DOI: 10.5061/dryad.6wwpzgn44
title: Infection-nutrition feedbacks: fat supports pathogen clearance but pathogens reduce fat in a wild mammal

description: 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.  
description: 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 <em>B.
 trehalosi</em>, <em>P. multocida</em>, and
 leukotoxigenic <em>M. haemolytica/glucosida</em>) 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 <em>P.
 multocida</em> in March and only <em>M. haemolytica</em>
 the following December, we considered that individual to have a
 Pasteurellaceae richness of 1 at both capture events, to have cleared 1
 Pasteurellaceae spp. (<em>P. multocida</em>) and to have
 acquired 1 Pasteurellaceae spp. (<em>M.
 haemolytica</em>).
description: # 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.