Agboka Komi Mensah, Ndjomatchoua Frank Thomas, Rossini Luca, Guimapi Ritter A, Abdel-Rahman Elfatih M
International Centre of Insect Physiology and Ecology (icipe), Nairobi P.O. Box 30772-00100, Kenya.
Department of Plant Sciences University of Cambridge, Cambridge CB2 3EA, United Kingdom.
MethodsX. 2025 Jul 28;15:103537. doi: 10.1016/j.mex.2025.103537. eCollection 2025 Dec.
The biological life cycle of terrestrial arthropods, using temperature as the primary driving factor has a large interest for insect pests in agriculture, forestry, urban ecosystems, as constitutes the basics for the development of mathematical models for decision making. A recent study proposed a physiologically-based risk index () which finds large applications in the definition of risk maps; however, further case studies are needed to better explore its strengths and limitations. This study aims to extend this knowledge by presenting an application of the on two economically significant pests: the fall armyworm and the stem borer , major treats for maize production.•While the case of follows the theoretical expectations, providing values for temperature ranges typical of the regions of its confirmed persistence, the model fails for , as for weather conditions where field presence and damage are well-documented.•Accordingly, we trace the breakdown to limiting model assumptions, particularly temperature-only drivers, linear cause-and-effect biodemographic parameters, omission of seasonal dynamics, and reliance on laboratory parameters.•This dual-case contrast highlights both the potential and limitations of and calls for refinements that include a broader ecological realism and data availability.
以温度作为主要驱动因素的陆生节肢动物的生物生命周期，对农业、林业、城市生态系统中的害虫具有重大意义，因为它构成了用于决策的数学模型发展的基础。最近的一项研究提出了一种基于生理学的风险指数（），该指数在风险地图的定义中有广泛应用；然而，需要进一步的案例研究来更好地探索其优势和局限性。本研究旨在通过展示该指数在两种具有经济重要性的害虫上的应用来扩展这方面的知识：草地贪夜蛾和螟虫，它们是玉米生产的主要威胁。•虽然草地贪夜蛾的情况符合理论预期，为其已确认存在区域的典型温度范围提供了值，但该模型对螟虫不适用，因为在有充分记录的田间出现和造成损害的天气条件下，该模型给出的值不合理。•因此，我们将故障归因于有限的模型假设，特别是仅以温度为驱动因素、线性的因果生物统计学参数、忽略季节动态以及依赖实验室参数。•这种双案例对比突出了该指数的潜力和局限性，并呼吁进行改进，包括更广泛的生态现实性和数据可用性。
