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

Evaluation of sediment profile imagery as a tool for assessing water quality in Greenwich Bay, Rhode Island, USA

The Benthic Habitat Quality (BHQ) index was used to assess habitat visible in sediment profile images (SPI) following hypoxia disturbance in a shallow (\u3c10 m) estuarine embayment in Rhode Island, USA. We tested for associations between the BHQ, SPI features and water quality over several assessment windows (1, 3, 7, 14, and 28 days prior to imaging) and at multiple dissolved oxygen (DO) thresholds (2.0 mg l-1, 2.9 mg l-1, and 4.8 mg l-1). Using categorical data analysis, we established empirical relationships between hypoxia prevalence and presence/absence of biogenic features visible in SPI. Fecal pellets, tubes, feeding pits, voids, mounds, and BHQ score were good affirmative features, meaning that their presence (or score greater than 5) indicated a high probability of good water quality. However, low sensitivity to hypoxia precluded their usefulness as indicators, and was attributed to rarity in images and to factors acting on time intervals longer than those examined, e.g. long-term organic enrichment or hypoxia. Burrow structures and the apparent redox potential discontinuity (aRPD), or oxidized layer of surface sediment, were good discriminatory features, with high sensitivity and specificity for both hypoxia and normoxia. Both were strong surrogates for water quality over multiple assessment windows and DO thresholds, and had the highest overall predictive values. We conclude that SPI images can be used to widen the spatial extent of water quality monitoring efforts by utilizing the relationships between aRPD, burrows and hypoxia prevalence. © 2010 Elsevier Ltd. All rights reserved

Toward wind farm monitoring optimization: assessment of ecological zones from marine landscapes using machine learning algorithms

Within the perspective of siting wind farms offshore of Rhode Island, USA, the State and National Environmental Agencies had requested a local marine ecological assessment, which led to an ecological zoning of the area. In view of expanding this zoning outside its limit of the test area and filling gaps in ecological zones, an effort to model those ecological zones using marine landscape or abiotic features was carried out. This study tests the accuracy of selected machine learning algorithmic models, decision tree, and random forest, for relating marine landscapes features to ecological sub-regions. Both models show to be good predictive tools with accuracy after cross validation of the order of 5–3%. Key abiotic variables to provide an accurate model were investigated. The study demonstrates the importance of the distance to coast, the sediment characteristics (fraction of clay, median size of the sediments), the hydrodynamic features, in particular not only tidal current/drag force, but also wave drag force, and finally the oceanographic characteristics such as stratification and sea surface temperature to built a good predictive model. Those findings provide some insight on the pre-monitoring effort optimization

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\u27s 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. © 2010 Springer Science+Business Media, LLC

Mapping Seafloor Sediment Distributions Using Public Geospatial Data and Machine Learning to Support Regional Offshore Renewable Energy Development

Given the rapid expansion of offshore wind development in the United States (US), the accurate mapping of benthic habitats, specifically surficial sediments, is essential for mitigating potential impacts on these valuable ecosystems. However, offshore wind development has outpaced results from environmental monitoring efforts, compelling stakeholders to rely on a limited set of public geospatial data for conducting impact assessments. The present study therefore sought to develop and evaluate a systematic workflow for generating regional-scale sediment maps using public geospatial data that may pose integration and modeling challenges. To demonstrate this approach, sediment distributions were characterized on the northeastern US continental shelf where offshore wind development has occurred since 2016. Publicly available sediment and bathymetric data in the region were processed using national classification standards and spatial tools, respectively, and integrated using a machine learning algorithm to predict sediment occurrence. Overall, this approach and the generated sediment composite effectively predicted sediment distributions in coastal areas but underperformed in offshore areas where data were either scarce or of poor quality. Despite these shortcomings, this study builds on benthic habitat mapping efforts and highlights the need for regional collaboration to standardize seafloor data collection and sharing activities for supporting offshore wind energy decisions

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

A Re-assessment of Narragansett Bay Benthic Habitat Quality Between 1988 and 2008

The first bay-wide synoptic survey of benthic habitat quality in Narragansett Bay, Rhode Island, USA, was conducted in August of 1988. Twenty years later, we revisited the same sampling locations as the original survey using similar sediment profile imagery technology and analysis tools. Like estuaries throughout the US, increased temperatures and reductions to anthropogenic nutrient inputs have cumulatively affected Narragansett Bay in the intervening 20 years. To understand how these changes may have influenced benthic organic enrichment and habitat quality, we compared the prevalence and spatial arrangement of benthic biotopes (i.e., biotic and abiotic benthic descriptions) between 1988 and 2008 surveys. Biotopes dominated by Ampelisca spp. tubiculous amphipods increased \u3efivefold between 1988 and 2008, and expanded into the more urban, anthropogenically stressed Providence River estuary. Ampelisca beds occurred at critical boundaries in organic enrichment and habitat quality in both years and indicated the quantity of organic matter reaching the benthos. In general, benthic biotopes reflect the degree of benthic-pelagic coupling and are an important link between estuarine water quality and other marine life. As estuaries globally cope with the effects of increased warming and legislated anthropogenic nutrient reductions, rapid assessments of benthic biotopes will be critical for understanding changes to whole-estuary condition as a result of these cumulative stressors