Confronting models with data: carbon-phosphorus interactions under elevated CO2 in a mature forest ecosystem (EucFACE)

The importance of phosphorus (P) in plant function and ecosystem biogeochemistry has led to the addition of P cycle processes into a range of vegetation models, but the predictions of these P-enabled models have rarely been evaluated with ecosystem-scale data. Here, we confronted eight state-of-the-art, P-enabled models with data from EucFACE, a P-limited Eucalyptus forest subject to long-term Free-Air CO₂ Enrichment. We compiled a comprehensive ecosystem P-budget under both ambient and elevated CO₂ treatment, together with the associated ecosystem carbon (C) budget, to evaluate the model prediction accuracy and the underpinning mechanisms in capturing the observed elevated CO₂ responses in this forest ecosystem. Our data synthesis show a high likelihood that trees used P efficiently, but P captured by soil microbes constrained ecosystem P recycling and availability for plant uptake. In turn, plant strategies to stimulate microbial P cycling and plant P uptake may be essential for P-limited forests to increase C sequestration with rising CO₂. Our data-model intercomparison show that the inclusion of P-cycle processes into models is necessary to more realistically simulate ecosystem function and biogeochemistry, but this enhanced capacity did not directly translate into improved prediction accuracy. In particular, the P-enabled models still over-estimated the CO₂ fertilization effect on tree growth, with models showed diverging capability to capture the observed CO₂ responses. We identify leaf-to-canopy scaling of photosynthesis, plant tissue stoichiometry, plant belowground investment and the subsequent consequence for plant-microbe interaction to be crucial areas in which models of ecosystem C-P interaction can be improved. Confronting models with experimental responses observed at EucFACE represents a valuable opportunity to improve our understanding of the C-P interaction under rising CO₂, and is an important step towards more accurate predictions of the future land C sink under climate change.