Population subdivision among desert bighorn sheep (Oviscanadensis) ewes revealed by mitochondrial DNA analysis

We used behavioural observations and mitochondrial DNA (mtDNA) sequence analysis to examine demographic and genetic structure within and among home-range groups of desert bighorn sheep (Oviscanadensis) ewes in the Peninsular Ranges of southern California, USA. We identified substantial genetic variation in the first 515 bp of the mtDNA control region and determined that seven haplotypes were distributed in a nonrandom fashion among these ewe subpopulations. Although a significant (P < 0.01) amount of mtDNA variation (33%) was partitioned among home-range groups, we did not find strong evidence for matrilineal substructuring within these groups. Based on analyses of molecular variance, and comparisons of behavioural associations and distances between centres of activity, we concluded that within a given home-range group, bighorn sheep ewes generally associate with other ewes based on their availability rather than their matrilineal relationships. Our results also supported the conclusion that multiple ewe subpopulations exist within the Peninsular Ranges, and that these subpopulations are the most basic demographic and genetic units.     

Is Habitat Constraining Bighorn Sheep Restoration? A Case Study

Rocky Mountain bighorn sheep (Ovis canadensis) restoration continues to be a challenge throughout western North America despite nearly a century of efforts dedicated to the species' recovery. Though bighorn sheep restoration may be constrained by several environmental factors and behavioral tendencies, areas with unrealized restoration potential may exist if novel restoration strategies are considered. We used global positioning system (GPS) location data from 27 female bighorn sheep within the southern portion of the Madison Range in southwest Montana, USA, 2015–2017, to develop and validate winter and summer habitat models, which we extrapolated throughout the entire Madison Range to identify potential seasonal habitat. We estimated potential bighorn sheep minimum population estimates within the extrapolation area by linking our top-ranked winter habitat model to population count data. During summer, female bighorn sheep selected areas characterized by rugged and steep terrain, reduced canopy cover, southwestern aspects, and ridgelines. During winter, female bighorn sheep selected areas characterized by low elevations, southwestern aspects, steep slopes, reduced canopy cover, ridgelines, high normalized difference vegetation index amplitude, and areas close to steep terrain. Predicted summer habitat was concentrated along the high-elevation ridgelines associated with steep slopes and reduced canopy cover. Predicted winter habitat occurred in a non-contiguous distribution primarily along the low-elevation, southwest-facing aspects along the western slopes of the Madison Range. Our results suggest that the Madison Range may be capable of supporting 780–1,730 animals, which is 2–4 times the number of bighorn sheep currently observed within the range. Further, our findings provide managers with a quantification of female bighorn sheep habitat and suggests that a strategy focused on establishing a metapopulation through a series of within-range translocations may enhance bighorn sheep restoration. We suggest that similar restoration opportunities may be common in other unoccupied areas of bighorn sheep historical range. © 2020 The Wildlife Society.     

Desert bighorn sheep habitat selection,group size,and mountain lion predation risk

Bighorn sheep (Ovis canadensis) evolved for thousands of years in the presence of numerous predators, including mountain lions (Puma concolor). Bighorn sheep have presumably developed predator avoidance strategies; however, the effectiveness of these strategies in reducing risk of mountain lion predation is not well understood. These strategies are of increasing interest because mountain lion predation on bighorn sheep has been identified as a leading cause of mortality in some sheep populations. Therefore, we investigated how mountain lions affect both bighorn sheep habitat selection and risk of mortality in Arizona, USA. We used 2 approaches to investigate the predator-prey relationship between mountain lions and bighorn sheep. We fit 103 bighorn sheep (81 females and 22 males) with global positioning system radio-collars in 2 Arizona populations from 2013 to 2017, and used a negative binomial resource selection probability function to evaluate whether bighorn sheep selected for habitat features in accordance with presumed predator avoidance strategies, including terrain ruggedness, slope, topographic position, and horizontal obstruction, in 2 seasons (winter and summer). We then estimated how habitat features such as terrain ruggedness, slope, horizontal obstruction, and group size, influence the risk of mortality due to mountain lion predation using an Andersen-Gill proportional hazards model. Generally, both sexes selected areas with lower horizontal obstruction and intermediate ruggedness and slope, but selection patterns differed between seasons and sexes. The use of more rugged areas and steeper slopes decreased the risk of mortality due to mountain lion predation, consistent with presumed predator avoidance strategies. Increased group size decreased risk of bighorn sheep mortality due to mountain lion predation but this effect became marginal at approximately 10 individuals/group. We did not identify a relationship between horizontal obstruction and bighorn sheep mortality risk. Our findings can be used in habitat and population management decisions such as the prioritization of habitat restoration sites or selection of translocation sites. In addition, we suggest that augmentation of low-density bighorn sheep populations may reduce mountain lion predation risk by increasing group size, and that releasing large groups of bighorn sheep in population augmentation and reintroduction efforts may help to reduce mountain lion predation.     

