Purpose
The purpose of the FAIRALL AWARD is to recognise the research of up and coming students that have submitted a manuscript to the African Journal of Wildlife Research. For this recognition, SAWMA awards an annual prize to the best journal article by a student author. This award is named in recognition to the service that Neil Fairall gave to both SAWMA and the African Journal of Wildlife Research (previously South African Journal of Wildlife Research).
Eligibility
Adjudication process
The award
The FAIRALL AWARD will be presented at the Annual SAWMA symposium each year. The winner of the award will receive;
Michelle received her award from Jeanette Fouché the SAWMA Student Representative on Council.
The 2021 best student paper was by Michelle Pretorius entitled “African wild dog movement ecology in a small protected area in SA”. (African J. of Wildlife Research, 51(1): (2021). https://doi.org/10.3957/056.051.0054
Michelle is a PhD candidate at the Institute for Communities and Wildlife in Africa a the University of Cape Town
Dramatic population declines of African wild dogs (Lycaon pictus) led to a managed metapopulation approach for wild dog conservation in South Africa. Monitoring the survival and habitat use of packs reintroduced into protected areas (PAs) is an essential part of adaptive management and improving the health and, ultimately, the survival of the metapopulation. Our study describes the territoriality and habitat selection of a pack of wild dogs reintroduced into Manyoni Private Game Reserve (219 km2) in northern KwaZulu-Natal, South Africa. Despite being introduced into a small PA, the pack only utilized half their available space (121 km2) and avoided the central areas of the reserve. Post hoc analysis of African lion (Panthera leo) localities suggested competitive avoidance was a strong factor in shaping the habitat usage of the pack; however, further research is required. Habitat selection also varied seasonally and with denning. Ultimately, we showed that spatio-temporal analyses can help identify high-risk areas within wild dog territories, such as hotspots of activity along fencelines. These analyses can then be used to increase targeted management of these areas, such as improving the maintenance of well-used fencelines, which is an important consideration for the sustained success of the metapopulation across small PAs.
The winner of the 2019 Fairall Award is Tafadzwa Shumba for his paper, “African wild dog habitat use modelling using telemetry data and citizen scientist sightings: are the results comparable?”, published in African Journal of Wildlife Research, Volume 48 Number 1, Apr 2018, p. 1 – 13.
Click here to read the article
Quantifying landscape characteristics that wildlife select is essential for conservation and management action. Models that map wildlife resource selection tend to be informed by telemetry technology which is costly to acquire/maintain and potentially risky to deploy. Therefore, there is value in pursuing alternative data collection protocols, such as citizen scientist approaches to ascertain whether they can reveal results comparable to those derived from telemetry studies. The conservation of African wild dogs (Lycaon pictus) presents an interesting case study to examine this topic. The species is rare and wide-ranging, hence data collection is both challenging and costly. They are, however, a group-living species with unique and conspicuous coat markings, making them potentially well-suited to citizen science data collection strategies. Here, we fitted resource selection functions (RSFs) built from Global Position System (GPS) telemetry data, and from citizen scientist data, collected in and around Hwange National Park, Zimbabwe. We assessed comparability of these RSFs by evaluating the relative importance of parameters, parameter coefficients (direction and magnitude of effect), and the spatial predictions of relative probability of use by African wild dogs. The most important predictors in both models were proportion of woodland and bushland, the number of habitat types, and distance to waterhole. Furthermore, spatial predictions from both models displayed a high degree of overlap (r = 0.74), indicating similarities in selected and avoided habitat patches. Our analysis demonstrates that sufficient citizen science data can be a valuable alternative to telemetry data for African wild dogs. We thus encourage the collection and use of citizen science data for similar analyses, particularly when funding is limited. Our work also highlights areas in and around Hwange National Park with the highest probability of being used by African wild dogs, which is where conservation efforts should be intensified.