Abstract ID: 3.11077 | Accepted as Talk | Talk | TBA | TBA

The Gran Paradiso National Park (GPNP), Western Italian Alps, is the oldest National Park in Italy and extends over about 710 square km with an elevation range between 800 and 4,061 m a.s.l. The Park, created in 1922 for the conservation of the Alpine ibex (Capra ibex) and its habitat, is characterized by a high bio- and geodiversity and hosts open semi-natural areas resulting from centuries of human activity. At high elevations, grasslands forage alpine ungulates, provide the support system to pastoralism, act as regulators of the hydrological cycle and have a fundamental role in the nutrient and carbon cycling. To understand the dynamics of Alpine grasslands and to explore the impact of the ongoing climate change on the Park’s habitats, which is part of the European LTER network, IGG-CNR started a long-term monitoring programme of the water and carbon dioxide fluxes in the Nivolet plain (2,600-2,800 m a.s.l.). Since 2016, Gross Primary Production (GPP), Ecosystem Respiration (ER), Net Ecosystem Exchange (NEE=GPP-ER) and Evapotranspiration (ET) have been measured at the interface between soil, vegetation and atmosphere using portable flux chambers. Four sites, characterized by soils with different bedrock, elevation and aspect have been identified within the Nivolet plain to study the spatial and temporal variability of the fluxes. An eddy covariance station, affiliated to the ICOS network as Associated station (IT-NIV) has been installed at one of these sites in 2018. Since 2020, two automated chambers were also installed at the same site. The flux monitoring is complemented with measurements of meteoclimatic variables and ecological descriptors that allowed for the study of flux drivers via multi-regressions models of GPP, ER and ET. The different measurement methods were combined to build a robust framework for describing flux patterns across scales, from small-scale variability obtained with chamber method, to site-scale patterns provided by the eddy covariance method, and landscape-scale estimates that include in-situ and satellite-derived information. Such monitoring and modelling efforts can inform the identification of threats to Alpine grasslands, as well as efficient conservation and management strategies.