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Record W2784805535 · doi:10.1126/science.aam9712

Moving in the Anthropocene: Global reductions in terrestrial mammalian movements

2018· article· en· W2784805535 on OpenAlexaff
Marlee A. Tucker, Katrin Böhning‐Gaese, William F. Fagan, John M. Fryxell, Bram Van Moorter, Susan C. Alberts, Abdullahi H. Ali, Andrew M. Allen, Nina Attias, Tal Avgar, Hattie L. A. Bartlam‐Brooks, Jerrold L. Belant, Alessandra Bertassoni, Dean E. Beyer, Laura R. Bidner, Floris M. van Beest, Stephen Blake, Niels Blaum, Chloe Bracis, Danielle Brown, P J Nico de Bruyn, Francesca Cagnacci, Justin M. Calabrese, Constança Camilo-Alves, Simon Chamaillé‐Jammes, André Chiaradia, Sarah C. Davidson, Todd E. Dennis, Stephen DeStefano, Duane R. Diefenbach, Iain Douglas‐Hamilton, Julian Fennessy, Claudia Fichtel, Wolfgang Fiedler, Christina Fischer, Ilya R. Fischhoff, Christen H. Fleming, Adam T. Ford, Susanne A. Fritz, Benedikt Gehr, Jacob R. Goheen, Eliezer Gurarie, Mark Hebblewhite, Marco Heurich, A. J. Mark Hewison, Christian Hof, Edward Hurme, Lynne A. Isbell, René Janssen, Florian Jeltsch, Petra Kaczensky, Adam Kane, Peter M. Kappeler, Matthew J. Kauffman, Roland Kays, Duncan M. Kimuyu, Flávia Koch, Bart Kranstauber, Scott LaPoint, Peter Leimgruber, John D. C. Linnell, Pascual López‐López, A. Catherine Markham, Jenny Mattisson, Emília Patrícia Medici, Ugo Mellone, Evelyn H. Merrill, Guilherme Mourão, Ronaldo Gonçalves Morato, Nicolas Morellet, Thomas A. Morrison, Samuel L. Díaz‐Muñoz, Atle Mysterud, Nandintsetseg Dejid, Ran Nathan, Aidin Niamir, John Oddén, Robert B. O’Hara, Luiz Gustavo Rodrigues Oliveira‐Santos, Kirk A. Olson, Bruce D. Patterson, Rogério Cunha de Paula, Luca Pedrotti, Björn Reineking, Martin Rimmler, Tracey L. Rogers, Christer M. Rolandsen, Christopher S. Rosenberry, Daniel I. Rubenstein, Kamran Safi, Sonia Saı̈d, Nir Sapir, Hall Sawyer, Niels Martin Schmidt, Nuria Selva, Agnieszka Sergiel, Enkhtuvshin Shiilegdamba, João Paulo Silva, Navinder J. Singh, Erling J. Solberg, Orr Spiegel, Olav Strand, Siva R. Sundaresan, Wiebke Ullmann, Ulrich Voigt, Jake Wall, David W. Wattles, Martin Wikelski, Christopher C. Wilmers, John W. Wilson, George Wittemyer, Filip Zięba, Tomasz Zwijacz‐Kozica, Thomas Mueller

Bibliographic record

VenueScience · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of LethbridgeUniversity of AlbertaUniversity of Guelph
FundersDivision of Biological InfrastructureUniversity of California, DavisNorges ForskningsrådDeutsche ForschungsgemeinschaftRobert Bosch StiftungLeverhulme TrustAmerican Society of MammalogistsDivision of Environmental BiologyIrish Research CouncilEuropean CommissionLeakey FoundationAgence Nationale de la RechercheNational Aeronautics and Space AdministrationMinisterio de Economía y CompetitividadNational Science Foundation
KeywordsAnthropoceneEnvironmental scienceGeographyEnvironmental ethicsAstrobiologyEarth scienceGeologyBiologyPaleontologyPhilosophy

Abstract

fetched live from OpenAlex

Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.282
Teacher spread0.266 · 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

Citations1,287
Published2018
Admission routes1
Has abstractyes

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