19 resultados para Habitat mapping
em Publishing Network for Geoscientific
Resumo:
The continuously influence of human impacts on the seafloor and benthic habitats demands the knowledge of clearly defined habitats to assess recent conditions and to monitor future changes. In this study, a benthic habitat dominated by sorted bedforms was mapped in 2010 using biological, sedimentological and acoustic data. This approach reveals the first interdisciplinary analysis of macrofauna communities in sorted bedforms in the German Bight. The study area covered 4 km², and was located ca. 3.5 km west of island of Sylt. Sorted bedforms formed as sinuous depressions with an east west orientation. Inside these depressions coarse sand covers the seafloor, while outside predominantly fine to medium sand was found. Based on the hydroacoustic data, two seafloor classes were identified. Acoustic class 1 was linked to coarse sand (type A) found inside these sorted bedforms, whereas acoustic class 2 was related to mainly fine to medium sands (type B). The two acoustic classes and sediment types corresponded with the macrofauna communities 1 and 2. The Aoinides paucibranchiata-Goniadella bobretzkii community on coarse sand and the Spiophanes bombyx - Magelona johnstonii community on fine sand. A transitional community 3 (Scoloplos armiger - Ophelia community), with species found in communities 1 and 2, could not be detected by hydroacoustic methods. This study showed the limits of the used acoustic methods, which were unable to detect insignificant differences in the fauna composition of sandy areas.
Resumo:
The present data set was used as a training set for a Habitat Suitability Model. It contains occurrence (presence-only) of living Lophelia pertusa reefs in the Irish continental margin, which were assembled from databases, cruise reports and publications. A total of 4423 records were inspected and quality assessed to ensure that they (1) represented confirmed living L. pertusa reefs (so excluding 2900 records of dead and isolated coral colony records); (2) were derived from sampling equipment that allows for accurate (<200 m) geo-referencing (so excluding 620 records derived mainly from trawling and dredging activities); and (3) were not duplicated. A total of 245 occurrences were retained for the analysis. Coral observations are highly clustered in regions targeted by research expeditions, which might lead to falsely inflated model evaluation measures (Veloz, 2009). Therefore, we coarsened the distribution data by deleting all but one record within grid cells of 0.02° resolution (Davies & Guinotte 2011). The remaining 53 points were subject to a spatial cross-validation process: a random presence point was chosen, grouped with its 12 closest neighbour presence points based on Euclidean distance and withheld from model training. This process was repeated for all records, resulting in 53 replicates of spatially non-overlapping sets of test (n=13) and training (n=40) data. The final 53 occurrence records were used for model training.
Resumo:
Sediment dynamics on a storm-dominated shelf (western Bay of Plenty, New Zealand) were mapped and analyzed using the newly developed multi-sensor benthic profiler MARUM NERIDIS III. An area of 60 km × 7 km between 2 and 35 m water depth was surveyed with this bottom-towed sled equipped with a high-resolution camera for continuous close-up seafloor photography and a CTD with connected turbidity sensor. Here we introduce our approach of using this multi-parameter dataset combined with sidescan sonography and sedimentological analyses to create detailed lithofacies and bedform distribution maps and to derive regional sediment transport patterns. For the assessment of sediment distribution, photographs were classified and their spatial distribution mapped out according to associated acoustic backscatter from a sidescan sonar. This provisional map was used to choose target locations for surficial sediment sampling and subsequent laboratory analysis of grain size distribution and mineralogical composition. Finally, photographic, granulometric and mineralogical facies were combined into a unified lithofacies map and corresponding stratigraphic model. Eight distinct types of lithofacies with seawards increasing grain size were discriminated and interpreted as reworked relict deposits overlain by post-transgressional fluvial sediments. The dominant transport processes in different water depths were identified based on type and orientation of bedforms, as well as bottom water turbidity and lithofacies distribution. Observed bedforms include subaquatic dunes, coarse sand ribbons and sorted bedforms of varying dimensions, which were interpreted as being initially formed by erosion. Under fair weather conditions, sediment is transported from the northwest towards the southeast by littoral drift. During storm events, a current from the southeast to the northweast is induced which is transporting sediment along the shore in up to 35 m water depth. Shorewards oriented cross-shore transport is taking place in up to 60 m water depth and is likewise initiated by storm events. Our study demonstrates how benthic photographic profiling delivers comprehensive compositional, structural and environmental information, which compares well with results obtained by traditional probing methods, but offers much higher spatial resolution while covering larger areas. Multi-sensor benthic profiling enhances the interpretability of acoustic seafloor mapping techniques and is a rapid and economic approach to seabed and habitat mapping especially in muddy to sandy facies.
Resumo:
Wind- induced exposure is one of the major forces shaping the geomorphology and biota in coastal areas. The effect of wave exposure on littoral biota is well known in marine environments (Ekebon et al., 2003; Burrows et al., 2008). In the Cabrera Archipelago National Park wave exposure has demostrated to have an effect on the spatial distribution of different stages of E.marginatus (Alvarez et al., 2010). Standarized average wave exposures during 2008 along the Cabrera Archipelago National park coast line were calculated to be applied in studies of littoral species distribution within the archipelago. Average wave exposure (or apparent wave power) was calculated for points located 50 m equidistant on the coastline following the EXA methodology (EXposure estimates for fragmented Archipelagos) (Ekebon et al., 2003). The average wave exposures were standardized from 1 to 100 (minimum and maximum in the area), showing coastal areas with different levels of mea wave exposure during the year. Input wind data (direction and intensity) from 2008 was registered at the Cabrera mooring located north of Cabrera Archipelago. Data were provided by IMEDEA (CSIC-UIB, TMMOS http://www.imedea.uib-csic.es/tmoos/boyas/). This cartography has been developed under the framework of the project EPIMHAR, funded by the National Park's Network (Spanish Ministry of Environment, Maritime and Rural Affairs, reference: 012/2007 ). Part of this work has been developed under the research programs funded by "Fons de Garantia Agrària i Pesquera de les Illes Balears (FOGAIBA)".
Resumo:
In 2014, UniDive (The University of Queensland Underwater Club) conducted an ecological assessment of the Point Lookout Dive sites for comparison with similar surveys conducted in 2001 - the PLEA project. Involvement in the project was voluntary. Members of UniDive who were marine experts conducted training for other club members who had no, or limited, experience in identifying marine organisms and mapping habitats. Since the 2001 detailed baseline study, no similar seasonal survey has been conducted. The 2014 data is particularly important given that numerous changes have taken place in relation to the management of, and potential impacts on, these reef sites. In 2009, Moreton Bay Marine Park was re-zoned, and Flat Rock was converted to a marine national park zone (Green zone) with no fishing or anchoring. In 2012, four permanent moorings were installed at Flat Rock. Additionally, the entire area was exposed to the potential effects of the 2011 and 2013 Queensland floods, including flood plumes which carried large quantities of sediment into Moreton Bay and surrounding waters. The population of South East Queensland has increased from 2.49 million in 2001 to 3.18 million in 2011 (BITRE, 2013). This rapidly expanding coastal population has increased the frequency and intensity of both commercial and recreational activities around Point Lookout dive sites (EPA 2008). Habitats were mapped using a combination of towed GPS photo transects, aerial photography and expert knowledge. This data provides georeferenced information regarding the major features of each of the Point Lookout Dive Sites.
Resumo:
The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.