Post-fire Pinus radiata invasion in a threatened biodiversity hotspot forest: A multi-scale remote sensing assessment

Abstract

Biological invasions are one of the most relevant factors of biodiversity loss, especially after fire disturbances. Wildfires can accelerate invasions of fire-prone species, like Pinus radiata, and dramatically alter ecosystems. However, how to assess the main impacts of this invasion process on the composition, structure, and functionality of ecosystems, including the post-fire revegetation processes, has not been fully resolved. This study aimed to evaluate the impacts of P. radiata invasion on fire-damaged forest ecosystems using combined remote sensing and in situ data, focusing particularly on changes in biodiversity, ecosystem structure, and functionality. The recovery of forest leaf area index (LAI) and the fraction of photosynthetically active radiation (FPAR) were monitored using Sentinel-2 time series products. Then the pre- and post-fire native community composition and the relationships of invasion and biodiversity with biotic and abiotic components were characterized using structural equation modeling (SEM). The postfire P. radiata density was mapped to quantify invasion intensity in three burned native forest fragments using generalized additive modeling (GAM) regressions based on UAS multispectral data. Biophysical metrics indicate that all forest fragments impacted by high, medium-high, and medium-low severity fires achieved a partial recovery of their canopy. The SEM model showed that microtopographic features and vegetation height explain native species diversity under pre-fire conditions due to their close relationship with favorable microclimatic conditions for species establishment. Vegetation height determined the abundance of P. radiata in post-fire conditions, and it negatively impacted diversity by promoting the homogenization of vegetation cover and altering diversity patterns. The general composition and abundance metrics also showed a substantial modification associated with the heavy (significant) invasion of P. radiata species. Predictive mapping of P. radiata density showed high accuracies (R2 =0.73 and explained deviation of 80%). The maps depicted an intense concentration of the invasive tree with a mean density of 76,217 individuals per ha−1 and high invasion spots with more than 176,000 individuals per ha−1. The quantification of invasion and mapping is a fundamental input for prioritizing areas and resources for a large-scale restoration program, and is a priority to avoid the loss of these highly threatened forest ecosystems.