Collaborators:
Charles Sims (University of Tennessee)
David Finnoff (University of Wyoming)
Alan Hastings (University of California, Davis)
We consider the case where a species provides a flow of economic benefits, is threatened by possible extinction, and is being considered for addition to the Endangered Species List. Listing the species as endangered is costly but increases the flow of social benefits and reduces the likelihood of extinction. If the species recovers sufficiently, is more abundant than initial estimates, or less valuable than previously thought, additional costs can be incurred to subsequently delist the species. By treating listing and delisting as a pair of linked investment options, we show that delisting is difficult to justify economically. We also illustrate that listing decisions are more influenced by biological sources of uncertainty while economic uncertainty is more influential in delisting decisions. Biological sources of uncertainty may cause species most in need of protection to be passed over in favor of more stable species that represent a “sure bet” for species preservation.
Collaborators:
Edward Barbier (University of Wyoming)
Stuart Hamilton (Salisbury University)
Mangrove forests reduce the damaging effects of cyclones through their ability to attenuate storm surge waves and buffer winds. An emerging literature has sought to quantify the coastal effects of cyclone exposure on economic activity but has not captured if these adverse effects are attenuated by the presence of coastal wetlands. We examine mangrove storm protection services by synthesizing global geospatial datasets on economic development, cyclones paths, topography and mangrove forests. We exploit sub-provincial and time-varying data to identify a causal link between cyclone exposure and economic growth. Cyclone-exposed areas receive a subsequent 2.2% growth reduction without evidence of returning to trend. Consistent with a growing literature on optimal adaptation theory, historically cyclone-prone areas appear better able to endure exposure. Higher elevation and increased width of mangrove forests attenuate adverse growth effects. Post-disaster growth is stimulated by 0.1% for every 10 meters of elevation and 0.4% for every kilometre of seaward mangrove forests. We estimate that mangrove forests continue to recede annually by approximately 0.28 meters per km width in cyclone years and 1.06 meters per km width in non-cyclone years. Suspected storm disruption of mangrove-conversion activities curtailed mangrove losses by an estimated 12.7 percentage points or 86,000 ha. Policy interventions may consider targeting mangrove conservation in particularly low-lying areas without a natural topographic protection from tropical cyclones. Climate change predictions of decreased storm frequency and increased storm intensity risk increasing the natural rate of mangrove conversion by creating longer windows of uninterrupted conversion activity.
Collaborators:
David Aadland (University of Wyoming)
David Finnoff (University of Wyoming)
Charles Sims (University of Tennessee)
This paper examines optimal wildlife management in a spatial predator-prey model. The model is motivated by the spatiotemporal dynamics between elk, wolves, hunters and cattle ranchers in the Greater Yellowstone Ecosystem (GYE). Wildlife managers set hunting rates for elk and wolves to maximize the stream of ecosystem services derived from the GYE over time. The management component of the model considers tradeoffs between tourism, hunting, and cattle grazing currently facing wildlife managers. The predator-prey component of the model incorporates intraspecific competition and spatially explicit predation risk calibrated to the GYE. Contrary to a recent judicial ruling that has placed a moratorium on hunting wolves in Wyoming, optimal management within our model calls for more aggressive wolf hunting outside of Yellowstone National Park (YNP). We also find that a more equitable distribution of ecosystem service provisioning across the U.S. states surrounding YNP can be achieved with only modest losses in welfare.
Collaborators:
Teevrat Garg (Columbia University)
Evan Plous (London School of Economics)
Stuart Hamilton (Salisbury University)
John Talbot (Eastern Shore Regional GIS Cooperative)
Waterborne diseases are the leading cause of mortality in developing countries. We emphasize a previously ignored cause of diarrhea- upstream river bathing. Using newly constructed data on upstream-downstream hydrological linkages along with village census panel data in Indonesia, we find that upstream river bathing can explain as many as 2,180 diarrheal deaths each year. Our results, which are net of avoidance behavior, show no effect of trash disposal on diarrheal infections. Furthermore we find that individuals engage in avoidance behavior in response to trash disposal (visible pollutants) but not river bathing (invisible pollutants). We conduct policy simulations to show that targeting upstream individuals could generate substantial environmental and health savings relative to targeting downstream individuals. This provides a potential roadmap for low- and middle-income countries with limited resources for enforcement of water pollution.
Collaborators:
Katherine Lee (University of Wyoming)
Leticia Varelas (Oregon State University)
Brad Parry (University of Wyoming)
Jason Shogren (University of Wyoming)
Climate change mitigation is a global public good. The United Nations’ Conference of the Parties (COP) is designed to facilitate the global community’s voluntary contributions to reduce the possibility of crossing a global climate threshold. The challenge rests in getting parties to contribute to risk reduction and not free ride. Two realities dominate the COP agenda--domestic politics of participants and use of mitigation thresholds (e.g., 1990 emission levels by 2020). Herein we show that if the COP instead focused on the scale economies that arise from “working together” (i.e., decreasing marginal costs of commitment), voluntary contributions increase significantly regardless of domestic constraints and threshold targets. We demonstrate this result in a unique real-time puzzle-public goods experiment. Each player decides how much to contribute based on real-time effort in assembling a 25-piece jigsaw puzzle.
