Infection-nutrition feedbacks: fat supports pathogen clearance but pathogens reduce fat in a wild mammal
Data files
Jun 05, 2024 version files 272.44 KB
Abstract
Though far less obvious than direct effects (clinical disease or mortality), the indirect influences of pathogens are difficult to estimate but may hold fitness consequences. Here, we disentangle the directional relationships between infection and energetic reserves, evaluating the hypotheses that energetic reserves influence infection status of the host and that infection elicits costs to energetic reserves. Using repeated measures of fat reserves and infection status in individual bighorn sheep (Ovis canadensis) in the Greater Yellowstone Ecosystem, we documented that fat influenced ability to clear pathogens (Mycoplasma ovipneumoniae) and infection with respiratory pathogens was costly to fat reserves. Costs of infection approached, and in some instances exceeded, costs of rearing offspring to independence in terms of reductions to fat reserves. Fat influenced probability of clearing pathogens, pregnancy, and over-winter survival; from an energetic perspective, an animal could survive for up to 23 days on the amount of fat that was lost to high levels of infection. Cost of pathogens may amplify tradeoffs between reproduction and survival. In the absence of an active outbreak, the influence of resident pathogens often is overlooked. Nevertheless, the energetic burden of pathogens likely has consequences for fitness and population dynamics, especially when food resources are insufficient.
README: Energetic costs of infection in bighorn sheep
Captured data from female bighorn sheep in northwest Wyoming 2015-2021.
Description of the data and file structure
All raw data, other than spatial data used to obtain snow depth values, is in energeticcostsdata_20240514.csv. occupancydata_20240514.csv has the data formatted for use in an occupancy model in unmarked. The data is also pseudoreplicated (10 secondary periods created for each primary period) to allow for a fixed detection probability. Survival and pregnancy data are included in survivaldata.csv and pregnancydata.csv, respectively. We were not able to catch all sheep at each capture event, and thus some animals are missing data for certain events, indicated by NA.
Columns in energeticcostsdata_20240515.csv-
IFBF: ingesta-free body fat (percent)
Herd: population that the individual is a part of
Month: month of capture
Year: year of capture
Age: estimated age (years)
M.ovi: test result for Mycoplasma ovipneumoniae, 1 indicating positive detection, 0 indicating negative
detection
Recruit: recruitment status determined in December via lactation status, 1 indicating an individual does have an offspring
surviving to December, 0 indicating an individual does not have an offspring surviving to December
Pathrich: number of species in the Pasteurellaceae family detected
prevIFBF: IFBF of the individual at the preceding capture event (%)
Moviclear: whether or not an individual cleared M. ovipneumoniae between the preceding and current
capture event, 1 indicating that the individual tested positive for M. ovipneumoniae at the preceding capture and tested negative at the current capture, 0 indicating any other situation
pathsclear2: Number of pathogen species the individual cleared (i.e., tested positive for in the preceding
capture and negative at the current capture) between the preceding and current capture
Movigain: whether or not an individual acquired M. ovipneumoniae between the preceding and current
capture event, 1 indicating that the individual tested negative for M. ovipneumoniae at the preceding capture and tested positive at the current capture, 0 indicating any other situation
pathsgain2: Number of pathogen species the individual acquired (i.e., tested negative for in the
preceding capture and positive at the current capture) between the preceding and current capture
AID: Animal identification number, unique for each individual (randomized)
Columns in occupancydata_20240518.csv-
Region: herd that individual is in
season: Month of capture
Year: year of capture
Movi: detection of Mycoplasma ovipneumoniae, 0 indicating negative detection, 1 indicating
positive detection. The data is pseudo-replicated to force a 0.85 detection probability as per Butler et al. (2017).
IFBF: ingesta-free body fat (%)
Primary: primary period of capture
Secondary: Pseudo-replicated secondary period which were created to force a 0.85 detection
probability.
