Peder Engelstad

About Me

I am a Research Associate in the Vogeler Lab and a PhD student in the Graduate Degree Program in Ecology at Colorado State University in Fort Collins, CO. I am the primary developer on the Invasive Species Habitat Tool (INHABIT), a web-based decision support tool hosted by the USGS. I am also the primary developer and maintainer of climatchR, an R package for rapid climate comparisons during large scale risk assessments (e.g., horizon scans).

My current research focuses on the development of new and novel methods for the production, evaluation, and interpretation of species distribution models. Primarily, I work with models of invasive terrestrial plant species to better our understanding of the spatial processes underlying plant invasions and improve the utility of models for practitioners tasked with the management of invasive species.

 

Education

PhD Ecology Colorado State University 2026 (Anticipated)
MS Watershed Science Colorado State University 2018
BA Anthropology University of Wisconsin-Madison 2006

 

Publications

In Review

Daniel, W., Sofaer, H.S., Jarnevich, C.S., Erickson, R.E., DeGregorio, B., Engelstad, P.S., … Lieurance, D. Vertebrates in Trade Pose High Invasion Risk to the United States.

Engelstad, P., Sofaer, H.R., Jarnevich, C.S. #modelevaluation: generating spatial testing and cross-validation splits for ecological models using hashtag geometry.

Evangelista, P., Young, N., Schulte, D., Tricorache, P., Luizza, M., Durant, S., Jones, K., Mitchell, N., Maule, T., Abdullahi, A., Tesfai, R., Engelstad, P. Mapping illegal trade routes of live cheetah (Acinonyx jubatus) from the Horn of Africa to the Arabian Peninsula.

Williams, D.A., Shadwell, K.S., Pearse, I.S., Prevéy, J.S., Engelstad, P., Henderson, G.C., & Jarnevich, C.S. Predictor Importance in Habitat Suitability Models for Invasive Terrestrial Plants.


Peer-Reviewed Journal Articles
  1. Evans, A.E., Jarnevich, C.S., Beaury, E.M., Engelstad, P.S., Teich, N.B., LaRoe, J.M., & Bradley, B.A. (2023). Shifting hotspots: Climate change projected to drive contractions and expansions of invasive plant abundance habitats. Diversity and Distributions, ddi.13787. https://doi.org/10.1111/ddi.13787

  2. Burner, R.C., Daniel, W.M., Engelstad, P.S., Churchill, C.J., & Erickson, R.A. (2023). BioLake: A First Assessment of Lake Temperature-Derived Bioclimatic Predictors for Aquatic Invasive Species. Ecosphere 14(7): e4616. https://doi.org/10.1002/ecs2.4616

  3. Beaury, E.M., Jarnevich, C.S., Pearse, I., Evans, A.E., Teich, N., Engelstad, P., LaRoe, J., & Bradley, B.A. (2023). Modeling habitat suitability across different levels of invasive plant abundance. Biological Invasions 1-13. https://doi.org/10.1007/s10530-023-03118-z

  4. Jarnevich, C., Engelstad, P., LaRoe, J., Hays, B., Hogan, T., Jirak, J., Pearse, I., Prevéy, J., Sieracki, J., Simpson, A., Wenick, J., Young, N., & Sofaer, H. R. (2023). Invaders at the doorstep: Using species distribution modeling to enhance invasive plant watch lists. Ecological Informatics, 101997. https://doi.org/10.1016/j.ecoinf.2023.101997

  5. Engelstad P., Jarnevich C.S., Hogan T., Sofaer H.R., Pearse I.S., et al. (2022). INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States. PLOS ONE 17(2): e0263056. https://doi.org/10.1371/journal.pone.0263056

  6. Erickson, R.A., Engelstad, P.S., Jarnevich, C.S., Sofaer, H.R., & Daniel, W.M. (2022). Climate matching with the climatchR R package. Environmental Modelling & Software, 10551 https://doi.org/10.1016/j.envsoft.2022.105510

  7. Jarnevich, C.S., Sofaer H.R., Engelstad P., & Belamaric, P. (2022). Regional models do not outperform continental models for invasive species. Neobiota. https://doi.org/10.3897/neobiota.77.86364

  8. Jarnevich, C.S., Sofaer, H.R., & Engelstad, P. (2021). Modelling presence versus abundance for invasive species risk assessment. Diversity and Distributions, 27(12), 2454-2464. https://doi.org/10.1111/ddi.13414

  9. Young, N.E., Jarnevich, C.S., Sofaer, H.R., Pearse, I., Sullivan, J., Engelstad, P., & Stohlgren, T.J. (2020). A modeling workflow that balances automation and human intervention to inform invasive plant management decisions at multiple spatial scales. PLOS ONE, 15(3), e0229253. https://doi.org/10.1371/journal.pone.0229253

  10. Engelstad, P.S., Falkowski, M.J., D’Amato, A.W., Slesak, R.A., Palik, B.J., Domke, G.M. & Russell, M.B. (2019). Mapping black ash dominated stands using geospatial and forest inventory data in northern Minnesota, USA. Canadian Journal of Forest Research, 48(8), 892-902. https://doi.org/10.1139/cjfr-2018-0481

