The serious loss of mangrove forest over the largest delta of Africa, Niger Delta: causes and reasons

Diankai Wang, Zhijun Dai, Chuqi Long, Xixing Liang, Yuan Xiong, Jinping Cheng

Research output: Contribution to journalArticlepeer-review

Abstract

While global mangrove forests have suffered significant loss, raising widespread concern, little information is available on how mangrove forests have changed along Africa's coast. This study employed multi-temporal remote sensing data and machine learning techniques between 1988 and 2023 to assess the spatiotemporal changes in mangrove forests cover across the Niger Delta, Africa's largest delta. This results indicated a decreasing trend in mangrove area within the Niger Delta, with a total loss of 2536 km2 over the past 38 years, leaving 7058 km2 by 2023. The mangrove forests have become increasingly interiorly fragmented while retreating landward at an average rate of 13.58 m per year. Spatially, mangrove distribution remains concentrated in estuarine extensions, with most retreat occurring at mangrove edges. The intensification of oil spills and urban expansion likely contribute to the internal degradation within the Niger Delta's mangrove forests, of which 54.27 % of the mangrove loss may have been caused by oil spills. Meanwhile, high-energy waves are the primary driver of edge erosion, and variations in wave energy result in a gradual slowdown of the landward retreat of mangrove boundaries-from the central Arcuate Niger Delta toward its flanking regions. Furthermore, increased sediment discharge from river into coastal waters enhances mangrove expansion in estuarine zones, and accelerating sea-level rise presents a growing threat to mangrove sustainability. The findings provide critical insights into the drivers of mangrove gain and loss, offering actionable guidance for optimizing global mangrove conservation and restoration strategies.

Original languageEnglish
Article number107350
JournalMarine Environmental Research
Volume210
DOIs
StatePublished - Sep 2025

Keywords

  • Gain and loss
  • Machine learning technique
  • Mangrove forest
  • Niger delta
  • Oil spills

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