983 resultados para predictive habitat mapping


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This study presents an analysis of the application of underwater video data collected for training and validating benthic habitat distribution models. Specifically, we quantify the two major sources of error pertaining to collection of this type of reference data. A theoretical spatial error budget is developed for a positioning system used to co-register video frames to their corresponding locations at the seafloor. Second, we compare interpretation variability among trained operators assessing the same video frames between times over three hierarchical levels of a benthic classification scheme. Propagated error in the positioning system described was found to be highly correlated with depth of operation and varies from 1.5m near the surface to 5.7m in 100m of water. In order of decreasing classification hierarchy, mean overall observer agreement was found to be 98% (range 6%), 82% (range 12%) and 75% (range 17%) for the 2, 4, and 6 class levels of the scheme, respectively. Patterns in between-observer variation are related to the level of detail imposed by each hierarchical level of the classification scheme, the feature of interest, and to the amount of observer experience. © 2014 Copyright © Taylor & Francis Group, LLC.

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We used ground surveys to identify breeding habitat for Whimbrel (Numenius phaeopus) in the outer Mackenzie Delta, Northwest Territories, and to test the value of high-resolution IKONOS imagery for mapping additional breeding habitat in the Delta. During ground surveys, we found Whimbrel nests (n = 28) in extensive areas of wet-sedge low-centered polygon (LCP) habitat on two islands in the Delta (Taglu and Fish islands) in 2006 and 2007. Supervised classification using spectral analysis of IKONOS imagery successfully identified additional areas of wet-sedge habitat in the region. However, ground surveys to test this classification found that many areas of wet-sedge habitat had dense shrubs, no standing water, and/or lacked polygon structure and did not support breeding Whimbrel. Visual examination of the IKONOS imagery was necessary to determine which areas exhibited LCP structure. Much lower densities of nesting Whimbrel were also found in upland habitats near wetlands. We used habitat maps developed from a combination of methods, to perform scenario analyses to estimate the potential effects of the Mackenzie Gas Project on Whimbrel habitat. Assuming effective complete habitat loss within 20 m, 50 m, or 250 m of any infrastructure or pipeline, the currently proposed pipeline development would result in loss of 8%, 12%, or 30% of existing Whimbrel habitat. If subsidence were to occur, most Whimbrel habitat could become unsuitable. If the facility is developed, follow-up surveys will be required to test these models.

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The new found ability to measure physical attributes of the marine environment at high resolution across broad spatial scales has driven the rapid evolution of benthic habitat mapping as a field in its own right. Improvement of the resolution and ecological validity of seafloor habitat distribution models has, for the most part, paralleled developments in new generations of acoustic survey tools such as multibeam echosounders. While sonar methods have been well demonstrated to provide useful proxies of the relatively static geophysical patterns that reflect distribution of benthic species and assemblages, the spatially and temporally variable influence of hydrodynamic energy on habitat distribution have been less well studied. Here we investigate the role of wave exposure on patterns of distribution of near-shore benthic habitats. A high resolution spectral wave model was developed for a 624 km2 site along Cape Otway, a major coastal feature of western Victoria, Australia. Comparison of habitat classifications implemented using the Random Forests algorithm established that significantly more accurate estimations of habitat distribution were obtained by including a fine-scale numerical wave model, extended to the seabed using linear wave theory, than by using depth and seafloor morphology information alone. Variable importance measures and map interpretation indicated that the spatial variation in wave-induced bottom orbital velocity was most influential in discriminating habitat classes containing the canopy forming kelp Ecklonia radiata, a foundation kelp species that affects biodiversity and ecological functioning on shallow reefs across temperate Australasia. We demonstrate that hydrodynamic models reflecting key environmental drivers on wave-exposed coastlines are important in accurately defining distributions of benthic habitats. This study highlights the suitability of exposure measures for predictive habitat modeling on wave-exposed coastlines and provides a basis for continuing work relating patterns of biological distribution to remotely-sensed patterns of the physical environment.

