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Record W6967068991 · doi:10.5061/dryad.47d7wm3m0

Density data for Lake Erie benthic invertebrate assemblages from 1930 to 2019

2024· dataset· en· W6967068991 on OpenAlexaffabout

Bibliographic record

VenueOpen MIND · 2024
Typedataset
Languageen
FieldComputer Science
TopicSensor Technology and Measurement Systems
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsBenthic zoneInvertebrateTrophic levelTaxonBenthosAbundance (ecology)Fauna

Abstract

fetched live from OpenAlex

Benthic invertebrates are important trophic links in food webs and useful bioindicators of environmental conditions, but long-term benthic organism abundance data across broad geographic areas are rare, and historic data sets are often not readily accessible. This data set for a companion paper by Karatayev et al. (2022) provides densities of benthic macroinvertebrates collected from 1930 to 2019 during surveys in Lake Erie, a Laurentian Great Lake. The surveys were funded by the governments of the United States and Canada to investigate the status and changes in benthic community. From the total of 21 lake- and basin-wide benthic surveys conducted in Lake Erie from 1929 to 2019, we were able to acquire data for 17 surveys, including species-level data for 10 surveys and data by higher taxonomic groups for 7 surveys. Our amassed Lake Erie dataset includes data from 11 surveys (including 5 with species-level data) conducted in the western basin in 1930–2019, 7 surveys (6 with species-level data) in the central basin, and 8 surveys (7 with species-level data) in the eastern basin (1973–2019). This Lake Erie dataset represents the most extensive temporal dataset of benthic invertebrates available for any of the Laurentian Great Lakes. Benthic samples were collected using Ponar or Shipek bottom dredges and taxa densities were calculated as individuals per m2 using the area of the dredge. Density data are provided for taxa in the Annelida, Arthropoda, Mollusca, Cnidaria, Nemertea, and Platyhelminthes phyla. Current taxonomy was used for most groups, but in a few cases, older taxonomic names were used for consistency with historical data. Analysis of this dataset indicated that eutrophication, water quality improvement, and dreissenid introduction were the major drivers of changes in the benthic community in the western basin, while hypoxia was a major factor in the central basin, and dreissenid introduction was most important in the eastern basin. The previously diverse benthic community of the western basin has changed dramatically over 90 years, transitioning from a diverse benthic species assemblage indicative of good water quality in the 1930s to a one of low- diversity assemblage dominated by oligochaetes and other pollution-tolerant species in the 1960s, followed by recovery in the early 2000s to a state similar to that reported in 1930. In contrast, the central basin benthic community has over the past 60 years been consistently dominated by low oxygen-tolerant taxa, signifying the persistence of hypoxia. The eastern basin community changed dramatically in recent decades, with the disappearance of Diporeia after the introduction of Dreissena in the 1990s and more recent declines in oligochaetes, amphipods, gastropods, sphaeriid clams, and leeches. Considering the rarity of high taxonomic resolution long-term benthic data for lake ecosystems, this data set could be useful to explore broader aspects of ecological theory, including effects of eutrophication, hypoxia, invasive species, and other factors on community organization, phylogenetic and functional diversity, and spatial and temporal scales of variation in community structure. In addition, the data set could be useful for studies on individual species including abundance and distribution, species co-occurrence, and how the patterns of dominance and rarity change over space and time. Use of this data set for academic or educational purposes is encouraged. In doing so, we kindly request the data source be properly cited using the title of this dataset, the names of the authors, the year of publication, and the link to Dryad.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.052
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0100.003
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.016

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.108
GPT teacher head0.335
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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