JULIA

Joining ecophysiological Understanding and global ecosystem modelling for improved simulation of Land surface Interactions with the Atmosphere

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 Obiettivo del progetto (Objective)

'A thorough understanding of feedbacks between the terrestrial biosphere and the climate system is pivotal for any climate change mitigation strategy. Such feedbacks could significantly affect and potentially accelerate climate change. Terrestrial biosphere models are increasingly coupled interactively to ocean and atmosphere models with the goal to quantify these feedbacks. However, state-of-the-art terrestrial biosphere models fall short of the current understanding of important ecophysiological controls of land surface processes, as evidenced by the increasing amount of ecosystem observations that have become available recently. This project aims at bridging the gap between observational science and large scale biosphere modelling by developing representations of relevant ecophysiological processes at a level of detail suitable for an Earth system model. Two of the most important fields that urgently need to be better represented will be addressed, namely the biological control of canopy conductance and plant-soil interactions. Both substantially influence land surface fluxes, ecosystem productivity and long-term carbon sequestration. The project will use innovative techniques to develop novel process representations of canopy conductance by combining different types of ecosystem observations such as eddy-covariance based flux observations and plant trait data collected by the IGBP fast track initiative on plant functional types. Novel representations of soil organic matter dynamics, including a substrate control, and plant nutrient uptake pathways will be developed and evaluated based on recent laboratory and ecosystem manipulation experiments. The improved model will be used to revise predictions of state-of-the-art terrestrial biosphere models for present-day and future conditions. The project will thus provide a tool to better quantify potential future interactions of the terrestrial biosphere and the climate system for the use in coupled Earth system models.'

Descrizione progetto (Article)

State-of-the-art terrestrial biosphere models require a greater understanding of land surface processes than was previously available. The EU-funded JULIA project helped close the gap between observational science and large scale modelling of biosphere processes at a level of detail suitable for an Earth system model.

Two of the most important areas that needed to be addressed were plant-soil interactions and the facctors controlling water fluxes from tree canopies. Both fields have a significant influence on land surface fluxes, ecosystem productivity and long-term carbon sequestration. Scientists used flux measurements, plant characteristics and the outcomes of ecosystem monitoring studies to create sophisticated terrestrial computer models of the biosphere.

A particular focus of the JULIA project was the role of the nitrogen cycle in the climate system and its impact on the natural carbon cycle. In addition, JULIA assessed the impact of nitrogen from human activities on terrestrial greenhouse gas fluxes. The studies showed that greater effort is needed to mitigate climate change as the carbon sequestration capacity of the terrestrial biosphere has been previously overestimated. Furthermore, nitrogen management is important for controlling changes to the climate system resulting from human activities.

This work resulted in a series of publications on the nitrogen cycle, the modelling of plant soil interaction and the effect of drought on tree canopies. Results were incorporated into a model system that is part of the international Global Carbon Project and provides data for the Intergovernmental Panel on Climate Change (IPCC) and its Fifth Assessment Report (AR5).

The JULIA project successfully developed a tool to better quantify interactions of the terrestrial biosphere and the climate system for use in Earth system models, thereby enabling more accurate predictions to be made for future climate conditions.