990 resultados para habitat maps


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Our experience suggests trained community voluteers can collect reliable habitat data that can be used to ground-truth habitat maps in a cost effective- manner. Without a basic understanding of the delineation of subtidal habitats, marine ecosystems cannot be managed effectively, and importantly the effects of climate change, protection or other human impacts cannot begin to be predicted

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The effective management of our marine ecosystems requires the capability to identify, characterise and predict the distribution of benthic biological communities within the overall seascape architecture. The rapid expansion of seabed mapping studies has seen an increase in the application of automated classification techniques to efficiently map benthic habitats, and the need of techniques to assess confidence of model outputs. We use towed video observations and 11 seafloor complexity variables derived from multibeam echosounder (MBES) bathymetry and backscatter to predict the distribution of 8 dominant benthic biological communities in a 54 km2 site, off the central coast of Victoria, Australia. The same training and evaluation datasets were used to compare the accuracies of a Maximum Likelihood Classifier (MLC) and two new generation decision tree methods, QUEST (Quick Unbiased Efficient Statistical Tree) and CRUISE (Classification Rule with Unbiased Interaction Selection and Estimation), for predicting dominant biological communities. The QUEST classifier produced significantly better results than CRUISE and MLC model runs, with an overall accuracy of 80% (Kappa 0.75). We found that the level of accuracy with the size of training set varies for different algorithms. The QUEST results generally increased in a linear fashion, CRUISE performed well with smaller training data sets, and MLC performed least favourably overall, generating anomalous results with changes to training size. We also demonstrate how predicted habitat maps can provide insights into habitat spatial complexity on the continental shelf. Significant variation between patch-size and habitat types and significant correlations between patch size and depth were also observed.

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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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This dataset consists of global raster maps indicating the habitat suitability for 7 suborders of cold water octocorals (Octocorallia found deeper than 50m). Maps present a relative habitat suitability index ranging from 0 (unsuitable) to 100 (highly suitable). Two maps are provided for each suborder (Alcyoniina, Calcaxonia, Holaxonia, Scleraxonia, Sessiliflorae, Stolonifera, and Subselliflorae). A publicly accessable low resolution map (grid size 10x10 arc-minutes) and a restricted access high resolution map (grid size 30x30 arc-seconds). Maps are geotiff format incorporating LZW compression to reduce file size. Please contact the corresponding author (Chris Yesson) for access to the high resolution data.

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Repeatable and accurate seagrass mapping is required for understanding seagrass ecology and supporting management decisions. For shallow (< 5 m) seagrass habitats, these maps can be created by integrating high spatial resolution imagery with field survey data. Field survey data for seagrass is often collected via snorkelling or diving. However, these methods are limited by environmental and safety considerations. Autonomous Underwater Vehicles (AUVs) are used increasingly to collect field data for habitat mapping, albeit mostly in deeper waters (>20 m). Here we demonstrate and evaluate the use and potential advantages of AUV field data collection for calibration and validation of seagrass habitat mapping of shallow waters (< 5 m), from multispectral satellite imagery. The study was conducted in the seagrass habitats of the Eastern Banks (142 km2), Moreton Bay, Australia. In the field, georeferenced photos of the seagrass were collected along transects via snorkelling or an AUV. Photos from both collection methods were analysed manually for seagrass species composition and then used as calibration and validation data to map seagrass using an established semi-automated object based mapping routine. A comparison of the relative advantages and disadvantages of AUV and snorkeller collected field data sets and their influence on the mapping routine was conducted. AUV data collection was more consistent, repeatable and safer in comparison to snorkeller transects. Inclusion of deeper water AUV data resulted in mapping of a larger extent of seagrass (~7 km2, 5 % of study area) in the deeper waters of the site. Although overall map accuracies did not differ considerably, inclusion of the AUV data from deeper water transects corrected errors in seagrass mapped at depths to 5 m, but where the bottom is visible on satellite imagery. Our results demonstrate that further development of AUV technology is justified for the monitoring of seagrass habitats in ongoing management programs.

