Spatial modeling with repopulation potential for three flora species of Huaytapallana Regional Conservation Area, Peru

• Autores: Bravo Verde, Renato Saul Nino, Castro Pulido, Jean Paul, Cornejo Tueros, Jose Vladimir
• Formato: tesis de grado
• Fecha de Publicación: 2022
• Institución: Universidad Continental
• Repositorio: CONTINENTAL-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.continental.edu.pe:20.500.12394/11778
• Enlace del recurso: https://hdl.handle.net/20.500.12394/11778; https://doi.org/10.1088/1755-1315/1008/1/012021
• Nivel de acceso: acceso abierto
• Materia: Árboles; Repoblación forestal; Conservación y restauración; http://purl.org/pe-repo/ocde/ford#2.07.00

In the high mountain ecosystems of the Huaytapallana Regional Conservation Area (ACR-H) there are three species of flora (Krapfia macropetala, Gentianella scarlatinostriata and Senecio canescens) of social, economic, cultural and medicinal importance, however their population status and undefined local distribution make these species area more vulnerable to extinction. Therefore, the objective of this work is to determine the population distribution for repopulation purpose in the ACR-H from the potential distribution in Peru using Maxent algorithm and a local model developed with the Saaty pairwise hierarchy matrix, adding a soil sample for a better application of the final model. The results show that the Species Distribution Models (SDMs) have a high confidence because the Area Under the Curve (AUC) surpass 0.90. Otherwise, the local model is consistent by showing a Consistency Ratio (CR) of less than 0.10. As a final result, all species obtained optimal spaces for repopulation near the Huaytapallana Cordillera, where Krapfia macropetala obtained the largest extension (715.334 ha) and Gentianella scarlatinostriata is the smallest (650.096 ha). Further there were no differences in the parameters evaluated in the three soil samples, which facilitates the application of the models for the repopulation of these three species.