Find research datasets worth reusing

Fig. 1 in Traceback of the Psoroptes outbreak in British Columbian bighorn sheep (Ovis Canadensis)

Fig. 1. Characteristic long segmented peduncle (circle) that differentiates the genus of Psoroptes spp. from other psoroptidae that have relatively short unsegmented peduncles. (40× magnification captured on a Zeiss Universal compound light microscope outfitted with a TRke SPOT camera using SPOT image capture software).

Fig. 4 in Traceback of the Psoroptes outbreak in British Columbian bighorn sheep (Ovis Canadensis)

Fig. 4. Distribution of outer opisthosomal setae (OOS) lengths of Psoroptes collected from rabbits (labelled Rabbit), USA bighorn sheep (labelled BHS_USA), and Canada-outbreak associated bighorn sheep (labelled BHS_CAN). Each is marked with the province or state of host origin. Horizontal lines represent median OOS of each host grouping.

Fig. 3 in Traceback of the Psoroptes outbreak in British Columbian bighorn sheep (Ovis Canadensis)

Fig. 3. (a) Micrograph of a characteristic opisthosomal lobe of a USA bighorn mites (10× magnification captured on an Olympus C×33 compound light microscope with an Olympus EP50 camera using EP view software). The photographed mite was collected from a bighorn sheep in the Hells Canyon metapopulation. Note the more prominent outer opisthosomal lobe edge (circle) and broad base to the outer opisthosomal setae (arrow), (b) Micrograph of a characteristic opisthosomal lobe of BC bighorn origin mites (10× magnification captured on an Olympus C×33 compound light microscope with an Olympus EP50 camera using EP view software). This mite was collected from a bighorn in the Okanagan region of BC. Note the less distinct outer opisthosomal edge (circle) and the relatively less prominent base of the outer opisthosomal setae (arrow). (c) Micrograph of a characteristic opisthosomal lobe of rabbit origin mites (10× magnification captured on an Olympus C×33 compound light microscope with an Olympus EP50 camera using EP view software). This mite was collected from a rabbit in Maple Ridge, British Columbia. Note the less distinct outer opisthosomal edge (circle) and the relatively less prominent base of the outer opisthosomal setae (arrow).

opencc-by-4.0Aug 2024View details →

Fig. 2 in Patterns of gastrointestinal parasite infections in bighorn sheep, Ovis canadensis, with respect to host sex and seasonality

Fig. 2. Seasonal differences in fecal egg counts in female (blue) and male (red) bighorn sheep. Point intervals display the mean count ±95% confidence intervals as predicted by generalised linear mixed effects models. Seasons are: Late gestation (Late gestation/early lactation between April to June); Lactation/summer (between July and October); Rut (November and December); Winter (Winter/early gestation from January to March). Parasites are a) Strongyle; b) Nematodirus; c) Marshallagia; d) Protostrongylus lungworm; e) Eimeria. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

opencc-by-4.0Aug 2024View details →

Fig. 1 in Patterns of gastrointestinal parasite infections in bighorn sheep, Ovis canadensis, with respect to host sex and seasonality

Fig. 1. Schematic of the reproductive biology and seasons of bighorn sheep. The blue circle represents the entire year, where the top is December, 3 o'clock March, 6 o'clock June, 10 o'clock October etc. The grey quarter circle represents the season Jan–March = Winter/early gestation; the dark green quarter circles represent the season from April–June = late gestation/early lactation; the light green line represents the season between July and October, which is also representing lactation/summer; and the brown line is representing November and December, or the rutting season. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

opencc-by-4.0Aug 2024View details →

Fig. 3 in Patterns of gastrointestinal parasite infections in bighorn sheep, Ovis canadensis, with respect to host sex and seasonality

Fig. 3. Differences in mean and standard error in strongyle counts between males that use the coursing or tending mating tactic. Point intervals display the mean count ±95% confidence intervals as predicted by the generalised linear mixed effects model.

opencc-zeroJun 2022View details →

Data from: Bighorn sheep show similar in-host responses to the same pathogen strain in two contrasting environments

Ecological context – the biotic and abiotic environment, along with its influence on population mixing dynamics and individual susceptibility – are thought to have major bearing on epidemic outcomes. However, direct comparisons of disease events in contrasting ecological contexts in wildlife systems are often confounded by concurrent differences in host genetics, exposure histories, or pathogen strains. Here, we compare disease dynamics of a Mycoplasma ovipneumoniae spillover event that affected bighorn sheep populations in two contrasting ecological contexts. One event occurred on the herd's home range near the Rio Grande Gorge in New Mexico, while the other occurred in a captive facility at Hardware Ranch in Utah. While data collection regimens varied between the two sites, general patterns of antibody signal strength and symptom emergence were consistent. Symptoms appeared in the captive setting an average of 12.9 days post-exposure, average time to seroconversion was 24.9 days, and clinical signs peaked at approximately 36 days post-infection. These patterns were consistent with serological testing and subsequent declines in symptom intensity in the free-ranging herd. At the captive site, older animals exhibited more severe declines in body condition and loin thickness, higher symptom burdens, and slower antibody response to the pathogen than younger animals. Younger animals were more likely than older animals to clear infection by the time of sampling at both sites. The patterns presented here suggest that environment may not be a major determinant of epidemiological outcomes in the bighorn sheep - M. ovipneumoniae system, elevating the possibility that host- or pathogen-factors may be responsible for observed variation.

