Biodiversity indicators are used to inform decisions and measure progress toward global targets, such as the United Nations Sustainable Development Goals. Indicators aggregate and simplify complex information, so underlying information influencing its reliability and interpretation (e.g., variability in data and uncertainty in indicator values) can be lost. Communicating uncertainty is necessary to ensure robust decisions and limit misinterpretations of trends, yet variability and uncertainty are rarely quantified in biodiversity indicators. We developed a guide to representing uncertainty and variability in biodiversity indicators. We considered the key purposes of biodiversity indicators and commonly used methods for representing uncertainty (standard error, bootstrap resampling, and jackknife resampling) and variability (quantiles, standard deviation, median absolute deviation, and mean absolute deviation) with intervals. Using 3 high-profile biodiversity indicators (Red List Index, Living Planet Index, and Ocean Health Index), we tested the use, suitability, and interpretation of each interval method based on the formulation and data types underpinning the indicators. The methods revealed vastly different information; indicator formula and data distribution affected the suitability of each interval method. Because the data underpinning each indicator were not normally distributed, methods relying on normality or symmetrical spread were unsuitable. Quantiles, bootstrapping, and jackknifing provided useful information about the underlying variability and uncertainty. We built a decision tree to inform selection of the appropriate interval method to represent uncertainty or variation in biodiversity indicators, depending on data type and objectives. Our guide supports transparent and effective communication of biodiversity indicator trends to facilitate accurate interpretation by decision makers.

中文翻译：

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在生物多样性指标中表示可变性和不确定性的指南

生物多样性指标用于为决策提供信息并衡量实现全球目标的进展，例如联合国可持续发展目标。指标汇总并简化了复杂信息，因此可能会丢失影响其可靠性和解释的基础信息（例如，数据的可变性和指标值的不确定性）。交流不确定性对于确保稳健的决策和限制对趋势的误解是必要的，但生物多样性指标中很少量化可变性和不确定性。我们制定了一份指南来表示生物多样性指标的不确定性和可变性。我们考虑了生物多样性指标的主要目的以及用于表示不确定性（标准误差、bootstrap 重采样和折刀重采样）和变异性（分位数、标准偏差、中值绝对偏差和平均绝对偏差）与区间。使用 3 个备受瞩目的生物多样性指标（红色名录指数、地球生命力指数和海洋健康指数），我们根据支持指标的公式和数据类型测试了每种间隔方法的使用、适用性和解释。这些方法揭示了截然不同的信息；指标公式和数据分布影响了每种区间方法的适用性。因为支撑每个指标的数据不是正态分布的，依赖正态性或对称分布的方法是不合适的。分位数、bootstrapping 和 jackknifing 提供了有关潜在可变性和不确定性的有用信息。我们构建了一个决策树，根据数据类型和目标，选择合适的区间方法来表示生物多样性指标的不确定性或变化。我们的指南支持生物多样性指标趋势的透明和有效沟通，以促进决策者的准确解释。