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Record W2981559613 · doi:10.1038/s41598-019-51884-5

Longest terrestrial migrations and movements around the world

2019· article· en· W2981559613 on OpenAlexaff
Kyle Joly, Eliezer Gurarie, Mathew S. Sorum, Petra Kaczensky, Matthew D. Cameron, Andrew F. Jakes, Bridget L. Borg, Nandintsetseg Dejid, J. Grant C. Hopcraft, Bayarbaatar Buuveibaatar, Paul F. Jones, Thomas Mueller, Chris Walzer, Kirk A. Olson, John C. Payne, Adiya Yadamsuren, Mark Hebblewhite

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsAlberta Conservation Association
FundersNational Park ServiceZoologische Gesellschaft FrankfurtEcological Society of AmericaMassachusetts Department of Fish and GameAlaska Department of Fish and GameWildlife Conservation SocietyBritish Ecological SocietyU.S. Department of the InteriorAustrian Science FundNational Aeronautics and Space AdministrationU.S. Fish and Wildlife ServiceEuropean CommissionNational Science Foundation
KeywordsGuildPredationHerbivoreGeographyTrophic levelEcologyHabitatBiology

Abstract

fetched live from OpenAlex

Long-distance terrestrial migrations are imperiled globally. We determined both round-trip migration distances (straight-line measurements between migratory end points) and total annual movement (sum of the distances between successive relocations over a year) for a suite of large mammals that had potential for long-distance movements to test which species displayed the longest of both. We found that caribou likely do exhibit the longest terrestrial migrations on the planet, but, over the course of a year, gray wolves move the most. Our results were consistent with the trophic-level based hypothesis that predators would move more than their prey. Herbivores in low productivity environments moved more than herbivores in more productive habitats. We also found that larger members of the same guild moved less than smaller members, supporting the 'gastro-centric' hypothesis. A better understanding of migration and movements of large mammals should aid in their conservation by helping delineate conservation area boundaries and determine priority corridors for protection to preserve connectivity. The magnitude of the migrations and movements we documented should also provide guidance on the scale of conservation efforts required and assist conservation planning across agency and even national boundaries.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.999

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)0.0020.000

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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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.

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

Citations161
Published2019
Admission routes1
Has abstractyes

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