  11. Engelstad, P.S., Falkowski, M., Wolter, P., Poznanovic, A., & Johnson, P. (2019). Estimating canopy fuel attributes from low-density LiDAR. Fire, 2(3), 38. https://doi.org/10.3390/fire2030038

  12. Woodward, B., Engelstad, P., Vorster, A., Beddow, C., Krail, S., Vashisht, A., & Evangelista, P. (2017). Forest harvest dataset for northern Colorado Rocky Mountains (1984–2015) generated from a Landsat time series and existing forest harvest records. Data in brief, 15, 724-727. https://doi.org/10.1016/j.dib.2017.10.030



Book Chapters

  1. Engelstad, P., Carver, D., & Young, N. E. (2024). Creating Presence and Absence Points. In J. A. Cardille, M. A. Crowley, D. Saah, & N. E. Clinton (Eds.), Cloud-Based Remote Sensing with Google Earth Engine (pp. 1133–1155). Springer International Publishing. https://doi.org/10.1007/978-3-031-26588-4_52

  2. Engelstad, P., Carver, D., & Young, N. E. (2024). Working with GPS and Weather Data. In J. A. Cardille, M. A. Crowley, D. Saah, & N. E. Clinton (Eds.), Cloud-Based Remote Sensing with Google Earth Engine (pp. 1121–1131). Springer International Publishing. https://doi.org/10.1007/978-3-031-26588-4_51



Software & Datasets

  1. Engelstad P., Jarnevich, C., Sofaer, H., Daniel, W., Peterman, L., Erickson, R.A. (2023). climatchR: An implementation of CLIMATCH in R. v2.0. U.S. Geological Survey software release. Reston, VA. https://doi.org/10.5066/P9ILPPTC

  2. Jarnevich, C.S., LaRoe, J., Engelstad, P., Hays, B., Henderson, G., Williams, D., Shadwell, K., Pearse, I.S., Prevey, J.S., & Sofaer, H.R. (2023). INHABIT species potential distribution across the contiguous United States (ver. 3.0, February 2023): U.S. Geological Survey data release. https://doi.org/10.5066/P9V54H5K

  3. Evans, A., Beaury, E.M., Engelstad, P.S., Teich, N.B., & Bradley, B.A. (2022). Shifting hotspots: Climate change projected to drive contractions and expansions of invasive plant abundance ranges. Data and Datasets. 157. https://doi.org/10.7275/f172-4c95


Peder Engelstad

About Me

I am a Research Associate in the Vogeler Lab and a PhD student in the Graduate Degree Program in Ecology at Colorado State University in Fort Collins, CO. I am the primary developer on the Invasive Species Habitat Tool (INHABIT), a web-based decision support tool hosted by the USGS. I am also the primary developer and maintainer of climatchR, an R package for rapid climate comparisons during large scale risk assessments (e.g., horizon scans).

My current research focuses on the development of new and novel methods for the production, evaluation, and interpretation of species distribution models. Primarily, I work with models of invasive terrestrial plant species to better our understanding of the spatial processes underlying plant invasions and improve the utility of models for practitioners tasked with the management of invasive species.

 

Education

PhD Ecology Colorado State University 2026 (Anticipated)
MS Watershed Science Colorado State University 2018
BA Anthropology University of Wisconsin-Madison 2006

 

Publications

In Review

Daniel, W., Sofaer, H.S., Jarnevich, C.S., Erickson, R.E., DeGregorio, B., Engelstad, P.S., … Lieurance, D. Vertebrates in Trade Pose High Invasion Risk to the United States.

Engelstad, P., Sofaer, H.R., Jarnevich, C.S. #modelevaluation: generating spatial testing and cross-validation splits for ecological models using hashtag geometry.

Evangelista, P., Young, N., Schulte, D., Tricorache, P., Luizza, M., Durant, S., Jones, K., Mitchell, N., Maule, T., Abdullahi, A., Tesfai, R., Engelstad, P. Mapping illegal trade routes of live cheetah (Acinonyx jubatus) from the Horn of Africa to the Arabian Peninsula.

Williams, D.A., Shadwell, K.S., Pearse, I.S., Prevéy, J.S., Engelstad, P., Henderson, G.C., & Jarnevich, C.S. Predictor Importance in Habitat Suitability Models for Invasive Terrestrial Plants.


