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Record W7065400327

Double-Crested Cormorant Colony Effects on Soil Chemistry, Vegetation Structure and Avian Diversity in a Southeastern Reservoir System

2019· article· en· W7065400327 on OpenAlexaboutno aff

Bibliographic record

VenueUtah State Research and Scholarship (Utah State University) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsCormorantVegetation (pathology)Temperate forestHabitatTemperate rainforestTemperate climateNest (protein structural motif)CanopySpecies diversity
DOInot available

Abstract

fetched live from OpenAlex

Ornithogenic material delivered by Double-crested Cormorants (Phalacrocorax auritus) from their nesting colonies have been documented to effect vegetation, soil chemistry and tree and plant health in the northern breeding grounds of Canada and the United States (U.S.). However, little work has been done on impacts to avian communities or in temperate forest ecosystems. We compared soil chemistry, vegetation and tree structure and diversity and effects on avian communities among colony islands, uninhabited islands and abandoned colony islands within Guntersville Reservoir, a temperate forest ecosystem. Concentrations of potassium (K), phosphorus (P) and nitrate (NO3-) in soil were negatively related to cormorant use, while tree diversity was lower on historic (tree mean = 4.35 ± 2.46 species) and colony (tree mean = 3.91 ± 3.12 species) islands relative to control islands (tree mean = 9.11 ± 3.88 species). Canopy cover was less (min: < 20%), and midstories denser on colony and historic islands relative to control islands. Avian diversity was lower for colony islands (mean = 6 ± 3 species) than both control (11 ± 7 species) and historic (10 ± 7 species) islands. These effects of cormorant nesting can be seen even after 10 years of colony abandonment supporting that cormorants can have long-term effects on insular habitats even in temperate forest ecosystems.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.025
GPT teacher head0.258
Teacher spread0.233 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2019
Admission routes1
Has abstractyes

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