Understanding the future
Planning implies preparing for the future, a familiar challenge for households, companies and governments. Because we live in a changing world that is unlikely to be the same next year, we commonly project trends that are sufficiently well behaved to allow linear extrapolation using various mathematical transformations.
Most systems are nonlinear and affected by variables other than time. Nevertheless, they can be predictable if the main drivers of change can be identified and properly linked. Foresight analysis and systems dynamics modeling have been insightfully applied (Alcamo 2008). However, an increasingly, important aspect of planning involves assessment of risk and the open question of its tolerability (Boulder et al. 2007, Kennedy 2008).
Some appreciation of uncertainty can be gained by adding selected stochastic elements to systems dynamics models. This generates more believable outputs and sometimes reveals stable points, turning points, and other thresholds. An array of tools permit quantitative assessment of risk [particularly the probability of failure] that certainly help us deal with random events. Agent-based models offer some promise for revealing the emergent properties of systems and are particularly useful for identifying the means of control. However, none of these tools prepare us for the unfathomable events that broadside us whether or not of our own doing (Samuel et al. 2009).
Increasingly, we live in a world not just of uncertainty but also surprise. Anthropogenic climate change, HIV, and BSE were not and perhaps could not have been anticipated. At several points in history, societies have declared that everything is known. So the solution may not be a massive broadly-based scientific initiative to determine whatever is left. Rather, focus might turn to resilience to complement the usual measures of productivity, efficiency and profitability.
Preparing for the future
Significant challenges face food system adaptation (Fresco 2008). Some are related to profitable and sustainable food production, processing and distribution. Others are related to the changing public attitudes, political environment and the outcome of international negotiations (Tansey and Rajotte 2008).
New fundamentals
Rethinking the global food system and Alberta’s part in it demands re-examination of the basic assumptions that underlie the evolution of the current system. The following issues will change the way we do business:
- Oil and energy is the basis of the food economy but heavy dependence on this key input narrows margins and creates volatility in food commodity markets.
- Transportation is the basis of globalization but the food industry must prepare for a low mobility future (Moriarty and Honnery 2008). Beyond the relationship between transport cost of and oil prices, are concerns about impacts on climate change and the spread of infectious disease.
- Water scarcity has always been an issue in expansion of the agricultural frontier but it is no longer just a matter of water development as sources are depleted and degraded worldwide.
- Biodiversity is an emerging concern that did not constrain food production in the past. Valuation of ecosystem services changes the balance sheet (Soderbaum 2008).
- Disease has become an important issue in participation in world markets and protection of local industries (Levin 2007). Because of travel, trade, climate change and landscape transformation, infectious zoonotic diseases have gained unexpected significance (Patz et al. 2007).
- Urbanisation/industrialization has distanced consumers from sources of food and agricultural industries from the environment that sustains them. Urban dwellers do not know where their food comes from and food suppliers are increasingly unaware of the where and how of production.
- Public sentiment changes as basic needs are met and this raises new questions about food sovereignty (Wenche and Kracht 2007) and the future of the industrial production model (Yunus 2007).
Sustainability science
The Millennium Ecosystem Assessment synthesized a vast but fragmented body of knowledge, provided a new framework for understanding socio-ecological systems, and turned attention to the ability of ecosystems to provide provisioning, regulating, and cultural services. Although trends, key drivers and management interventions have been identified, we still lack insight into the dynamics of these coupled socio-ecological systems (Carpenter et al. 2009). This is the challenge that defines the emerging field of Sustainability Science. This research is necessarily transdisciplinary and addresses the linkages of science, policy and practice.
Ecosystems can be described in terms of their composition (biodiversity), structure (ecological integrity) or function (ecosystem health). Biodiversity is the best known measure. The original definition of species diversity has been broadened to include genomes at the finer and landscapes at the larger scale. Diversity is believed to confer ecosystem resilience – the ability to resist environmental shocks (Ives and Carpenter 2007).
Biodiversity is useful as a concept but it can be misunderstood and misapplied. Indices of species richness makes sense only at certain scales and not all contributions to species richness can be considered positive (invasive species). Comprehensive biodiversity assessments including large number of taxa become insensitive as indicators of impact. Attention is turning from biodiversity to ecological integrity shifting emphasis from elements to processes. The next step, ecosystem health, describes emergent properties of ecosystems such as resistance to biological invasions and other expressions of resilience. Clearly this is the most operational form but it is curioiusly difficult to assess at relevant scales.
Large-scale transdisciplinary science of the sort needed presents unique challenges. Neither institutions nor individual scientists are comfortable working at this scale. Reward structures, institutional organization and funding mechanisms are not prepared to deal with the challenge. The “science of team science” explores complex dynamics of working groups and how they might achieve focus (MacMynowski 2007, Meyer, M. 2007, Pahl-Wostl et al. 2008, Stokol et al. 2008). As important as this may be for properly planning for resilience (Brand 2009), the incentives, organizational structures and funding mechanisms are not there to encourage it.
LearningThe current educational system is designed to prepare people for the industrial economy. In a world where the turnover time of information is so brief and the complexity of problems so great, educational systems will need a complete overhaul. Mark Federman emphasizes the importance of the 4 Cs of education (successor to the 3 Rs). These are: connection, context, complexity, and connotation. These skills are learned in different ways (Mejia and Espinosa 2007, McIntosh et al. 2007). It is very different from the familiar “innovation chain”. Such a major transformation of the knowledge cycle and skill acquisition system will prove as intractable as restructuring the global food system.
