Dynamique spatio-temporelle de la forêt de mangrove dans la province de Trat en Thaïlande

Abstract

In the United Nations 2021–2030 ecosystem restoration programme, coastal ecosystems such as mangroves are listed as a priority for biodiversity restoration. Therefore, understanding mangrove species diversity and changes over time are essential to predict ecosystem health, viability and resilience to changing climatic and human pressures. However, when considering future conservation ambitions and policies for mangroves, it is also crucial to understand the effects of conservation interventions. To address these concerns, we needed to develop reliable inventory methods for mangrove forests, spatialised predictions of biodiversity and good practices for using Earth observation data. In this study, we investigated the gaps in knowledge concerning the spatial organisation, intertidal zones and the recent history of mangroves in Thailand's Trat province. We investigated the impacts on forest diversification of environmental parameters, such as topography, and of human interventions such as stand rehabilitation or plantations. We were able to integrate historical multi-satellite data, current ecological data and micro-topographic measurements to establish the status and describe the spatial organisation of the mangrove forests in the Province of Trat. Using the method described in this study, we were able to overcome the technical limitations of monitoring protocols and thus develop a powerful decision-support system to assess the recovery period of mangrove forests, their structural growth and the species composition of plantations and natural native stands over three decades. Our study also identifies the main influencing factors that compromise the quality of Earth observation data, and proposes specific best practices for monitoring mangrove ecosystems. In addition, we developed the ARMA tool (Automatic Regrowth Monitoring Algorithm) and summarized functional indicators (secondary succession) by type of stand. ARMA can identify the years of planting, recovery period, age and structural development of rehabilitated mangroves compared to adjacent natural and naturally regenerating mangroves. We believe that our study makes a significant contribution to research on mangrove biodiversity, as it has several potential applications for forest restoration planning and management. It can therefore be a useful tool to measure and assess biodiversity and thereby improve ecosystem-based mangrove forest management.