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This paper distinguishes between bridging and bonding social capital to assess their roles for individual farmers’ adaptation strategies taken through technology adoption. Based on primary data collected in Langcang River (LCR) basin area in southwestern China, the paper finds: (1) adaptation measures have been widely taken by surveyed households, but non-infrastructure-based measures are more prevalent than infrastructure-based measures and (2) surveyed households have strong social capital while having weak bridging social capital. Their bonding social capital has significantly positive relationship with their adaptation decisions, but bridging social capital does not have such statistically significant relationship. It recommends that the governments contemplate carefully how to help the poor to get a good combination of bonding and bridging social capital when designing policies to help the rural poor to improve their long-term adaptive capacity and achieve sustainable rural development. [ABSTRACT FROM AUTHOR]

Climate change is a potential threat to achieving food security, particularly in the most food insecure regions. However, interpreting climate change projections to better understand the potential impacts of a changing climate on food security outcomes is challenging. This paper addresses this challenge through presenting a framework that enables rapid country-level assessment of vulnerability to food insecurity under a range of climate change and adaptation investment scenarios. The results show that vulnerability to food insecurity is projected to increase under all emissions scenarios, and the geographic distribution of vulnerability is similar to that of the present-day; parts of sub-Saharan Africa and South Asia are most severely affected. High levels of adaptation act to off-set these increases; however, only the scenario with the highest level of mitigation combined with high levels of adaptation shows improvements in vulnerability compared to the present-day. The results highlight the dual requirement for mitigation and adaptation to avoid the worst impacts of climate change and to make gains in tackling food insecurity. The approach is an update to the existing Hunger and Climate Vulnerability Index methodology to enable future projections, and the framework presented allows rapid updates to the results as and when new information becomes available, such as updated country-level yield data or climate model output. This approach provides a framework for assessing policy-relevant human food security outcomes for use in long-term climate change and food security planning; the results have been made available on an interactive website for policymakers (www.metoffice.gov.uk/food-insecurity-index). [ABSTRACT FROM AUTHOR]

Total factor productivity (TFP) analysis has been the focus of a large number of methodological and empirical studies over the past several decades. One remarkable gap in this literature is the omission of climatic variables as regressors in the models used to derive TFP measures. The purpose of this paper is to narrow this gap by developing climate-adjusted (CA) TFP measures. We combine information from the Climatic Research Unit with Food and Agriculture Organization data for 28 Latin American and Caribbean countries over a 52-year period (1961-2012) to estimate random parameter stochastic production frontier (SPF) models. The goal is to investigate the impact of climatic variability on TFP. The estimated coefficients from the SPF models are used to construct a climatic effects index across countries and over time. The average annual variation in climatic conditions is stronger at the end of the 2000s compared to earlier periods. Climatic variability has a negative effect on production in 20 of the 28 LAC countries analyzed, and this is more severe over Central America and the Caribbean. The average reduction in output across the region attributable to climatic variables is between 0.02 and 22.7% over the last decade compared to the period 1961-1999. The estimated average annual growth rate of CATFP (0.69%) is consistently lower than TFP (1.08%), confirming the adverse impact of climatic variability on agricultural output and productivity in LAC. The results show considerable variability across countries, and this points to the importance of accounting for climatic effects in analyzing TFP. [ABSTRACT FROM AUTHOR]

Climate change is increasingly affecting rural areas worldwide. The Lower Mekong Basin (LMB) is at particular risk due to heat stress, changing rainfall patterns, rising sea levels, and more frequent and extreme climatic events. It is imperative that local-level adaptation plans are developed in a manner that builds resilience to these growing threats. Strategies for developing adaptation plans tend to comprise predominantly science-led or predominantly community-led processes. This study examines an approach that balances inputs from both processes in characterizing community vulnerability as a component of the adaptation planning workflow. Evaluation sites are located within four distinct sub-regions of the LMB: the Vietnam Mekong Delta, the Annamite Mountains of Lao PDR, the Cambodia central lowlands, and the mid-elevation forests of northern Thailand. Our results indicate that by merging science-based data with community-level perspective, knowledge gaps from both sides are filled and a more comprehensive understanding of vulnerability is factored into adaptation planning. [ABSTRACT FROM AUTHOR]

The susceptibility of agriculture to changing environmental conditions is arguably the most dangerous short-term consequence of climate change, and predictions on the geography of changes will be useful for implementing mitigation strategies. Ecological niche modeling (ENM) is a technique used to relate presence records of species to environmental variables. By extrapolation, ENM maps the suitability of a landscape for the species in question. Recently, ENM was successfully applied to predict the geographic distribution of agriculture. Using climate and soil conditions as predictor variables, agricultural suitability was mapped across the Old World. Here, I present analogous ENM-based maps of the suitability for agriculture under climate change scenarios for the year 2050. Deviations of predicted scenarios from a current conditions model were analyzed by (1) comparing relative average change across regions, and (2) by relating country-wide changes to the data indicative of the wealth of nations. The findings indicate that different regions vary considerably in whether they win or lose in agricultural suitability, even if average change across the entire study region is small. A positive relationship between the wealth of nations and change in agriculture conditions was found, but variability around this trend was high. Parts of Africa, Europe and southern and eastern Asia were predicted to be particularly negatively affected, while north-eastern Europe, among other regions, can expect more favorable conditions for agriculture. The results are presented as an independent 'second opinion' to previously published, more complex forecasts on agricultural productivity and food supply variability due to climatic change, which were based on fitting environmental variables to yield statistics. [ABSTRACT FROM AUTHOR]