生物多样性 ›› 2019, Vol. 27 ›› Issue (1): 13-23. DOI: 10.17520/biods.2018193
所属专题: 钱江源国家公园生物多样性保护与管理
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,*()
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:
Ren Peng1,Yu Jianping2,Chen Xiaonan2,Shen Xiaoli3,Song Xiao1,Zhang Tiantian1,Yu Yongquan2,Ding Ping1,*()
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。
任鹏, 余建平, 陈小南, 申小莉, 宋虓, 张田田, 余永泉, 丁平 (2019) 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. 生物多样性, 27, 13-23. DOI: 10.17520/biods.2018193.
Ren Peng, Yu Jianping, Chen Xiaonan, Shen Xiaoli, Song Xiao, Zhang Tiantian, Yu Yongquan, Ding Ping (2019) Seasonal variation in the distribution of Elliot’s pheasant (Syrmaticus ellioti) in Gutianshan National Nature Reserve. Biodiversity Science, 27, 13-23. DOI: 10.17520/biods.2018193.
自变量 Independent variable | 回归系数 Coefficients | 标准误差 Standard error | z | P | |
---|---|---|---|---|---|
逻辑斯谛回归 Logistic regression, P < 0.0001 | |||||
雌 + 雄 Female + male | 海拔 Altitude | -0.259 | 0.100 | -2.592 | 0.0095** |
日平均气温 Daily average temperature | 0.643 | 0.108 | 5.937 | 0.0000*** | |
雌 Female | 海拔 Altitude | -0.307 | 0.145 | -2.119 | 0.0341* |
日平均气温 Daily average temperature | 0.563 | 0.156 | 3.6 | 0.0003*** | |
雄 Male | 海拔 Altitude | -0.216 | 0.115 | -1.874 | 0.061 |
日平均气温 Daily average temperature | 0.685 | 0.129 | 5.314 | 0.0000*** | |
线性回归 Linear regression, P < 0.0001 | |||||
雌 + 雄 Female + male | 月平均气温 Month average temperature | 6.231 | 0.980 | 6.361 | 0.0000*** |
月平均降水量 Month average precipitation | -1.104 | 0.980 | -1.127 | 0.273 | |
线性回归 Linear regression, P < 0.0001 | |||||
海拔 Altitude | 月平均气温 Month average temperature | 6.107 | 0.413 | 14.803 | 0.0000*** |
月平均降水量 Month average precipitation | 0.000 | 0.002 | 0.182 | 0.856 |
表1 逻辑斯谛回归和线性回归分析结果
Table 1 The results of logistic regression and linear regression analysis
自变量 Independent variable | 回归系数 Coefficients | 标准误差 Standard error | z | P | |
---|---|---|---|---|---|
逻辑斯谛回归 Logistic regression, P < 0.0001 | |||||
雌 + 雄 Female + male | 海拔 Altitude | -0.259 | 0.100 | -2.592 | 0.0095** |
日平均气温 Daily average temperature | 0.643 | 0.108 | 5.937 | 0.0000*** | |
雌 Female | 海拔 Altitude | -0.307 | 0.145 | -2.119 | 0.0341* |
日平均气温 Daily average temperature | 0.563 | 0.156 | 3.6 | 0.0003*** | |
雄 Male | 海拔 Altitude | -0.216 | 0.115 | -1.874 | 0.061 |
日平均气温 Daily average temperature | 0.685 | 0.129 | 5.314 | 0.0000*** | |
线性回归 Linear regression, P < 0.0001 | |||||
雌 + 雄 Female + male | 月平均气温 Month average temperature | 6.231 | 0.980 | 6.361 | 0.0000*** |
月平均降水量 Month average precipitation | -1.104 | 0.980 | -1.127 | 0.273 | |
线性回归 Linear regression, P < 0.0001 | |||||
海拔 Altitude | 月平均气温 Month average temperature | 6.107 | 0.413 | 14.803 | 0.0000*** |
月平均降水量 Month average precipitation | 0.000 | 0.002 | 0.182 | 0.856 |
