How Strong Sustainability Became Safety
Abstract
:1. Introduction
2. Materials and Methods
3. Strong Sustainability
3.1. Strong Sustainability for Resource-Dependent Human Societies
3.1.1. The Folk Theorem: Substituting Renewables for Depleted Exhaustibles to Achieve Sustainability
3.1.2. An Initial Exploration of the Relationships among Resource Stocks, Environmental Services, and Dependable Harvests
- (i)
- Suppose E(t) is valued but H(t) is not, and E(t) = f (), , with positive first derivative and negative second derivative. Then, there will be an optimal (t) trajectory. In the simplest case, where technology of producing E(t) from S(t) is unchanging, the optimal time-path of (t) implies an optimal time path of S*(t), from a beginning S0 that may be larger or smaller than optimal, that will converge to a constant for the remainder of the time path.
- (ii)
- Suppose E(t) and H(t) are both valued and they compete such that / < 0. When the trade-off is resolved, |< |= 0; that is, concern for E will reduce the optimal harvest. Hmin(t), if relevant, is a given and cannot be adjusted downward to make room for additional E(t).
- (iii)
- Suppose E(t) is valued but so is D(t), an activity that competes with E(t) and S(t) for a fixed supply of land so that / < 0. When the trade-off is resolved, | < |D(t) = 0; that is, demand for a competing land-using activity will reduce the optimal quantity of environmental services, an outcome that may be consistent with the value system of WS but is unacceptable to many SS proponents (Section 3.2).
3.1.3. SS for Threatened Resources One by One
3.1.4. SS for Constant Natural Capital
3.2. SS Is a Big Tent in Terms of Motivations
SS for Landscapes and Ecosystems
4. The Emergence of a Safety Interpretation of SS
4.1. Stochastic Systems
4.1.1. Stochasticity in Renewable Resource Systems—Safeguarding the Harvest
4.1.2. Adapting Ciriacy-Wantrup’s SMS to Preservation of Unique Natural Assets
4.2. Complex Dynamic Systems, Phase 1
4.3. Complex Dynamic Systems, Phase 2
4.3.1. Panarchy
- Complex systems are discontinuously structured. The hypothesis that key variables are distributed discontinuously has been confirmed in a wide variety of contexts including animal body mass, city size, firm size, and aquatic communities. Several tests in shallow lakes have confirmed that variability increases when regime change is approached.
- Complex systems undergo cycles of renewal and destruction. Cycling is observed in a wide class of complex systems, and there is some evidence that cycles of renewal and collapse occur at distinct spatial and temporal scales.
- Cross-scale linkages are critical to system structure. Panarchy predicts the existence of cases where small-scale variables control system dynamics. Confirming evidence has been observed for contagious processes, e.g., pest outbreaks and wildfire. There is also some empirical support for the conjecture that cross-scale distribution of system functions is critical to maintaining system
4.3.2. The Concept of Resilience Evolved along with the Understanding of CDS
4.4. Implications for Policy and Management
4.4.1. Stochastic Risk in Newtonian Systems
4.4.2. Complex Dynamic Systems, Phase 1
4.4.3. Complex Dynamic Systems, Phase 2
4.5. Can SS Be a Comprehensive Sustainability Program?
4.6. SS as Safety
5. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Randall, A. How Strong Sustainability Became Safety. Sustainability 2022, 14, 4578. https://doi.org/10.3390/su14084578
Randall A. How Strong Sustainability Became Safety. Sustainability. 2022; 14(8):4578. https://doi.org/10.3390/su14084578
Chicago/Turabian StyleRandall, Alan. 2022. "How Strong Sustainability Became Safety" Sustainability 14, no. 8: 4578. https://doi.org/10.3390/su14084578