Drivers of Human‒wildlife interactions in a co-existence area: a case study of the Ngorongoro conservation area, Tanzania

Communities in Africa bordering national parks or protected areas commonly overlap with wildlife. However, it is unclear to what degree such overlaps result in interactions with wildlife. The Ngorongoro Conservation Area (NCA) was designated a multiple land-use conservation area in 1959. Maasai and Datoga pastoralists and Hadzabe hunter-gatherers reside with protected wildlife in NCA. The study was carried out in four Maasai villages within the NCA, including Kayapus, Endulen, Meshili, and Nainokanoka. A cross-sectional study was used to assess drivers of human‒wildlife interactions using questionnaire surveys, focus group discussions, and field visits. A total of 396 households participated in the survey. The collected data were analysed using qualitative data analysis techniques and descriptive statistics such as frequencies and means. The habitat, which comprises water, pasture, shelter, and space, accounted for 100% of interactions, indicating that it is the primary driver of human‒wildlife conflict. Other driving factors for human‒wildlife interactions are the increase in wildlife, collections of firewood, domestic animals kept, and influence of community sleeping arrangements, searching for traditional medicines, and killing of lions for ritual purposes or defense. Large household sizes (36 family members) coupled with climate change have also driven and fuelled human‒wildlife interactions. Challenges identified as threatening human‒wildlife co-existence are injuries, deaths, disease transmission, and destruction of property. To mitigate human‒wildlife conflicts, the following are recommended: the increase in boarding schools coupled with the increase in enrolment of students in boarding schools or providing reliable transport, distribution of tap water, increasing food assistance to the community living in poverty, controlling population increase through reallocation the population in other areas, introducing zero-grazing, using biogas, discouraging community sleeping arrangements, i.e., humans with calves in the same house, improving record-keeping of the wildlife attacks, provisional dissemination of research findings to the community

Coffee, Alcohol, Smoking, Physical Activity and QT Interval Duration: Results from the Third National Health and Nutrition Examination Survey

Abnormalities in the electrocardiographic QT interval duration have been associated with an increased risk of ventricular arrhythmias and sudden cardiac death. However, there is substantial uncertainty about the effect of modifiable factors such as coffee intake, cigarette smoking, alcohol consumption, and physical activity on QT interval duration.We studied 7795 men and women from the Third National Health and Nutrition Survey (NHANES III, 1988-1994). Baseline QT interval was measured from the standard 12-lead electrocardiogram. Coffee and tea intake, alcohol consumption, leisure-time physical activities over the past month, and lifetime smoking habits were determined using validated questionnaires during the home interview.In the fully adjusted model, the average differences in QT interval comparing participants drinking ≥6 cups/day to those who did not drink any were -1.2 ms (95% CI -4.4 to 2.0) for coffee, and -2.0 ms (-11.2 to 7.3) for tea, respectively. The average differences in QT interval duration comparing current to never smokers was 1.2 ms (-0.6 to 2.9) while the average difference in QT interval duration comparing participants drinking ≥7 drinks/week to non-drinkers was 1.8 ms (-0.5 to 4.0). The age, race/ethnicity, and RR-interval adjusted differences in average QT interval duration comparing men with binge drinking episodes to non-drinkers or drinkers without binge drinking were 2.8 ms (0.4 to 5.3) and 4.0 ms (1.6 to 6.4), respectively. The corresponding differences in women were 1.1 (-2.9 to 5.2) and 1.7 ms (-2.3 to 5.7). Finally, the average differences in QT interval comparing the highest vs. the lowest categories of total physical activity was -0.8 ms (-3.0 to 1.4).Binge drinking was associated with longer QT interval in men but not in women. QT interval duration was not associated with other modifiable factors including coffee and tea intake, smoking, and physical activity

STILBENOID CONSTITUENTS IN WELWITSCHIA MIRABILIS

Welwitschia mirabilis is an endangered and unique gymnosperm of the Namibian Desert of South West Africa. It is a monotypic member of the Genus Welwitschia. Since its discovery about 140 years ago, very little is known about its chemical constituents. In the present study we report the isolation and structure elucidation of 10 new stilbenoids from the stem and root of the plant along with some known compounds. The structures of the compounds were assigned by spectroscopic analysi

Evaluation of the Variability and Frequency of Infectious Diseases in the Ngorongoro Conservation Area, Ngorongoro District in Arusha Region, Tanzania

