Transmission of climate risks across sectors and borders

Systemic climate risks, which result from the potential for cascading impacts through inter-related systems, pose particular challenges to risk assessment, especially when risks are transmitted across sectors and international boundaries. Most impacts of climate variability and change affect regions and jurisdictions in complex ways, and techniques for assessing this transmission of risk are still somewhat limited. Here, we begin to define new approaches to risk assessment that can account for transboundary and trans-sector risk transmission, by presenting: (i) a typology of risk transmission that distinguishes clearly the role of climate versus the role of the social and economic systems that distribute resources; (ii) a review of existing modelling, qualitative and systems-based methods of assessing risk and risk transmission; and (iii) case studies that examine risk transmission in human displacement, food, water and energy security. The case studies show that policies and institutions can attenuate risks significantly through cooperation that can be mutually beneficial to all parties. We conclude with some suggestions for assessment of complex risk transmission mechanisms: use of expert judgement; interactive scenario building; global systems science and big data; innovative use of climate and integrated assessment models; and methods to understand societal responses to climate risk. These approaches aim to inform both research and national-level risk assessment

South India projected to be susceptible to high future groundnut failure rates for future climate change and geo-engineered scenarios

With an increase in global mean temperature predicted for this century accompanied by more frequent extremes, will farming communities need to brace for increased crop failures and hardship? Solar dimming climate geoengineering has been proposed as a possible solution to combat rising global temperature but what effect will it or other climate related adaptation have on crop failures? We performed a crop modelling study using future climate and geoengineering projections to investigate these questions. Our results indicate that groundnut crop failure rates in Southern India are very sensitive to climate change, and project an increase of approximately a factor of two on average over this century, affecting one out of every two to three years instead of one in every five years. We also project that solar dimming geoengineering will have little impact on reducing these failure rates. In contrast, the projections for the rest of Indian regions show decreasing failure rates of 20-30%. In this research, we indicate why south India is more susceptible than the rest of the country and show that neither Solar dimming geoengineering nor reducing heat or water stress are able to fully counteract the increase in failure rates for this region. Thus our modelling projections indicate the potential for a grountnut crop failure crisis for the South India

DynamicSDM: an R package for species geographical distribution and abundance modelling at high spatiotemporal resolution

1. Species distribution models (SDM) are widely applied to understand changing species geographical distribution and abundance patterns. However, existing SDM tools are inherently static and inadequate for modelling species distributions that are driven by dynamic environmental conditions. 2. dynamicSDM provides novel tools that explicitly consider the temporal dimension at key SDM stages, including functions for: (a) Cleaning and filtering species occurrence records by spatial and temporal qualities; (b) Generating pseudo-absence records through space and time; (c) Extracting spatiotemporally buffered explanatory variables; (d) Fitting SDMs whilst accounting for temporal biases and autocorrelation and (e) Projecting intra-and inter-annual geographical distributions and abundances at high spatiotemporal resolution. 3. Package functions have been designed to be: flexible for targeting specific study species; compatible with other SDM tools; and, by utilising Google Earth Engine and Google Drive, to have low computing power and storage needs. We illustrate dynamicSDM functions with an example of a nomadic bird in southern Africa, the red-billed quelea Quelea quelea. 4. As dynamicSDM functions are flexible and easily applied, we suggest that these tools could be readily applied to other taxa and systems globally

Initial lists of AMMA-2050 user-relevant climate metrics

AMMA-2050 (African Monsoon Multi-disciplinary Analysis 2050) will improve understanding of how the West African monsoon will be affected by climate change in the coming decades – and help West African societies prepare and adapt

Agriculture, food security and climate change: Outlook for knowledge, tools and action

Agriculture and food security are key sectors for intervention under climate change. Agricultural production is highly vulnerable even to 2C (lowend) predictions for global mean temperatures in 2100, with major implications for rural poverty and for both rural and urban food security. Agriculture also presents untapped opportunities for mitigation, given the large land area under crops and rangeland, and the additional mitigation potential of aquaculture. This paper presents a summary of current scientific knowledge on the impacts of climate change on farming and food systems, and on the implications for adaptation and mitigation. Many of the trends and impacts are highly uncertain at a range of spatial and temporal scales; we need significant advances in predicting how climate variability and change will affect future food security. Despite these uncertainties, it is clear that the magnitude and rate of projected changes will require adaptation. Actions towards adaptation fall into two broad overlapping areas: (1) better management of agricultural risks associated with increasing climate variability and extreme events, for example improved climate information services and safety nets, and (2) accelerated adaptation to progressive climate change over decadal time scales, for example integrated packages of technology, agronomy and policy options for farmers and food systems. Maximization of agriculture’s mitigation potential will require, among others, investments in technological innovation and agricultural intensification linked to increased efficiency of inputs, and creation of incentives and monitoring systems that are inclusive of smallholder farmers. The challenges posed by climate change to agriculture and food security require a holistic and strategic approach to linking knowledge with action. Key elements of this are greater interactions between decision-makers and researchers in all sectors, greater collaboration among climate, agriculture and food security communities, and consideration of interdependencies across whole food systems and landscapes. Food systems faced with climate change need urgent action in spite of uncertainties

Setting the agenda: Climate change adaptation and mitigation for food systems in the developing world

New agricultural development pathways are required to meet climate change adaptation and mitigation needs in the food systems of low-income countries. A research and policy agenda is provided to indicate where innovation and new knowledge are needed. Adaptation requires identifying suitable crop varieties and livestock breeds, as well as building resilient farming and natural resources systems, institutions for famine and crop failure relief, and mechanisms for rapid learning by farmers. Mitigation requires transitioning to ‘low climate impact’ agriculture that reduces emissions while achieving food security, economic well-being and sustainability. Efficient interventions, incentives for large-scale shifts in practices, and monitoring systems are required. Integrated assessments of adaptation and mitigation are needed to better understand the synergies and trade-offs among outcomes

Crop modelling: towards locally relevant and climate-informed adaptation

A gap between the potential and practical realisation of adaptation exists: adaptation strategies need to be both climate-informed and locally relevant to be viable. Place-based approaches study local and contemporary dynamics of the agricultural system, whereas climate impact modelling simulates climate-crop interactions across temporal and spatial scales. Crop-climate modelling and place-based research on adaptation were strategically reviewed and analysed to identify areas of commonality, differences, and potential learning opportunities to enhance the relevance of both disciplines through interdisciplinary approaches. Crop-modelling studies have projected a 7–15% mean yield change with adaptation compared to a non-adaptation baseline (Nature Climate Change 4:1–5, 2014). Of the 17 types of adaptation strategy identified in this study as place-based adaptations occurring within Central America, only five were represented in crop-climate modelling literature, and these were as follows: fertiliser, irrigation, change in planting date, change in cultivar and area cultivated. The breath and agency of real-life adaptation compared to its representation in modelling studies is a source of error in climate impact simulations. Conversely, adaptation research that omits assessment of future climate variability and impact does not enable to provide sustainable adaptation strategies to local communities so risk maladaptation. Integrated and participatory methods can identify and reduce these sources of uncertainty, for example, stakeholder’s engagement can identify locally relevant adaptation pathways. We propose a research agenda that uses methodological approaches from both the modelling and place-based approaches to work towards climate-informed locally relevant adaptation

Global wheat production with 1.5 and 2.0°C above pre‐industrial warming

Efforts to limit global warming to below 2°C in relation to the pre‐industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre‐industrial period) on global wheat production and local yield variability. A multi‐crop and multi‐climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by −2.3% to 7.0% under the 1.5°C scenario and −2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980–2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter‐annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer—India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade