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Record W4385441707 · doi:10.1111/nph.19164

Soil properties constrain predicted poleward migration of plants under climate change

2023· article· en· W4385441707 on OpenAlexafffund
Ming Ni, Mark Vellend

Bibliographic record

VenueNew Phytologist · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsClimate changeEnvironmental scienceSoil waterLatitudeEcologyHabitatSpecies distributionClimatologyAtmospheric sciencesSoil scienceGeographyGeologyBiology

Abstract

fetched live from OpenAlex

Many plant species are predicted to migrate poleward in response to climate change. Species distribution models (SDMs) have been widely used to quantify future suitable habitats, but they often neglect soil properties, despite the importance of soil for plant fitness. As soil properties often change along latitudinal gradients, higher-latitude soils might be more or less suitable than average conditions within the current ranges of species, thereby accelerating or slowing potential poleward migration. In this study, we built three SDMs - one with only climate predictors, one with only soil predictors, and one with both - for each of 1870 plant species in Eastern North America, in order to investigate the relative importance of soil properties in determining plant distributions and poleward shifts under climate change. While climate variables were the most important predictors, soil properties also had a substantial influence on continental-scale plant distributions. Under future climate scenarios, models including soil predicted much smaller northward shifts in distributions than climate-only models (c. 40% reduction). Our findings strongly suggest that high-latitude soils are likely to impede ongoing plant migration, and they highlight the necessity of incorporating soil properties into models and predictions for plant distributions and migration under environmental change.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.087
GPT teacher head0.270
Teacher spread0.183 · 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; both teacher heads agree on what is shown here.

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

Citations49
Published2023
Admission routes2
Has abstractyes

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