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  • 1
    Publication Date: 2022-07-19
    Language: English
    Type: poster , doc-type:Other
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  • 2
    Publication Date: 2022-07-19
    Description: Biological erosion is a key process for the recycling of carbonate and the formation of calcareous sediments in the oceans. Experimental studies showed that bioerosion is subject to distinct temporal variability, but previous long-term studies were restricted to tropical waters. Here, we present results from a 14-year bioerosion experiment that was carried out along the rocky limestone coast of the island of Rhodes, Greece, in the Eastern Mediterranean Sea, in order to monitor the pace at which bioerosion affects carbonate substrate and the sequence of colonisation by bioeroding organisms. Internal macrobioerosion was visualised and quantified by micro-computed tomography and computer-algorithm-based segmentation procedures. Analysis of internal macrobioerosion traces revealed a dominance of bioeroding sponges producing eight types of characteristic Entobia cavity networks, which were matched to five different clionaid sponges by spicule identification in extracted tissue. The morphology of the entobians strongly varied depending on the species of the producing sponge, its ontogenetic stage, available space, and competition by other bioeroders. An early community developed during the first 5 years of exposure with initially very low macrobioerosion rates and was followed by an intermediate stage when sponges formed large and more diverse entobians and bioerosion rates increased. After 14 years, 30 % of the block volumes were occupied by boring sponges, yielding maximum bioerosion rates of 900 g m^−2 yr^−1. A high spatial variability in macrobioerosion prohibited clear conclusions about the onset of macrobioerosion equilibrium conditions. This highlights the necessity of even longer experimental exposures and higher replication at various factor levels in order to better understand and quantify temporal patterns of macrobioerosion in marine carbonate environments.
    Language: English
    Type: article , doc-type:article
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  • 3
    Publication Date: 2022-07-19
    Language: English
    Type: poster , doc-type:Other
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  • 4
    Publication Date: 2022-07-19
    Description: Two new species of cheilostome Bryozoa are described from continental-slope habitats off Mauritania, including canyon and coldwater-coral (mound) habitats. Internal structures of both species were visualised and quantified using micro-computed tomographic (micro-CT) methods. Cellaria bafouri n. sp. is characterised by the arrangement of zooids in alternating longitudinal rows, a smooth cryptocyst, and the presence of an ooecial plate with denticles. Smittina imragueni n. sp. exhibits many similarities with Smittina cervicornis (Pallas, 1766), but differs especially in the shape and orientation of the suboral avicularium. Observations on Smittina imragueni and material labelled as Smittina cervicornis suggest that the latter represents a species group, members of which have not yet been discriminated, possibly because of high intracolony variation and marked astogenetic changes in surface morphology. Both new species are known only from the habitats where they were collected, probably reflecting the paucity of bryozoan sampling from this geographic area and depth range. Both species are able to tolerate low oxygen concentration, which is assumed to be compensated by the high nutrient supply off Mauritania. The application of micro-CT for the semiautomatic quantification of zooidal skeletal characters was successfully tested. We were able to automatically distinguish individual zooidal cavities and acquire corresponding morphological datasets. Comparing the obtained results with conventional SEM measurements allowed ascertaining the reliability of this new method. The employment of micro-CT allows the observation and quantification of previously un- seen characters that can be used in describing and differentiating species that were previously indistinguishable. Further- more, this method might help elucidate processes of colony growth and the function of individual zooids during this process.