Restoration Potential of Bighorn Sheep in a Prairie Region

Efforts to recover Rocky Mountain bighorn sheep (Ovis canadensis canadensis) throughout western North America have had limited success with the majority of current populations remaining in small and isolated areas on a fraction of their historical range. Prairie environments with rugged topography throughout the Northern Great Plains ecoregion were historically occupied by relatively robust bighorn sheep populations. We predicted there is likely unrealized potential habitat for restoring bighorn sheep to these areas; however, relatively little attention has been devoted to identifying habitat in unoccupied prairie regions. We used global positioning system (GPS)-collar data collected from 43 female bighorn sheep in 2 populations located in the eastern Montana, USA, portion of the Northern Great Plains during 2014–2018 to estimate a population-level annual resource selection model and identify the important factors affecting bighorn sheep resource selection. We extrapolated model predictions across eastern Montana's prairie region and identified potential habitat to understand restoration potential and assist with future translocations of bighorn sheep. Resource selection of bighorn sheep was most strongly associated with terrain slope and ruggedness, tree canopy cover, and a normalized difference vegetation index metric. Within currently unoccupied areas of the historical range, the model extrapolation predicted 7,211 km² of habitat, with most owned and managed by private landowners (44%), Bureau of Land Management (33%), and the United States Fish and Wildlife Service (15%). Our results provide an empirical evaluation of landscape covariates influencing resource selection of bighorn sheep occupying prairie environments and provide a habitat model that may be generalizable to other areas in the Northern Great Plains ecoregion. We demonstrate substantial potential for restoration opportunities of bighorn sheep in the Northern Great Plains ecoregion. Broad restoration of bighorn sheep across the ecoregion would likely require strong collaboration among and between public resource managers, private landowners, and livestock producers given the heterogeneous land ownership patterns, management strategies, and domestic sheep distributions. © 2020 The Wildlife Society.     

Montane refugia predict population genetic structure in the Large‐blotched Ensatina salamander

Understanding the biotic consequences of Pleistocene range shifts and fragmentation remains a fundamental goal in historical biogeography and evolutionary biology. Here, we combine species distribution models (SDM) from the present and two late Quaternary time periods with multilocus genetic data (mitochondrial DNA and microsatellites) to evaluate the effect of climate‐induced habitat shifts on population genetic structure in the Large‐blotched Ensatina (Ensatina eschscholtzii klauberi), a plethodontid salamander endemic to middle and high‐elevation conifer forest in the Transverse and Peninsular Ranges of southern California and northern Baja California. A composite SDM representing the range through time predicts two disjunct refugia, one in southern California encompassing the core of the species range and the other in the Sierra San Pedro Mártir of northern Baja California at the southern limit of the species range. Based on our spatial model, we would expect a pattern of high connectivity among populations within the northern refugium and, conversely, a pattern of isolation due to long‐term persistence of the Sierra San Pedro Mártir population. Our genetic results are consistent with these predictions based on the hypothetical refugia in that (i) historical measures of population connectivity among stable areas are correlated with gene flow estimates; and (ii) there is strong geographical structure between separate refugia. These results provide evidence for the role of recent climatic change in shaping patterns of population persistence and connectivity within the Transverse and Peninsular Ranges, an evolutionary hotspot.     

