The Living Planet Index's ability to capture biodiversity change from uncertain data

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.

Automated summary

The Living Planet Index (LPI) is a crucial tool for tracking global biodiversity change. However, it sacrifices information to summarize population trends into a single index. Evaluating the impact of this information loss is important to ensure the index reflects the truth. The study analyzed uncertainty propagation in the LPI and found that measurement and process uncertainty consistently biased the index below the true trend, particularly when populations are small. These findings highlight the importance of considering variability and covarying populations in assessing population change trends for a more accurate LPI.