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The mapping and geospatial analysis of benthic environments are multidisciplinary tasks that have become more accessible in recent years because of advances in technology and cost reductions in survey systems. The complex relationships that exist among physical, biological, and chemical seafloor components require advanced, integrated analysis techniques to enable scientists and others to visualize patterns and, in so doing, allow inferences to be made about benthic processes. Effective mapping, analysis, and visualization of marine habitats are particularly important because the subtidal seafloor environment is not readily viewed directly by eye. Research in benthic environments relies heavily, therefore, on remote sensing techniques to collect effective data. Because many benthic scientists are not mapping professionals, they may not adequately consider the links between data collection, data analysis, and data visualization. Projects often start with clear goals, but may be hampered by the technical details and skills required for maintaining data quality through the entire process from collection through analysis and presentation. The lack of technical understanding of the entire data handling process can represent a significant impediment to success. While many benthic mapping efforts have detailed their methodology as it relates to the overall scientific goals of a project, only a few published papers and reports focus on the analysis and visualization components (Paton et al. 1997, Weihe et al. 1999, Basu and Saxena 1999, Bruce et al. 1997). In particular, the benthic mapping literature often briefly describes data collection and analysis methods, but fails to provide sufficiently detailed explanation of particular analysis techniques or display methodologies so that others can employ them. In general, such techniques are in large part guided by the data acquisition methods, which can include both aerial and water-based remote sensing methods to map the seafloor without physical disturbance, as well as physical sampling methodologies (e.g., grab or core sampling). The terms benthic mapping and benthic habitat mapping are often used synonymously to describe seafloor mapping conducted for the purpose of benthic habitat identification. There is a subtle yet important difference, however, between general benthic mapping and benthic habitat mapping. The distinction is important because it dictates the sequential analysis and visualization techniques that are employed following data collection. In this paper general seafloor mapping for identification of regional geologic features and morphology is defined as benthic mapping. Benthic habitat mapping incorporates the regional scale geologic information but also includes higher resolution surveys and analysis of biological communities to identify the biological habitats. In addition, this paper adopts the definition of habitats established by Kostylev et al. (2001) as a “spatially defined area where the physical, chemical, and biological environment is distinctly different from the surrounding environment.” (PDF contains 31 pages)

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Habitat mapping and characterization has been defined as a high-priority management issue for the Olympic Coast National Marine Sanctuary (OCNMS), especially for poorly known deep-sea habitats that may be sensitive to anthropogenic disturbance. As a result, a team of scientists from OCNMS, National Centers for Coastal Ocean Science (NCCOS), and other partnering institutions initiated a series of surveys to assess the distribution of deep-sea coral/sponge assemblages within the sanctuary and to look for evidence of potential anthropogenic impacts in these critical habitats. Initial results indicated that remotely delineating areas of hard bottom substrate through acoustic sensing could be a useful tool to increase the efficiency and success of subsequent ROV-based surveys of the associated deep-sea fauna. Accordingly, side scan sonar surveys were conducted in May 2004, June 2005, and April 2006 aboard the NOAA Ship McArthur II to: (1) obtain additional imagery of the seafloor for broader habitat-mapping coverage of sanctuary waters, and (2) help delineate suitable deep-sea coral/sponge habitat, in areas of both high and low commercial-fishing activities, to serve as sites for surveying-in more detail using an ROV on subsequent cruises. Several regions of the sea floor throughout the OCNMS were surveyed and mosaicked at 1-meter pixel resolution. Imagery from the side scan sonar mapping efforts was integrated with other complementary data from a towed camera sled, ROVs, sedimentary samples, and bathymetry records to describe geological and biological (where possible) aspects of habitat. Using a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999), we created a preliminary map of various habitat polygon features for use in a geographical information system (GIS). This report provides a description of the mapping and groundtruthing efforts as well as results of the image classification procedure for each of the areas surveyed. (PDF contains 60 pages.)

