Comparing mean species abundance and the biodiversity intactness index to guide robust biodiversity investment decisions

1. Mean species abundance (MSA) and the biodiversity intactness index (BII) are two leading biodiversity metrics used to quantify how species composition differs between a control site and an impacted site. Both are proposed for global biodiversity monitoring, are used by companies to create corporate biodiversity impact accounts, and are being considered by financial institutions seeking to integrate biodiversity into investment decisions. Understanding the extent to which MSA and BII are interchangeable is therefore essential for assessing whether valid comparisons can be made across companies reporting different metrics. At a market level, comparability determines whether investments are steered towards similar sets of companies: if metrics are poorly comparable, they may create confused or conflicting incentives for reducing biodiversity impact. 2. We assess the comparability of the metrics by: (i) deriving mathematical conditions under which they are equal; (ii) examining their parameter sensitivity using simulated communities; and (iii) applying them to the same real dataset. 3. We find that comparability increases with higher species evenness and total abundance in control communities, but decreases with increasing species richness. Rank correlation between the metrics is strongest at sites where species richness increases, total abundance declines, and evenness remains high or decreases slightly between control and impacted sites. Conversely, correlation is weakest when richness declines from high to intermediate levels and total abundance increases, with no consistent direction of change in evenness. Across biogeographic realms, the metrics generally show strong rank correlation. 4. Overall, across real and simulated data, we find that MSA and BII produce broadly comparable rankings of sites, but the magnitudes of the metrics often differ substantially for any given site. On this basis, companies, financial institutions, and standard-setters can use either metric, but direct numerical comparison between them is rarely appropriate, requiring the consistent use of one metric. To support metric selection, we outline the contexts and business–biodiversity framings in which each metric is most suitable.