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Record W3092828464 · doi:10.3389/fevo.2020.578524

Altering Neighborhood Relatedness and Species Composition Affects Interior Douglas-Fir Size and Morphological Traits With Context-Dependent Responses

2020· article· en· W3092828464 on OpenAlexafffund
Amanda K. Asay, Suzanne W. Simard, Susan A. Dudley

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsMcMaster UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIntraspecific competitionInterspecific competitionContext (archaeology)BiologyKin recognitionBiomass (ecology)BotanyEcology

Abstract

fetched live from OpenAlex

Trees often exist in a complex ecological system with many biological interactions. Here we examine kin interactions of Pseudotsuga menziesii var. glauca (interior Douglas-fir) both in the context of pure kin stands, in accordance with established plant kin selection and recognition studies, but also in combination with inter and intraspecific neighbors in order to observe how interactions may differ in a more complex system. Seedlings grown with kin neighbors (i.e. in stands that contained only kin) were significantly larger (biomass, height and root length) than those grown with any type of unrelated neighbor. However, of those with an unrelated neighbor, performance was better if that neighbor was interspecific (lodgepole pine rather than a stranger, or non-kin, Douglas-fir neighbor). Interestingly when Douglas-fir was grown in mixed stands, the four growth and four morphological traits of the seedlings examined paralleled neither pure stranger nor pure kin stands. This suggests that a mixed stand environment yielded cues that were uniquely different than either type of pure stand and that these seedlings are able to integrate that information and respond in a different way; for example, with increased early mycorrhizal fungal colonization. The morphological traits fine: coarse root allocation and slenderness (height relative to diameter) closely paralleled the seeding-size results, with the greatest values in pure kin stands. Whereas, fine root: needle allocation showed a kin response of less fine root allocation relative to needle mass compared to strangers, but kin seedlings had more fine root allocation when grown with a pine compared to a stranger Douglas-fir neighbor. We have demonstrated that the kin response in Douglas-fir is influenced by the complexity of the environment in which it grows, and this has significant effects on growth, morphology and mycorrhizal fungal colonization that may affect the success and resiliency of regeneration.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.411

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.193
Teacher spread0.186 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2020
Admission routes2
Has abstractyes

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