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Record W1989062892 · doi:10.1177/0309133308094081

Impacts of climate change on species, populations and communities: palaeobiogeographical insights and frontiers

2008· article· en· W1989062892 on OpenAlexaff
Glen M. MacDonald, K. D. Bennett, Stephen T. Jackson, Laura Parducci, Felisa A. Smith, John P. Smol, Katherine J. Willis

Bibliographic record

VenueProgress in Physical Geography Earth and Environment · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsQueen's University
Fundersnot available
KeywordsClimate changeEcologyBiosphereGeographyCenozoicPopulationBiodiversityPaleoclimatologyEnvironmental changeQuaternaryBiologyPaleontology

Abstract

fetched live from OpenAlex

Understanding climate change and its potential impact on species, populations and communities is one of the most pressing questions of twenty-first-century conservation planning. Palaeobiogeographers working on Cenozoic fossil records and other lines of evidence are producing important insights into the dynamic nature of climate and the equally dynamic response of species, populations and communities. Climatic variations ranging in length from multimillennia to decades run throughout the palaeo-records of the Quaternary and earlier Cenozoic and have been shown to have had impacts ranging from changes in the genetic structure and morphology of individual species, population sizes and distributions, community composition to large-scale bio-diversity gradients. The biogeographical impacts of climate change may be due directly to the effects of alterations in temperature and moisture on species, or they may arise due to changes in factors such as disturbance regimes. Much of the recent progress in the application of palaeobiogegraphy to issues of climate change and its impacts can be attributed to developments along a number of still advancing methodological frontiers. These include increasingly finely resolved chronological resolution, more refined atmosphere-biosphere modelling, new biological and chemical techniques in reconstructing past species distributions and past climates, the development of large and readily accessible geo-referenced databases of biogeographical and climatic information, and new approaches in fossil morphological analysis and new molecular DNA techniques.

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)0.002
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0010.003
Scholarly communication0.0020.005
Open science0.0000.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.231
Teacher spread0.204 · 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
GenreReview

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

Citations101
Published2008
Admission routes1
Has abstractyes

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Same venueProgress in Physical Geography Earth and EnvironmentSame topicSpecies Distribution and Climate ChangeFrench-language works237,207