What frequency and scale of monitoring is needed to reliably report on the Ne 500 indicator: a test using simulations

Biodiversity indicators need to be reliable if they are to shape policy, conservation, management, and ultimately the future of our planet. An indicator can be considered reliable if it detects and summarizes biodiversity trends accurately, precisely, and without bias. However, the performance of genetic diversity indicators has not yet been robustly quantified. Here, we address this gap by testing the performance of one of the KMGBF indicators for genetic diversity, the Headline Indicator A.4 “Proportion of populations with an effective size greater than 500 (Ne > 500)” using simulations and subsampled real data.  We focus on the scenario in which census size, Nc, is used as a proxy for Ne (we only simulate demography, not DNA-based data).

We show that this indicator can be reliably measured under realistic population trends, monitoring intervals, and observer error. Performance is consistently high for both declining and increasing populations, and across different levels of national investment in population recovery. Our results suggest the following guidelines for KMGBF monitoring of this indicator: assess populations every 1–4 years, monitor at least 40–60% of populations per species, and include at least 8% of species when species pools contain several thousand taxa, increasing up to 56% when species pools contain fewer than 100 taxa.

These findings show that the Headline Indicator A.4 is feasible and technically reliable under realistic scenarios of biodiversity change and on-the-ground monitoring constraints. Beyond this individual indicator, we emphasize the need for performance testing of additional metrics to ensure trust in monitoring and reporting progress toward KMGBF targets and the goal of halting biodiversity loss. The model we present - using simulated and real data under realistic biodiversity trends, timelines, and logistical constraints (e.g., observation error, monitoring gaps) - provides a viable pathway to quantify indicator reliability and strengthen confidence of policymakers, conservationists, and businesses investing in biodiversity restoration.