Lists of seamounts and knolls in different formats

Seamounts and knolls are 'undersea mountains', the former rising more than 1000 m from the sea floor. These features provide important habitats for aquatic predators, demersal deep-sea fish and benthic invertebrates. However most seamounts have not been surveyed and their numbers and locations are not well known. Previous efforts to locate and quantify seamounts have used relatively coarse bathymetry grids. Here we use global bathymetric data at 30 arc-second resolution to identify seamounts and knolls. We identify 33,452 seamounts and 138,412 knolls, representing the largest global set of identified seamounts and knolls to date. We compare estimated seamount numbers, locations, and depths with validation sets of seamount data from New Zealand and Azores. This comparison indicates the method we apply finds 94% of seamounts, but may overestimate seamount numbers along ridges and in areas where faulting and seafloor spreading creates highly complex topography. The seamounts and knolls identified herein are significantly geographically biased towards areas surveyed with ship-based soundings. As only 6.5% of the ocean floor has been surveyed with soundings it is likely that new seamounts will be uncovered as surveying improves. Seamount habitats constitute approximately 4.7% of the ocean floor, whilst knolls cover 16.3%. Regional distribution of these features is examined, and we find a disproportionate number of productive knolls, with a summit depth of <1.5 km, located in the Southern Ocean. Less than 2% of seamounts are within marine protected areas and the majority of these are located within exclusive economic zones with few on the High Seas. The database of seamounts and knolls resulting from this study will be a useful resource for researchers and conservation planners.

Upper Cenozoic dinoflagellate cysts from the continental slope and rise off New Jersey

This report contains the occurrence data for dinoflagellate cysts recorded from 163 samples taken from Sites 902 through 906, during Ocean Drilling Program (ODP) Leg 150. The dinoflagellate cyst (dinocyst) stratigraphy has been presented in Mountain, Miller, Blum, et al. (1994, doi:10.2973/odp.proc.ir.150.1994), and was based on these data. This report provides the full dinocyst data set supporting the dinocyst stratigraphic interpretations made in Mountain, Miller, Blum, et al. (1994). For Miocene shipboard dinocyst stratigraphy, I delineated 10 informal zones: pre-A, and A through I, in ascending stratigraphic order. These zones are defined in Shipboard Scientific Party (1994a, doi:10.2973/odp.proc.ir.150.103.1994), and are based on my studies of Miocene dinocyst stratigraphy in the Maryland and Virginia coastal plain (de Verteuil and Norris, 1991, 1992; de Verteuil, 1995). This zonation has been slightly revised (de Verteuil and Norris, 1996), and the new formal zone definitions are repeated below. Each new zone has an alpha-numeric abbreviation starting with "DN" (for Dinoflagellate Neogene). The equivalence between the informal zones reported in Mountain, Miller, Blum, et al. (1994), and the new DN zones is illustrated in Figure 1. For clarity, I delineated both zonations in the range charts that accompany this report (Tables 1-6). De Verteuil and Norris (1996a), using these and other data, correlated the DN zonation with the geological time scale of Berggren et al. (1995). Figure 2 summarizes these correlations and can be used to check the chronostratigraphic position of samples in this report, as determined by dinocyst stratigraphy. A thorough discussion of the basis for, and levels of uncertainty associated with, these correlations to the Cenozoic time scale can be found in de Verteuil and Norris (1996a). The Appendix lists all the dinocyst taxa recorded during shipboard analyses of Leg 150 samples. Open nomenclature is used for undescribed taxa. The range charts and Appendix also include reference to several new taxa that de Verteuil and Norris (1996b) described from Miocene coastal plain strata in Maryland and Virginia. Names of these taxa in Tables 1 through 6 and in the Appendix of this report are not intended for effective publication as defined in the International Code of Botanical Nomenclature (ICBN, Greuter et al., 1994). Therefore, taxonomic nomenclature contained in this report is not to be treated as meeting the conditions of effective and valid publication (ICBN; Article 29).

