Chile’s temperate forest is a global biodiversity hotspot. An upsurge in alien forest plantations has disturbed and fragmented the landscape, promoting biological invasions. The invasion process is not fully understood since monitoring large and inaccessible areas can be prohibitively expensive and logistically challenging using field-based methods alone. Here, a remote sensing approach using Sentinel-2 satellite imagery, fragmentation analysis, and random forest modelling is applied to detect alien tree stands and describe their extent in relation to fragmentation and landscape structure in study areas around Malalcahuello National Reserve and Villarrica National Park. Detailed vegetation maps are produced, with classification accuracies >81% and including four forest classes, two native and two alien. An altitudinal pattern was observed in both sites. At lower altitudes, there was greater total area covered by alien trees and more fragmented native forests than at higher altitudes. However, Villarrica had less alien tree cover than Malalcahuello, but was a more fragmented landscape. Random forest modelling identified that alien pine tree mean patch area was positively correlated with both land cover diversity and Araucaria araucana forest mean patch area in both sites. Given their conservation and cultural relevance, the locations of protected areas need reconsidering to strengthen the protection of A. araucana, which could be outcompeted by alien trees in a context of increasing productive forestry. This is especially urgent in Villarrica, where protected areas already have a substantial presence of alien trees, with most A. araucana found outside protected areas.
- Alien species
- temperate forests
- random forests
- land cover
MARTIN GALLEGO, MARIA. DEL. PILAR., APLIN, PAUL., MARSTON, CHRISTOPHER., Altamirano, A., & Pauchard, A. (2020). Detecting and modelling alien tree presence using Sentinel-2 satellite imagery in Chile’s temperate forests. Forest Ecology and Management, 474, . https://doi.org/10.1016/j.foreco.2020.118353