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NOAA’s Coral Reef Conservation program (CRCP) develops coral reef management priorities by bringing together various partners to better understand threats to coral reef ecosystems with the goal of conserving, protecting and restoring these resources. Place-based and ecosystem-based management approaches employed by CRCP require that spatially explicit information about benthic habitats and fish utilization are available to characterize coral reef ecosystems and set conservation priorities. To accomplish this, seafloor habitat mapping of coral reefs around the U.S. Virgin Islands (USVI) and Puerto Rico has been ongoing since 2004. In 2008, fishery acoustics surveys were added to NOAA survey missions in the USVI and Puerto Rico to assess fish distribution and abundance in relation to benthic habitats in high priority conservation areas. NOAA’s National Centers for Coastal Ocean Science (NCCOS) have developed fisheries acoustics survey capabilities onboard the NOAA ship Nancy Foster to complement the CRCP seafloor habitat mapping effort spearheaded by the Center for Coastal Monitoring and Assessment Biogeography Branch (CCMA-BB). The integration of these activities has evolved on the Nancy Foster over the three years summarized in this report. A strategy for improved operations and products has emerged over that time. Not only has the concurrent operation of multibeam and fisheries acoustics surveys been beneficial in terms of optimizing ship time and resources, this joint effort has advanced an integrated approach to characterizing bottom and mid-water habitats and the fishes associated with them. CCMA conducts multibeam surveys to systematically map and characterize coral reef ecosystems, resulting in products such as high resolution bathymetric maps, backscatter information, and benthic habitat classification maps. These products focus on benthic features and live bottom habitats associated with them. NCCOS Centers (the Center for Coastal Fisheries and Habitat Research and the Center for Coastal Environmental Health and Biomolecular Research) characterize coral reef ecosystems by using fisheries acoustics methods to capture biological information through the entire water column. Spatially-explicit information on marine resources derived from fisheries acoustics surveys, such as maps of fish density, supports marine spatial planning strategies and decision making by providing a biological metric for evaluating coral reef ecosystems and assessing impacts from pollution, fishing pressure, and climate change. Data from fisheries acoustics surveys address management needs by providing a measure of biomass in management areas, detecting spatial and temporal responses in distribution relative to natural and anthropogenic impacts, and identifying hotspots that support high fish abundance or fish aggregations. Fisheries acoustics surveys conducted alongside multibeam mapping efforts inherently couple water column data with information on benthic habitats and provide information on the heterogeneity of both benthic habitats and biota in the water column. Building on this information serves to inform resource managers regarding how fishes are organized around habitat structure and the scale at which these relationships are important. Where resource managers require place-based assessments regarding the location of critical habitats along with high abundances of fish, concurrent multibeam and fisheries acoustics surveys serve as an important tool for characterizing and prioritizing coral reef ecosystems. This report summarizes the evolution of fisheries acoustics surveys onboard the NOAA ship Nancy Foster from 2008 to 2010, in conjunction with multibeam data collection, aimed at characterizing benthic and mid-water habitats in high priority conservation areas around the USVI and Puerto Rico. It also serves as a resource for the continued development of consistent data products derived from acoustic surveys. By focusing on the activities of 2010, this report highlights the progress made to date and illustrates the potential application of fisheries data derived from acoustic surveys to the management of coral reef ecosystems.

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Sediment particle size analysis (PSA) is routinely used to support benthic macrofaunal community distribution data in habitat mapping and Ecological Status (ES) assessment. No optimal PSA Method to explain variability in multivariate macrofaunal distribution has been identified nor have the effects of changing sampling strategy been examined. Here, we use benthic macrofaunal and PSA grabs from two embayments in the south of Ireland. Four frequently used PSA Methods and two common sampling strategies are applied. A combination of laser particle sizing and wet/dry sieving without peroxide pre-treatment to remove organics was identified as the optimal Method for explaining macrofaunal distributions. ES classifications and EUNIS sediment classification were robust to changes in PSA Method. Fauna and PSA samples returned from the same grab sample significantly decreased macrofaunal variance explained by PSA and caused ES to be classified as lower. Employing the optimal PSA Method and sampling strategy will improve benthic monitoring. © 2012 Elsevier Ltd.