Quantifying Landscape Ruggedness for Animal Habitat Analysis: A Case Study Using Bighorn Sheep in the Mojave Desert

Abstract: Terrain ruggedness is often an important variable in wildlife habitat models. Most methods used to quantify ruggedness are indices derived from measures of slope and, as a result, are strongly correlated with slope. Using a Geographic Information System, we developed a vector ruggedness measure (VRM) of terrain based on a geomorphological method for measuring vector dispersion that is less correlated with slope. We examined the relationship of VRM to slope and to 2 commonly used indices of ruggedness in 3 physiographically different mountain ranges within the Mojave Desert of the southwestern United States. We used VRM, slope, distance to water, and springtime bighorn sheep (Ovis canadensis nelsoni) adult female locations to model sheep habitat in the 3 ranges. Using logistic regression, we determined that the importance of ruggedness in habitat selection remained consistent across mountain ranges, whereas the relative importance of slope varied according to the characteristic physiography of each range. Our results indicate that the VRM quantifies local variation in terrain more independently of slope than other methods tested, and that VRM and slope distinguish 2 different components of bighorn sheep habitat.     

A comparative evaluation of presence-only methods for modelling species distribution

In spite of increasing application of presence-only models in ecology and conservation and the growing number of such models, little is known about the relative performance of different modelling methods, and some of the leading models (e.g. GARP and ENFA) have never been compared with one another. Here we compare the performance of six presence-only models that have been selected to represent an increasing level of model complexity [BIOCLIM, HABITAT, Mahalanobis distance (MD), DOMAIN, ENFA, and GARP] using data on the distribution of 42 species of land snails, nesting birds, and insectivorous bats in Israel. The models were calibrated using data from museum collections and observation databases, and their predictions were evaluated using Cohen's Kappa based on field data collected in a standardized sampling design covering most parts of Israel. Predictive accuracy varied between modelling methods with GARP and MD showing the highest accuracy, BIOCLIM and ENFA showing the lowest accuracy, and HABITAT and DOMAIN showing intermediate accuracy levels. Yet, differences between the various models were relatively small except for GARP and MD that were significantly more accurate than BIOCLIM and ENFA. In spite of large differences among species in prevalence and niche width, neither prevalence nor niche width interacted with the modelling method in determining predictive accuracy. However, species with relatively narrow niches were modelled more accurately than species with wider niches. Differences among species in predictive accuracy were highly consistent over all modelling methods, indicating the need for a better understanding of the ecological and geographical factors that influence the performance of species distribution models.     

A comparison of approaches for modelling the occurrence of marine animals

Approaches for modelling the distribution of animals in relation to their environment can be divided into two basic types, those which use records of absence as well as records of presence and those which use only presence records. For terrestrial species, presence–absence approaches have been found to produce models with greater predictive ability than presence-only approaches. This study compared the predictive ability of both approaches for a marine animal, the harbour porpoise (Phoceoena phocoena). Using data on the occurrence of harbour porpoises in the Sea of Hebrides, Scotland, the predictive abilities of one presence–absence approach (generalised linear modelling—GLM) and three presence-only approaches (Principal component analysis—PCA, ecological niche factor analysis—ENFA and genetic algorithm for rule-set prediction—GARP) were compared. When the predictive ability of the models was assessed using receiver operating characteristic (ROC) plots, the presence–absence approach (GLM) was found to have the greatest predictive ability. However, all approaches were found to produce models that predicted occurrence significantly better than a random model and the GLM model did not perform significantly better than ENFA and GARP. The PCA had a significantly lower predictive ability than GLM but not the other approaches. In addition, all models predicted a similar spatial distribution. Therefore, while models constructed using presence–absence approaches are likely to provide the best understanding of species distribution within a surveyed area, presence-only models can perform almost as well. However, careful consideration of the potential limitations and biases in the data, especially with regards to representativeness, is needed if the results of presence-only models are to be used for conservation and/or management purposes. Guest editor: V. D. Valavanis Essential Habitat Mapping in the Mediterranean     

Evaluating models to assess the distribution of Buxus balearica in southern Spain

