The SWCNH (South Willamette Coupled Natural Human) Dataverse is the repository for the programs, code and output data for the US NSF-funded, multi-university collaboration “CNH: Collab Research: The Interactions of Climate Change, Land-Management Policies, and Forest Succession on Fire Hazard and Ecosystem Trajectories in the Wildland-Urban Interface”. The SWCNH Dataverse is the highest level of organization and contains five datasets: SWCNH Dataverse ReadMe files, Envision Installation Package, SWCNH Envision installation and use tutorials, Envision Fire Generator, and SWCNH Envision canonical simulation outputs. The research project and its coupled modeling system development was a collaborative effort of more than 25 researchers and students from the University of Oregon (UO), Oregon State University (OSU), and the USDA Forest Service. Bart Johnson (UO) and John Bolte (OSU) served as Principal Investigators. Co-PIs included David Hulse, Robert Ribe and Scott Bridgham (UO), and Ronald Neilson (OSU). Senior researchers included Alan Ager, Jane Kertis, Constance Harrington, Dominique Bachelet, Allan Branscomb, Chris Enright, Peter Gould, Max Nielsen-Pincus, James Lenihan, James Merzenich, and Alison Reger. Graduate students included Gabriel Yospin, Tim Sheehan, David Conklin, Nathan Ulrich, Cody Evers, Gwynne Mhuireach and Wu Hong. Fire Behavior calculations were produced with models developed by the Missoula Fire Sciences Laboratory, Missoula, MT. Stu Brittain modified the fire behavior code library for Envision’s wildfire submodel. Michelle Day built the fire generator system and generated fire lists. Haiganoush Preisler assisted with the algorithms for fire-climate relationships. James Sulzman implemented most Envision code. This research is based upon work supported by the National Science Foundation under Grants No. 0816475 and 0816228 with added support from the USDA Forest Service Western Wildland Environmental Threat Assessment Center (WWETAC) and the USFS Missoula Fire Lab at the Rocky Mountain Research Station (21-CS-11221637-131).
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4. SWCNH Envision canonical simulation outputs
Jul 15, 2023
Johnson, Bart, 2023, "4. SWCNH Envision canonical simulation outputs", https://doi.org/10.7910/DVN/0JNJFB, Harvard Dataverse, V2
This dataset contains the simulation outputs generated from 600 canonical SWCNH Envision model runs. They contain all outputs generated from 12 scenarios comprised of a fully crossed set of three scenario dimensions. Each scenario was run 50 times to produce 50 scenario replicates.
0. SWCNH Dataverse ReadMe Files
Jul 15, 2023
Johnson, Bart, 2023, "0. SWCNH Dataverse ReadMe Files", https://doi.org/10.7910/DVN/ELMITB, Harvard Dataverse, V1
This dataset contains a ReadMe file describing the SWCNH Dataverse and its associated datasets, as well as individual ReadMe files describing the specific data used for each paper that cites this repository and employs its programs, outputs and other associated data.
3. Envision Fire Generator
Jul 12, 2023
Johnson, Bart, 2023, "3. Envision Fire Generator", https://doi.org/10.7910/DVN/TKLWDB, Harvard Dataverse, V1, UNF:6:KuM2L2e3rrjFH543T8BNXg== [fileUNF]
This dataset contains the Rcode and all data needed to generate Envision fire lists for the Eugene_Springfield study area
2. SWCNH Envision installation and use tutorials
2. SWCNH Envision installation and use tutorials
Jul 12, 2023
Johnson, Bart, 2023, "2. SWCNH Envision installation and use tutorials", https://doi.org/10.7910/DVN/PUWTBQ, Harvard Dataverse, V1
This package contains installation instructions and user tutorials developed over a series of courses taught by Bart Johnson and Gwynne Mhuireach to University of Oregon students from 2011-2013, including Landscape Architecture Design and Planning studios, and Climate Adaptation courses.
1. Envision Installation Package
Jul 12, 2023
Bolte, John, 2023, "1. Envision Installation Package", https://doi.org/10.7910/DVN/OWAXF2, Harvard Dataverse, V1
The Envision Installation package contains all materials needed to run the SWCNH Envision simulation model.
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