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Estimating absence locations of a species is important in conservation biology and conservation planning. For instance, using reliable absence as much as presence information, species distribution models can enhance their performance and produce more accurate predictions of the distribution of a species. Unfortunately, estimating reliable absence locations is difficult and often requires a deep knowledge of the species’ distribution and of its abiotic and biotic environmental preferences and tolerance. In this paper, we propose a methodology to reconstruct reliable absence information from presence-only information, and the conditions that those presence-only data have to meet to make this possible. Large species occurrence data collections (otherwise called occurrence datasets) contain high quality and expert-reviewed species observation records from scientific surveys. These surveys can be used to retrieve species presence locations, but they also record places where the species in their target list were not observed. Although these absences could be simply due to sampling variation, it is possible to intersect many of these reports to estimate true absence locations, i.e. those due to habitat unsuitability or geographical hindrances. In this paper, we present a method to generate reliable absence locations of this type for marine species, using scientific surveys reports contained in the Ocean Biogeographic Information System (OBIS), an authoritative species occurrence dataset. Our method spatially aggregates information from surveys focussing on the same target species. It detects absence locations for a given species as those locations in which repeated surveys (that included the species of interest in their target list) reported information only on other species. We qualitatively demonstrate the reliability of our method using distribution records of the Atlantic cod as a case study. Additionally, we quantitatively estimate its performance using another authoritative large species occurrence dataset, the Global Biodiversity Information Facility (GBIF). We also demonstrate that our approach has higher accuracy and presents complementary behaviour with respect to another method using environmental envelopes. Our process can support species distribution models (as well as other types of models, e.g. climate change models) by providing reliable data to presence/absence approaches. It can manage regional as well as global scale scenarios and runs within a collaborative e-Infrastructure (D4Science) that publishes it as-a-Service, allowing biologists to reproduce, repeat and share experimental results.

The Census of Marine Life was a 10-year, international research effort to explore poorly known ocean habitats and conduct large-scale experimentation with new technology. The goal of Census 2010 in its mission statement was to describe what did live in the oceans, what does live in the oceans, and what will live in the ocean. Many of the findings and techniques from census research may prove valuable in making a transition, which many governments have publicly endorsed, from single-species fisheries management to more holistic ecosystem management. Census researchers sampled continental margins, mid-Atlantic ridges, ocean floor vents and seeps, and abyssal plains and polar seas and organized massive amounts of past and new information in a public online database called the Ocean Biogeographic Information System (www.iobis.org). The census described and categorized seamount biology worldwide for its vulnerability to fishing, advanced large-scale animal tracking with acoustic arrays and satellite a...

Across many scientific domains, the ability to aggregate disparate datasets enables more meaningful global analyses. Within marine biology, the Census of Marine Life served as the catalyst for such a global data aggregation effort. Under the Census framework, the Ocean Biogeographic Information System was established to coordinate an unprecedented aggregation of global marine biogeography data. The OBIS data system now contains 31.3 million observations, freely accessible through a geospatial portal. The challenges of storing, querying, disseminating, and mapping a global data collection of this complexity and magnitude are significant. In the face of declining performance and expanding feature requests, a redevelopment of the OBIS data system was undertaken. Following an Open Source philosophy, the OBIS technology stack was rebuilt using PostgreSQL, PostGIS, GeoServer and OpenLayers. This approach has markedly improved the performance and online user experience while maintaining a standards-compliant and interoperable framework. Due to the distributed nature of the project and increasing needs for storage, scalability and deployment flexibility, the entire hardware and software stack was built on a Cloud Computing environment. The flexibility of the platform, combined with the power of the application stack, enabled rapid re-development of the OBIS infrastructure, and ensured complete standards-compliance.

