使用模糊逻辑来比较基于专家知识和采样记录开发的物种分布模型:在物种分布建模中,专家知识与采样对比
David Romero1, Raúl Maneyro2, José Carlos Guerrero3
1Biogeography, Diversity, and Conservation Research Team, Department of Animal Biology, Faculty of Sciences, Universidad de Málaga, Málaga, Spain. davidrp@uma.es.
Frontiers in zoology
|December 8, 2023
概括
模糊逻辑建模有效地比较了专家知识和物种记录,以预测乌拉圭的两动物分布. 专家知识更好地解释了受威胁的物种,而对通用物种的记录更准确.
科学领域:
- 生态生态学 生态生态学
- 保护生物学 保护生物学
- 计算生物学 计算生物学
背景情况:
- 专家知识和物种记录被用于物种分布建模 (SDM).
- 模糊逻辑建模提供了一个框架,通过赋予连续真实值来整合这些不同的数据源.
- 这种方法允许在不同类型的数据中建立一个可比的"有利性"单位.
研究的目的:
- 应用模糊逻辑建模来比较专家知识和观察记录,以推断乌拉圭的两动物分布.
- 评估这些模型对受威胁,无处不在和非受威胁/非无处不在物种的性能.
- 通过结合两个数据源,获得有利位置的统一预测.
主要方法:
- 使用模糊逻辑建模,从专家知识和物种发生记录中创建分布模型.
- 模型的比较是基于它们预测不同物种类别有利位置的能力.
- 计算了一个模糊交叉点,以整合来自两个知识来源的预测.
主要成果:
- 基于专家的模型使用了更多的变量,并且不太容易产生抽样偏差.
- 专家知识模型对危物种的记录模型表现同样好或比记录模型更好.
- 观察记录为非受威胁,非无处不在和无处不在的物种提供了更准确的模型.
结论:
- 模糊建模提供了一个客观的方法来比较SDM中的专家知识和物种记录.
- 专家知识对 threatened 威胁物种的建模更有效,而观察到的数据对一般物种更优越.
- 这些发现有助于在保护规划中战略性地利用专家知识.
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