abundance.
Catherine has developed a research program to assist multiple agencies and groups with species distributions, focusing on invasive species. Her current research involves the application of habitat suitability models to answer different applied research and management questions for various species across a range of taxa and spatial scales. She has also been working with spatially explicit state and transition modeling to inform efficient landscape scale invasive plant management.
Professional Experience
Research ecologist, Fort Collins Science Center, U. S. Geological Survey, Ft. Collins, CO: 2011 - present
Ecologist, Fort Collins Science Center, U. S. Geological Survey, Ft. Collins, CO: 2000 - 2011
Education and Certifications
Ph.D., Colorado State University (Ecology), 2004
B.S., University of New Mexico, NM (Double major: Biology and Anthropology), 1998
Science and Products
Integrating landscape simulation models with economic and decision tools for invasive species control
The relationship between invader abundance and impact
Modeling the distributions of tegu lizards in native and potential invasive ranges
A tale of two wildfires; testing detection and prediction of invasive species distributions using models fit with topographic and spectral indices
Forecasting an invasive species’ distribution with global distribution data, local data, and physiological information
Misleading prioritizations from modelling range shifts under climate change
Iterative near-term ecological forecasting: Needs, opportunities, and challenges
Response: The geographic distribution of Ixodes scapularis (Acari: Ixodidae) revisited: The importance of assumptions about error balance
Minimizing effects of methodological decisions on interpretation and prediction in species distribution studies: An example with background selection
Comparison of four modeling tools for the prediction of potential distribution for non-indigenous weeds in the United States
Crossing boundaries in a collaborative modeling workspace
Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software
Science and Products
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Integrating landscape simulation models with economic and decision tools for invasive species control
In managing invasive species, land managers and policy makers need information to help allocate scarce resources as efficiently and effectively as possible. Decisions regarding treatment methods, locations, effort, and timing can be informed by the integration of landscape simulation models with economic tools. State and transition simulation models align with conceptual models of ecosystem changeAuthorsCatherine Cullinane Thomas, Helen Sofaer, Sarah A. Cline, Catherine S. JarnevichThe relationship between invader abundance and impact
The impacts of invasive species generally increase with their abundance, but the form of invader abundance–impact relationships remain poorly described. We highlight the utility of abundance–impact curves for three questions. First, abundance–impact relationships can clarify whether prevention and management should focus on the species likely to become abundant or those likely to cause large impacAuthorsHelen Sofaer, Catherine S. Jarnevich, Ian S. PearseModeling the distributions of tegu lizards in native and potential invasive ranges
Invasive reptilian predators can have substantial impacts on native species and ecosystems. Tegu lizards are widely distributed in South America east of the Andes, and are popular in the international live animal trade. Two species are established in Florida (U.S.A.) - Salvator merianae (Argentine black and white tegu) and Tupinambis teguixin sensu lato (gold tegu) – and a third has been recordedAuthorsCatherine S. Jarnevich, Mark Hayes, Lee A. Fitzgerald, Amy Yackel, Bryan Falk, Michelle Collier, Lea Bonewell, Page Klug, Sergio Naretto, Robert ReedA tale of two wildfires; testing detection and prediction of invasive species distributions using models fit with topographic and spectral indices
ContextDeveloping species distribution models (SDMs) to detect invasive species cover and evaluate habitat suitability are high priorities for land managers.ObjectivesWe tested SDMs fit with different variable combinations to provide guidelines for future invasive species model development based on transferability between landscapes.MethodsGeneralized linear model, boosted regression trees, multivAuthorsAmanda M. West, Paul H. Evangelista, Catherine S. Jarnevich, Darin ShulteForecasting an invasive species’ distribution with global distribution data, local data, and physiological information
Understanding invasive species distributions and potential invasions often requires broad‐scale information on the environmental tolerances of the species. Further, resource managers are often faced with knowing these broad‐scale relationships as well as nuanced environmental factors related to their landscape that influence where an invasive species occurs and potentially could occur. Using invasAuthorsCatherine S. Jarnevich, Nicholas E. Young, Marian Talbert, Colin TalbertMisleading prioritizations from modelling range shifts under climate change
AimConservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution mAuthorsHelen Sofaer, Catherine S. Jarnevich, Curtis H. FlatherIterative near-term ecological forecasting: Needs, opportunities, and challenges
Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-AuthorsMike Dietze, Andrew Fox, Lindsay Beck-Johnson, Julio L. Betancourt, Mevin Hooten, Catherine S. Jarnevich, Timothy H. Keitt, Melissa A. Kenney, Christine M. Laney, Laurel G. Larsen, Henry W. Loescher, Claire K. Lunch, Bryan Pijanowski, James T. Randerson, Emily K. Read, Andrew T. Tredennick, Rodrigo Vargas, Kathleen C. Weathers, Ethan P. WhiteResponse: The geographic distribution of Ixodes scapularis (Acari: Ixodidae) revisited: The importance of assumptions about error balance
No abstract available.AuthorsMicah Hahn, Catherine S. Jarnevich, Andrew J. Monaghan, Rebecca J. EisenMinimizing effects of methodological decisions on interpretation and prediction in species distribution studies: An example with background selection
Evaluating the conditions where a species can persist is an important question in ecology both to understand tolerances of organisms and to predict distributions across landscapes. Presence data combined with background or pseudo-absence locations are commonly used with species distribution modeling to develop these relationships. However, there is not a standard method to generate background or pAuthorsCatherine S. Jarnevich, Marian Talbert, Jeffrey T. Morisette, Cameron L. Aldridge, Cynthia Brown, Sunil Kumar, Daniel J. Manier, Colin Talbert, Tracy R. HolcombeComparison of four modeling tools for the prediction of potential distribution for non-indigenous weeds in the United States
This study compares four models for predicting the potential distribution of non-indigenous weed species in the conterminous U.S. The comparison focused on evaluating modeling tools and protocols as currently used for weed risk assessment or for predicting the potential distribution of invasive weeds. We used six weed species (three highly invasive and three less invasive non-indigenous species) tAuthorsRoger Magarey, Leslie Newton, Seung C. Hong, Yu Takeuchi, Dave Christie, Catherine S. Jarnevich, Lisa Kohl, Martin Damus, Steven I. Higgins, Leah Miller, Karen Castro, Amanda M. West, John Hastings, Gericke Cook, John Kartesz, Anthony KoopCrossing boundaries in a collaborative modeling workspace
There is substantial literature on the importance of bridging across disciplinary and science–management boundaries. One of the ways commonly suggested to cross boundaries is for participants from both sides of the boundary to jointly produce information (i.e., knowledge co-production). But simply providing tools or bringing people together in the same room is not sufficient. Here we present a casAuthorsJeffrey T. Morisette, Amanda E. Cravens, Brian W. Miller, Marian Talbert, Colin Talbert, Catherine S. Jarnevich, Michelle Fink, Karin Decker, Eric OdellUsing multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software
Among the most pressing concerns of land managers in post-wildfire landscapes are the establishment and spread of invasive species. Land managers need accurate maps of invasive species cover for targeted management post-disturbance that are easily transferable across space and time. In this study, we sought to develop an iterative, replicable methodology based on limited invasive species occurrencAuthorsAmanda M. West, Paul H. Evangelista, Catherine S. Jarnevich, Sunil Kumar, Aaron Swallow, Matthew Luizza, Steve Chignell - Software
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