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Modelling Blow Fly (Diptera: Calliphoridae) Spatiotemporal Species Richness and Total Abundance Across Land-Use Types.
- Source :
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Insects (2075-4450) . Oct2024, Vol. 15 Issue 10, p822. 19p. - Publication Year :
- 2024
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Abstract
- Simple Summary: Geographic Information Systems provide the means to examine the distribution of insect species that recycle nutrients in our environment. Blow flies were trapped using liver-baited bottle traps across Windsor–Essex County (Ontario, Canada), with sites randomly chosen using geospatial mapping technology, and compared to land-use types. In the spring (mid-June), the number of blow fly species was lower near residential, commercial, wooded areas, roads, and wheat/corn fields, but higher near streams and tomato fields. Waste areas both increased and decreased the number of blow fly species, depending on whether land-use categories were considered at distances of 0.5, 1, or 2 km from the trapping site. In the summer (late August), the number of blow fly species was lower near roads, waste, and wheat/corn fields but higher near commercial, residential, orchards/vineyards, and streams. In both spring and summer, the highest overall number of blow flies were trapped near streams, orchards/vineyards, and specifically in summer, near sugar beets/other vegetable fields. This study provides baseline methods to examine blow fly use of different foods across time and space as influenced by humans, and initial insights into how our choices to modify the landscape impact the distribution of these important insects. Geographic Information Systems provide the means to explore the spatial distribution of insect species across various land-use types to understand their relationship with shared or overlapping spatiotemporal resources. Blow fly species richness and total fly abundance were correlated among six land-use types (residential, commercial, waste, woods, roads, and agricultural crop types) and distance to streams. To generate multivariate models of species richness and total fly abundance, blow fly trapping sites were chosen across the land-use gradient of Windsor–Essex County (Ontario, Canada) using a stratified random sampling approach. Sampling occurred in mid-June (spring), late August (summer), and late October (fall). Spring species richness correlated highest to residential (−), woods (−), distance to streams (+), and tomato fields (+) in models across all three land-use buffer scale distances (0.5, 1, 2 km), with waste (+/−), roads (−), wheat/corn (−), and commercial (−) correlating at only two of the three scales. Spring total fly abundance correlated with all but one land-use variable across all buffer scale distances, but the distance to streams (+), followed by orchards/vineyards (+) exhibited the greatest importance to these models. Summer blow fly species richness correlated with roads (−) and commercial (+) across all buffer distances, whereas at two of three buffer distances wheat/corn (−), residential (+), distance to streams (+), waste (−), and orchards/vineyards (+) were also important. Summer total fly abundance correlated to models with distance to streams (+), orchards/vineyards (+), and sugar beets/other vegetables (+) at the 2 km scale. Species richness and total abundance models at the 0.5 km buffer distance exhibited the highest correlation, lowest root mean square error, and similar prediction error to those derived at larger buffer distances. This study provides baseline methods and models for future validation and expansion of species-specific knowledge regarding adult blow fly relationships with spatiotemporal resources across land-use types and landscape features. [ABSTRACT FROM AUTHOR]
- Subjects :
- *STANDARD deviations
*GEOGRAPHIC information systems
*CROPS
*SUGAR beets
*BLOWFLIES
Subjects
Details
- Language :
- English
- ISSN :
- 20754450
- Volume :
- 15
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- Insects (2075-4450)
- Publication Type :
- Academic Journal
- Accession number :
- 180530282
- Full Text :
- https://doi.org/10.3390/insects15100822