Collaboration with other disciplines

Many of the identified limitations cannot be addressed by IAMs alone. The underlying assumptions, granularity of available data or the analysis of results require IAMs to draw on insights from other disciplines or to develop new tools jointly with other scientific communities. As the 17 SDGs cover many scientific fields, providing research needs for all these domains would be beyond the scope of this report. We focus here on select research needs conceivable to be relevant for IAMs in the foreseeable future and related to trends dealt with in this chapter.

Figure 3.17. IAM representation of SDGs. Colors represent average score for individual target coverage based on a survey among IAM models. Green: SDG is well captured and most targets can be modeled (darkest green: average score above 3, green: average score between 2 and 3, light green: average score between 1.5 and 2).

Orange: SDG can partly be quantified (not all targets or only proxy indicators), with average scores between 1 and 1.5. Red: SDG is not well captured, with average scores below 1. Source: adapted from van Soest et al. (in review).

Linking scientific communities and developing integrated pathways within a consistent framework Many interactions, deemed important by experts, are not currently covered by IAMs, and in some cases they are also not considered to be fully quantifiable in the foreseeable future (van Soest et al., in review). Knowledge gaps lie in interactions across the human development goals, where research could aim to identify and test the causal links. This relates mainly to human

development interactions and governance, institutions and existence of legal frameworks and policies (Allen et al., 2016) and their effects on many other SDGs: the effect of poverty on education, of education on economy, of gender equality on inequalities, and of peace on international cooperation. These could be covered differently than through model advances, foremost e.g., by linking scientific communities and combining models. Such an approach would be beneficial especially for the Box 3.9. Bringing regional perspectives to TWI2050 – The African Dialogues.

Highlighting the regional perspectives in SDPs will be key to foster the transformation processes at multiple levels. Therefore, an important branch of activities in the TWI2050 consortium focuses on cross-scale questions including the regional perspectives and cross-scale relationships. This is also illustrated by the different trends in land use in two alternative sustainability-oriented scenarios: i.e. the SSP1 baseline and the derived mitigation scenario consistent with the 1.5°C climate target (Doelman et al., 2018;

Rogelj et al., 2018; van Vuuren et al., 2017) (Figure 3.18). Similar differences in regional land use also play a role other sustainability scenarios.

Figure 3.18. Change in land use (percentages of grid cells) between 2010 and 2100; deforestation and conversion of other natural land to agriculture (red) and reforestation and abandonment of agriculture to other natural land (green) for SSP1 baseline scenario and SSP1 1.5 °C mitigation scenarios (1.9 W/m²). The circles emphasize the contrasting resulting land use patterns for Latin America and Africa. In SSP1, the premise is that livestock sector intensifies substantially, and food losses and dietary preferences for animal products are reduced, leading to abandonment of grazing land. Abandonment takes place in relatively productive areas (predominantly north-western Brazil, for instance) leading to high potential for bioenergy production. In sub-Saharan Africa, SSP1 shows a decrease of grazing land, though cropland is still expanding. When considering additional mitigation measures (b), the amount of deforestation in the Brazilian Cerrado and sub-Saha-ran Africa reduces significantly, with a considerable increase of forest areas. REDD together with reforestation of degraded forest areas leads to substantial increases in forest area in the mitigation scenarios. However, in Africa, in the mitigation scenario, agricultural demand cannot be fulfilled within the region, requiring high levels of net import from other regions.Source: Doelman et al (2018).

social and institutional areas (e.g., demography, governance, and poverty research) (van Soest et al., in review; Zimm et al., 2018).

More integrated pathways with contributions from a variety of scientific communities could be brought together by a joint narrative and harmonized exogenous assumptions, similar to the SSPs (O’Neill et al., 2017; Riahi et al., 2017). Zimm et al.

(2018) provide an overview of knowledge gaps (e.g., on gender, oceans or governance) within the SSPs vis-à-vis the SDGs that call for collaboration across scientific fields. They call for fur-ther development of the SSP narrative and quantifications to

encompass SDG dimensions currently not considered, on a way to a more comprehensive framework. Already today, the SSPs enable researchers from different scientific disciplines to base their work on consistent assumptions and to adapt them to their specific needs and methods (e.g., Hegre et al. (2016)), telling a joint story. This kind of research approach needs to be broade-ned to inform policymakers working on SDG implementation.

