Computational Model Library

BHSPopDy (Bighorn sheep population dynamics) (1.2.0)

This is an agent-based model coded in NetLogo. The model simulates population dynamics of bighorn sheep population in the Hell’s Canyon region of Idaho and will be used to develop a better understanding of pneumonia dynamics in bighorn sheep populations. The overarching objective is to provide a decision-making context for effective management of pneumonia in wild populations of bighorn sheep.

BHS_POPDY_beta interface.png

Release Notes

We have updated the age-classes in BHS_POPDY_1.0.2. Also, the user can now specify mortality rates for each age-sex class.

Associated Publications

BHSPopDy (Bighorn sheep population dynamics) 1.2.0

Submitted by Aniruddha Belsare Published Nov 05, 2019 Last modified Nov 05, 2019

This is an agent-based model coded in NetLogo. The model simulates population dynamics of bighorn sheep population in the Hell’s Canyon region of Idaho and will be used to develop a better understanding of pneumonia dynamics in bighorn sheep populations. The overarching objective is to provide a decision-making context for effective management of pneumonia in wild populations of bighorn sheep.

Release Notes

We have updated the age-classes in BHS_POPDY_1.0.2. Also, the user can now specify mortality rates for each age-sex class.

Cite this Model

Aniruddha Belsare, Ryan Long, E Frances Cassirer (2019, November 05). “BHSPopDy (Bighorn sheep population dynamics)” (Version 1.2.0). CoMSES Computational Model Library. Retrieved from: https://doi.org/10.25937/a7fz-tw30

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Contributors
Aniruddha Belsare Ryan Long E Frances Cassirer
DOI

10.25937/a7fz-tw30

Model Version
1.2.0
License
CC-BY-4.0
Programming Language
NetLogo
Software Framework
NetLogo
Operating System
Windows
Publish Date
Tuesday, November 05, 2019
Last Updated
Thursday, November 07, 2019
Downloads 84
Peer Reviewed
Open Code Badge
Version Submitter First published Last modified Status
1.2.0 Aniruddha Belsare Tue Nov 5 17:11:57 2019 Thu Nov 7 16:29:57 2019 Published Peer Reviewed https://doi.org/10.25937/a7fz-tw30

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