In 1992 a mental models-based survey in Pittsburgh, Pennsylvania, revealed that educated laypeople often conflated global climate change and stratospheric ozone depletion, and appeared relatively unaware of the role of anthropogenic carbon dioxide emissions in global warming. This study compares those survey results with 2009 data from a sample of similarly well-educated laypeople responding to the same survey instrument. Not surprisingly, following a decade of explosive attention to climate change in politics and in the mainstream media, survey respondents in 2009 showed higher awareness and comprehension of some climate change causes. Most notably, unlike those in 1992, 2009 respondents rarely mentioned ozone depletion as a cause of global warming. They were also far more likely to correctly volunteer energy-use as a major cause of climate change; many in 2009 also cited natural processes and historical climatic cycles as key causes. When asked how to address the problem of climate change, while respondents in 1992 were unable to differentiate between general “good environmental practices” and actions specific to addressing climate change, respondents in 2009 have begun to appreciate the differences. Despite this, many individuals in 2009 still had incorrect beliefs about climate change, and still did not appear to fully appreciate key facts such as that global warming is primarily due to increased concentrations of carbon dioxide in the atmosphere, and the single most important source of this carbon dioxide is the combustion of fossil fuels.

HighlightsWe use surveys of husbands and wives in Tanzania to explore rural household decision-making.We find perceptions of household decision-making authority differ depending on the spouse asked.Factors associated with a wife’s authority include age, education, health, children, and labor hours.The allocation of intra-household authority also varies across thirteen different decision questions.A lack of “intra-household accord” over authority may be a barrier to empowerment efforts.

No abstract

Many environmental factors constrain the production of major food crops in Sub-Saharan Africa and South Asia. At the same time, these food production systems themselves have a range of negative impacts on the environment. In this paper we review the published literature and assess the depth of recent research (since 2000) on crop x environment interactions for rice, maize, sorghum/millets, sweetpotato/yam and cassava in these two regions. We summarize current

No abstract

Systematic reviews and meta-analyses generally focus on intervention impacts or outcomes. Less common, however, are reviews of the assumptions and theory underlying the pathways between intervention and outcome. We consider the hypothetical case for interventions to empower female farmers, either by prioritising women for new investments or re-allocating existing resources. Empowerment is defined as increased women's decision-making authority related to agricultural resources, management and production, and income. We hypothesise two avenues through which productivity or health benefits might arise: (i) eliminating female-male differences in, e.g. input access; or (ii) leveraging gendered risk, time, and social preferences leading women to differentially allocate resources. A review of evidence highlights the extent of support for the baseline, behaviour change, and economic benefit assumptions behind these hypothesised avenues. Findings suggest returns to investing in female farmers could be significant in various contexts but estimates of economic returns to empowering women in agriculture remain limited.

Previous research has shown that men and women, on average, have different risk attitudes and may therefore see different value propositions in response to new opportunities. We use data from smallholder farm households in Mali to test whether risk perceptions differ by gender and across domains. We model this potential association across six risks (work injury, extreme weather, community relationships, debt, lack of buyers, and conflict) while controlling for demographic and attitudinal characteristics. Factor analysis highlights extreme weather and conflict as eliciting the most distinct patterns of participant response. Regression analysis for Mali as a whole reveals an association between gender and risk perception, with women expressing more concern except in the extreme weather domain; however, the association with gender is largely absent when models control for geographic region. We also find lower risk perception associated with an individualistic and/or fatalistic worldview, a risk‐tolerant outlook, and optimism about the future, while education, better health, a social orientation, self‐efficacy, and access to information are generally associated with more frequent worry—with some inconsistency. Income, wealth, and time poverty exhibit complex associations with perception of risk. Understanding whether and how men's and women's risk preferences differ, and identifying other dominant predictors such as geographic region and worldview, could help development organizations to shape risk mitigation interventions to increase the likelihood of adoption, and to avoid inadvertently making certain subpopulations worse off by increasing the potential for negative outcomes.

Studies of improved seed adoption in developing countries are almost always based on household surveys and are premised on the assumption that farmers can accurately self-report their use of improved seed varieties. However, recent studies suggest that farmers' reports of seed varieties planted, or even whether the seed is local or improved, are sometimes inconsistent with the DNA fingerprinting results of those crops. We use household survey data from Tanzania to test the alignment between farmer-reported and DNA-identified maize seed types planted. In the sample, 70% of maize seed observations are correctly reported as local or improved, while 16% are type I errors (falsely reported as improved) and 14% are type II errors (falsely reported as local). Type I errors are more likely to have been sourced from other farmers, rather than formal channels. An analysis of input use,