It also leads to cross-fertilization between research communi-ties, especially social and natural sciences. These communities need to develop a common understanding and language to be able to work together and find solutions for the grand challen-ges the SDGs aim to overcome. The TWI2050 framework aims In the coming years, it is foreseen that multiple SDPs will be created in the scope of TWI2050, also presenting regional differences, representing different regional branching points, trade-offs, policy options and – not less important - premises related to the regio-nal developments. A good illustration is the first regioregio-nal stakeholder workshop of the TWI2050 process, which was held in 2017 in close collaboration with SwedBio and the SDG Centre for Africa in Kigali, Rwanda. The focus of the 1st Dialog Workshop was on how agriculture in Africa can contribute to meeting the SDGs within the planetary boundaries. The Dialog brought together a diverse group of stakeholders to explore SDPs and add different African perspectives. The event was organized around clusters of SDGs. Figure 3.19 presents a schematic overview of the core pathway elements discussed during the event, synthesized around governance and agricultural practices issues. The long-term vision is to refine the process of building regional pathways, using them to enrich the global pathways, while also promoting the cross-scale discussion about SDG implementation in subsequent work-shops. Those will, for instance, use a structured multi-scale, participatory scenario process (Rosa et al., 2017; Folhes et al., 2015;

Oteros-Rozas et al., 2015) to create and integrate pathways according to the TWI2050 framework. We intend this to be the seed for many other similar activities to be replicated in other contexts.

Figure 3.19. Messages from the discussions of the African Dialog include that SDPs must acknowledge the multiple roles, functions and impacts of agriculture for social-ecological resilience and wellbeing. Africa’s agricultural landscapes and food systems have been shaped and sustained by deep social, traditional and cultural values. African cultural values for food and agriculture need reviving in many places and need recognition and protection in policy. Furthermore, participants argued that rural and agricultural livelihoods need to be seen as attractive. The current waves of urbanization compound the problems of degradation of natural re-sources and fragmentation of rural communities. The view that only cities provide opportunities is particularly prevalent among the youth, driving a sector-specific brain drain that harms the sustainability and effectiveness of the agricultural sector at large. Incentives and policies to retain youth and increase women’s partici-pation in agribusiness may counteract this trend. The complete workshop report is available at: https://swed.bio/reports/report/dialogue-workshop-report-afri-can-dialogue-twi2050/. Source: Collste et al. (in preparation).

to provide such a bridging function, and the interdisciplinary CD-LINKS⁴, PATHWAYS⁵ and REINVENT⁶ projects provide further examples of developing a common understanding.

Reflecting societal change and governance better IAMs apply a number of concepts, including narratives, pa-thways, policy assumptions, etc. which so far largely use ad hoc assumptions on societal change and governance. Thorough theory-based assumptions that underpin causal relationships between societal change and governance on the one side and sustainable development on the other are only now emerging (Chapter 5). These concepts provide entry points for social sci-ence knowledge, which can enrich modeling efforts in various ways: i) insights on the use and function of narratives in socie-ties, ii) insights on (drivers of) value changes in sociesocie-ties, iii) insights on (drivers of) changes of political systems and orders, iv) insights on (drivers of) policy change and diffusion, v) in-sights on the adoption rates of certain technologies, vi) a review of current suggestions and potentially further development of indicators for measuring SDGs 16 and 17, vii) an indicator and data set on country implementation capacities at a global scale, viii) country case studies on the political economy of policy/

nexus/SDG implementation. Social science research is also re-levant when it comes to the implementability and acceptability of policies(Devine-Wright et al., 2017). Empirical analyses will also be needed for concrete policy advice at local and national level (van Soest et al., in review).

Application of demographic tools in the field of global environmental change

Despite a close link between population and sustainability, demography remains under-represented in global change re-search. Historical development of the field of population and environment since the 1960s in which the Malthusian ‘limits to growth’ was dominant carries bitter controversies regarding family planning and reproductive rights. This makes many con-temporary demographers shy away from the topic of environ-mental change (McDonald, 2016). However, demography has relevant theoretical concepts and methodological tools that can be useful in sustainability research. This includes, for in-stance, population estimates and projections and the study of differential vulnerability (Muttarak et al., 2015). In particular, the potential in forecasting can contribute to the understanding of how the world will look like under different socioeconomic development scenarios (Lutz and Muttarak, 2017). More appli-cation of demographic tools in the field of global change and sustainable development thus is needed. In particular, taking account of heterogeneous characteristics of the population and their spatial distribution is crucial for policy planning since consumption patterns and vulnerability vary with population characteristics (Lutz and Striessnig, 2015). Recent population projections by IIASA researchers, for example, have introduced education and labor force participation in addition to age and

4 http://www.cd-links.org/

5 http://www.pathways-project.eu/

6 https://www.reinvent-project.eu/

7 The IPCC secretariat is currently consolidating a research agenda on urbanization, cities and climate change: https://citiesipcc.org/beyond/conference-outputs/

sex to describe population heterogeneities (Lutz et al., 2018;

Lutz et al., 2017; Loichinger, 2015). These population characte-ristics matter not only for demography but also for a societies’

adaptive capacity, economic growth, governance and the like (Lutz and Muttarak, 2017; Muttarak and Lutz, 2014; Lutz et al., 2010; Lutz et al., 2008).

