MoosePOPd Web Interactive: Software to investigate the demography of Moose in New York, USA from 2015-2019

This software is being shared under a MIT license. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use,...

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Bibliographic Details
Main Authors: Connelly, Patrick, Hanley, Brenda, Frair, Jacqui, Schuler, Krysten
Format: Software
Language:English
Published: 2020
Subjects:
Online Access:https://hdl.handle.net/1813/70162
https://doi.org/10.7298/k033-va79
Description
Summary:This software is being shared under a MIT license. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. We would like to thank Mathew Plourde and the online R troubleshooting community for the code segment used to create the sequentially illuminated tabs in the user interface. Population matrix models are analytical tools used to understand the demographic properties of populations. We used the annual counts of calf, young adult, and mature adult moose in the Adirondack region of New York, USA between 2015 and 2019 understand population dynamics. We used a combinatorial optimization algorithm to estimate the life table, predicted annual abundances, growth rates (asymptotic, transient and cumulative), stable stage distribution, reproductive value, survival rates, sensitivities, elasticities, damping ratios, harmonic and arithmetic mean abundances, and reactivity. This interactive software displays the results, and may be modified to investigate moose dynamics in regions outside New York state. Funding provided by the Federal Aid in Wildlife Restoration Act ...