Whilst skilful seasonal climate forecasts are routinely produced, their ability to support profitable agricultural decision-making remains uncertain, particularly in regions with modest seasonal predictability and high climate variability. We assess the financial implications of using a statistically derived seasonal maize crop-yield forecast for a medium-size commercial farm in South Africa, focusing on how forecast attributes interact with farmer investment strategies. A cumulative profit framework is used to evaluate three stylised strategies representing different levels of risk exposure under forecast uncertainty. The crop-yield forecasts exhibit measurable skill but limited reliability, notably underpredicting the likelihood of ‘normal’ crop-yield seasons – and this reliability bias has important financial consequences. Reinvesting all available capital can be highly profitable when forecasts are mostly accurate, but leads to catastrophic losses when forecasts are given with a high degree of confidence, but are ultimately inaccurate. Conversely, partial reinvestment offers greater resilience to forecast errors, while a fixed annual investment strategy often produces the most stable long-term outcomes. Riskier strategies are most profitable when forecast weaknesses are avoided. These results demonstrate that even highly skilful seasonal yield forecasts can produce adverse financial outcomes if forecast reliability and decision risk are not explicitly considered. Aligning investment strategies with forecast attributes (such as reliability) and risk tolerance, and complementing standard forecast verification with simple financial metrics, is essential for effective agricultural climate services.

Seasonal climate forecasts (SCFs) are explored as an additional tool for farmers to use to act against seasonal climate fluctuations and to support greater food security for themselves and their customers. In this study, we compared the SCF needs and possible emerging farming actions of commercial farmers and smallholder farmers while exploring the prospects for developing SCF tools to aid farmers. Our intent was not to produce a new SCF, but to improve the farmers' reception, understanding and uptake of existing SCFs. The results show that both farmer groups saw value in SCFs in improving their farming actions (and, by implication, improving their food security) and provided detailed information on their specific SCF needs to support their decision-making, such as how to improve trust, the type of information they would like to receive, how to make SCFs more understandable, and how to make SCFs relevant for their farming actions. The needs of the two groups differed marginally, but the major barrier for smallholder farmers was SCF access as a result of a lack of smartphones and network coverage.

Africa is highly vulnerable to climate change, with Indigenous peoples and smallholder farmers being among the most vulnerable. However, there is limited understanding of how Indigenous knowledge (IK) and local knowledge (LK) can reduce or contribute to smallholder farmers’ vulnerability and the conditions under which they can effectively reduce overall climate risk. This is partly because IK and LK are often excluded from vulnerability assessments. Therefore, we developed a locally calibrated Livelihood Vulnerability Index (LVI) that integrates IK and LK as one of the pathways to assess the vulnerability of smallholder farmers to climate variability and change in Chiredzi, Zimbabwe. A cross-sectional survey of 100 smallholder farmers was conducted to understand their perceptions, household-level sensitivity, exposure, and adaptative capacity. Analysis of local climate data (1972–2021) showed a delayed onset of the rainy season for sorghum and maize and increased mean maximum annual temperatures—important changes in local climate that align with changes perceived by smallholder farmers and affect their exposure and livelihoods. Farmers with IK and LK had a higher adaptive capacity and lower vulnerability than farmers with no IK and LK. Farmers with IK and LK reduced their vulnerability (LVI = 0.379) by using IK and LK weather and seasonal forecasts to make climate-informed decisions that improved food and livelihood strategies compared to farmers with no IK and LK (LVI = 0.412). Farmers with IK and LK diversify the number of crops they plant and implement more crop adaptation responses, thereby diversifying the risk of crop failure and reducing food shortage. Although Indigenous peoples and local communities including smallholder farmers are generally highly vulnerable, this study shows that IK and LK can reduce absolute and relative vulnerability, thus highlighting the important role of IK and LK in reducing smallholder farmers’ livelihood vulnerability by improving their adaptive capacity.

