三峡大:基于贝叶斯空间时间模型和5年纵向研究的贝叶斯空间时间模型和5年纵向研究的牛密度变化的空间时间演变的潜在差异驱动因素和趋势
Yanfeng Gong1,2,3, Yixin Tong1,2,3, Honglin Jiang1,2,3
1Fudan University School of Public Health, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.
Parasites & vectors
|July 14, 2023
概括
三峡大 (TGD) 地区的牛密度反弹. 温度,湿度和植被影响了下游的牛丰度,而上游的种群受到降水,斜率和植被的影响.
科学领域:
- 生态生态学 生态生态学
- 环境科学 环境科学
- 空间分析 空间分析
背景情况:
- 牛的丰富性表现出显著的空间和时间变化.
- 关于影响三峡大 (TGD) 上游和下游牛密度的不同因素的研究有限.
研究的目的:
- 调查影响TGD上游和下游地区牛密度的差异驱动因素.
- 分析这些驱动因素对牛种群动态的时空影响.
主要方法:
- 在长江流域200个地点进行了为期5年的牛调查.
- 收集有关气象,植被,地形和经济变量的数据.
- 采用贝叶斯的时空建模框架来确定牛密度变化的决定因素.
主要成果:
- 与上游地区相比,牛密度显示TGD下游的波动性增加.
- 下游的牛密度与1月最低温度,前一年的NDVI和湿度正相关;与7月最高温度和夜间光线负相关.
- 上游的牛密度与NDVI和降水正相关;与斜率负相关.
结论:
- 在2015年至2019年期间,牛密度反弹.
- 确定了关键驱动因素:温度,湿度,植被和人类活动 (下游);降水,斜坡和植被 (上游).
- 这些发现支持针对牛种群管理和控制的有针对性的战略.
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