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Record W2155631325 · doi:10.2989/16085914.2011.559706

Aspects of population dynamics and feeding by piscivorous birds in the intermittently open Riet River estuary, Eastern Cape, South Africa

2011· article· en· W2155631325 on OpenAlexfundno aff
P. William Froneman, J D Blake, P. E. Hulley

Bibliographic record

VenueAfrican Journal of Aquatic Science · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
FundersRhodes UniversityCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorMcGill University
KeywordsCormorantCapeEstuaryForagingPopulationBiologyLittoral zoneEcologyHabitatFisheryGeographyPredationDemography

Abstract

fetched live from OpenAlex

Aspects of the population dynamics and feeding activity of piscivorous birds in the small (c. 5 ha) intermittently open Riet River estuary, on the south-eastern coastline of South Africa, were investigated monthly from August 2005 to July 2006. A total of 188 birds of 13 species were recorded, of which six were wading piscivores, four aerial divers and three were pursuit swimmers. The Reed Cormorant (Phalacrocorax africanus) was the numerically dominant species, with a mean of 8.25 (SD ± 7.90) individuals per count. Mean numbers of the Pied Kingfisher (Ceryle rudis) and Giant Kingfisher (Megaceryle maximus) were 3.42 (SD ± 1.20) and 1.17 (SD ± 0.60) individuals per count, respectively. The remaining 10 species revealed mean values <0.5 individuals per count. Breaching events were associated with a change in feeding groups from waders to pursuit feeders, and a decrease in total bird numbers, most likely due to loss of potential littoral zone foraging habitat for waders resulting from reduced water levels. The highest bird numbers were recorded in winter reflecting the migration of large numbers of Reed Cormorant into the system. Monthly food consumption by all piscivorous birds showed large temporal variability, ranging from 26.35 to 140.58 kg per month.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.221
Teacher spread0.194 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2011
Admission routes1
Has abstractyes

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