Extreme climatic effects hamper livestock production in Somalia

Ticks and tick-borne pathogens of domestic animals in Somalia and neighbouring regions of Ethiopia and Kenya

Ticks and tick-borne pathogens (TBPs) of domestic animals in Somalia and neighbouring regions of Ethiopia and Kenya are reviewed to identify knowledge gaps in these regions, where unrestricted livestock movements across borders are common. Major scientific databases, such as PubMed, Web of Science, Scopus, CABI, and Google Scholar were searched, to retrieve articles based on papers published between 1960 and March 2023. Thirty-one tick species representing six genera (Rhipicephalus, Hyalomma, Amblyomma, Haemaphysalis, Ornithodoros and Argas) were reported to infest domestic animals, mainly livestock. Overall, the most represented species were Rhipicephalus pulchellus (up to 60% of specimens identified), followed by Hyalomma dromedarii (up to 57%), Hyalomma truncatum (up to 57%), Amblyomma lepidum (up to 21%), Amblyomma variegatum (up to 21%) and Amblyomma gemma (up to 19%), with morphological characterization being the principal method of tick identification. In addition, 18 TBPs, including zoonotic pathogens (e.g., Crimean-Congo haemorrhagic fever virus), were detected, with Babesia spp., Theileria spp., and Rickettsia spp. being the most commonly reported. Half of the pathogens documented were detected using molecular techniques, while the other half were detected by serology and microscopic techniques. Generally, ticks and TBPs in the region are under-studied, particularly, data relating to pet animals and equines is lacking. Further, the infection intensity and herd prevalence of ticks and TBPs is unclear because of insufficient data and poor approaches to quantitative analysis, making it difficult to propose management policies in the region. There is an urgent need, therefore, for more and better studies, particularly those that take a 'One Health' perspective, focusing on the prevalence and socio-economic impact of ticks and TBPs in animals as well as in humans, so that sustainable control strategies against them can be planned.

Modelling the impacts of climate change on cereal crop production in East Africa: evidence from heterogeneous panel cointegration analysis

Climate change has become an issue of concern for sustainable agriculture production. East African nations are heavily reliant on the agriculture sector, which accounts for a substantial amount of their gross domestic product (GDP) and employment. Due to climatic fluctuations, the output of the sector became very unpredictable. Hence, this study investigates the effects of climate change on cereal crop production in nine East African nations between 1990 and 2018. The study implemented pooled mean group (PMG) approach to examine the long-run and short-run dynamic impacts of the varying climatic circumstances on the output of cereal crops. The results reveal that rainfall and carbon emissions have favourable and significant long-run effects on cereal crop output, even though their short-run impacts are negligible. Additionally, cultivated land area and rural population have a constructive role in enhancing agricultural output both in the long-run and short-run. However, average temperatures have negative repercussions on cereal crop production in the long-run and short-run, even though the magnitude of sensitivity is greater in the short-run. Dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) validated the robustness of the long-run findings of the PMG technique. Besides, the Dumitrescu-Hurlin panel causality outcomes indicate that cereal crop output has a bidirectional causality with temperature, carbon emissions, and cropped area. The study further demonstrated unidirectional causation from rural population to cereal crop yield. The study recommends that East African policymakers improve the quality of farm inputs, the adoption of climate-resilient farming practices, the development of water retention facilities and the establishment of crop diversification initiatives.

The relationship between environmental degradation, agricultural crops, and livestock production in Somalia

Climate change is an imminent threat to both developing and developed countries. Various determinants of climate change have been discovered in the literature including, inter alia, the agriculture sector. To this end, this study models the role of agricultural crops - maize, sesame, sorghum, and wheat productions - and livestock production in environmental degradation in Somalia for the period of 1985 to 2017. The study applied the autoregressive distributed lag model (ARDL) for the long-run cointegration between the variables, and vector error correction modeling (VECM) for short- and long-run causalities among the variables. The empirical result revealed the presence of a long-run cointegration between environmental degradation, agricultural crops, and livestock production. All the crops and livestock production increase environmental degradation except wheat production which has a constructive role in reducing environmental degradation in the long run. In contrast, the VECM results detected a short-run causality from sorghum to livestock production. Environmental degradation, sesame, sorghum, and wheat productions cause maize production significantly in the short run as well as in the long run. Moreover, sesame production causes sorghum production in the short run. Likewise, a long-run causality is established from environmental degradation, maize, sesame, livestock, and wheat production to sorghum production. However, Somalia policymakers should institute agricultural policies that are not only sustainable for agricultural production practices to meet the growing food demand but also sustainable to the environment.

Examining the effects of climate change and political instability on maize production in Somalia

Agricultural production is sensitive to climate variability, so climate change-agriculture sector nexus is topical in developing countries. To this end, this study examines the impact of climate change variables-rainfall and temperature-and non-climatic factors on maize production in Somalia for the period between 1980 and 2018 using the autoregressive distributed lag (ARDL) bound test, dynamic ordinary least square (DOLS), variance decomposition(VD), and impulse response function (IRF). The empirical results of the ARDL bound test confirmed the presence of long-run cointegration between the dependent variable and the explanatory variables. Furthermore, the long-run results revealed that average temperature, average rainfall, and political instability significantly inhibit maize production in the long and short runs, but rainfall has a favorable effect on maize production in the short run. Furthermore, rural population and land area under maize cultivation have negative and positive effects on maize production in the long run, respectively-albeit they are statistically insignificant. The empirical results of the study are robust to different econometric methods. Based on these findings, the study emphasizes the importance of the de-escalation of conflicts and the implementation of irrigation facilities which will enhance the productivity of maize crop production.