Land surface phenology is a key indicator for monitoring the effects of climate change on vegetation, notably droughts and heatwaves. This research characterizes phenological patterns within Mediterranean-type ecosystems in Chile, highlighting their strong associations with vegetation growth forms and dominant species composition.
The study is conducted in Mediterranean-type ecosystems located in central Chile.
We used remote sensing phenological data derived from MODIS vegetation index time series and applied unsupervised machine learning clustering algorithms to identify ecosystem functional types (EFTs) within the Mediterranean-type ecosystem in Chile. Ordination analyses were employed and indicator species were identified to elucidate the relationships between EFTs, vegetation growth forms, and species composition, using land cover maps and vegetation cadastre data.
We identified nine distinct EFTs that exhibited a strong correlation with vegetation growth forms and composition diversity across the study region. Southern forests, primarily dominated by deciduous tree communities of the Nothofagus genus, displayed the highest productivity values and a delayed productivity season. Meanwhile, early-season onset was observed in areas with sclerophyll-type species like Quillaja saponaria, Cryptocarya alba, and Lithraea caustica. Xerophytic shrub communities, composed of Trevoa trinervis, Colliguaja odorifera, and Baccharis spp., exhibited high variation and early-season onset. These findings contribute to reporting changes within different conservation units present in the study area.
Evaluating greenness-based vegetation phenology provides insights into vegetation growth forms as well as richness and abundance of dominant species. Remote sensing and modern algorithms enable high-resolution monitoring of greenness variability, supporting effective management in a rapidly changing environment. This integrated approach uncovers links among ecosystem attributes and offers a valuable tool to assess environmental impacts, thereby guiding conservation and management decisions.