25 resultados para Information Files

em Publishing Network for Geoscientific


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Kelp forests represent a major habitat type in coastal waters worldwide and their structure and distribution is predicted to change due to global warming. Despite their ecological and economical importance, there is still a lack of reliable spatial information on their abundance and distribution. In recent years, various hydroacoustic mapping techniques for sublittoral environments evolved. However, in turbid coastal waters, such as off the island of Helgoland (Germany, North Sea), the kelp vegetation is present in shallow water depths normally excluded from hydroacoustic surveys. In this study, single beam survey data consisting of the two seafloor parameters roughness and hardness were obtained with RoxAnn from water depth between 2 and 18 m. Our primary aim was to reliably detect the kelp forest habitat with different densities and distinguish it from other vegetated zones. Five habitat classes were identified using underwater-video and were applied for classification of acoustic signatures. Subsequently, spatial prediction maps were produced via two classification approaches: Linear discriminant analysis (LDA) and manual classification routine (MC). LDA was able to distinguish dense kelp forest from other habitats (i.e. mixed seaweed vegetation, sand, and barren bedrock), but no variances in kelp density. In contrast, MC also provided information on medium dense kelp distribution which is characterized by intermediate roughness and hardness values evoked by reduced kelp abundances. The prediction maps reach accordance levels of 62% (LDA) and 68% (MC). The presence of vegetation (kelp and mixed seaweed vegetation) was determined with higher prediction abilities of 75% (LDA) and 76% (MC). Since the different habitat classes reveal acoustic signatures that strongly overlap, the manual classification method was more appropriate for separating different kelp forest densities and low-lying vegetation. It became evident that the occurrence of kelp in this area is not simply linked to water depth. Moreover, this study shows that the two seafloor parameters collected with RoxAnn are suitable indicators for the discrimination of different densely vegetated seafloor habitats in shallow environments.

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Over the last decade pockmarks have proven to be important seabed features that provide information about fluid flow on continental margins. Their formation and dynamics are still poorly constrained due to the lack of proper three dimensional imaging of their internal structure. Numerous fluid escape features provide evidence for an active fluid-flow system on the Norwegian margin, specifically in the Nyegga region. In June-July 2006 a high-resolution seismic experiment using Ocean Bottom Seismometers (OBS) was carried out to investigate the detailed 3D structure of a pockmark named G11 in the region. An array of 14 OBS was deployed across the pockmark with 1 m location accuracy. Shots fired from surface towed mini GI guns were also recorded on a near surface hydrophone streamer. Several reflectors of high amplitude and reverse polarity are observed on the profiles indicating the presence of gas. Gas hydrates were recovered with gravity cores from less than a meter below the seafloor during the cruise. Indications of gas at shallow depths in the hydrate stability field show that methane is able to escape through the water-saturated sediments in the chimney without being entirely converted into gas hydrate. An initial 2D raytraced forward model of some of the P wave data along a line running NE-SW across the G11 pockmark shows, a gradual increase in velocity between the seafloor and a gas charged zone lying at ~300 m depth below the seabed. The traveltime fit is improved if the pockmark is underlain by velocities higher than in the surrounding layer corresponding to a pipe which ascends from the gas zone, to where it terminates in the pockmark as seen in the reflection profiles. This could be due to the presence of hydrates or carbonates within the sediments.

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Studies on the impact of historical, current and future global change require very high-resolution climate data (less or equal 1km) as a basis for modelled responses, meaning that data from digital climate models generally require substantial rescaling. Another shortcoming of available datasets on past climate is that the effects of sea level rise and fall are not considered. Without such information, the study of glacial refugia or early Holocene plant and animal migration are incomplete if not impossible. Sea level at the last glacial maximum (LGM) was approximately 125m lower, creating substantial additional terrestrial area for which no current baseline data exist. Here, we introduce the development of a novel, gridded climate dataset for LGM that is both very high resolution (1km) and extends to the LGM sea and land mask. We developed two methods to extend current terrestrial precipitation and temperature data to areas between the current and LGM coastlines. The absolute interpolation error is less than 1°C and 0.5 °C for 98.9% and 87.8% of all pixels for the first two 1 arc degree distance zones. We use the change factor method with these newly assembled baseline data to downscale five global circulation models of LGM climate to a resolution of 1km for Europe. As additional variables we calculate 19 'bioclimatic' variables, which are often used in climate change impact studies on biological diversity. The new LGM climate maps are well suited for analysing refugia and migration during Holocene warming following the LGM.

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This dataset provides scaling information applicable to satellite derived coarse resolution surface soil moisture datasets following the approach by Wagner et al. (2008). It is based on ENVISAT ASAR data and can be utilized to apply the Metop ASCAT dataset (25 km) for local studies as well as to assess the representativeness of in-situ measurement sites and thus their potential for upscaling. The approach based on temporal stability (Wagner et al. 2008) consists of the assessment of the validity of the coarse resolution datasets at medium resolution (1 km, product is the so called 'scaling layer').