Integrating complexity in population modelling: From matrix to dynamic models

IF 5.8 2区 环境科学与生态学 Q1 ECOLOGY Ecological Informatics Pub Date : 2024-11-08 DOI:10.1016/j.ecoinf.2024.102884
Adrián Flores-García , John Y. Dobson , Eva S. Fonfría , David García-García , César Bordehore
{"title":"Integrating complexity in population modelling: From matrix to dynamic models","authors":"Adrián Flores-García ,&nbsp;John Y. Dobson ,&nbsp;Eva S. Fonfría ,&nbsp;David García-García ,&nbsp;César Bordehore","doi":"10.1016/j.ecoinf.2024.102884","DOIUrl":null,"url":null,"abstract":"<div><div>Matrix models are widely used in population ecology studies and are valuable for analysing population dynamics, although they are limited in the use of time-varying parameters. This limitation can be overcome by dynamic models. In this study, we revisit a previously published study on a matrix model of a population of the box jellyfish <em>Carybdea marsupialis</em> (L. 1758) in the Western Mediterranean. A dynamic model integrating the transition matrix of the original model is developed in STELLA Architect with the following improvements: (1) Sensitivity study of the reliability of the methodology for calculating the transition matrix and estimation of the errors of the fitting parameters; (2) Closure of the jellyfish life cycle by adding the polyp stage. This will make it possible to simulate scenarios of ecological interest over several years such as a decline in food supply, jellyfish removal strategies, changes in drift currents and changes in substrate availability for planulae to settle. (3) The inclusion of more biological reality. In particular, a temporal pattern of strobilation is added, which improves the fit of the model to the field data.</div></div>","PeriodicalId":51024,"journal":{"name":"Ecological Informatics","volume":"84 ","pages":"Article 102884"},"PeriodicalIF":5.8000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Informatics","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574954124004266","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Matrix models are widely used in population ecology studies and are valuable for analysing population dynamics, although they are limited in the use of time-varying parameters. This limitation can be overcome by dynamic models. In this study, we revisit a previously published study on a matrix model of a population of the box jellyfish Carybdea marsupialis (L. 1758) in the Western Mediterranean. A dynamic model integrating the transition matrix of the original model is developed in STELLA Architect with the following improvements: (1) Sensitivity study of the reliability of the methodology for calculating the transition matrix and estimation of the errors of the fitting parameters; (2) Closure of the jellyfish life cycle by adding the polyp stage. This will make it possible to simulate scenarios of ecological interest over several years such as a decline in food supply, jellyfish removal strategies, changes in drift currents and changes in substrate availability for planulae to settle. (3) The inclusion of more biological reality. In particular, a temporal pattern of strobilation is added, which improves the fit of the model to the field data.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
将复杂性融入人口模型:从矩阵模型到动态模型
矩阵模型广泛应用于种群生态学研究,对分析种群动态很有价值,但在使用时变参数方面有局限性。动态模型可以克服这一局限。在本研究中,我们重温了之前发表的关于地中海西部箱水母 Carybdea marsupialis (L. 1758) 种群矩阵模型的研究。在 STELLA Architect 中开发了一个动态模型,集成了原始模型的过渡矩阵,并做了以下改进:(1) 对过渡矩阵计算方法的可靠性进行敏感性研究,并估算拟合参数的误差;(2) 通过增加息肉阶段来封闭水母的生命周期。这将有可能模拟若干年的生态情景,如食物供应减少、水母移除策略、漂流水流的变化和可供浮游动物定居的底质的变化。(3) 纳入更多的生物现实。特别是增加了频闪的时间模式,从而提高了模型与实地数据的拟合度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Ecological Informatics
Ecological Informatics 环境科学-生态学
CiteScore
8.30
自引率
11.80%
发文量
346
审稿时长
46 days
期刊介绍: The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change. The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.
期刊最新文献
Decadal variations in the driving factors of increasing water-use efficiency in China's terrestrial ecosystems from 2000 to 2022 Using a knowledge representation logic to estimate the availability of Imbrasia epimethea (Lepidoptera: Saturniidae), an important edible insect in Subsaharan Africa Analysis of vegetation dynamics from 2001 to 2020 in China's Ganzhou rare earth mining area using time series remote sensing and SHAP-enhanced machine learning Deep learning-enhanced remote sensing-integrated crop modeling for rice yield prediction Socio-economic factors boosting the effectiveness of marine protected areas: A Bayesian network analysis
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1