Geospatial physiologically based demographic modeling and analysis of thirteen invasive species in Africa: why the biology matters

• DOI: 10.1186/s12302-025-01084-y
• Publication Date: 2025-04-29T10:02:04Z
• Authors: Andrew Paul Gutie...; Luigi Ponti; Markus Neteler; Federica Stocchino; Jose Ricardo Cure; Peter E. Kenmore; George Simmons

Abstract

Background Globally, research and policy groups often lack the expertise to develop models to analyze invasive and native species of agroecological and veterinary/human health importance; models to inform management and policy under extant and climate change scenarios at various geographic scales. Species distribution models (SDMs) correlate weather and other variables to species presence records and are currently the mainstay for predicting the geographic distribution of species, but SDMs do not predict the underpinning dynamics required to develop policy and management strategies. Weather-driven physiologically based demographic models (PBDMs) of single and multi-trophic dynamics based on sound biological data can bridge much of this gap. The development of web platform software is proposed to assist non-experts in formulating PBDMs to help solve agroecological and veterinary/human health pest problems.

Results PBDMs are time-varying life tables (TVLTs) that capture the weather-driven biology of per capita resource acquisition and allocation to growth and reproduction in age-mass structured trophic settings independent of time and place. Two approaches are used to parameterize PBDMs: (1) mass/energy acquisition and allocation, and (2) biodemographic functions fitted to vital rates estimated from age-specific life table studies conducted under a range of abiotic conditions; vital rates that result from resource acquisition and allocation under experimental conditions. To outline the development and demonstrate the utility of this approach as web platform software for nonexperts, PBDMs for thirteen species of agroecological and medical/veterinary importance to Africa are developed and used to predict prospectively their geographic distribution, relative abundance, and dynamics across the continent. Where possible, PBDM predictions are compared to published studies and references are made to their use in management and policy development.

Conclusions The development and utility of web platform software based on the PBDM paradigm is outlined, which aims to guide non-experts in formulating realistic models and gathering the biological data to parameterize them while providing links to relevant weather data for running the models and tools for GIS mapping and statistical analysis of model output for policy and management development. Numerous published heritage PBDMs that the web platform software would make available are summarized in the Supplementary Information.