Anthony Gibbons , Francesco Martini , Cian White , Emma King , Jane C. Stout , Ian Donohue , Andrew Parnell
{"title":"ExActR: A Shiny app for creating ecosystem extent accounts","authors":"Anthony Gibbons , Francesco Martini , Cian White , Emma King , Jane C. Stout , Ian Donohue , Andrew Parnell","doi":"10.1016/j.ecoinf.2025.103072","DOIUrl":null,"url":null,"abstract":"<div><div>Ecosystem accounting is a structured way to integrate nature into sustainable decision-making. The System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) was adopted by the United Nations as a set of international standards for the collection of habitat data and compiling ecosystem accounts. The ecosystem extent account is one of the four pillars of the SEEA-EA framework, where the spatial composition of an ecosystem accounting area is grouped by habitat types, and the land cover change over time is quantified. Although a variety of tools exist for preparing extent accounts, most of them require moderate to high levels of technical expertise. Here, we present <em>ExActR</em> (Extent Accounts in R), an open-source application for generating extent accounts using shapefiles, a geospatial vector data format. The app is built in <span>R</span> and the associated Shiny framework, which automatically updates as the user interacts with it. The application supports multiple timepoints, where extent accounts (tables) are generated for consecutive pairs of timepoints, accommodating users’ needs for dynamic ecosystem assessments across several periods. Data visualisations are generated in the form of both interactive (leaflet) and static maps of each timepoint, and barplots to illustrate land type composition and change. A version of the app has been deployed (available at <span><span>https://gibbona1.shinyapps.io/extent_app/</span><svg><path></path></svg></span>), offering a space for interactive exploration of ecosystems. Shiny’s reactivity, combined with JavaScript plugins for copying tables into multiple formats, including LaTeX and plots, make the application results suitable to insert directly into reports. The app is suitable for using with any spatial grouping variable. We test its functionality on small and large study sites on CORINE land cover data, as well as land cover maps generated using very-high resolution satellite imagery of a wind farm site in Ireland, during and post construction, demonstrating its ability to adapt to various land cover classification systems. The tool can be used to understand, visualise and track changes in ecosystem assets, aiding interpretation by both scientists and stakeholders.</div></div>","PeriodicalId":51024,"journal":{"name":"Ecological Informatics","volume":"87 ","pages":"Article 103072"},"PeriodicalIF":5.8000,"publicationDate":"2025-02-22","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/S1574954125000810","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}
ExActR: A Shiny app for creating ecosystem extent accounts
Ecosystem accounting is a structured way to integrate nature into sustainable decision-making. The System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) was adopted by the United Nations as a set of international standards for the collection of habitat data and compiling ecosystem accounts. The ecosystem extent account is one of the four pillars of the SEEA-EA framework, where the spatial composition of an ecosystem accounting area is grouped by habitat types, and the land cover change over time is quantified. Although a variety of tools exist for preparing extent accounts, most of them require moderate to high levels of technical expertise. Here, we present ExActR (Extent Accounts in R), an open-source application for generating extent accounts using shapefiles, a geospatial vector data format. The app is built in R and the associated Shiny framework, which automatically updates as the user interacts with it. The application supports multiple timepoints, where extent accounts (tables) are generated for consecutive pairs of timepoints, accommodating users’ needs for dynamic ecosystem assessments across several periods. Data visualisations are generated in the form of both interactive (leaflet) and static maps of each timepoint, and barplots to illustrate land type composition and change. A version of the app has been deployed (available at https://gibbona1.shinyapps.io/extent_app/), offering a space for interactive exploration of ecosystems. Shiny’s reactivity, combined with JavaScript plugins for copying tables into multiple formats, including LaTeX and plots, make the application results suitable to insert directly into reports. The app is suitable for using with any spatial grouping variable. We test its functionality on small and large study sites on CORINE land cover data, as well as land cover maps generated using very-high resolution satellite imagery of a wind farm site in Ireland, during and post construction, demonstrating its ability to adapt to various land cover classification systems. The tool can be used to understand, visualise and track changes in ecosystem assets, aiding interpretation by both scientists and stakeholders.
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.