𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗮𝗻𝗱 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝘀 𝗳𝗼𝗿 𝗣𝗼𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗗𝘆𝗻𝗮𝗺𝗶𝗰𝘀 𝗶𝗻 𝗮 𝗖𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝗪𝗼𝗿𝗹𝗱

𝗖𝗮𝗹𝗹 𝗳𝗼𝗿 𝗣𝗮𝗽𝗲𝗿𝘀

𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗮𝗻𝗱 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝘀 𝗳𝗼𝗿 𝗣𝗼𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗗𝘆𝗻𝗮𝗺𝗶𝗰𝘀 𝗶𝗻 𝗮 𝗖𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝗪𝗼𝗿𝗹𝗱

𝗝𝗼𝘂𝗿𝗻𝗮𝗹:
Mathematical Population Studies

𝗣𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗿:
Taylor & Francis Group

𝗠𝗮𝗻𝘂𝘀𝗰𝗿𝗶𝗽𝘁 𝗗𝗲𝗮𝗱𝗹𝗶𝗻𝗲:
30 June 2026

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗜𝘀𝘀𝘂𝗲

Mathematical Population Studies invites submissions for its Special Issue on Advanced Computational and Mathematical Models for Population Dynamics in a Changing World. The issue aims to explore innovative computational and mathematical approaches that enhance understanding of population behaviours under rapidly changing ecological, environmental, and societal conditions.

Advanced computational and mathematical models have become indispensable tools for examining complex population interactions, incorporating biological, environmental, and anthropogenic factors to predict growth patterns, dispersal, competition, extinction risks, disease transmission, and resilience. The integration of sophisticated computational techniques, machine learning, and agent-based modelling with classical mathematical frameworks is expanding the scope and applicability of population studies.

The Special Issue seeks original contributions that advance theoretical developments, computational methods, and practical applications capable of informing conservation strategies, resource management, and evidence-based policymaking in an increasingly uncertain world.

𝗧𝗼𝗽𝗶𝗰𝘀 𝗼𝗳 𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁

Submissions may address, but are not limited to, the following themes:

• Stochastic modelling of population growth and extinction risks under environmental uncertainty
• Spatially explicit models of habitat fragmentation and population connectivity
• Agent-based simulations of adaptive behaviours in heterogeneous populations
• Integration of machine learning with classical mathematical population models
• Nonlinear dynamics and bifurcation analysis in ecological and epidemiological systems
• Multiscale modelling linking individual behaviours with population-level outcomes
• Species invasion modelling and impacts on native populations
• Disease transmission and epidemiological modelling in changing demographic environments
• Computational challenges and optimisation techniques in large-scale population simulations
• Climate change impacts on reproductive rates and migratory patterns
• Coupling socio-economic variables with ecological models for human-natural systems analysis
• Evolutionary dynamics and genetic diversity modelling
• Validation techniques and uncertainty quantification in complex population models
• Dispersal and migration modelling in metapopulation and landscape ecology
• Policy-driven population management models incorporating conservation feedback mechanisms

𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗜𝘀𝘀𝘂𝗲 𝗠𝗮𝘁𝘁𝗲𝗿𝘀

The issue highlights the importance of developing robust, scalable, and interdisciplinary population models capable of addressing pressing global challenges such as biodiversity loss, ecosystem degradation, food security, environmental change, and demographic transformations. By integrating environmental, socio-economic, and policy dimensions into population modelling frameworks, the Special Issue seeks to foster innovations that bridge theory and practice.

𝗦𝘂𝗯𝗺𝗶𝘀𝘀𝗶𝗼𝗻 𝗚𝘂𝗶𝗱𝗲𝗹𝗶𝗻𝗲𝘀

• Interested authors should first submit an abstract to the Guest Editors by 25 June 2025.
• Authors of selected abstracts will be invited to submit full manuscripts by 30 June 2026.
• Manuscripts should be submitted through ScholarOne and authors must select the appropriate Special Issue title during submission.
• Submissions should include the following sections: Title Page, Abstract, Keywords, Introduction, Materials and Methods, Results, Discussion, Acknowledgements, Declaration of Interest Statement, References, Appendices (if applicable), Tables, Figures, and Figure Captions.
• Manuscripts should include an unstructured abstract of approximately 200 words.

𝗚𝘂𝗲𝘀𝘁 𝗘𝗱𝗶𝘁𝗼𝗿𝘀

• Dr. Ahmad Kadri Junoh, Universiti Malaysia Perlis, Malaysia
• Dr. Suhaila Saidat, Irbid National University, Jordan
• Dr. Achmad Abdurrazzaq, Indonesia Defense University, Indonesia

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