We hypothesized that bighorn sheep ewes with chronic nasal Mycoplasma ovipneumoniae carriage are the source of infection that results in fatal lamb pneumonia. We tested this hypothesis in captive bighorn ewes at two study facilities over a 5-year period, by identifying carrier ewes and then comparing lamb fates in groups that did (exposed pens) or did not (non-exposed pens) include one or more carrier ewes. This data set describes the outcomes of those experiments.

Between 2004 and 2011 bighorn sheep were darted in Glacier National Park and in Dinosaur National Monument. Blood was drawn. These are the genotypes resulting from an Ovine HD array from the bighorns. The first 3 columns refers to bighorn sheep identifiers: 'Herd_Unit', 'IndID', and 'AgencyID'. IndID is the identifier assigned at Montana State University. Subsequent columns each represent a locus, with the values in the locus representing the allele.

Between 2004 and 2011 bighorn sheep were darted in Glacier National Park and in Dinosaur National Monument. Blood was drawn. These are the genotypes resulting from an Ovine HD array from the bighorns. The first 3 columns refers to bighorn sheep identifiers: 'Herd_Unit', 'IndID', and 'AgencyID'. IndID is the identifier assigned at Montana State University. Subsequent columns each represent a locus, with the values in the locus representing the allele.

Between 2004 and 2011 bighorn sheep were darted in Glacier National Park. Blood was drawn. These are the genotypes resulting from an Ovine HD array from 30 of those bighorns.

Between 2004 and 2011 bighorn sheep were darted in Glacier National Park. Blood was drawn. These are the genotypes resulting from an Ovine HD array from 30 of those bighorns.

These datasets (S2-S3) document the transmission of a bacterial pathogen (Mycoplasma agassizii) between desert tortoises (Gopherus agassizii) experimentally introduced in captivity and were used to create and compare models predicting transmission probability given data on the hosts and their interactions. Dataset S2 includes variables describing the individual tortoises interacting, e.g. id, sex; variables describing the length of their interaction, e.g., number of days cohabitating, hours of direct contact; and variables estimating the infection level (based on data in S3) of infected tortoises involved in the interaction with the focal host. Interaction time and the amount of bacteria present in an infected host were used to calculate “dose” variables that represent the intensity of exposure to the pathogen. These data were used to estimate model parameters for multiple generalized linear models (glm) with predictor variables related to exposure time to an infected host and host characteristics. The response variable or event of interest was the infection status of the exposed tortoise after a period of interaction. Infection status was defined in two ways (described in section 15) and determined using qPCR of tissue samples collected at intervals – the results of which are presented in the S3 dataset. The analyses allowed us to identify interactions that have high transmission likelihood, and so we explored the contact patterns of a wild tortoise population (25 individuals with overlapping or contiguous homeranges) to estimate how frequently high-risk contacts occur (Dataset S4). This dataset includes all interactions (tortoise ids of interacting pair, date & time interaction began, and interaction duration) documented between tortoises fitted with proximity logging devices. Each device detects other devices when tortoises are approximately 10 cm apart and ends an interaction when tortoises have remained further than 10 cm for 1 minute. These data are associated with the following publication: Aiello, C. M., Nussear, K. E., Esque, T. C., Emblidge, P. G., Sah, P., Bansal, S. and Hudson, P. J. (2016), Host contact and shedding patterns clarify variation in pathogen exposure and transmission in threatened tortoise Gopherus agassizii: implications for disease modelling and management. J Anim Ecol, 85: 829–842. doi:10.1111/1365-2656.12511