Question: Which is the best model to predict the habitat distribution of Buxus balearica Lam. in southern Spain? Location: Málaga and Granada, Spain, across an area of 38 180 km². Methods: Prediction models based on 17 environmental variables were tested. Six methods were compared: multivariate adaptive regression spline (MARS), maximum entropy approach to modelling species' distributions (Maxent), two generic algorithms based on environmental metrics dissimilarity (BIOCLIM and DOMAIN), Genetic Algorithm for Rule‐set Prediction (GARP), and supervised learning methods based on generalized linear classifiers (support vector machines, SVMs). To test the predictive power of the models we used the Kappa index. Results: Maxent most accurately predicted the habitat distribution of B. balearica, followed by MARS models. The other models tested yielded lower accuracy values. A comparison of the predictive power of the models revealed that climate variables made the highest contributions among the environmental variables studied. The variables that made the lowest contributions were the insolation models. To examine the sensitivity of the models to a reduction in the number of variables, a test showed that accuracy of over 0.90 was maintained by applying just three climatic variables (spring rainfall, mean temperature of the warmest month, and mean temperature of the coldest month). Maps derived from the algorithms of all models tested coincided well with the known distribution of the species. Conclusions: Model habitat prediction is a preliminary step towards highlighting areas of high habitat suitability of B. balearica. These data support the results of previous research, which show that MaxEnt is the best technique for modelling species distributions with small sample sizes.     

Assessing extinction-risk of endangered plants using species distribution models: a case study of habitat depletion caused by the spread of greenhouses

The species distribution models (SDMs) are useful tools for investigating rare and endangered species as well as the environmental variables affecting them. In this paper, we propose the application of SDMs to assess the extinction-risk of plant species in relation to the spread of greenhouses in a Mediterranean landscape, where habitat depletion is one of the main causes of biodiversity loss. For this purpose, presence records of the model species (Linaria nigricans, a endemic and threatened species) and the greenhouses, a dataset of environmental variables, and different only presence-based modelling algorithms (Bioclim, Domain, GARP, MaxEnt and ENFA) were used to build SDMs for L. nigricans as well as for greenhouses. To evaluate the models a modified approach of the area-under-curve ROC was applied. Combining the most accurate models, we generated an extinction-risk model of L. nigricans populations, which enabled us to assess the sustainability of the most threatened populations. Our results show that is possible to model greenhouses spreading as a “biological invasion”. The procedure explained and used in this work is quite novel, and offers an objective spatial criterion intended for the management of natural resources and for the conservation of the biodiversity in areas threatened by habitat depletion processes as particular as greenhouses expansion.     

Comparing contemporary models to traditional indices to estimate abundance of desert bighorn sheep

Aerial surveys for large ungulates produce count data that often underrepresent the number of animals. Errors in count data can lead to erroneous estimates of abundance if they are not addressed. Our objective was to address imperfect detection probability by developing a framework that produces realistic and defensible estimates of bighorn sheep (Ovis canadensis) abundance. We applied our framework to a population of desert bighorn sheep (O. c. nelsoni) in the Great Basin, Nevada, USA. We captured and marked 24 desert bighorn sheep with global positioning system (GPS)-collars and then conducted helicopter surveys naïve to the locations of collared animals. We developed a Bayesian integrated data model to leverage information from telemetry data, helicopter survey counts, and habitat characteristics to estimate abundance while accounting for availability and perception probability (i.e., detection given availability). Distance to ridgeline, terrain ruggedness, tree cover, and slope influenced perception probability of sheep given they were viewable from the helicopter. There was also annual variation in perception probability (2018: median = 0.64, credible interval [CrI] = 0.37–0.87; 2019: median = 0.81, CrI = 0.49–0.97). The abundance estimates from the integrated data model decreased from 2018 (594; 95% CrI = 537–656) to 2019 (487; 95% CrI = 436–551). In addition, accounting for availability and imperfect perception resulted in greater estimates of abundance compared to traditional directed search methods, which were 340 for 2018 and 320 for 2019. Our modeling framework can be used to generate more defensible population estimates of bighorn sheep and other large mammals that have been surveyed in a similar manner.     

