ArticleAerobiologia2014
Gamma, Gaussian and logistic distribution models for airborne pollen grains and fungal spore season dynamics.
Article in Aerobiologia, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Estimating Daily Taxon-specific Tree Pollen at a 1-km Resolution in Atlanta, GA from 2020 to 2024.bioRxiv : the preprint server for biology · 2026Article
- Article
- The Clinical Utility of Pollen Counts.Clinical reviews in allergy & immunology · 2019Review
- Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing.International journal of biometeorology · 2017Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The characteristics of a pollen season, such as timing and magnitude, depend on a number of factors such as the biology of the plant and environmental conditions. The main aim of this study was to develop mathematical models that explain dynamics in atmospheric concentrations of pollen and fungal spores recorded in Rzeszów (SE Poland) in 2000-2002. Plant taxa with different characteristics in the timing, duration and curve of their pollen seasons, as well as several fungal taxa were selected for this analysis. Gaussian, gamma and logistic distribution models were examined, and their effectiveness in describing the occurrence of airborne pollen and fungal spores was compared. The Gaussian and differential logistic models were very good at describing pollen seasons with just one peak. These are typically for pollen types with just one dominant species in the flora and when the weather, in particular temperature, is stable during the pollination period. Based on
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Registered trials
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