Natural selection may result in local adaptation to different environmental conditions across the range of a species. Understanding local adaptation, in turn, informs management decisions such as translocation to restore locally-extinct populations. We used a landscape genomics approach to detect genetic signatures of selection related to climatic variation among desert bighorn sheep populations across their indigenous range in the western United States. This approach allowed us to investigate broad patterns of both neutral and adaptive genetic variation across very different environments. Analyses suggested that ancestry and isolation by distance were the most significant forces driving genetic variation in desert bighorn sheep, but that climate was associated with at least 1 locus (i.e., location on the genome) under directional selection. The alternate allele (i.e., variant) at this locus was associated with biologically significant increases in elevation and precipitation, decreases in temperature, and was nearly private to herds occupying the Great Basin ecosystem. Our results suggest climate conditions at higher latitudes may have resulted in a distinct ecotype of desert bighorn sheep whose adaptations are still apparent among the few remaining indigenous populations in the Great Basin. We also found 2 highly supported candidate genes in the genomic region linked to this outlier. How the molecular function of these candidate genes may affect physiological response of desert bighorn sheep to climate is unclear, although their identification provides new insight into the genetic mechanisms potentially underlying environmental adaptation. We identified several other loci under strong directional selection not related to climate and described a previously unknown pattern of strong genetic divergence of bighorn sheep within the White Mountains compared to other populations. Overall, these findings suggest selection from environmental factors may influence genomic variation at the ecosystem-scale in desert bighorn sheep and these results extend our understanding of how this subspecies may respond to different environmental conditions.

Natural selection may result in local adaptation to different environmental conditions across the range of a species. Understanding local adaptation, in turn, informs management decisions such as translocation to restore locally-extinct populations. We used a landscape genomics approach to detect genetic signatures of selection related to climatic variation among desert bighorn sheep populations across their indigenous range in the western United States. This approach allowed us to investigate broad patterns of both neutral and adaptive genetic variation across very different environments. Analyses suggested that ancestry and isolation by distance were the most significant forces driving genetic variation in desert bighorn sheep, but that climate was associated with at least 1 locus (i.e., location on the genome) under directional selection. The alternate allele (i.e., variant) at this locus was associated with biologically significant increases in elevation and precipitation, decreases in temperature, and was nearly private to herds occupying the Great Basin ecosystem. Our results suggest climate conditions at higher latitudes may have resulted in a distinct ecotype of desert bighorn sheep whose adaptations are still apparent among the few remaining indigenous populations in the Great Basin. We also found 2 highly supported candidate genes in the genomic region linked to this outlier. How the molecular function of these candidate genes may affect physiological response of desert bighorn sheep to climate is unclear, although their identification provides new insight into the genetic mechanisms potentially underlying environmental adaptation. We identified several other loci under strong directional selection not related to climate and described a previously unknown pattern of strong genetic divergence of bighorn sheep within the White Mountains compared to other populations. Overall, these findings suggest selection from environmental factors may influence genomic variation at the ecosystem-scale in desert bighorn sheep and these results extend our understanding of how this subspecies may respond to different environmental conditions.

,The dataset includes clinical data from an experimental swine and ferret challenge and transmission study with 3 strains of swine H1 influenza A virus. Data are presented in two spreadsheets, one for pigs and one for ferrets.,,

Natural selection may result in local adaptation to different environmental conditions across the range of a species. Understanding local adaptation, in turn, informs management decisions such as translocation to restore locally-extinct populations. We used a landscape genomics approach to detect genetic signatures of selection related to climatic variation among desert bighorn sheep populations across their indigenous range in the western United States. This approach allowed us to investigate broad patterns of both neutral and adaptive genetic variation across very different environments. Analyses suggested that ancestry and isolation by distance were the most significant forces driving genetic variation in desert bighorn sheep, but that climate was associated with at least 1 locus (i.e., location on the genome) under directional selection. The alternate allele (i.e., variant) at this locus was associated with biologically significant increases in elevation and precipitation, decreases in temperature, and was nearly private to herds occupying the Great Basin ecosystem. Our results suggest climate conditions at higher latitudes may have resulted in a distinct ecotype of desert bighorn sheep whose adaptations are still apparent among the few remaining indigenous populations in the Great Basin. We also found 2 highly supported candidate genes in the genomic region linked to this outlier. How the molecular function of these candidate genes may affect physiological response of desert bighorn sheep to climate is unclear, although their identification provides new insight into the genetic mechanisms potentially underlying environmental adaptation. We identified several other loci under strong directional selection not related to climate and described a previously unknown pattern of strong genetic divergence of bighorn sheep within the White Mountains compared to other populations. Overall, these findings suggest selection from environmental factors may influence genomic variation at the ecosystem-scale in desert bighorn sheep and these results extend our understanding of how this subspecies may respond to different environmental conditions.