Education as a means for achieving other SDGs

Education is commonly treated as an end, a goal in the sustai-nable development agenda. However, recently it has been argued that education is also a means through which other goals are to be met (Bengtsson et al., 2018). In the context of health, for instance, a recent study empirically shows that it was an increase in mean years of schooling that explains an increase in life expectancy glo-bally, and not income as presented in early literature (Lutz and Kebede, 2018). Similarly, in the field of vulnerability, the level of education is found to be a better predictor of disaster mortality in a country than GDP (Striessnig et al., 2013). Research of this kind is needed, especially because it can inform policymakers which area of sustainable development to prioritize.

Advancing health research and global change

The complex interactions and feedbacks between health, de-velopment, and drivers of global change remain largely unex-plored. Better understanding of these feedbacks could provide insights into facilitating transformations to achieve the SDGs and future health goals. A comprehensive health research agen-da would emphasize first and foremost a vision of system trans-formation in light of global changes. Thus, cross-disciplinary collaborations between health experts and those in other sectors are needed to better understand likely feedbacks between health and other systems, which could further inform existing narrati-ves around health systems under global change with regards to the level and timing of investments to protect and promote health in a future that will differ significantly from today (Sellers and Ebi, 2018). Once feedbacks between health and other sectors are better understood, then they could be incorporated into IAMs to quantify their spatial and temporal variability as well as likely magnitude.

Pushing urbanization research

Key research gaps in urbanization research are the development of structured scenarios that quantitatively and qualitatively cha-racterize sustainability implications of different choices made.

The specific goals of SDG 11 have not yet been explored quan-titatively and with respect to development in 2030 or 2050. One reason is that the urban/housing/mobility community empha-sizes the problematic situation in specific cities but hesitates to generalize patterns and dynamics across cities. Another reason is that issues like adequate housing have been not consistently defined and may subjectively vary between different cities. Top-down scenarios in turn might not be very informative as they lack detail. A transdisciplinary approach would be very helpful to push the agenda⁷.

Developing an integrated understanding of demand Using consumption and demand as an entry point (3.3.1) to dif-ferent systems opens up a diverse research area which on the one hand, calls for individual disciplines (such as anthropology, sociology, psychology, economics, engineering) to deepen their knowledge on the underlying drivers (Creutzig et al., 2018b)A synthesis of research on cultural norms and values, socio-demo-graphics, habits, preferences and structural aspects of consump-tion and consumpconsump-tion patterns is essential. On the other hand, bringing together the scientific knowledge of these diverse di-sciplines to jointly work on an integrated assessment of demand for services and products and their potential environmental im-pacts (e.g., carbon or material footprint) will push the scientific frontier. Interdisciplinary and transdisciplinary research will improve modeling human decisions, and further approaches treating humans as agents.

In addition, research on policy options that influence demand and its socioeconomic and environmental impacts is needed;

on question of: which measures are effective, socially and poli-tically acceptable, and under which conditions can they be im-plemented? Combining theories on behavioral tipping points, social norms, transition theory, and insights from bottom-up assessment of techno-economic studies and models with IAMs will be one way forward, reflecting interactions between sectors and systems. For more consistent and systematic modeling ef-forts, it is important to be able to access and compare grounded assumptions on demand. A common interdisciplinary

frame-work such as put forth by TWI2050 can help systematize such assumptions and how they are reflected in models, fostering cross-sectoral learning.

Improving the representation of labor markets, innovation and inequality

Macro-economic modeling frameworks capturing the inter-action between technological progress, frictional labor markets and distributional implications for household income are ac-tively researched, and a better understanding is needed which of these frameworks are mature and computationally efficient enough to be adopted by large-scale numerical modeling with IAMs. A huge force in shaping future innovation, employment, and inequality will be the digital revolution and the associated automation of cognitive tasks. Collaboration between the ma-cro-economics, machine learning and sustainability research communities is needed to assess the opportunities and threats of these developments for a sustainability transformation.

All the above research needs address elements that will enhan-ce the evidenenhan-ce-base guiding the implementation of the SDGs, provided that the scientific community can convey its knowled-ge to national decision makers on policy choices and actions, strengthening the national science-policy interface (Colglazier, 2018). For this to happen, governments and institutions at all levels need to prepare for these advances and actively promote and support the scientific community.