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 (link to recent presentation here). I am also the primary developer and maintainer of climatchR and the GDPE Course Archive and Syllabus Search Tool (CASST).

I consider myself a quantitative ecologist working primarily with R programming to answer questions related to computational, spatial, and invasion ecology.

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 and patterns underlying plant invasions. The ideal outcome of this work is to both contribute to the research community 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

 

Software & Datasets

  1. Jarnevich, C.S., Engelstad, P., Williams, D.A., Shadwell, K.S., Reimer, C.J., Henderson, G.C., Prevéy, J.S., & Pearse, I.S. (2024) INHABIT species potential distribution across the contiguous United States (ver. 4.0, June 2024): U.S. Geological Survey data release. https://doi.org/10.5066/P14HNEJF

  2. 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

  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


Peer-Reviewed Publications

  1. Jarnevich C.S., Engelstad P., Williams D., Shadwell K., Reimer C., Henderson G., Prevéy J.S., Pearse I.S. (2024) Predicted occurrence and abundance habitat suitability of invasive plants in the contiguous United States: updates for the INHABIT web tool. NeoBiota 96:261-278. https://doi.org/10.3897/neobiota.96.134842

  2. Evangelista, P.H., Young, N.E., Schulte, D.K., Tricorache, P.D., Luizza, M.W., Durant, S.M., Jones, K.W., Mitchell, N., Maule, T., Ali, A.H., Tesfai, R.T., & Engelstad, P.S. (2024). Mapping illegal trade routes of live cheetahs from the Horn of Africa to the Arabian Peninsula. Conservation Biology, e14412. https://doi.org/10.1111/cobi.14412

  3. Williams, D.A., Shadwell, K.S., Pearse, I.S., Prevéy, J.S., Engelstad, P., Henderson, G.C., & Jarnevich, C.S. (2024). Predictor importance in habitat suitability models for invasive terrestrial plants. Diversity and Distributions, e13906. https://doi.org/10.1111/ddi.13906

  4. Evans, A.E., Jarnevich, C.S., Beaury, E.M., Engelstad, P.S., Teich, N.B., LaRoe, J.M., & Bradley, B.A. (2024). 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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


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 (link to recent presentation here). I am also the primary developer and maintainer of climatchR and the GDPE Course Archive and Syllabus Search Tool (CASST).

I consider myself a quantitative ecologist working primarily with R programming to answer questions related to computational, spatial, and invasion ecology.

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 and patterns underlying plant invasions. The ideal outcome of this work is to both contribute to the research community 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

 

Software & Datasets

  1. Jarnevich, C.S., Engelstad, P., Williams, D.A., Shadwell, K.S., Reimer, C.J., Henderson, G.C., Prevéy, J.S., & Pearse, I.S. (2024) INHABIT species potential distribution across the contiguous United States (ver. 4.0, June 2024): U.S. Geological Survey data release. https://doi.org/10.5066/P14HNEJF

  2. 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

  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


Peer-Reviewed Publications

  1. Jarnevich C.S., Engelstad P., Williams D., Shadwell K., Reimer C., Henderson G., Prevéy J.S., Pearse I.S. (2024) Predicted occurrence and abundance habitat suitability of invasive plants in the contiguous United States: updates for the INHABIT web tool. NeoBiota 96:261-278. https://doi.org/10.3897/neobiota.96.134842

  2. Evangelista, P.H., Young, N.E., Schulte, D.K., Tricorache, P.D., Luizza, M.W., Durant, S.M., Jones, K.W., Mitchell, N., Maule, T., Ali, A.H., Tesfai, R.T., & Engelstad, P.S. (2024). Mapping illegal trade routes of live cheetahs from the Horn of Africa to the Arabian Peninsula. Conservation Biology, e14412. https://doi.org/10.1111/cobi.14412

  3. Williams, D.A., Shadwell, K.S., Pearse, I.S., Prevéy, J.S., Engelstad, P., Henderson, G.C., & Jarnevich, C.S. (2024). Predictor importance in habitat suitability models for invasive terrestrial plants. Diversity and Distributions, e13906. https://doi.org/10.1111/ddi.13906

  4. Evans, A.E., Jarnevich, C.S., Beaury, E.M., Engelstad, P.S., Teich, N.B., LaRoe, J.M., & Bradley, B.A. (2024). 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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