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In recent years, predictive habitat distribution models, derived by combining multivariate statistical analyses with Geographic Information System (GIS) technology, have been recognised for their utility in conservation planning. The size and spatial arrangement of suitable habitat can influence the long-term persistence of some faunal species. In southwestern Victoria, Australia, populations of the rare swamp antechinus (Antechinus minimus maritimus) are threatened by further fragmentation of suitable habitat. In the current study, a spatially explicit habitat suitability model was developed for A. minimus that incorporated a measure of vegetation structure. Models were generated using logistic regression with species presence or absence as the dependent variable and landscape variables, extracted from both GIS data layers and multi-spectral digital imagery, as the predictors. The most parsimonious model, based on the Akaike Information Criterion, was spatially extrapolated in the GIS. Probability of species presence was used as an index of habitat suitability. A negative association between A. minimus presence and both elevation and habitat complexity was evidenced, suggesting a preference for relatively low altitudes and a vegetation structure of low vertical complexity. The predictive performance of the selected model was shown to be high (91%), indicating a good fit of the model to the data. The proportion of the study area predicted as suitable habitat for A. minimus (Probability of occurrence greater-or-equal, slanted0.5) was 11.7%. Habitat suitability maps not only provide baseline information about the spatial arrangement of potentially suitable habitat for a species, but they also help to refine the search for other populations, making them an important conservation tool.

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Accurate estimates of fish species occurrence are important to any species’ assessments and distribution model. With increasing emphasis on nondestructive sampling, underwater video techniques are commonly used without a thorough understanding of their advantages and disadvantages. This study compared data collected from baited remote underwater stereo-video systems (stereo BRUVS) and towed-video systems to determine; (1) the differences between these video techniques in terms of fish assemblages, functional groups (i.e. pelagic carnivore, epibenthic carnivore/omnivore or herbivore) and observability (i.e. conspicuous or cryptic), and (2) what impact do these two techniques have on the interpretation of spatially-explicit, predictive models. We found stereo BRUVS and towedvideo techniques recorded very different assemblages, functional groups and observability categories across structurally complex benthic biological habitats (i.e. macroalgae dominated habitats). However, as the habitat complexity became less (e.g. seagrass and areas with no visible macro-biota) both techniques appeared to provide similar fish assemblage information. We also found considerable differences in the predicted extents of habitat suitability between the two video techniques.

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The collection includes three major data types

- Seafloor structure information: Collation of seafloor structure information (bathymetry and softness hardness) collected using multibeam sonar systems as part of the Victorian Marine Habitat Mapping Project and bathymetric light detection and ranging data (LiDAR) collected as part of the future coats program. The geographic is Victorian State waters (~1400km2 multibeam sonar & ~4000 km2 for LiDAR as of 2012

- Video information: ~800 linear kilometres of precisely georeferenced towed video data from depths of 10-100m in Victorian coastal waters. 300 baited stereo video drops in Hopkins and Discovery Bay site locations. All video has been classified to the lowest taxonomic resolution possible with the video systems employed and converted to spatial data layers in the GIS environment.

- Habitat maps: Predicted habitat models integrating seafloor structure and video information developed using classification algorithms and remote sensing technologies.

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Map comparison is a relatively uncommon practice in acoustic seabed classification to date, contrary to the field of land remote sensing, where it has been developed extensively over recent decades. The aim here is to illustrate the benefits of map comparison in the underwater realm with a case study of three maps independently describing the seabed habitats of the Te Matuku Marine Reserve (Hauraki Gulf, New Zealand). The maps are obtained from a QTC View classification of a single-beam echosounder (SBES) dataset, manual segmentation of a sidescan sonar (SSS) mosaic, and automatic classification of a backscatter dataset from a multibeam echosounder (MBES). The maps are compared using pixel-to-pixel similarity measures derived from the literature in land remote sensing. All measures agree in presenting the MBES and SSS maps as the most similar, and the SBES and SSS maps as the least similar. The results are discussed with reference to the potential of MBES backscatter as an alternative to SSS mosaic for imagery segmentation and to the potential of joint SBES–SSS survey for improved habitat mapping. Other applications of map-similarity measures in acoustic classification of the seabed are suggested.

