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.

It is apparent that before emplacement of the dam gully degradation in terraces was restored by periodic alluvial deposition from river floods, but perhaps even more important is the redistribution of flood sands onto higher terraces by wind. Thus, we propose the term "restorative base-level hypothesis" to emphasize the dynamic equilibrium between gully erosion and renewed deposition, a process that remains active in Cataract Canyon but is disrupted in Grand Canyon by the presence and operation of the dam.

We developed type geomorphic settings to develop a conceptual process model for the diverse small-catchment geomorphic system in Grand Canyon. Research findings explain how streams are able to cross broad, flat terraces given a rainfall event and how they become progressively more integrated with the river. The primary channelization processes are ponding and overflow, alluvial fan progradation, and infiltration and piping, all of which contribute to nickpoint migration. An understanding of these processes was essential to building the geomorphic model.

The predictive mathematical model quantifies erosional vulnerability by applying a hypothetical rainfall event of 25 mm/hour onto a catchment above a "pristine" terrace sequence. The principal driving factor for erosion is basin area. The principal resisting factor for erosion is terrace diffusion capacity, which is a function of terrace sand cross-sectional area and infiltration capacity. Several important modifying factors are applied to the basic model to determine relative vulnerability of each terrace to gully erosion. Vulnerability of the top terrace at each catchment is plotted against the measured amount of gully erosion in that terrace, providing a base line against which progressive changes in gully depth can be easily monitored in the future.

Field studies and research show that: (1) gully erosion of terraces has been severe during the past 20 years in Grand Canyon due to unusually high precipitation; and (2) sediment deprivation coupled with the lack of large annual floods has caused a reduction in restorative (depositional) factors. Continued measurement and documentation of geomorphic processes in catchments, particularly at type geomorphic settings, will further refine and verify the predictability of the model. We conclude that beach-habitat-building flows are essential for initiating natural restorative processes and that one of the most important processes in gully mitigation may be eolian reworking of newly deposited flood sands onto higher terraces. Prior to the construction of Glen Canyon Dam, gully-deepening and river/wind depositional processes were in dynamic equilibrium, allowing the preservation of ancient cultural sites for the past several thousand years.

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.