999 resultados para Lagrangian modeling


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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., AUC = 0.77). 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., AUC = 0.49 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.

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The purpose of this project is to model seabird flock size data to provide recommendations to the Bureau of Ocean and Energy Management for offshore wind turbine placement. Our hypothesis is that ecological characteristics influence which statistical distribution will provide the best fit to seabird flock size data. To test this, seabird species can be grouped based on shared ecological traits, such as foraging mechanism or diet.

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The Charleston Gyre region is characterized by continuous series of cyclonic eddies that propagate northeastwards before decaying or coalescing with the Gulf Stream south of Cape Hatteras, NC, USA. Over 5 d, chlorophyll-a concentration, zooplankton displacement volume, and zooplankton composition and abundance changed as the eddy moved to the northeast. Surface chlorophyll-a concentration decreased, and zooplankton displacement remained unchanged as the eddy propagated. Zooplankton taxa known to be important dietary constituents of larval fish increased in concentration as the eddy propagated. The concurrent decrease in chlorophyll-a concentration and static zooplankton displacement volume can be explained by initial stimulation of chlorophyll-a concentration by upwelling and nutrient enrichment near the eddy core and to possible grazing as zooplankton with short generation times and large clutch sizes increased in concentration. The zooplankton community did not change significantly within the 5 d that the eddy was tracked, and there was no indication of succession. Mesoscale eddies of the region are dynamic habitats as eddies propagate northeastwards at varying speeds within monthly periods. The abundance of zooplankton important to the diets of larval fish indicates that the region can provide important pelagic nursery habitat for larval fish off the southeast coast of the United States. A month of feeding and growth is more than half the larval duration of most fish spawned over the continental shelf of the southeastern United States in winter.

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Moving ecosystem modeling from research to applications and operations has direct management relevance and will be integral to achieving the water quality and living resource goals of the 2010 Chesapeake Bay Executive Order. Yet despite decades of ecosystem modeling efforts of linking climate to water quality, plankton and fish, ecological models are rarely taken to the operational phase. In an effort to promote operational ecosystem modeling and ecological forecasting in Chesapeake Bay, a meeting was convened on this topic at the 2010 Chesapeake Modeling Symposium (May, 10-11). These presentations show that tremendous progress has been made over the last five years toward the development of operational ecological forecasting models, and that efforts in Chesapeake Bay are leading the way nationally. Ecological forecasts predict the impacts of chemical, biological, and physical changes on ecosystems, ecosystem components, and people. They have great potential to educate and inform not only ecosystem management, but also the outlook and opinion of the general public, for whom we manage coastal ecosystems. In the context of the Chesapeake Bay Executive Order, ecological forecasting can be used to identify favorable restoration sites, predict which sites and species will be viable under various climate scenarios, and predict the impact of a restoration project on water quality.

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Nonindigenous species (NIS) are a major threat to marine ecosystems, with possible dramatic effects on biodiversity, biological productivity, habitat structure and fisheries. The Papahānaumokuākea Marine National Monument (PMNM) has taken active steps to mitigate the threats of NIS in Northwestern Hawaiian Islands (NWHI). Of particular concern are the 13 NIS already detected in NWHI and two invasive species found among the main Hawaiian Islands, snowflake coral (Carijoa riseii) and a red alga (Hypnea musciformis). Much of the information regarding NIS in NWHI has been collected or informed by surveys using conventional SCUBA or fishing gear. These technologies have significant drawbacks. SCUBA is generally constrained to depths shallower than 40 m and several NIS of concern have been detected well below this limit (e.g., L. kasmira – 256 m) and fishing gear is highly selective. Consequently, not all habitats or species can be properly represented. Effective management of NIS requires knowledge of their spatial distribution and abundance over their entire range. Surveys which provide this requisite information can be expensive, especially in the marine environment and even more so in deepwater. Technologies which minimize costs, increase the probability of detection and are capable of satisfying multiple objectives simultaneously are desired. This report examines survey technologies, with a focus on towed camera systems (TCSs), and modeling techniques which can increase NIS detection and sampling efficiency in deepwater habitats of NWHI; thus filling a critical data gap in present datasets. A pilot study conducted in 2008 at French Frigate Shoals and Brooks Banks was used to investigate the application of TCSs for surveying NIS in habitats deeper than 40 m. Cost and data quality were assessed. Over 100 hours of video was collected, in which 124 sightings of NIS were made among benthic habitats from 20 to 250 m. Most sightings were of a single cosmopolitan species, Lutjanus kasmira, but Cephalopholis argus, and Lutjanus fulvus, were also detected. The data expand the spatial distributions of observed NIS into deepwater habitats, identify algal plain as an important habitat and complement existing data collected using SCUBA and fishing gear. The technology’s principal drawback was its inability to identify organisms of particular concern, such as Carijoa riseii and Hypnea musciformis due to inadequate camera resolution and inability to thoroughly inspect sites. To solve this issue we recommend incorporating high-resolution cameras into TCSs, or using alternative technologies, such as technical SCUBA diving or remotely operated vehicles, in place of TCSs. We compared several different survey technologies by cost and their ability to detect NIS and these results are summarized in Table 3.