Aim Ecologists seeking to describe patterns at ever larger scales require compilations of data on the global abundance and distribution of species. Comparable compilations of biological data are needed to elucidate the mechanisms behind these patterns, but have received far less attention. We assess the availability of biological data across an entire assemblage: the well-documented demersal marine fauna of the United Kingdom. We also test whether data availability for a species depends on its taxonomic group, maximum body size, the number of times it has been recorded in a global biogeographic database, or its commercial and conservation importance.

A large-scale database concerning benthic copepods from the Arctic, Baltic Sea, North Sea, British Isles, Adriatic Sea and Crete was compiled to assess species richness, biodiversity, communities, ecological range size and biogeographical patterns. The Adriatic showed the highest evenness and the most species-rich communities. Assemblages from the North Sea, British Isles, Baltic and Crete had a lower evenness. The British Isles were characterised by impoverished communities. The ecological specificity of copepod species showed two diverging trends: higher specificity of species in more diverse assemblages was observed in the Adriatic, North Sea and Baltic. A uniformly high species specificity disregarding sample diversity was found on Crete and in the British Isles. Benthic copepod communities showed distinct patterns that clearly fit the predefined geographical regions. Communities were distinguishable and β-diversity was found to be high around Europe, indicating a high species turnover on the scale of this investigation. The British Isles and the North Sea were found to be faunistic links to the Baltic and the Arctic.

Reiss, H., Degraer, S., Duineveld, G. C. A., Kröncke, I., Aldridge, J., Craeymeersch, J., Eggleton, J. D., Hillewaert, H., Lavaleye, M. S. S., Moll, A., Pohlmann, T., Rachor, E., Robertson, M., vanden Berghe, E., van Hoey, G., and Rees, H. L. 2010. Spatial patterns of infauna, epifauna, and demersal fish communities in the North Sea. – ICES Journal of Marine Science, 67: 278–293. Understanding the structure and interrelationships of North Sea benthic invertebrate and fish communities and their underlying environmental drivers is an important prerequisite for conservation and spatial ecosystem management on scales relevant to ecological processes. Datasets of North Sea infauna, epifauna, and demersal fish (1999–2002) were compiled and analysed to (i) identify and compare spatial patterns in community structure, and (ii) relate these to environmental variables. The multivariate analyses revealed significantly similar large-scale patterns in all three components with major distinctions between a southern community (Oyster Ground and German Bight), an eastern Channel and southern coastal community, and at least one northern community (>50 m deep). In contrast, species diversity patterns differed between the components with a diversity gradient for infauna and epifauna decreasing from north to south, and diversity hotspots of demersal fish, e.g. near the major inflows of Atlantic water. The large-scale hydrodynamic variables were the main drivers for the structuring of communities, whereas sediment characteristics appeared to be less influential, even for the infauna communities. The delineation of ecologically meaningful ecosystem management units in the North Sea might be based on the structure of the main faunal ecosystem components.

Parallel data manipulation using R has previously been addressed by members of the R community, however most of these studies produce ad hoc solutions that are not readily available to the average R user. Our targeted users, ranging from the expert ecologist/microbiologists to computational biologists, often experience difficulties in finding optimal ways to exploit the full capacity of their computational resources. In addition, improving performance of commonly used R scripts becomes increasingly difficult especially with large datasets. Furthermore, the implementations described here can be of significant interest to expert bioinformaticians or R developers. Therefore, our goals can be summarized as: (i) description of a complete methodology for the analysis of large datasets by combining capabilities of diverse R packages, (ii) presentation of their application through a virtual R laboratory (RvLab) that makes execution of complex functions and visualization of results easy and readily available to the end-user. In this paper, the novelty stems from implementations of parallel methodologies which rely on the processing of data on different levels of abstraction and the availability of these processes through an integrated portal. Parallel implementation R packages, such as the pbdMPI (Programming with Big Data – Interface to MPI) package, are used to implement Single Program Multiple Data (SPMD) parallelization on primitive mathematical operations, allowing for interplay with functions of the vegan package. The dplyr and RPostgreSQL R packages are further integrated offering connections to dataframe like objects (databases) as secondary storage solutions whenever memory demands exceed available RAM resources. The RvLab is running on a PC cluster, using version 3.1.2 (2014-10-31) on a x86_64-pc-linux-gnu (64-bit) platform, and offers an intuitive virtual environmet interface enabling users to perform analysis of ecological and microbial communities based on optimized vegan functions. A beta version of the RvLab is available after registration at: https://portal.lifewatchgreece.eu/

Within the context of topical global issues such as climate change, loss of biological diversity, persistent contamination and depletion of marine fisheries, assessing effects of environmental chan...