With 40% of the South African population experiencing moderate to severe food insecurity and climate change predicted to impact agriculture negatively, there is a future role for inland fisheries to help feed 60 million people. To support the expansion of inland fisheries, reducing the current postharvest losses of ~25% of fish requires improving the current preservation and storage techniques. This review aims to assess the potential benefits for Sub-Saharan Africa’s freshwater aquaculture and fisheries to utilise an emerging technology to reduce postharvest losses, using South Africa as a case study. We demonstrate the potential for plasma activated water (PAW) for preserving fresh fish. PAW offers non-thermal and non-toxic bacterial inactivation. Considered safe for human use, PAW is currently used in medical applications and has been investigated as a postharvest sanitiser for many fruits and vegetables, effectively increasing the shelf life of fresh food. The limited studies of PAW treatment of fresh fish show increased shelf life with some generally insignificant changes to quality. This novel treatment's success depends on the optimisation of application methods, including PAW-derived ice (PAWDI). To strengthen the value chain of the fresh fish industry, PAW/PAWDI could extend the shelf life of fish from origin to market. Investment in food supply chain development would preserve more harvested fish and improve the quality. Utilising solar power to produce PAW or PAWDI in situ potentially offers benefits for the small communities of inland fisheries to commercial production. This technology as well as changes to traditional preservation and transport chains could be utilised in other Sub-Saharan African nations.

Owing to probabilistic uncertainties associated with seasonal forecasts, especially over areas such as southern Africa where forecast skill is limited, non-climatologists and users of such forecasts frequently prefer them to be presented or distributed in terms of the likelihood (expressed as a probability) of certain categories occurring or thresholds being exceeded. Probabilistic forecast verification is needed to verify such forecasts. Whilst the resulting verification statistics can provide clear insights into forecast attributes, they are often difficult to understand, which might hinder forecast uptake and use. This problem can be addressed by issuing forecasts with some understandable evidence of skill, with the purpose of reflecting how similar forecasts may have performed in the past. In this paper, we present a range of different probabilistic forecast verification scores, and determine if these statistics can be readily compared to more commonly known and understood ‘ordinary’ correlations between forecasts and their associated observations – assuming that ordinary correlations are more intuitively understood and informative to seasonal forecast users. Of the range of scores considered, the relative operating characteristics (ROC) was found to be the most intrinsically similar to correlation.

Vulnerability to climate variability and change differs from one group to another, from sector to another, and between regions. Understanding the degree to which smallholder farmers are vulnerable to climate risk is critical when assessing adaptation responses to offset current and future risks. Here, we assessed the vulnerability of smallholder farmers to climate variability in Chiredzi, Zimbabwe. Vulnerability is assessed using a two-dimensional approach – quantitative analysis of observed climate data to assess farmers’ exposure and qualitative analysis of farmers’ socio-economic data. The Livelihood Vulnerability Index (LVI) is applied to understand levels of farmers’ livelihood vulnerability. 16 rainfall and temperature indices and extreme events critical to rainfed smallholder farmers were analysed at annual and seasonal scales from 1972–2021. A cross-sectional survey was conducted on 100 smallholder farmers. Our results confirm an increased warming trend, and forward shift of the rainy season onset, with both of these indices showing statistically significant trends. A maximum temperature increase of 0.1 o C annum -1 was observed. All the other indices and extreme events exhibited insignificant trends. The total seasonal rainfall has increased by 3.2 mm annum -1 . Increased interseasonal variability of the measured indices was observed. Hot days for maize and sorghum have increased by 0.25 and 0.85 days annum -1 respectively. The combination of increased delayed rainy season onset and a decreasing trend for rainy season length suggests that the rainy season is shrinking slowly. There was alignment between farmers’ perceptions of the climate and trends from observed climate data on the majority (seven) of the indices. Livelihood vulnerability to climate risk varied for farmers in communal and resettled wards. Farmers in resettled areas had a higher LVI (0.4076) than farmers in communal areas (0.3762). The LVI-IPCC shows a relatively similar index for both communal and resettled wards (-0.0874 and -0.0849 respectively). Importantly, farmers with Indigenous knowledge (IK) and local knowledge (LK) background showed lower LVI than farmers without IK and LK, implying the important role of IK and LK, in climate vulnerability assessment and in increasing farmers’ adaptive capacity. Our results have implications on the implementation of climate adaptation responses by smallholder farmers in Chiredzi. Adaptation measures should be tailored based on the vulnerability levels of farmers and their exposure to climate risks. This is important for the implementation of effective climate adaptation responses in the Chiredzi district.

