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Record W2004680489 · doi:10.1139/z09-108

Factors influencing large-scale distribution of two sister species of pine voles (Microtus lusitanicus and Microtus duodecimcostatus): the importance of spatial autocorrelation

2009· article· en· W2004680489 on OpenAlexvenueno aff
Sara Santos, António Mira, María da Luz Mathias

Bibliographic record

VenueCanadian Journal of Zoology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsBiologyMicrotusVoleEcologySpatial distributionEcotoneGrasslandHabitatPopulationGeography

Abstract

fetched live from OpenAlex

The Lusitanian pine vole ( Microtus lusitanicus (Gerbe, 1879)) and the Mediterranean pine vole ( Microtus duodecimcostatus de Selys-Longchamps, 1839) are sister species with burrowing habits and a restricted European distribution. Our aim was to assess the relative effect of environmental, soil, and spatial characteristics on the distribution of these species in Portugal, and obtain predicted occurrence maps for each species, particularly to identify areas of sympatry. We used spatial eigenvector mapping (SEVM) to describe the spatial autocorrelation in species data, and we partitioned the variance in species distributions to quantify the relative effects of environmental, soil, and spatial characteristics. The spatial variables explained the major part of variability in both species distributions and were more important than environmental or soil variables. The Lusitanian pine vole occurs in areas outside landscape units of grassland, higher rainfall, frost, and cambisols, with mostly acid soils, lower abundance of litosols, and presence of solonshaks. The Mediterranean pine vole is distributed in grassland areas within intermediate values of soil pH, dominated by litosols and luvisols, and lower rainfall, frost, and cambisols. Our results showed disjunct sympatric areas of small size and a parapatry boundary for the centre of Portugal, suggesting that contact zones are probably narrow.

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 score0.093
Threshold uncertainty score0.921

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 head0.011
GPT teacher head0.227
Teacher spread0.215 · 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

Citations19
Published2009
Admission routes1
Has abstractyes

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