Data and code associated with “Supporting Adaptive Management with Ecological Forecasting: Chronic Wasting Disease in the Jackson Elk Herd”

Galloway, Nathan L.; Monello, Ryan J.; Brimeyer, Doug; Cole, Eric K.; Hobbs, N. Thompson

Data and code associated with “Supporting Adaptive Management with Ecological Forecasting: Chronic Wasting Disease in the Jackson Elk Herd”

dc.contributor.author	Galloway, Nathan L.
dc.contributor.author	Monello, Ryan J.
dc.contributor.author	Brimeyer, Doug
dc.contributor.author	Cole, Eric K.
dc.contributor.author	Hobbs, N. Thompson
dc.coverage.temporal	1997-2016	en_US
dc.date.accessioned	2021-08-20T20:13:34Z
dc.date.available	2021-08-20T20:13:34Z
dc.date.issued	2021
dc.description	Final_Data.zip contains several spreadsheets representing data collected by both the Wyoming Game and Fish Department and the US Fish and Wildlife Service for elk management: Jackson feedground census, 1998-2016; Harvest data, 1997-2015; Hunt area census, 1998-2016; Chronic wasting disease test results, 1998-2015. Final_Code.zip contains several Program R scripts written for data analysis and model fitting as described in the full associated article.	en_US
dc.description	Department of Ecosystem Science and Sustainability
dc.description.abstract	Adaptive management has emerged as the prevailing approach for combining environmental research and management to advance science and policy. Adaptive management, as originally formulated by Carl Walters in 1986, depends on the use of Bayesian models to provide a framework to accumulate knowledge. The emergence of ecological forecasting using the Bayesian framework has provided robust tools and supports a new approach to informing adaptive management, which can be particularly useful in developing policy for managing infectious disease in wildlife. We used the potential infection of elk populations with chronic wasting disease in the Jackson Valley of Wyoming and the National Elk Refuge as a model system to show how Bayesian forecasting can support adaptive management in anticipation of management challenges. The core of our approach resembles the sex- and age-structured, discrete time models used to support management decisions on elk harvest throughout western North America. Our model differs by including stages for CWD infected and unaffected animals. We used data on population counts, sex and age classification, and CWD testing, as well as results from prior research, in a Bayesian statistical framework to predict model parameters and the number of animals in each age, sex, and disease stage over time. Initial forecasts suggested CWD may reach a mean prevalence in the population of 12%, but uncertainty in this forecast is large and we cannot rule out a mean forecasted prevalence as high as 20%. Using recruitment rates observed during the last two decades, the model predicted that a CWD prevalence of 7% in females would cause the population growth rate (l) to drop below 1, resulting in population declines even when female harvest was zero. The primary value of this ecological forecasting approach is to provide a framework to assimilate data with understanding of disease processes to enable continuous improvement in understanding the ecology of CWD and its management.	en_US
dc.description.sponsorship	Data collection was funded as part of management efforts by the Wyoming Game and Fish Department and the US Fish and Wildlife Service. Data analysis and work for publication was funded by the US Fish and Wildlife Service and the National Park Service.	en_US
dc.format.medium	ZIP
dc.format.medium	CSV
dc.format.medium	R
dc.format.medium	PDF
dc.identifier.uri	https://hdl.handle.net/10217/233650
dc.identifier.uri	http://dx.doi.org/10.25675/10217/233650
dc.language	English	en_US
dc.language.iso	eng	en_US
dc.publisher	Colorado State University. Libraries	en_US
dc.relation.ispartof	Research Data
dc.relation.isreferencedby	Galloway NL, Monello RJ, Brimeyer D, Cole EK, Hobbs NT. Supporting adaptive management with ecological forecasting: chronic wasting disease in the Jackson Elk Herd. Ecosphere. 2021 Oct;12(10):e03776. https://doi.org/10.1002/ecs2.3776	en_US
dc.rights.license	The material is open access and distributed under the terms and conditions of the Creative Commons Public Domain "No rights reserved" (https://creativecommons.org/share-your-work/public-domain/cc0/).
dc.rights.uri	https://creativecommons.org/share-your-work/public-domain/cc0/
dc.subject	adaptive management	en_US
dc.subject	Cervus canadensis	en_US
dc.subject	chronic wasting disease	en_US
dc.subject	disease invasion	en_US
dc.subject	ecological forecasting	en_US
dc.subject	elk	en_US
dc.title	Data and code associated with “Supporting Adaptive Management with Ecological Forecasting: Chronic Wasting Disease in the Jackson Elk Herd”	en_US
dc.type	Dataset	en_US