Perceptions of Climate Change and Drivers of Insect Pest Outbreaks in Vegetable Crops in Limpopo Province of South Africa

Ontogenetic responses of physiological fitness in Spodoptera frugiperda (Lepidoptera: Noctuidae) in response to repeated cold exposure

In this era of global climate change, intrinsic rapid and evolutionary responses of invasive agricultural pests to thermal variability are of concern given the potential implications on their biogeography and dire consequences on human food security. For insects, chill coma recovery time (CCRT) and critical thermal minima (CTmin), the point at which neuromuscular coordination is lost following cold exposure, remain good indices for cold tolerance. Using laboratory-reared Spodoptera frugiperda (Lepidoptera: Noctuidae), we explored cold tolerance repeated exposure across life stages of this invasive insect pest. Specifically, we measured their CTmin and CCRT across four consecutive assays, each 24 h apart. In addition, we assessed body water content (BWC) and body lipid content (BLC) of the life stages. Our results showed that CTmin improved with repeated exposure in 5th instar larvae, virgin males and females while CCRT improved in 4th, 5th and 6th instar larvae following repeated cold exposure. In addition, the results revealed evidence of cold hardening in this invasive insect pest. However, there was no correlation between cold tolerance and BWC as well as BLC. Our results show capacity for cold hardening and population persistence of S. frugiperda in cooler environments. This suggests potential of fall armyworm (FAW) to withstand considerable harsh winter environments typical of its recently invaded geographic range in sub-Saharan Africa.

Disentangling a Neotropical pest species complex: genetic diversity and population structure of the native rice stink bug Oebalus poecilus and the invasive O. ypsilongriseus

BACKGROUND

A first step in any pest management initiative is recognizing the existing problem - identifying the pest species and its abundance and dispersal capacities. This is not simple and even more challenging when insidious (invasive) species are involved constituting a pest complex. Understanding a species' population diversity and structure can provide a better understanding of its adaptation and relative pest potential. Such is the need for the native rice stink bug Oebalus poecilus and the invasive O. ypsilongriseus in low and high flatlands of South America.

RESULTS

The genetic structure differed between both rice stink bug species (F_ST  = 0.157, P = 0.001), where 84% of the overall genetic variability takes place within species and three genetic groups were recognized through Bayesian approach (K = 3). Oebalus poecilus exhibited slightly higher genetic diversity (H_E  = 0.253) and structuring (F_ST  = 0.050, P = 0.001) than the invasive O. ypsilongriseus (H_E  = 0.211; F_ST  = 0.038, P = 0.013). Nonetheless, only the former exhibited significant correlation between genetic and geographic distances (r = 0.48, P = 0.013).

CONCLUSION

Despite the pointed peculiarities, the obtained results indicate overlap in both species' occurrence and similar genetic structure allowing for a compound problem to be dealt with as the complex requires managing without, as yet, a prevailing species or a niche specialization. © 2022 Society of Chemical Industry.

Assessment of the effects of climate change on the occurrence of tomato invasive insect pests in Uganda

The shift in the geographical spread of invasive pests in Africa has rarely been linked directly to climate change. However, it is predicted that environmental changes play a significant role in spreading and expanding pests. The occurrence of new tomato invasive insect pests has been increasing in Uganda during the past century. Assessing the impact of temperature, rainfall, relative humidity, and windspeed on the occurrence of invasive tomato insect pests, gives a better understanding of managing and limiting the bio-invasion process sustainably. We used the Mann Kendall trend Test to establish trends in climate variables from 1981 to 2020 and to document the trend in the occurrence of new invasive pests. The relationship between climate variables and pests occurrence is analyzed using Pearson's correlation and the Generalized Linear Model (GLM-quasi-Poisson) in R-software. The results showed that temperature and windspeed have significantly increased in both Kampala and Namutumba by 0.049 °C, 0.005 m ^s-1and by 0.037 °C, 0.003 m ^s-1 per year respectively while in Mbale there was no change in wind speed pattern and a non-significant decrease in temperature. There was an overall rainfall increase in Kampala (p = 0.029) by 0.241 mm, Mbale (p = 0.0011) by 9.804 mm, and Namutumba (p = 0.394) by 0.025 mm. On the other hand, humidity has decreased both in Kampala (p = 0.001) by 13.3% and in Namutumba (p = 0.035) by 13.2% while there was a no significant change in Mbale. The results of GLM showed that each variable, taken individually, had a direct effect on the pests' occurrence in all three districts. However, with all these climate variables taken together, the effect on the pests' occurrence varied with each of the three districts; Kampala, Mbale, and Namutumba. This study demonstrated that pest occurrence is different from one agroecology to another. Our findings suggest that climate change is a driver that favors bio-invasion of tomato invasive insect pests occurrence in Uganda. It calls for awareness to policymakers and stakeholders to consider climate-smart pest management practices and policies to deal with bio-invasion.

