A biological condition gradient model for historical assessment of estuarine habitat structure.

Coastal ecosystems are affected by ever-increasing natural and human pressures. Because the physical, chemical, and biological characteristics unique to estuarine ecosystems control the ways that biological resources respond to ecosystem stressors, we present a flexible and adaptable biological assessment method for estuaries. The biological condition gradient (BCG) is a scientific framework of biological response to increasing anthropogenic stress that is comprehensive and ecosystem based and evaluates environmental conditions and the status of ecosystem services in order to identify, communicate, and prioritize management action. Using existing data, we constructed the first estuarine BCG framework that examines changes in habitat structure through time. Working in a New England (U.S.) estuary with a long history of human influence, we developed an approach to define a reference level, which we described as a "minimally disturbed" range of conditions for the ecosystem, anchored by observations before 1850 AD. Like many estuaries in the U.S., the relative importance of environmental stressors changed over time, but even qualitative descriptions of the biological indicators' status provided useful information for defining condition levels. This BCG demonstrated that stressors rarely acted alone and that declines in one biological indicator influenced the declines of others. By documenting the biological responses to cumulative stressors, the BCG inherently suggests an ecosystem-based approach to management. Additionally, the BCG process initiates thinking over long time scales and can be used to inspire scientists, managers, and the public toward environmental action.

An adaptive framework for selecting environmental monitoring protocols to support ocean renewable energy development.

Offshore renewable energy developments (OREDs) are projected to become common in the United States over the next two decades. There are both a need and an opportunity to guide efforts to identify and track impacts to the marine ecosystem resulting from these installations. A monitoring framework and standardized protocols that can be applied to multiple types of ORED would streamline scientific study, management, and permitting at these sites. We propose an adaptive and reactive framework based on indicators of the likely changes to the marine ecosystem due to ORED. We developed decision trees to identify suites of impacts at two scales (demonstration and commercial) depending on energy (wind, tidal, and wave), structure (e.g., turbine), and foundation type (e.g., monopile). Impacts were categorized by ecosystem component (benthic habitat and resources, fish and fisheries, avian species, marine mammals, and sea turtles) and monitoring objectives were developed for each. We present a case study at a commercial-scale wind farm and develop a monitoring plan for this development that addresses both local and national environmental concerns. In addition, framework has provided a starting point for identifying global research needs and objectives for understanding of the potential effects of ORED on the marine environment.

Marine habitat classification for ecosystem-based management: a proposed hierarchical framework.

Creating a habitat classification and mapping system for marine and coastal ecosystems is a daunting challenge due to the complex array of habitats that shift on various spatial and temporal scales. To meet this challenge, several countries have, or are developing, national classification systems and mapping protocols for marine habitats. To be effectively applied by scientists and managers it is essential that classification systems be comprehensive and incorporate pertinent physical, geological, biological, and anthropogenic habitat characteristics. Current systems tend to provide over-simplified conceptual structures that do not capture biological habitat complexity, marginalize anthropogenic features, and remain largely untested at finer scales. We propose a multi-scale hierarchical framework with a particular focus on finer scale habitat classification levels and conceptual schematics to guide habitat studies and management decisions. A case study using published data is included to compare the proposed framework with existing schemes. The example demonstrates how the proposed framework's inclusion of user-defined variables, a combined top-down and bottom-up approach, and multi-scale hierarchical organization can facilitate examination of marine habitats and inform management decisions.