Eco-Evolutionary Dynamics in Human-Dominated Systems: Data-Driven Insights for Conservation and Sustainability

Human activity now shapes the majority of the planet’s ecosystems. Urbanisation, land-use change, agriculture, and environmental disturbance are altering habitats, reshaping species distributions, and driving rapid ecological and evolutionary responses in the organisms and communities that persist within human-dominated landscapes. At the same time, the digitalisation of environmental observation has produced unprecedented volumes of data, from remote sensing and biodiversity monitoring to sensor networks and citizen science, opening new opportunities to study these dynamics at scales and resolutions that were previously impossible.This Research Topic explores how data-driven theories, models, and technologies can advance our understanding of ecological and evolutionary processes in human-dominated, socio-ecological systems. Rather than treating computational methods as an end in themselves, the collection positions artificial intelligence, machine learning, and network and systems modelling as analytical tools applied to ecological and evolutionary questions: how biodiversity, ecosystem function, and evolutionary trajectories respond to anthropogenic pressure, and how this knowledge can inform fairer, more sustainable, and more effective conservation and environmental decision-making. We particularly welcome interdisciplinary work that bridges computational, ecological, and evolutionary perspectives.We welcome original research, reviews, and methodological contributions addressing, but not limited to:• Ecological and evolutionary responses of species and communities to urbanisation, land-use change, and anthropogenic disturbance • Data-driven approaches to biodiversity monitoring, ecosystem assessment, and conservation planning in human-dominated landscapes • Machine learning, network, and systems modelling applied to socio-ecological and human-environment dynamics • Eco-evolutionary dynamics, adaptation, and resilience in urban and modified environments • Decision-making frameworks for ecosystem sustainability and conservation, including fairness, transparency, and equity in environmental management • Reproducible workflows, open data, and methodological innovation for ecological and evolutionary research Topic editors: Zongshui Wang, Maria Anunciação Ventura, Hong Zhao Source: https://www.frontiersin.org/research-topics/83118/eco-evolutionary-dynamics-in-human-dominated-systems-data-driven-insights-for-conservation-and-sustainability