Quantile normalisation enables interpretable spatial prioritisation of persistence-related mechanistic suitability under uncertainty for tomato red spider mite (Tetranychus evansi) in Africa

Publication Type

Journal Article

Journal Name

Frontiers in Agronomy

Name of Author

• Komi Mensah Agboka, International Centre of Insect Physiology and Ecology Nairobi
• Luca Rossini, University of Reading
• Quinto Juma Meltus, International Centre of Insect Physiology and Ecology Nairobi
• Bonoukpoè Mawuko Sokame, International Centre of Insect Physiology and Ecology Nairobi
• Abdulmutallab G.A. Azrag, International Centre of Insect Physiology and Ecology Nairobi
• Thomas Dubois, International Centre of Insect Physiology and Ecology Nairobi
• Elfatih M. Abdel-Rahman, International Centre of Insect Physiology and Ecology Nairobi

Publication Date

9-1-2026

Abstract

Mechanistic trait models are increasingly considered to estimate persistence-related suitability for invasive species, although translating reproduction metrics into operational indicators for spatial decision-making remains challenging. Branching-process transformations are widely applied to convert mechanistic reproduction numbers into probabilities of establishment; however, such transformations may compress spatial gradients when persistence is broadly feasible. Using tomato red spider mite (Tetranychus evansi) as a case study across Africa, this study developed an uncertainty-aware, physiologically-based model and generated spatially explicit estimates of expected reproduction (R0). We compared three representations: raw mechanistic suitability, branching-process persistence probability, and quantile-normalised suitability. Although all representations preserved rank ordering, branching probability showed strong spatial saturation (>93% of pixels have (Formula presented) close to 1), reducing effective resolution for prioritisation. In contrast, quantile normalisation retained uniform spatial contrast and stable hotspot delineation under fixed-effort targeting. Our findings demonstrate that indicator choice fundamentally affects interpretability, and that rank-based transformations may provide more robust ecological indicators for spatial and spatiotemporal decision support under uncertainty.

Keywords

branching-process persistence probability, invasive pest risk assessment, Monte Carlo uncertainty propagation, quantile-normalised suitability, spatial prioritisation, trait-based R0 modelling

Recommended Citation

Agboka, K., Rossini, L., Meltus, Q., Sokame, B., Azrag, A., Dubois, T., & Abdel-Rahman, E. (2026). Quantile normalisation enables interpretable spatial prioritisation of persistence-related mechanistic suitability under uncertainty for tomato red spider mite (Tetranychus evansi) in Africa. Frontiers in Agronomy, 8 https://doi.org/10.3389/fagro.2026.1840571

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.