Fractured Genetic Connectivity Threatens a Southern California Puma (Puma concolor) Population

Pumas (Puma concolor; also known as mountain lions and cougars) in southern California live among a burgeoning human population of roughly 20 million people. Yet little is known of the consequences of attendant habitat loss and fragmentation, and human-caused puma mortality to puma population viability and genetic diversity. We examined genetic status of pumas in coastal mountains within the Peninsular Ranges south of Los Angeles, in San Diego, Riverside, and Orange counties. The Santa Ana Mountains are bounded by urbanization to the west, north, and east, and are separated from the eastern Peninsular Ranges to the southeast by a ten lane interstate highway (I-15). We analyzed DNA samples from 97 pumas sampled between 2001 and 2012. Genotypic data for forty-six microsatellite loci revealed that pumas sampled in the Santa Ana Mountains (n = 42) displayed lower genetic diversity than pumas from nearly every other region in California tested (n = 257), including those living in the Peninsular Ranges immediately to the east across I-15 (n = 55). Santa Ana Mountains pumas had high average pairwise relatedness, high individual internal relatedness, a low estimated effective population size, and strong evidence of a bottleneck and isolation from other populations in California. These and ecological findings provide clear evidence that Santa Ana Mountains pumas have been experiencing genetic impacts related to barriers to gene flow, and are a warning signal to wildlife managers and land use planners that mitigation efforts will be needed to stem further genetic and demographic decay in the Santa Ana Mountains puma population.     

Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China

Climate change poses a serious threat to biodiversity. Predicting the effects of climate change on the distribution of a species' habitat can help humans address the potential threats which may change the scope and distribution of species. Pterocarya stenoptera is a common fast‐growing tree species often used in the ecological restoration of riverbanks and alpine forests in central and eastern China. Until now, the characteristics of the distribution of this species' habitat are poorly known as are the environmental factors that influence its preferred habitat. In the present study, the Maximum Entropy Modeling (Maxent) algorithm and the Genetic Algorithm for Ruleset Production (GARP) were used to establish the models for the potential distribution of this species by selecting 236 sites with known occurrences and 14 environmental variables. The results indicate that both models have good predictive power. Minimum temperature of coldest month (Bio6), mean temperature of warmest quarter (Bio10), annual precipitation (Bio12), and precipitation of driest month (Bio14) were important environmental variables influencing the prediction of the Maxent model. According to the models, the temperate and subtropical regions of eastern China had high environmental suitability for this species, where the species had been recorded. Under each climate change scenario, climatic suitability of the existing range of this species increased, and its climatic niche expanded geographically to the north and higher elevation. GARP predicted a more conservative expansion. The projected spatial and temporal patterns of P. stenoptera can provide reference for the development of forest management and protection strategies.     

Modelling habitat-suitability using museum collections: an example with three sympatric Apodemus species from the Alps

Aim, Location Although the alpine mouse Apodemus alpicola has been given species status since 1989, no distribution map has ever been constructed for this endemic alpine rodent in Switzerland. Based on redetermined museum material and using the Ecological-Niche Factor Analysis (ENFA), habitat-suitability maps were computed for A. alpicola , and also for the co-occurring A. flavicollis and A. sylvaticus .
Methods In the particular case of habitat suitability models, classical approaches (GLMs, GAMs, discriminant analysis, etc.) generally require presence and absence data. The presence records provided by museums can clearly give useful information about species distribution and ecology and have already been used for knowledge-based mapping. In this paper, we apply the ENFA which requires only presence data, to build a habitat-suitability map of three species of Apodemus on the basis of museum skull collections.
Results Interspecific niche comparisons showed that A. alpicola is very specialized concerning habitat selection, meaning that its habitat differs unequivocally from the average conditions in Switzerland, while both A. flavicollis and A. sylvaticus could be considered as 'generalists' in the study area.
Main conclusions Although an adequate sampling design is the best way to collect ecological data for predictive modelling, this is a time and money consuming process and there are cases where time is simply not available, as for instance with endangered species conservation. On the other hand, museums, herbariums and other similar institutions are treasuring huge presence data sets. By applying the ENFA to such data it is possible to rapidly construct a habitat suitability model. The ENFA method not only provides two key measurements regarding the niche of a species (i.e. marginality and specialization), but also has ecological meaning, and allows the scientist to compare directly the niches of different species.     

