Département de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada.
Québec Centre for Biodiversity Science, Montréal, Québec, Canada.
Ecology. 2023 Jun;104(6):e4044. doi: 10.1002/ecy.4044. Epub 2023 Apr 11.
The Living Planet Index (LPI) is a crucial tool to track global biodiversity change, but necessarily sacrifices information to summarize thousands of population trends into a single communicable index. Evaluating when and how this information loss affects the LPI's performance is essential to ensure interpretations of the index reflect the truth as reliably as possible. Here, we evaluated the ability of the LPI to accurately and precisely capture trends of population change from uncertain data. We derived a mathematical analysis of uncertainty propagation in the LPI to track how measurement and process uncertainty may bias estimates of population growth rate trends, and to measure the overall uncertainty of the LPI. We demonstrated the propagation of uncertainty using simulated scenarios of declining, stable, or growing populations fluctuating independently, synchronously, or asynchronously, to assess the bias and uncertainty of the LPI in each scenario. We found that measurement and process uncertainty consistently pull the index below the expected true trend. Importantly, variability in the raw data scales up to draw the index further below the expected trend and to amplify its uncertainty, particularly when populations are small. These findings echo suggestions that a more complete assessment of the variability in population change trends, with particular attention to covarying populations, would enrich the LPI's already critical influence on conservation communication and decisions.
生命星球指数(LPI)是追踪全球生物多样性变化的重要工具,但为了将数千个人口趋势汇总为一个可传播的指数,它必然会牺牲一些信息。评估这种信息损失何时以及如何影响 LPI 的性能对于确保对该指数的解释尽可能可靠地反映事实至关重要。在这里,我们评估了 LPI 从不确定数据中准确和精确捕捉人口变化趋势的能力。我们推导出了 LPI 中不确定性传播的数学分析,以跟踪测量和过程不确定性如何可能使人口增长率趋势的估计产生偏差,并衡量 LPI 的总体不确定性。我们使用独立、同步或异步波动的下降、稳定或增长的模拟场景来演示不确定性的传播,以评估 LPI 在每种情况下的偏差和不确定性。我们发现,测量和过程不确定性始终使指数低于预期的真实趋势。重要的是,原始数据的可变性会增加,从而使指数进一步低于预期趋势,并放大其不确定性,尤其是当种群较小时。这些发现呼应了这样一种观点,即更全面地评估人口变化趋势的可变性,特别关注相互关联的种群,将丰富 LPI 对保护沟通和决策的已有重要影响。