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

Author:

Schleimer Anna12ORCID,Wittische Julian12ORCID,Luttringer Amanda12,Rupprecht Christina3,Andrási Bálint1,Ariey Hinatea12,Cruz António1ORCID,Gallego Gil1ORCID,Lippert Stéphanie12,Purnomo Chanistya Ayu1ORCID,Herrera‐Mesías Fernanda14ORCID,Eickermann Michael5ORCID,Kharrat‐Jarboui Imen1ORCID,Castelen Lorenzo1,Cantú‐Salazar Lisette5ORCID,Thissen Dylan1ORCID,Meimberg Harald3ORCID,Weigand Alexander M.1ORCID,Frantz Alain C.12ORCID

Affiliation:

1. Musée National d'Histoire Naturelle Luxembourg Luxembourg

2. Fondation Faune‐Flore Luxembourg Luxembourg

3. Institute for Integrative Nature Conservation Research University of Natural Resources and Life Sciences (BOKU) Vienna Austria

4. Department of Animal Ecology, Evolution and Biodiversity Ruhr‐Universität Bochum Germany

5. Luxembourg Institute of Science and Technology Esch‐sur‐Alzette Luxembourg

Abstract

Abstract 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.

Funder

Fonds National de la Recherche Luxembourg

Publisher

Wiley

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