In this article, I offer an institutional history of the ecosystem concept, tracing shifts in its meaning and application as it has become the key organizing principle for the Everglades restoration program in Florida. Two institutional forms are analyzed here: (1) quasi- governmental organizations, a term I use to describe interagency science collaboratives and community stakeholder organizations, and (2) government bureaucracies, which are the administrative agencies tasked with Everglades restoration planning and implementation. In analyzing these knowledge trajectories, I both document the complex networks of relations that facilitate the ecosystem’s emergence as an object of knowledge and examine the bureaucratic claims to authority that circumscribe the ecosystem’s transformation into policy.

An Adaptive Environmental Assessment and Management workshop process was used to assist Grand Canyon scientists and managers in developing conceptual and simulation models for the Colorado ecosystem affected by Glen Canyon Dam. This model examines ecosystem variables and processes at multiple scales in space and time, ranging from feet and hours for benthic algal response to diurnal flow changes, to reaches and decades for sediment storage and dynamics of long-lived native fish species. Its aim is to help screen policy options ranging from changes in hourly variation in flow allowed from Glen Canyon Dam, to major structural changes for restoration of more natural temperature regimes. It appears that we can make fairly accurate predictions about some components of ecosystem response to policy change (e.g., autochthonous primary production, insect communities, riparian vegetation, rainbow trout population), but we are moderately or grossly uncertain about others (e.g., long-term sediment storage, response of native and non-native fishes to physical habitat restoration). Further, we do not believe that existing monitoring programs are adequate to detect responses of native fishes or vegetation to anything short of gross habitat changes. Some experimental manipulations (such as controlled floods for beach/habitat- building) should proceed, but most should await development of better monitoring programs and sound temporal baseline information from those programs.

Restoration of riverine ecosystems is often stated as a management objective for regulated rivers, and floods are one of the most effective tools for accomplishing restoration. The National Re- search Council (NRC 1992) argued that ecological restoration means re- turning "an ecosystem to a close approximation of its condition prior to disturbance" and that "restoring altered, damaged, O f destroyed lakes, rivers, and wetlands is a high-priority task." Effective restoration must be based on a clear definition of the value of riverine resources to society; on scientific studies that document ecosystem status and provide an understanding of ecosystem processes and resource interactions; on scientific studies that predict, mea- sure, and monitor the effectiveness of restoration techniques; and on engineering and economic studies that evaluate societal costs and benefits of restoration.

In the case of some large rivers, restoration is not a self-evident goal. Indeed, restoration may be impossible; a more feasible goal may be rehabilitation of some ecosystem components and processes in parts of the river (Gore and Shields 1995, Kondolfand Wilcock 1996, Stanford et al. 1996). In other cases, the appropriate decision may be to do nothing. The decision to manipulate ecosystem processes and components involves not only a scientific judgment that a restored or rehabilitated condition is achievable, but also a value judgment that this condition is more desirable than the status quo. These judgments involve prioritizing different river resources, and they should be based on extensive and continuing public debate.

In this article, we examine the appropriate role of science in determining whether or not to restore or rehabilitate the Colorado River in the Grand Canyon by summarizing studies carried out by numerous agencies, universities, and consulting firms since 1983. This reach of the Colorado extends 425 km between Glen Canyon Dam and Lake Mead reservoir (Figure 1). Efforts to manipulate ecosystem processes and components in the Grand Canyon have received widespread public attention, such as the 1996 controlled flood released from Glen Canyon Dam and the proposal to drain Lake Powell reservoir.

Summary: 

Interview conducted by: Dr. Paul Hirt, Arizona State University and Jennifer Sweeney, Four East Historical Research, LLC. Glen Canyon Dam Adaptive Management Program Administrative History Project. Administered by Arizona State University Supported by a grant from the US Bureau of Reclamation.

Biography: 

Aquatic ecologist Richard "Rich" Valdez has been associated with GCDAMP (Glen Canyon Adaptive Management Program) since 1989, when he led a study on endangered humpback chub for GCES, the program's predecessor. Valdez began studying Colorado River fish in 1968, and is an expert on humpback chub and other native species. He has been associated with the environmental consulting companies BIO-WEST and SWCA for much of his career. In addition to GCDAMP, Valdez has contributed his expertise to the Upper Colorado River Endangered Fish Recovery Program and other river basin recovery efforts.

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman’s correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns.