Population genetics of a lethally managed medium-sized predator

Globally, levels of human–wildlife conflict are increasing as a direct consequence of the expansion of people into natural areas resulting in competition with wildlife for food and other resources. By being forced into increasingly smaller pockets of suitable habitat, many animal species are at risk of becoming susceptible to loss of genetic diversity, inbreeding depression and the associated inability to adapt to environmental changes. Predators are often lethally controlled due to their threat to livestock. Predators such as jackals (black backed, golden and side striped; Canis mesomelas, C. aureus and C. adustus, respectively), red foxes (Vulpes vulpes) and coyotes (C. latrans) are highly adaptable and may respond to ongoing persecution through compensatory reproduction such as reproducing at a younger age, producing larger litters and/or compensatory immigration including dispersal into vacant territories. Despite decades of lethal management, jackals are problematic predators of livestock in South Africa and, although considered a temporary measure, culling of jackals is still common. Culling may affect social groups, kinship structure, reproductive strategies and sex-biased dispersal in this species. Here, we investigated genetic structure, variation and relatedness of 178 culled jackals on private small-livestock farms in the central Karoo of South Africa using 13 microsatellites. Genetic variation was moderate to high and was similar per year and per farm. An absence of genetic differentiation was observed based on STRUCTURE, principal component analysis and AMOVA. Relatedness was significantly higher within farms (r = 0.189) than between farms (r = 0.077), a result corroborated by spatial autocorrelation analysis. We documented 18 occurrences of dispersal events where full siblings were detected on different farms (range: 0.78–42.93 km). Distance between identified parent–offspring varied from 0 to 36.49 km. No evidence for sex-biased dispersal was found. Our results suggest that in response to ongoing lethal management, this population is most likely able to maintain genetic diversity through physiological and behavioural compensation mechanisms.APPENDIX S1. Supplementary methods.SUPPLEMENTARY TABLES. TABLE S1. Primer details for microsatellite loci used to genotype black-backed jackals (Canis Mesomelas). TABLE S2. Per-locus summary statistics as calculated in Cervus v3.0.7. The non-exclusion probabilities and combined non-exclusion probabilities (final row, italics) are relevant indicators of the power of the loci for parentage and sibship analyses. TABLE S3. Summary statistics for 20 sampling localities (farms) with >1 sample and for all farms pooled. Produced using the basicStats command of the diveRsity package v1.9.90 in R v3.6.2 and RStudio v1.2.5033. Standard deviation was calculated across loci in Microsoft Excel (stdev.s). Sampling localities with only one sample are not shown. TABLE S4. Summary statistics per year and for all years pooled. Produced using the basicStats command of the diveRsity package v1.9.90 in R v3.6.2 and RStudio v1.2.5033. Standard deviation was calculated across loci in Microsoft Excel (STDEV.S). TABLE S5. Pairwise FST values between farms with the full dataset (below diagonal) and associated significance at a level of 0.05 (above diagonal), where significant values are indicated by a “+” and non-significant values by a “−”. Calculated in Arlequin 3.5.2.2. TABLE S6. Pairwise FST values between farms with relatives removed (below diagonal) and associated significance at a level of 0.05 (above diagonal), where significant values are indicated by a “+” and non-significant values by a “−”. Calculated in Arlequin 3.5.2.2. TABLE S7. Comparison of mean pairwise relatedness (r) between years and mean individual inbreeding coefficients (F) between years. P-values for the Wilcoxon tests for difference in means are shown on the inside of the table (bordered by grey), with P-values for inbreeding comparisons shown below the diagonal (bottom left) and P-values for relatedness comparisons shown above the diagonal (top right). The mean F for each year is shown in the left-most column “outside” the main table, with the mean r for each year shown in the top row “outside” the main table. The numbers in parentheses after each year are the number of observations/data points for that year (number of samples for F and number of pairwise relatedness comparisons for r).SUPPLEMENTARY FIGURES. FIGURE S1. STRUCTURE HARVESTER results for (a) Delta K values and (b) probability (-LnPr) of K = 1–27 averaged over 20 runs and (c) genetic differentiation between the jackal sample locations (farms) based on STRUCTURE analysis (performed with K = 2–6) of 1 = GV, 2 = BB, 3 = BR, 4 = BD, 5 = DS, 6 = GG, 7 = HK, 8 = KD, 9 = KW, 10 = KK, 11 = KT, 12 = NG, 13 = ND, 14 = OG, 15 = RV, 16 = RE, 17 = RT, 18 = RD, 19 = SG, 20 = SK, 21 = VR, 22 = WK, 23 = CL, 24 = KR, 25 = WB and 26 = TD. FIGURE S2. STRUCTURE HARVESTER results for (a) Delta K values and (b) probability (-LnPr) of K = 1–27 averaged over 20 runs and (c) genetic differentiation between the jackal sample locations (farms) based on STRUCTURE analysis (performed with K = 2–6 and K = 14) of 1 = GV, 2 = BB, 3 = BD, 4 = DS, 5 = GG, 6 = HK, 7 = KW, 8 = KT, 9 = NG, 10 = ND, 11 = OG, 12 = RV, 13 = RE, 14 = RD, 15 = SG, 16 = SK, 17 = VR, 18 = WK and 19 = CL. After removing relatives, some localities had no samples, hence fewer sampling localities as compared to the full dataset. Note: The Evanno method (DeltaK) does not evaluate K = 1. FIGURE S3. Principal component analysis (PCA) of the different jackal sampling locations (farms) with related individuals removed. FIGURE S4. Plot comparing the relatedness estimates using six estimators and simulated individuals of known relatedness. Di, Dyadic likelihood estimator “DyadML”; LL, Lynch-Li estimator; LR, Lynch and Ritland estimator; QG, Queller and Goodnight estimator; Tri, Triadic likelihood estimator “TrioML”; W, Wang estimator. Plot produced with ggplot2 3.3.0 (Wickham, 2016). FIGURE S5. Results of the spatial autocorrelation analysis for A females and B males. The blue line indicates the autocorrelation coefficient of the data, with the 95% confidence interval at each distance class indicated by the black error bars, as determined by 1000 bootstrap resampling replicates. The red dashed lines indicate the 95% confidence interval around the null hypothesis (no spatial structure, i.e. rauto = 0), as determined by permutation (999 steps). Thus, if the error bars around the blue line do not overlap with the red dashed lines in a distance class, then genotypes were more (positive rauto) or less (negative rauto) similar than expected under the null hypothesis in that distance class. Such cases are indicated with an asterisk (*).The National Zoological Gardens, Pretoria and the University of South Africa.https://zslpublications.onlinelibrary.wiley.com/journal/14697998hj2023BiochemistryGeneticsMicrobiology and Plant Patholog

