Data from: Climate-driven increase in transmission of a wildlife malaria parasite over the last quarter century
Data files
Mar 06, 2026 version files 164.31 KB
-
AT_GlobalChangeCode.txt
11.75 KB
-
BlueTitSamplingData.csv
83.69 KB
-
climwin_250603.txt
46.67 KB
-
HatchDates.csv
16.95 KB
-
README.md
5.26 KB
Abstract
Climate warming is expected to influence the prevalence of vector-transmitted parasites. Understanding the extent to which this is ongoing, or has already occurred, requires empirical data from populations monitored over long periods of time, but these studies are sparse. Further, vector-disease research involving human health is often influenced by disease control efforts that supersede natural trends. By screening for malaria parasite infections in a wild population of blue tits (Cyanistes caeruleus) in Northern Europe, over 26 years, we tested whether prevalence and transmission changes were climate-driven. We found that all three malaria parasite genera occurring in blue tits (Haemoproteus, Plasmodium, and Leucocytozoon) have increased significantly in their prevalence and transmission over time. The most common parasite in the study, Haemoproteus majoris, increased in prevalence from 47% (1996) to 92% (2021), and this was a direct consequence of warmer temperatures elevating transmission. Climate window analyses revealed that elevated temperatures between May 9th and June 24th, a time period that overlaps with the host nestling period, were strongly positively correlated with H. majoris transmission in one-year-old birds. A warming climate during this narrow timeframe has had a demonstrable impact on parasite transmission, and this has favored an increase in the prevalence of parasites in wild birds in a temperate region of Europe. While more challenging to measure, similar implications of climate warming on human vector-disease systems might be occurring. It is therefore critical that we understand what specific aspects of malaria parasite development and transmission are most influenced by climate warming, for the benefit of human and wildlife health.
Dataset DOI: 10.5061/dryad.37pvmcvz2
Description of the data and file structure
Blue tits (Cyanistes caeruleus) were sampled from 1996 and 2021 as part of an experimental nest box system used to study their breeding. Age and sex data were obtained for all breeding birds in the study, along with blood samples. DNA was extracted from blood samples and used to identify infections with three different avian malaria genera: Haemoproteus, Plasmodium, and Leucocytozoon. The archived data and code were used to: (1) identify the prevalence and transmission patterns for malaria parasites over the study duration and (2) assess the relationship between warming temperatures and transmission patterns. Additionally, we include information on when eggs hatch (hatch dates) in the study system.
Files and variables
File: AT_GlobalChangeCode.txt
Description: Code used to:
(1) Obtain the total number of birds sampled by age group, and for each time period of the study.
(2) Obtain the total number of recaptured birds and re-sampling events.
(3) Plot hatching dates for 1882 clutches spanning the three time periods of the study.
(4) Assess blue tit prevalence and transmission trends over time and plot model outputs.
(5) Plot Haemoproteus prevalence, Number of biting midges caught, and average temperatures in the associated climate window.
File: climwin_250603.txt
Description: Code used for climate window and path analyses
File: BlueTitSamplingData.csv
Description: Sampling data from the blue tit population
Variables
- Ring number: Unique identifier for each bird in the study
- Year: The year that the sample was collected
- Month: The month that the sample was collected
- Day: The day that the sample was collected
- Age: Age of the bird at sampling (e.g., 20 = one-year-old bird, 30 = two-year-old, etc.)
- Age_Simple: Separates one-year-old birds (Age_Simple = 1) from all older age classes (Age_Simple = 2)
- Haem1: Results from first screening for Haemoproteus (Uninfected = 0, Infected = 1).
- Plas1: Results from first screening for Plasmodium (Uninfected = 0, Infected = 1)
- Leuco1: Results from first screening for Leucocytozoon (Uninfected = 0, Infected = 1)
- Haem2: Results from second screening for Haemoproteus (Uninfected = 0, Infected = 1)
- Plas2: Results from second screening for Plasmodium (Uninfected = 0, Infected = 1)
- Leuco2: Results from second screening for Leucocytozoon (Uninfected = 0, Infected = 1)
- Haem.final: Combined results from both screenings used for downstream analysis of Haemoproteus infection. "NA" refers to infection statuses that could not be determined from both screens.
- Plas.final: Combined results from both screenings used for downstream analysis of Plasmodium infection. "NA" refers to infection statuses that could not be determined from both screens.
- Leuco.final: Combined results from both screenings used for downstream analysis of Leucocytozoon infection. "NA" refers to infection statuses that could not be determined from both screens.
File: HatchDates.csv
Description: Hatching dates for 1882 blue tit clutches hatched between 1996 and 2021
Variables
- Year: Year of sampling
- Day: Number of days from April 1st.
Code/software
All code is from statistical analyses completed using R software. Users will need to have access to the following R packages:
- dplyr: For cleaning and organizing data
- ggplot2: For data visualization
- lme4: For generalized linear models (GLMs)
- visreg: For visualizing outputs from GLMs
- ggpubr: For exporting plots
- piecewiseSEM: For structural equation modeling
- climwin: For climate window analyses
- lubridate: For working with time series data.
- purrr: For writing functions
- ggeffects: For computing estimated marginal effects
- ggplotify: For converting plot objects into grid objects
- png: For storing images in .png format
- ggrepel: For preventing overlapping of text labels
Access to climate data
Daily temperature used in this study were obtained from the Swedish Meteorological and Hydrological Institute (SMHI) Open Data portal: https://www.smhi.se/data/temperatur-och-vind/temperatur/airtemperatureInstant/53430
These data originate from the Lund weather station (station ID: 53430). Because SMHI distributes these observations under a Creative Commons Attribution (CC BY) license, which is not compatible with Dryad's CC0 requirement, the raw temperature data cannot be redistributed in this repository.
Users can access the required temperature variables directly from the SMHI portal using the link above. The analyses in this study used daily minimum, maximum, and mean air temperature values from 1995-01-01 to 2021-12-31 recorded at the Lund station.
If users experience difficulty with downloading the necessary temperature data from SMHI, the authors can provide these datasets upon request.
