发生数据来源对物种分布建模有意义:基于Biomod2的Quercus variabilis的案例研究
Yipei Zhao1, Jianfeng Liu1, Qi Wang1
1State Key Laboratory of Efficient Production of Forest Resources, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration Research Institute of Forestry, Chinese Academy of Forestry Beijing China.
Ecology and evolution
|May 9, 2025
概括
选择正确的物种发生数据对于准确的气候变化影响预测至关重要. 科学调查数据提供了比在线样本数据更可靠的物种分布模型 (SDM),用于预测未来的息地变迁.
科学领域:
- 生态学和生物地理学
- 气候变化生物学 气候变化生物学
- 保护科学 保护科学
背景情况:
- 气候变化正在增加自然灾害的频率和严重程度,影响物种分布.
- 物种分布模型 (SDM) 对于评估气候变化对生物多样性的影响至关重要.
- SDM的准确性受到发生数据的质量和来源的重大影响.
研究的目的:
- 为了比较SDM的准确性,使用在线样本数据与科学调查数据对*Quercus variabilis*进行比较.
- 在未来的气候场景下分析预测分布范围的差异,环境变量贡献和心状移动.
- 为可靠的SDM预测提供选择最佳事件数据源的指导.
主要方法:
- 利用Biomod2集合建模平台来构建SDM.
- 对比了两个不同的发生数据来源:在线样本记录和科学调查数据.
- 使用AUC和TSS指标评估模型准确性,并分析预测的分布转移和变量重要性.
主要成果:
- 使用科学调查数据构建的SDM显示出更高的预测准确性 (AUC=0.9720,TSS=0.8370).
- 科学调查数据为当前分布提供了更准确的预测,以及更明显的未来息地转移和中位移动.
- 虽然关键的环境变量相似,但它们的重要性不同:在线数据的人类活动 (17.76%) 和调查数据的高度 (17.79%).
结论:
- 事件数据源的选择显著影响SDM结果和可靠性.
- 科学调查数据对于精确的物种分布建模和预测气候驱动范围变化的优越.
- 这项研究强调了仔细选择数据源的关键需求,以改善气候变化下的保护计划.
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