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Estimation of Body‐Size Traits by Photogrammetry in Large Mammals to Inform Conservation

2012· article· en· W1892444675 on OpenAlexaboutno aff
Joël Berger

Bibliographic record

VenueConservation Biology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsJuvenileTraitEstimationPhotogrammetryGeographySnowEcologyDemographyPhysical geographyBiologyRemote sensingComputer scienceSociology

Abstract

fetched live from OpenAlex

Photography, including remote imagery and camera traps, has contributed substantially to conservation. However, the potential to use photography to understand demography and inform policy is limited. To have practical value, remote assessments must be reasonably accurate and widely deployable. Prior efforts to develop noninvasive methods of estimating trait size have been motivated by a desire to answer evolutionary questions, measure physiological growth, or, in the case of illegal trade, assess economics of horn sizes; but rarely have such methods been directed at conservation. Here I demonstrate a simple, noninvasive photographic technique and address how knowledge of values of individual-specific metrics bears on conservation policy. I used 10 years of data on juvenile moose (Alces alces) to examine whether body size and probability of survival are positively correlated in cold climates. I investigated whether the presence of mothers improved juvenile survival. The posited latter relation is relevant to policy because harvest of adult females has been permitted in some Canadian and American jurisdictions under the assumption that probability of survival of young is independent of maternal presence. The accuracy of estimates of head sizes made from photographs exceeded 98%. The estimates revealed that overwinter juvenile survival had no relation to the juvenile's estimated mass (p < 0.64) and was more strongly associated with maternal presence (p < 0.02) than winter snow depth (p < 0.18). These findings highlight the effects on survival of a social dynamic (the mother-young association) rather than body size and suggest a change in harvest policy will increase survival. Furthermore, photographic imaging of growth of individual juvenile muskoxen (Ovibos moschatus) over 3 Arctic winters revealed annual variability in size, which supports the idea that noninvasive monitoring may allow one to detect how some environmental conditions ultimately affect body growth.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.258
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), 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

Citations52
Published2012
Admission routes1
Has abstractyes

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