生境因子 Habitat factor | 植被类型 Vegetation type | 森林起源 Forest origin | 乔木郁闭度 Tree canopy closure | 灌木盖度 Shrub coverage | 草本盖度 Herbaceous coverage | 100 m内水源 Source of water in 100 meters | 海拔 Altitude (m) | 坡位 Position |
---|---|---|---|---|---|---|---|---|
森林起源 Forest origin | -0.415*** | |||||||
乔木郁闭度 Tree canopy closure | 0.135* | -0.142* | ||||||
灌木盖度 Shrub coverage | 0.146** | 0.018 | 0.111* | |||||
草本盖度 Herbaceous coverage | -0.059 | 0.142* | -0.08 | 0.069 | ||||
100 m内水源 Source of water in 100 meters | -0.125* | 0.032 | 0.127* | 0.082 | -0.145** | |||
海拔 Altitude (m) | 0.244*** | -0.452*** | 0.087 | 0.041 | -0.188*** | 0.287*** | ||
坡位 Position | 0.118* | -0.092 | 0.043 | -0.195*** | -0.056 | -0.421*** | 0.185*** | |
坡度 Gradient | 0.041 | 0.003 | 0.181** | 0.281*** | -0.186*** | 0.06 | 0.154** | -0.095 |
表2 栖息地特征参数间的相关系数
Table 2 Correlation coefficients among the characteristic parameters of habitat
生境因子 Habitat factor | 植被类型 Vegetation type | 森林起源 Forest origin | 乔木郁闭度 Tree canopy closure | 灌木盖度 Shrub coverage | 草本盖度 Herbaceous coverage | 100 m内水源 Source of water in 100 meters | 海拔 Altitude (m) | 坡位 Position |
---|---|---|---|---|---|---|---|---|
森林起源 Forest origin | -0.415*** | |||||||
乔木郁闭度 Tree canopy closure | 0.135* | -0.142* | ||||||
灌木盖度 Shrub coverage | 0.146** | 0.018 | 0.111* | |||||
草本盖度 Herbaceous coverage | -0.059 | 0.142* | -0.08 | 0.069 | ||||
100 m内水源 Source of water in 100 meters | -0.125* | 0.032 | 0.127* | 0.082 | -0.145** | |||
海拔 Altitude (m) | 0.244*** | -0.452*** | 0.087 | 0.041 | -0.188*** | 0.287*** | ||
坡位 Position | 0.118* | -0.092 | 0.043 | -0.195*** | -0.056 | -0.421*** | 0.185*** | |
坡度 Gradient | 0.041 | 0.003 | 0.181** | 0.281*** | -0.186*** | 0.06 | 0.154** | -0.095 |
模型组合 Model combination | 自由度 df | 似然对数 Log-Likelihood | AICc | Delta | 权重 Weight |
---|---|---|---|---|---|
e | 2 | -59.12 | 122.39 | 0.00 | 0.18 |
a × e | 3 | -58.26 | 122.80 | 0.42 | 0.14 |
b × e | 3 | -59.01 | 124.30 | 1.91 | 0.07 |
d × e | 3 | -59.01 | 124.30 | 1.91 | 0.07 |
a × d × e | 4 | -57.99 | 124.46 | 2.07 | 0.06 |
c × e | 3 | -59.12 | 124.53 | 2.14 | 0.06 |
a | 2 | -60.33 | 124.79 | 2.40 | 0.05 |
a × b × e | 4 | -58.24 | 124.96 | 2.57 | 0.05 |
a × c × e | 4 | -58.26 | 124.99 | 2.60 | 0.05 |
b × d × e | 4 | -58.85 | 126.16 | 3.77 | 0.03 |
a × d | 3 | -60.01 | 126.30 | 3.91 | 0.02 |
c × d × e | 4 | -59.00 | 126.47 | 4.09 | 0.02 |
b × c × e | 4 | -59.01 | 126.49 | 4.10 | 0.02 |
a × b × d × e | 5 | -57.94 | 126.60 | 4.22 | 0.02 |
a × c × d × e | 5 | -57.99 | 126.69 | 4.30 | 0.02 |
a × b | 3 | -60.26 | 126.80 | 4.41 | 0.02 |
a × c | 3 | -60.26 | 126.80 | 4.41 | 0.02 |
a × b × c × e | 5 | -58.24 | 127.20 | 4.81 | 0.02 |
d | 2 | -62.09 | 128.32 | 5.94 | 0.01 |
b × c × d × e | 5 | -58.82 | 128.36 | 5.97 | 0.01 |
c | 2 | -62.14 | 128.42 | 6.04 | 0.01 |
a × b × d | 4 | -59.98 | 128.43 | 6.04 | 0.01 |
a × c × d | 4 | -60.00 | 128.46 | 6.07 | 0.01 |
