Five years after adoption of the 2030 Agenda, there is a general lack of progress in reaching its Sustainable Development Goals—be it on national, regional, or global scales. Scientists attribute this above all to insufficient understanding and addressing of interactions between goals and targets. This study aims to contribute to the methodological conceptualization of the 2030 Agenda’s implementation at the national level. To this end, taking the case of Switzerland, we tested and enhanced existing approaches for assessing interactions among the 2030 Agenda’s targets and for analysing the systemic relevance of priority targets. Building on our insights, the article concludes with an eight-step proposal for creating knowledge to support national 2030 Agendas.

This study examines the validity of the assumption that international large-scale land acquisition (LSLA) is motivated by the desire to secure control over water resources, which is commonly referred to as ‘water grabbing’. This assumption was repeatedly expressed in recent years, ascribing the said motivation to the Gulf States in particular. However, it must be considered of hypothetical nature, as the few global studies conducted so far focused primarily on the effects of LSLA on host countries or on trade in virtual water. In this study, we analyse the effects of 475 intended or concluded land deals recorded in the Land Matrix database on the water balance in both host and investor countries. We also examine how these effects relate to water stress and how they contribute to global trade in virtual water. The analysis shows that implementation of the LSLAs in our sample would result in global water savings based on virtual water trade. At the level of individual LSLA host countries, however, water use intensity would increase, particularly in 15 sub-Saharan states. From an investor country perspective, the analysis reveals that countries often suspected of using LSLA to relieve pressure on their domestic water resources—such as China, India, and all Gulf States except Saudi Arabia—invest in agricultural activities abroad that are less water-intensive compared to their average domestic crop production. Conversely, large investor countries such as the United States, Saudi Arabia, Singapore, and Japan are disproportionately externalizing crop water consumption through their international land investments. Statistical analyses also show that host countries with abundant water resources are not per se favoured targets of LSLA. Indeed, further analysis reveals that land investments originating in water-stressed countries have only a weak tendency to target areas with a smaller water risk.

In the ongoing discussions on the transition to low-carbon systems a reduction of working hours has gained increased interest. A shift to lower incomes coupled with more discretionary time might promote low(er) individual carbon lifestyles without impairing individual well-being. Lower carbon emissions have been linked to shorter working hours on a macroeconomic level and to lower income, and thus less carbon-intensive activities on an individual level. However, little empirical research has been done on the effects of a self-determined reduction of working time on an intra-individual level. The aim of this paper was to explore whether and how a reduction of working hours facilitates low(er)-carbon lifestyles. We do this by means of 17 qualitative guideline interviews with Swiss employees that had recently reduced their working hours. Our results suggest that the underlying motives behind the employees’ decisions to reduce their working hours are crucial. A beneficial climate-saving effect arose only for those employees who dedicated their newly gained time to binding activities, that require a certain degree of commitment, such as parenting and further education. In contrast, those who reduced their working hours due to a desire for more recreational time risked increasing the carbon intensity of their lifestyles due to carbon-intensive leisure activities.

In land systems, equitably managing trade-offs between planetary boundaries and human development needs represents a grand challenge in sustainability oriented initiatives. Informing such initiatives requires knowledge about the nexus between land use, poverty, and environment. This paper presents results from Lao PDR, where we combined nationwide spatial data on land use types and the environmental state of landscapes with village-level poverty indicators. Our analysis reveals two general but contrasting trends. First, landscapes with paddy or permanent agriculture allow a greater number of people to live in less poverty but come at the price of a decrease in natural vegetation cover. Second, people practising extensive swidden agriculture and living in intact environments are often better off than people in degraded paddy or permanent agriculture. As poverty rates within different landscape types vary more than between landscape types, we cannot stipulate a land use–poverty–environment nexus. However, the distinct spatial patterns or configurations of these rates point to other important factors at play. Drawing on ethnicity as a proximate factor for endogenous development potentials and accessibility as a proximate factor for external influences, we further explore these linkages. Ethnicity is strongly related to poverty in all land use types almost independently of accessibility, implying that social distance outweighs geographic or physical distance. In turn, accessibility, almost a precondition for poverty alleviation, is mainly beneficial to ethnic majority groups and people living in paddy or permanent agriculture. These groups are able to translate improved accessibility into poverty alleviation. Our results show that the concurrence of external influences with local—highly contextual—development potentials is key to shaping outcomes of the land use–poverty–environment nexus. By addressing such leverage points, these findings help guide more effective development interventions. At the same time, they point to the need in land change science to better integrate the understanding of place-based land indicators with process-based drivers of land use change.