Laura M. Kracker

Deep-Sea Benthic Footprint of the Deepwater Horizon Blowout

The Deepwater Horizon (DWH) accident in the northern Gulf of Mexico occurred on April 20, 2010 at a water depth of 1525 meters, and a deep-sea plume was detected within one month. Oil contacted and persisted in parts of the bottom of the deep-sea in the Gulf of Mexico. As part of the response to the accident, monitoring cruises were deployed in fall 2010 to measure potential impacts on the two main soft-bottom benthic invertebrate groups: macrofauna and meiofauna. Sediment was collected using a multicorer so that samples for chemical, physical and biological analyses could be taken simultaneously and analyzed using multivariate methods. The footprint of the oil spill was identified by creating a new variable with principal components analysis where the first factor was indicative of the oil spill impacts and this new variable mapped in a geographic information system to identify the area of the oil spill footprint. The most severe relative reduction of faunal abundance and diversity extended to 3 km from the wellhead in all directions covering an area about 24 km2. Moderate impacts were observed up to 17 km towards the southwest and 8.5 km towards the northeast of the wellhead, covering an area 148 km2. Benthic effects were correlated to total petroleum hydrocarbon, polycyclic aromatic hydrocarbons and barium concentrations, and distance to the wellhead; but not distance to hydrocarbon seeps. Thus, benthic effects are more likely due to the oil spill, and not natural hydrocarbon seepage. Recovery rates in the deep sea are likely to be slow, on the order of decades or longer.

The Geography of Fish: The Use of Remote Sensing and Spatial Analysis Tools in Fisheries Research

Rather than seeing the oceans as an expansive void, researchers using acoustic technologies can detect the heterogeneity of biological resources and view the marine environment as a three-dimensional landscape. Underwater remote sensing, using acoustics, provides high resolution maps of the spatial distribution of organisms in aquatic ecosystems. Analyzing the spatial pattern of species distribution within the water column and the impact of that organization on ecological processes bridges the fields of fisheries and spatial analysis. Tools and concepts familiar to geographers, such as remote sensing, GIS, and landscape ecology, contribute to the investigation of large lake and marine ecosystems.

Mapping Reef Fish and the Seascape: Using Acoustics and Spatial Modeling to Guide Coastal Management

Reef fish distributions are patchy in time and space with some coral reef habitats supporting higher densities (i.e., aggregations) of fish than others. Identifying and quantifying fish aggregations (particularly during spawning events) are often top priorities for coastal managers. However, the rapid mapping of these aggregations using conventional survey methods (e.g., non-technical SCUBA diving and remotely operated cameras) are limited by depth, visibility and time. Acoustic sensors (i.e., splitbeam and multibeam echosounders) are not constrained by these same limitations, and were used to concurrently map and quantify the location, density and size of reef fish along with seafloor structure in two, separate locations in the U.S. Virgin Islands. Reef fish aggregations were documented along the shelf edge, an ecologically important ecotone in the region. Fish were grouped into three classes according to body size, and relationships with the benthic seascape were modeled in one area using Boosted Regression Trees. These models were validated in a second area to test their predictive performance in locations where fish have not been mapped. Models predicting the density of large fish (≥29 cm) performed well (i.e., AUCu200a=u200a0.77). Water depth and standard deviation of depth were the most influential predictors at two spatial scales (100 and 300 m). Models of small (≤11 cm) and medium (12–28 cm) fish performed poorly (i.e., AUCu200a=u200a0.49 to 0.68) due to the high prevalence (45–79%) of smaller fish in both locations, and the unequal prevalence of smaller fish in the training and validation areas. Integrating acoustic sensors with spatial modeling offers a new and reliable approach to rapidly identify fish aggregations and to predict the density large fish in un-surveyed locations. This integrative approach will help coastal managers to prioritize sites, and focus their limited resources on areas that may be of higher conservation value.

Decision support framework for the prioritization of coral reefs in the U.S. Virgin Islands

Abstract The coral reef ecosystems of the U.S. Virgin Islands are some of the most intensively surveyed and threatened tropical ecosystems on earth. These coral reefs vary widely in terms of biophysical structure, seascape context, socio-economic value and exposure to threats presenting a complex challenge for resilience-based management. How and where should managers prioritize actions to maximize conservation outcomes? To meet multiple conservation objectives, a novel map-based decision-support tool was designed which synthesized large amounts of data to help managers identify and rank coral reefs according to multiple ecological qualities, ecosystem services and threats. The spatial framework integrates local expert knowledge from SCUBA divers, scientific field data and spatial models to characterize and rank priority coral reefs. With user-defined flexibility, the tool provides information to guide management processes such as risk assessments of coastal development, management of protected areas, site selection in science and monitoring design, broader marine spatial planning and community education and outreach.