Environmental heterogeneity across an urban gradient influences detritus and nutrients within artificial containers and their associated vector Aedes sp. larvae in San Juan, Puerto Rico
Data files
Apr 25, 2025 version files 9.41 KB
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SJMA_gradient_and_containers.csv
9.41 KB
Abstract
Detrital inputs from the surrounding terrestrial environment provide essential nutrients that sustain mosquito populations in aquatic containers. The larvae of Aedes aegypti often develop in artificial habitats in urban areas but little is known about how that environment shapes their life history or phenotypic traits. We sampled mosquito larvae, container detritus, and suspended particulate organic matter in 44 locations across the San Juan Metropolitan Area urban gradient in Puerto Rico. We characterized the surrounding environment in terms of land cover, land use, and vegetation α diversity. We show that container detritus and nutrients are influenced by fine-scale environmental variations environment, affecting Ae. aegypti and its competitor Ae. mediovittatus larvae phenotypic traits and nutrient composition.
Dataset DOI: 10.5061/dryad.573n5tbkh
Description of the data and file structure
We sampled mosquito larvae (density, biomass, nutrients), container detritus (type, biomass, nutrients), and suspended particulate organic matter (SPOM) in 44 locations and characterized the surrounding environment in terms of land cover, land use, and vegetation α diversity. Percent impervious cover (%) and canopy cover (%) were estimated in a 200 m buffer. Canopy cover directly over larval containers was also measured with a handheld densitometer. A 1.52 m radius visual survey from each container was conducted to determine vegetation α diversity. A foot survey along a 25 m transect from each container was conducted while recording number of structures (e.g., houses), green spaces, and house abandonment.
Files and variables
File: SJMA_gradient_and_containers.csv
Description:
Variables
- Container: Container identification number
- H: Number of houses along 25 m transect
- GS: Number of green spaces along 25 m transect
- AB: Number of abandoned structures along 25 m transect
- Adb: animal detritus biomass (g) in container
- Pdb: plant detritus biomass (g) in container
- flb: flower detritus biomass (g) in container
- lvb: Leaves detritus biomass (g) in container
- sdb: seed detritus biomass (g) in container
- FCN: container suspended particulate organic matter Carbon:Nitrogen
- detN: container detritus Nitrogen (%)
- detCN: container detritus Carbon:Nitrogen
- detNi: container detritus d15N
- detC: container detritus Carbon (%)
- detCi: container detritus d13C
- FN: container suspended particulate organic matter Nitrogen (%)
- Fni: container suspended particulate organic matter d15N
- FC: container suspended particulate organic matter Carbon (%)
- Fci: container suspended particulate organic matter d13C
- canb: container canopy cover % on a 200m buffer area
- imp: container impervious cover % on a 200m buffer area
- cano: canopy cover over container measured with densitometer
- alphadiv: container vegetation alpha diversity in a 1.52 m radius
- AMd: *Aedes mediovittatus *density
- AMb: *Aedes mediovittatus *biomass
- AEd: Aedes aegypti density
- AEb: Aedes aegypti biomass
- AMCN: *Aedes mediovittatus *Carbon:Nitrogen
- AECN: *Aedes aegypti *Carbon:Nitrogen
- AEN: *Aedes aegypti *nitrogen (%)
- AENi: *Aedes aegypti *d15N
- AEC: *Aedes aegypti *carbon (%)
- AECi: *Aedes aegypti *d13C
- AMN: Aedes mediovittatus nitrogen (%)
- AMNi: *Aedes mediovittatus *d15N
- AMC: *Aedes mediovittatus *carbon (%)
- AMCi: *Aedes mediovittatus *d13C
- NA: Variable not measured due to absence i.e., not a true zero.
Code/software
Statistical analyses were conducted using RStudio 2023.12.0+369 "Ocean Storm". We performed an iterative PCA algorithm using the impute PCA function from the missMDA package. We also selected important variables contributing to each principal component using the fviz_contrib function from the factoextra package.