Global distributions of picophytoplankton abundance and biomass - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The smallest marine phytoplankton, collectively termed picophytoplankton, have been routinely enumerated by flow cytometry since the late 1980s, during cruises throughout most of the world ocean. We compiled a database of 40,946 data points, with separate abundance entries for Prochlorococcus, Synechococcus and picoeukaryotes. We use average conversion factors for each of the three groups to convert the abundance data to carbon biomass. After gridding with 1° spacing, the database covers 2.4% of the ocean surface area, with the best data coverage in the North Atlantic, the South Pacific and North Indian basins. The average picophytoplankton biomass is 12 ± 22 µg C L-1 or 1.9 g C m-2. We estimate a total global picophytoplankton biomass, excluding N2-fixers, of 0.53 - 0.74 Pg C (17 - 39 % Prochlorococcus, 12 - 15 % Synechococcus and 49 - 69 % picoeukaryotes). Future efforts in this area of research should focus on reporting calibrated cell size, and collecting data in undersampled regions.

Large-Area Photo-Mosaicking tool (LAPM tool)

This paper presents a new tool for large-area photo-mosaicking (LAPM tool). This tool was developed specifically for the purpose of underwater mosaicking, and it is aimed at providing end-user scientists with an easy and robust way to construct large photo-mosaics from any set of images. It is notably capable of constructing mosaics with an unlimited number of images on any modern computer (minimum 1.30 GHz, 2 GB RAM). The mosaicking process can rely on both feature matching and navigation data. This is complemented by an intuitive graphical user interface, which gives the user the ability to select feature matches between any pair of overlapping images. Finally, mosaic files are given geographic attributes that permit direct import into ArcGIS. So far, the LAPM tool has been successfully used to construct geo-referenced photo-mosaics with photo and video material from several scientific cruises. The largest photo-mosaic contained more than 5000 images for a total area of about 105,000 m**2. This is the first article to present and to provide a finished and functional program to construct large geo-referenced photo-mosaics of the seafloor using feature detection and matching techniques. It also presents concrete examples of photo-mosaics produced with the LAPM tool.

(Table 3) Leaf area and leaf nitrogen for deciduous, evergreen, forb and graminoid species at Barrow, Svalbard and Zackenberg

Arctic vegetation is characterized by high spatial variability in plant functional type (PFT) composition and gross primary productivity (P). Despite this variability, the two main drivers of P in sub-Arctic tundra are leaf area index (LT) and total foliar nitrogen (NT). LT and NT have been shown to be tightly coupled across PFTs in sub-Arctic tundra vegetation, which simplifies up-scaling by allowing quantification of the main drivers of P from remotely sensed LT. Our objective was to test the LT-NT relationship across multiple Arctic latitudes and to assess LT as a predictor of P for the pan-Arctic. Including PFT-specific parameters in models of LT-NT coupling provided only incremental improvements in model fit, but significant improvements were gained from including site-specific parameters. The degree of curvature in the LT-NT relationship, controlled by a fitted canopy nitrogen extinction co-efficient, was negatively related to average levels of diffuse radiation at a site. This is consistent with theoretical predictions of more uniform vertical canopy N distributions under diffuse light conditions. Higher latitude sites had higher average leaf N content by mass (NM), and we show for the first time that LT-NT coupling is achieved across latitudes via canopy-scale trade-offs between NM and leaf mass per unit leaf area (LM). Site-specific parameters provided small but significant improvements in models of P based on LT and moss cover. Our results suggest that differences in LT-NT coupling between sites could be used to improve pan-Arctic models of P and we provide unique evidence that prevailing radiation conditions can significantly affect N allocation over regional scales.

Effects of plant functional traits on soil stability: intraspecific variability matters

This data set describes different vegetation, soil and plant functional traits (PFTs) of 15 plant species in 30 sampling plots of an agricultural landscape in the Haean-myun catchment in South Korea. We divided the data set into two main tables, the first one includes the PFTs data of the 15 studied plant species, and the second one includes the soil and vegetation characteristics of the 30 sampling plots. For a total of 150 individuals, we measures the maximum plant height (cm) and leaf size (cm**2), which means the leaf surface area for the aboveground compartment of each individual. For the belowground compartment, we measured root horizontal width, which is the maximum horizontal spread of the root, rooting length, which is the maximum rooting depth, root diameter, which is the average root diameter of a the whole root, specific root length (SRL), which is the root length divided by the root dry mass, and root/shoot ratio, which is the root dry mass divided by the shoot dry mass. At each of the 30 studied plots, we estimated three different variables describing the vegetation characteristics: vegetation cover (i.e. the percentage of ground covered by vegetation), species richness (i.e. the number of observed species) and root density (estimated using a 30 cm x 30 cm metallic frame divided into nine 10 cm x 10 cm grids placed on the soil profile), as we calculated the total number of roots that appear in each of the nine grids and then we converted it into percentage based on the root count, following. Moreover, in each plot we estimated six different soil variables: Bulk density (g/cm**3), clay % (i.e. percentage of clay), silt % (i.e. percentage of silt), soil aggregate stability, using mean weight diameter (MWD), penetration resistance (kg/cm**2), using pocket penetrometer and soil shear vane strength (kPa).