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AbstractAgriculture is a significant source of GHGsglobally and ruminant livestock animals are one of the largest contributors to these emissions, responsible for an estimated 14% of GHGs (CH4and N2O combined) worldwide. A large portion of GHG fluxes from agricultural activities is related to CH4 emissions from ruminants. Both direct and indirect methods are available. Direct methods include enclosure techniques, artificial (e.g. SF6) or natural (e.g. CO2) tracer techniques, and micrometeorological methods using open-path lasers. Under the indirect methods, emission mechanisms are understood, where the CH4 emission potential is estimated based on the substrate characteristics and the digestibility (i.e. from volatile fatty acids). These approximate methods are useful if no direct measurement is possible. The different systems used to quantify these emission potentials are presented in this chapter. Also, CH4 from animal waste (slurry, urine, dung) is an important source: methods pertaining to measuring GHG potential from these sources are included.

AbstractSustainable Development Goal 2 aims to end hunger, achieve food and nutrition security and promote sustainable agriculture by 2030. This requires that small-scale producers be included in, and benefit from, the rapid growth and transformation under way in food systems. Small-scale producers interact with various actors when they link with markets, including product traders, logistics firms, processors and retailers. The literature has explored primarily how large firms interact with farmers through formal contracts and resource provision arrangements. Although important, contracts constitute a very small share of smallholder market interactions. There has been little exploration of whether non-contract interactions between small farmers and both small- and large-scale value chain actors have affected small farmers’ livelihoods. This scoping review covers 202 studies on that topic. We find that non-contract interactions, de facto mostly with small and medium enterprises, benefit small-scale producers via similar mechanisms that the literature has previously credited to large firms. Small and medium enterprises, not just large enterprises, address idiosyncratic market failures and asset shortfalls of small-scale producers by providing them, through informal arrangements, with complementary services such as input provision, credit, information and logistics. Providing these services directly supports Sustainable Development Goal 2 by improving farmer welfare through technology adoption and greater productivity.

Lao People’s Democratic Republic is a poorly developed, surface water-rich country that has traditionally given limited priority to its groundwater resources, which has resulted in a situation of inadequate scientific knowledge, technical capacity, and policies within the sector. This is slowly changing as the role of groundwater in socioeconomic development is better recognized. This chapter presents an overview of the country’s groundwater resources. It examines the state of knowledge, challenges, gaps, and barriers for effective groundwater resource development. It also reviews the scope and degree of success of recent efforts to enhance groundwater governance. Finally, it presents a concise outlook for groundwater governance, including policy, capacity development, and research perspectives.

This Research Report presents the first comprehensive overview of the multiple climate hazard risks, and the proposed key issues and challenges facing the South Asian region. This report suggests methods for mapping such risks and estimating their impacts on people and agriculture in South Asia. Regional, country-wise and sub-national assessment of five climate-related risks – floods, droughts, extreme rainfall, extreme temperature and sea-level rise – is carried out. The approach involves overlaying climate hazard, sensitivity and adaptive capacity maps, and follows the vulnerability assessment framework of the Intergovernmental Panel on Climate Change (IPCC). A combined index based on hazard, exposure and adaptive capacity is introduced to identify areas susceptible to extreme risk. There is a lack of a systematic and comprehensive risk assessment capturing multiple climate hazards for the entire South Asian region and the need for a common framework for risk assessment. While this approach is well grounded in theories and integration of various spatial data including remote sensing data to derive hazard information, there is a clear need for linking additional elements from the ground at a finer scale among various sectors in developing comprehensive risk assessment information for a disaster risk management plan and promoting risk financing strategies.

The potential for social learning to address complex, interconnected social and environmental challenges, such as climate change adaptation, is receiving increasing attention in research and practice. Social learning approaches vary, but commonly include cycles of knowledge sharing and joint action to co‐create knowledge, relationships, and practices among diverse stakeholders. This results in learning and change that goes beyond the individual into communities, networks, or systems. Many authors have focused on analysis of case studies to better understand the contexts in which such learning occurs. In this paper, we look across this literature to draw out lessons for international development practice. To support those looking to purposively design social learning interventions for adaptation, we focus on four areas: lessons learned and the principles adopted when using a social learning approach, examples of tools and methods used, approaches to evaluating social learning, and examples of its impact. While we identify important lessons for practice within each of these areas, three cross‐cutting themes emerge. These are: the importance of developing a shared view among those initiating learning processes of how change might happen and of how social learning fits within it, linking this locus of desired change to the tools employed; the centrality of skilled facilitation and in particular how practitioners may shift toward being participants in the collective learning process; and the need to attend to social difference, recognizing the complexity of social relations and the potential for less powerful actors to be co‐opted in shared decision making.WIREs Clim Change2015, 6:509–522. doi: 10.1002/wcc.348This article is categorized under:Vulnerability and Adaptation to Climate Change > Learning from Cases and AnalogiesClimate and Development > Knowledge and Action in Development

AbstractIn sub‐Saharan Africa (SSA), few studies have quantified greenhouse gas (GHG) emissions following application of soil amendments, for development of accurate national GHG inventories. Therefore, this study quantified soil GHG emissions using static chambers for two maize cropping seasons (one full year) of four different soil amendments in the central highlands of Kenya. The four treatments were (i) animal manure, (ii) inorganic fertilizer, (iii) combined animal manure and inorganic fertilizer, and (iv) a no‐N control (no amendment) laid out in a randomized complete block design. Cumulative annual soil fluxes (February 2017 to February 2018) ranged from −1.03 ± 0.19 kg CH4‐C ha−1 yr−1 from the manure inorganic fertilizer treatment to −0.09 ± 0.03 kg CH4‐C ha−1 yr−1 from the manure treatment, 1,391 ± 74 kg CO2‐C ha−1 yr−1 from the control treatment to 3,574 ± 113 kg CO2‐C ha−1 yr−1 from the manure treatment, and 0.13 ± 0.08 to 1.22 ± 0.12 kg N2O‐N ha−1 yr−1 in the control and manure treatments, respectively. Animal manure amendment produced the highest cumulative CO2 emissions (P < 0.001), N2O emissions (P < 0.001), and maize yields (P = 0.002) but the lowest N2O yield‐scaled emission (YSE) (0.5 g N2O–N kg−1 grain yield). Manure combined with inorganic fertilizer had the highest cumulative CH4 uptake (P < 0.001) and N2O YSE (2.2 g N2O–N kg−1 grain yield). Our results indicate that while the use of animal manure may increase total GHG emissions, the concurrent increase in maize yields results in reduced yield‐scaled GHG emissions.