Climate change research is at an impasse. The transformation of economies and everyday practices is more urgent, and yet appears ever more daunting as attempts at behaviour change, regulations, and global agreements confront material and social-political infrastructures that support the status quo. Effective action requires new ways of conceptualizing society, climate and environment and yet current research struggles to break free of established categories. In response, this contribution revisits important insights from the social sciences and humanities on the co-production of political economies, cultures, societies and biophysical relations and shows the possibilities for ontological pluralism to open up for new imaginations. Its intention is to help generate a different framing of socionatural change that goes beyond the current science-policy-behavioural change pathway. It puts forward several moments of inadvertent concealment in contemporary debates that stem directly from the way issues are framed and imagined in contemporary discourses. By placing values, normative commitments, and experiential and plural ways of knowing from around the world at the centre of climate knowledge, we confront climate change with contested politics and the everyday foundations of action rather than just data.
The development of crop varieties that are better suited to new climatic conditions is vital for future food production 1,2 . Increases in mean temperature accelerate crop development, resulting in shorter crop durations and reduced time to accumulate biomass and yield 3,4 . The process of breeding, delivery and adoption (BDA) of new maize varieties can take up to 30 years. Here, we assess for the first time the implications of warming during the BDA process by using five bias-corrected global climate models and four representative concentration pathways with realistic scenarios of maize BDA times in Africa. The results show that the projected di erence in temperature between the start and end of the maize BDA cycle results in shorter crop durations that are outside current variability. Both adaptation and mitigation can reduce duration loss. In particular, climate projections have the potential to provide target elevated temperatures for breeding. Whilst options for reducing BDA time are highly context dependent, common threads include improved recording and sharing of data across regions for the whole BDA cycle, streamlining of regulation, and capacity building. Finally, we show that the results have implications for maize across the tropics, where similar shortening of duration is projected.By 2050 the majority of African countries will have significant experience of novel climates 1 . However, precise information as to when novel climates will occur has not been available until the recent development of techniques to identify the time of emergence of climate change signals 5,6 . These techniques quantify the signal of a change in climate relative to the background 'noise' of current climate variability. Metrics that capture the response of crops to single or multiple aspects of weather or climate (crop-climate indices 7 ) are another tool that has been developed intensively in recent years. Alongside crop yield modelling, these techniques now enable assessments of the projected times at which climate change will alter crop productivity. These alterations are mediated through both crop growth (that is, photosynthesis and biomass accumulation) and development (phenological and morphological responses).We use seven crop-climate indices (Supplementary Table S2) to identify when heat stress, drought stress and crop duration (that is, time from germination to maturity) become systematically and significantly outside the ranges at present experienced by maize cultivation in sub-Saharan Africa. Crop breeders have long been aware of the need to develop new crop varieties that are suited to future climates, particularly with respect to heat and drought stress 8,9 . Heat stress impacts are evident in our analysis. However, heat stress indices are not sufficiently constrained at present (that is, uncertainty in their values is too great) for detection of a climate change signal; only the signal in crop duration changes exceeded the noise of climate variability and thus showed a time of emergence within this century (see...
Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects.The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available.The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components:Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk?Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output.Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper.
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