Improve the management of CWD-affected wild cervid populations

Activities to be performed include data wrangling to populate the surveillance optimization project for chronic wasting disease (SOP4CWD) data warehouse [hereafter, 'data wrangling'] funding priority: improve the management of CWD‐affected wild cervid populations by increasing reporting capacity of CWD in wild cervids. Expected results: incorporation of additional surveillance and auxiliary data from western US states and provinces into the SOP4CWD data warehouse (hereafter, 'warehouse') will improve early detection and subsequent management of CWD by wildlife agencies. Expected benefits: incorporation of data from additional wildlife habitats, species (mule deer, ELK, moose, caribou, etc.), and landscapes will benefit all agencies participating in the warehouse in (1) decision‐support tools (i.e., models) embedded in the warehouse (2) easier data sharing with subsets of data released for use in approved research activities by external researchers with wildlife agency approval, (3) enhanced and increasingly sophisticated modeling techniques allowing for development of precise and dynamic surveillance systems that account for efforts and disease distribution in adjoining jurisdiction, and (4) where capacity does not currently exist, in data storage in a single, secure location; expert elicitation of CWD emergence and spread risk factors [hereafter, 'expert elicitation'] funding priority: improve the management of CWD‐affected wild cervid populations through advances in risk analysis. 3 expected results: implementation of a practical solution to identify and rank CWD risk factors (introduction and spread) for wildlife management agencies. Expected benefits: the warehouse uses habitat data and expert elicitation in conjunction with a previously published hazard model (schuler ET AL. 2022) to pinpoint areas of disproportionate risk of CWD emergence from natural (i.e., migration) and anthropogenic (i.e., translocation or transport) movements. Gathering expert elicitation of risks for western habitats will expand the hazard model for use in the western portion of the continent and with all CWD‐susceptible species.; expert elicitation of CWD emergence and spread risk factors [hereafter, 'expert elicitation'] funding priority: improve the management of CWD‐affected wild cervid populations through advances in risk analysis. 3 expected results: implementation of a practical solution to identify and rank CWD risk factors (introduction and spread) for wildlife management agencies. Expected benefits: the W arehouse uses habitat data and expert elicitation in conjunction with a previously published hazard model (schuler ET AL. 2022) to pinpoint areas of disproportionate risk of CWD emergence from natural (i.e., migration) and anthropogenic (i.e., translocation or transport) movements. Gathering expert elicitation of risks for western habitats will expand the hazard model for use in the western portion of the continent and with all CWD‐susceptible species. Given successful completion of this proposed work, wildlife agencies will be in position to better curate, standardize, and store their data, and apply the most relevant SOP4CWD models all CWD‐susceptible species, which will improve the management of CWD‐affected wild cervid populations through advances in risk analysis. This approach 1) saves financial and personnel resources by identifying and targeting CWD efforts and 2) improves early detection, which provides better management success. The hazard model has already been successfully used to detect the first cases of CWD in tennessee, alabama, and florida. Our target audience are wildlife agencies, who are responsible for using science‐based approaches to manage and sustain healthy wild cervid herds. They will directly benefit from software to store and standardize data and develop risk‐based surveillance in their states. Expansion of models to other CWD‐suscept ible species will support an ecosystem approach to CWD transmission and management, which will be beneficial to large land managers such as state wildlife agencies, federal agencies (US dept. Of the interior ‐ national park service, bureau of land management, fish and wildlife service; US dept. Of agriculture - forest service), and tribal nations. Wafwa representative thompson will lead the work between the cwhl team and wafwa to organize and submit data into the warehouse as well as work with schuler to convene representatives and implement resulting methods to collect data on risk factors for disease