Accessible, reliable and diverse sources of climate information are needed to inform climate change adaptation at all levels of society, particularly for vulnerable sectors such as smallholder farming. Globally, many smallholder farmers use Indigenous knowledge (IK) and local knowledge (LK) to forecast weather and climate; however, less is known about how the use of these forecasts connects to decisions and actions for reducing climate risks. We examined the role of IK and LK in seasonal forecasting and the broader climate adaptation decision-making of smallholder farmers in Chiredzi, Zimbabwe. The data were collected from a sample of 100 smallholder farmers. Seventy-three of the 100 interviewed farmers used IK and LK weather and climate forecasts, and 32% relied solely on IK and LK forecasts for climate adaptation decision-making. Observations of cuckoo birds, leaf-sprouting of Mopane trees, high summer temperatures, and Nimbus clouds are the main indicators used for IK and LK forecasts. The use of IK and LK climate forecasts was significantly positively associated with increasing farmer age and farmland size. Farmers using IK and LK forecasts implemented, on average, triple the number of adaptation measures compared with farmers not using IK and LK. These findings demonstrate the widespread reliance of farmers on IK and LK for seasonal forecasts, and the strong positive link between the use of IK and LK and the implementation of climate adaptation actions. This positive association between IK and LK usage and the implementation of adaptation actions may be widespread in smallholder farming communities throughout Africa and globally. Recognition and inclusion of IK and LK in climate services is important to ensure their continued potential for enhancing climate change adaptation.

Evidence is increasing of human responses to the impacts of climate change in Africa. However, understanding of the effectiveness of these responses for adaptation to climate change across the diversity of African contexts is still limited. Despite high reliance on indigenous knowledge (IK) and local knowledge (LK) for climate adaptation by African communities, potential of IK and LK to contribute to adaptation through reducing climate risk or supporting transformative adaptation responses is yet to be established. Here, we assess the influence of IK and LK for the implementation of water sector adaptation responses in Africa to better understand the relationship between responses to climate change and indigenous and local knowledge systems. Eighteen (18) water adaptation response types were identified from the academic literature through the Global Adaptation Mapping Initiative (GAMI) and intended nationally determined contributions (iNDCs) for selected African countries. Southern, West, and East Africa show relatively high evidence of the influence of IK and LK on the implementation of water adaptation responses, while North and Central Africa show lower evidence. At country level, Zimbabwe displays the highest evidence (77.8%) followed by Ghana (53.6%), Kenya (46.2%), and South Africa (31.3%). Irrigation, rainwater harvesting, water conservation, and ecosystem-based measures, mainly agroforestry, were the most implemented measures across Africa. These were mainly household and individual measures influenced by local and indigenous knowledge. Adaptation responses with IK and LK influence recorded higher evidence of risk reduction compared to responses without IK and LK. Analysis of iNDCs shows the most implemented water adaptation actions in academic literature are consistent with water sector adaptation targets set by most African governments. Yet only 10.4% of the African governments included IK and LK in adaptation planning in the iNDCs. This study recommends a coordinated approach to adaptation that integrates multiple knowledge sources, including IK and LK, to ensure sustainability of both current and potential water adaptation measures in Africa.

The study assessed the sociodemographic characteristics of cassava-based (CB) farmers’ and their perception of climate variability as predictors of their adaptation strategies. The study covers cassava-based farmers in both the rain forest and derived savannah ecosystems of Nigeria. The study described the farmers’ socioeconomic characteristics, their perception of climate variability, adaptation strategies and their socio-demographic factors influencing climate variability adaptation strategies. A cross-sectional survey using a multistage sampling procedure, was used to sample 400 cassava-based farmers in the study area. The data collected were analysed using descriptive statistics and multivariate probit (MVP) regression. Results indicated that 71.68% of the CB farmers were males, married (85.21%), had primary school certificates (30.08%) and received trainings in local adaptation strategy technologies (62.41%) and climate adaptation strategies (65.16%). Majority (68.67%) felt climate variability implied low yield and reduced water supply for farming activities in some years (69.42%). Most (85.21%) CB farmers combatted climate variability through water management practices, 68.17% utilised weather forecast information while 44.86% adapted planting and harvesting time to target peak produce prices. Farmers’ perception and their socioeconomic characteristics that predicted their climate variability strategies included access to extension training (p<0.01), experience of previous season’s low yield (p<0.01), membership of professional associations (p<0.01), farming experience (p<0.10) and credit access (p<0.10). Cassava-based farmers’ climate variability perception and their sociodemographic characteristics predicted their climate variability adaptation strategies. Enhancement trainings and improved formal credit access are veritable ways to minimise the adverse effects of climate variability on cassava production in the study area. Keywords: Climate, Perception, Adaptation, Cassava farmers, Ecosystem, Multivariate probit. DOI: 10.7176/DCS/10-11-04 Publication date: November 30 th 2020

Abstract Evidence of human adaptation actions responding to climate impacts is increasing in Africa. However, a holistic understanding of effective adaptation across the diversity of African contexts is still limited at a continental scale. Despite high reliance on indigenous knowledge (IK) and local knowledge (LK) for climate adaptation in Africa, the potential risk reduction of IK and LK and its role in supporting transformative adaptation responses is yet to be established. Here, we assess the influence of IK and LK on the implementation of water sector adaptation in Africa and describe the relationship between adaptation and indigenous and local knowledge systems. Eighteen (18) water sector response types were identified from the academic literature through the Global Adaptation Mapping Initiative (GAMI). The most implemented measures across Africa influenced by IK and LK were household-level and individual measures and included irrigation, rainwater harvesting, water conservation and ecosystem-based measures (mainly agroforestry). Southern, west, and east Africa show relatively high evidence of the influence of IK and LK on the implementation of water adaptation responses while north, and central Africa show lower evidence. At country level, Zimbabwe display highest evidence (77.8%) followed by Ghana (53.6%), Kenya (46.2%) and South Africa (31.3%). Adaptation responses with IK and LK influence recorded higher evidence of risk reduction compared to articles without IK and LK. Analysis of intended nationally determined contributions (iNDCs) shows the most implemented water adaptation actions in academic literature are consistent with water sector adaptation targets set by most African governments. Yet only 10.4% of the African governments included IK and LK in adaptation planning in the iNDCs. The study recommends a coordinated approach to adaptation that integrates multiple knowledge sources including IK and LK to ensure greater effectiveness and scalability of current and potential water adaptation measures in Africa.

Anthropogenic climate change likely influences the beginning of 2020 growing season's water deficit in parts of southern Africa, with severe consequences to food security.

Grasslands occupy nearly half the world's ice-free land and provide forage for livestock and native herbivores on almost one-third of the world's ice-free land. They are generally located in drier regions (arid and semiarid) with large diurnal temperature variations and high interannual rainfall variability. Rainfall is a key driver of pasture and livestock production, and managing drought is a common and challenging experience for pastoral managers. Here we examine the agroclimatic association of the worlds grasslands, looking specifically at grasslands in Australia, South America (Uruguay), and South Africa as examples of important grassland communities. These grazing regions are all affected by more than one climate driver, and the influence of the different drivers on rainfall varies geographically across the world. These climate drivers operate on scales from seasonal to interdecadal, but understanding of the El Nino-Southern Oscillation (ENSO) has provided the most widespread application of climate science into pastoral decision-making. Although ENSO is the most predictable climate driver, the reliability is limited to the austral spring and summer periods in years with strong ENSO anomalies, and even so, the reliability is moderate at best. Nonetheless, information on current conditions and seasonal forecasts have been generated and disseminated on national scales for decades (Australia late 1980s, Uruguay 1997, and South Africa early 1990s) but the uptake by agricultural decision-makers has been modest (one in three in Australia), and use by governments has largely been limited to crisis management during droughts. There has been little evidence and motivation by governments to manage the hydrological and hydro-illogical cycles by preparing pastoralists for drought by implementing strong policy platforms around early warning, preparedness, and national alerts. Despite the modest uptake of seasonal forecasts, there is evidence that their use in decision-making can increase productivity, profitability, and resource sustainability of pastoral enterprises in some parts of the world. These modest adoption rates have been attributed to poor presentation, lack of understanding of terminology, failure to show value and match forecast scale with decision-making at the value chain level, short lead times, poor reliability, and inappropriate dissemination methods. There is evidence of higher adoption rates at the regional scale where a combination of the following arrangements are most likely to contribute to more widespread use of climate forecasts in the future: (i) strong integration and support from institutions that generate and disseminate forecasts, (ii) information is customized for the region and industry, (iii) trust is built between the institutions and decision-makers, (iv) regional climate champions provide support and training in understanding and use of forecasts, and (v) institutions provide a climate service that delivers climate literacy and regionally relevant decision- and discussion-support tools. Incorporating climate science into climate-integrated agricultural models, decision support tools, training, and education and extension packages has made a valuable contribution to agricultural decision-making for governments, institutions, businesses, and pastoralists, but greater understanding is required to improve application and adoption for beneficial outcomes in both developing and developed world grassland communities.

