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Record W1927459645 · doi:10.22621/cfn.v117i4.823

An Aerial Survey Technique for the Forest-Dwelling Ecotype of Woodland Caribou, <em>Rangifer tarandus caribou</em>

2003· article· en· W1927459645 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Canadian Field-Naturalist · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsCenter for Northern StudiesUniversité du Québec à RimouskiMinistère des Ressources naturelles et des Forêts
Fundersnot available
KeywordsWoodland caribouAerial surveyGeographyVital ratesPopulationConfidence intervalTransectForestryEcologyEnvironmental scienceBiologyHabitatDemographyStatisticsCartographyMathematicsPopulation growth

Abstract

fetched live from OpenAlex

Accurate and precise population estimates for the forest-dwelling ecotype of Woodland Caribou (Rangifer tarandus caribou) are very difficult to obtain because these Caribou are found at very low densities and in small herds dispersed over large areas. In order to suggest a standardized method, data from aerial surveys conducted in 1991 and 1993 (12 000 km2 blocks) were used to simulate various survey scenarios. Simulations showed that all the major groups of Caribou would have to be found and counted to obtain a confidence interval of ± 20% (α = 0.10). We tested this technique in a survey carried out in winter 1999 in a 42 539 km2 study site, opting for a total coverage carried out in two phases. In phase one, we used an airplane, flying north-south transects spaced 2.1 km apart so as to detect most Caribou track networks. In phase two, a helicopter was used to count and determine the sex and age classes (calves/adults) of Caribou found in phase one. Using 20 radio-collared Caribou, the visibility rate of Caribou groups (phase one) and that of Caribou within the groups (phase two) were estimated at 0.90 and 0.94 respectively for an overall rate of 0.85 (SE = 0.08; α = 0.10). The corrected density was estimated at 1.6 Caribou per 100 km2 with a 15% confidence interval (α = 0.10). The survey cost approximately $4/km2, which is lower than that of two previous surveys ($7/km2). Two main factors contributed to diminish costs: (1) the use of long-range airplanes (5-7 hours flying range) in phase one to minimize travel between the airports and the study site, and (2) the use of helicopters only in phase two for counting and determining the age and sex of the Caribou.Il est très difficile d’obtenir des estimations de population exactes et précises pour l’écotype forestier du Caribou des bois (Rangifer tarandus caribou) parce qu’on le retrouve en très faibles densités et qu’il est distribué en petites hardes réparties sur de vastes superficies. Les résultats de deux inventaires aériens réalisés en 1991 et 1993 (12 000 km2) ont été utilisés pour simuler divers scénarios d’inventaire afin de suggérer une méthode standardisée. Les simulations ont montré qu’il fallait trouver et recenser tous les groupes principaux pour obtenir un intervalle de confiance de ± 20 % (α = 0,10). Nous avons testé cette approche dans un site d’étude de 42 539 km2 où nous avons opté pour un plan en deux phases. En phase un, l’avion a été utilisé pour couvrir totalement le site d’étude selon des virées équidistantes de 2,1 km afin de détecter la plupart des réseaux de pistes. L’hélicoptère fut utilisé en phase deux pour dénombrer et sexer les Caribous dans les réseaux de pistes détectés en phase un. D’après 20 Caribous munis de colliers émetteurs, le taux de visibilité global était de 0,85 (SE = 0,08; α = 0,10), soit 0,90 en phase 1 et 0,94 en phase 2. La densité corrigée était de 1,6 Caribou par 100 km2 avec une erreur relative de 15 % (α = 0,10). L’inventaire a coûté 4 $/km2, ce qui est inférieur aux montants investis lors des inventaires antérieurs (7 $/km2). La diminution des coûts est attribuable à deux facteurs principaux : (1) l’utilisation d’avions à grand rayon d’action (5-7 heures d’autonomie) pour minimiser les déplacements en phase un; (2) l’emploi d’hélicoptères exclusivement pour le dénombrement et le sexage des caribous.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.315
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.238
Teacher spread0.218 · 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