ID: animal identification number, unique for each individual (randomized)
Columns in pregnancydata.csv-
randomID: animal identification number, unique for each individual (randomized)
prevIFBF: IFBF of the individual at the preceding capture event(%)
Herd: population that individual is a part of, categorical
Preg: pregnancy status in March, determined via ultrasonography,
Columns in survivaldata.csv-
Month: Month of capture
Year: year of capture
randomID: animal identification number, unique for each individual (randomized)
Date: date of capture
IFBF: IFBF of the individual at the capture event (%)
Herd: population that individual is a part of, categorical
Age: estimated age (years)
MortCensor:used to indicate whether the animal died (1) or was censored (0) during the interval after the capture event
diff: difference between date of capture and mortality/censor date. We defined winter as 150 days post-capture, so values of 151 indicate the animal lived through winter
start: julian data of capture
end: end of interval, either time of mortality, censor, or end of winter
Event: indicitive of survival (0), censor (0), or mortality (1)
randomID: animal identification number, unique for each individual (randomized)
Butler, C.J., Edwards, W.H., Jennings-Gaines, J.E., Killion, H.J., Wood, M.E., McWhirter, D.E., et al. (2017). Assessing respiratory pathogen communities in bighorn sheep populations: Sampling realities, challenges, and improvements. PLoS One, 12, 121.
Methods
We used repeated measures of infection status and energetic reserves in female bighorn sheep from three populations in the Greater Yellowstone Ecosystem, USA that are geographically adjacent: the Whiskey Mountain population in the Wind River Range (43.4364,47 -109.551299); the Jackson population in the Gros Ventre Range (43.573926, -110.586624); and the Upper Shoshone population in the Absaroka Range (44.420117, -109.714750). We captured adult (4+ years old) females using helicopter net-gunning and chemical immobilization. Each subsequent March and December until March 2021, we recaptured previously collared females and captured new animals to maintain sample sizes. Each animal was assigned a unique identification number. All capture and handling protocols were approved by an independent Institutional Animal Care and Use Committee at the University of Wyoming (Protocol #20180305KM00296-03).
At each capture, we estimated ingesta-free body fat (IFBFat, hereafter, fat) using a combination of ultrasonography (5‐MHz transducer; Ibex Pro, E.I. Medical Imaging, Loveland, CO, USA) to measure rump fat and body palpations to assign a body condition score. Each December we determined lactation status using udder palpations to assess recruitment status. We used horn annuli and tooth eruption to estimate the age of each sheep.
We collected nasal and tonsil swabs at each capture event to determine the presence of bacteria species. All diagnostic tests were completed at the Wyoming Game and Fish Department Wildlife Health Laboratory using a combination of culture and PCR. We considered a positive result in either tonsil or nasal swabs to indicate a detection of a given bacteria for the sheep at that capture event. Detection of bacterial presence was imperfect and we did not differentiate between strains of bacterial species. Therefore, these data represent the minimum known bacterial species an individual was carrying during a sampling period, though it is possible our metrics of infection underestimated true infection status.
We used the number of Pasteurellaceae species (leukotoxigenic B. trehalosi, P. multocida, and leukotoxigenic M. haemolytica/glucosida) detected in each sheep at each capture event to quantify Pasteurellaceae richness. We used seasonal changes in fat, which requires two sequential captures of an individual (summer fat change = December fat – March fat, winter fat change = March fat – December fat), as a metric of seasonal acquisition and catabolism of energetic reserves. We also quantified changes in pathogen species detected between subsequent capture events. We defined the number of species cleared as the pathogen species that we detected in a capture event but were undetected the subsequent capture. We defined the number of species acquired as the number of pathogen species that were undetected in a capture event but were detected the subsequent capture. For example, if an individual tested positive for only P. multocida in March and only M. haemolytica the following December, we considered that individual to have a Pasteurellaceae richness of 1 at both capture events, to have cleared 1 Pasteurellaceae spp. (P. multocida) and to have acquired 1 Pasteurellaceae spp. (M. haemolytica).