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Global trends in wetland degradation and loss have created an urgency to monitor wetland extent, as well as track the distribution and causes of wetland loss. Satellite imagery can be used to monitor wetlands over time, but few efforts have attempted to distinguish anthropogenic wetland loss from climate-driven variability in wetland extent. We present an approach to concurrently track land cover disturbance and inundation extent across the Mid-Atlantic region, United States, using the Landsat archive in Google Earth Engine. Disturbance was identified as a change in greenness, using a harmonic linear regression approach, or as a change in growing season brightness. Inundation extent was mapped using a modified version of the U.S. Geological Survey’s Dynamic Surface Water Extent (DSWE) algorithm. Annual (2015–2018) disturbance averaged 0.32% (1095 km2 year-1) of the study area per year and was most common in forested areas. While inundation extent showed substantial interannual variability, the co-occurrence of disturbance and declines in inundation extent represented a minority of both change types, totaling 109 km2 over the four-year period, and 186 km2, using the National Wetland Inventory dataset in place of the Landsat-derived inundation extent. When the annual products were evaluated with permitted wetland and stream fill points, 95% of the fill points were detected, with most found by the disturbance product (89%) and fewer found by the inundation decline product (25%). The results suggest that mapping inundation alone is unlikely to be adequate to find and track anthropogenic wetland loss. Alternatively, remotely tracking both disturbance and inundation can potentially focus efforts to protect, manage, and restore wetlands.

The purpose of this article is to use a case study example to demonstrate how a transparent, transdisciplinary approach to decision making allows the US Environmental Protection Agency Region III (USEPA Region III) to fulfill its decision-making responsibilities while taking critical steps toward engaging in sustainability discussions. The case study goals were to use information about environmental condition to inform staff and fiscal resource prioritization and allocation for the federal 2010 fiscal year. This article will use a select group of 3 indicators to show 1) that data are not the same as indicators, 2) the feasibility of using disparate data in the same analysis, and 3) specific discussions about indicators can lead to transdisciplinary learning, supporting more informed decision making. We show that, when used in a transdisciplinary learning process, these indicator lessons provide a stepping stone for organizations like USEPA Region III to consider sustainability as more than just a lofty, ethical concept. Instead, these kinds of organizations can more routinely and substantively address sustainability through a progression of individual decisions. We discuss how sustainability can be linked to decision making through a process that requires stakeholders to articulate and confront their values. In this process, selecting indicators and understanding what those choices imply regarding the issues that are highlighted and the population affected is part of the assessment of environmental condition, which is the focus of the case study.

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