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Record W4401642562 · doi:10.1002/ldr.5268

Unveiling the influence of seawater intrusion and vegetation type on coastal arbuscular mycorrhizal fungal communities in China

2024· article· en· W4401642562 on OpenAlexfundno aff
Shilin Ma, Tao Li, Bo Zhang, Lu Zhai, Xin Liu, Jinchi Zhang

Bibliographic record

VenueLand Degradation and Development · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsChina Scholarship CouncilGovernment of Jiangsu ProvinceLakehead University
KeywordsVegetation (pathology)EcosystemEcologyBiodiversityEnvironmental scienceGlomeromycotaSalinityPlant communityBiologyEcological successionMycorrhizaSymbiosis

Abstract

fetched live from OpenAlex

Abstract Continuously rising sea levels pose severe threats to the diversity and stability of coastal ecosystems. However, the responses of endospheric and rhizospheric arbuscular mycorrhizal (AM) fungal communities to accelerated seawater intrusion and changing vegetation types unfortunately remains unknown. Such insights will assist in revealing the structure of AM fungi across different tidal zones, enabling the development of effective measures to conserve biodiversity. Here, we investigated changes in endospheric and rhizospheric AM fungal communities associated with four types of coastal vegetation in Dafeng City, Jiangsu Province, China, in response to sea level variations by analyzing their characteristics and connections to selected environmental factors. It was found that the AM fungal communities of coastal vegetation differed significantly in their compositions, diversity, and stability (the resilience or resistance of a community). Despite the responses of endospheric and rhizospheric AM fungi to soil environmental factors, the soil electrical conductivity, cation exchange content, and inorganic carbon were identified as core elements that influenced the characteristics of AM fungal communities between different coastal vegetation species. Lastly, the major endospheric and rhizospheric species of AM fungi were important predictors that explained much of the variation in the soil environment. Consequently, the dynamics of AM fungal communities were correlated with the plant–soil system under different conditions. Apart from the coastal vegetation species, the characteristics of AM fungal communities can also be driven by high salinity and the inorganic carbon content induced by the intrusion of seawater.

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 score0.073
Threshold uncertainty score0.133

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)0.0000.000

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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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