The Ngorongoro Conservation Area (NCA) frequently experiences the emergence and re-emergence of infectious diseases. However, it is unclear how emergence varies or changes in frequency. Hence, the objective of this was to evaluate the Variability and frequency of infectious diseases in the Ngorongoro Conservation Area, Ngorongoro district in the Arusha region of Tanzania using appropriate standard methods such as questionnaire surveys, field visits, documentation reviews, and focus group discussions. A total of 396 households participated in the survey from four selected villages, Nainokanoka, Endulen, Kayapus, and Meshili, within the NCA. The collected responses were analysed to determine physical and cultural practices potentially influencing the variability and frequency of infectious diseases. The results suggest a combination of environmental factors, cultural practices, and wildlife conservation measures influence the variability and frequency of infectious diseases in the study including climatic conditions, meat consumption, and scarcity of suitable land for pasture, the presence of wildlife corridors, large livestock numbers and lack of hygiene. Diseases frequently reported to occur were Anthrax, Tuberculosis, Brucellosis, Rabies, Malignant catarrhal fever (MCF), and Malaria. Mitigating pathogens transmission risk will require mapping high-risk areas precisely and public education initiatives to minimize contact between pathogens and the populace within the study area

Drivers of Human‒wildlife interactions in a co-existence area: a case study of the Ngorongoro conservation area, Tanzania

Abstract Communities in Africa bordering national parks or protected areas commonly overlap with wildlife. However, it is unclear to what degree such overlaps result in interactions with wildlife. The Ngorongoro Conservation Area (NCA) was designated a multiple land-use conservation area in 1959. Maasai and Datoga pastoralists and Hadzabe hunter-gatherers reside with protected wildlife in NCA. The study was carried out in four Maasai villages within the NCA, including Kayapus, Endulen, Meshili, and Nainokanoka. A cross-sectional study was used to assess drivers of human‒wildlife interactions using questionnaire surveys, focus group discussions, and field visits. A total of 396 households participated in the survey. The collected data were analysed using qualitative data analysis techniques and descriptive statistics such as frequencies and means. The habitat, which comprises water, pasture, shelter, and space, accounted for 100% of interactions, indicating that it is the primary driver of human‒wildlife conflict. Other driving factors for human‒wildlife interactions are the increase in wildlife, collections of firewood, domestic animals kept, and influence of community sleeping arrangements, searching for traditional medicines, and killing of lions for ritual purposes or defense. Large household sizes (36 family members) coupled with climate change have also driven and fuelled human‒wildlife interactions. Challenges identified as threatening human‒wildlife co-existence are injuries, deaths, disease transmission, and destruction of property. To mitigate human‒wildlife conflicts, the following are recommended: the increase in boarding schools coupled with the increase in enrolment of students in boarding schools or providing reliable transport, distribution of tap water, increasing food assistance to the community living in poverty, controlling population increase through reallocation the population in other areas, introducing zero-grazing, using biogas, discouraging community sleeping arrangements, i.e., humans with calves in the same house, improving record-keeping of the wildlife attacks, provisional dissemination of research findings to the community

Size distributions of polycyclic aromatic hydrocarbons in urban atmosphere: sorption mechanism and source contributions to respiratory deposition

Current knowledge on atmospheric particle-phase polycyclic aromatic hydrocarbons (PAHs) size distribution remains incomplete. Information is missing on sorption mechanisms and the influence of the PAHs' sources on their transport in human respiratory system. Here we present the studies systematically investigating the modal distribution characteristics of the size-fractioned PAHs and calculating the source contribution to adverse health effects through inhalation. Aerosol samples with nine size fractions were collected from Shanghai urban air over one year period 2012–2013. A high correlation coefficient existed between measured and predicted values (<i>R</i>²= 0.87), indicated that the data worked very well in current study. Most PAHs were observed on the small particles followed with seasonality differences. When normalized by PAHs across particle diameters, the size distribution of PAHs exhibited bimodal patterns, with a peak (0.4–2.1 &mu;m) in fine mode and another peak (3.3–9.0 &mu;m) in coarse mode, respectively. Along with the increasing ring number of PAHs, the intensity of the fine mode peak increased, while coarse mode peak decreased. Plotting of log(PAH/PM) against log(<i>D</i>_<i>p</i>) showed that all slope values were above −1 with the increase towards less-ring PAHs, suggesting that multiple mechanisms, i.e. adsorption and absorption controlled the PAHs on particles, but adsorption played a much stronger role for 5- and 6-ring than 3- and 4-ring PAHs. The mode distribution behavior of PAHs showed that fine particles were major carriers for the more-ring PAHs. Further calculations using inhaling PAHs data showed the total deposition fluxes in respiratory tract were 8.8 ± 2.0 ng h^-1. Specifically, fine particles contributed 10–40 % of PAHs deposition fluxes to the alveolar region, while coarse particles contributed 80–95 % of ones to the head region. Estimated lifetime cancer risk (LCR) for people exercised in haze days (1.5 &times; 10^-6) was bigger than the cancer risk guideline value (10^-6). The largest PAHs contribution for LCR mainly came from the accumulation particles. Based on source apportionment results generated by positive matrix factorization (PMF), it was found that the cancer risk caused in accumulated mode mainly resulted from biomass burning (24 %), coal combustion (25 %) and vehicular emission (27 %). The present results contribute to a mechanistic understanding of PAHs size distribution causing adverse health effects and will help develop some source control strategies or policies by relying on respiratory assessment data