Population ecology and community structure of mosquitoes (Diptera: Culicidae) across multiple periurban habitats in the West Island of Montreal, Quebec, Canada
Bibliographic record
Abstract
Globally, mosquitoes represent one of the most medically and economically important group of arthropods. Despite this, the ecology and distribution of mosquitoes is poorly understood in many parts of the world. The goal of this study was to examine mosquito population ecology and community structure across a variety of habitat types on the West Island of Montreal (Quebec, Canada) over a two year period (2014 & 2015). Mosquitoes were collected from 20 fixed sampling locations spanning suburban backyards, fields and forests with the use of LED EVS traps baited with CO2. Chapter 1 is a literature review examining work conducted locally and across North America and explores how habitat and climatic conditions shape species distributions and community structure. Chapter 2 examines spatial patterns of community structure as this relates to three broad periurban habitats. Chapter 3 analyses temporal aspects including; inter-annual community structure, phenology, and the effect of temperature and precipitation using a lag effect model.Our results demonstrate that different habitats produce distinct communities but these vary between years. Habitats with structural similarities have similar community structure. Forest and field habitat generate greater species diversity and abundance compared to suburban habitat. Species dominance is attributed to a few species that show consistency in habitat preference and timing of emergence. Timing of peak emergence and number of peaks for total mosquito abundance is variable between years. Temperature and precipitation may explain some of the observed patterns. These variables reveal biologically plausible patterns of association with mosquito abundance. Temperature seems to correlate with flight activity in the short term and precipitation may correlate with reproduction over longer periods. Detailed ecological studies of mosquito community structure can provide important baselines that can help to streamline surveillance and management programmes. Understanding the environmental drivers of mosquitoes allows for a better awareness of the nuisance potential and risk of mosquito-borne disease transmission, within Quebec and beyond.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".