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Without knowledge of basic seafloor characteristics, the ability to address any number of critical marine and/or coastal management issues is diminished. For example, management and conservation of essential fish habitat (EFH), a requirement mandated by federally guided fishery management plans (FMPs), requires among other things a description of habitats for federally managed species. Although the list of attributes important to habitat are numerous, the ability to efficiently and effectively describe many, and especially at the scales required, does not exist with the tools currently available. However, several characteristics of seafloor morphology are readily obtainable at multiple scales and can serve as useful descriptors of habitat. Recent advancements in acoustic technology, such as multibeam echosounding (MBES), can provide remote indication of surficial sediment properties such as texture, hardness, or roughness, and further permit highly detailed renderings of seafloor morphology. With acoustic-based surveys providing a relatively efficient method for data acquisition, there exists a need for efficient and reproducible automated segmentation routines to process the data. Using MBES data collected by the Olympic Coast National Marine Sanctuary (OCNMS), and through a contracted seafloor survey, we expanded on the techniques of Cutter et al. (2003) to describe an objective repeatable process that uses parameterized local Fourier histogram (LFH) texture features to automate segmentation of surficial sediments from acoustic imagery using a maximum likelihood decision rule. Sonar signatures and classification performance were evaluated using video imagery obtained from a towed camera sled. Segmented raster images were converted to polygon features and attributed using a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999) for use in a geographical information system (GIS). (PDF contains 41 pages.)

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Determinar áreas de vida tem sido um tema amplamente discutido em trabalhos que procuram entender a relação da espécie estudada com as características de seu habitat. A Baía de Guanabara abriga uma população residente de botos-cinza (Sotalia guianensis) e o objetivo do presente estudo foi analisar o uso espacial de Sotalia guianensis, na Baía de Guanabara (RJ), entre 2002 e 2012. Um total de 204 dias de coleta foi analisado e 902 pontos selecionados para serem gerados os mapas de distribuição. A baía foi dividida em quatro subáreas e a diferença no esforço entre cada uma não ultrapassou 16%. O método Kernel Density foi utilizado nas análises para estimativa e interpretação do uso do habitat pelos grupos de botos-cinza. A interpretação das áreas de concentração da população também foi feita a partir de células (grids) de 1,5km x 1,5km com posterior aplicação do índice de sobreposição de nicho de Pianka. As profundidades utilizadas por S. guianensis não apresentaram variações significativas ao longo do período de estudo (p = 0,531). As áreas utilizadas durante o período de 2002/2004 foram estimadas em 79,4 km com áreas de concentração de 19,4 km. Os períodos de 2008/2010 e 2010/2012 apresentaram áreas de uso estimadas em um total de 51,4 e 58,9 km, respectivamente e áreas de concentração com 10,8 e 10,4 km, respectivamente. As áreas utilizadas envolveram regiões que se estendem por todo o canal central e região nordeste da Baía de Guanabara, onde também está localizada a Área de Proteção Ambiental de Guapimirim. Apesar disso, a área de vida da população, assim como suas áreas de concentração, diminuiu gradativamente ao longo dos anos, especialmente no entorno da Ilha de Paquetá e centro-sul do canal central. Grupos com mais de 10 indivíduos e grupos na classe ≥ 25% de filhotes em sua composição, evidenciaram reduções de mais de 60% no tamanho das áreas utilizadas. A população de botos-cinza vem decrescendo rapidamente nos últimos anos, além de interagir diariamente com fontes perturbadoras, sendo estas possíveis causas da redução do uso do habitat da Baía de Guanabara. Por esse motivo, os resultados apresentados são de fundamental importância para a conservação desta população já que representam consequências da interação em longo prazo com um ambiente costeiro altamente impactado pela ação antrópica.

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Fish-habitat associations were examined at three spatial scales in Monterey Bay, California, to determine how benthic habitats and landscape configuration have structured deepwater demersal fish assemblages. Fish counts and habitat variables were quantified by using observer and video data collected from a submersible. Fish responded to benthic habitats at scales ranging from cm’s to km’s. At broad-scales (km’s), habitat strata classified from acoustic maps were a strong predictor of fish assemblage composition. At intermediate-scales (m’s−100 m’s), fish species were associated with specific substratum patch types. At fine-scales (<1 m), microhabitat associations revealed differing degrees of microhabitat specificity, and for some species revealed niche separation within patches. The use of habitat characteristics in ecosystembased management, particularly as a surrogate for species distributions, will depend on resolving fish-habitat associations and habitat complexity over multiple scales.

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Range overlap patterns were observed in a dataset of 10,446 expert-derived marine species distribution maps, including 8,295 coastal fishes, 1,212 invertebrates (crustaceans and molluscs), 820 reef-building corals, 50 seagrasses and 69 mangroves. Distributions of tropical Indo-Pacific shore fishes revealed a concentration of species richness in the northern apex and central region of the Coral Triangle epicenter of marine biodiversity. This pattern was supported by distributions of invertebrates and habitat-forming primary producers. Habitat availability, heterogeneity and sea surface temperatures were highly correlated with species richness across spatial grains ranging from 23,000 to 5,100,000 km2 with and without correction for autocorrelation. The consistent retention of habitat variables in our predictive models supports the area of refuge hypothesis which posits reduced extinction rates in the Coral Triangle. This does not preclude support for a center of origin hypothesis that suggests increased speciation in the region may contribute to species richness. In addition, consistent retention of sea surface temperatures in models suggests that available kinetic energy may also be an important factor in shaping patterns of marine species richness. Kinetic energy may hasten rates of both extinction and speciation. The position of the Indo-Pacific Warm Pool to the east of the Coral Triangle in central Oceania and a pattern of increasing species richness from this region into the central and northern parts of the Coral Triangle suggests peripheral speciation with enhanced survival in the cooler parts of the Coral Triangle that also have highly concentrated available habitat. These results indicate that conservation of habitat availability and heterogeneity is important to reduce extinction and that changes in sea surface temperatures may influence the evolutionary potential of the region.

