| Literature DB >> 26209969 |
Anna Skoracka1, Sara Magalhães, Brian G Rector, Lechosław Kuczyński.
Abstract
There are approximately 55,000 described Acari species, accounting for almost half of all known Arachnida species, but total estimated Acari diversity is reckoned to be far greater. One important source of currently hidden Acari diversity is cryptic speciation, which poses challenges to taxonomists documenting biodiversity assessment as well as to researchers in medicine and agriculture. In this review, we revisit the subject of biodiversity in the Acari and investigate what is currently known about cryptic species within this group. Based on a thorough literature search, we show that the probability of occurrence of cryptic species is mainly related to the number of attempts made to detect them. The use of, both, DNA tools and bioassays significantly increased the probability of cryptic species detection. We did not confirm the generally-accepted idea that species lifestyle (i.e. free-living vs. symbiotic) affects the number of cryptic species. To increase detection of cryptic lineages and to understand the processes leading to cryptic speciation in Acari, integrative approaches including multivariate morphometrics, molecular tools, crossing, ecological assays, intensive sampling, and experimental evolution are recommended. We conclude that there is a demonstrable need for future investigations focusing on potentially hidden mite and tick species and addressing evolutionary mechanisms behind cryptic speciation within Acari.Entities:
Mesh:
Year: 2015 PMID: 26209969 PMCID: PMC4559570 DOI: 10.1007/s10493-015-9954-8
Source DB: PubMed Journal: Exp Appl Acarol ISSN: 0168-8162 Impact factor: 2.132
Parameter values (on the logit scale) of the model relating the proportion of cryptic species detected within each superfamily with their lifestyle (0: free-living, 1: symbiotic), the number of taxa analyzed for the presence of cryptic species and the research methods used (the use of DNA-based methods 0 = No, 1 = Yes; the use of bioassays 0 = No, 1 = Yes)
| Parameter | Estimate | SE | z value |
|
|---|---|---|---|---|
| Intercept | −8.50 | 0.46 | −18.52 | <0.0001 |
| Lifestyle | −0.12 | 0.34 | −0.34 | 0.73 |
| No. of taxa analyzed | 2.06 | 0.28 | 7.29 | <0.0001 |
| DNA | 3.48 | 0.52 | 6.71 | <0.0001 |
| Bioassay | 1.52 | 0.58 | 2.63 | 0.0085 |
| Taxa:DNA | −2.10 | 0.29 | −7.16 | <0.0001 |
| Taxa:bioassay | 0.06 | 0.10 | 0.61 | 0.54 |
| DNA:bioassay | −1.14 | 0.66 | −1.72 | 0.086 |
All two-way interactions between variables coding the research effort (no. of taxa analyzed, the use of DNA, the use of bioassays) were included in the model, allowing for testing the potential acceleration in cryptic species detection when using an integrated approach
Fig. 1Results of the generalized linear model presenting the effect of the life style (a), the number of taxa verified for the existence of cryptic species (b), if DNA (c) or bioassays (d) were used (0 = No, 1 = Yes) of the studied Acari on the probability of cryptic species occurrence within a superfamily. Values on vertical axes are partial residuals. Solid lines are estimates and dashed lines are standard errors around them
Fig. 2Accumulation curves and their 95 % confidence intervals for Aceria tosichella cryptic species resulting from an intensive sampling scheme. As the sampling effort increased, the total number of recorded genetic lineages rose and reached an asymptote that corresponds to an estimated size of the total lineage pool (including those lineages yet unknown). It was recently found (Chiu et al. 2014) that this type of estimate gives only the lower limit of the richness parameter. Thus, it is likely that the “true” number of genetic lineages within the Aceria tosichella complex (provided that sampling is restricted to the same geographic region, range of habitats and host species) will be higher. The panels represent different nonparametric methods of estimation of accumulation curves: S—no. of biotypes, Bootstrap—bootstrap estimator, described in Smith and van Belle (1984). Calculations were made in R using the function “specpool” from the package “vegan” (Oksanen et al. 2013)