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Here, we evaluated the potential of using bathymetric Light Detection and Ranging (LiDAR) to characterise shallow water (<30 m) benthic habitats of high energy subtidal coastal environments. Habitat classification, quantifying benthic substrata and macroalgal communities, was achieved in this study with the application of LiDAR and underwater video groundtruth data using automated classification techniques. Bathymetry and reflectance datasets were used to produce secondary terrain derivative surfaces (e.g., rugosity, aspect) that were assumed to influence benthic patterns observed. An automated decision tree classification approach using the Quick Unbiased Efficient Statistical Tree (QUEST) was applied to produce substrata, biological and canopy structure habitat maps of the study area. Error assessment indicated that habitat maps produced were primarily accurate (>70%), with varying results for the classification of individual habitat classes; for instance, producer accuracy for mixed brown algae and sediment substrata, was 74% and 93%, respectively. LiDAR was also successful for differentiating canopy structure of macroalgae communities (i.e., canopy structure classification), such as canopy forming kelp versus erect fine branching algae. In conclusion, habitat characterisation using bathymetric LiDAR provides a unique potential to collect baseline information about biological assemblages and, hence, potential reef connectivity over large areas beyond the range of direct observation. This research contributes a new perspective for assessing the structure of subtidal coastal ecosystems, providing a novel tool for the research and management of such highly dynamic marine environments. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

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L’utilizzo del Multibeam Echo sounder (MBES) in ambienti di transizione poco profondi, con condizioni ambientali complesse come la laguna di Venezia, è ancora in fase di studio e i dati biologici e sedimentologici inerenti ai canali della laguna di Venezia sono attualmente scarsi e datati in letteratura. Questo studio ha lo scopo di mappare gli habitat e gli oggetti antropici di un canale della laguna di Venezia in un intervallo di profondità tra 0.3 e 20 m (Canale San Felice) analizzando i dati batimetrici e di riflettività (backscatter) acquisiti da ISMAR-Venezia nell’ambito del progetto RITMARE. A tale scopo il fondale del canale San Felice (Venezia) è stato caratterizzato dal punto di vista geomorfologico, sedimentologico e biologico; descrivendo anche l’eventuale presenza di oggetti antropici. L’ecoscandaglio utilizzato è il Kongsberg EM2040 Dual-Compact Multibeam in grado di emettere 800 beam (400 per trasduttore) ad una frequenza massima di 400kHZ e ci ha consentito di ricavare ottimi risultati, nonostante le particolari caratteristiche degli ambienti lagunari. I dati acquisiti sono stati processati tramite il software CARIS Hydrographic information processing system (Hips) & Sips, attraverso cui è possibile applicare le correzioni di marea e velocità del suono e migliorare la qualità dei dati grezzi ricavati da MBES. I dati sono stati quindi convertiti in ESRI Grid, formato compatibile con il software ArcGIS 10.2.1 (2013) che abbiamo impiegato per le interpretazioni e per la produzione delle mappe. Tecniche di ground-truthing, basate su riprese video e prelievi di sedimento (benna Van Veen 7l), sono state utilizzate per validare il backscatter, dimostrandosi molto efficaci e soddisfacenti per poter descrivere i fondali dal punto di vista biologico e del substrato e quindi degli habitat del canale lagunare. Tutte le informazioni raccolte durante questo studio sono state organizzate all’interno di un geodatabase, realizzato per i dati relativi alla laguna di Venezia.

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Marine protection has been emphasized through global and European conventions which highlighted the need for the establishment of special areas of conservation. Classification and habitat mapping have been developed to enhance the assessment of marine environment and improve spatial and strategic planning of human activities and to help on the implementation of ecosystem based management. European Nature information System (EUNIS) is a comprehensive habitat classification system to facilitate the harmonised description and collection of habitat and biotopes that has been developed by the European Environment Agency (EEA) in collaboration with experts from institutions throughout Europe.