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Record W2133350802 · doi:10.1111/nph.12699

Interactions with soil biota shift from negative to positive when a tree species is moved outside its native range

2014· article· en· W2133350802 on OpenAlexaboutno aff
Michael J. Gundale, Paul Kardol, Marie‐Charlotte Nilsson, Richard W. Lucas, David A. Wardle

Bibliographic record

VenueNew Phytologist · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersSkogforsk
KeywordsBiotaRange (aeronautics)EcologyInvasive speciesTree (set theory)Environmental scienceBiologyBotanyMathematics

Abstract

fetched live from OpenAlex

Studies evaluating plant-soil biota interactions in both native and introduced plant ranges are rare, and thus far have lacked robust experimental designs to account for several potential confounding factors. Here, we investigated the effects of soil biota on growth of Pinus contorta, which has been introduced from Canada to Sweden. Using Swedish and Canadian soils, we conducted two glasshouse experiments. The first experiment utilized unsterilized soil from each country, with a full-factorial cross of soil origin, tree provenance, and fertilizer addition. The second experiment utilized gamma-irradiated sterile soil from each country, with a full-factorial cross of soil origin, soil biota inoculation treatments, tree provenance, and fertilizer addition. The first experiment showed higher seedling growth on Swedish soil relative to Canadian soil. The second experiment showed this effect was due to differences in soil biotic communities between the two countries, and occurred independently of all other experimental factors. Our results provide strong evidence that plant interactions with soil biota can shift from negative to positive following introduction to a new region, and are relevant for understanding the success of some exotic forest plantations, and invasive and range-expanding native species.

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 score0.222
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)0.0010.001

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 head0.017
GPT teacher head0.246
Teacher spread0.229 · 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

Citations112
Published2014
Admission routes1
Has abstractyes

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