Taxonomic lists and abundances of the Lower Miocene bivalve assemblages of the Vives quarry (Meilhan, SW France)

Biodiversity estimates through geological times are difficult because of taphonomic perturbations that affect sedimentary records. Pristine shell assemblages, however, allow for calibration of past diversity. Diversity structures of two exceptionally preserved Miocene bivalve assemblages are quantitatively determined, compared with recent communities and used as paleoenvironmental proxy. The extremely rich assemblages were collected in Aquitanian (Early Miocene) carbonate sands of the Vives Quarry (Meilhan, SW France). Both paleontological and sedimentological data indicate a coral patch-reef environment, which deposits were affected by transport processes. Among two samples more than 28.000 shells were counted and 135 species identified. Sample Vives 1 is interpreted as a proximal debris flow and Sample Vives 2 as a sandy shoreface/foreshore environment influenced by storms. The two Vives assemblages have a similar diversity structure despite facies differences. Rarefaction curves level off at ~600 shells. The rare species account for more than 80 % of the species pool. The high values of PIE diversity index suggest a relatively high species richness and an even distribution of abundance of the most common species within the assemblages. The fossil data are compared to death shell assemblages (family level) of a modern reefal setting (Touho area, New Caledonia). The shape of the rarefaction curves and PIE indices of Meilhan fossil assemblages compare well to modern data, especially those of deep (>10 m water depth), sandy depositional environments found downward the reef slope (slope and pass settings). In addition to primary ecological signals, the similarity of the Vives samples and the Recent deep samples derives from taphonomic processes. This assumption is supported by sedimentological and paleontological observations. Sediment transports gather allochthonous and in situ materials leading to mixing of various ecological niches. Such taphonomic processes are recorded in the diversity metrics. Environmental mixing and time-averaging of the shell assemblages disturb the preservation of local-scale diversity properties but favour the sampling of the regional-scale diversity.

List of size fractionated eukaryotic plankton community samples and associated metadata (Database W1)

The present data set provides an Excel file in a zip archive. The file lists 334 samples of size fractionated eukaryotic plankton community with a suite of associated metadata (Database W1). Note that if most samples represented the piconano- (0.8-5 µm, 73 samples), nano- (5-20 µm, 74 samples), micro- (20-180 µm, 70 samples), and meso- (180-2000 µm, 76 samples) planktonic size fractions, some represented different organismal size-fractions: 0.2-3 µm (1 sample), 0.8-20 µm (6 samples), 0.8 µm - infinity (33 samples), and 3-20 µm (1 sample). The table contains the following fields: a unique sample sequence identifier; the sampling station identifier; the Tara Oceans sample identifier (TARA_xxxxxxxxxx); an INDSC accession number allowing to retrieve raw sequence data for the major nucleotide databases (short read archives at EBI, NCBI or DDBJ); the depth of sampling (Subsurface - SUR or Deep Chlorophyll Maximum - DCM); the targeted size range; the sequences template (either DNA or WGA/DNA if DNA extracted from the filters was Whole Genome Amplified); the latitude of the sampling event (decimal degrees); the longitude of the sampling event (decimal degrees); the time and date of the sampling event; the device used to collect the sample; the logsheet event corresponding to the sampling event ; the volume of water sampled (liters). Then follows information on the cleaning bioinformatics pipeline shown on Figure W2 of the supplementary litterature publication: the number of merged pairs present in the raw sequence file; the number of those sequences matching both primers; the number of sequences after quality-check filtering; the number of sequences after chimera removal; and finally the number of sequences after selecting only barcodes present in at least three copies in total and in at least two samples. Finally, are given for each sequence sample: the number of distinct sequences (metabarcodes); the number of OTUs; the average number of barcode per OTU; the Shannon diversity index based on barcodes for each sample (URL of W4 dataset in PANGAEA); and the Shannon diversity index based on each OTU (URL of W5 dataset in PANGAEA).

Habitat map of Danajon Bank, Philippines, derived from a high-spatial-resolution multi-spectral satellite image and georeferenced point intercept transect and spot-check survey field data, using an object-based image classification method

A mosaic of two WorldView-2 high resolution multispectral images (Acquisition dates: October 2010 and April 2012), in conjunction with field survey data, was used to create a habitat map of the Danajon Bank, Philippines (10°15'0'' N, 124°08'0'' E) using an object-based approach. To create the habitat map, we conducted benthic cover (seafloor) field surveys using two methods. Firstly, we undertook georeferenced point intercept transects (English et al., 1997). For ten sites we recorded habitat cover types at 1 m intervals on 10 m long transects (n= 2,070 points). Second, we conducted geo-referenced spot check surveys, by placing a viewing bucket in the water to estimate the percent cover benthic cover types (n = 2,357 points). Survey locations were chosen to cover a diverse and representative subset of habitats found in the Danajon Bank. The combination of methods was a compromise between the higher accuracy of point intercept transects and the larger sample area achievable through spot check surveys (Roelfsema and Phinn, 2008, doi:10.1117/12.804806). Object-based image analysis, using the field data as calibration data, was used to classify the image mosaic at each of the reef, geomorphic and benthic community levels. The benthic community level segregated the image into a total of 17 pure and mixed benthic classes.