Data from: Resource quantity affects infection success and impacts of a microsporidian on hosts
Data files
Sep 24, 2025 version files 60.37 KB
-
BodyLength.csv
8.18 KB
-
DOC_Ordospora.csv
180 B
-
Feeding_Rate_Survivorship.csv
7.30 KB
-
FeedingRates.csv
38.78 KB
-
InfectionStatusAndBurden.csv
1.43 KB
-
Ordospora_AE.csv
181 B
-
README.md
4.32 KB
Abstract
Resource quantity in the environment often changes over time and influences the nutritional status of hosts that may encounter parasites. If resource availability significantly alters both infection success and within-host growth of a parasite, fluctuations in resources may underlie the seasonal disease outbreaks that have been observed for some parasites. Moreover, resource quantity may affect how a parasite impacts host survivorship and traits, including feeding rate and assimilation of nutrients. Some parasites, such as intracellular microsporidia with highly reduced genomes, may be particularly sensitive to variation in host nutritional status and more likely to have resource-dependent impacts. To determine how resource quantity affects infection success and parasite impacts on hosts, we conducted laboratory experiments using the microsporidian parasite Ordospora pajunii and its zooplankton host, the dominant grazer Daphnia dentifera. We found that infection probability and spore burden were higher when resources were more abundant, suggesting O. pajunii benefits when host quality is higher. However, parasite virulence, which was measured in terms of host mortality, was greater when resources were more limited. Parasite exposure depressed host feeding rate, but the timing of this reduction differed across the resource gradient. Further investigation of host carbon assimilation efficiency and dissolved organic carbon release during infections when resources were more limited revealed no significant impact of infection. Overall, resource-dependent impacts of O. pajunii, including reductions in zooplankton host feeding rate and increased host mortality, may contribute to seasonality of disease outbreaks and drive trophic cascades in lakes.
https://doi.org/10.5061/dryad.2v6wwpzzr
Description of the data and file structure
# experimental study on how resource quantity affects infections and impacts of a parasite on hosts
Files and variables
## Description of the data and file structure
1. scripts: this contains the code used to create figures and conduct analyses.
2. data: this contains the data collected during the study.
_______________________________________________________________________________________________________________
DATA
InfectionStatusAndBurden.csv: this data file contains the infection status and spore burden of Daphnia dentifera exposed to a microsporidian parasite. ID = the identification code for experimental individual. Food_Level = resource quantity treatment (high = high food, medium = 12.5% of the high food treatment, low = 6.25% of the high food treatment). Concentration = number of copies per microliter (copies/microliter) of a microsporidian infecting a host. InfectionStatus = binary response indicating infected (1) or uninfected (0)
Feeding_Rate_Survivorship.csv: this data file contains the survivorship data for the feeding rate experiment. ID = the identification code for experimental individual. Treatment = unexposed or exposed to parasite spores for the experiment. Food.Level = resource quantity treatments for the experiment (high = high food, medium = 12.5% of the high food treatment, low = 6.25% of the high food treatment). Lifespan = day the host died. Status = binary indicator describing whether the host survived to the end of the assay (0) or died earlier (1)
FeedingRates.csv: this data file contains the feeding rate data. Plate = plate identification for each sampling date. Date = date of the assay. Days.PostExposure = number of days after the parasite exposure. Sample.Round = temporal sampling round. Sample = the identification code for experimental individual. Treatment = unexposed (control) or exposed to parasite spores for the experiment. Food = resource quantity treatment for the experiment (high = high food, medium = 12.5% of the high food treatment, low = 6.25% of the high food treatment). Average = fluorescence value (relative fluorescence units). Feeding.Rate = calculation of feeding rate of an individual (mL per hour). Binary.Infection.Status = binary response indicating infected (1) or uninfected (0). n/a for Binary.Infection.Status means that it was not applicable to label control (unexposed) individuals as infected or uninfected or that individuals exposed to the microsporidian died before infection checks and thus could not be categorized as infected or uninfected. Infection.Status = categorical status of host indicating no exposure (control), exposed and infection, or exposed and uninfected. n/a for Infection.Status means that it was not applicable to determine the infection status of individuals exposed to the microsporidian that died before infection checks or could not be preserved for molecular detection of spores.
Ordospora_AE.csv: this data file contains the assimilation efficiency data. ID = individual sample code. Treatment = unexposed or exposed to parasite spores for the experiment. Replicate = replicate number. AE = assimilation efficiency (%).
DOC_Ordospora.csv: this data file contains the dissolved organic carbon release data. Treatment = unexposed or exposed to parasite spores for the experiment. Replicate = replicate number. TOC = total dissolved organic carbon released over four hours (mg/L).
BodyLength.csv: Individual = individual sample code. Treatment = unexposed (control) or exposed to parasite spores for the experiment. Food.Level = categorical resource quantity treatment for the experiment (high = high food, medium = 12.5% of the high food treatment, low = 6.25% of the high food treatment). Date = date of the assay. Day = number of days after the parasite exposure. Body.Length = body length of individual (micrometers).
Code/software
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.