    Language: English
    Type: article , doc-type:article
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  • 5
    Publication Date: 2022-07-19
    Language: English
    Type: article , doc-type:article
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  • 6
    Publication Date: 2022-07-19
    Description: Many natural objects contain pores and cavities that are filled with the same material that also surrounds the object. When such objects are imaged using, for example, computed tomography, the pores and cavities cannot be distinguished from the surrounding material by considering gray values and texture properties of the image. In this case, morphological operations are often used to fill the inner region. This is efficient, if the pore and cavity structures are small compared to the overall size of the object and if the object’s shape is mainly convex. If this is not the case, the segmentation might be very difficult and may result in a lot of noise. We propose the usage of ambient occlusion for the segmentation of pores and cavities. One nice property of ambient occlusion is that it generates smooth scalar fields. Due to this smoothness property, a segmentation based on those fields will result in smooth boundaries at the pore and cavity openings. This is often desired, particularly when dealing with natural objects.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
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  • 7
    Publication Date: 2022-07-19
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 8
    Publication Date: 2022-07-19
    Description: During the last decades, X-ray (micro-)computed tomography has gained increasing attention for the description of porous skeletal and shell structures of various organism groups. However, their quantitative analysis is often hampered by the difficulty to discriminate cavities and pores within the object from the surrounding region. Herein, we test the ambient occlusion (AO) algorithm and newly implemented optimisations for the segmentation of cavities (implemented in the software Amira). The segmentation accuracy is evaluated as a function of (i) changes in the ray length input variable, and (ii) the usage of AO (scalar) field and other AO-derived (scalar) fields. The results clearly indicate that the AO field itself outperforms all other AO-derived fields in terms of segmentation accuracy and robustness against variations in the ray length input variable. The newly implemented optimisations improved the AO field-based segmentation only slightly, while the segmentations based on the AO-derived fields improved considerably. Additionally, we evaluated the potential of the AO field and AO-derived fields for the separation and classification of cavities as well as skeletal structures by comparing them with commonly used distance-map-based segmentations. For this, we tested the zooid separation within a bryozoan colony, the stereom classification of an ophiuroid tooth, the separation of bioerosion traces within a marble block and the calice (central cavity)-pore separation within a dendrophyllid coral. The obtained results clearly indicate that the ideal input field depends on the three-dimensional morphology of the object of interest. The segmentations based on the AO-derived fields often provided cavity separations and skeleton classifications that were superior to or impossible to obtain with commonly used distance- map-based segmentations. The combined usage of various AO-derived fields by supervised or unsupervised segmentation algorithms might provide a promising target for future research to further improve the results for this kind of high-end data segmentation and classification. Furthermore, the application of the developed segmentation algorithm is not restricted to X-ray (micro-)computed tomographic data but may potentially be useful for the segmentation of 3D volume data from other sources.
    Language: English
    Type: article , doc-type:article
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  • 9
    Publication Date: 2022-07-19
    Description: During the last decades, X-ray (micro-)computed tomography has gained increasing attention for the description of porous skeletal and shell structures of various organism groups. However, their quantitative analysis is often hampered by the difficulty to discriminate cavities and pores within the object from the surrounding region. Herein, we test the ambient occlusion (AO) algorithm and newly implemented optimisations for the segmentation of cavities (implemented in the software Amira). The segmentation accuracy is evaluated as a function of (i) changes in the ray length input variable, and (ii) the usage of AO (scalar) field and other AO-derived (scalar) fields. The results clearly indicate that the AO field itself outperforms all other AO-derived fields in terms of segmentation accuracy and robustness against variations in the ray length input variable. The newly implemented optimisations improved the AO field-based segmentation only slightly, while the segmentations based on the AO-derived fields improved considerably. Additionally, we evaluated the potential of the AO field and AO-derived fields for the separation and classification of cavities as well as skeletal structures by comparing them with commonly used distance-map-based segmentations. For this, we tested the zooid separation within a bryozoan colony, the stereom classification of an ophiuroid tooth, the separation of bioerosion traces within a marble block and the calice (central cavity)-pore separation within a dendrophyllid coral. The obtained results clearly indicate that the ideal input field depends on the three-dimensional morphology of the object of interest. The segmentations based on the AO-derived fields often provided cavity separations and skeleton classifications that were superior to or impossible to obtain with commonly used distance- map-based segmentations. The combined usage of various AO-derived fields by supervised or unsupervised segmentation algorithms might provide a promising target for future research to further improve the results for this kind of high-end data segmentation and classification. Furthermore, the application of the developed segmentation algorithm is not restricted to X-ray (micro-)computed tomographic data but may potentially be useful for the segmentation of 3D volume data from other sources.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
    Library Location Call Number Volume/Issue/Year Availability
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  • 10
    Publication Date: 2022-07-19
    Language: English
    Type: article , doc-type:article
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