The List of East African Plants (LEAP) is an electronic database of the species, subspecies, and varieties of vascular plants (angiosperms, gynmosperms, ferns, and fern allies) that are native or naturalised in East Africa (Uganda, Kenya, and Tanzania). The information in LEAP comes primarily from the Flora of Tropical East Africa (FTEA; published as family fascicles from 1952 to present) and is supplemented by other published sources, such as The Sedges and Rushes of East Africa (Haines & Lye, 1983), Pteridophytes of Tropical East Africa (Johns, 1991), Upland Kenya Wild Flowers (Agnew & Agnew, 1995), and Kenya Trees, Shrubs and Lianas (Beentje, 1995), and specimen information from the East African Herbarium (EA) and other sources for those plant families not yet written for FTEA. This information includes taxon names, author citations, life form, origin, altitudinal range, geographic distribution (using FTEA floral division codes), and higher-level classification. Presented below is a brief history of LEAP, the current structure and organisation of LEAP version 1.3, a discussion of potential applications for herbarium management and plant biodiversity research (along with the limitations of such a database) and the work to be conducted in the future.

Global patterns of species richness and their structuring forces have fascinated biologists since Darwin and provide critical context for contemporary studies in ecology, evolution and conservation. Anthropogenic impacts and the need for systematic conservation planning have further motivated the analysis of diversity patterns and processes at regional to global scales. Whereas land diversity patterns and their predictors are known for numerous taxa, our understanding of global marine diversity has been more limited, with recent findings revealing some striking contrasts to widely held terrestrial paradigms. Here we examine global patterns and predictors of species richness across 13 major species groups ranging from zooplankton to marine mammals. Two major patterns emerged: coastal species showed maximum diversity in the Western Pacific, whereas oceanic groups consistently peaked across broad mid-latitudinal bands in all oceans. Spatial regression analyses revealed sea surface temperature as the only environmental predictor highly related to diversity across all 13 taxa. Habitat availability and historical factors were also important for coastal species, whereas other predictors had less significance. Areas of high species richness were disproportionately concentrated in regions with medium or higher human impacts. Our findings indicate a fundamental role of temperature or kinetic energy in structuring cross-taxon marine biodiversity, and indicate that changes in ocean temperature, in conjunction with other human impacts, may ultimately rearrange the global distribution of life in the ocean.

Plankton are the main food source in the majority of marine ecosystems and have a crucial role in climate change through primary production and the export of carbon to the deep ocean. Understanding how ocean biology and biogeochemical cycles contribute and respond to climate and other global change is a major challenge of high significance for the future of mankind. Given their importance it is a major concern that, with the exception of data collected by the Continuous Plankton Recorder (CPR) survey, our knowledge of plankton at ocean scales and over time is still rudimentary. Using ships of opportunity, the CPR survey has sampled the plankton for more than 75 years in the North Atlantic, aided more recently by sister surveys in Southern Ocean, North Pacific and Australasian waters. Monitoring plankton variability over large areas of oceanic and coastal water with the CPR is efficient and cost effective and is a powerful, proven tool for detecting and predicting oceanic impacts of both global and climate change. There is an urgent need to improve global coverage of plankton and provide data for modelling. To address this need we propose the development and implementation of an integrated and appropriately funded global CPR programme linked to SOOP/VOS. Our vision is to build regional surveys with common standards for sampling, analysis, data processing and sample storage that generate compatible and freely exchangeable data. It is envisaged that the resulting global network, of preferably instrumented CPR routes, would be closely associated with other traditional and new plankton sampling and analysing technologies, plus remote sensing and the Global Tracking Network (GTN). To develop this network it is proposed that SAHFOS should have a central role as a ‘Centre of Excellence’ for coordination, training and quality control, as well as the production of indicators, habitat niche modelling and other global outreach products.

