可访问性推动了对亚马逊类的研究工作
Bruna L B Façanha1,2, Raquel L Carvalho3, Rony P S Almeida2,4
1Centro Avançado de Pesquisa-Ação da Conservação e Recuperação Ecossistêmica da AMazônia (CAPACREAM), Universidade Federal do Amapá, Macapá, Amapá, Brazil.
Proceedings. Biological sciences
|February 3, 2026
概括
巴西亚马逊地区的生物多样性知识分布不均,偏远地区和土著领土被忽视. 有针对性的调查和社区参与对于有效保护研究不足的物种,如类,至关重要.
科学领域:
- 生物多样性研究的研究.
- 保护科学 保护科学
- 机器学习在生态学的应用.
背景情况:
- 热带地区拥有巨大的生物多样性,但面临着严重的知识缺口,特别是在巴西亚马逊地区.
- 亚马逊地区的人类干扰正在加速物种消失,需要更好地评估生物多样性.
- 尽管类具有生态重要性和公共卫生相关性,但它们往往被研究不足.
研究的目的:
- 绘制巴西亚马逊地区 sarcosaprophagous 的知识分布图.
- 确定生物多样性采样和知识生成中的偏见.
- 通过强调被忽视的地区和分类群体,为有针对性的保护战略提供信息.
主要方法:
- 利用8244个的发生记录进行分析.
- 采用机器学习技术,在不同的空间尺度 (家族,物种,零模型) 上建模知识概率.
- 评估了与可访问性和土地使用模式相关的知识分布.
主要成果:
- 在亚马逊地区的知识分布中发现了显著的空间偏差.
- 大约40%的森林地区的家庭和物种的发生概率低于10%.
- 知识的概率与可访问性呈正相关性,退化地区的代表过多,偏远的,具有高保护价值的地区,包括土著领土,被忽视.
结论:
- 解决生物多样性知识差距需要不仅仅是增加研究力度;它需要对未经调查的地区和种类进行战略准.
- 缺乏研究的群体,如类,对于了解生态系统的功能至关重要,需要集中研究.
- 在偏远地区进行协作调查和与当地社区接触对于全面评估和保护亚马逊生物多样性至关重要.
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