Peer-Reviewed Journal Articles
  1. Evans, A.E., Jarnevich, C.S., Beaury, E.M., Engelstad, P.S., Teich, N.B., LaRoe, J.M., & Bradley, B.A. (2023). Shifting hotspots: Climate change projected to drive contractions and expansions of invasive plant abundance habitats. Diversity and Distributions, ddi.13787. https://doi.org/10.1111/ddi.13787

  2. Burner, R.C., Daniel, W.M., Engelstad, P.S., Churchill, C.J., & Erickson, R.A. (2023). BioLake: A First Assessment of Lake Temperature-Derived Bioclimatic Predictors for Aquatic Invasive Species. Ecosphere 14(7): e4616. https://doi.org/10.1002/ecs2.4616

  3. Beaury, E.M., Jarnevich, C.S., Pearse, I., Evans, A.E., Teich, N., Engelstad, P., LaRoe, J., & Bradley, B.A. (2023). Modeling habitat suitability across different levels of invasive plant abundance. Biological Invasions 1-13. https://doi.org/10.1007/s10530-023-03118-z

  4. Jarnevich, C., Engelstad, P., LaRoe, J., Hays, B., Hogan, T., Jirak, J., Pearse, I., Prevéy, J., Sieracki, J., Simpson, A., Wenick, J., Young, N., & Sofaer, H. R. (2023). Invaders at the doorstep: Using species distribution modeling to enhance invasive plant watch lists. Ecological Informatics, 101997. https://doi.org/10.1016/j.ecoinf.2023.101997

  5. Engelstad P., Jarnevich C.S., Hogan T., Sofaer H.R., Pearse I.S., et al. (2022). INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States. PLOS ONE 17(2): e0263056. https://doi.org/10.1371/journal.pone.0263056

  6. Erickson, R.A., Engelstad, P.S., Jarnevich, C.S., Sofaer, H.R., & Daniel, W.M. (2022). Climate matching with the climatchR R package. Environmental Modelling & Software, 10551 https://doi.org/10.1016/j.envsoft.2022.105510

  7. Jarnevich, C.S., Sofaer H.R., Engelstad P., & Belamaric, P. (2022). Regional models do not outperform continental models for invasive species. Neobiota. https://doi.org/10.3897/neobiota.77.86364

  8. Jarnevich, C.S., Sofaer, H.R., & Engelstad, P. (2021). Modelling presence versus abundance for invasive species risk assessment. Diversity and Distributions, 27(12), 2454-2464. https://doi.org/10.1111/ddi.13414

  9. Young, N.E., Jarnevich, C.S., Sofaer, H.R., Pearse, I., Sullivan, J., Engelstad, P., & Stohlgren, T.J. (2020). A modeling workflow that balances automation and human intervention to inform invasive plant management decisions at multiple spatial scales. PLOS ONE, 15(3), e0229253. https://doi.org/10.1371/journal.pone.0229253

  10. Engelstad, P.S., Falkowski, M.J., D’Amato, A.W., Slesak, R.A., Palik, B.J., Domke, G.M. & Russell, M.B. (2019). Mapping black ash dominated stands using geospatial and forest inventory data in northern Minnesota, USA. Canadian Journal of Forest Research, 48(8), 892-902. https://doi.org/10.1139/cjfr-2018-0481

  11. Engelstad, P.S., Falkowski, M., Wolter, P., Poznanovic, A., & Johnson, P. (2019). Estimating canopy fuel attributes from low-density LiDAR. Fire, 2(3), 38. https://doi.org/10.3390/fire2030038

  12. Woodward, B., Engelstad, P., Vorster, A., Beddow, C., Krail, S., Vashisht, A., & Evangelista, P. (2017). Forest harvest dataset for northern Colorado Rocky Mountains (1984–2015) generated from a Landsat time series and existing forest harvest records. Data in brief, 15, 724-727. https://doi.org/10.1016/j.dib.2017.10.030



Book Chapters

  1. Engelstad, P., Carver, D., & Young, N. E. (2024). Creating Presence and Absence Points. In J. A. Cardille, M. A. Crowley, D. Saah, & N. E. Clinton (Eds.), Cloud-Based Remote Sensing with Google Earth Engine (pp. 1133–1155). Springer International Publishing. https://doi.org/10.1007/978-3-031-26588-4_52

  2. Engelstad, P., Carver, D., & Young, N. E. (2024). Working with GPS and Weather Data. In J. A. Cardille, M. A. Crowley, D. Saah, & N. E. Clinton (Eds.), Cloud-Based Remote Sensing with Google Earth Engine (pp. 1121–1131). Springer International Publishing. https://doi.org/10.1007/978-3-031-26588-4_51



Software & Datasets

  1. Engelstad P., Jarnevich, C., Sofaer, H., Daniel, W., Peterman, L., Erickson, R.A. (2023). climatchR: An implementation of CLIMATCH in R. v2.0. U.S. Geological Survey software release. Reston, VA. https://doi.org/10.5066/P9ILPPTC

  2. Jarnevich, C.S., LaRoe, J., Engelstad, P., Hays, B., Henderson, G., Williams, D., Shadwell, K., Pearse, I.S., Prevey, J.S., & Sofaer, H.R. (2023). INHABIT species potential distribution across the contiguous United States (ver. 3.0, February 2023): U.S. Geological Survey data release. https://doi.org/10.5066/P9V54H5K

  3. Evans, A., Beaury, E.M., Engelstad, P.S., Teich, N.B., & Bradley, B.A. (2022). Shifting hotspots: Climate change projected to drive contractions and expansions of invasive plant abundance ranges. Data and Datasets. 157. https://doi.org/10.7275/f172-4c95