The synergic influence of land use and climate change on future forest dynamics is hard to disentangle, especially in human-dominated forest ecosystems. Forest gain in mountain ecosystems often creates different spatial–temporal patterns between upper and lower elevation belts. We analyzed land cover dynamics over the past 50 years and predicted Business as Usual future changes on an inner subalpine watershed by using land cover maps, derived from five aerial images, and several topographic, ecological, and anthropogenic predictors. We analyzed historical landscape patterns through transition matrices and landscape metrics and predicted future forest ecosystem change by integrating multi-layer perceptron and Markov chain models for short-term (2050) and long-term (2100) timespans. Below the maximum timberline elevation of the year 1965, the dominant forest dynamic was a gap-filling process through secondary succession at the expense of open areas leading to an increase of landscape homogeneity. At upper elevations, the main observed dynamic was the colonization of unvegetated soil through primary succession and timberline upward shift, with an increasing speed over the last years. Future predictions suggest a saturation of open areas in the lower part of the watershed and stronger forest gain at upper elevations. Our research suggests an increasing role of climate change over the last years and on future forest dynamics at a landscape scale.

Land Use Modeling Predicts Divergent Patterns of Change Between Upper and Lower Elevations in a Subalpine Watershed of the Alps

Anselmetto N.
First
;
Meloni F.;Garbarino M.
Last
2022-01-01

Abstract

The synergic influence of land use and climate change on future forest dynamics is hard to disentangle, especially in human-dominated forest ecosystems. Forest gain in mountain ecosystems often creates different spatial–temporal patterns between upper and lower elevation belts. We analyzed land cover dynamics over the past 50 years and predicted Business as Usual future changes on an inner subalpine watershed by using land cover maps, derived from five aerial images, and several topographic, ecological, and anthropogenic predictors. We analyzed historical landscape patterns through transition matrices and landscape metrics and predicted future forest ecosystem change by integrating multi-layer perceptron and Markov chain models for short-term (2050) and long-term (2100) timespans. Below the maximum timberline elevation of the year 1965, the dominant forest dynamic was a gap-filling process through secondary succession at the expense of open areas leading to an increase of landscape homogeneity. At upper elevations, the main observed dynamic was the colonization of unvegetated soil through primary succession and timberline upward shift, with an increasing speed over the last years. Future predictions suggest a saturation of open areas in the lower part of the watershed and stronger forest gain at upper elevations. Our research suggests an increasing role of climate change over the last years and on future forest dynamics at a landscape scale.
2022
25
1295
1310
https://link.springer.com/article/10.1007/s10021-021-00716-7
alpine forest; land abandonment; land use change modeling; Markov chain; multi-layer perceptron; natural park
Anselmetto N.; Sibona E.M.; Meloni F.; Gagliardi L.; Bocca M.; Garbarino M.
File in questo prodotto:
File Dimensione Formato  
2021_anselmetto_ECOSY.pdf

Accesso aperto

Descrizione: PDF Editoriale Open Access
Tipo di file: PDF EDITORIALE
Dimensione 2.16 MB
Formato Adobe PDF
2.16 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1827829
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 5
social impact