Offering a case study of coastal Bangladesh, this study examines the adaptation of agriculturalists to degrading environmental conditions likely to be caused or exacerbated under global climate change. It examines four central components: (1) the rate of self-reported adoption of adaptive mechanisms (coping strategies) as a result of changes in climate; (2) ranking the potential coping strategies based on their perceived importance to agricultural enterprises; (3) identification the socio-economic factors associated with adoption of coping strategies, and (4) ranking potential constraints to adoption of coping strategies based on farmers' reporting on the degree to which they face these constraints. As a preliminary matter, this paper also reports on the perceptions of farmers in the study about their experiences with climatic change. The research area is comprised of three villages in the coastal region (Sathkhira district), a geographic region which climate change literature has highlighted as prone to accelerated degradation. One-hundred (100) farmers participated in the project's survey, from which the data was used to calculate weighted indexes for rankings and to perform logistic regression. The rankings, model results, and descriptive OPEN ACCESSClimate 2014, 2 224 statistics, are reported here. Results showed that a majority of the farmers self-identified as having engaged in adaptive behavior. Out of 14 adaptation strategies, irrigation ranked first among farm adaptive measures, while crop insurance has ranked as least utilized. The logit model explained that out of eight factors surveyed, age, education, family size, farm size, family income, and involvement in cooperatives were significantly related to self-reported adaptation. Despite different support and technological interventions being available, lack of available water, shortage of cultivable land, and unpredictable weather ranked highest as the respondent group's constraints to coping with environmental degradation and change effects. These results provide policy makers and development service providers with important insight, which can be used to better target interventions which build promote or facilitate the adoption of coping mechanisms with potential to build resiliency to changing climate and resulting environmental impacts.

We use county-level data to examine how the COVID-19 pandemic affected the tourism and hospitality sector, which was by far the most impacted of all sectors, focusing on employment and wage changes. Results support our hypothesis that rural counties experienced fewer negative impacts or even benefited from the COVID-19 pandemic in terms of job growth . We present maps showing the pandemic’s effects on leisure and hospitality (L&H) employment across the nation, identifying the communities both hardest hit and least impacted. A linear regression model is developed to explore independent factors that influenced the pandemic’s local impact. Results are robust across different measures of the key variable (rurality), including rural-urban continuum codes, distance from metropolitan areas, and population density. We also consider the impacts of social capital, income, and local economic diversification, among other factors. Our results suggest that remote, less-populated counties were more likely to experience stable employment in the L&H sector relative to pre-pandemic levels, and in some cases even experienced employment growth. JEL Classification: J2, J3, R1

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