A comprehensive assessment of mangrove species and carbon stock on Pohnpei, Micronesia

Abstract

Mangrove forests are the most important ecosystems on Pohnpei Island, Federated States of Micronesia, as the island communities of the central Pacific rely on the forests for many essential services including protection from sea-level rise that is occurring at a greater pace than the global average. As part of a multi-component assessment to evaluate vulnerabilities of mangrove forests on Pohnpei, mangrove forests were mapped at two points in time: 1983 and 2018. In 2018, the island had 6,426 ha of mangrove forest. Change analysis indicated a slight (0.76%) increase of mangrove area between 1983 and 2018, contrasting with global mangrove area declines. Forest structure and aboveground carbon (AGC) stocks were inventoried using a systematic sampling of field survey plots and extrapolated to the island using k-nearest neighbor and random forest species models. A gridded or wall to wall approach is suggested when possible for defining carbon stocks of a large area due to high variability seen in our data. The k-nearest neighbor model performed better than random forest models to map species dominance in these forests. Mean AGC was 167 ± 11 MgC ha-1, which is greater than the global average of mangroves (115 ± 7 MgC ha-1) but within their global range (37–255 MgC ha-1) Kauffman et al. (2020). In 2018, Pohnpei mangroves contained over 1.07 million MgC in AGC pools. By assigning the mean AGC stock per species per area to the map, carbon stock distributions were visualized spatially, allowing future conservation efforts to be directed to carbon dense stands.

Assessment and Prediction of Sea Level and Coastal Wetland Changes in Small Islands Using Remote Sensing and Artificial Intelligence

“…The two most recent years of data available suggest that mangrove habitats may again be decreasing, almost reaching their lowest point on record once more. These findings may be compared to a recent study of Pohnpei by Woltz et al [47], which included a field survey. According to Woltz et al, Pohnpei had 6377 ha of mangrove in 1983, and the total gain over the 35 years to 2018 was 49 ha, the result of 16 ha lost, and a 65 ha gain in other locations.…”

Above-ground biomass mapping of mangrove forest using WorldView-3 imagery in Gili Lawang, Nusa Tenggara Barat

“…Therefore, this study aims to estimate the biomass content in the Gili Lawang mangrove forest using highresolution imagery and vegetation index transformation. Based on research by Woltz et al (2022) [9], WorldView-3 images can be used to classify mangrove species based on the K-Nearest Neighbor and Random Forest algorithm models. The model is used to determine training data and testing data so that the classification results can be used in mapping aboveground biomass and carbon stock.…”