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Distribution of unionid freshwater mussels depends on the distribution of host fishes on a regional scale

2012· article· en· W1969703553 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDiversity and Distributions · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsUniversity of GuelphFisheries and Oceans CanadaUniversity of Waterloo
FundersFisheries and Oceans CanadaRural Development AdministrationMinistry of Natural Resources
KeywordsMusselEcologyUnionidaeWatershedBiologySpatial distributionSpecies distributionFisheryGeographyHabitatBivalviaMollusca

Abstract

fetched live from OpenAlex

Abstract Aim The successful conservation of endangered mussel communities requires, in part, a thorough understanding of the processes that shape their distribution. Therefore, we tested the prediction that (1) the distribution of host fishes explains a significant amount of variation in mussel community composition. In addition, because mussel distribution also depends on spatial processes and environmental variables, we predicted that (2) the distribution and community composition of mussels in Ontario varies across eight contiguous watersheds, flowing into three different basins of the Great Lakes (Huron, St. Clair and Erie); and (3) environmental variables also explain part of the mussel distribution. Location Watersheds in south‐western Ontario, North America, Great Lakes Region. Methods Existing data on the distribution of mussels and fishes, and environmental and spatial information were compiled. Variation partitioning with redundancy analysis was used to examine what proportion of the variation in mussels' community composition was explained by watershed (as a spatial component), environmental differences and host fish presence. Redundancy analysis for mussel abundances was used to illustrate the similarities in the distributions of mussels and fishes, and the association of differences in community composition of mussels among watersheds with certain mussel species and environmental variables. Results Host fish presence explained 44%, watershed identity 28% and environmental factors 23% of the variation in mussel species composition. However, much of the explained variation was shared among these components, and all three components together explained 55% of the total variation in species composition. Even after statistically eliminating the other explanatory variables, host fish distribution was the most important group of predictor variables, although we used a subset of relevant environmental variables because of the scale of the study. Main conclusions Our results highlight the important role played by host fishes in shaping current distributions of freshwater mussels and underscore the necessity of incorporating these relationships in conservation efforts and management actions.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.026
GPT teacher head0.215
Teacher spread0.189 · 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