Marcel E Visser, Geerten M Hengeveld, Jelske de Kraker, Ioannis N Athanasiadis, Elisabeth S Bakker, W Daniel Kissling, Stanley Nmor, Catharina J M Philippart, Karline Soetaert, Stefan J G Vriend, Amber Woutersen, Zhiming Zhao, Qing Zhan, Andries F Hof
{"title":"Digital twins as a tool for ecosystem research.","authors":"Marcel E Visser, Geerten M Hengeveld, Jelske de Kraker, Ioannis N Athanasiadis, Elisabeth S Bakker, W Daniel Kissling, Stanley Nmor, Catharina J M Philippart, Karline Soetaert, Stefan J G Vriend, Amber Woutersen, Zhiming Zhao, Qing Zhan, Andries F Hof","doi":"10.1016/j.tree.2026.04.016","DOIUrl":null,"url":null,"abstract":"<p><p>To understand the functioning of ecosystems and to carry out scenario studies to forecast functional change, we need to integrate different fields of research. An emerging approach to do so is digital twins: innovative tools for integrated ecosystem analysis, capturing species interactions, biodiversity dynamics, and ecosystem carrying capacity. Digital twins can be characterised as (i) being tailored to and behave like a specific ecosystem, and as such accepted by empiricists as representing a description of a real ecosystem, (ii) having a dynamic interaction between the digital twin and the physical ecosystem, (iii) integrating diverse information and data sources, (iv) combining complementary models, and (v) enabling scenario studies. Development of digital twins of ecosystems is instrumental to bend the curve of biodiversity loss and enhance climate resilience, and is timely because of breakthroughs in digital technologies.</p>","PeriodicalId":23274,"journal":{"name":"Trends in ecology & evolution","volume":" ","pages":"715-725"},"PeriodicalIF":17.9000,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in ecology & evolution","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.tree.2026.04.016","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/6/23 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
To understand the functioning of ecosystems and to carry out scenario studies to forecast functional change, we need to integrate different fields of research. An emerging approach to do so is digital twins: innovative tools for integrated ecosystem analysis, capturing species interactions, biodiversity dynamics, and ecosystem carrying capacity. Digital twins can be characterised as (i) being tailored to and behave like a specific ecosystem, and as such accepted by empiricists as representing a description of a real ecosystem, (ii) having a dynamic interaction between the digital twin and the physical ecosystem, (iii) integrating diverse information and data sources, (iv) combining complementary models, and (v) enabling scenario studies. Development of digital twins of ecosystems is instrumental to bend the curve of biodiversity loss and enhance climate resilience, and is timely because of breakthroughs in digital technologies.
期刊介绍:
Trends in Ecology & Evolution (TREE) is a comprehensive journal featuring polished, concise, and readable reviews, opinions, and letters in all areas of ecology and evolutionary science. Catering to researchers, lecturers, teachers, field workers, and students, it serves as a valuable source of information. The journal keeps scientists informed about new developments and ideas across the spectrum of ecology and evolutionary biology, spanning from pure to applied and molecular to global perspectives. In the face of global environmental change, Trends in Ecology & Evolution plays a crucial role in covering all significant issues concerning organisms and their environments, making it a major forum for life scientists.