Background: Understanding the distribution of marine biodiversity is a crucial first step towards the effective and sustainable management of marine ecosystems. Recent efforts to collate location records from marine surveys enable us to assemble a global picture of recorded marine biodiversity. They also effectively highlight gaps in our knowledge of particular marine regions. In particular, the deep pelagic ocean - the largest biome on Earth - is chronically under-represented in global databases of marine biodiversity.\ud \ud Methodology/Principal Findings: We use data from the Ocean Biogeographic Information System to plot the position in the water column of ca 7 million records of marine species occurrences. Records from relatively shallow waters dominate this global picture of recorded marine biodiversity. In addition, standardising the number of records from regions of the ocean differing in depth reveals that regardless of ocean depth, most records come either from surface waters or the sea bed. Midwater biodiversity is drastically under-represented.\ud \ud Conclusions/Significance: The deep pelagic ocean is the largest habitat by volume on Earth, yet it remains biodiversity's big wet secret, as it is hugely under-represented in global databases of marine biological records. Given both its value in the provision of a range of ecosystem services, and its vulnerability to threats including overfishing and climate change, there is a pressing need to increase our knowledge of Earth's largest ecosystem.\ud

The history of life is written in the ocean, and the history of the ocean is written in DNA. Geologists have shown us that hundreds of millions of years of ocean history can be revealed from records of a single phylum in cores of mud from abyssal plains. We are now accumulating genetic tools to unravel the relationships of hundreds of phyla to track this history back billions of years. The technologies demonstrated by the Census of Marine Life (CoML) mean that the ocean is no longer opaque or unknowable. The secrets of the largest component of the biosphere are knowable. The cost of understanding the history of ocean life is not cheap, but it is also not prohibitive. A transparent, open ocean is available for us to use to understand ourselves. This article develops a model of biodiversity equilibration in a single, physically static ocean as a step towards biodiversity in physically complex real oceans. It attempts to be quantitative and to simultaneously account for biodiversity patterns from bacteria to whales focusing on emergent properties rather than details. Biodiversity reflects long-term survival of DNA sequences, stabilizing “ecosystem services” despite environmental change. In the ocean, mechanisms for ensuring survival range from prokaryotes maintaining low concentrations of replicable DNA throughout the ocean volume, anticipating local change, to animals whose mobility increases with mass to avoid local change through movement. Whales can reach any point in the ocean in weeks, but prokaryotes can only diffuse. The high metabolic costs of mobility are offset by the dramatically lower number of DNA replicates required to ensure survival. Reproduction rates probably scale more or less inversely with body mass. Bacteria respond in a week, plankton in a year, whales in a century. We generally lack coherent theories to explain the origins of animals (metazoans) and the contributions of biodiversity to ecosystems. The One Ocean Model suggests that mobile metazoans paved the way for their own energetic life styles by decreasing the amount of primary production sinking to feed the benthic anaerobic prokaryotes. Increasing metazoan mobility and diversity ensured that less and less production sank and accelerated development of the aerobic oceans they require. High biodiversity among middle-sized organisms stabilizes the system, but rapid environmental changes can decrease diversity in a positive feedback loop ending in mass extinction events and the return of the anaerobes. The oceans have gone through this cycle several times. Global warming may be a mild flu compared to “the revenge of the microbes”.