opencc-zeroOct 2022View details →

Natural history of a bighorn sheep pneumonia epizootic

A respiratory disease epizootic at the National Bison Range (NBR) in Montana in 2016-2017 caused an 85% decline in the bighorn sheep population, documented by observations of its unmarked but individually identifiable members, the subjects of an ongoing long-term study. The index case was likely one of a small group of young bighorn sheep on a short-term exploratory foray in early summer of 2016. Disease subsequently spread through the population, with peak mortality in September and October and continuing signs of respiratory disease and sporadic mortality of all age classes through early July 2017. Body condition scores and clinical signs suggested that the disease affected ewe groups before rams, although by the end of the epizootic ram mortality (90% of 71) exceeded ewe mortality (79% of 84). Microbiological sampling 10 years to 3 months prior to the epizootic had documented no evidence of infection or exposure to Mycoplasma ovipneumoniae at NBR, but during the epizootic a single genetic strain of Mycoplasma ovipneumoniae was detected in affected animals. Retrospective screening of domestic sheep flocks near the NBR identified the same genetic strain in one flock, presumptively the source of the epizootic infection. Evidence of fatal lamb pneumonia was observed during the first two lambing seasons following the epizootic but was absent during the third season following the death of the last identified M. ovipneumoniae carrier ewe. Monitoring of life history traits prior to the epizootic provided no evidence that environmentally and/or demographically induced nutritional or other stress contributed to the epizootic. Furthermore, the epizootic occurred despite proactive management actions undertaken to reduce risk of disease and increase resilience in this population. This closely observed bighorn sheep epizootic uniquely illustrates the natural history of the disease including the (presumptive) source of spillover, course, severity, and eventual pathogen clearance.

zenodo36/100

Fig. 2 in Traceback of the Psoroptes outbreak in British Columbian bighorn sheep (Ovis Canadensis)

Fig. 2. Map of the sample origin locations and associated host groups of Psoroptes samples used.

opencc-zeroDec 2022View details →

Different proxies, different stories? Imperfect correlations and different determinants of fitness in bighorn sheep

Measuring individual fitness empirically is required to assess selective pressures and predict evolutionary changes in nature. There is, however, little consensus on how fitness should be empirically estimated. As fitness proxies vary in their underlying assumptions, their relative sensitivity to individual, environmental, and demographic factors may also vary. Here, using a long-term study, we aimed at identifying the determinants of individual fitness in bighorn sheep (Ovis canadensis) using seven fitness proxies. Specifically, we compared four-lifetime fitness proxies: lifetime breeding success, lifetime reproductive success, individual growth rate, and individual contribution to population growth, and three multi-generational proxies: number of granddaughters, individual descendance in the next generation, and relative genetic contribution to the next generation. We found that all proxies were positively correlated, but the magnitude of the correlations varied substantially. Longevity was the main determinant of most fitness proxies. Individual fitness calculated over more than one generation was also affected by population density and growth rate. Because they are affected by contrasting factors, our study suggests that different fitness proxies should not be used interchangeably as they may convey different information about selective pressures and lead to divergent evolutionary predictions. Uncovering the mechanisms underlying variation in individual fitness and improving our ability to predict evolutionary change might require the use of several, rather than one, proxy of individual fitness.

opencc-zeroJan 2023View details →

Data from: Population connectivity patterns of genetic diversity, immune responses and exposure to infectious pneumonia in a metapopulation of desert bighorn sheep

Habitat fragmentation is an important driver of biodiversity loss and can be remediated through management actions aimed at maintenance of natural connectivity in metapopulations. Connectivity may protect populations from infectious diseases by preserving immunogenetic diversity and disease resistance. However, connectivity could exacerbate the risk of infectious disease spread across vulnerable populations. We tracked the spread of a novel strain of Mycoplasma ovipneumoniae in a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave desert to investigate how variation in connectivity among populations influenced disease outcomes. M. ovipneumoniae was detected throughout the metapopulation, indicating that the relative isolation of many of these populations did not protect them from pathogen invasion. However, we show that connectivity among bighorn sheep populations was correlated with higher immunogenetic diversity, a protective immune response and lower disease prevalence. Variation in protective immunity predicted infection risk in individual bighorn sheep and was associated with heterozygosity at genetic loci linked to adaptive and innate immune signalling. Together, these findings may indicate that population connectivity maintains immunogenetic diversity in bighorn sheep populations in this system and has direct effects on immune responses in individual bighorn sheep and their susceptibility to infection by a deadly pathogen. Our study suggests that the genetic benefits of population connectivity could outweigh the risk of infectious disease spread and supports conservation management that maintains natural connectivity in metapopulations.