Model-Based Estimation of Amazonian Forests Recovery Time after Drought and Fire Events

Evaluating Effects of Post-Fire Climate and Burn Severity on the Early-Term Regeneration of Forest and Shrub Communities in the San Gabriel Mountains of California from Sentinel-2(MSI) Images

Studying the early changes in post-fire vegetation communities may improve the overall resilience of forests. The necessity for doing so was demonstrated by the Bobcat Fire, which seriously threatened the central San Gabriel Mountains and the Angeles National Forest in California. This study aimed to monitor and quantify the effects of climatological and topographic conditions along with burn severity on early (within 1 year) post-fire forests and shrubs community regeneration. In this study, we used Sentinel-2(MSI) intensive time-series imagery (July 2020–October 2021) to make a confusion matrix combined with 389 vegetation sample points on Google Earth Pro. The overall accuracy (OA) and the Kappa coefficient, calculated from the confusion matrix, were used as evaluation parameters to validate the classification results. With multiple linear regression models and Environmental Systems Research Institute (ESRI) historical images, we analyzed the effects of climate and slope aspects on the regeneration of post-fire forest and shrub communities. We also quantitatively analyzed the regeneration rates based on five burn severity types. The results show that the normalized burning rate (NBR) was the most accurate vegetation classification indicator in this study (OA: 92.3–99.5%, Kappa: 0.88–0.98). The vegetation classification accuracy based on SVM is about 6.6% higher than K-Means. The overall accuracy of the burn area is 94.87%. Post-fire climate factors had a significant impact on the regeneration of the two vegetation communities (R2: 0.42–0.88); the optimal regeneration slope was 15–35°; and the fire severity changed the original competition relationship and regeneration rate. The results provide four main insights into the regeneration of post-fire vegetation communities: (1) climate factors in the first regenerating season have important impacts on the regeneration of forest and shrub communities; (2) daytime duration and rainfall are the most significant factors for forests and shrubs regeneration; (3) tolerable low burn severity promotes forests regeneration; and (4) forests have a certain ability to resist fires, while shrubs can better tolerate high-intensity fire ecology. This study could support the implementation of strategies for regionalized forest management and the targeted enhancement of post-fire vegetation community resilience.

Assessing the carbon capture potential of a reforestation project

The number of reforestation projects worldwide is increasing. In many cases funding is obtained through the claimed carbon capture of the trees, presented as immediate and durable, whereas reforested plots need time and maintenance to realise their carbon capture potential. Further, claims usually overlook the environmental costs of natural or anthropogenic disturbances during the forest’s lifetime, and greenhouse gas (GHG) emissions associated with the reforestation are not allowed for. This study uses life cycle assessment to quantify the carbon footprint of setting up a reforestation plot in the Peruvian Amazon. In parallel, we combine a soil carbon model with an above- and below-ground plant carbon model to predict the increase in carbon stocks after planting. We compare our results with the carbon capture claims made by a reforestation platform. Our results show major errors in carbon accounting in reforestation projects if they (1) ignore the time needed for trees to reach their carbon capture potential; (2) ignore the GHG emissions involved in setting up a plot; (3) report the carbon capture potential per tree planted, thereby ignoring limitations at the forest ecosystem level; or (4) under-estimate tree losses due to inevitable human and climatic disturbances. Further, we show that applications of biochar during reforestation can partially compensate for project emissions.