Curating protected area-level species lists in an era of diverse and dynamic data sources

IF 5.8 2区 环境科学与生态学 Q1 ECOLOGY
Elizabeth Wenk , Thomas Mesaglio , David Keith , Will Cornwell
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引用次数: 0

Abstract

Dynamic yet accurate species lists for protected areas are essential for conservation and biodiversity research. Even when such lists exist, changing taxonomy, ongoing species migrations and invasions, and new discoveries of historically overlooked species mean static lists can become rapidly outdated. Biodiversity databases such as the Global Biodiversity Information Facility, and citizen science platforms such as iNaturalist, offer rapidly accessible, georeferenced data, but their accuracy is rarely tested. Here we compare species lists generated for two of the world's oldest, more famous protected areas – Yosemite National Park in California, United States and Royal National Park in New South Wales, Australia – using both automated data extraction techniques and extensive manual curation steps. We show that automated list creation without manual curation offers inflated measures of species diversity. Lists generated from herbarium vouchers required more curation than lists generated from iNaturalist, with both incorrect coordinates attached to vouchers and long-outdated names inflating voucher-based species lists. In comparison, iNaturalist data had relatively few errors, in part due to continual curation by a large community, including many botanical experts, and the frequent and automatic implementation of taxonomic updates. As such, iNaturalist will become an increasingly accurate supplementary source for automated biodiversity lists over time, but currently offers poor coverage of graminoid species and introduced species relative to showier, native taxa, and relies on continued expert contributions to identifications. At this point, researchers must manually curate lists extracted from herbarium vouchers or static park lists, and integrate these data with records from iNaturalist, to produce the most robust and taxonomically up-to-date species lists for protected areas.
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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.
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