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Record W3048448154 · doi:10.1111/mam.12210

Modelling the spatial distribution of selected North American woodland mammals under future climate scenarios

2020· article· en· W3048448154 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMammal Review · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWoodlandClimate changeRange (aeronautics)Species distributionBiodiversityEcologyGeographyHabitatClimate modelEnvironmental niche modellingEcological nicheBiology

Abstract

fetched live from OpenAlex

Abstract North America has a diverse array of mammalian species. Model projections indicate significant variations in future climate conditions of North America, and the habitats of woodland mammals of this continent may be particularly sensitive to changes in climate. We report on the potential spatial distributions of 13 wide‐ranging, relatively common species of North American woodland mammals under future climate scenarios. We examined the potential influence of the mean and seasonal climate variables on the distribution of species. Presence‐only occurrence records of species, four predictor variables, two future climate scenarios (Representative Concentration Pathways 4.5 and 8.5), and two time steps (current and 2070) were used to build species’ distribution models using a maximum entropy algorithm (MaxEnt). Our results suggested that overall, 11 of the 13 species are likely to gain climatically suitable space (regions where climate conditions will be similar to those of area currently occupied) at the continental scale, but American marten Martes americana and ‘woodland’ caribou Rangifer tarandus are likely to lose suitable climate range by 2070. Furthermore, climate space is likely to be expanding northwards under future climate scenarios for most of the mammals, and many jurisdictions in the border region between Canada and the USA are likely to lose iconic species, such as moose Alces alces . We identified regions as potential in situ and ex situ climate change refugia, which are increasingly considered to be important for biodiversity conservation. The model results suggest significant implications for conservation planning for the 13 mammalian species under global climate change, especially at fine spatial scales. Numerous species that are presently common at their southern range edge will be functionally or completely extirpated in 50 years. The potential in situ and ex situ climate change refugia could provide an effective support for adaptive strategies aimed at species conservation planning.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0060.000

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 head0.242
Teacher spread0.215 · 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