Network Analysis for Ecologists (NWAE01) https://www.prstats.org/course/network-analysis-for-ecologists-nwae01/
*Dates:* 4–5 November 2025 *Format:* Live online, 2 days × 3 hours per day. Also recorded with a further 30 days access *Fee:* £250 standard | £225 early-bird (early-bird now sold out) *Time zone:* UK (GMT) local time *Recording access:* All sessions recorded and available to participants for 30 days ------------------------------ Why Take This Course? Ecosystems are connected webs of interactions — predation, mutualism, competition, parasitism — and understanding these relationships is essential to answering key ecological questions. *Network analysis* provides a powerful framework to quantify, visualise, and model these interaction webs. Whether you're studying pollination networks, food webs, host–parasite systems, or microbial interactions, this course will give you the tools to turn raw interaction data into ecological insight. *Network Analysis for Ecologists (NWAE01)* is a focused, intensive two-day course that introduces the core concepts, methodologies, and computational tools needed to analyse ecological networks using R (especially via the *igraph*package). You’ll move from theory to hands-on practice with real datasets and simulation models, under expert guidance. ------------------------------ What You’ll Learn Over the course of two days, participants will progress through: - The fundamentals of network construction: vertices, edges, adjacency matrices, and graph formats - Data wrangling and preparing interaction data for network analysis - Network-level measures: modularity, nestedness, degree distributions, network connectance, and more - Node-level (local) properties: degree centrality, betweenness, closeness, eigenvector centrality - Comparing and interpreting structural patterns across networks - Simulation of population dynamics on networks using ordinary differential equations (ODEs) - Combining simulations with empirical network structures to explore stability, robustness, and dynamics - Visualisation and reproducible workflows: creating compelling network graphics and reproducible code pipelines All concepts are reinforced through guided coding exercises and participant engagement with datasets—both provided and your own, if you bring them. ------------------------------ Format & Support - Each session pairs lecture, demonstration, and hands-on lab work - Time allocated for discussion of participants’ own datasets (if time allows) - All course materials, scripts, and datasets provided - Recorded sessions available for 30 days post-course - Email support from instructors for 30 days after the course ------------------------------ Who Should Attend This course targets ecologists, conservation biologists, and researchers interested in applying network theory to ecological interactions and community dynamics. A working familiarity with *R* (data importing, manipulation, basic plotting) is expected. While no prior experience in network analysis is required, some comfort with quantitative concepts (distributions, summary statistics, algebra) will help. Knowledge of calculus or differential equations is not essential but aids in understanding the simulation modules. ------------------------------ Instructor The course is led by *Dr Miguel Lurgi*, Associate Professor at Swansea University and a specialist in computational ecology and network modelling. His research spans species interaction networks, community assembly, and the ecological impacts of global change. PR Stats <https://www.prstats.org/course/network-analysis-for-ecologists-nwae01/> ------------------------------ Why This Course Matters for Your Research - Networks can uncover hidden structure in ecosystems (e.g. keystone species, modules, network resilience) - Understand how interactions shape stability, robustness, and cascading effects - Link network structure to species dynamics via simulations - Enhance ecological inference in systems from pollinators, host–parasite, food webs, to microbiomes - Present network-based results with clarity using visualisation and reproducible code ------------------------------ Registration & Details Spaces are limited to maintain an interactive, supportive environment. The early-bird rate (£225) is already sold out; standard registration is £250. For full details, schedule, and registration, visit: Network Analysis for Ecologists (NWAE01) <https://www.prstats.org/course/network-analysis-for-ecologists-nwae01/?utm_source=chatgpt.com> -- Oliver Hooker PhD. PR stats [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
