Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Remote Sensing for Sustainable Wetland Management, Likouala Aux Herbes River, Lac Tele Community Reserve (LTCR), Republic of Congo

Version 1 : Received: 16 October 2023 / Approved: 17 October 2023 / Online: 19 October 2023 (03:51:06 CEST)

A peer-reviewed article of this Preprint also exists.

Ndzana Biloa, E.B.; Mamonekene, V.; Micha, J.-C. Characterization of Fish Spawning Grounds near the Likouala-Aux-Herbes River, Lac Tele Community Reserve (LTCR), Republic of Congo, for Sustainable Wetland Management. Sustainability 2024, 16, 3353. Ndzana Biloa, E.B.; Mamonekene, V.; Micha, J.-C. Characterization of Fish Spawning Grounds near the Likouala-Aux-Herbes River, Lac Tele Community Reserve (LTCR), Republic of Congo, for Sustainable Wetland Management. Sustainability 2024, 16, 3353.

Abstract

The analysis of the land use dynamics of the Lac Télé Community Reserve (RCLT) using Landsat Thematic Mapper (TM) and (Enhance Thematic Mapper) ETM+ images highlight significant changes in the vegetation cover from 1980 to 2000 and 2018. Thus, the rate of forest area decreased by 21.41% for the entire LTCR in favor of savannahs which increased by 15.23%. The conversion of this forest area to savannah due to the practice of slash and burn agriculture facilitates the opening up of the forest area and contributes to greatly degrading the spawning grounds of fish species from the Likouala aux herbes river. For the mapping of fishing activity in general and the ecological characterization of the 151 identified spawning grounds in particular; the respective mean values of the physical and chemical water parameters; temperature (28.13°C), pH (4.23) and depth (3.34) did not vary significantly from one selected village to another between July and September 2019. The fish diversity unregistered during the study, in the 07 pilot villages would be due to the diversity of the microhabitats noted in the villages of the LTCR, especially from the villages; Botongo, Mossengue and Bouanela where the indices of ichthyological diversity were the highest.

Keywords

remote sensing; Geographic Information Systems (GIS); fish biodiversity

Subject

Biology and Life Sciences, Aquatic Science

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