{"title":"A general DDE framework to describe insect populations: Why delays are so important?","authors":"Luca Rossini , Nicolás Bono Rosselló , Ouassim Benhamouche , Mario Contarini , Stefano Speranza , Emanuele Garone","doi":"10.1016/j.ecolmodel.2024.110937","DOIUrl":null,"url":null,"abstract":"<div><div>Physiologically-based models are a valuable tool to describe the biology of terrestrial arthropods, as it is the case of insects. These models represent the division of the life cycle in various discrete stages and provide explicit connections with the external environment, making them good candidates for decision support system tools. However, despite the current literature offering good theoretical frameworks, most of them lack of a description of the minimum time required by the organisms to develop to the next life stage. This problem leads to an overestimation of the population and to a compression of the peaks of the generations, hindering their application in real scenarios. In this study we provide a new general model based on Delay Differential Equations (DDE) that overcomes the problem of the minimum development time by introducing time-dependent delays. Those delays generally depend not only on the biology of the species, but on time and on the environmental conditions. This theoretical extension has new implications from the parameter estimation point of view, which are discussed with the support of a case study of agronomic relevance: the brown marmorated stink bug <em>Halyomorpha halys</em>. Besides supporting the description of the model, the case of <em>H. halys</em> was also considered to validate the model using datasets from two geographical locations, for an overall of 5 fields. Simulations showed that the DDE model describes the experimental data better than its previous version based on ordinary differential equations. The model represents an overall step forward in theory development and can be of great support to describe multivoltine species.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"499 ","pages":"Article 110937"},"PeriodicalIF":2.6000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Modelling","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304380024003259","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Physiologically-based models are a valuable tool to describe the biology of terrestrial arthropods, as it is the case of insects. These models represent the division of the life cycle in various discrete stages and provide explicit connections with the external environment, making them good candidates for decision support system tools. However, despite the current literature offering good theoretical frameworks, most of them lack of a description of the minimum time required by the organisms to develop to the next life stage. This problem leads to an overestimation of the population and to a compression of the peaks of the generations, hindering their application in real scenarios. In this study we provide a new general model based on Delay Differential Equations (DDE) that overcomes the problem of the minimum development time by introducing time-dependent delays. Those delays generally depend not only on the biology of the species, but on time and on the environmental conditions. This theoretical extension has new implications from the parameter estimation point of view, which are discussed with the support of a case study of agronomic relevance: the brown marmorated stink bug Halyomorpha halys. Besides supporting the description of the model, the case of H. halys was also considered to validate the model using datasets from two geographical locations, for an overall of 5 fields. Simulations showed that the DDE model describes the experimental data better than its previous version based on ordinary differential equations. The model represents an overall step forward in theory development and can be of great support to describe multivoltine species.
期刊介绍:
The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).