Natural zonal vegetation of the Azores Islands: characterization and potential distribution
Date
2016Abstract
Aims: To present a statistically based classification of Azorean natural zonal vegetation; (2) to characterize
the main features of this vegetation and (3) to present the first model of its potential distribution in the nine
Azorean Islands. Study area: Azores (São Miguel, Pico, Terceira and Flores islands). Methods: Information
from 139 plots set up in the best preserved vegetation patches was used. Ward’s agglomerative clustering method
was applied in order to identify community types. Potential distribution of these community-level entities
was modeled in relation to climatic predictors, using MAXENT. Results: Eight vegetation belts were identified:
Erica-Morella Coastal Woodlands, Picconia-Morella Lowland Forests, Laurus Submontane Forests, Juniperus-
Ilex Montane Forests, Juniperus Montane Woodlands, Calluna-Juniperus Altimontane Scrublands, Calluna-
Erica Subalpine Scrublands and Calluna Alpine Scrublands. Modeling results suggest that
Picconia-Morella and Laurus forests (Laurel forests) are the potential dominant vegetation in the Azores. With
the possible exception of Juniperus woodlands, Pico could have all vegetation types, in contrast with Santa
Maria, Graciosa and Corvo with only three. Conclusions: Most of Azorean natural vegetation has been transformed
or degraded by human action, with a greater impact on Laurel forests. The best preserved vegetation
belts are located above 600 m a.s.l., including Juniperus-Ilex Forests and Juniperus Woodlands, perhaps the only
example of island montane cloud forests existing outside the tropics. In the present work, for the first time we
used a statistical method to classify zonal vegetation, gave it a bioclimatic foundation and applied it to the whole
archipelago, thus defining and describing the main vegetation belts of the Azores. This work also gives the first
potential distribution maps of the zonal vegetation for each island. This information may be used for landscape
planning and management, selection of sites and species for ecological restoration and evaluation of climate
change effects.