Ecological Niche Models of Four Hard Tick Genera (Ixodidae) in Mexico

Abstract

Simple Summary: Vector-borne diseases currently represent a significant threat to public health, mainly due to the changes that humans are producing in ecosystems and climates. Analyzing the environmental conditions that allow the establishment and survival of ticks could help determine possible sites for the appearance of infectious outbreaks. In this study, nine ecological niche models were generated from different algorithms to determine the current potential distribution of four tick genera in Mexico. Temperature and moisture have been considered as the main factors limiting tick distribution. However, the analysis of the ecological niche models determined that the four genera exhibited different distribution patterns, which may be associated with their physiological and ecological differences. This type of analysis can improve our understanding of the dynamics of ticks and, therefore, can be very useful in monitoring programs of the diseases they transmit.Abstract: Ticks are vectors of a large number of pathogens of medical and veterinary importance, and in recent years, they have participated in the rise of multiple infectious outbreaks around the world. Studies have proposed that temperature and precipitation are the main variables that limit the geographical distribution of ticks. The analysis of environmental constraints with ecological niche modeling (ENM) techniques can improve our ability to identify suitable areas for emergence events. Algorithms used in this study showed different distributional patterns for each tick genera; the environmental suitability for Amblyomma includes warm and humid localities below 1000 m above the sea level, while Ixodes is mainly associated with ecosystems with high vegetation cover. Dermacentor and Rhipicephalus genus presented wider distribution patterns; the first includes species that are well adapted to resist desiccation, whereas the latter includes generalist species that are mostly associated with domestic hosts in Mexico. Ecological niche models have proven to be useful in estimating the geographic distribution of many taxa of ticks. Despite our limited knowledge of tick's diversity, ENM can improve our understanding of the dynamics of vector-borne diseases and can assist public health decision-making processes.

Geo-Spatial Characteristics of 567 Places of Tick-Borne Encephalitis Infection in Southern Germany, 2018–2020

“…Lastly, different algorithms used for ecological niche models and species distribution models can return different estimates [ 33 ]. Comparing multiple predicted models for the same study region may help discover areas of agreement regarding the suitability for TBE foci and the probability of disease transmission [ 33 ].…”

“…PubMed was searched for the terms “TBE” OR “tick-borne encephalitis” OR “Ixodes Ricinus” AND “risk” OR “ecolog*” OR “environment*” OR “geograph*” OR “habitat” OR “climat*”. Additional articles were selected through snowball sampling [ 2 , 6 , 12 , 16 , 32 , 33 ] and expert recommendations [ 10 , 30 , 34 ].…”

Spatial Suitability Modeling of Zoonosis: Implicated Risk Areas of B. anthracis and Trends under climate change Scenarios in Ethiopia

“…Thus, the ENMevaluate result of ΔAICc (delta akaikae information criterion adjusted for small sample size) which is equal to 0 was chosen. ΔAICc has been used by several authors to select the best possible features of environmental layers and to choose the corresponding Regularization multiplier prior to running MaxEnt modeling [19–20] [24].…”

“…Maximum Entropy (MaxEnt) modeling technique has long been used to model species distribution across the area of interest including disease causing agents and vectors [12][13][14] [ [19][20]. MaxEnt is the preferred method to model species distribution because of its simplicity to employ and can easily extrapolate the current distribution of species in charge into the future projectile climatic scenarios.…”

Models for Studying the Distribution of Ticks and Tick-Borne Diseases in Animals: A Systematic Review and a Meta-Analysis with a Focus on Africa

“…Swets rules. Models References Accuracy Bayesian hierarchical model [ 102 ] Useful Classification and regression tree (CART) [ 17 , 91 ] Highly accurate [ 17 , 33 , 71 , 77 ] Useful Ecological niche factor analysis [ 39 ] Highly accurate [ 39 ] Useful Environmental niche model (ENM) [ 75 , 93 ] Highly accurate Generalized linear model (GLM) [ 17 , 38 , 53 , 91 ] Highly accurate [ 17 , 33 , 59 , 63 , 71 , 83 , 99 , 108 , ...…”