Memorias do Instituto Oswaldo Cruz · 2024
Investigating the distribution of a rare Colombo-Venezuelan kissing bug, Rhodnius neivai, Lent, 1953, using geographical information system-based analyses.
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Corrêa-do-Nascimento Guilherme Sanches, Galvão Cleber, Leite Gustavo Rocha
Аннотация
BACKGROUND: Rhodnius neivai, a kissing bug found in the dry regions of Colombia and Venezuela, has limited documented occurrences. While it is not deemed a significant vector for Chagas disease, distributional and ecological studies are essential in monitoring species domiciliation and shedding light on the evolutionary aspects of the Rhodniini tribe.
OBJECTIVES: The study aims to provide a detailed revision of R. neivai distribution and evaluate general spatial data quality for ecological niche modelling (ENM). It will also provide the first published ENM for the species, which may aid species sampling and future analytical improvement.
METHODS: Registers and other spatial information were gathered by literature review; data georeferencing, preliminary geographical investigations, and model editing were conducted in GIS platforms; ENMs were built using R and explored the uncertainty of parameters and algorithms.
FINDINGS: Twenty four unique sites were identified, unearthing 17 previously uncovered records. Data lacks robust spatial and temporal precision; however, ENMs had acceptable validations. The models present some variation in suitability but with objective areas for sampling effort.
MAIN CONCLUSIONS: Rhodnius neivai distribution is better explained by conditions that characterise dry ecotypes, but further sampling is essential to improve modelling and advance with ecological and evolutive matters.
OBJECTIVES: The study aims to provide a detailed revision of R. neivai distribution and evaluate general spatial data quality for ecological niche modelling (ENM). It will also provide the first published ENM for the species, which may aid species sampling and future analytical improvement.
METHODS: Registers and other spatial information were gathered by literature review; data georeferencing, preliminary geographical investigations, and model editing were conducted in GIS platforms; ENMs were built using R and explored the uncertainty of parameters and algorithms.
FINDINGS: Twenty four unique sites were identified, unearthing 17 previously uncovered records. Data lacks robust spatial and temporal precision; however, ENMs had acceptable validations. The models present some variation in suitability but with objective areas for sampling effort.
MAIN CONCLUSIONS: Rhodnius neivai distribution is better explained by conditions that characterise dry ecotypes, but further sampling is essential to improve modelling and advance with ecological and evolutive matters.