Assessing introgressive hybridization in roan antelope (Hippotragus equinus):Lessons from South Africa

Biological diversity is being lost at unprecedented rates, with genetic admixture and introgression presenting major threats to biodiversity. Our ability to accurately identify introgression is critical to manage species, obtain insights into evolutionary processes, and ultimately contribute to the Aichi Targets developed under the Convention on Biological Diversity. The current study concerns roan antelope, the second largest antelope in Africa. Despite their large size, these antelope are sensitive to habitat disturbance and interspecific competition, leading to the species being listed as Least Concern but with decreasing population trends, and as extinct over parts of its range. Molecular research identified the presence of two evolutionary significant units across their sub-Saharan range, corresponding to a West African lineage and a second larger group which includes animals from East, Central and Southern Africa. Within South Africa, one of the remaining bastions with increasing population sizes, there are a number of West African roan antelope populations on private farms, and concerns are that these animals hybridize with roan that naturally occur in the southern African region. We used a suite of 27 microsatellite markers to conduct admixture analysis. Our results indicate evidence of hybridization, with our developed tests using a simulated dataset being able to accurately identify F1, F2 and non-admixed individuals at threshold values of qi > 0.80 and qi > 0.85. However, further backcrosses were not always detectable with backcrossed-Western roan individuals (46.7-60%), backcrossed-East, Central and Southern African roan individuals (28.3-45%) and double backcrossed (83.3-98.3%) being incorrectly classified as non-admixed. Our study is the first to confirm ongoing hybridization in this within this iconic African antelope, and we provide recommendations for the future conservation and management of this species

Hybridization in an isolated population of blesbok and red hartebeest

Hybridization in antelope species has been widely reported in South African national parks and provincial reserves as well as on private land due to anthropogenic effects. In a closed management setting, hybridization may occur due to the crossbreeding of closely related species with unequal sex ratios, resulting in either sterile or fertile offspring. In this study, we used molecular techniques to evaluate the risk of anthropogenic hybridization between blesbok (Damaliscus pygargus phillipsi) and red hartebeest (Alcelaphus buselaphus caama) in an isolated group that purposely included the two species with unequal sex ratios (one red hartebeest male and 19 male and female blesbok). Genetic analysis based on microsatellites confirmed the presence of seven hybrid individuals. Mitochondrial analysis verified that hybridization occurred between blesbok females and the red hartebeest male. STRUCTURE and NEWHYBRIDS classified the hybrids as F1. It is suspected that the hybrid individuals were sterile as the males had undeveloped testes and only F1 hybrids were detected. Thus, the risk of hybridization between these two species may be limited in the wild. In captive settings, genetic monitoring should be included in management plans for blesbok and red hartebeest to ensure that the long-term consequences of wasted reproductive effort are limited

Broad-scale genetic assessment of Southern Ground-Hornbills (Bucorvus leadbeateri) to inform population management.