In contrast to the standard public goods experiment, our real-time puzzle experiment captures (1) climate policy friction in domestic politics, and (2) how decreasing marginal costs of commitment affect overall contribution. We proxy domestic constraints by each person’s innate ability to assemble the puzzle, which we define as his or her average product of effort. The marginal cost of commitment decreases as the puzzle is completed because the most work is required to make the first connection, when the pool of unconnected pieces is largest, and declines until the last connection is made. We find that commitment becoming less costly over time, not an individual’s relative ability or the practicality of meeting a group threshold, is the primary driver of overall contribution. Our results suggest the COP should bring the decreasing costs of contribution, not the total emission reductions needed, to the forefront. This strategy elicits higher contribution among even those countries with the most stringent domestic political constraints.
Collaborators:
David Finnoff (University of Wyoming)
Bioeconomic models routinely highlight feedback loops in jointly determined ecological and economic systems. Ecological systems provide benefits, or ecosystem services, to humans and human actions influence the provisioning of those services. To analyze tradeoffs in management, these services are often combined in a welfare function. Simplifying assumptions, designed to preserve model tractability, are common. These assumptions, in some cases, limit the scope of the resulting policy recommendations. We show that analytical tractability can be preserved and policy recommendations improved when finer ecological detail is employed in the specification of ecosystem services. Using a game-theoretic approach, an application of this concept is made by modeling three foundations of the behavioral ecology of wolves: refuge-seeking behavior, optimal foraging group size and territoriality. These behavioral patterns allow us to predict the density of wolves within and across management jurisdictions, which enables us to specify visitor congestion effects on public land, frequency of wildlife viewing, harvest success rates, the number of recreation days within a harvest season and harvest season length. This approach makes a notable contribution by examining management tradeoffs not only between but also within competing consumptive and non-consumptive ecosystem services.
Collaborators:
Edward Barbier (University of Wyoming)
We modify an endogenous growth model to allow for households' differential access to markets. Such local production spillovers highlight a new dimension of inequality arising through geographic remoteness and predicts divergent growth patterns among countries with poorly market-integrated households. The model is tested using an instrumental variables approach that takes advantage of the relationship between market accessibility and exogenous geographic features of the landscape as well as spatial data derived from a unique global dataset characterizing country-level market accessibility distributions. We find evidence that production spillovers diminish concavely across space before tapering off convexly in remote areas. This result suggests that the marginal household exhibiting production spillovers is located approximately five hours from the nearest market center. The policy implications are that governments could adopt pro-growth inequality-reducing policies using targeted infrastructural investments, relocation subsidies or income redistribution mechanisms. Based on our spillover threshold estimates, these policies would be access-equality enhancing for 5.1 billion people globally and access-equality reducing for 825 million people globally. We also present findings that growth divergence occurs among countries with geographically less pervasive markets. This outcome may explain why wealthier nations exhibit divergent growth paths relative to poorer nations.
Collaborators:
Yuanhao Li (Norwegian School of Economics)
David Finnoff (University of Wyoming)
Jason Shogren (University of Wyoming)
The red wolf (Canis rufus), a gray wolf-coyote hybrid species, was declared endangered in 1967 and extinct in the wild in 1980. Captive populations were reintroduced in 1987 launching a long-standing recovery effort. Today, approximately 50 to 75 wild red wolves populate five counties in eastern North Carolina constituting the world’s only wild red wolf population. Habitat loss spurred a westward migration of the population onto private agricultural lands without which population recovery would be infeasible. Successful recovery is also threatened by interbreeding, or hybridization, with local coyote populations, which jeopardizes the species’ genetic distinctiveness and will remain a concern until recovery is complete. Hybridization is prevented by sterilizing a "placeholder" coyote population that defends a buffer territory between fertile coyotes and red wolves accounting for a significant portion of the recovery budget. The spatial pattern of red wolf recolonization, arising from private agricultural land retirement choices, therefore influences species recovery and recovery costs. The policy problem is to incentivize private agricultural landholders to voluntarily modify their land to accommodate the growing population while financing an anti-hybridization program that is increasingly costly in habitat fragmentation.
Landowner incentive programs are common, often voluntary and pay a fixed rental rate on retired parcels of land. The fixed payment structure does not reward the added benefit that accompanies interconnected habitat. The agglomeration bonus is an incentive program that rewards the added value of contiguous habitat with a one-time bonus on adjacent retired parcels. The agglomeration design is vulnerable to overcompensating "green" landholders and undercompensating "brown" landholders because rental rates and bonus payments are fixed. An alternative and potentially cost-effective approach is to target landholders spatially using payments realized through a reverse auction that ensures contiguity is achieved. Both the agglomeration and spatial targeting mechanisms attempt to provide least-cost contiguous habitat. We expand this line of work by recognizing wildlife agencies choose between (i) reuniting fragmented habitat for species recovery and (ii) implementing costly conservation methods to foster species recovery in fragmented areas.