Preprints
https://doi.org/10.5194/egusphere-2023-2824
https://doi.org/10.5194/egusphere-2023-2824
23 Jan 2024
 | 23 Jan 2024
Status: this preprint is open for discussion.

Predicting the productivity of Alpine grasslands using remote sensing information

Saverio Vicario, Marta Magnani, Maria Adamo, Gianna Vivaldo, Chiara Richiardi, Mariasilvia Giamberini, and Antonello Provenzale

Abstract. Gross primary productivity (GPP) is a crucial variable for ecosystem dynamics, and it can significantly vary on the small spatial scales of vegetation and environmental heterogeneity. This is especially true for mountain ecosystems, which pose severe difficulties to field monitoring. In addition, the specificity of such ecosystems and the extreme abiotic conditions that they experience often make global and regional models unsuited to predictions. In this case, remote sensing products offer the opportunity to explore the productivity of vegetation communities in remote areas such as Alpine grasslands all year round, and empirical models can help in the challenge of modelling Alpine GPP. Along these lines, we took a hybrid approach, blending several remote sensing data sources (such as a high-definition digital terrain model and moderate- and high- resolution satellite products such as MODIS and Sentinel 2) and gridded datasets such as ERA5 with in situ measurements to implement a specific empirical model. The resulting remote-sensing-based model developed here was suited to represent the measured primary productivity in different areas within a high-altitude grassland at the Nivolet plain, in the north-western Italian Alps at 2700–2500 m amsl. A cross-validation approach allowed us to evaluate to what extent a single empirical model could represent diverse communities and different abiotic factors found in these areas. We finally identified the ratio between MCARI2 and MSAVI2 as a good predictor of light use efficiency, a key factor in the empirical model, probably due to its good correlation with the leaves phenological status, inasmuch it estimates the ratio between chlorophyll and the ensemble of leaf pigments.

Saverio Vicario, Marta Magnani, Maria Adamo, Gianna Vivaldo, Chiara Richiardi, Mariasilvia Giamberini, and Antonello Provenzale

Status: open (until 05 Mar 2024)

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Saverio Vicario, Marta Magnani, Maria Adamo, Gianna Vivaldo, Chiara Richiardi, Mariasilvia Giamberini, and Antonello Provenzale
Saverio Vicario, Marta Magnani, Maria Adamo, Gianna Vivaldo, Chiara Richiardi, Mariasilvia Giamberini, and Antonello Provenzale

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Short summary
The high altitude Alpine grassland in Gran Paradiso National Park is a productive ecosystem key in the conservation of Alpine Ibex, in the preservation the practice transhumance relevant for alpine economy. The article develop an empirical model to robustly estimate primary productivity. In the analysis, the ratio of chlorophyll over total leaf pigments stand as a powerful addition, once climate model estimate of soil moisture fail to correctly follow real trends in the alpine valley of Nivolet.