Modelling of Extremely High Rainfall in Limpopo Province of South Africa

Extreme value theory is a powerful method that is known to provide statistical models for events rarely observed. This paper presents a modelling framework for the maximum rainfall data recorded in Limpopo province, South Africa, from 1960 to 2020. Daily and monthly rainfall data were obtained from the South Africa Weather Service. In this work, the r-largest order statistics modelling approach is used. Yearly blocks were used in fitting a 61 years’ data set. The parameters of the developed models were estimated using the maximum likelihood method. After the suitable model for data was chosen, i.e., GEVDr=8, the 50-year return level was estimated as 368 mm, which means a probability of 0.02 exceeding 368 mm in fifty years in the Thabazimbi area. This study helps decision-makers in government and non-profit organisations improve preparation strategies and build resilience in reducing disasters resulting from extreme weather events such as excessive rainfall.

Developing climate-resilient crops: improving plant tolerance to stress combination

Global warming and climate change are driving an alarming increase in the frequency and intensity of different abiotic stresses, such as droughts, heat waves, cold snaps, and flooding, negatively affecting crop yields and causing food shortages. Climate change is also altering the composition and behavior of different insect and pathogen populations adding to yield losses worldwide. Additional constraints to agriculture are caused by the increasing amounts of human-generated pollutants, as well as the negative impact of climate change on soil microbiomes. Although in the laboratory, we are trained to study the impact of individual stress conditions on plants, in the field many stresses, pollutants, and pests could simultaneously or sequentially affect plants, causing conditions of stress combination. Because climate change is expected to increase the frequency and intensity of such stress combination events (e.g., heat waves combined with drought, flooding, or other abiotic stresses, pollutants, and/or pathogens), a concentrated effort is needed to study how stress combination is affecting crops. This need is particularly critical, as many studies have shown that the response of plants to stress combination is unique and cannot be predicted from simply studying each of the different stresses that are part of the stress combination. Strategies to enhance crop tolerance to a particular stress may therefore fail to enhance tolerance to this specific stress, when combined with other factors. Here we review recent studies of stress combinations in different plants and propose new approaches and avenues for the development of stress combination- and climate change-resilient crops.

Modelling temperature extremes in the Limpopo province: bivariate time-varying threshold excess approach

A common problem that arises in extreme value theory when dealing with several variables (such as weather or meteorological) is to find an appropriate method to assess their joint or conditional multivariate extremal dependence behaviour. The method for choosing an appropriate threshold in peaks-over threshold approach is also another problem of endless debate. In this era of climate change and global warming, extreme temperatures accompanied by heat waves and cold waves pose serious economic and health challenges particularly in small economies or developing countries like South Africa. The present study attempts to address these problems, in particular, to deal with and capture dependencies in extreme values of two variables, by applying bivariate conditional extremes modelling with a time-varying threshold to Limpopo province's monthly maximum temperature series. Limpopo and North West provinces are the two hottest provinces in South Africa characterised by heat waves and the present study is carried out in the Limpopo province at Mara, Messina, Polokwane and Thabazimbi meteorological stations for the period 1994-2009. With the aim to model extremal dependence of maximum temperature at these four meteorological stations, two modelling approaches are applied: bivariate conditional extremes model and time-varying threshold. The latter approach was used to capture the climate change effects in the data. The main contribution of this paper is in combining these two approaches in bivariate extremal dependence modelling of maximum temperature extremes in the Limpopo province of South Africa. The findings of the study revealed both significant positive and negative extremal dependence in some pairs of meteorological stations. Among the major findings were the significant strong positive extremal dependence of Thabazimbi on high-temperature values at Mara and the strong negative extremal dependence of Polokwane on high-temperature values at Messina. The findings of this study play an important role in revealing information useful to meteorologists, climatologists, agriculturalists, and planners in the energy sector among others.