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Browsing by Author "Wayne Twine"

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Now showing 1 - 9 of 9
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    Double malnutrition and associated factors in a middleaged and older rural South African population
    Faheem Seedat; Stephen Tollman; Wayne Twine; Anne R. Cappola; Alisha Wade
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    A global survey of the societal benefits of trophy hunting in Africa
    (ELSEVIER SCI LTD) Lochran Traill; Thomas C. Wanger; Wayne Twine; Shaya van Houdt; Richard P Brown
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    Influences of Climate Variability on Land Use and Land Cover Change in Rural South Africa
    (MDPI AG) Buster Mogonong; Wayne Twine; Gregor Timothy Feig; Helga Van der Merwe; Jolene Fisher
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    Nexus between summer climate variability and household food security in rural Mpumalanga Province, South Africa
    (2023-09) Farirai Rusere; Lori Hunter; Mark Collinson; Wayne Twine
    depend on rainfed subsistence agriculture. This paper investigates the relationship between summer climate variability and household food security in rural Mpumalanga, South Africa. We used a household panel data set nested in the Agincourt Health and Socio-Demographic Surveillance System, together with rainfall and temperature data for the summer periods 2006-07 to 2018-19 from three weather stations that surround the study area. We quantified the variability of rainfall using coefficient of variation and the standardised rainfall anomaly index, while temperature variability was reflected by the standardised temperature anomaly. In addition, the Mann-Kendall analysis was applied to detect temporal trends in rainfall and temperature. Longitudinal models accounting for socioeconomic and climate factors were used to estimate the relationship between weather and climate. The results reveal significant impact on food security from high inter-annual rainfall variability through fluctuations in food consumption, dietary diversity, and the experience of hunger. This study offers significant insights on how dietary diversity, food availability and overall food security are positively associated with greater average rainfall through subsistence agriculture as a livelihood strategy. These insights have important implications by suggesting seasonal forecasts to predict periods of potential food insecurity in local communities and can guide government policy and interventions to lessen food insecurity in rural areas
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    Nontimber forest products as poverty traps Fact or fiction
    (ELSEVIER SCIENCE BV) C M Shackleton; H Garekae; M Sardeshpande; G Sinasson Sanni; Wayne Twine
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    Patterns and trends in household food security in rural Mpumalanga Province South Africa
    Farirai Rusere; Lori Hunter; Mark Collinson; Wayne Twine
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    Patterns and trends in household food security in rural Mpumalanga Province, South Africa
    (2024-02-05) Farirai Rusere; Lori Hunter; Mark Collinson; Wayne Twine
    This study examines patterns and trends in household food security in Bushbuckridge, Mpumalanga Province, South Africa, from 2010 to 2019. We use data from a household panel nested in the Agincourt Health and Socio- Demographic Surveillance System. Findings indicate that there have been improvements in household food security in this rural setting over the last decade. By polychoric principal component analysis, an aggregate food security index was constructed and we observed a small, yet important, proportion of households (7.8 %) that remained chronically food insecure. An ordered probit model was used to estimate the determinants of food security. Findings reveal that the observed differences in household food security status are as a result of differences in socioeconomic status. We therefore recommend that focus must be placed on identifying economic opportunities and empowering the chronically food insecure households if universal household food security is to be attained in rural South Africa and beyond.
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    Quantifying the role of termite decomposition in a mesic savanna
    (WILEY-BLACKWELL) Katherine Bunney; Mark Robertson; Paul Eggleton; Wayne Twine; Catherine Parr
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    Typologies of South African smallscale farmers and their risk perceptions an unsupervised machine learning approach
    (EMERALD GROUP PUBLISHING LIMITED) Sara Yazdan Bakhsh; Kingsley Ayisi; Reimund P Rotter; Wayne Twine; Jan-Henning Feil

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