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A density estimation model of plateau pika (Ochotona curzoniae) supporting camera‐monitoring programs

As an important species in the Qinghai‐Tibet Plateau, the roles played by plateau pikas in grassland degradation and protection are controversial. The behavior characteristics and population density of this species are important in answering this question, but these traits have not been fully elucid...

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Autores principales: Jia, Ying‐Hui, Qiu, Jun, Ma, Cang, Wang, Jin‐Zhao, Wang, Guang‐Qian, Li, Fang‐Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328412/
https://www.ncbi.nlm.nih.gov/pubmed/34367597
http://dx.doi.org/10.1002/ece3.7865
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author Jia, Ying‐Hui
Qiu, Jun
Ma, Cang
Wang, Jin‐Zhao
Wang, Guang‐Qian
Li, Fang‐Fang
author_facet Jia, Ying‐Hui
Qiu, Jun
Ma, Cang
Wang, Jin‐Zhao
Wang, Guang‐Qian
Li, Fang‐Fang
author_sort Jia, Ying‐Hui
collection PubMed
description As an important species in the Qinghai‐Tibet Plateau, the roles played by plateau pikas in grassland degradation and protection are controversial. The behavior characteristics and population density of this species are important in answering this question, but these traits have not been fully elucidated to date. Camera‐capture methods have been used widely in recent years to characterize or calculate population density with the advantage of simple operation and nonintrusive investigation. However, establishing the relationship between actual population density and monitoring data with the condition that individual identification is not possible is a major challenge for this method. In this study, a model composed of a behavioral module and a burrow system module is proposed and applied to simulate the moving path of each individual pika. Based on Monte Carlo method, the model is used to develop the relationship between population density and recorded capture number, which is compared with the results derived from the random encounter model (REM) based on field observations. The simulated results mixed with the calculated density based on observation data could reach R (2) = 0.98 using linear fitting, with proper parameter settings. A novel index named activity intensity of pikas per population density is also proposed, providing information on both the ecological physical characteristics and monitoring space. The influence of different parameters on this index, mainly the pika number per burrow system, pika activity time outside the burrow, and activity intensity, is discussed. The proposed methodology can be applied to different scenarios in further studies when behavioral characteristics of pikas change for such reasons as climate change and vegetation degradation.
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spelling pubmed-83284122021-08-06 A density estimation model of plateau pika (Ochotona curzoniae) supporting camera‐monitoring programs Jia, Ying‐Hui Qiu, Jun Ma, Cang Wang, Jin‐Zhao Wang, Guang‐Qian Li, Fang‐Fang Ecol Evol Original Research As an important species in the Qinghai‐Tibet Plateau, the roles played by plateau pikas in grassland degradation and protection are controversial. The behavior characteristics and population density of this species are important in answering this question, but these traits have not been fully elucidated to date. Camera‐capture methods have been used widely in recent years to characterize or calculate population density with the advantage of simple operation and nonintrusive investigation. However, establishing the relationship between actual population density and monitoring data with the condition that individual identification is not possible is a major challenge for this method. In this study, a model composed of a behavioral module and a burrow system module is proposed and applied to simulate the moving path of each individual pika. Based on Monte Carlo method, the model is used to develop the relationship between population density and recorded capture number, which is compared with the results derived from the random encounter model (REM) based on field observations. The simulated results mixed with the calculated density based on observation data could reach R (2) = 0.98 using linear fitting, with proper parameter settings. A novel index named activity intensity of pikas per population density is also proposed, providing information on both the ecological physical characteristics and monitoring space. The influence of different parameters on this index, mainly the pika number per burrow system, pika activity time outside the burrow, and activity intensity, is discussed. The proposed methodology can be applied to different scenarios in further studies when behavioral characteristics of pikas change for such reasons as climate change and vegetation degradation. John Wiley and Sons Inc. 2021-07-13 /pmc/articles/PMC8328412/ /pubmed/34367597 http://dx.doi.org/10.1002/ece3.7865 Text en © 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Jia, Ying‐Hui
Qiu, Jun
Ma, Cang
Wang, Jin‐Zhao
Wang, Guang‐Qian
Li, Fang‐Fang
A density estimation model of plateau pika (Ochotona curzoniae) supporting camera‐monitoring programs
title A density estimation model of plateau pika (Ochotona curzoniae) supporting camera‐monitoring programs
title_full A density estimation model of plateau pika (Ochotona curzoniae) supporting camera‐monitoring programs
title_fullStr A density estimation model of plateau pika (Ochotona curzoniae) supporting camera‐monitoring programs
title_full_unstemmed A density estimation model of plateau pika (Ochotona curzoniae) supporting camera‐monitoring programs
title_short A density estimation model of plateau pika (Ochotona curzoniae) supporting camera‐monitoring programs
title_sort density estimation model of plateau pika (ochotona curzoniae) supporting camera‐monitoring programs
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328412/
https://www.ncbi.nlm.nih.gov/pubmed/34367597
http://dx.doi.org/10.1002/ece3.7865
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