Sharing of Pasteurella spp. between free-ranging bighorn sheep and feral goats

Pasteurella spp. were isolated from feral goats and free-ranging bighorn sheep (Ovis canadensis canadensis) in the Hells Canyon National Recreation Area bordering Idaho, Oregon, and Washington (USA). Biovariant 1 Pasteurella haemolytica organisms were isolated from one goat and one of two bighorn sheep found in close association. Both isolates produced leukotoxin and had identical electrophoretic patterns of DNA fragments following cutting with restriction endonuclease HaeIII. Similarly Pasteurella multocida multocida a isolates cultured from the goat and one of the bighorn sheep had D type capsules, serotype 4 somatic antigens, produced dermonecrotoxin and had identical HaeIII electrophoretic profiles. A biovariant U(beta) P.haemolytica strain isolated from two other feral goats, not known to have been closely associated with bighorn sheep, did not produce leukotoxin but had biochemical utilization and HaeIII electrophoretic profiles identical to those of isolates from bighorn sheep. It was concluded that identical Pasteurella strains were shared by the goats and bighorn sheep. Although the direction of transmission could not be established, evidence suggests transmission of strains from goats to bighorn sheep. Goats may serve as a reservoir of Pasteurella strains that may be virulent in bighorn sheep; therefore, goats in bighorn sheep habitat should be managed to prevent contact with bighorn sheep. Bighorn sheep which have nose-to-nose contact with goats should be removed from the habitat.     

Evaluating apparent competition in limiting the recovery of an endangered ungulate

Predation can disproportionately affect endangered prey populations when generalist predators are numerically linked to more abundant primary prey. Apparent competition, the term for this phenomenon, has been increasingly implicated in the declines of endangered prey populations. We examined the potential for apparent competition to limit the recovery of Sierra Nevada bighorn sheep (Ovis canadensis sierrae), an endangered subspecies under the US Endangered Species Act. Using a combination of location, demographic, and habitat data, we assessed whether cougar (Puma concolor) predation on endangered bighorn sheep was a consequence of their winter range overlap with abundant mule deer (Odocoileus hemionus). Consistent with the apparent competition hypothesis, bighorn sheep populations with higher spatial overlap with deer exhibited higher rates of cougar predation which had additive effects on adult survival. Bighorn sheep killed by cougars were primarily located within deer winter ranges, even though those areas constituted only a portion of the bighorn sheep winter ranges. We suspect that variation in sympatry between bighorn sheep and deer populations was largely driven by differences in habitat selection among bighorn sheep herds. Indeed, bighorn sheep herds that experienced the highest rates of predation and the greatest spatial overlap with deer also exhibited the strongest selection for low elevation habitat. Although predator-mediated apparent competition may limit some populations of bighorn sheep, it is not the primary factor limiting all populations, suggesting that the dynamics of different herds are highly idiosyncratic. Management plans for endangered species should consider the spatial distributions of key competitors and predators to reduce the potential for apparent competition to hijack conservation success.     

A genome-wide set of SNPs detects population substructure and long range linkage disequilibrium in wild sheep

The development of genomic resources for wild species is still in its infancy. However, cross-species utilization of technologies developed for their domestic counterparts has the potential to unlock the genomes of organisms that currently lack genomic resources. Here, we apply the OvineSNP50 BeadChip, developed for domestic sheep, to two related wild ungulate species: the bighorn sheep (Ovis canadensis) and the thinhorn sheep (Ovis dalli). Over 95% of the domestic sheep markers were successfully genotyped in a sample of fifty-two bighorn sheep while over 90% were genotyped in two thinhorn sheep. Pooling the results from both species identified 868 single-nucleotide polymorphisms (SNPs), 570 were detected in bighorn sheep, while 330 SNPs were identified in thinhorn sheep. The total panel of SNPs was able to discriminate between the two species, assign population of origin for bighorn sheep and detect known relationship classes within one population of bighorn sheep. Using an informative subset of these SNPs (n=308), we examined the extent of genome-wide linkage disequilibrium (LD) within one population of bighorn sheep and found that high levels of LD persist over 4 Mb.     

