Monitoring immediate post-fire vegetation dynamics of tropical mountain grasslands using phenocameras

Abstract

The growing incidence of uncontrolled wildfires all over the globe has called for urgent close monitoring of fire events, awareness, prevention, and management approaches. Phenocameras, ground sensors for monitoring plant phenology by taking sequential RGB digital images, can be an accessible and accurate tool for identifying, monitoring, and analyzing fire events and vegetation recovery. Here, we evaluated the application of an RGB camera system as a methodological approach to monitor and assess the post-fire recovery of a tropical mountain grasslands, the Brazilian campo rupestre. Using camera-derived vegetation indices, we investigated the immediate post-fire regrowth, and short-term post-fire leafing among four vegetation types: wet grassland, peatbog, stony grassland, and rocky outcrop. We recorded significant variations in the post-fire recovery among the grassy vegetation types. The results indicated that fire represents an important driver of leafing dynamics by shortening the length of post-fire growing seasons. The phenological metric of growing season length (GSL) indicated a full post-fire ecosystem recovery in the third year after the fire. The green-up index represented well the dynamics of post-fire vegetation regrowth and recovery across the landscape. Phenocameras rapidly detected fire occurrence and post-fire vegetation responses across vegetation types, demonstrating their significant application in the fire ecology of grassy ecosystems. The accessible, low-cost, and easy-to-setup camera system allows the application of near-remote phenology as a monitoring system and an indicator of vegetation recovery, which may improve restoration and management plans, promoting the conservation of the highly diverse campo rupestre grassland ecosystems.