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Record W3123550459 · doi:10.1111/ibi.12931

Knowledge gaps and biases in the Pantanal indicate future directions for ornithological research in large wetlands

2021· article· en· W3123550459 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIbis · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsWetlandOrnithologyEcologyBiodiversityThreatened speciesGeographySpecies richnessAbundance (ecology)Bird conservationEcosystemBiologyHabitatSouthern Hemisphere

Abstract

fetched live from OpenAlex

While taxonomic and biogeographical biases are often acknowledged, those for certain biological responses and species traits are routinely overlooked, generating major gaps in knowledge and conservation of biodiversity. Biases in research on birds ‒ an over‐sampled, diverse vertebrate class ‒ may be readily detectable, and wetlands are important species‐rich ecosystems in which to identify biases and research gaps for birds. The Pantanal, one of the world’s largest wetlands, is globally relevant for bird conservation. In this wetland, we determined spatial, temporal, taxonomic and biological response‐related biases in ornithological studies to guide future research in this ecosystem and, ultimately, in major global wetlands. Avian research was geographically biased, with 61 studies conducted in the Brazilian Pantanal and only one in Bolivia. Most studies were concentrated near urban centres, with poorly explored areas in the central Pantanal. Research was also over‐represented during the dry season when field conditions are more favourable, but such temporal bias may hamper migration studies. Considering their richness, some families were studied disproportionately more (e.g. Jacanidae) or less (e.g. Tyrannidae). Some species (e.g. Wood Stork Mycteria americana and Yellow‐billed Cardinal Paroaria capitata ) were included in > 25% of studies, whereas a relatively low number of threatened bird species were studied. Behaviour was the most studied response, followed by abundance and reproduction, which were considered for > 65% of species studied. We conclude that further research needs to be focused on unexplored areas and periods, less detectable species, and ecological processes (e.g. interspecific interactions). Additionally, our results can provide useful information to better address future work and bird conservation actions in other large wetlands. For example, major gaps detected here constitute a primary roadmap to guide research in under‐sampled regions, such as the Canadian peatlands and Tonlé Sap Lake. Specifically, more studies on waterbirds in highly diverse wetlands from low‐income countries (e.g. Okavango and Sundarban Delta) may help to disentangle the essential functional role provided for these species and to prioritize conservation actions in regions with limited research capacity.

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)0.001
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 score0.052
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.084
GPT teacher head0.355
Teacher spread0.271 · 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