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The United States Coral Reef Task Force (USCRTF) was established in 1998 by Presidential Executive Order 13089 to lead U.S. efforts to preserve and protect coral reef ecosystems. Current, accurate, and consistent maps greatly enhance efforts to preserve and manage coral reef ecosystems. With comprehensive maps and habitat assessments, coral reef managers can be more effective in designing and implementing a variety of conservation measures, including: • Long-term monitoring programs with accurate baselines from which to track changes; • Place-based conservation measures such as marine protected areas (MPAs); and • Targeted research to better understand the oceanographic and ecological processes affecting coral reef ecosystem health. The National Oceanic and Atmospheric Administration’s (NOAA) National Ocean Service (NOS) is tasked with leading the coral ecosystem mapping element of the U.S. Coral Reef Task Force (CRTF) under the authority of the Presidential Executive Order 13089 to map and manage the coral reefs of the United States.

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Black-and-white snub-nosed monkeys (Rhinopithecus bieti) are endemic to the Trans-Himalayas in Northwest Yunnan and Southeast Tibet between the upper Yangtze and Mekong Rivers. Based on field surveys and previous reports, we identified the dark-coniferous forest, the mixed coniferous and broadleaf forest, and oak patches as suitable habitats (SH) for the monkeys. Summer grazing lands (SGL), which were made by local people cutting and burning the dark-coniferous forest at the high altitude belt, replaced SH. To have a general view of the status of the SH in Yunnan, we estimated the areas of SH and SGL from satellite images in 1997, and compared with areas estimated from aerial photo-based maps (ca. 1958). The work resulted in: 1) the area of SH was 4,169 km(2) in 1997; 2) SGL was 1,923 km(2); 3) during the past 40 years, the area of SH decreased by 31% (1,887 km(2)), and SGL increased by 204% (1,291 km(2)); and 4) the mean size of forest patches decreased from 15.6 to 5.4 km(2). In addition, the area of SGL is positively correlated to local human population (R-2 greater than or equal to0.53), implying that the reduction and fragmentation of habitat for Rhinopithecus bieti is a result of population growth of humans, who mostly employ traditional modes of production. Only 11 monkey groups remained in the changing habitat. Considering that forests at lower elevation were also encroached upon by farmlands in a similar way, the forest ecosystem is highly threatened. The destruction will continue unless there is a change in the mode of production in the region.

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Joern Fischer, David B. Lindermayer, and Ioan Fazey (2004). Appreciating Ecological Complexity: Habitat Contours as a Conceptual Landscape Model. Conservation Biology, 18 (5)pp.1245-1253 RAE2008

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The oceanographic drivers of marine vertebrate habitat use are poorly understood yet fundamental to our knowledge of marine ecosystem functioning. Here, we use composite front mapping and high-resolution GPS tracking to determine the significance of mesoscale oceanographic fronts as physical drivers of foraging habitat selection in northern gannets Morus bassanus. We tracked 66 breeding gannets from a Celtic Sea colony over 2 years and used residence time to identify area-restricted search (ARS) behaviour. Composite front maps identified thermal and chlorophyll-a mesoscale fronts at two different temporal scales—(i) contemporaneous fronts and (ii) seasonally persistent frontal zones. Using generalized additive models (GAMs), with generalized estimating equations (GEE-GAMs) to account for serial autocorrelation in tracking data, we found that gannets do not adjust their behaviour in response to contemporaneous fronts. However, ARS was more likely to occur within spatially predictable, seasonally persistent frontal zones (GAMs). Our results provide proof of concept that composite front mapping is a useful tool for studying the influence of oceanographic features on animal movements. Moreover, we highlight that frontal persistence is a crucial element of the formation of pelagic foraging hotspots for mobile marine vertebrates.

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Dissertação de Mestrado, Estudos Integrados dos Oceanos, 25 de Março de 2013, Universidade dos Açores.

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Tese de Doutoramento, Ciências do Mar (Biologia Marinha)