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Record W4390106358 · doi:10.1111/oik.10474

Multiple dimensions of phylogenetic diversity are needed to explain the complex aboveground–belowground diversity relationships

2023· article· en· W4390106358 on OpenAlexaff
Xiaorong Lu, Marc W. Cadotte, Pandeng Wang, Shan Rao, Xiaoye Shi, Siyuan Ren, Xihua Wang, Shaopeng Li

Bibliographic record

VenueOikos · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsSpecies richnessPhylogenetic diversityPhylogenetic treeBiodiversityEcologyBiologyDivergence (linguistics)Species diversityGamma diversityAlpha diversityDiversity (politics)Phylogenetics

Abstract

fetched live from OpenAlex

The complex relationship between aboveground and belowground diversity and whether they act as surrogates for one another remains unresolved. Increasing evidence suggests that investigating phylogenetic diversity could provide valuable insights into the interplay between plants and soil microbes, but the proliferation of phylogenetic diversity metrics has hindered comparative studies and the identification of general patterns. To overcome this challenge, we implemented a multi‐dimensional framework that classifies phylogenetic diversity metrics into three dimensions: richness, divergence, and regularity, each of which captures different ecological aspects of species differences. Then we applied this framework to investigate the relationship between above and belowground diversity in a subtropical forest in eastern China. We found that phylogenetic diversity of plant and soil microbes, including bacteria and fungi, were more strongly correlated at the richness and regularity dimensions compared with divergence dimension. Further analyses revealed that these observed correlation patterns align with variations in soil total phosphorus content, a key factor influencing both plant and microbial phylogenetic diversity at richness and regularity dimensions. Together, our study demonstrated the necessity of using a multi‐dimensional approach to advance our understanding of the complex relationships between plant and soil microbial biodiversity.

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 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 score0.160
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
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.084
GPT teacher head0.231
Teacher spread0.147 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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