b | 2 | -62.18 | 128.50 | 6.11 | 0.01 |
a × b × c | 4 | -60.18 | 128.84 | 6.45 | 0.01 |
a × b × c × d × e | 6 | -57.93 | 128.88 | 6.49 | 0.01 |
c × d | 3 | -62.08 | 130.43 | 8.04 | 0.00 |
b × d | 3 | -62.09 | 130.46 | 8.08 | 0.00 |
b × c | 3 | -62.14 | 130.56 | 8.17 | 0.00 |
a × b × c × d | 5 | -59.96 | 130.63 | 8.24 | 0.00 |
b × c × d | 4 | -62.08 | 132.62 | 10.24 | 0.00 |
表3 模型平均各参数的组合结果
Table 3 The result of combined the parameters of the model average
模型组合 Model combination | 自由度 df | 似然对数 Log-Likelihood | AICc | Delta | 权重 Weight |
---|---|---|---|---|---|
e | 2 | -59.12 | 122.39 | 0.00 | 0.18 |
a × e | 3 | -58.26 | 122.80 | 0.42 | 0.14 |
b × e | 3 | -59.01 | 124.30 | 1.91 | 0.07 |
d × e | 3 | -59.01 | 124.30 | 1.91 | 0.07 |
a × d × e | 4 | -57.99 | 124.46 | 2.07 | 0.06 |
c × e | 3 | -59.12 | 124.53 | 2.14 | 0.06 |
a | 2 | -60.33 | 124.79 | 2.40 | 0.05 |
a × b × e | 4 | -58.24 | 124.96 | 2.57 | 0.05 |
a × c × e | 4 | -58.26 | 124.99 | 2.60 | 0.05 |
b × d × e | 4 | -58.85 | 126.16 | 3.77 | 0.03 |
a × d | 3 | -60.01 | 126.30 | 3.91 | 0.02 |
c × d × e | 4 | -59.00 | 126.47 | 4.09 | 0.02 |
b × c × e | 4 | -59.01 | 126.49 | 4.10 | 0.02 |
a × b × d × e | 5 | -57.94 | 126.60 | 4.22 | 0.02 |
a × c × d × e | 5 | -57.99 | 126.69 | 4.30 | 0.02 |
a × b | 3 | -60.26 | 126.80 | 4.41 | 0.02 |
a × c | 3 | -60.26 | 126.80 | 4.41 | 0.02 |
a × b × c × e | 5 | -58.24 | 127.20 | 4.81 | 0.02 |
d | 2 | -62.09 | 128.32 | 5.94 | 0.01 |
b × c × d × e | 5 | -58.82 | 128.36 | 5.97 | 0.01 |
c | 2 | -62.14 | 128.42 | 6.04 | 0.01 |
a × b × d | 4 | -59.98 | 128.43 | 6.04 | 0.01 |
a × c × d | 4 | -60.00 | 128.46 | 6.07 | 0.01 |
b | 2 | -62.18 | 128.50 | 6.11 | 0.01 |
a × b × c | 4 | -60.18 | 128.84 | 6.45 | 0.01 |
a × b × c × d × e | 6 | -57.93 | 128.88 | 6.49 | 0.01 |
c × d | 3 | -62.08 | 130.43 | 8.04 | 0.00 |
b × d | 3 | -62.09 | 130.46 | 8.08 | 0.00 |
b × c | 3 | -62.14 | 130.56 | 8.17 | 0.00 |
a × b × c × d | 5 | -59.96 | 130.63 | 8.24 | 0.00 |
b × c × d | 4 | -62.08 | 132.62 | 10.24 | 0.00 |
模型平均 Model averaging | 100 m内水源 Source of water in 100 meters | 海拔 Altitude | 坡度 Gradient | 草本盖度 Herbaceous coverage | 灌木盖度 Shrub coverage |
---|---|---|---|---|---|
重要值 Importance value | 0.82 | 0.51 | 0.30 | 0.27 | 0.26 |
标准化回归系数β Standardized regression coefficient β | 1.026 | -0.172 | 0.096 | 0.122 | 0.009 |
P | 0.031* | 0.044* | 0.299 | 0.438 | 0.570 |
表4 各变量的重要值、模型回归系数及P值
Table 4 Importance values, model regression coefficient and the P-value of variables
模型平均 Model averaging | 100 m内水源 Source of water in 100 meters | 海拔 Altitude | 坡度 Gradient | 草本盖度 Herbaceous coverage | 灌木盖度 Shrub coverage |
---|---|---|---|---|---|
重要值 Importance value | 0.82 | 0.51 | 0.30 | 0.27 | 0.26 |
标准化回归系数β Standardized regression coefficient β | 1.026 | -0.172 | 0.096 | 0.122 | 0.009 |
P | 0.031* | 0.044* | 0.299 | 0.438 | 0.570 |
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