Browsing by Author "Brown, Calum"
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Item Open Access Achievement of Paris climate goals unlikely due to time lags in the land system(Nature Publishing Group, 2019-02-18) Brown, Calum; Alexander, Peter; Arneth, Almut; Holman, Ian P.; Rounsevell, MarkAchieving the Paris Agreement’s aim of limiting average global temperature increases to 1.5 °C requires substantial changes in the land system. However, individual countries’ plans to accomplish these changes remain vague, almost certainly insufficient and unlikely to be implemented in full. These shortcomings are partially the result of avoidable ‘blind spots’ relating to time lags inherent in the implementation of land-based mitigation strategies. Key blind spots include inconsistencies between different land-system policies, spatial and temporal lags in land-system change, and detrimental consequences of some mitigation options. We suggest that improved recognition of these processes is necessary to identify achievable mitigation actions, avoiding excessively optimistic assumptions and consequent policy failures.Item Open Access Bridging uncertainty concepts across narratives and simulations in environmental scenarios(2018-05-11) Pedde, Simona; Kok, Kasper; Onigkeit, Janina; Brown, Calum; Holman, Ian P.; Harrison, Paula A.Uncertainties in our understanding of current and future climate change projections, impacts and vulnerabilities are structured by scientists using scenarios, which are generally in qualitative (narrative) and quantitative (numerical) forms. Although conceptually strong, qualitative and quantitative scenarios have limited complementarity due to the lack of a fundamental bridge between two different concepts of uncertainty: linguistic and epistemic. Epistemic uncertainty is represented by the range of scenarios and linguistic variables within them, while linguistic uncertainty is represented by the translation of those linguistic variables via the fuzzy set approach. Both are therefore incorporated in the models that utilise the final quantifications. The application of this method is demonstrated in a stakeholder-led development of socioeconomic scenarios. The socioeconomic scenarios include several vague elements due to heterogeneous linguistic interpretations of future change on the part of stakeholders. We apply the so-called ‘Centre of Gravity’ (CoG) operator to defuzzify the quantifications of linguistic values provided by stakeholders. The results suggest that, in these cases, uniform distributions provide a close fit to the membership functions derived from ranges of values provided by stakeholders. As a result, the 90 or 95% intervals of the probability density functions are similar to the 0.1 or 0.05 degrees of membership of the linguistic values of linguistic variables. By bridging different uncertainty concepts (linguistic and epistemic uncertainties), this study offers a substantial step towards linking qualitative and quantitative scenarios.Item Open Access Identifying uncertainties in scenarios and models of socio-ecological systems in support of decision-making(Cell Press, 2021-07-23) Rounsevell, Mark D. A.; Arneth, Almut; Brown, Calum; Cheung, William W. L.; Gimenez, Olivier; Holman, Ian P.; Leadley, Paul; Luján, Criscely; Mahevas, Stéphanie; Maréchaux, Isabelle; Pélissier, Raphaël; Verburg, Peter H.; Vieilledent, Ghislain; Wintle, Brendan A.; Shin, Yunne-JaiThere are many sources of uncertainty in scenarios and models of socio-ecological systems, and understanding these uncertainties is critical in supporting informed decision-making about the management of natural resources. Here, we review uncertainty across the steps needed to create socio-ecological scenarios, from narrative storylines to the representation of human and biological processes in models and the estimation of scenario and model parameters. We find that socio-ecological scenarios and models would benefit from moving away from “stylized” approaches that do not consider a wide range of direct drivers and their dependency on indirect drivers. Indeed, a greater focus on the social phenomena is fundamental in understanding the functioning of nature on a human-dominated planet. There is no panacea for dealing with uncertainty, but several approaches to evaluating uncertainty are still not routinely applied in scenario modeling, and this is becoming increasingly unacceptable. However, it is important to avoid uncertainties becoming an excuse for inaction in decision-making when facing environmental challenges.Item Open Access Implementing land-based mitigation to achieve the Paris Agreement in Europe requires food system transformation(IOP, 2019-10-04) Lee, Heera; Brown, Calum; Seo, Bumsuk; Holman, Ian P.; Audsley, Eric; Cojocaru, George; Rounsevell, MarkLand-based mitigation, particularly through afforestation, reforestation and avoided deforestation, is an important component of the 'Paris Agreement' to limit average global temperature increases to between 1.5 and 2 ◦C. However, the specific actions that would ensure sufficient carbon sequestration in forests remain unclear, as do their trade-offs against other land-based objectives. We use a regional integrated assessment model to identify the conditions under which European forests reach the extent required by mitigation targets. We compare stylised scenarios of changes in meat demand, bioenergy crop production, irrigation efficiency, and crop yield improvement. Only 42 out of 972 model simulations achieved minimum levels of food provision and forest extent without the need to change dietary preferences, but relied on crop yield improvements within Europe of at least 30%. Maintaining food imports at today's levels to avoid the potential displacement of food production and deforestation required at least a 15 % yield improvement, or a drastic reduction in meat consumption (avg. 57 %). The results suggest that the large-scale afforestation/reforestation planned in European targets is virtually impossible to achieve without transformation of the food system, making it unlikely that Europe will play its required role in global efforts to limit climate change without utilising land beyond its borders.Item Open Access Improving the representation of adaptation in climate change impact models(Springer, 2018-04-13) Holman, Ian P.; Brown, Calum; Carter, Timothy R.; Harrison, Paula A.; Rounsevell, MarkClimate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate.