ArticleScientific data2024
Finnish inventory data of underwater marine biodiversity.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Review
- Article
- Marine biodiversity loss in Finnish coastal waters: Evidence and implications for management.Ambio · 2025Article
- Finnish inventory data of underwater marine biodiversity.Scientific data · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
25 authors.
Funding
Abstract
Since 2004, marine biodiversity inventory data have been systematically collected with diving, video, and benthic sampling methods in Finland. To date, this collection of data consists of more than 194 000 spatially explicit observations, covering more than 280 aquatic genera, representing mainly macroalgae, vascular plants, water mosses, and invertebrates. We describe the data collection and storage methods, data extraction from national databases, and provide potential users a curated, open-access version of the inventory data. Additionally, examples of data applications and discussion on potential limitations are provided. This extensive dataset can be used in ecological and biogeographical studies to provide general descriptions of biodiversity patterns and species distributions, as well as in more applied studies to support marine management, conservation, and sustainable use of marine areas. The sampling strategy and high spatial and taxonomic resolution allow for statistical modelling, which further increases the usability of the data in research, for instance in identifying key biodiversity areas, estimating biodiversity loss, and assessing efficiency of conservation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.