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Seasonal changes in the abundance and distribution of thrips (Thysanoptera) in a diverse agricultural landscape in the Levubu region, Limpopo province, South Africa
* 1 , 2 , 1 , 1
1  Department of Zoology and Entomology, Forestry and Agricultural Biotechnology Institute, University of Pretoria, Hatfield 0028, South Africa
2  Department of Conservation Ecology and Entomology, Stellenbosch University, Stellenbosch 7600, South Africa
Academic Editor: Antonella Di Palma

Abstract:

Thrips (Thysanoptera) are major pests of fruit crops globally. In South Africa, Scirtothrips aurantii Faure (Thripidae) damages avocados and macadamias, reducing their yield and profitability. Understanding the spatial distribution of S. aurantii over time will enable the targeted application of control measures. Therefore, we aimed to document the seasonal changes in the abundance, diversity, and distribution of thrips to identify areas as hot spots (high-abundance) and cold spots (low-abundance). We sampled thrips in the Levubu region of Limpopo province, South Africa, using 150 yellow sticky traps deployed at monthly intervals between September and January in the avocado and macadamia production seasons of 2021/22 and 2022/23. Eight species of thrips were encountered, namely the Caliothrips sp., Frankliniella occidentalis, the Franklinothrips sp., Haplothrips gowdeyi, Heliothrips haemorrhoidalis, the Megalunothrips sp., S. aurantii, and Thrips tenellus. Across the entire area, S. aurantii was the most abundant in September, coinciding with avocado and macadamia flowering. A geographic information system (GIS) was used to map and symbolise the mean S. aurantii sticky trap catch. An optimised hot spot analysis was used to classify and summarise trap catches aggregated into a raster layer of 1×1 km (1 km2) through the use of zonal statistics and the minimum bounding geometry. Significant S. aurantii hot spots (with 90-99% confidence) were concentrated in the hot and dry regions of the eastern and northeastern parts of Levubu, whereas significant cold spots were concentrated in the colder and wetter areas in the northwest of the region. Non-significant areas of random variation in S. aurantii's abundance were mostly found in the central region. However, the hot spot and cold spot locations changed over the months and production seasons, suggesting the potential for local microclimates, topography, vegetation type, and plant phenology as drivers of S. aurantii's distribution and abundance.

Keywords: Scirtothrips aurantii, geographical information systems, Optimised hot spot analysis, zonal statistics, hot spots, cold spots.
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