The deep sea is the largest ecosystem on the planet, comprising more than 90% of the volume that life can inhabit, yet it is the least explored biome in the world. The deep sea includes the benthos, which makes up 91.5 % of all the seafloor globally, and the water column deeper than 200 meters. It hosts a wealth of ecosystems including deep-sea vents, seamount coral gardens, abyssal plains, high-productivity whale falls, and life even in the deepest trenches. We now understand that all of these ecosystems host a variety of habitats, each with their own ecology and unique species. These ecosystems and habitats- and their associated biodiversity- provide essential ecosystem services such as carbon sequestration, nutrient regeneration, microbial processes detoxification, fisheries provisioning, and many others. However, despite the uniqueness of these ecosystems and the importance of the services they provide, we still know far less about them than we do about their shallow water and terrestrial counterparts. In this dissertation, I contribute new insights about the patterns of biodiversity in the Pacific Ocean across a large geographic area, and across a wide range of depths. To that end, in Chapter 1, I have used one of the largest ocean exploration datasets to look for patterns of the abundance and diversity across the most common benthic invertebrate families found on Pacific seamounts: Anthozoa, Porifera, and Echinodermata across the Central and Western Pacific. In addition to quantifying the diversity and abundance of known taxa, I also documented patterns of as-of-yet unidentified taxa by region, depth, and deepwater feature (seamount shape). Building on patterns associated with seamount shape that were described in Chapter 2, I focused on the effect of seamount shape on the diversity and abundance of deep-sea coral communities in Chapter 3. The analysis presented in Chapter 3 provides strong support for the novel hypothesis that gross seamount morphology is a significant driver of community composition. In Chapter 4, I focused on a single seamount to investigate biodiversity and abundance of coral and sponge taxa on a finer spatial scale, examining the role of direction (N, S, E, W) on different flanks of a single equatorial seamount. This analysis yielded interesting consistent patterns of zonation on all sides of the seamount in terms of depth, but with differences in abundance patterns on each flank for individual taxa. Finally, in Chapter 5, I took a global perspective to investigate gaps in deepwater data, with the goal of determining what regions need further exploration to conclusively determine patterns of deep-sea biodiversity, which will be critical for determining the health of deepwater ecosystems under climate change conditions with increased exploitation pressure and cooccuring with increased conservation efforts. Merging Ocean Biogeographic Information System (OBIS) records with the largest collection of deep submergence dive records ever collected, I used proposed biogeographic provinces schema to identify areas with the least supporting data. Additionally, I coupled records from OBIS with climate change projections to identify the areas with the fewest number of biodiversity records that are likely to change the fastest under different IPCC projections. These areas of low number of records and high likelihood of change by the end of the century should become priority targets for future exploration. Taken together, this dissertation provides valuable insights and generates new hypotheses about patterns and drivers of deep-sea biodiversity, and puts forth recommendations for future research and exploration efforts.

The diploma thesis deals with the development of a software library for aggregating data from electricity meters and sending data to a central station. The most used protocols in smart grids are described. The work deals in more detail with the most important parts of the DLMS/COSEM standard. The DLMS protocol is described, which ensures communication between clients and servers. Next, the COSEM object model is described, which specifies object modeling, for access to measuring devices, and the OBIS system, which determines the identification of data objects. The Gurux library, which specializes in intelligent meter readings, is also described. The results of the work describe the implementation and testing of a software library for aggregation of data from servers using the DLMS/COSEM protocol using the GURUX library. At the end of the work is described a series of tests that were performed using this software library.

This thesis is focused on application development with ARM processor architecture and Linux operating system. It uses cloud hosting services to build, test and deploy applications with container-based virtualization. The application communicates with smart meters on serial buses. It stores measurements in a database. It provides access to devices and measurements in internet network.