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Record W2112868246 · doi:10.2980/i1195-6860-13-3-372.1

Local spatial pattern of two specialist beetle species (Ciidae) in the fruiting bodies of<i>Fomitopsis pinicola</i>

2006· article· en· W2112868246 on OpenAlexvenueno aff
Atte Komonen

Bibliographic record

VenueEcoscience · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
FundersAcademy of Finland
KeywordsQuadratSpatial distributionCommon spatial patternSpatial dispersionBiologyEcologyBotanyBorealTransectForestryGeographyPhysics

Abstract

fetched live from OpenAlex

:The spatial pattern in the occurrence of two congeneric beetle species in the fruiting bodies of the wood-decaying fungus Fomitopsis pinicola was studied in an old-growth boreal forest in eastern Finland. The aim was to characterize the spatial pattern of the common Cis glabratus (Coleoptera: Ciidae) and the rare C. quadridens. A 25-ha study area was divided into 25- × 25-m quadrats (n = 400), and all the dead and dying fruiting bodies of F. pinicola (n = 737) were taken to a laboratory to collect the two species living inside. The quadrat-based count data were analyzed using the Index of Dispersion (Id), the SADIE Index of Aggregation (Ia), and Moran’s I spatial correlograms. The frequency distribution of the quadrat counts of F. pinicola deviated from a random, Poisson distribution towards significant aggregation (Id). There was also a significant spatial autocorrelation (Moran’s I) at short (≤ 100 m) distances. The SADIE methodology, however, showed that there was no overall spatial structure in the arrangement of the counts of F. pinicola fruiting bodies, i.e., the observed quadrat counts were randomly distributed in the 25-ha study area. Similarly, the counts of the trees occupied by the two beetle species occurred randomly among the quadrats with fruiting bodies, and the pattern was consistent at all lag distances. These results indicate that both species can readily utilize available resources in the study area, despite their spatial location.

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 score0.075
Threshold uncertainty score0.999

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 head0.020
GPT teacher head0.211
Teacher spread0.191 · 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

Citations5
Published2006
Admission routes1
Has abstractyes

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