20 pages., Agricultural extension and advisory services in information and technology dissemination and delivery are critical in a
developing country’s food security and sustainability. Without extension service provision, the productivity and
production smallholder farmers are experiencing would have been much lower, and current global hunger and
malnutrition worse. This paper assesses the effects of COVID-19 on the sustainability of agricultural extension
models/approaches for smallholder farmers in developing countries. Over 60 papers were reviewed covering 2019-2021,
commencing with the disease outbreak in China. Based on characteristics and usage, the findings indicate most reviewed
extension models were disrupted. No single model was entirely disbanded as the impact of COVID-19 was being felt.
However, each model incorporated a digital means of communication to keep farmers and service providers in touch.
There is considerable criticism around the inadequacy of these extension techniques in advancing the agenda for
smallholder farming’s long-term viability that needs to be addressed
20 pages, As global climate change progresses, the United States (US) is expected to experience warmer temperatures as well as more frequent and severe extreme weather events, including heat waves, hurricanes, and wildfires. Each year, these events cost dozens of lives and do billions of dollars' worth of damage, but there has been limited research on how they influence human decisions about migration. Are people moving toward or away from areas most at risk from these climate threats? Here, we examine recent (2010–2020) trends in human migration across the US in relation to features of the natural landscape and climate, as well as frequencies of various natural hazards. Controlling for socioeconomic and environmental factors, we found that people have moved away from areas most affected by heat waves and hurricanes, but toward areas most affected by wildfires. This relationship may suggest that, for many, the dangers of wildfires do not yet outweigh the perceived benefits of life in fire-prone areas. We also found that people have been moving toward metropolitan areas with relatively hot summers, a dangerous public health trend if mean and maximum temperatures continue to rise, as projected in most climate scenarios. These results have implications for policymakers and planners as they prepare strategies to mitigate climate change and natural hazards in areas attracting migrants.
15pgs, Agriculture is crucial in catering to the increasing demand for food and employment. Thus, adoption of novel technologies is important. Many scientists have developed different theories and models explaining the process of behavioral change relevant to adoption. They are either completely different, similar, or improvements of previously developed models. Therefore, compilation and summarization of these theories and models will support future studies and researchers. Thus, an analysis of literature on technology adoption was conducted. The review was prepared based on literature from various sources spanning around 50 years. The theories and models identified by different studies were compiled and analyzed in this review paper. Many theories and models in agricultural technology adoption such as transtheoretical model, theory of reasoned action, theory of interpersonal behavior, model for innovation-decision process, different versions of technology acceptance model, theory of planned behavior, theory of diffusion of innovation, task-technology fit, technology readiness, unified theory of acceptance and use of technology, expectancy livelihood model, social cognitive theory, and perceived characteristics of innovating theory were compiled. Each theory and model has its own uniqueness, which had explained different aspects of technology adoption process and factors determining the behavioral change. These theories and models included affecting factors such as technological, personal, social, and economical factors. In conclusion, it can be stated that, rather than having a single theory or a model, an integrated and amalgamated form will be more explanatory for technology adoption.
25pgs, We combine farm accounting data with high-resolution meteorological data, and climate scenarios to estimate climate change impacts and adaptation potentials at the farm level. To do so, we adapt the seminal model of Moore and Lobell (2014) who applied panel data econometrics to data aggregated from the farm to the regional (subnational) level. We discuss and empirically investigate the advantages and challenges of applying such models to farm-level data, including issues of endogeneity of explanatory variables, heterogeneity of farm responses to weather shocks, measurement errors in meteorological variables, and aggregation bias. Empirical investigations into these issues reveal that endogeneity due to measurement errors in temperature and precipitation variables, as well as heterogeneous responses of farms toward climate change may be problematic. Moreover, depending on how data are aggregated, results differ substantially compared to farm-level analysis. Based on data from Austria and two climate scenarios (Effective Measures and High Emission) for 2040, we estimate that the profits of farms will decline, on average, by 4.4% (Effective Measures) and 10% (High Emission). Adaptation options help to considerably ameliorate the adverse situation under both scenarios. Our results reinforce the need for mitigation and adaptation to climate change.
