MétaCan
Menu
Back to cohort
Record W2256035393 · doi:10.1071/wr15029

Precision, accuracy and bias of walked line-transect distance sampling to estimate eastern grey kangaroo population size

2015· article· en· W2256035393 on OpenAlex
Ruth Glass, David M. Forsyth, Graeme Coulson, Marco Festa‐Bianchet

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.

Bibliographic record

VenueWildlife Research · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaParks Victoria
KeywordsTransectDistance samplingSampling (signal processing)Abundance (ecology)PopulationAerial surveyEcologyGeographyAbundance estimationStatisticsPhysical geographyBiologyCartographyMathematicsDemography

Abstract

fetched live from OpenAlex

Context Distance sampling is widely used to estimate the size of wildlife populations, including kangaroos. However, the performance of distance-sampling abundance estimates has seldom been evaluated for wild mammal populations of known size. Aims We evaluated the precision, accuracy, bias and interval coverage of abundance estimates from walked line-transect sampling, a commonly used distance-sampling method, for a marked free-ranging population of eastern grey kangaroos (Macropus giganteus) at Yanakie Isthmus, Wilsons Promontory National Park, south-eastern Australia. Methods In each of two study periods (November 2012 and May 2013) we first determined the true size of the uniquely marked kangaroo population by conducting 10 intensive searches of the study area. We then conducted distance sampling along six systematically spaced line transects. We walked each transect four times in November 2012 and seven times in May 2013. Data were analysed using Program DISTANCE. Key results Our intensive searches revealed that 141 and 124 collared kangaroos were present in the study area in November 2012 and May 2013, respectively. When transects were walked four or more times (i.e. =400 observations), maximum precision (coefficient of variation; CV of ~13%) was achieved in both survey periods. Walking transects twice (i.e. ~200 observations) produced abundance estimates with CVs of <20% in each study period. The accuracy (root mean square error) of abundance estimates varied from 1 to 13 (November 2012) and from 3 to 28 (May 2013). Bias ranged from -9% to +23%, but stabilised at between -1% and -9% when transects were walked four or more times in each study period. The 95% confidence intervals for the abundance estimates always included the true population size. Conclusions Our results indicated that walked line-transect distance sampling is a precise and accurate method for estimating eastern grey kangaroo abundance. The small negative biases that occurred when sample sizes were large were likely to be due to some animals moving outside the study area. Implications Provided that the key design elements and assumptions are met, estimates of kangaroo abundance from walked line-transect distance sampling should have good precision (CV < 20%) and minimal (<10%) bias.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.009
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
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 science0.0000.000
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 head0.147
GPT teacher head0.403
Teacher spread0.256 · 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