Catherine Jarnevich, Ph.D.
Biography
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. Since that time she has developed a research program through the USGS Resource for Advanced Modeling to assist multiple agencies and groups with species distributions, focusing on invasive species. Catherine’s 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.
Science and Products
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...
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...
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.
Facilitating the USGS Scientific Data Management Foundation by integrating the process into current scientific workflow systems
Increasing attention is being paid to the importance of proper scientific data management and implementing processes that ensure that products being released are properly documented. USGS policies have been established to properly document not only publications, but also the related data and software. This relatively recent expansion of documentation requirements for data and software may...
NEON Workshop: Operationalizing Ecological Forecasts
Ecosystems are changing worldwide and critical decisions that affect ecosystem health and sustainability are being made every day. As ecologists, we have a responsibility to ensure that these decisions are made with access to the best available science. However, to bring this idea into practice, ecology needs to make a substantial leap forward towards becoming a more predictive science....
Integrating ecological forecasting methods to improve applications for natural resource management: An invasive species example
Projecting the effects of climate change on plant and animal species distributions and abundance is critical to successful long‐term conservation and restoration efforts. There have been significant recent advances made in the areas of: (1) climate forecasts; (2) habitat niche modeling; (3) mechanistic modeling; and (4) observation techniques and networks. However, projections of biological...
Cheatgrass mapping in Squirrel Creek Wildfire, WY in 2014
This data bundle contains some of the inputs, all of the processing instructions and all outputs from two VisTrails/SAHM workflow. These models specifically include field data of locations with >40% cover of cheatgrass (presence) and <40% cover of cheatgrass (absence). Predictors included rasters derived from LandSat 8 imagery or from a digital elevation model.
Data associated with Sofaer and Jarnevich 'Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants'
These data were analyzed for the publication 'Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants'
Developing an expert elicited simulation model to evaluate invasive species and fire management alternatives
Invasive species can alter ecosystem properties and cause state shifts in landscapes. Resource managers charged with maintaining landscapes require tools to understand implications of alternative actions (or inactions) on landscape structure and function. Simulation models can serve as a virtual laboratory to explore these alternatives and their...
Jarnevich, Catherine S.; Cullinane Thomas, Catherine; Young, Nicholas E.; Backer, Dana M.; Cline, Sarah A.; Frid, Leonardo; Grissom, Perry Not so normal normals: Species distribution model results are sensitive to choice of climate normals and model type
Species distribution models have many applications in conservation and ecology, and climate data are frequently a key driver of these models. Often, correlative modeling approaches are developed with readily available climate data; however, the impacts of the choice of climate normals is rarely considered. Here, we produced species distribution...
Jarnevich, Catherine S.; Young, Nicholas E. The area under the precision‐recall curve as a performance metric for rare binary events
Species distribution models are used to study biogeographic patterns and guide decision‐making. The variable quality of these models makes it critical to assess whether a model's outputs are suitable for the intended use, but commonly used evaluation approaches are inappropriate for many ecological contexts. In particular, unrealistically high...
Sofaer, Helen R.; Hoeting, Jennifer A.; Jarnevich, Catherine S. 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...
Cullinane Thomas, Catherine; Sofaer, Helen R.; Cline, Sarah A.; Jarnevich, Catherine S. The 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...
Sofaer, Helen R.; Jarnevich, Catherine S.; Pearse, Ian S. Modeling 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...
Jarnevich, Catherine S.; Hayes, Mark; Fitzgerald, Lee A.; Yackel, Amy; Falk, Bryan; Collier, Michelle; Bonewell, Lea; Klug, Page; Naretto, Sergio; Reed, Robert A 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....
West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Shulte, Darin Forecasting 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...
Jarnevich, Catherine S.; Young, Nicholas E.; Talbert, Marian; Talbert, Colin Misleading 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...
Sofaer, Helen R.; Jarnevich, Catherine S.; Flather, Curtis H. Iterative 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...
Dietze, Michael C.; Fox, Andrew; Beck-Johnson, Lindsay; Betancourt, Julio L.; Hooten, Mevin B.; Jarnevich, Catherine S.; Keitt, Timothy H.; Kenney, Melissa A.; Laney, Christine M.; Larsen, Laurel G.; Loescher, Henry W.; Lunch, Claire K.; Pijanowski, Bryan; Randerson, James T.; Read, Emily; Tredennick, Andrew T.; Vargas, Rodrigo; Weathers, Kathleen C.; White, Ethan P. Comparison 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...
Magarey, Roger; Newton, Leslie; Hong, Seung C.; Takeuchi, Yu; Christie, Dave; Jarnevich, Catherine S.; Kohl, Lisa; Damus, Martin; Higgins, Steven I.; Miller, Leah; Castro, Karen; West, Amanda M.; Hastings, John; Cook, Gericke; Kartesz, John; Koop, Anthony Minimizing 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...
Jarnevich, Catherine S.; Talbert, Marian; Morisette, Jeffrey T.; Aldridge, Cameron L.; Brown, Cynthia; Kumar, Sunil; Manier, Daniel J.; Talbert, Colin; Holcombe, Tracy R.