Depth integrated nitrogen fixation from the northern Benguela upwelling system during Maria S. Merain cruise MSM18/5

Nitrogen fixation data from the cruise number MSM18/5 with research vessel "Maria S. Merian" from 22.08.-20.09.2011 (from Walvis Bay to Walvis Bay) in front of Angola and northern Namibia. Samples taken by CTD- rosette sampler from different depths and incubated in glass bottles (535 ml) at light intensities that resemble the in situ light intensities of the sampling depth after 15N2 gas was injected to the sample. After the incubation time of 6 hours, the complete bottle content was filtered onto a pre-combusted Whatman GF/F filter. Filters were frozen, transported to the institute on dry ice and measured in a mass spectrometer for Delta 15N. The principle of the method was described by Montoya et al. (1996) and calculation was done according to their spread sheet. From the data of the single depths, the nitrogen fixation per square meter within the upper 40 m of the water column was calculated. The methods are described in detail in a paper submitted by Wasmund et al. in 2014 to be printed in 2015. Some results are surprisingly below zero. This occurs if the Delta 15N of the blank is higher than the measurement after incubation. It indicates that no nitrogen fixation occurred. Due to natural variability, the variability of the nitrogen fixation data is high. In an overall estimate, also over several cruises, negative and positive values compensate more or less, suggesting that nitrogen fixation is insignificant in the waters in front of northern Namibia and southern Angola.

Mineral nitrogen from KCl extractions of soil from the Jena Experiment (Main Experiment up to 30cm depth, year 2002)

As an estimate of plant-available N, this data set contains measurements of inorganic nitrogen (NO3-N and NH4-N, the sum of which is termed mineral N or Nmin) determined by extraction with 1 M KCl solution of soil samples from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Five soil cores (diameter 0.01 m) were taken at a depth of 0 to 0.15 m and 0.15 to 0.3 m of the mineral soil from each of the experimental plots in September 2002. Samples of the soil cores per plot were pooled during each sampling campaign. NO3-N and NH4-N concentrations were determined by extraction of soil samples with 1 M KCl solution and were measured in the soil extract with a Continuous Flow Analyzer (CFA, Skalar, Breda, Netherlands).

Mineral nitrogen from KCl extractions of soil from the Jena Experiment (Main Experiment up to 30cm depth, year 2004)

As an estimate of plant-available N, this data set contains measurements of inorganic nitrogen (NO3-N and NH4-N, the sum of which is termed mineral N or Nmin) determined by extraction with 1 M KCl solution of soil samples from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Five soil cores (diameter 0.01 m) were taken at a depth of 0 to 0.15 m and 0.15 to 0.3 m of the mineral soil from each of the experimental plots in March and October 2004. Samples of the soil cores per plot were pooled during each sampling campaign. NO3-N and NH4-N concentrations were determined by extraction of soil samples with 1 M KCl solution and were measured in the soil extract with a Continuous Flow Analyzer (CFA, Skalar, Breda, Netherlands).

Mineral nitrogen from KCl extractions of soil from the Jena Experiment (Main Experiment up to 15cm depth, year 2005)

As an estimate of plant-available N, this data set contains measurements of inorganic nitrogen (NO3-N and NH4-N, the sum of which is termed mineral N or Nmin) determined by extraction with 1 M KCl solution of soil samples from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. Soil sampling and analysis: Five soil cores (diameter 0.01 m) were taken at a depth of 0 to 0.15 m of the mineral soil from each of the experimental plots in April and September 2005. Samples of the soil cores per plot were pooled during each sampling campaign. NO3-N and NH4-N concentrations were determined by extraction of soil samples with 1 M KCl solution and were measured in the soil extract with a Continuous Flow Analyzer (CFA, Skalar, Breda, Netherlands).

Secchi depth maps for the Baltic Sea, 2003-2012, with links to GeoTIFs

Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.