生物多样性 ›› 2019, Vol. 27 ›› Issue (1): 13-23.DOI: 10.17520/biods.2018193

• 研究报告 • 上一篇    下一篇

古田山国家级自然保护区白颈长尾雉的分布格局及其季节变化

任鹏1,余建平2,陈小南2,申小莉3,宋虓1,张田田1,余永泉2,丁平1,*()   

  1. 1 浙江大学生命科学学院, 杭州 310058
    2 钱江源国家公园生态资源保护中心, 浙江开化 324300
    3 中国科学院植物研究所植被与环境变化国家重点实验室, 北京 100093
  • 收稿日期:2018-07-15 接受日期:2018-10-12 出版日期:2019-01-20 发布日期:2019-03-15
  • 通讯作者: 丁平
  • 基金资助:
    浙江省科技计划(2015C02016)

Seasonal variation in the distribution of Elliot’s pheasant (Syrmaticus ellioti) in Gutianshan National Nature Reserve

Ren Peng1,Yu Jianping2,Chen Xiaonan2,Shen Xiaoli3,Song Xiao1,Zhang Tiantian1,Yu Yongquan2,Ding Ping1,*()   

  1. 1 College of Life Sciences, Zhejiang University, Hangzhou 310058
    2 Center of Ecology and Resources, Qianjiangyuan National Park, Kaihua, Zhejiang 324300
    3 State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093
  • Received:2018-07-15 Accepted:2018-10-12 Online:2019-01-20 Published:2019-03-15
  • Contact: Ding Ping

摘要:

为了解浙江省古田山国家级自然保护区内白颈长尾雉(Syrmaticus ellioti)的分布格局和季节变化, 2014年5月至2016年4月, 我们对其进行了为期2年的网格化监测。共有44个公里网格拍摄到白颈长尾雉, 独立探测数量为211次, 雌雄性比为1 : 1.64。白颈长尾雉主要分布在实验区和缓冲区, 其探测率在常绿落叶阔叶混交林、杉木(Cunninghamia lanceolata)林、针阔叶混交林、人工油茶(Camellia oleifera)林和常绿阔叶林中依次递减, 主要分布在海拔600-800 m。冬、春两季, 白颈长尾雉活动强度和区域相对较小, 而夏、秋两季活动强度和区域相对增加, 其分布在海拔段(F4,12 = 3.76, P < 0.05)和季节间(F3,12 = 3.34, P < 0.05)都存在显著差异。对海拔和气候因子进行回归分析发现, 日平均气温和海拔对白颈长尾雉是否出现均有极显著影响(P < 0.01); 白颈长尾雉月探测率和探测到白颈长尾雉位点的海拔均与月平均气温呈极显著正相关(P < 0.001), 而与月平均降水量无显著线性关系(P > 0.05)。这表明白颈长尾雉的活动在很大程度上受海拔和气温影响, 随月平均气温的升高有向高海拔迁移的趋势。模型选择和多模型推断显示, 最优模型仅保留“100 m内水源”这一个变量, 次优模型是“100 m内水源 × 海拔”, 最优和次优模型的权重分别为0.18和0.14, “100 m内水源”和“海拔”是影响白颈长尾雉在保护区内分布的重要因子, 重要值分别为0.82和0.51。因此, 白颈长尾雉的分布并非仅由某一个或几个环境变量决定, 而是由多个环境变量共同决定。气温的变化和对不同海拔段的选择是导致白颈长尾雉形成不同季节分布格局的原因。

关键词: 红外相机技术, 白颈长尾雉, 分布特征, 气候, 模型选择和多模型推断

Abstract:

Here we studied the seasonal variation in the distribution pattern of Elliot’s pheasant (Syrmaticus ellioti) in Gutianshan National Nature Reserve, in Zhejiang Province, China. From May 2014 to April 2016, Elliot’s pheasants were monitored with camera traps as part of the grid monitoring system. Elliot’s pheasants were detected in 44 1 km × 1 km survey blocks, 211 independent times. The observed sex ratio was F : M = 1 : 1.64. These results showed that Elliot’s pheasant is mainly distributed in the buffer and experimental zones. Within the reserve, the detection rate of Elliot’s pheasant decreased over the gradient from mixed evergreen and deciduous broad leaf forest, Cunninghamia lanceolata forest, mixed coniferous and broad leaf forest to artificial Camellia oleifera forest and evergreen broad leaf forest. Elliot’s pheasant mainly lived at altitudes of 600-800 m. In winter and spring, their activity intensity was lower and the active area of Elliot’s pheasant was relatively smaller compared with the summer and autumn. In short, the distribution between altitudinal intervals (F4,12 = 3.76, P < 0.05) and seasons (F3,12 = 3.34, P < 0.05) differed significantly. Performing a regression analysis on altitudinal intervals and climatic factors showed that the daily average temperature and altitudinal intervals both significantly influenced the presence of Elliot’s pheasant (P < 0.01). Both the monthly detection rate of Elliot’s pheasant and the altitude at which Elliot’s pheasant was detected had a significant positive correlation with the monthly mean temperature (P < 0.001), but had no significant linear relationship with the monthly mean rainfall (P > 0.05). These results showed that the presence of Elliot’s pheasant was largely influenced by altitude and temperature. Elliot’s pheasants tended to move to higher altitude as the average monthly temperature increased. According to the results of model selection and multimodel inference, the optimal model only included by the variable “source of water within 100 meters”, and the suboptimal model was “source of water within 100 meters × altitude”, with weights of 0.18 and 0.14. This means that “source of water within 100 meters” and “altitude” were important factors affecting the distribution of Elliot’s pheasant, whose importance values were 0.82 and 0.51, respectively. Overall, the distribution of Elliot’s pheasant was determined by various environmental variables, rather than one and/or several environmental variables. In addition, the changes in temperature and the range of altitudinal intervals led to the differing seasonal distribution pattern of Elliot’s pheasant.

Key words: camera-trapping, Elliot’s pheasant;, distribution pattern, climate, model selection and multimodel inference