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Prediction of Parasite Infection Dynamics in Primate Metapopulations Based on Attributes of Forest Fragmentation

2006· article· en· W2059296245 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConservation Biology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMcGill University
FundersNational Science Foundation
KeywordsMetapopulationBiologyFragmentation (computing)EcologySpecies richnessParasite hostingHabitat fragmentationHabitatBiological dispersalPopulation

Abstract

fetched live from OpenAlex

Although the effects of forest fragmentation on species and ecological processes have been the focus of considerable research in conservation biology, our capacity to predict how processes will be altered and which taxonomic or functional groups will be most affected by fragmentation is still poor. This problem is exacerbated by inherent temporal and spatial variability in fragment attributes. To improve our understanding of this interplay, we examined how various fragment attributes affect one potentially important ecological process, parasite infection dynamics, and considered how changes in this process affect host metapopulations. From August 1999 to July 2003 we surveyed red colobus (Piliocolobus tephrosceles) metapopulations inhabiting nine fragments (1.2 to 8.7 ha) in western Uganda to determine the prevalence and richness of strongyle and rhabditoid nematodes, a group of potentially pathogenic gastrointestinal parasites. We used noninvasive fecal flotation and sedimentation (n = 536) to detect parasite eggs, cysts, and larvae in colobus fecal samples. To obtain an index of infection risk, we determined environmental contamination with Oesophagostomum sp., a representative strongyle nematode, in canopy (n = 30) and ground vegetation plots (n = 30). Concurrently, physical (i.e., size, location, and topography) and biological (i.e., tree diversity, tree density, stump density, and colobine density) attributes were quantified for each fragment. Interfragment comparisons of nine potential factors demonstrated that an index of degradation and human presence (tree stump density) strongly influenced the prevalence of parasitic nematodes. Infection risk was also higher in the fragment with the highest stump density than in the fragment with the lowest stump density. These results demonstrate that host-parasite dynamics can be altered in complex ways by forest fragmentation and that intensity of extraction (e.g., stump density) best explains these changes.

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.

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 score0.123
Threshold uncertainty score0.553

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 head0.020
GPT teacher head0.250
Teacher spread0.230 · 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