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Record W4303859828 · doi:10.1111/ddi.13630

Migration‐based simulations for Canadian trees show limited tracking of suitable climate under climate change

2022· article· en· W4303859828 on OpenAlexaffabout
Laura Boisvert‐Marsh, John Pedlar, Sylvie de Blois, Amaël Le Squin, Kevin Lawrence, Daniel W. McKenney, Charlene Williams, Isabelle Aubin

Bibliographic record

VenueDiversity and Distributions · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsVineland Research and Innovation CentreUniversité de SherbrookeNatural Resources CanadaMcGill UniversityCanadian Forest Service
Fundersnot available
KeywordsBiological dispersalHabitatRange (aeronautics)Representative Concentration PathwaysSpecies distributionClimate changeEcologyEnvironmental sciencePhysical geographyClimatologyClimate modelGeographyGeologyBiologyPopulation

Abstract

fetched live from OpenAlex

Abstract Aim Species distribution models typically project climatically suitable habitat for trees in eastern North America to shift hundreds of kilometres this century. We simulated potential migration, accounting for various traits that affect species' ability to track climatically suitable habitat. Location Eastern Canada, covering ~3.7 million km 2 . Methods We simulated migration‐constrained range shifts through 2100 using a hybrid approach combining projections of climatically suitable habitat based on two Representative Concentration Pathways (RCP4.5, RCP8.5) for three time periods and two species distribution modelling approaches with process‐based models parameterized using data related to dispersal ability and generation time. We developed a unique “migration kernel” that uses seed dispersal traits and observed migration velocities to obtain kernel shape and dispersal probabilities for each tree species. We then calculated lags between the migration‐constrained range limits obtained through simulations and limits of climatically suitable habitat. Results All species demonstrated northward range shifts at the leading edge of their simulated distribution through 2100, but the magnitude and rate of that shift varied by species and time period. Climatically suitable habitat limits were found to be north of simulated distribution limits across both RCPs, with lags increasing through time. On average, simulated distribution that remained within climatically suitable habitat declined more under RCP8.5 than RCP4.5, with large areas of the rear edge of the simulated distribution becoming partially or completely climatically unsuitable for many species. Main conclusions Climatically suitable habitat limits projected for 2100 far exceeded migration‐constrained range limits for all 10 tree species, particularly for temperate species. This study underlines the limited extent to which tree species will track climate change via natural migration. Integrating observed migration velocities, seed dispersal and generation time with SDM outputs allows for more realistic evaluations of tree migration ability under climate change and may help orient forest conservation and restoration efforts.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient 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 score0.157
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.076
GPT teacher head0.252
Teacher spread0.175 · 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

Citations29
Published2022
Admission routes2
Has abstractyes

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