bioRxivEcologyPreprint
Introduction, spread, and evolutionary dynamics of non-native spiders in North America
Abstract
Tracing the introduction, spread, and evolution of non-native species is crucial for risk assessment and management. Spiders represent one of the largest groups of terrestrial arthropod predators, and an increasing number of species have been introduced globally, posing growing challenges to local biodiversity and ecosystem stability. Yet, their global introduction routes, spatial diversity patterns, and evolutionary dynamics remain poorly understood. Here, we conducted a global-scale survey of 53,172 taxon records and updated the checklist of North American spiders to 5,401 species, including 118 non-native species. By integrating historical records with species occurrence data, we reconstructed the geographic origins of non-native species and found that most originated from Asia and Europe, consistent with long-standing transcontinental trade and intensive human activities. Mapping the contemporary distributions of all non-native species revealed at least six richness hotspots, such as Los Angeles and San Francisco metropolitan areas, underscoring strong associations between non-native spider accumulation and population density, trade intensity, and human-mediated dispersal pathways. By analyzing genomes of 45 native and five non-native spider species within North America, we detected a set of metabolic, stress tolerance and immune defense genes under positive selection and rapid evolution in non-native species, suggesting that putative functional innovations may contribute to their establishment, expansion, and ongoing local adaptation. Altogether, our study provides the most comprehensive survey to date of introduction routes, spatial dynamics, and evolutionary signatures of non-native spiders in North America, and highlights putative mechanisms that may facilitate arthropod introductions under global change.
- assay: proteomics
- assay: metagenomics
- research focus: ecology & biodiversity
- approach: statistical model
- approach: genetic perturbation / CRISPR
- Citations
- 0
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