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We present a model of the optimal timing of a large-scale habitat restoration project. The model is a dynamic benefit optimization that includes ecosystem costs caused by the presence of a large dam. We use a single stochastic variable to incorporate two sources of uncertainty: uncertainty about how ecosystem costs will evolve over time and the possibility of the ecosystem jumping to an undesirable state. We use our model to illustrate two main results. First, variability in ecosystem costs creates an incentive to delay a project intended to restore ecosystem health. The uncertainty regarding ecosystem costs creates an option value to waiting to invest in restoration at a later date. Second, the possibility of jumping to an irreversible and unacceptably bad ecosystem state (such as species extinction) creates an incentive to hasten restoration. These results formalize the countervailing incentives faced by policy makers when multiple uncertainties and irreversibilities are present in managed ecosystems.
Cameron Speir; Sam Pittman; David Tomberlin. Uncertainty, Irreversibility and the Optimal Timing of Large-Scale Investments in Protected Species Habitat Restoration. Frontiers in Marine Science 2015, 2, 1 .
AMA StyleCameron Speir, Sam Pittman, David Tomberlin. Uncertainty, Irreversibility and the Optimal Timing of Large-Scale Investments in Protected Species Habitat Restoration. Frontiers in Marine Science. 2015; 2 ():1.
Chicago/Turabian StyleCameron Speir; Sam Pittman; David Tomberlin. 2015. "Uncertainty, Irreversibility and the Optimal Timing of Large-Scale Investments in Protected Species Habitat Restoration." Frontiers in Marine Science 2, no. : 1.
This paper examines the extent to which there are differential incentives that motivate the adoption of environmental management practices (EMPs) and pollution prevention (P2) methods. We analyze the role of internal drivers such as managerial attitudes towards the environment and external pressures using both observed characteristics of facilities and perceived pressures. We estimate a structural equation model using survey data from facilities in Oregon that involves simultaneous estimation of the latent dependent and explanatory variables and the two regression equations explaining adoption behavior of EMPs and P2. We find that perceived regulatory pressures and managerial attitudes have a statistically significant impact on the adoption of both EMPs and P2 practices, while market pressures were significant in influencing the adoption of EMPs but not P2 methods. Furthermore; we find that both external regulatory pressures and internal managerial attitudes had a larger impact in motivating adoption by facilities that did not view environmental issues as being a significant concern as compared to facilities that did.
Madhu Khanna; Cameron Speir. Motivations for Proactive Environmental Management. Sustainability 2013, 5, 2664 -2692.
AMA StyleMadhu Khanna, Cameron Speir. Motivations for Proactive Environmental Management. Sustainability. 2013; 5 (6):2664-2692.
Chicago/Turabian StyleMadhu Khanna; Cameron Speir. 2013. "Motivations for Proactive Environmental Management." Sustainability 5, no. 6: 2664-2692.