One to rule them all? Assessing the performance of sustainable forest management indicators against multitaxonomic data for biodiversity conservation

Abstract

Several regional initiatives and reporting efforts assess the state of forest biodiversity through broad-scale indicators based on data from national forest inventories. Although valuable, these indicators are essentially indirect and evaluate habitat quantity and quality rather than biodiversity per se. Therefore, their link to biodiversity may be weak, which decreases their usefulness for decision-making. For several decades, Forest Europe indicators assessed the state of European forests, in particular their biodiversity. However, no extensive study has been conducted to date to assess their performance - i.e. the capacity of the indicators to reflect variations in biodiversity - against multitaxonomic data. We hypothesized that no single biodiversity indicator from Forest Europe can represent overall forest biodiversity, but that several indicators would reflect habitat quality for at least some taxa in a comprehensive way. We tested the set of Forest Europes indicators against the species richness of six taxonomic and functional groups across several hundreds of sampling units over Europe. We showed that, while some indicators perform relatively well across groups (e.g. deadwood volume), no single indicator represented all biodiversity at once, and that a combination of several indicators performed better. Forest Europe indicators were chosen for their availability and ease of understanding for most people. However, we showed that gaps in the monitoring framework persist, and that surveying certain taxa along with stand structure is necessary to support policymaking and tackle forest biodiversity loss at the large scale. Adding context (e.g. forest type) may also contribute to increase the performance of biodiversity indicators. Impact statementBiodiversity indicators used to assess the state of Europes forests perform unequally; a combination of indicators is more informative