Species delimitation of the <i>Dermacentor</i> ticks based on phylogenetic clustering and niche modeling

Wang, Fang; Wang, Duo; Guo, Ge; Hu, Yonghong; Wei, Jiufeng; Liu, Jingze

doi:10.7717/peerj.6911

Cited by 32 publications

(20 citation statements)

References 71 publications

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“…Species delimitation is one of the most debated subjects in biological research, fostering discussions that extend from a strictly philosophical nature to practical concerns related to areas such as conservation, agronomy, and health (Peterson & Navarro-Sigüenza 1999, Sites & Marshall 2003, Najafzadeh et al 2009, Rojas-Soto et al 2010, Shirley et al 2013, Wang et al 2019. The definition of biological species has attracted significant attention from biologists, and a daunting array of species concepts has been proposed in an attempt to cope with both theoretical and practical aspects of biodiversity investigation (Hey 2001, De Queiroz 2005, 2007, Velasco 2008, Casiraghi et al 2016.…”

Section: Introductionmentioning

confidence: 99%

Employing statistical learning to derive species‐level genetic diversity for mammalian species

Schrago

Mello

2020

Mammal Review

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1. The patterns of genetic diversity in several genomic regions have been used in mammalian systematics for decades. For instance, when studying closely related species, it is generally assumed that the mitochondrial cytochrome b gene (cytb) exhibits significant information that can be used for differentiation between intraspecies and interspecies variation in mammals. Because of sampling limitations, early analyses of this proposition were conducted mainly on rodents and bats. 2. Currently, more than 57000 cytb sequences are available covering all major lineages of mammals, and sequencing of several individuals per species is common practice in molecular systematics. We were thus prompted to carry out a large-scale analysis of the utility of cytb genetic variation as a predictor of whether a pair of sequences came from within-species or between-species comparisons. 3. Using predetermined species-level assignments, we employed standard methods from statistical learning to calculate the cutoff values able to classify genetic distances in either intraspecies or interspecies categories; we then measured the performance of such statistical classifiers to predict the species-level taxonomic rank as defined by experts. 4. Depending on the classifier, our results showed that when adopting cytb distance cutoff values of 7.3% and 5.5% for small mammals (Metatheria, Rodentia, Chiroptera, and Eulipotyphla) and 4.3% and 3% for medium-sized to large mammals (Primates, Carnivora, and Artiodactyla), the frequency of incorrect assignment of within-species divergences to the between-species category (type I error) varied from 7 to 11%. 5. In order to avoid over-splitting by future researchers, we calculated cutoff values using a more conservative evaluation and provided a list of mammalian species that are likely to consist of complexes of cryptic species. We show that our supervised method can provide practical guidelines to improve the performance of unsupervised algorithms for species delimitation. Finally, we discuss limitations of large-scale approaches (e.g. effects of misclassification in databases and the need for case-by-case evaluation of cryptic species complexes) and their consequences for conservation policies. SUPPORTING INFORMATION Additional supporting information may be found in the online version of this article at the publisher's web-site. Appendix S1. Empirically estimated density distributions for within-and between-species genetic distances.

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Section: Introductionmentioning

confidence: 99%

Employing statistical learning to derive species‐level genetic diversity for mammalian species

Schrago

Mello

2020

Mammal Review

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“…Globally, 36 species of Dermacentor are recognized [81], 11 of which are documented in Mexico. In general, Dermacentor ticks are found in all biogeographic regions [82], but they are better represented in the Holarctic region.…”

Section: Discussionmentioning

confidence: 99%

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

Emilio

Moreno-Arzate

López‐González

2020

Animals

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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.

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“…The 10th percentile replicate training presence logistic threshold was used to define the suitable and unsuitable habitats for P. pentagona. This threshold is widely used in species distribution modeling, especially when the observation datasets were collected by different observers and methods over a long period of time [53]. The potential distribution map area of P. pentagona was divided into four levels using the above threshold (0.2168): < threshold denotes unsuitable habitat; threshold-0.4 denotes low habitat suitability; 0.4-0.6 denotes moderate habitat suitability; and 0.6-1 denotes high habitat suitability.…”

Section: Environmental Niche Modelsmentioning

confidence: 99%

The Potential Global Distribution of the White Peach Scale Pseudaulacaspis pentagona (Targioni Tozzetti) under Climate Change

Zhao

Cheng

et al. 2020

Forests

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The white peach scale Pseudaulacaspis pentagona (Hemiptera: Diaspididae) is a pest that causes significant damage to more than 221 genera of host plants in more than 112 countries. P. pentagona primarily feeds on mulberry, peach, and tea, and this leads to the loosening of the epidermis of trees, which damages nutrient and water transportation in the branches, leading to branch death. P. pentagona is native to China and Japan, and has become an invasive species all over the world. However, the potential distribution of P. pentagona remains unclear. In this study, a potential distribution map of P. pentagona was developed using current and future climate information using MaxEnt. The model indicates that Asia, Europe, South America and North America are a highly suitable habitat range for this species. The MaxEnt models for the potential distribution of P. pentagona for the 2050s and 2070s suggest that in the case of no significant increase or even decrease in the highly suitable area, the suitable area increased significantly on any future climatic scenarios. The predicted area gain in the suitable habitat is 2.82 × 10 7 km 2 , including more of Asia, such as China, Japan, and Mongolia, and also including India, in Europe, which shows an increase of 24.5% over the current habitat on RCP8.5 emission scenarios for the 2070s. With the warming of the climate, significant expansions are predicted in the suitable area, especially in Europe and East Asia. Under RCP8.5 for the 2050s, the model-predicted that the area of suitable habitat in China and the Korean Peninsula gains an increase of 18.8% over the current suitable habitat area. Under other climate scenarios, RCP8.5-2070s, the suitable areas were the largest, compared to projection for the current climate scenario (ca. 24.1% increase) which increased to 7.89 × 10 6 km 2 . In Europe, under RCP8.5 for the 2070s, the highly suitable areas were the largest, compared to the projection for the current climate scenario (ca. 46.2% increase), which increased to 8.64 × 10 5 km 2 , the area of suitable habitat suitability increased to 4.99 × 10 6 km 2 (29.2% increase of the current condition). Potential increases or decreases in distribution ranges were modeled under future climatic scenarios. This study suggests that the most important factor that influenced current distribution of this pest was temperature, and BIO3 (isothermality) was the most important factor that contributed to 48.6% of the potential distribution map. Given the rapid spread of P. pentagona and the serious risk this species poses to local ecosystems, warning modelling and practical strategies to prevent the establishment and expansion of this species should be sought. This distribution map will help governments to identify areas that are suitable for current and future infestations, and to optimize pest management strategies.

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Species delimitation of the Dermacentor ticks based on phylogenetic clustering and niche modeling

Cited by 32 publications

References 71 publications

Employing statistical learning to derive species‐level genetic diversity for mammalian species

Employing statistical learning to derive species‐level genetic diversity for mammalian species

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

The Potential Global Distribution of the White Peach Scale Pseudaulacaspis pentagona (Targioni Tozzetti) under Climate Change

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