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Record W3041349217 · doi:10.1080/11956860.2020.1772613

Microarthropod abundance and community structure along a chronosequence within the Tanana River floodplain, Alaska

2020· article· en· W3041349217 on OpenAlexvenueno aff
Robin N. Andrews, Roger W. Ruess

Bibliographic record

VenueEcoscience · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsChronosequenceEcologyAbundance (ecology)Ecological successionBalsamBasal areaSpecies richnessAlderBiologyBotany

Abstract

fetched live from OpenAlex

We investigated abundance and community structure of soil microarthropods in three stages of a primary successional chronosequence along the Tanana River in interior Alaska: early-successional alder stands, mid-successional balsam poplar stands and late successional white spruce stands. Microarthropod abundances in alder stands were uniformly low and tended to increase in balsam popular stands where abundances were highly variable among sites. White spruce stands had the highest abundances, almost 8 times those of alder sites. Arthropod taxon and Oribatida family richness also increased (alder: 29 taxa, 6 families; balsam poplar: 34 taxa, 10 families; white spruce: 40 taxa, 14 families). Non-metric multidimensional ordination of arthropod taxa indicated microarthropod communities became more similar within stand types later in succession and environmental fit of the site characteristics found organic matter thickness, soil degree days, organic layer phosphorus (P), mineral layer concentrations of carbon (C), nitrogen (N), and manganese (Mn), and white spruce basal area were significant (p < 0.05). Regression analysis indicated prey abundance and predator abundance were positively correlated (R2 = 0.43; p< 0.001). Our findings point to the importance of vegetation, soil development and temperature, site stability, microarthropod colonization time, and possibly predator abundance in shaping these microarthropod communities.

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 score0.109
Threshold uncertainty score0.892

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 studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.209
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

Citations2
Published2020
Admission routes1
Has abstractyes

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