Disease,population viability,and recovery of endangered Sierra Nevada bighorn sheep

Sierra Nevada bighorn sheep (Ovis canadensis sierrae) experienced a severe population decline after European settlement from which they have never recovered; this subspecies was listed as endangered under the United States Endangered Species Act (ESA) in 1999. Recovery of a listed species is accomplished via federally mandated recovery plans with specific population goals. Our main objective was to evaluate the potential impact of disease on the probability of meeting specific population size and persistence goals, as outlined in the Sierra Nevada bighorn sheep recovery plan. We also sought to heuristically evaluate the efficacy of management strategies aimed at reducing disease risk to or impact on modeled bighorn populations. To do this, we constructed a stochastic population projection model incorporating disease dynamics for 3 populations (Langley, Mono, Wheeler) based on data collected from 1980 to 2007. We modeled the dynamics of female bighorns in 4 age classes (lamb, yearling, adult, senescent) under 2 disease scenarios: 5% lower survival across the latter 3 age classes and persistent 65% lower lamb survival (i.e., mild) or 65% reduced survival across all age classes followed by persistent 65% lower lamb survival (i.e., severe). We simulated management strategies designed to mitigate disease risk: reducing the probability of a disease outbreak (to represent a strategy like domestic sheep grazing management) and reducing mortality rate (to represent a strategy that improved survival in the face of introduced disease). Results from our projection model indicated that management strategies need to be population specific. The population with the highest growth rate ( ; Langley; = 1.13) was more robust to the effects of disease. By contrast, the population with the lowest growth rate (Mono; = 1.00) would require management intervention beyond disease management alone, and the population with a moderate growth rate (Wheeler; = 1.07) would require management sufficient to prevent severe disease outbreaks. Because severe outbreaks increased adult mortality, disease can directly reduce the probability of meeting recovery plan goals. Although mild disease outbreaks had minimal direct effects on the populations, they reduced recruitment and the number of individuals available for translocation to other populations, which can indirectly reduce the probability of meeting overall, range-wide minimum population size goals. Based on simulation results, we recommend reducing the probability of outbreak by continuing efforts to manage high-risk (i.e., spatially close) allotments through restricted grazing regimes and stray management to ensure recovery for Wheeler and Mono. Managing bighorn and domestic sheep for geographic separation until Sierra Nevada bighorn sheep achieve recovery objectives would enhance the likelihood of population recovery. © 2011 The Wildlife Society.     

Infectious keratoconjunctivitis in bighorn sheep, Silver Bell Mountains, Arizona, USA

An infectious keratoconjunctivitis (IKC) epizootic in bighorn sheep (Ovis canadensis) occurred in the Silver Bell Mountains, Arizona, USA, from 1 December 2003 to 31 March 2004. We used standard culture methods and polymerase chain reaction (PCR) amplification of the 16S rRNA gene to test for the causative agents of IKC and other diseases reported to be associated with bighorn sheep populations. All bighorn sheep and domestic goat test results were negative except for Mycoplasma spp. and Branhamella spp. The culture and PCR results differed. Conjunctival swabs from four of 19 IKC-affected bighorn sheep tested by culture were positive for Mycoplasma spp., whereas 22 of 22 bighorn sheep samples tested by PCR were positive for Mycoplasma spp. None of 13 domestic goats tested positive by culture for Mycoplasma spp., whereas five of 16 tested positive by PCR. Three of 16 domestic goats and seven of 24 IKC-affected bighorn sheep tested positive for Branhamella spp. by culture. Bighorn sheep began showing clinical signs of IKC between 21 and 28 days following initial detection of domestic goats in bighorn sheep habitat. The IKC epizootic lasted 122 days, and individual bighorn sheep were blind for an average of 38.4 days. Given the clear potential for disease transmission to bighorn sheep, we recommend that land managers not allow the pasturing of domestic goats near occupied bighorn sheep habitat.