Research and Conservation in the Greater Gombe Ecosystem: Challenges and Opportunities.

The study of chimpanzees in Gombe National Park, Tanzania, started by Jane Goodall in 1960, provided pioneering accounts of chimpanzee behavior and ecology. With funding from multiple sources, including the Jane Goodall Institute (JGI) and grants from private foundations and federal programs, the project has continued for sixty years, providing a wealth of information about our evolutionary cousins. These chimpanzees face two main challenges to their survival: infectious disease - including simian immunodeficiency virus (SIVcpz), which can cause Acquired Immune Deficiency Syndrome (AIDS) in chimpanzees - and the deforestation of land outside the park. A health monitoring program has increased understanding of the pathogens affecting chimpanzees and has promoted measures to characterize and reduce disease risk. Deforestation reduces connections between Gombe and other chimpanzee populations, which can cause loss of genetic diversity. To promote habitat restoration, JGI facilitated participatory village land use planning, in which communities voluntarily allocated land to a network of Village Land Forest Reserves. Expected benefits to people include stabilizing watersheds, improving water supplies, and ensuring a supply of forest resources. Surveys and genetic analyses confirm that chimpanzees persist on village lands and remain connected to the Gombe population. Many challenges remain, but the regeneration of natural forest on previously degraded lands provides hope that conservation solutions can be found that benefit both people and wildlife. Conservation work in the Greater Gombe Ecosystem has helped promote broader efforts to plan and work for conservation elsewhere in Tanzania and across Africa.

Environmental determinants influencing anthrax distribution in Queen Elizabeth Protected Area, Western Uganda.

Bacillus anthracis, the bacteria that causes anthrax, a disease that primarily affects herbivorous animals, is a soil borne endospore-forming microbe. Environmental distribution of viable spores determines risky landscapes for herbivore exposure and subsequent anthrax outbreaks. Spore survival and longevity depends on suitable conditions in its environment. Anthrax is endemic in Queen Elizabeth Protected Area in western Uganda. Periodic historical outbreaks with significant wildlife losses date to 1950s, but B. anthracis ecological niche in the ecosystem is poorly understood. This study used the Maximum Entropy modeling algorithm method to predict suitable niche and environmental conditions that may support anthrax distribution and spore survival. Model inputs comprised 471 presence-only anthrax occurrence data from park management records of 1956-2010, and 11 predictor variables derived from the World Climatic and Africa Soil Grids online resources, selected considering the ecology of anthrax. The findings revealed predicted suitable niche favoring survival and distribution of anthrax spores as a narrow-restricted corridor within the study area, defined by hot-dry climatic conditions with alkaline soils rich in potassium and calcium. A mean test AUC of 0.94 and predicted probability of 0.93 for anthrax presence were registered. The five most important predictor variables that accounted for 93.8% of model variability were annual precipitation (70.1%), exchangeable potassium (12.6%), annual mean temperature (4.3%), soil pH (3.7%) and calcium (3.1%). The predicted suitable soil properties likely originate from existing sedimentary calcareous gypsum rocks. This has implications for long-term presence of B. anthracis spores and might explain the long history of anthrax experienced in the area. However, occurrence of suitable niche as a restricted hot zone offers opportunities for targeted anthrax surveillance, response and establishment of monitoring strategies in QEPA.

Ecological niche modeling as a tool for prediction of the potential geographic distribution of Bacillus anthracis spores in Tanzania.

INTRODUCTION: Anthrax is caused by the spore-forming, Gram-positive bacterium Bacillus anthracis. The aim of this study was to predict the potential distribution of B. anthracis in Tanzania and produce epidemiological evidence for the management of anthrax outbreaks in the country. METHODS: The Maxent algorithm was used to predict areas at risk of anthrax outbreaks based on the occurrence and environmental data in Arusha and Kilimanjaro regions; the model was later transferred to predict the entire country. Seventy percent of the occurrence data were used to train the model, while 30% were used for model evaluation. RESULTS: Four regions of northern Tanzania are predicted to have a high risk for anthrax outbreaks, while the southern and western regions had low-risk areas. Soil type (56.5%), soil pH (23.7%), and isothermally (10.4%) were the most important variables for the model prediction, and the most significant soil types were solonetz, fluvisols, and lithosols. CONCLUSIONS: A strong risk level across districts of the Tanzania mainland was identified in this study. A total of 18 districts in Tanzania Mainland are predicted to be at very high risk of an anthrax outbreak occurrence. These findings are important for policymakers to effectively mount targeted control measures for anthrax outbreaks in Tanzania.

Population status of chimpanzees in the Masito-Ugalla Ecosystem, Tanzania.

More than 75 percent of Tanzania's chimpanzees live at low densities on land outside national parks. Chimpanzees are one of the key conservation targets in the region and long-term monitoring of these populations is essential for assessing the overall status of ecosystem health and the success of implemented conservation strategies. We aimed to assess change in chimpanzee density within the Masito-Ugalla Ecosystem (MUE) by comparing results of re-walking the same line transects in 2007 and 2014. We further used published remote sensing data derived from Landsat satellites to assess forest cover change within a 5 km buffer of these transects over that same period. We detected no statistically significant decline in chimpanzee density across the surveyed areas of MUE between 2007 and 2014, although the overall mean density of chimpanzees declined from 0.09 individuals/km(2) in 2007 to 0.05 individuals/km(2) in 2014. Whether this change is biologically meaningful cannot be determined due to small sample sizes and large, entirely overlapping error margins. It is therefore possible that the MUE chimpanzee population has been stable over this period and indeed in some areas (Issa Valley, Mkanga, Kamkulu) even showed an increase in chimpanzee density. Variation in chimpanzee habitat preference for ranging or nesting could explain variation in density at some of the survey sites between 2007 and 2014. We also found a relationship between increasing habitat loss and lower mean chimpanzee density. Future surveys will need to ensure a larger sample size, broader geographic effort, and random survey design, to more precisely determine trends in MUE chimpanzee density and population size over time.