Abstract

Highlights What are the main findings? A 2022 leaf-miner outbreak produced the strongest EVI decline in forests over 20 years. Nothofagus obliquaPhenological anomalies coincided with larval development and persisted across two growing seasons. What are the implications of the main findings? Linking satellite phenology with insect life cycles improves attribution of biotic forest disturbances. The approach enables scalable early detection of native insect outbreaks using time-series remote sensing.Highlights What are the main findings? A 2022 leaf-miner outbreak produced the strongest EVI decline in forests over 20 years. Nothofagus obliquaPhenological anomalies coincided with larval development and persisted across two growing seasons. What are the implications of the main findings? Linking satellite phenology with insect life cycles improves attribution of biotic forest disturbances. The approach enables scalable early detection of native insect outbreaks using time-series remote sensing.Abstract Nothofagus obliqua forests in south-central Chile are increasingly threatened by outbreaks of a native leaf-miner complex, dominated by the moth Heterobathmia pseuderiocrania. Despite the high ecological and economic value of these forests, landscape-scale monitoring of forest-insect interactions remains limited, particularly regarding the attribution of phenological anomalies to biotic disturbances. This study aimed to detect and quantify the late-2022 outbreak and evaluate its effects on Land Surface Phenology (LSP), addressing signal attribution challenges associated with remote-sensing-based monitoring of insect defoliation. Using MODIS Enhanced Vegetation Index (EVI) time series (2003-2024), Seasonal-Trend decomposition (STL) was applied to isolate long-term trend anomalies. An EVI condition index was developed to compare 2022-2023 observations against a historical baseline, and synchrony between vegetation condition loss and larval developmental phases was assessed. Additionally, Highest Density Regions (HDR) were used to quantify the statistical probability of spectral anomalies. Results revealed a sharp decline in EVI trend during late 2022, reaching the lowest recorded value in the 20-year time series. Phenological decoupling began in November, coinciding with larval development and peak defoliation, with impacts extending across two growing seasons. Ecosystem condition declined to a minimum of 42%, falling with the 4% historical probability region. Notably, exceptional pre-outbreak vigor (160% condition) preceded the disturbance. By integrating spectral anomaly detection with insect life-cycle dynamics, this multi-layered approach strengthens biotic disturbance attribution and provides a scalable framework for remote forest health monitoring. The findings also address key knowledge gaps in Southern Hemisphere Forest entomology and improve early detection strategies for native insect outbreaks.