Ethics was granted under the Cape Peninsula University of Technology (201016974/01/2020) and Nottingham Trent University (#ARE192039). Even though Livestock Guardian Dogs (LGDs) have shown to be an effective form of reducing livestock predation (Coppinger, 1988; Green and Woodruff, 1988; Marker et al., 2005; Rust et al., 2013; Potgieter et al., 2015; Eklund et al., 2017; Whitehouse-Tedd et al., 2019; Marker et al., 2020; Spencer et al., 2020), not all landholders use LGDs. This study aims to understand the factors that determine or influence LGD use and to design a framework to understand the drivers behind LGD use by landholders in South Africa. The dataset is a survey response comprising of 128 questionnaire items for two stakeholder groups being, livestock farmers using LGDs and those not using LGDs. The questionnaire was divided into the following nine sections: (1) A series of sociodemographic factors, (2) the type and number of farming enterprises and size of the livestock herd and/or flocks, (3) the livestock depredation mitigation methods, (4) the predator type and factors relating to predators, (5) tangible and intangible costs of predators, (6) Wildlife Tolerance Model (WTM) variables (Kansky et al., 2016), (7) Wildlife Value Orientation (WVO) variables (Teel et al., 2010), (8) perspective-taking aspects of empathy and finally, (9) awareness amongst farmers of seven organizations related to depredation management. Of these organizations, two are focused on LGD placement and management, and the other five organizations are general farming support organizations which include some depredation management and mitigation. Both commercial and subsistence farms from eight of the nine provinces were recorded – no participants from Gauteng as no livestock farmers were included in this province – in South Africa. Participants were selected based primarily on predator related interaction as opposed to geography or sociodemographic variables. Participants were informed that the survey was to be utilized in understanding the use of mitigation methods in a HWC context. In the case of LGD users, participants were informed that this was a LGD mitigation method focused study. Farmers not using LGDs as a mitigation method were then investigated as to the other lethal and/or non-lethal mitigation methods they were using. Due to restrictions and challenges posed by COVID with in-person questionnaires, I designed an online questionnaire using the software alchemer (https://www.alchemer.com/). Alchemer allows for advanced coding enabling target question-based display logic and the validation of questions based on certain selection criteria. All 113 completed responses were answered on the online platform. Attempts to reduce non-response bias included the anonymization of data and follow-up communication with non-responders. Although all participants gave signed consent for the use of their anonymized data, please note that due to the Protection of Personal Information Act (POPI), this is sensitive and private data that should not be shared publicly.

Infestations by the parasitic weed genus Striga result in significant losses to cereal crop yields across sub-Saharan Africa. The problem disproportionately affects subsistence farmers who frequently lack access to novel technologies. Effective Striga management therefore requires the development of strategies utilising existing cultural management practices. We report a multi-year, landscape-scale monitoring project for Striga asiatica in the mid-west of Madagascar, undertaken over 2019-2020 with the aims of examining cultural, climatic and edaphic factors currently driving abundance and distribution. Long-distance transects were established across the middle-west region of Madagascar, over which Striga asiatica abundance in fields was estimated. Analysis of the data highlights the importance of crop variety and legumes in driving Striga density. Moreover, the dataset revealed significant effect of precipitation seasonality, mean temperature and altitude in determining abundance. A com...

Duration of illness, number of caregivers, lost workdays, loss of income and indirect costs per VL episode in US$ (1US$ = 28.91 ET Birr in 2019).