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Record W2886408554 · doi:10.1002/ecs2.2345

Spatial heterogeneity in the abundance and fecundity of Arctic mosquitoes

2018· article· en· W2886408554 on OpenAlexfundno aff
Lauren E. Culler, Matthew P. Ayres, Ross A. Virginia

Bibliographic record

VenueEcosphere · 2018
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersDartmouth CollegeArctic Institute of North AmericaNational Science Foundation
KeywordsEcologyAbundance (ecology)BiologyTundraFecundityHabitatArcticAbiotic componentRange (aeronautics)PopulationMosquito control

Abstract

fetched live from OpenAlex

Abstract The abundance of mosquitoes is strongly influenced by biotic and abiotic factors that act on the immature (aquatic) and adult (terrestrial) life stages. Rapid changes in land use and climate, which impact aquatic and terrestrial mosquito habitat, necessitate studying the ecological mechanisms, and their interplay with the changing environment, that affect mosquito abundance. These data are crucial for anticipating how environmental change will impact their roles as pests, disease vectors, and in food webs. We studied a population of Arctic mosquitoes ( Aedes nigripes , Diptera: Culicidae) in western Greenland, a region experiencing rapid environmental change, to quantify spatial variation in adult abundance and reproduction. Using sweep nets, we collected about sevenfold more mosquitoes within the town of Kangerlussuaq and within a low‐elevation tundra valley compared to three other tundra locations. Dissections of adult female mosquitoes revealed that only 17% were gravid overall, with a range of 7–43% among sites. If gravid, mosquitoes matured an average of 60 eggs per individual—more in larger females. We found no indication of autogenous egg development. Analyses using our field data indicated that spatial variation in adult fecundity and survival of immatures could each account for a 10‐fold range in the per capita growth of mosquito populations. The availability of vertebrate hosts and aquatic habitat is changing in many parts of the Arctic and can be expected to influence Arctic mosquito abundance. In the Arctic, and elsewhere, life‐history data from natural populations of mosquitoes will significantly aid in understanding controls on the abundance of these globally ubiquitous insects.

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 score0.112
Threshold uncertainty score0.523

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 head0.010
GPT teacher head0.272
Teacher spread0.262 · 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

Citations13
Published2018
Admission routes1
Has abstractyes

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