The Southern Ground-hornbill (SGH) (Bucorvus leadbeateri) is considered an umbrella species for biodiversity conservation in savannah biomes since they require large territories and significant protection measures that help to conserve a wide range of biodiversity with similar savanna and grassland requirements. Declines of the species are attributed to low reproductive rates coupled with multiple anthropogenic threats, including secondary poisoning, and persecution. Little is known about connectivity and population structure of SGH populations in Africa, south of the equator. Knowledge of population differentiation is needed to ensure that targeted conservation management plans can be implemented to slow population declines and ensure survival of the species. To inform a long-term conservation strategy, we investigated the broad-scale population structure of Southern Ground-hornbill across their sub-equatorial range. Our study based on 16 microsatellite loci identified moderate variation (average of 5.889 alleles per locus and a mean observed heterozygosity of 0.546) similar to other long-lived avian species. In contrast, mitochondrial DNA sequences analysis identified low diversity (Hd = 0.3313, π = 0.0015). A Bayesian assignment approach, principal component analysis, analysis of molecular variance and phylogenetic analysis identified weak to moderate population structuring across long distances and mitochondrial data showed a shallow phylogeny. Restriction to long-distance dispersal was detected that could not be attributed to isolation by distance, suggesting that other factors, such as their dispersal biology, are shaping the observed genetic differentiation. Although our study does not support the designation of populations as independent conservation units, we advocate that population management should continue to follow the Precautionary Principle (mixing founders from the same range state, rather than allowing mixing of founders from the extremes of the range) until there is scientific certainty. Following further research, if no independent conservation units are detected, then the global captive population can contribute to reintroductions across the range. In the wild, populations at the edge of the species range may need additional management strategies and gene flow should be promoted between neighbouring populations

Lessons for conservation management: Monitoring temporal changes in genetic diversity of Cape mountain zebra (Equus zebra zebra)

The Cape mountain zebra (Equus zebra zebra) is a subspecies of mountain zebra endemic to South Africa. The Cape mountain zebra experienced near extinction in the early 1900's and their numbers have since recovered to more than 4,800 individuals. However, there are still threats to their long-term persistence. A previous study reported that Cape mountain zebra had low genetic diversity in three relict populations and that urgent conservation management actions were needed to mitigate the risk of further loss. As these suggestions went largely unheeded, we undertook the present study, fifteen years later to determine the impact of management on genetic diversity in three key populations. Our results show a substantial loss of heterozygosity across the Cape mountain zebra populations studied. The most severe losses occurred at De Hoop Nature Reserve where expected heterozygosity reduced by 22.85% from 0.385 to 0.297. This is alarming, as the De Hoop Nature Reserve was previously identified as the most genetically diverse population owing to its founders originating from two of the three remaining relict stocks. Furthermore, we observed a complete loss of multiple private alleles from all populations, and a related reduction in genetic structure across the subspecies. These losses could lead to inbreeding depression and reduce the evolutionary potential of the Cape mountain zebra. We recommend immediate implementation of evidence-based genetic management and monitoring to prevent further losses, which could jeopardise the long term survival of Cape mountain zebra, especially in the face of habitat and climate change and emerging diseases

Screening tests for active pulmonary tuberculosis in children

Objectives This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To determine the sensitivity, specificity, and positive and negative predictive value of 1) the presence of one or more tuberculosis symptoms, or symptom combinations; 2) chest radiography; 3) Xpert MTB/RIF; 4) Xpert Ultra; and 5) combinations of the aforementioned tests as screening tests for detecting active pulmonary tuberculosis in children in the following groups. Household contacts of a person with active tuberculosis; School contacts of a person with active tuberculosis; Other close contacts of a person with active tuberculosis; Children living with HIV; Children with pneumonia; Other risk groups (e.g. children with a history of previous tuberculosis, malnourished children); Children in the general population in high burden settings Secondary objectives To compare the accuracy of the different index tests, including different applications of tests (e.g. CXR with any abnormality versus, more specifically, CXR with abnormality suggestive of tuberculosis); we are interested in the accuracy of the index tests in any setting (i.e. community, outpatient, and inpatient). To investigate potential sources of heterogeneity in accuracy estimates in relation to age group, HIV status, whether the study was conducted in a high tuberculosis burden country, and whether the child received a single screening or more than one screening

The contribution of digital sequence information to conservation biology: a Southern African perspective

Many recent contributions have made a compelling case that genetic diversity is not adequately reflected in international frameworks and policies, as well as in local governmental processes implementing such frameworks. Using digital sequence information (DSI) and other publicly available data is supported to assess genetic diversity, toward formulation of practical actions for long‐term conservation of biodiversity, with the particular goal of maintaining ecological and evolutionary processes. Given the inclusion of specific goals and targets regarding DSI in the latest draft of the Global Biodiversity Framework negotiated at the 15th Conference of the Parties (COP15) in Montreal in December 2022 and the crucial decisions on access and benefit sharing to DSI that will be taken in the coming months and future COP meetings, a southern African perspective on how and why open access to DSI is essential for the conservation of intraspecific biodiversity (genetic diversity and structure) across country borders is provided

Interspecific hybridization between greater kudu and nyala

Hybridization of wildlife species, even in the absence of introgression, is of concern due to wasted reproductive effort and a reduction in productivity. In this study we detail an accidental mating between a female nyala (Tragelaphus angasii) and a male greater kudu (T. strepsiceros). The hybrid was phenotypically nyala and was identified as such based on mitochondrial DNA. Further genetic analysis based on nine microsatellite markers, chromosome number and chromosome morphology however, confirmed its status as an F1 hybrid. Results obtained from a reproductive potential assessment indicated that this animal does not have the potential to breed successfully and can be considered as sterile.http://link.springer.com/journal/10709hb201