ArticleJournal of Great Lakes research2019
A reference inventory for aquatic fauna of the Laurentian Great Lakes.
Article in Journal of Great Lakes research, 2019. 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
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.
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.
- Long-term monitoring and remote sensing reveal waterbird colony collapses with rising lake levels and multiple stressors.Ecological applications : a publication of the Ecological Society of America · 2026Article
- Integrating invasive species risk assessment into environmental DNA metabarcoding reference libraries.Ecological applications : a publication of the Ecological Society of America · 2023Article
- Evaluating the performance of DNA metabarcoding for assessment of zooplankton communities in Western Lake Superior using multiple markers.Metabarcoding and metagenomics · 2021Article
- Comparison of Larval Fish Detections Using Morphology-Based Taxonomy versus High-Throughput Sequencing for Invasive Species Early Detection.Canadian journal of fisheries and aquatic sciences. Journal canadien des sciences halieutiques et aquatiques · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The Laurentian Great Lakes encompass an expansive and diverse set of freshwater ecosystems that contain a concordantly large and diverse vertebrate and invertebrate fauna. Although numerous publications exist concerning the composition and distribution of this fauna, there is at present no single readily available resource that brings all this information together. Here, we present and describe the compilation process for a comprehensive Great Lakes aquatic fauna inventory covering fishes, reptiles, amphibians, zooplankton, mollusks, annelids, insects, mites, and various other aquatic invertebrates. Inventory entries were developed via an extensive search of literature and internet sources and are attributed with detailed nomenclature information, general lake and habitat occurrences, and supporting citations and links to life history and genetic marker information. The inventory scope is the Laurentian Great Lakes proper and their connecting rivers, and their fringing coastal wetlands and lower tributaries. Over 2200 unique taxa are contained in the inventory -- 85% resolved to species and 14% to genus. The listing substantially expands previous richness estimates for invertebrates in the Great Lakes, but taxonomic resolution and spatial distribution information for them remains quite uneven. Example pattern analyses for fauna in this inventory show that aquatic vertebrates are generally more widely distributed than invertebrates, and that biodiversity is concentrated in the coastal margins. The inventory is being packaged into a public, searchable database that showcases the biodiversity of the Great Lakes aquatic fauna and can assist the research and management community in their biological investigations.
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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.