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Record W3115057276 · doi:10.1002/wat2.1506

Revisiting global trends in freshwater insect biodiversity

2020· article· en· W3115057276 on OpenAlexfundno aff
Sonja C. Jähnig, Viktor Baranov, Florian Altermatt, Peter S. Cranston, Juergen Geist, Fengzhi He, Jani Heino, Daniel Hering, Franz Hölker, Jonas Jourdan, Gregor Kalinkat, Jens Kiesel, Florian Leese, Alain Maasri, Michael T. Monaghan, Ralf B. Schäfer, Klement Tockner, Jonathan D. Tonkin, Sami Domisch

Bibliographic record

VenueWiley Interdisciplinary Reviews Water · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsnot available
FundersLeibniz-GemeinschaftBundesamt für NaturschutzBioFuelNet CanadaNational Science Foundation
KeywordsBiodiversityFreshwater ecosystemAbundance (ecology)Biomass (ecology)EcologyEcosystemMeta-analysisSelection (genetic algorithm)GeographyEnvironmental scienceBiologyEnvironmental resource management

Abstract

fetched live from OpenAlex

Abstract A recent global meta‐analysis reported a decrease in terrestrial but increase in freshwater insect abundance and biomass (van Klink et al., Science 368, p. 417). The authors suggested that water quality has been improving, thereby challenging recent reports documenting drastic global declines in freshwater biodiversity. We raise two major concerns with the meta‐analysis and suggest that these account for the discrepancy with the declines reported elsewhere. First, total abundance and biomass alone are poor indicators of the status of freshwater insect assemblages, and the observed differences may well have been driven by the replacement of sensitive species with tolerant ones. Second, many of the datasets poorly represent global trends and reflect responses to local conditions or nonrandom site selection. We conclude that the results of the meta‐analysis should not be considered indicative of an overall improvement in the condition of freshwater ecosystems. This article is categorized under: Water and Life > Conservation, Management, and Awareness

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0050.006
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.259
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

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

Citations72
Published2020
Admission routes1
Has abstractyes

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