Cycling of carbon and water in mountain ecosystems under changing climate and land use (CYCLAMEN)

Land ecosystems presently sequester around 25% of the carbon dioxide (CO2) that is emitted into the atmosphere by human activity and thus, along with the oceans (absorbing a similar fraction), slow down the increase of atmospheric CO2. Whether land ecosystems will be able to continue to sequester atmospheric CO2 at similar rates in the future or whether carbon cycle-climate feedbacks will cause the land sink to saturate or even turn into a source, is a topic of controversial discussion. While taking up CO2 through the stomata, plants inevitably lose water through transpiration. Terrestrial evapotranspiration (ET) can have a feedback to (local) precipitation and therefore modulate near-surface climate. The terrestrial carbon and water cycles are highly connected and controlled by complex interactions between biological and abiotic drivers. Mountain ecosystems in the European Alps are a hot spot of climate and land-use changes. Over the last century, temperatures have increased in the region with a rate double that of the global average and are expected to rise rapidly. In addition, precipitation changes are highly complex with an increasing and a decreasing trend in the northern and southern Alps, respectively and different seasonal patterns. Socio-economic development in the Alps during the past centuries have caused large-scale changes in land-use and its intensity, which has contributed to the uncertainty about future land-atmosphere interactions. The objective of the CYCLAMEN project is to quantify and project the resilience and vulnerability of carbon and water cycling in North and South Tyrol. We aim at providing information for predicting likely future changes in climate and land-use over the region.

In the study we used a comprehensive and multidisciplinary approach to model biosphere-atmosphere interactions in the Alps. Data from eddy covariance stations spread across the region were chosen to test and calibrate the biosphere model SiB4. The meteorological data from the same stations was used to train a stochastic Weather Generator and simulate weather conditions under climate scenarios RCP8.5 and RCP2.6 until 2100. To account for future land- use/ land- cover (LULC) changes the SPA-LUCC model was used. Both the simulated weather conditions and the expected LULC were fed back to the SiB4 model to calculate ecosystem parameters, including carbon dioxide net ecosystem exchange and evapotranspiration. In parallel, an enhanced thermal remote sensing dataset was produced, specifically adapted for mountainous areas. This dataset will be the main driver for modelling ET with an energy balance model whose output will be cross compared with the one of the biosphere model SiB4.