A Landscape Genetics Approach Reveals Species-Specific Connectivity Patterns for Stream Insects in Fragmented Habitats.

Journal: Ecology And Evolution
Published:
Abstract

Dispersal is a critical process in ecology and evolution, shaping global biodiversity patterns. In stream habitats, which often exist within diverse and fragmented landscapes, dispersal ensures population connectivity and survival. For aquatic insects in particular, landscape features may significantly influence the degree of genetic connectivity among populations. Thus, understanding connectivity drivers in such populations is essential for the conservation and management of streams. We conducted a landscape genetic study using mitochondrial DNA (mtDNA) and genome-wide single nucleotide polymorphism (SNP) markers to assess the functional connectivity of stream insects in a fragmented pasture-dominated landscape. We focused on three species with terrestrial winged adults: the mayfly Coloburiscus humeralis, the stonefly Zelandobius confusus, and the caddisfly Hydropsyche fimbriata. We observed significant spatial genetic structure at larger geographical distances (populations separated by ~30 and 170 km). However, the effects of landscape factors, which were assessed at fine spatial scales, varied among species: for C. humeralis SNP data, genetic differentiation was weakly correlated with land cover, suggesting greater population connectivity within stream channels protected by forested riparian zones compared to fragmented streams; for Z. confusus, widespread gene flow indicated high dispersal potential across forested and pasture land; while overland dispersal was reduced for H. fimbriata (potentially due to local habitat features), this did not seem to hinder broader population connectivity. Our results emphasise the importance of assessing landscape features when evaluating population connectivity in stream riparian zones, which can greatly benefit stream management efforts through an enhanced understanding of connectivity dynamics.

Authors
Vanessa De Araujo Barbosa, S Graham, Ian Hogg, Brian Smith, Angela Mcgaughran