ALBERT

Description: Megafauna play an important role in benthic ecosystem function and are sensitive indicators of environmental change. Non-invasive monitoring of benthic communities can be accomplished by seafloor imaging. However, manual quantification of megafauna in images is labor-intensive and therefore, this organism size class is often neglected in ecosystem studies. Automated image analysis has been proposed as a possible approach to such analysis, but the heterogeneity of megafaunal communities poses a non-trivial challenge for such automated techniques. Here, the potential of a generalized object detection architecture, referred to as iSIS (intelligent Screening of underwater Image Sequences), for the quantification of a heterogenous group of megafauna taxa is investigated. The iSIS system is tuned for a particular image sequence (i.e. a transect) using a small subset of the images, in which megafauna taxa positions were previously marked by an expert. To investigate the potential of iSIS and compare its results with those obtained from human experts, a group of eight different taxa from one camera transect of seafloor images taken at the Arctic deep-sea observatory HAUSGARTEN is used. The results show that inter-and intra-observer agreements of human experts exhibit considerable variation between the species, with a similar degree of variation apparent in the automatically derived results obtained by iSIS. Whilst some taxa (e. g. Bathycrinus stalks, Kolga hyalina, small white sea anemone) were well detected by iSIS (i.e. overall Sensitivity: 87%, overall Positive Predictive Value: 67%), some taxa such as the small sea cucumber Elpidia heckeri remain challenging, for both human observers and iSIS.

Description: Biomineralized structures and tissues are composites, containing a biologically produced organic matrix and nano- or microscale amorphous or crystalline minerals. Two main examples of organic matrices – the amino-polysaccharide chitin and the asymmetric protein collagen – are presented and discussed as the basic structural modules and organo-templates for calcium and silica biomineralization in nature. Both serve as templates, providing preferential sites for nucleation and controlling the location and orientation of mineral phases. Here, for the first time, chitin and collagen are analysed from evolutionary, structural, and functional points of view with respect to their templating properties in calcification and silicification phenomena, using both in vivo and in vitro data. It is proposed that these biopolymers be characterized as fundamental templates in biomineralization, inasmuch as they are very ancient from an evolutionary point of view, common to many species and biological systems with a global distribution. The two polymers also exhibit very similar hierarchical structural organizations, in spite of the possible alternatives they provide in chemical nature and origin. In addition, the phenomenon of multi-phase mineralization – where two minerals, amorphous and crystalline CaCO3, form from one biomolecule, chitin – is also described, analysed, and discussed for the first time.

Description: Cold-water coral reefs are known to locally enhance the diversity of deep-sea fauna as well as of microbes. Sponges are among the most diverse faunal groups in these ecosystems, and many of them host large abundances of microbes in their tissues. In this study, twelve sponge species from three cold-water coral reefs off Norway were investigated for the relationship between sponge phylogenetic classification (species and family level), as well as sponge type (high versus low microbial abundance), and the diversity of sponge-associated bacterial communities, taking also geographic location and water depth into account. Community analysis by Automated Ribosomal Intergenic Spacer Analysis (ARISA) showed that as many as 345 (79%) of the 437 different bacterial operational taxonomic units (OTUs) detected in the dataset were shared between sponges and sediments, while only 70 (16%) appeared purely sponge-associated. Furthermore, changes in bacterial community structure were significantly related to sponge species (63% of explained community variation), sponge family (52%) or sponge type (30%), whereas mesoscale geographic distances and water depth showed comparatively small effects (〈5% each). In addition, a highly significant, positive relationship between bacterial community dissimilarity and sponge phylogenetic distance was observed within the ancient family of the Geodiidae. Overall, the high diversity of sponges in cold-water coral reefs, combined with the observed sponge-related variation in bacterial community structure, support the idea that sponges represent heterogeneous, yet structured microbial habitats that contribute significantly to enhancing bacterial diversity in deep-sea ecosystems.

Description: Despite coelacanths, Latimeria chalumnae, being listed as either endangered by CITES or critically endangered by the IUCN, their population size within South Africa is unknown and still needs to be estimated. Their conservation status unfortunately excludes the use of conventional tagging to mark individual animals for a possible mark–recapture experiment. This study shows that because coelacanths have a unique spot patterning it is possible to quickly and accurately identify specific individuals photographically using computer-aided identification software. Without any manual intervention by an operator, the software accurately identified between 56 and 92% of the individuals. Indentification success increased to 100% if the operator could also manually select from other potential matching photographs. It was also shown that fish exhibiting a yaw angle not exceeding 60° could be accurately identified in photographs, although the percentage of fish correctly identified without operator-intervention decreased rapidly with increasing yaw angle. Computer-aided identification should therefore facilitate future coelacanth research as it is both efficient and accurate while also reducing potential stress on the animals observed.

Description: This study presents the first multi-scale survey of bacterial diversity in cold-water coral reefs, spanning a total of five observational levels including three spatial scales. It demonstrates that bacterial communities in cold-water coral reefs are structured by multiple factors acting at different spatial scales, which has fundamental implications for the monitoring of microbial diversity and function in those ecosystems.

Description: A new compound, jolynamine (1), was isolated from the marine brown alga Jolyna laminarioides collected from the coast of Karachi, Pakistan. In addition, four known compounds, namely saringosterol (2), loliolide (3), methyl-4-hydroxybenzoate (4) and propyl-4-hydroxybenzoate (5), were isolated for the first time from the marine brown alga Iyengaria stellata, and two known compounds, namely 3,4,5-trimethylaniline (6) and harmine (7), were isolated for the first time from the marine brown alga Melanothamnus afaqhusainii. Compound 6 is synthetically known but was isolated for the first time from a natural source. The structures of these compounds were elucidated with the help of powerful spectroscopic techniques. Furthermore, the methanolic extracts of both algae showed anti-microbial activities against various bacteria and fungi.

