Remote sensing applications for managing a large-scale restoration dynamics project throughout the City of Gold Coast conservation estate

Abstract

The City of Gold Coast established a program to restore native forests throughout the conservation estate (∼13,789 ha) utilizing constructed (CNR), assisted (ANR), and unassisted natural regeneration (UNR). Each year the city maintains over 4000 Ha of restoration works. The program is supported by an environmental decision support tool (oRestore) for the smart allocation of restoration funds over space and time (see [1] for details). We introduce the Restoration Dynamics Project, a quantitative evidence-based evaluation of the success of restoration actions undertaken between 2005 and 2022. Based on 17 restoration work areas (historically pasture dominated by exotic grasses, and open eucalypt forest vegetation (preclearing Regional Ecosystem 12.11.3), we compared optical and LiDAR vegetation metrics with field BioCondition assessments. UNR is suppressed by the presence of weed species that dominate cleared areas, resulting in low BioCondition. Unassisted, weeds can persist for decades, and intervention (ANR) is required for the recovery of native vegetation. CNR (tree-planting) provides canopy cover, however, lacks species diversity in the shrub layer. Assisted NR (controlling invasive species) is optimal for maximizing biodiversity in open eucalypt forests. LiDAR analytics can be a surrogate for BioCondition however field surveys are needed to determine non-native plant cover.