ArticleScientific data2024
Geolocated fish spawning habitats.
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 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
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Who cites it
2 citing papers in PubMed.
- Global microplastic pollution poses a disproportionate reproductive threat to critically endangered marine fishes.Environmental science and ecotechnology · 2026Article
- Geolocated fish spawning habitats.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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fish spawning locations are a crucial input into fisheries management and conservation plans, and many stocks are especially sensitive to the environmental conditions within these localized zones. Globally collated data on spawning locations across many species has been unavailable, hindering global stock assessments and analyses of sustainable development and global environmental change. To address this, we created a geocoded fish spawning dataset using qualitative spawning information from FishBase and Science and Conservation of Fish Aggregations (SCRFA). We cleaned and geocoded the spawning locations of 1,045 marine fish species into 2,931 regions. Each spawning region is defined by one or more polygons, and most spawning regions are associated with spawning months. The resulting dataset covers oceans globally. This dataset will be useful to scientists studying marine fish population dynamics and their interactions with the physical environment on regional to large scales.
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