Globally, fisheries support livelihoods of over half a billion people who are exposed to multiple climatic stresses and shocks that affect their capacity to subsist. Yet, only limited research exists on the vulnerability of fishery-based livelihood systems to climate change. We assess the vulnerability of fishery-based livelihoods to the impacts of climate variability and change in two coastal fishing communities in Bangladesh. We use a composite index approach to calculate livelihood vulnerability and qualitative methods to understand how exposure, sensitivity, and adaptive capacity measured by sub-indices produce vulnerability. Our results suggest that exposure to floods and cyclones, sensitivity (such as dependence on small-scale marine fisheries for livelihoods), and lack of adaptive capacity in terms of physical, natural, and financial capital and diverse livelihood strategies construe livelihood vulnerability in different ways depending on the context. The most exposed community is not necessarily the most sensitive or least able to adapt because livelihood vulnerability is a result of combined but unequal influences of bio-physical and socio-economic characteristics of communities and households. But within a fishing community, where households are similarly exposed, higher sensitivity and lower adaptive capacity combine to create higher vulnerability. Initiatives to reduce livelihood vulnerability should be correspondingly multifaceted.

Understanding farmers’ perceptions of how rainfall fluctuates and changes is crucial in anticipating the impacts of changing climate patterns, as only when a problem is perceived will appropriate steps be taken to adapt to it. This article seeks to: (1) identify southern African farmers’ perceptions of rainfall, rainfall variations, and changes; (2) examine the nature of meteorological evidence for the perceived rainfall variability and change; (3) document farmers’ responses to rainfall variability; and (4) discuss why discrepancies may occur between farmers’ perceptions and meteorological observations of rainfall. Semi-structured interviews were used to identify farmers’ perceptions of rainfall changes in Botswana and Malawi. Resulting perceptions were examined in conjunction with meteorological data to assess perceived and actual rainfall with regards to: what was changing (onset, duration or cessation), and how it was changing (amount, frequency, intensity or inter-annual variability). Most farmers perceived that the rains used to start earlier and end later. Meteorological data provided no evidence to support farmer perceptions of rainfall starting as early as September (south Malawi) or October (Botswana); however, a high inter-annual variability in the timing of the onset was observed alongside an increasing number of dry days and declining amounts of rainfall at the onset and cessation of precipitation. While some rainfall patterns are associated with El Niño-Southern Oscillation (ENSO) fluctuations and larger-scale changes, one explanation for the differences between farmer perceptions and meteorological evidence is that rainfall changes can be easily confused with changes in farming system sensitivity. Our findings suggest that scientists, policymakers, and developers of climate adaptation projects need to be more in tune with farmers' and extension workers’ understandings of how weather is changing in order to improve adaptation policy formulation and implementation.

Sallu, S. M., C. Twyman, and L. C. Stringer. 2010. Resilient or vulnerable livelihoods? Assessing livelihood dynamics and trajectories in rural Botswana. Ecology and Society 15(4): 3. https://doi.org/10.5751/ES-03505-150403

Combustion of fuels in the residential sector for cooking and heating results in the emission of aerosol and aerosol precursors impacting air quality, human health, and climate. Residential emissions are dominated by the combustion of solid fuels. We use a global aerosol microphysics model to simulate the impact of residential fuel combustion on atmospheric aerosol for the year 2000. The model underestimates black carbon (BC) and organic carbon (OC) mass concentrations observed over Asia, Eastern Europe, and Africa, with better prediction when carbonaceous emissions from the residential sector are doubled. Observed seasonal variability of BC and OC concentrations are better simulated when residential emissions include a seasonal cycle. The largest contributions of residential emissions to annual surface mean particulate matter (PM_2.5) concentrations are simulated for East Asia, South Asia, and Eastern Europe. We use a concentration response function to estimate the human health impact due to long-term exposure to ambient PM_2.5 from residential emissions. We estimate global annual excess adult (> 30 years of age) premature mortality (due to both cardiopulmonary disease and lung cancer) to be 308 000 (113 300–497 000, 5th to 95th percentile uncertainty range) for monthly varying residential emissions and 517 000 (192 000–827 000) when residential carbonaceous emissions are doubled. Mortality due to residential emissions is greatest in Asia, with China and India accounting for 50 % of simulated global excess mortality. Using an offline radiative transfer model we estimate that residential emissions exert a global annual mean direct radiative effect between −66 and +21 mW m⁻², with sensitivity to the residential emission flux and the assumed ratio of BC, OC, and SO₂ emissions. Residential emissions exert a global annual mean first aerosol indirect effect of between −52 and −16 mW m⁻², which is sensitive to the assumed size distribution of carbonaceous emissions. Overall, our results demonstrate that reducing residential combustion emissions would have substantial benefits for human health through reductions in ambient PM_2.5 concentrations.