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Research | Open Access

Temporal patterns of three sympatric pheasant species in the Nanling Mountains: N-mixture modeling applied to detect abundance

Fasheng Zou1 ( )Qiang Zhang1Min Zhang1Myung-Bok Lee1Xincai Wang1Yuening Gong2Changteng Yang2
Guangdong Key Laboratory of Animal Conservation and Resource Utilization, Guangdong Public Laboratory of Wild Animal Conservation and Utilization, Guangdong Institute of Applied Biological Resources, Guangzhou 510260, China
Guangdong Nanling National Nature Reserve, Ruyuan 512727, China
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Abstract

Background

The reliability of long-term population estimates is crucial for conservation and management purposes. Most previous studies assume that count indices are proportionally related to abundance; however, this assumption may not hold when detection varies spatially and temporally. We examined seasonal variations in abundance of three bird species (Cabot's Tragopan Tragopan caboti, Silver Pheasant Lophura nycthemera, and White-necklaced Partridge Arborophila gingica) along an elevational gradient, using N-mixture models that take into account imperfect detection in our bird data.

Methods

Camera-trapping was used to monitor temporal activity patterns of these species at Guangdong Nanling National Nature Reserve from December 2013 to November 2017 (4 seasons per year). For abundance analysis (N-mixture modeling), we divided a year into 4 seasons, i.e. 3 months per season, and performed the analysis by season. Elevation was incorporated into the N-mixture model as a covariate that may affect abundance. We compared the N-mixture model with a null model (no covariate model) and selected the better model based on AIC values to make an inference.

Results

From 24 sampling sites, we obtained 6786 photographs of 8482 individuals of 44 bird species and 26 mammal species. Silver Pheasant was photographed much more frequently and showed higher temporal activity frequency than White-necklaced Partridge or Cabot's Tragopan. Silver Pheasant was camera-captured most frequently in summer, and other two species in winters. All three species had two daytime activity peaks: between 6:00 a.m. and 10:00 a.m., and between 5:00 p.m. and 7:00 p.m., respectively. Our estimated abundance and detection probability from the N-mixture model were variable by season. In particular, all three species showed greater abundance in summer than in winter, and estimated abundance patterns of all three species were more similar with observed camera-trapping counts in summers. Moreover, in winter, elevation had a positive impact on abundance of Silver Pheasant and Cabot's Tragopan, but not on White-necklaced Partridge.

Conclusions

Our results demonstrate that the N-mixture model performed well in the estimation of temporal population abundance at local fixed permanent plots in mountain habitat in southern China, based on the modeling of repeated camera-trapping counts. The seasonal differences in abundance of the three endemic bird species and the strong effect of elevation on abundance of two species in winter were only indicative of variations in spatio-temporal distribution within species and between species. In identifying suitable habitat for endemic pheasants, the positive elevational effect also suggests that more attention should be paid to conservation of areas with higher elevation in the Nanling Mountains.

References

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Avian Research
Article number: 42

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Cite this article:
Zou F, Zhang Q, Zhang M, et al. Temporal patterns of three sympatric pheasant species in the Nanling Mountains: N-mixture modeling applied to detect abundance. Avian Research, 2019, 10(1): 42. https://doi.org/10.1186/s40657-019-0181-6

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Received: 25 January 2019
Accepted: 28 October 2019
Published: 04 November 2019
© The Author(s) 2019.

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.