Abstract

Keywords

soil nutrient status, ICP Forests, tree growth

Abstract

Abstract Nutrient availability influences virtually every aspect of an ecosystem, and is a critical modifier of ecosystem responses to global change. Although this crucial role of nutrient availability in regulating ecosystem structure and functioning has been widely acknowledged, nutrients are still often neglected in observational and experimental synthesis studies due to difficulties in comparing the nutrient status across sites. In the current study, we explain different nutrient-related concepts and discuss the potential of soil-, plant- and remote sensing-based metrics to compare the nutrient status across space. Based on our review and additional analyses on a dataset of European, managed temperate and boreal forests (ICP [International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests] Forests dataset), we conclude that the use of plant- and remote sensing-based metrics that rely on tissue stoichiometry is limited due to their strong dependence on species identity. The potential use of other plant-based metrics such as Ellenberg indicator values and plant-functional traits is also discussed. We conclude from our analyses and review that soil-based metrics have the highest potential for successful intersite comparison of the nutrient status. As an example, we used and adjusted a soil-based metric, previously developed for conifer forests across Sweden, against the same ICP Forests data. We suggest that this adjusted and further adaptable metric, which included the organic carbon concentration in the upper 20 cm of the soil (including the organic fermentation-humus [FH] layer), the C:N ratio and of the FH layer, can be used as a complementary tool along with other indicators of nutrient availability, to compare the background nutrient status across temperate and boreal forests dominated by spruce, pine or beech. Future collection and provision of harmonized soil data from observational and experimental sites is crucial for further testing and adjusting the metric.

LWF Classification

Network: LWF, Category: ISI,