1. Theme 2:
Crises and tipping points: Past, present and future interactions between food insecurity and ES at the forest-agricultural interface

2. Definition of Tipping Points
Tipping points represent significant shifts that abruptly change the system from one state to another

3. Example of a tipping point: Climate change
A climate 'tipping point' occurs when a small change in forcing triggers a strongly nonlinear response in the internal dynamics of part of the climate system, qualitatively changing its future state.

4. Example of a tipping point: Political Change/Major Disaster
Our results show that the collapse of the Soviet Union in 1991 caused a major reorganization in land use systems. The effects of this socio-economic disturbance were at least as drastic as those of the nuclear disaster in the Chernobyl region in While the magnitudes of land abandonment were similar in Ukraine and Belarus in the case of the nuclear disaster (28% and 36% of previously farmed land, respectively), the rates of land abandonment after the collapse of the Soviet Union in Ukraine were twice as high as those in Belarus.

5. Example of a tipping point: Food Security in Tajikistan
Households in Tajikistan’s south are close to the tipping point in terms of their ability to feed themselves this year. Untimely rains over the past 12 months first damaged last year’s harvest and now threaten a severely compromised harvest this year. Accumulated economic hardships – increasing debt, diminishing food stocks, the brunt of natural disasters, and this year’s spiraling food costs – have brought vulnerable households to a point from which they will have great difficulty recovering without outside assistance. It remains to be seen how badly this situation will affect southern Tajikistan’s children, who are already showing widespread signs of acute malnutrition.

6. Example of a tipping point: Behavior change in India
Recent trends suggest that India might very well be at the "tipping point" of the transition in its agriculture dependent population. A large proportion of youth in the countryside is on their way out of agriculture. Rising disenchantment with the profession pushes them out of agriculture while opportunities in other sectors of the booming economy pull them out of agriculture.

7. Diffusion of Innovation Adoption Curve (Everett Rogers)
Diffusion of Innovations is a theory that seeks to explain how, why, and at what rate new ideas and technology spread through cultures. Everett Rogers, a professor of rural sociology, popularized the theory in his 1962 book Diffusion of Innovations. He said diffusion is the process by which an innovation is communicated through certain channels over time among the members of a social system. The origins of the diffusion of innovations theory are varied and span multiple disciplines.

8. Diffusion of Innovation Adoption Curve

9. Issues of Tipping Points
Are tipping points the result of random factors, tipping points, chaos theory or completely unpredicted black swans?
The issue is to understand how spatiotemporal data analysis can discover key variables and relationships involved in spatial temporal events
One of the main challenges in discovering tipping point-like events is that the general assumptions inherent in any technique may become violated after an event occurs

10. Space, complexity, and agent-based modeling
There is considerable interest in agent-based modeling as a tool to understand better the dynamics of complex systems. Particular attention has been focused by the land-change science community, but there has also been a good deal of effort in fields including epidemiology (Teweldemedhin et al, 2004), finance (LeBaron, 2000), computational sociology (Macy and Willer, 2002), ecology (Grimm et al, 2005), and computational economics (Tesfatsion, 2002).

11. Questions/topics for brainstorming
Which tipping points do we anticipate being important?
How are we going to test whether there are indeed tipping points?
Which tipping points are we interested in exploring?
Which variables are the driving variables?
How are we going to obtain information about them (e.g., household surveys,  health measurements and participatory mapping of ES, and any other field data that will be collected)?
What models will we use to explore tipping points under potential scenarios of (e.g., climate change, land use change, changes in ES and HWB)?