Most studies on climate change adaptation strategies adoption have focused on economic factors with little or no attention to the impact of collective actions and social capital networks. This paper investigates how farmers' participation in social capital networks influenced climate change adaptation strategies adoption in Nigeria. This study was carried out in the South-western Nigeria. Data were analysed using descriptive statistics, binary probit regression, multinomial logit regression, endogenous switching regression and multinomial endogenous switching regression models. The results suggest that significant differences exist in the years of membership in the social capital networks, access to weather information and market between farm managers who adopted climate change adaptation strategies and those who did not. Plot managers who adopted climate change adaptation strategies are found to have obtained much mean yield and farm revenue than their counterparts. The results further show that participation in the social capital networks does not only significantly influence plot manager's decision to adopt but also influences the choice of climate change adaptation strategies adopted by farmers. The study concludes that a farmer who chooses to participate in social capital networks has a higher level of adopting climate change adaptation strategies than what a random farmer would have had in Nigeria. We recommend that policies aimed at increasing the adoption of climate change adaptation strategies among farmers should be channelled through locally organised farmers-based social capital networks.

Coronavirus disease has created an unexpected negative situation globally, impacting the agricultural sector, economy, human health, and food security. This study examined research on COVID-19 in relation to agricultural production and food security. Research articles published in Web of Science and Scopus were sourced, considering critical situations and circumstance posed by COVID-19 pandemic with regards to the shortage of agricultural production activities and threat to food security systems. In total, 174 published papers in BibTeX format were downloaded for further study. To assess the relevant documents, authors used “effects of COVID-19 on agricultural production and food security (ECAP-FS) as a search keyword for research published between 2016 and April 2021 utilising bibliometric innovative methods. The findings indicated an annual growth rate of about 56.64%, indicating that research on ECAP-FS increased over time within the study period. Nevertheless, the research output on ECAP-FS varied with 2020 accounting for 38.5%, followed by 2021 with 37.9% as at April 2021. The proposed four stage processes for merging two databases for bibliometric analyses clearly showed that one can run collaboration network analyses, authors coupling among other analyses by following our procedure and finally using net2VOSviewer, which is embedded in Rstudio software package. The study concluded that interruptions in agricultural food supply as a result of the pandemic impacted supply and demand shocks with negative impacts on all the four pillars of food security.

Climate change significantly impacts global agricultural productivity. Therefore, a more dynamic farming system is needed to enable farmers to better adapt to climate change while contributing to efforts to produce enough food to feed the growing world population. In the context of climate change, this study analyzed the empirical scientific literature on the link between climate-smart agriculture and farm productivity. To evaluate the relevant articles, the authors used the search term “climate-smart agriculture amidst climate change to enhance agricultural production (CSA-CCAP)” to find studies published between 2009 and March 2022 using innovative bibliometric techniques. One hundred and sixteen published papers in BibTeX format were downloaded for further analysis. The most successful selected CSA approaches in Africa, such as in the Congo Basin forest, including sustainable land management practices, water-efficient maize hybrids, and others, aim to counteract climate change with signs of 200 percent output gains. The findings showed an annual growth rate of about 19%, demonstrating that research on CSA-CCAP expanded over time during the study period. Nonetheless, the research output on CSA-CCAP varied, with 2021 accounting for 30%, followed by 2020 with 16% as of March 2022. The study concluded that boosting agricultural productivity in the face of climate change may be accomplished through CSA to end hunger, eradicate poverty, and improve people’s well-being.

If not adequately managed, climate change is predicted to have a large negative impact on smallholder subsistence farmers, posing a significant danger to household food security. However, the role of adaptive techniques used by farming households to reduce these negative effects and, as a result, their food insecurity status has not been sufficiently evaluated. This study explores the factors that influence smallholder farmers’ adoption of climate change adaptation measures, as well as their impact on household food security. Using an endogenous treatment-effect ordered probit model, agricultural households’ food security status is likely to significantly improve when they employ measures to adapt to adverse climatic conditions. The empirical findings also show that the gender makeup of the household, age, tropical livestock unit, and access to climatic information improve the likelihood of smallholder farmers adopting climate change adaptation measures. Based on the findings, this study advocates that governments and non-governmental organizations (NGOs) support smallholder farmers’ Indigenous adaptation options with various institutional, regulatory, and technological assistance, with a particular emphasis on female-headed households.

Non-farm employment in agrarian communities in developing countries has received a lot of attention. However, its role in implementing climate change adaptation strategies is rarely discussed. This study employs a cross-sectional data to examine whether rural households in Southwest Nigeria are increasing the extent of climate change adaptation practices through their participation in non-farm employment. To account for selectivity bias, the study used endogenous treatment effect for count data model (precisely Poisson) augmented with the inverse probability-weighted-regression-adjustment (IPWRA) estimator. Both estimators found that rural non-farm jobs increase smallholder farmers' adaptive capacities and that participants would have used less adaptation techniques if they had not participated in non-farm work. Efforts to boost rural development must provide more employment opportunities for farmers, particularly during the off-cropping time. This will help farmers improve their ability to adopt more climate change adaptation strategies and, consequently increase farm productivity.