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Record W2110672747 · doi:10.1139/z07-052

Habitat deterioration affects antipredatory behavior, body condition, and parasite load of female <i>Psammodromus algirus</i> lizards

2007· article· en· W2110672747 on OpenAlexvenueno aff
Luisa Amo, Pílar López, José Martı́n

Bibliographic record

VenueCanadian Journal of Zoology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersMinisterio de Economía y Competitividad
KeywordsPredationBiologyEcologyLizardHabitatPredatorLacertidaeSauriaAbundance (ecology)

Abstract

fetched live from OpenAlex

Deforestation may increase predation risk for prey because it may make prey more conspicuous and limit the number of refuges suitable to avoid predators. Therefore, prey may need to increase the magnitude of escape responses. However, excessive antipredatory effort might lead to a loss of body mass and a decrease in defense against parasites, with important consequences for short- and long-term fitness. We analyzed whether Psammodromus algirus (L., 1758) lizards that inhabit patches with different levels of deterioration of the vegetation within the same oak forest differed in relative abundance numbers, microhabitat use, antipredatory strategies, and health state. Results showed lizards selected similar microhabitats regardless of the level of deterioration of the vegetation and relative abundance of lizards was similar in both areas. However, habitat deterioration seemed to increase predation risk, at least for females, because they were detected at longer distances in deteriorated areas. Females seemed to adjust their antipredatory behavior accordingly to high risk of predation by increasing approach distances allowed to predators. The costs associated with frequent antipredatory displays might explain why females in deteriorated habitats had lower body condition and greater blood parasite loads than females in natural areas. This loss of body condition and increased parasitemia might have deleterious consequences for female fitness and therefore affect the maintenance of lizard populations in the long-term.

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 score0.394
Threshold uncertainty score0.959

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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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

Citations30
Published2007
Admission routes1
Has abstractyes

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