Description: In this paper, we empirically investigate the robustness of random forests for regression problems. We also investigate the performance of six variations of the original random forest method, all aimed at improving robustness. These variations are based on three main ideas: (1) robustify the aggregation method, (2) robustify the splitting criterion and (3) taking a robust transformation of the response. More precisely, with the first idea, we use the median (or weighted median), instead of the mean, to combine the predictions from the individual trees. With the second idea, we use least-absolute deviations from the median, instead of least-squares, as splitting criterion. With the third idea, we build the trees using the ranks of the response instead of the original values. The competing methods are compared via a simulation study with artificial data using two different types of contaminations and also with 13 real data sets. Our results show that all three ideas improve the robustness of the original random forest algorithm. However, a robust aggregation of the individual trees is generally more profitable than a robust splitting criterion.

Description: The annual winter sardine run along the South African east coast impacts the KwaZulu-Natal (KZN) coastal system in a variety of ways. These include ecological impacts, such as enrichment of a largely oligotrophic environment, competition between migrant sardine Sardinops sagax, other migrant and resident small pelagic fish species, and interactions with predators, as well as the socio-economic impacts of the sardine run on the local people. Enrichment of KZN coastal waters with organic nitrogen contained within the sardine is compared with alternative sources of nitrogen such as upwelling, river, sewage and stormwater runoff, and groundwater discharge. The sardine run appears to contribute most nitrogen to this system—96 000 t compared to 500–3 300 t for each of the other significant sources at trophic level 2, although upwelling estimates are extremely wide. Nonetheless, the majority of surviving sardine, their young and predators return southwards, suggesting that the nett export of nitrogen to KZN waters during the run is likely to be of a similar order of magnitude as that from other sources. Further, whereas the sardine supply of nitrogen is exclusively during winter, the bulk of the riverine input is in summer, thus ensuring that nitrogen supply in the region is maintained at fairly constant levels throughout the year. Competition for food between small pelagic fish is minimised by resource partitioning, but further dietary data are needed for resident species. Although interactions between sardine and top predators must exist, further studies are needed to confirm links between top predator life cycles and the sardine run. The estimated value of sardine as a tourist spectacle is compared to that from a seasonal beach-seine or boat-based purse-seine fishery for this species. Whereas the estimated value of the sardine as a tourist attraction appears substantially higher than could be derived from catching them, the small-scale beach-seine fishery itself draws tourists and also provides limited, seasonal employment opportunities.

Description: Our understanding of the fundamental regulatory roles that tyrosine phosphatases play within cells has advanced significantly in the last two decades. Out-dated ideas that tyrosine phosphatases acts solely as the “off” switch counterbalancing the action of tyrosine kinases has proved to be flawed. PTP1B is the most characterized of all the tyrosine phosphatases and it acts as a critical negative and positive regulator of numerous signaling cascades. PTP1B’s direct regulation of the insulin and the leptin receptors makes it an ideal therapeutic target for type II diabetes and obesity. Moreover, the last decade has also seen several reports establishing PTP1B as key player in cancer serving as both tumor suppressor and tumor promoter depending on the cellular context. Despite many key advances in these fields one largely ignored area is what role PTP1B may play in the modulation of immune signaling. The important recognition that PTP1B is a major negative regulator of Janus kinase – signal transducer and activator of transcription (JAK-STAT) signaling throughout evolution places it as a key link between metabolic diseases and inflammation, as well as a unique regulator between immune response and cancer. This review looks at the emergence of PTP1B through evolution, and then explore at the cell and systemic levels how it is controlled physiologically. The second half of the review will focus on the role(s) PTP1B can play in disease and in particular its involvement in metabolic syndromes and cancer. Finally we will briefly examine several novel directions in the development of PTP1B pharmacological inhibitors.

Description: Species distribution models (SDMs) are an important tool in biogeography and ecology and are widely used for both fundamental and applied research purposes. SDMs require spatially explicit information about species occurrence and environmental covariates to produce a set of rules that identify and scale the environmental space where the species was observed and that can further be used to predict the suitability of a site for the species. More spatially accurate data are increasingly available, and the number of publications on the influence of spatial inaccuracies on the performance of modelling procedures is growing exponentially. Three main sources of uncertainty are associated with the three elements of a predictive function: the dependent variable, the explanatory variables and the algorithm or function used to relate these two variables. In this study, we review how spatial uncertainties influence model accuracy and we propose some methodological issues in the application of SDMs with regard to the modelling of fundamental and realized niches of species. We distinguish two cases suitable for different types of spatial data accuracy. For modelling the realized distribution of a species, particularly for management and conservation purposes, we suggest using only accurate species occurrence data and large sample sizes. Appropriate data filtering and examination of the spatial autocorrelation in predictors should be a routine procedure to minimize the possible influence of positional uncertainty in species occurrence data. However, if the data are sparse, models of the potential distribution of species can be created using a relatively small sample size, and this can provide a generalized indication of the main regional drivers of the distribution patterns. By this means, field surveys can be targeted to discover unknown populations and species in poorly surveyed regions in order to improve the robustness of the data for later modelling of the realized distributions. Based on this review, we conclude that (1) with data that are currently available, studies performed at a resolution of 1–100 km2 are useful for hypothesizing about the environmental conditions that limit the distribution of a species and (2) incorporating coarse resolution species occurrence data in a model, despite an increase in sample size, lowers model performance.