Abstract Predicting the geographical distribution of a species is a central topic in ecology, conservation and management of natural resources especially for invasive organisms. Invasive species can modify the structure and function of invaded ecosystems, altering their biodiversity, and causing significant economic losses locally and globally. Therefore, measuring and visualizing the uncertainty inherent in species’ potential distributions is fundamental for effective biodiversity monitoring and planning conservation interventions. This paper discusses a new Bayesian approach to mapping this uncertainty using cartograms, previously published knowledge, and presence/absence data.

中文翻译：

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物种分布模型中的制图不确定性：贝叶斯方法

摘要 预测物种的地理分布是自然资源生态学、保护和管理的中心课题，特别是对于入侵生物。入侵物种可以改变被入侵生态系统的结构和功能，改变其生物多样性，并在当地和全球造成重大经济损失。因此，测量和可视化物种潜在分布中固有的不确定性对于有效的生物多样性监测和规划保护干预措施至关重要。本文讨论了一种新的贝叶斯方法，可以使用制图、以前发布的知识和存在/不存在数据来映射这种不确定性。