Weighted distance based discriminant analysis: the R package WeDiBaDis

The WeDiBaDis package provides a user friendly environment to perform discriminant analysis (supervised classification). WeDiBaDis is an easy to use package addressed to the biological and medical communities, and in general, to researchers interested in applied studies. It can be suitable when the user is interested in the problem of constructing a discriminant rule on the basis of distances between a relatively small number of instances or units of known unbalanced-class membership measured on many (possibly thousands) features of any type. This is a current situation when analyzing genetic biomedical data. This discriminant rule can then be used both, as a means of explaining differences among classes, but also in the important task of assigning the class membership for new unlabeled units. Our package implements two discriminant analysis procedures in an R environment: the well-known distance-based discriminant analysis (DB-discriminant) and a weighteddistance- based discriminant (WDB-discriminant), a novel classifier rule that we introduce. This new procedure is based on an improvement of the DB rule taking into account the statistical depth of the units. This article presents both classifying procedures and describes the implementation of each in detail. We illustrate the use of the package using an ecological and a genetic experimental example. Finally, we illustrate the effectiveness of the new proposed procedure (WDB), as compared with DB. This comparison is carried out using thirty-eight, high-dimensional, class-unbalanced, cancer data sets, three of which include clinical features

Robotic Exploration: Place Recognition as a Tipicality Problem

Autonomous exploration is one of the main challenges of robotic researchers. Exploration requires navigation capabilities in unknown environments and hence, the robots should be endowed not only with safe moving algorithms but also with the ability to recognise visited places. Frequently, the aim of indoor exploration is to obtain the map of the robot’s environment, i.e. the mapping process. Not having an automatic mapping mechanism represents a big burden for the designer of the map because the perception of robots and humans differs significantly from each other. In addition, the loop-closing problem must be addressed, i.e. correspondences among already visited places must be identified during the mapping process. In this chapter, a recent method for topological map acquisition is presented. The nodes within the obtained topologicalmap do not represent single locations but contain information about areas of the environment. Each time sensor measurements identify a set of landmarks that characterise a location, the method must decide whether or not it is the first time the robot visits that location. From a statistical point of view, the problem we are concerned with is the typicality problem, i.e. the identification of new classes in a general classification context. We addressed the problem using the so-called INCA statistic which allows one to perform a typicality test (Irigoien & Arenas, 2008). In this approach, the analysis is based on the distances between each pair of units. This approach can be complementary to the more traditional approach units × measurements – or features – and offers some advantages over it. For instance, an important advantage is that once an appropriate distance metric between units is defined, the distance- based method can be applied regardless of the type of data or the underlying probability distribution

New Distance-Based approach for Genome-Wide Association Studies

With the raise of genome-wide association studies (GWAS), the analysis of typical GWAS data sets with thousands of potentially predictive single nucleotide-polymorphisms (SNPs) has become crucial in Biomedicine research. Here, we propose a new method to identify SNPs related to disease in case-control studies. The method, based on genetic distances between individuals, takes into account the possible population substructure, and avoids the issues of multiple testing. The method provides two ordered lists of SNPs; one with SNPs which minor alleles can be considered risk alleles for the disease, and another one with SNPs which minor alleles can be considered as protective. These two lists provide a useful tool to help the researcher to decide where to focus attention in a first stage

Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts

Diel vertical migrants and the ocean carbon pump: is there a ladder of migration?

Active flux performed by migrant biota is still a gap in the knowledge of the biological pump in the ocean. These organisms mainly feed upon epipelagic zooplankton and transport this carbon due to their feeding at the shallower layers and their defecation, respiration, excretion and mortality at depth. The recent finding that mesopelagic fish biomass in the ocean is one order of magnitude higher indicates that the active flux should be thoroughly evaluated. Here, we show enhanced plankton biomass, ranging from bacteria to zooplankton, reaching down to 4,000 m depth below the Atlantic and Pacific equatorial upwelling systems. We also found a striking close relationship between the zooplankton backscatter enhancement in the epi-, meso- and bathypelagic zones. Backscatter increased in a similar proportion along the subtropical, tropical, and equatorial areas in the three zones. Literature, recent data in subtropical waters, and these results suggest an intense active carbon transport from the epipelagic layer to the deep sea driven by zooplankton and micronekton, enhancing the efficiency of the biological pump and promoting true carbon sequestration beyond 1000 m depth.MALASPINA (CSD2008 00077) MAFIA (CTM2012-39587-C04

Vertical distribution of fish larvae in the Canaries-African coastal transition zone, in summer

