Ecological aspects of the distribution of Ismene amancaes in the Amancay Sanctuary private conservation area (ACP), 2023

Authors

DOI:

https://doi.org/10.21142/SS-0601-2025-e115

Keywords:

Ismene amancaes, biodiversity conservation, remote sensing, machine learning, coastal lomas

Abstract

This study focuses on the monitoring of Ismene amancaes, a plant endemic to the coastal hills of Lima, within the Lomas Quebrada Río Seco Private Conservation Area, also known as the Amancay Sanctuary. By integrating geographic information systems (GIS) and machine learning techniques, the distribution and morphological characteristics of the species, together with the environmental conditions influencing its habitat, were evaluated. Field monitoring, combined with supervised classification, achieved an accuracy of 86% in identifying vegetation cover, in accordance with the Kappa index. The results reveal that I. amancaes occupies an area of 2.96 hectares, with a density of between 18 and 26 individuals per square meter. The species is primarily distributed across soils and roads (58.19%), followed by open spaces (23.43%), light vegetation cover (14.26%), and dense vegetation cover (4.12%). The methodology applied demonstrates the effectiveness of machine learning tools for biodiversity monitoring in hard-to-reach desert regions. These findings not only expand ecological knowledge of the species, but also underscore the urgent need to conserve and properly manage its habitat, particularly in relation to road and route management, in favor of the conservation of the species. Additionally, the findings provide a solid foundation for the development of future conservation strategies in the coastal hill ecosystem, thereby benefiting both the ecosystem and local communities.

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Published

2025-01-23