EGU24-15620, updated on 09 Mar 2024
https://doi.org/10.5194/egusphere-egu24-15620
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Tuesday, 16 Apr, 14:45–14:55 (CEST)
 
Room 2.23

Forestline detection and treeline ecotone dynamics in the Italian Alps and Apennines by satellite remote sensing

Lorena Baglioni1, Donato Morresi2, Enrico Tonelli1, Emanuele Lingua3, Raffaella Marzano2, and Carlo Urbinati1
Lorena Baglioni et al.
  • 1Department of Agricultural, Food and Environmental Sciences, Marche Polytechnic University, Ancona, Italy (lorena.baglioni@pm.univpm.it)
  • 2Department of Agricultural, Forest and Food Sciences, University of Turin, Turin, Italy
  • 3Department of Land, Environment, Agriculture and Forestry, University of Padova, Padua, Italy

Treelines are dynamic ecotones largely influenced by climate and land use changes. The increasing development of remote sensing techniques and the interest on the ecological effects of global warming on forest vegetation have raised the number of treeline studies.

The aims of this study were: i) to define an automatic approach for mapping the current position of the upper forestlines in the Italian Alps and Apennines and ii) to locate hotspots of long-term vegetation dynamics using Landsat-based spectral trend analysis. Hotspots will serve us to analyse the ecological drivers of vegetation change and to predict future vegetation dynamics.

We used the Tree Cover Density (TCD) dataset (Copernicus Land Monitoring Service) and a nationwide digital elevation model to define the polylines representing the forestlines for the reference year 2018. We used the main Italian mountain peaks, extracted from the Global Mountain Biodiversity Assessment (GMBA) dataset polygons, as reference points to detect only the upper forest ecotones based on the elevation difference between peaks and forest pixels. We defined our study areas by applying a positive and negative buffer around the forestlines and we calculated several spectral vegetation indices (e.g. NDVI, EVI, Tasseled Cap Angle) from Landsat timeseries of the last 40 years. In this way, we inferred inter-annual vegetation dynamics, discriminating two sub-areas of interest: the closed forest (below the current forestline) and the upper treeline ecotone (above the current forestline). It should be noted that on the Alps, treelines mainly host conifer species, whereas on the Apennines, broadleaf species (mostly European beach) prevail. We tested the significance of long-term spectral trends through a Mann-Kendall test for monotonicity that accounted for autocorrelation in space and time.

An important outcome of the study was to set up a replicable and unsupervised method to enhance the study of vegetation dynamics at treeline ecotones. This approach will allow the delimitation of the forestlines on a global scale and an ecologically sound comparison between different treeline ecotones. This study is the first step in a nationwide project and will provide the basis for future local-scale investigations of treeline ecotones.

How to cite: Baglioni, L., Morresi, D., Tonelli, E., Lingua, E., Marzano, R., and Urbinati, C.: Forestline detection and treeline ecotone dynamics in the Italian Alps and Apennines by satellite remote sensing, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15620, https://doi.org/10.5194/egusphere-egu24-15620, 2024.