The lion Panthera leo is one of the world's most charismatic carnivores and is one of Africa's key predators. Here, we used a large dataset from 357 lions comprehending 1.13 megabases of sequence data and genotypes from 22 microsatellite loci to characterize its recent evolutionary history. Patterns of molecular genetic variation in multiple maternal (mtDNA), paternal (Y-chromosome), and biparental nuclear (nDNA) genetic markers were compared with patterns of sequence and subtype variation of the lion feline immunodeficiency virus (FIVPle), a lentivirus analogous to human immunodeficiency virus (HIV). In spite of the ability of lions to disperse long distances, patterns of lion genetic diversity suggest substantial population subdivision (mtDNA ΦST = 0.92; nDNA F ST = 0.18), and reduced gene flow, which, along with large differences in sero-prevalence of six distinct FIVPle subtypes among lion populations, refute the hypothesis that African lions consist of a single panmictic population. Our results suggest that extant lion populations derive from several Pleistocene refugia in East and Southern Africa (∼324,000–169,000 years ago), which expanded during the Late Pleistocene (∼100,000 years ago) into Central and North Africa and into Asia. During the Pleistocene/Holocene transition (∼14,000–7,000 years), another expansion occurred from southern refugia northwards towards East Africa, causing population interbreeding. In particular, lion and FIVPle variation affirms that the large, well-studied lion population occupying the greater Serengeti Ecosystem is derived from three distinct populations that admixed recently.
Within protected areas, biodiversity loss is often a consequence of illegal resource use. Understanding the patterns and extent of illegal activities is therefore essential for effective law enforcement and prevention of biodiversity declines. We used extensive data, commonly collected by ranger patrols in many protected areas, and Bayesian hierarchical models to identify drivers, trends, and distribution of multiple illegal activities within the Queen Elizabeth Conservation Area (QECA), Uganda. Encroachment (e.g., by pastoralists with cattle) and poaching of noncommercial animals (e.g., snaring bushmeat) were the most prevalent illegal activities within the QECA. Illegal activities occurred in different areas of the QECA. Poaching of noncommercial animals was most widely distributed within the national park. Overall, ecological covariates, although significant, were not useful predictors for occurrence of illegal activities. Instead, the location of illegal activities in previous years was more important. There were significant increases in encroachment and noncommercial plant harvesting (nontimber products) during the study period (1999-2012). We also found significant spatiotemporal variation in the occurrence of all activities. Our results show the need to explicitly model ranger patrol effort to reduce biases from existing uncorrected or capture per unit effort analyses. Prioritization of ranger patrol strategies is needed to target illegal activities; these strategies are determined by protected area managers, and therefore changes at a site-level can be implemented quickly. These strategies should also be informed by the location of past occurrences of illegal activity: the most useful predictor of future events. However, because spatial and temporal changes in illegal activities occurred, regular patrols throughout the protected area, even in areas of low occurrence, are also required.
Summary1. In many countries, areas delineated for conservation purposes can only achieve their objectives if effective law enforcement occurs within them. However, there is no method currently available to allocate law enforcement effort in a way that protects species and habitats in a cost-effective manner. Law enforcement is expensive and effort is usually concentrated near the locations of patrol stations where rangers are based. This hampers effective conservation, particularly in large protected areas, or regions with limited enforcement capacity. 2. Using the spatial planning tool Marxan, we demonstrate a method for prioritizing law enforcement in a globally important conservation landscape (the Greater Virunga Landscape, GVL, in central Africa) using data on the spatial distribution of illegal activities and conservation features within the landscape. 3. Our analysis of current patrol data shows that law enforcement activity is inadequate with only 22% of the landscape being effectively patrolled and most of this activity occurring within 3 km of a patrol post. We show that the current patrol effort does not deter illegal activities beyond this distance. 4. We discover that when we account for the costs of effective patrolling and set targets for covering key species populations and habitats, we can reduce the costs of meeting all conservation targets in the landscape by 63%, to $2Á2-3Á0 million USD, relative to the cost of patrolling the entire landscape. This cost is well within the current expenditure of approximately $5Á9 million USD for the GVL but would better target effort from both patrol posts and mobile patrol units in the landscape. 5. Synthesis and applications. Our results demonstrate a method that can be used to plan enforcement patrolling, resulting in more cost-efficient prevention of illegal activities in a way that is targeted at halting declines in species of conservation concern.
Protected areas are fundamental for conservation, yet are constantly threatened by illegal activities, such as cattle encroachment and wildlife poaching, which reduce biodiversity. Law enforcement is an essential component of reducing illegal activities. Although necessary, law enforcement is costly and its effectiveness in the field is rarely monitored. Improving ranger patrol efficiency is likely to decrease illegal activity occurrence and benefit biodiversity conservation, without additional resource implications. Using ranger-collected data, we develop a method to improve ranger patrol allocation, targeting different combinations of conservation priorities, and predict that detections of illegal activities can be greatly improved. In a field test in Queen Elizabeth Protected Area, Uganda, we increased detections of illegal activities in some cases by over 250% without a change in ranger resources. This easily implemented method can be used in any protected area where data on the distribution of illegal activities are collected, and improve law-enforcement efficiency in resource-limited settings.
BackgroundAnthrax is a zoonotic disease primarily of herbivores, caused by Bacillus anthracis, a bacterium with diverse geographical and global distribution. Globally, livestock outbreaks have declined but in Africa significant outbreaks continue to occur with most countries still categorized as enzootic, hyper endemic or sporadic. Uganda experiences sporadic human and livestock cases. Severe large-scale outbreaks occur periodically in hippos (Hippopotamus amphibious) at Queen Elizabeth Protected Area, where in 2004/2005 and 2010 anthrax killed 437 hippos. Ecological drivers of these outbreaks and potential of hippos to maintain anthrax in the ecosystem remain unknown. This study aimed to describe spatio-temporal patterns of anthrax among hippos; examine significant trends associated with case distributions; and generate hypotheses for investigation of ecological drivers of anthrax.MethodsSpatio-temporal patterns of 317 hippo cases in 2004/5 and 137 in 2010 were analyzed. QGIS was used to examine case distributions; Spearman’s nonparametric tests to determine correlations between cases and at-risk hippo populations; permutation models of the spatial scan statistics to examine spatio-temporal clustering of cases; directional tests to determine directionality in epidemic movements; and standard epidemic curves to determine patterns of epidemic propagation.Key findingsResults showed hippopotamus cases extensively distributed along water shorelines with strong positive correlations (p<0.01) between cases and at-risk populations. Significant (p<0.001) spatio-temporal clustering of cases occurred throughout the epidemics, pointing towards a defined source. Significant directional epidemic spread was detected along water flow gradient (206.6°) in 2004/5 and against flow gradient (20.4°) in 2010. Temporal distributions showed clustered pulsed epidemic waves.ConclusionThese findings suggest mixed point-source propagated pattern of epidemic spread amongst hippos and points to likelihood of indirect spread of anthrax spores between hippos mediated by their social behaviour, forces of water flow, and persistent presence of infectious carcasses amidst schools. This information sheds light on the epidemiology of anthrax in highly social wildlife, can help drive insight into disease control, wildlife conservation, and tourism management, but highlights the need for analytical and longitudinal studies aimed at clarifying the hypotheses.
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