13 pages, 6 figures, 2 tables.-- Printed version published Jul 2006.This study reports the vertical distribution of fish larvae during the 1999 summer upwelling season in the Canaries-African Coastal Transition Zone (the Canaries-ACTZ). The transition between the African coastal upwelling and the typical subtropical offshore conditions is a region of intense mesoscale activity that supports a larval fish population dominated by African neritic species. During the study, the thermal stratification extended almost to the surface everywhere, and the surface mixed layer was typically shallow or non-existent. Upwelling occurred on the African shelf in a limited coastal sub-area of our sampling. The vertical distributions of the entire larval fish population, as well as of individual species, were independent of the seasonal thermocline. Fish larvae and mesozooplankton were concentrated at intermediate depths regardless of the thermocline position, probably because of its weak signature and spatial and temporal variability. Day/night vertical distributions suggest that some species did not perform diel vertical migration (DVM), whereas others showed either type I DVM or type II DVM. The opposing DVM patterns of different species compensate for each other resulting in no net DVM for the larval fish population as a whole.Fieldwork was carried out as part of the CANIGO project, funded by the EU, and of the "Pelagic (EU-CICYT 1FD97-1084)" project from the Spanish Ministry of Education and the European Union

Processes and patterns of oceanic nutrient limitation

Microbial activity is a fundamental component of oceanic nutrient cycles. Photosynthetic microbes, collectively termed phytoplankton, are responsible for the vast majority of primary production in marine waters. The availability of nutrients in the upper ocean frequently limits the activity and abundance of these organisms. Experimental data have revealed two broad regimes of phytoplankton nutrient limitation in the modern upper ocean. Nitrogen availability tends to limit productivity throughout much of the surface low-latitude ocean, where the supply of nutrients from the subsurface is relatively slow. In contrast, iron often limits productivity where subsurface nutrient supply is enhanced, including within the main oceanic upwelling regions of the Southern Ocean and the eastern equatorial Pacific. Phosphorus, vitamins and micronutrients other than iron may also (co-)limit marine phytoplankton. The spatial patterns and importance of co-limitation, however, remain unclear. Variability in the stoichiometries of nutrient supply and biological demand are key determinants of oceanic nutrient limitation. Deciphering the mechanisms that underpin this variability, and the consequences for marine microbes, will be a challenge. But such knowledge will be crucial for accurately predicting the consequences of ongoing anthropogenic perturbations to oceanic nutrient biogeochemistry. © 2013 Macmillan Publishers Limited. All rights reserved

Pathways between Primary Production and Fisheries Yields of Large Marine Ecosystems

The shift in marine resource management from a compartmentalized approach of dealing with resources on a species basis to an approach based on management of spatially defined ecosystems requires an accurate accounting of energy flow. The flow of energy from primary production through the food web will ultimately limit upper trophic-level fishery yields. In this work, we examine the relationship between yield and several metrics including net primary production, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production. We also evaluate the relationship between yield and two additional rate measures that describe the export of energy from the pelagic food web, particle export flux and mesozooplankton productivity. We found primary production is a poor predictor of global fishery yields for a sample of 52 large marine ecosystems. However, chlorophyll concentration, particle-export ratio, and the ratio of secondary to primary production were positively associated with yields. The latter two measures provide greater mechanistic insight into factors controlling fishery production than chlorophyll concentration alone. Particle export flux and mesozooplankton productivity were also significantly related to yield on a global basis. Collectively, our analyses suggest that factors related to the export of energy from pelagic food webs are critical to defining patterns of fishery yields. Such trophic patterns are associated with temperature and latitude and hence greater yields are associated with colder, high latitude ecosystems

Molecular Evidence of the Toxic Effects of Diatom Diets on Gene Expression Patterns in Copepods

Diatoms are dominant photosynthetic organisms in the world's oceans and are considered essential in the transfer of energy through marine food chains. However, these unicellular plants at times produce secondary metabolites such as polyunsaturated aldehydes and other products deriving from the oxidation of fatty acids that are collectively termed oxylipins. These cytotoxic compounds are responsible for growth inhibition and teratogenic activity, potentially sabotaging future generations of grazers by inducing poor recruitment in marine organisms such as crustacean copepods.Here we show that two days of feeding on a strong oxylipin-producing diatom (Skeletonema marinoi) is sufficient to inhibit a series of genes involved in aldehyde detoxification, apoptosis, cytoskeleton structure and stress response in the copepod Calanus helgolandicus. Of the 18 transcripts analyzed by RT-qPCR at least 50% were strongly down-regulated (aldehyde dehydrogenase 9, 8 and 6, cellular apoptosis susceptibility and inhibitor of apoptosis IAP proteins, heat shock protein 40, alpha- and beta-tubulins) compared to animals fed on a weak oxylipin-producing diet (Chaetoceros socialis) which showed no changes in gene expression profiles.Our results provide molecular evidence of the toxic effects of strong oxylipin-producing diatoms on grazers, showing that primary defense systems that should be activated to protect copepods against toxic algae can be inhibited. On the other hand other classical detoxification genes (glutathione S-transferase, superoxide dismutase, catalase, cytochrome P450) were not affected possibly due to short exposure times. Given the importance of diatom blooms in nutrient-rich aquatic environments these results offer a plausible explanation for the inefficient use of a potentially valuable food resource, the spring diatom bloom, by some copepod species