Final Report Summary - FORESTPRIME (Predicting carbon release from forest soils through priming effects: a new approach to reconcile results across multiple scales)
The project ‘ForestPrime’ aimed to improve our understanding of soil carbon storage in forest ecosystems by filling critical knowledge gaps about plant-soil interactions. One of the challenges to this area of research is that mechanisms are studied under highly controlled conditions in the laboratory, whereas ecosystem processes are studied in large plots in the field. We tackled this challenge by conducting experiments at different scales in temperate and tropical forest, from small-scale lab incubations to large-scale field studies. We measured CO2 release from the soil (soil respiration) and changes in soil carbon and nutrients in response to experimental amendments of plant litter inputs at all scales. This approach revealed novel insights about the role of plant-soil interactions in carbon storage and allowed us to determine the extent to which the results of controlled laboratory experiments are representative of processes in the field. The research team also developed several other new approaches to overcome methodological constraints, which are now being used by researchers working on other projects.
Our results demonstrate that, despite major differences in climate and growth rates between tropical forest and temperate woodland, the response of the soil to altered plant litter inputs was largely consistent, and the magnitude of the response depended on the speed at which microbial decomposers were able to process the extra carbon. However, although additional litter inputs increase the overall amount of carbon stored in the soil, much of extra carbon was immediately available to microbes and highly susceptible to disturbance. By conducting experiments at different scales, we demonstrated that the results of lab experiments are not representative of field processes – even when the experimental treatments and measurements are directly comparable. The data from the project are currently being used to create models as a first step to overcoming this important issue.