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The Kenya climate risk profile data contains climate, biophysical, socio economic and demographic characteristics, crops production, stakeholders, characterization of selected value chains and risks and adaptation components. All the dataset, except climate records, were collected in three phases between 2016 and 2021. The risk profiles covered the 45 rural counties of Kenya (excluding the 2 urban counties of Nairobi and Mombasa) and were developed in partnership with the Kenya Ministry of Agriculture, Livestock, Fisheries and Cooperatives (MoALFC). Methodology: The methodology combined literature review (peer-reviewed journals, grey literature), data collection from key statistical resources (national census, county development plan, etc.), climate modelling and qualitative data collection tools such as key informant interviews, participatory workshops, and focus group discussions. For each profile, a prioritization process took place in the county with the key relevant stakeholders. The process included a presentation of the ten main value chains (VCs) of the county and a selection of the four main value chains by assessing them against a set of criteria: contribution to food security, productivity, importance to the economy; resilience to current and future climate change; population engaged in the value chain; and engagement of poor and marginalized groups.

This chapter focuses on the evaluation of adaptive capacities of community-level human systems related to agriculture and food security. It highlights findings regarding approaches and domains to monitor and evaluate behavioral changes from CGIAR’s research program on climate change, agriculture and food security (CCAFS). This program, implemented in five West African countries, is intended to enhance adaptive capacities in agriculture management of natural resources and food systems. In support of participatory action research on climate-smart agriculture, a monitoring and evaluation plan was designed with the participation of all stakeholders to track changes in behavior of the participating community members. Individuals’ and groups’ stories of changes were collected using most significant change tools. The collected stories of changes were substantiated through field visits and triangulation techniques. Frequencies of the occurrence of characteristics of behavioral changes in the stories were estimated. The results show that smallholder farmers in the intervention areas adopted various characteristics of behavior change grouped into five domains: knowledge, practices, access to assets, partnership and organization. These characteristics can help efforts to construct quantitative indicators of climate change adaptation at local level. Further, the results suggest that application of behavioral change theories can facilitate the development of climate change adaptation indicators that are complementary to indicators of development outcomes. We conclude that collecting stories on behavioral changes can contribute to biophysical adaptation monitoring and evaluation.

Field evaluation of breeding lines developed for drought tolerance for adaptation, yield, response to field diseases and agronomic quality

The impacts of increasing natural climate disasters are threatening food security in the Asia-Pacific region. Rice is Asia’s most important staple food. Climate variability and change directly impact rice production, through changes in rainfall, temperature and CO2 concentrations. The key for sustainable rice crop is water management. Adaptation can occur through shifts of cropping to higher latitudes and can profit from river systems (via irrigation) so far not considered. New opportunities arise to produce more than one crop per year in cooler areas. Asian wheat production in 2005 represents about 43 % of the global total. Changes in agronomic practices, such as earlier plant dates and cultivar substitution will be required. Fisheries play a crucial role in providing food security with the contribution of fish to dietary animal protein being very high in the region – up to 90 % in small island developing states (SIDS). With the warming of the Pacific and Indian Oceans and increased acidification, marine ecosystems are presently under stress. Despite these trends, maintaining or enhancing food production from the sea is critical. However, future sustainability must be maintained whilst also securing biodiversity conservation. Improved fisheries management to address the existing non-climate threats remains paramount in the Indian and Pacific Oceans with sustainable management regimes being established. Climate-related impacts are expected to increase in magnitude over the coming decades, thus preliminary adaptation to climate change is valuable.

SUMMARY China’s growing presence in Africa’s extractive industries has been the subject of much debate in recent years, reflecting concerns about both environmental sustainability and the governance of resource wealth for long-term benefit. In Cameroon, since 2000 the largest timber concession in the country has been held by a Chinese company. This provides an opportunity to take a deeper look at corporate practices in the extractive industry and explore the extent to which corporate behaviour varies between Chinese and non-Chinese companies. Through a general analysis of Cameroonian timber production and trade, and a detailed analysis of two European companies (one FSC-certified) and one Chinese company (without FSC certification), this paper assesses the effects of Chinese capital and China-related trade on rural livelihoods and forest condition in the Cameroonian forestry sector. Our findings suggest that while the Chinese market shapes the trade patterns and management activities of logging companies, it does so irrespective of the companies’ nationality. Also, findings suggest that nationality of firms has a weak influence on the impacts on local livelihoods around the sampled logging concessions in Cameroon.

The basins of the Indus and Ganges rivers cover 2.20 million km2 and are inhabited by more than a billion people. The region is under extreme pressures of population and poverty, unregulated utilization of the resources and low levels of productivity. The needs are: (1) development policies that are regionally differentiated to ensure resource sustainability and high productivity; (2) immediate development and implementation of policies for sound groundwater management and energy use; (3) improvement of the fragile food security and to broaden its base; and (4) policy changes to address land fragmentation and improved infrastructure. Meeting these needs will help to improve productivity, reduce rural poverty and improve overall human development.

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.

Continuous mono-cropping of rice-wheat (RW) system with conventional tillage (CT) based management practices have led to decline in soil health, groundwater table and farmers profit in north-west India. A medium-term (4 years) farmer’s participatory strategic research trial of basmati RW system was conducted to evaluate the effects of conservation agriculture (CA) based management practices on crop yields, water productivity, profitability and soil quality. Six treatments were compared varied in the cropping system, tillage, crop establishment and residue management. CA-based management under zero-till direct seeded rice-wheat-mungbean recorded 36% higher system yield than conventional till rice-wheat system (14.91 Mg ha−1). CA-based rice-wheat system and rice-wheat-mungbean system saved ~35% irrigation water compared to conventional RW system (2168 mm ha−1). Total water productivity (WPI+R) was improved by 67% with CA-based rice-wheat-mungbean system (0.90 kg grain m−3) over the conventional system. On system basis, 42% higher net return was recorded with CA-based rice-wheat-mungbean system compared to conventional system (USD 2570 ha−1). Mungbean integration in basmati RW system contributed 29% share in system net returns across the treatments. Soil chemical and biological properties were improved by ~40% and 150%, respectively, with CA-based management system.