Insect Landscape Genomics

Chaulk, Andrew C.; Keyghobadi, Nusha

doi:10.1007/13836_2022_106

Cited by 1 publication

(2 citation statements)

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“…While SNP markers have gained popularity in landscape genetic studies, microsatellite markers continue to be a prominent choice for studying population genetic structure (Chaulk & Keyghobadi, 2022; Hodel et al, 2016). SNPs do not require the design of specific primers in non‐model species, have a greater power to resolve fine‐scale structuring and provide information on adaptive selection (Dufresnes et al, 2023; Zimmerman et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…However, pollinator insect studies have been largely focussed on a limited number of taxa, with an underrepresentation of solitary bees and dipterans despite their prominent role in providing vital ecosystem services (Corbet et al, 1991; Doyle et al, 2020; Rader et al, 2016). A need exists for comprehensive investigations into species‐specific responses to human‐altered landscapes (Chaulk & Keyghobadi, 2022; Prendergast et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Genetic connectivity is maintained in two insect pollinators across a human‐altered landscape

Schleimer,

Wittische,

Luttringer

et al. 2024

Insect Conserv Diversity

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Population genetics is a valuable tool for assessing the impact of human‐altered landscapes on genetic connectivity in various species. However, when applied to insects, challenges arise due to potentially large effective population sizes (), high dispersal capacities and the recency of anthropogenic impacts. This study assessed the population genetic structure of two pollinators across a human‐altered landscape in Luxembourg. Samples from the ashy mining bee (Andrena cineraria, N = 201) and the greater bee fly (Bombylius major, N = 637) were genotyped at 25 microsatellite loci, including a genotyping‐by‐amplicon‐sequencing approach for A. cineraria. Despite high statistical power of > 0.002 in B. major and > 0.0025 in A. cineraria, no deviations from genetic homogeneity were detected. For both species, there was no evidence for isolation‐by‐distance or genetic clustering. Genetic homogeneity was most likely the result of high levels of gene flow that compensate for the effects of genetic drift. Estimates of ranged between several thousand to tens of thousands, although precision was low. Simulations highlighted that genetic lag times can substantially affect our ability to detect recent (<50 generations) population differentiation when is very large. Lag times were shorter with data from 25,000 simulated di‐allelic loci, but only when sample sizes remained high. Insect genetic studies should consider lag times due to large and ensure sample size and markers offer adequate power to reject the null hypothesis of no landscape effect on genetic connectivity.

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