AI-assisted event-dating of invasive transitions in Galápagos agroecosystems: Disentangling climate triggers and landscape susceptibility using Satellite Imagery and Bayesian–ML

In the Galapagos Archipelago, agricultural abandonment and biological invasions act as synergistic forces, creating "novel ecosystems" that threaten both endemic biodiversity and local food security. While historical land cover changes are well-documented, the mechanisms determining when and where productive land is lost to invasion remain obscured by complex interactions between climatic legacies and anthropogenic pressure. This study presents a unified spatiotemporal framework to assess the susceptibility of island agroecosystems to three critical transitions: agricultural abandonment, invasive species expansion, and invasive conversion (die-back).

We integrated dense Sentinel-1 SAR time-series (2018–2024) with high-resolution climatic variables (CHIRPS/TerraClimate) across the agricultural highlands (≈25,000 ha). Our hybrid workflow fuses satellite event-dating (Vertex AI + PELT) with epidemiological Case-Crossover designs to pinpoint specific climatic triggers, followed by Bayesian Spatial Modeling (R-INLA) and Random Forest classifiers to map landscape susceptibility.

Our results reveal distinct spatiotemporal fingerprints with direct implications for farm management. Temporally, agricultural abandonment is triggered by persistent drought stress (longer dry spells); spatially, risk is critically clustered in Silvopasture and Mixed Forest zones, identifying these productive assets as "stepping stones" to total land abandonment. Conversely, invasive expansion exhibits a "Rainfall Paradox": it is primed by short-term wetting pulses, while spatially, the models detect a process of "densification" within existing patches rather than purely frontier expansion. Finally, invasive retreat (die-back) is linked to extreme wet spikes and heat interaction, and is spatially confined to high-elevation climatic niches, supporting the "Environmental Filtering" hypothesis where native resilience limits invasive establishment.

By coupling AI-driven event detection with physics-aware spatial statistics, we demonstrate that invasive dynamics are pulsed by climate "windows of opportunity." The resulting risk maps provide a dual-purpose baseline for the Galapagos National Park and the Ministry of Agriculture, facilitating targeted interventions to protect native ecosystems while reinforcing the resilience of farming systems against climatic shocks.