This theme looks at how local and regional drivers can generate global-scale challenges like crises in energy, food, and water
Researchers have greatly advanced our understanding of the Anthropocene by mapping and quantifying linkages of many biophysical components at the planetary scale. However, we still have a poor understanding of social-ecological connectivity at the global scale. The pace and extent of global changes means there is a pressing need to develop our understanding of how social processes are interconnected and how they drive and interact with the processes of the biosphere at multiple scales.
Our research on these global dynamics is organized under the multi-organizational initiative "Changing Planet". 'Changing Planet' is an umbrella initiative to jointly coordinate global research at the Stockholm Resilience Centre, the Beijer Institute of Ecological Economics and the Global Economic Dynamics and the Biosphere Programme at the Royal Swedish Academy of Sciences. It is a response to the need for improved understanding of global and cross-scale processes and interactions between our Earth’s social and ecological components. This knowledge can improve our ability to realize sustainable stewardship of the biosphere.
Stockholm Resilience Centre's global research under this initiative aims to provide a platform to develop this knowledge, making use of the diverse methodological toolboxes and skillsets of the contributing research programs and their international partners.
Our research is centered around three broad questions:
How is the human enterprise shaping the biosphere, from local to global scales?
How do we better understand critical emerging risks and opportunities created by novel interconnections between human activities and the biosphere?
And how can we become better stewards of planet Earth?
Research news | 2016-08-24
How to use planetary boundaries as a guide for human ingenuity and innovation
Research news | 2016-06-28
New study examines where global infectious disease threat events come from
Research news | 2016-04-19
Announcing Global Sustainability, a new Open Access launch from Cambridge
Research news | 2016-03-23
Biodiversity observations on Twitter can contribute to ecological monitoring
Research news | 2016-01-18
Participatory scenario planning allows people to tackle complex environmental problems, but improvement needed
Research news | 2015-12-04
Reducing resilience to a few measurements can block deeper understanding
2016 - Journal / article
Infectious disease threat events (IDTEs) are increasing in frequency worldwide. We analyzed underlying drivers of 116 IDTEs detected in Europe during 2008–2013 by epidemic intelligence at the European Centre of Disease Prevention and Control. Seventeen drivers were identified and categorized into 3 groups: globalization and environment, sociodemographic, and public health systems. A combination of >2 drivers was responsible for most IDTEs. The driver category globalization and environment contributed to 61% of individual IDTEs, and the top 5 individual drivers of all IDTEs were travel and tourism, food and water quality, natural environment, global trade, and climate. Hierarchical cluster analysis of all drivers identified travel and tourism as a distinctly separate driver. Monitoring and modeling such disease drivers can help anticipate future IDTEs and strengthen control measures. More important, intervening directly on these underlying drivers can diminish the likelihood of the occurrence of an IDTE and reduce the associated human and economic costs.
2015 - Journal / article
Ongoing climate change is known to cause an increase in the frequency and amplitude of local temperature and precipitation extremes in many regions of the Earth. While gradual changes in the climatological conditions are known to strongly influence plant 5 flowering dates, the question arises if and how extremes specifically impact the timing of this important phenological phase. In this study, we systematically quantify simultaneities between meteorological extremes and the timing of flowering of four shrub species across Germany by means of event coincidence analysis, a novel statistical tool that allows assessing whether or not two types of events exhibit similar sequences 10 of occurrences. Our systematic investigation supports previous findings of experimental studies by highlighting the impact of early spring temperatures on the flowering of wildlife plants. In addition, we find statistically significant indications for some long-term relations reaching back to the previous year.
2015 - Journal / article
Identifying regions important for spreading and mediating perturbations is crucial to assess the susceptibilities of spatio-temporal complex systems such as the Earth’s climate to volcanic eruptions, extreme events or geoengineering. Here a data-driven approach is introduced based on a dimension reduction, causal reconstruction, and novel network measures based on causal effect theory that go beyond standard complex network tools by distinguishing direct from indirect pathways. Applied to a data set of atmospheric dynamics, the method identifies several strongly uplifting regions acting as major gateways of perturbations spreading in the atmosphere. Additionally, the method provides a stricter statistical approach to pathways of atmospheric teleconnections, yielding insights into the Pacific–Indian Ocean interaction relevant for monsoonal dynamics. Also for neuroscience or power grids, the novel causal interaction perspective provides a complementary approach to simulations or experiments for understanding the functioning of complex spatio-temporal systems with potential applications in increasing their resilience to shocks or extreme events.
2015 - Journal / article
Knowledge of metabolic processes is collected in easily accessible online databases which are increasing rapidly in content and detail. Using these databases for the automatic construction of metabolic network models requires high accuracy and consistency. In this bipartite study we evaluate current accuracy and consistency problems using the KEGG database as a prominent example and propose design principles for dealing with such problems. In the first half, we present our computational approach for classifying inconsistencies and provide an overview of the classes of inconsistencies we identified. We detected inconsistencies both for database entries referring to substances and entries referring to reactions. In the second part, we present strategies to deal with the detected problem classes. We especially propose a rule-based database approach which allows for the inclusion of parameterised molecular species and parameterised reactions. Detailed case-studies and a comparison of explicit networks from KEGG with their anticipated rule-based representation underline the applicability and scalability of this approach.