Mathematical modelling for optimizing predator–prey networks in a resilient wildlife ecosystem: a systematic literature review

Source abstract

The resilience of wildlife networks hinges on the adaptability and stability of complex predator-prey interactions. Mathematical modelling offers a crucial approach for examining and optimizing these dynamics under biological invasions and environmental pressures. This systematic literature review (SLR) employs a bibliometric analysis approach to synthesize global research on mathematical models applied to predator-prey network optimization, with an emphasis on their ecological implications, computational approaches, and modelling strategies. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), 50 peer- reviewed studies (2000–2025) were analyzed using the Scopus and Google Scholar databases. The study identifies classical models, such as the Lotka–Volterra, Leslie model, Holling-type I functional responses, and reaction-diffusion equations, as well as recent data-driven methods, including optimization techniques applied to differential-equation models and network-based simulations. The findings revealed that hybrid mathematical–computational frameworks significantly enhance ecological resilience assessment and prediction accuracy, accounting for the largest number of publications (38% of total included articles). Population dynamics was the strongest theme connected to other themes and found in the motor theme of the thematic map, while predator-prey systems were revealed as a cross-cutting one found in basic. Additionally, Springer was the most cited source, while Michael was found to be the most relevant author. This review concludes by suggesting future directions for adaptive modelling to enhance the management of biological invasion. This work is essential for informing adaptive management policymakers who optimize sustainable human–wildlife coexistence and ecological integrity.