Data for: Temperature and intraspecific variation affect host-parasite interactions
Cite this dataset
Lyberger, Kelsey (2023). Data for: Temperature and intraspecific variation affect host-parasite interactions [Dataset]. Dryad. https://doi.org/10.5061/dryad.g79cnp5w6
Abstract
Parasites play key roles in regulating aquatic ecosystems, yet the impact of climate warming on their ecology and disease transmission remains poorly understood. Isolating the effect of warming is challenging as transmission involves multiple interacting species and potential intraspecific variation in temperature responses of one or more of these species. Here, we leverage a wide-ranging mosquito species and its facultative parasite as a model system to investigate the impact of temperature on host-parasite interactions and disease transmission. We conducted a common garden experiment measuring parasite growth and infection rates at seven temperatures using 12 field-collected parasite populations and a single mosquito population. We find that both free-living growth rates and infection rates varied with temperature, which were highest at 18-24.5°C and 13°C, respectively. Further, we find intraspecific variation in peak performance temperature reflecting patterns of local thermal adaptation—parasite populations from warmer source environments typically had higher thermal optima for free-living growth rates. For infection rates, we found a significant interaction between parasite population and nonlinear effects of temperature. These findings underscore the need to consider both host and parasite thermal responses, as well as intraspecific variation in thermal responses, when predicting the impacts of climate change on disease in aquatic ecosystems.
README: Data from "Temperature and intraspecific variation affect host-parasite interactions"
Date modified: 09-09-2023
Dataset Metadata
We leverage a wide-ranging mosquito species and its facultative parasite as a model system to investigate the impact of temperature on host-parasite interactions and disease transmission. We conducted a common garden experiment measuring parasite growth and infection rates at seven temperatures using 12 field-collected parasite populations and a single mosquito population.
Description of the data and file structure
The data for this study are in 3 files. "infection data_final.csv" has data on the number of mosquito larvae infected and melanized from the infection experiment manipulating Lambornella parasite population and temperature. "thermal performance data_final.csv" has data on the number of cells per 100/ml from the experiment measuring growth rates of the free-living ciliate populations at 6 temperatures. "bioclim_data_final.csv" has data on the 19 bioclimatic variables for the 12 locations from which ciliates were collected. Bioclim variables are from Worldclim where the description of the variables has been provided below and can be found at https://www.worldclim.org/data/bioclim.html. The code to run the analysis and reproduce figures are in the files "Rev2_FINAL lambornella performance code.R" and "Rev2_FINAL Infection plots.R".
- Variables:
- tray: the tray in which the mosquitoes were reared, as there were multiple trays per temperature treatment.
- temperature: The incubation temperature in degrees Celsius.
- Lambo_pop: a unique ID for the 12 Lambornella populations.
- num_infected: The number of mosquitoes infected out of 5 possible.
- num_melanized: The number of mosquitoes with melanization spots out of 5 possible.
- day: the day of the experiment.
- color: a color that corresponds to one of the 12 Lambornella populations.
- 5C to 28C: the six temperature treatments for the Lambornella thermal performance experiment.
- Treehole_ID: a unique ID for the 9 treehole mosquito populations.
- lat: latitude
- long: longitude
- bio_1: Annual Mean Temperature in Celsius
- bio_2: Mean Diurnal Range (Mean of monthly (max temp - min temp))
- bio_3: Isothermality (BIO2/BIO7) (×100)
- bio_4: Temperature Seasonality (standard deviation ×100)
- bio_5: Max Temperature of Warmest Month in Celsius
- bio_6: Min Temperature of Coldest Month in Celsius
- bio_7: Temperature Annual Range (BIO5-BIO6)
- bio_8: Mean Temperature of Wettest Quarter in Celsius
- bio_9: Mean Temperature of Driest Quarter in Celsius
- bio_10: Mean Temperature of Warmest Quarter in Celsius
- bio_11: Mean Temperature of Coldest Quarter in Celsius
- bio_12: Annual Precipitation
- bio_13: Precipitation of Wettest Month in mm
- bio_14: Precipitation of Driest Month in mm
- bio_15: Precipitation Seasonality (Coefficient of Variation)
- bio_16: Precipitation of Wettest Quarter in mm
- bio_17: Precipitation of Driest Quarter in mm
- bio_18: Precipitation of Warmest Quarter in mm
- bio_19: Precipitation of Coldest Quarter in mm
Code/Software
R code to run the analysis and reproduce figures 3 and 4 are in "Rev2_FINAL Infection plots.R" and figures 5 and 6 are in "Rev2_FINAL lambornella performance code.R".
Funding
National Science Foundation, Award: DEB-2011147
National Institutes of Health, Award: R35GM133439
National Institutes of Health, Award: R01AI168097
National Institutes of Health, Award: R01AI102918
Stanford King Center on Global Development
Stanford Woods Institute for the Environment
Stanford University Center for Innovation in Global Health
Terman Award
Rose Hills Foundation
Bing-Mooney Fellowship
National Science Foundation, Award: 2208947