The public, industry, emergency managers and other decision makers can use weather, climate and impact forecasts more effectively in their decision making when the quality of forecasts is measured in terms that are meaningful and comprehensible to them. To encourage the development of user-oriented verification approaches and support the major projects of the World Meteorological Organization (WMO) World Weather Research Program, a challenge was issued to develop and demonstrate new user-oriented forecast verification metrics. Several new forecast verification metrics were proposed to meet the needs of very different user-communities including public safety and amenity, shipping, aviation, defence, agriculture, and water resources. A few general purpose metrics were also proposed. The winner of the inaugural verification challenge proposed a new metric called the Spatial Probability Score for assessing forecasts for the location of a relevant boundary or contour, for example, sea ice edge or extent of flood inundation. We hope and expect that many of the user-oriented forecast verification metrics submitted to the inaugural verification challenge will be taken up by the broader community.

Irrigation is a critical input for raising food production in southern Africa, parts of which are food-insecure, especially as a result of low levels of technology employed, low investments into the sector, small farm sizes, and high levels of exposure to the hazards of climate variability. Most food production (including exports) and irrigation in the region occurs in the arid south—in South Africa by a large margin. Further north, in Angola, Zambia, and the northern parts of Mozambique, water resources are abundant yet irrigation farming is far less developed and inefficient, resulting in water resources being less intensely managed. The region needs to become more tightly integrated economically, with a greater flow of technology, investment, and management capability to the north, allowing the north to produce more food (and other agricultural products) which would flow to the more industrialized south—essentially virtual water flows to that region.

Whilst there has been much focus on the utility of climate information on the seasonal timescale and several decades into the future vis-à-vis decision-making and responses to climate and related risks in Africa, less attention has been given to information on the decadal timescale. Yet much policy, planning and investment decision-making within African agricultural and food systems take place within this timescale. Decadal prediction research itself has become a hot topic, and it is against this background that we explore the questions, ‘what climate information could be utilised by farmers within this timescale and of what value will it be?’ Using case studies of both small and large-scale farming systems in east and southern Africa, we show decadal climate information potentially providing opportunities for flexible, proactive and innovative decision-making in response to projected dynamics within this period, ultimately bridging the current gap not covered by seasonal forecasts and climate change projections.

干旱在南非共和国地区是一种发生频率较高的自然灾害,干旱的发生会对粮食安全产生影响.根据南非共和国的自然气候特点和内部地表覆盖及地形特点,找出了一种合适的干旱监测指数.即通过ND VI的分级对南非共和国农业区不同地表覆盖度和不同地形植被进行单独计算归一化植被供水指数(VSWI),得到监测干旱的合成干旱监测指数(SDI).用于干旱的监测数据是2001-2014年MOD13A1和MOD11A2数据,采用SDI指数结合农业种植区得到14a南非共和国高时空分辨率农业干旱监测分布数据集.通过数据分析得出,南非共和国干旱主要发生于春季末、夏季初,一般在夏季末期影响达到最大.14a间,干旱影响较严重的年份是2002年、2007年和2013年,各省发生干旱时,一般是以轻度干旱和中度干旱为主,夏季末出现重度干旱的影响.干旱发生时往往是由降雨稀少的中部地区出现,进而向东部和南部扩张,并且中部地区出现轻度干旱的频率较高.SDI得到的干旱监测结果与南非共和国干旱发生事件基本一致,弥补了气象干旱监测的不足,因此SDI干旱指数可用于南非共和国地区干旱监测.

Agriculture is one of the most vulnerable sectors to climate change. Farmers have been exposed to multiple stressors including climate change, and they have managed to adapt to those risks. The adaptation actions undertaken by farmers and their decision making are, however, only poorly understood. By studying adaptation practices undertaken by apple farmers in three regions: Nagano and Kazuno in Japan and Elgin in South Africa, we categorize the adaptation actions into two types: farmer initiated bottom-up adaptation and institution led top-down adaptation. We found that the driver which differentiates the type of adaptation likely adopted was strongly related to the farmers' characteristics, particularly their dependence on the institutions, e.g. the farmers' cooperative, in selling their products. The farmers who rely on the farmers' cooperative for their sales are likely to adopt the institution-led adaptation, whereas the farmers who have established their own sales channels tend to start innovative actions by bottom-up. We further argue that even though the two types have contrasting features, the combinations of the both types of adaptations could lead to more successful adaptation particularly in agriculture. This study also emphasizes that more farm-level studies for various crops and regions are warranted to provide substantial feedbacks to adaptation policy.

Annex 51 from Adaptation to Climate Change: Stakeholder engagement and understanding impacts - International Council for Local Environment Initiatives (ICLEI) (Section 21) list of annexure