The future data needs of ocean science and ocean resource management will require a more seamless and accessible coupling of biological data with physical oceanographic processes. This bio-physical data framework will be built through the active integration of data from an extensive variety of sensors, observers, platforms and data archives across a wide range of space and time scales. This necessary synthesis of raw biological data into useful information and potentially new understanding is dependent on both new developments in ocean exploration as well as developments in information systems and informatics. The Ocean Biogeographic Information System (OBIS) is poised to play a significant and expanding role in the evolving ocean observation system.

Three different transect methods were compared at two different sites in Kenya, on their efficiency to estimate hard coral cover, genus richness and Shannon diversity index. For a modified line transect method (LTM), the line intercept method (LIT) and a linear point intercept (LPI) method the relative efficiency of the three methods was calculated with respect to the tested parameters. The three methods were examined along identical transect lines (10 m) and a total of 27 transect triplets were recorded in Vipingo and 21 in Mombasa. The correlation coefficients for all three ecological parameters were calculated for the three possible pairs of methods, and the accumulation curves plotted for each of the parameters using number of transects as the independent variable. Results from the three methods were virtually indistinguishable. When the parameters were plotted using measuring time on the x axis, the curves for the LPI method converged twice as fast as those for LTM, while LIT time was intermediate. It is suggested that the LPI method might be most suitable for assessing coral cover, richness and diversity where time and effort are significant constraints. Keywords :transect methods, coral cover West Indian Ocean Journal of Marine Science Vol. 4 (1) 2005: pp. 29-38

Two biotic indices, ATZI Marine Biotic Index (AMBI) and Benthic Quality Index (BQI) have been recently introduced within the EC Water Framework Directive to assess the quality of marine habitats: both are based on sensitivity/tolerance classification and quantitative information on the composition of soft-bottom macrofauna. Their performance, especially with regard to sampling effort was assessed based on two data sets collected in Southern Baltic and one from the Gulf of Lions Mediterranean. AMBI was not affected by sampling effort but BQI was. Two modifications were proposed for BQI (i.e., BQI) (1) the removal of the scaling term (i.e., BQIW), and (2) the replacement of the scaling term by different scaling term (i.e., BQIES). Both modified BQIs were largely independent of sampling effort. Variability was slightly lower for BQIW than for BQIES. BQI was highly correlated with BQIW and with BQIES both in the Southern Baltic and in the Gulf of Lions. However, the proportions of stations, which were not attributed the same ecological quality status (EcoQ) when using BQI and its two modified forms were always high. Differences in ecological classification were mostly due to the cales used to infer EcoQ. Based on this study we recommend to use BQIES in future studies because it apparently constitutes the best compromise in (1) being independent of sampling effort, (2) limiting the variability in computation in relation with sampling effort, (3) being correlated with BQI and corresponding EcoQ.

This paper reports on the occurrence of Syrphidae in East Africa (Kenya, Tanzania, Uganda), based on 5,600 specimen records incorporated in the biodiversity database of the National Museums of Kenya. In total, 219 species are reported from the region with 171 in Kenya, 123 in Tanzania and 127 in Uganda. The similarities between the faunal composition of the three countries, as well as the endemicity are discussed. Based on GIS mapping of the database records, distribution patterns and zoogeographical relationships are discussed. Journal of East African Natural History Vol. 86 (1&2) 1997: pp. 43-50

The International conference on Marine Biodiversity Data management ‘Ocean Biodiversity Informatics’ was held in Hamburg, Germany, from 29 November to 1 December 2004. Its objective was to offer a forum to marine biological data managers to discuss the state of the field, and to exchange ideas on how to further develop marine biological data systems. Many marine biologists are actively gathering knowledge, as they have been doing for a long time. What is new is that many of these scientists are willing to share their knowledge, including basic data, with others over the Internet. Our challenge now is to try and manage this trend, avoid confusing users with a multitude of contradicting sources of information, and make sure different data systems can be and are effectively integrated. Supported by IOC for UNESCO and VLIZ (Flanders Marine Institute) Document available in English. Published