Endemics–Area Relationships (EARs) are fundamental in theoretical and applied biogeography for understanding distribution patterns and promoting biodiversity conservation. However, calculating EARs for vascular plant species from existing data is problematic because of biased knowledge of endemic species distributions and differences between taxonomies. We aimed to overcome these challenges by developing a new standardized global dataset based on expert knowledge to produce a set of global EARs.

We developed a nested circle design, with grain sizes of 10⁴, 10⁵, 10⁶, 10⁷, and 10⁸ km², respectively, and a global distribution of plots based on a stratified random scheme. The number of vascular plant species endemic to each circle was then estimated independently by five experts randomly chosen from a pool of 23, as both a minimum and a maximum value (lower and upper bounds of the estimation), taking into account the limitations of current knowledge and varied species concepts in existing taxonomies. This procedure resulted in a dataset of 3000 expert estimates.

Based on the data, we produced three global EARs for endemic species richness using minimum, maximum and average estimates. As a validation, we used all three models to extrapolate to the entire world, producing estimates of 284,493 (minimum), 398,364 (maximum) and 312,243 (average) vascular plant species. These figures conform to the range of taxonomists’ estimates. From the models, we calculated the average area needed to harbour a single endemic species as 12,875 km² (range 9675–20,529).

The global vascular plant EARs we calculated represent the first standardized, quantitative expectations of plant endemism at any given scale (sampling unit size). These EARs allow us to provide a clear answer to a long-standing but elusive biogeographical question: how to assess whether any area on the surface of the Earth is rich or poor in endemics relative to the average.

地方-地区关系（EARs）在理论和应用生物地理学中对于理解分布模式和促进生物多样性保护至关重要。但是，由于对特有物种分布和分类法之间的差异的认识存在偏差，因此根据现有数据计算维管植物物种的EARs是有问题的。我们旨在通过基于专家知识开发新的标准化全局数据集以产生一组全局EAR来克服这些挑战。

我们开发了一种嵌套的圆的设计，具有10的晶粒尺寸⁴，10 ⁵，10 ⁶，10 ⁷，和10 ⁸ 公里²，分别与根据一个分层随机方案图的全局分布。然后由五种专家从23个样本库中随机选择每个圆的地方性维管植物物种数量，作为最小值和最大值（估计的上下限），同时考虑到当前的局限性现有分类法中的知识和各种物种概念。此过程产生了3000个专家估计值的数据集。

根据这些数据，我们使用最小，最大和平均估计值得出了三个全球地方性物种丰富度的EAR。作为验证，我们使用了所有三个模型来推断整个世界，得出的估计数量为284,493（最小），398,364（最大）和312,243（平均）维管植物物种。这些数字符合分类学家的估计范围。根据这些模型，我们计算出拥有一个地方特有物种所需的平均面积为12,875 km ²（范围9675–20,529）。

我们计算出的全球维管植物EAR代表了在任何给定规模（采样单位大小）下植物特有性的第一个标准化的，定量的期望。这些EARs使我们能够为一个长期但难以捉摸的生物地理学问题提供一个明确的答案：如何评估地球表面上相对于平均水平而言，地方性流行病是贫富。