Revealing post-megafire spectral and compositional recovery in the Siberian boreal forest using Landsat time series and regression-based unmixing approach

Abstract

Megafires trigger abrupt ecosystem changes and may lead to alternative successional pathways, thereby undermining the recovery and resilience of forests. However, comprehensive multi-perspective assessments of post-megafire forest recovery remain limited. In this study, we assessed short- and long-term spectral and compositional recovery following the 1987 Black Dragon Megafire in the Siberian boreal forest of Northeast China. We first disentangled continuous fractions of five forest cover types for eight time periods between 1987 and 2022 utilizing Landsat time series and regression-based unmixing approach. Machine learning regression models (support vector regression (SVR), random forest regression (RFR), and light gradient boosting machine regression (LGBMR)) were trained using synthetically mixed datasets generated from the Landsat spectral library. Independent accuracy assessment indicated that LGBMR outperformed SVR and RFR, with mean absolute errors ranging from 6.87% to 10.04% across five cover types, suggesting the effectiveness of the unmixing approach for mapping forest cover type fractions in the Siberian boreal forest. We then assessed post-megafire spectral and compositional recovery of forests using forest cover type fractions and spectral indices across different levels of burn severity. The short-term assessment indicated rapid spectral recovery rates dominated by shrubs and deciduous broadleaved forests, especially in high severity areas. Over the long-term scale, the spectral recovery required 15–16 years to return to pre-fire baselines, surpassing the rate of compositional recovery. Recovery rates were significantly faster for broadleaved forests compared to needleleaved forests, resulting in mixed forests in low-severity areas and a predominance of broadleaved forests in high-severity areas. Our findings indicated that megafires catalyzed a shift from needleleaved to broadleaved forests in the Siberian boreal forest, suggesting lower resilience of these forests to high-severity megafires. This study offers valuable insights into the profound and enduring effects of catastrophic events such as megafires on the recovery and resilience of boreal forests, and informs restoration and adaptation efforts thereafter.