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Land-based pollution is commonly identified as a major contributor to the observed deterioration of shallow-water coral reef ecosystem health. Human activity on the coastal landscape often induces nutrient enrichment, hypoxia, harmful algal blooms, toxic contamination and other stressors that have degraded the quality of coastal waters. Coral reef ecosystems throughout Puerto Rico, including Jobos Bay, are under threat from coastal land uses such as urban development, industry and agriculture. The objectives of this report were two-fold: 1. To identify potentially harmful land use activities to the benthic habitats of Jobos Bay, and 2. To describe a monitoring plan for Jobos Bay designed to assess the impacts of conservation practices implemented on the watershed. This characterization is a component of the partnership between the U.S. Department of Agriculture (USDA) and the National Oceanic and Atmospheric Administration (NOAA) established by the Conservation Effects Assessment Project (CEAP) in Jobos Bay. CEAP is a multi-agency effort to quantify the environmental benefits of conservation practices used by private landowners participating in USDA programs. The Jobos Bay watershed, located in southeastern Puerto Rico, was selected as the first tropical CEAP Special Emphasis Watershed (SEW). Both USDA and NOAA use their respective expertise in terrestrial and marine environments to model and monitor Jobos Bay resources. This report documents NOAA activities conducted in the first year of the three-year CEAP effort in Jobos Bay. Chapter 1 provides a brief overview of the project and background information on Jobos Bay and its watershed. Chapter 2 implements NOAA’s Summit to Sea approach to summarize the existing resource conditions on the watershed and in the estuary. Summit to Sea uses a GIS-based procedure that links patterns of land use in coastal watersheds to sediment and pollutant loading predictions at the interface between terrestrial and marine environments. The outcome of Summit to Sea analysis is an inventory of coastal land use and predicted pollution threats, consisting of spatial data and descriptive statistics, which allows for better management of coral reef ecosystems. Chapters 3 and 4 describe the monitoring plan to assess the ecological response to conservation practices established by USDA on the watershed. Jobos Bay is the second largest estuary in Puerto Rico, but has more than three times the shoreline of any other estuarine area on the island. It is a natural harbor protected from offshore wind and waves by a series of mangrove islands and the Punta Pozuelo peninsula. The Jobos Bay marine ecosystem includes 48 km² of mangrove, seagrass, coral reef and other habitat types that span both intertidal and subtidal areas. Mapping of Jobos Bay revealed 10 different benthic habitats of varying prevalence, and a large area of unknown bottom type covering 38% of the entire bay. Of the known benthic habitats, submerged aquatic vegetation, primarily seagrass, is the most common bottom type, covering slightly less than 30% of the bay. Mangroves are the dominant shoreline feature, while coral reefs comprise only 4% of the total benthic habitat. However, coral reefs are some of the most productive habitats found in Jobos Bay, and provide important habitat and nursery grounds for fish and invertebrates of commercial and recreational value.