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Carbon-phosphorus cycle models overestimate CO 2 enrichment response in a mature Eucalyptus forest.

Mingkai JiangBelinda E MedlynDavid WårlindJürgen KnauerKatrin FleischerDaniel S GollStefan OlinXiaojuan YangLin YuSönke ZaehleHaicheng ZhangHe LvKristine Y CrousYolima CarrilloCatriona A MacdonaldIan C AndersonMatthias M BoerMark FarrellAndrew N GherlendaLaura Castañeda-GómezShun HasegawaKlaus A JaroschPaul James MilhamRaul Ochoa-HuesoVarsha S PathareJohanna PihlbladJuan Piñeiro NevadoJeff R PowellSally A PowerPeter B ReichMarkus RieglerDavid S EllsworthBenjamin Smith
Published in: Science advances (2024)
The importance of phosphorus (P) in regulating ecosystem responses to climate change has fostered P-cycle implementation in land surface models, but their CO 2 effects predictions have not been evaluated against measurements. Here, we perform a data-driven model evaluation where simulations of eight widely used P-enabled models were confronted with observations from a long-term free-air CO 2 enrichment experiment in a mature, P-limited Eucalyptus forest. We show that most models predicted the correct sign and magnitude of the CO 2 effect on ecosystem carbon (C) sequestration, but they generally overestimated the effects on plant C uptake and growth. We identify leaf-to-canopy scaling of photosynthesis, plant tissue stoichiometry, plant belowground C allocation, and the subsequent consequences for plant-microbial interaction as key areas in which models of ecosystem C-P interaction can be improved. Together, this data-model intercomparison reveals data-driven insights into the performance and functionality of P-enabled models and adds to the existing evidence that the global CO 2 -driven carbon sink is overestimated by models.
Keyphrases
  • climate change
  • human health
  • primary care
  • microbial community
  • risk assessment
  • machine learning
  • big data