ReviewEcology and evolution2026
A Beginner's How-To Guide to Urban Population Genetics and Genomics.
Review in Ecology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 authors.
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Abstract
Urbanization is one of the most significant drivers of environmental change, shaping the ecological and evolutionary processes of plants and animals. Understanding how species evolve in urban landscapes requires integrating population genetics and genomics with urban ecology. Thus, accessible guidance is necessary to facilitate interdisciplinary approaches for applying population genetic and genomic tools to understand the ecology and evolution of urban species. Here, we present a how-to guide with key concepts and methodologies for studying urban population genetics, including identifying genetic markers, choosing appropriate analytical tools, and applying spatial genetic modeling approaches. We emphasize practical applications to assess genetic diversity, population connectivity, and adaptation, relevant in the generation of management strategies for conservation, pest control, and assisted gene flow. By bridging the gap between population genomics and urban ecology, this guide aims to equip researchers, wildlife managers, and conservation practitioners with essential tools to study and manage urban populations. Strengthening collaborations between urban ecologists, pest management professionals, geneticists, and city planners will enhance our ability to develop sustainable cities that support biodiversity, mitigate urban pests and invasive species, and promote coexistence between urban development and nature.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.