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Found 19 results.

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Limecola balthica - biomass (AFDW)

Distribution of biomass (ash free dry weight in g/m²) for 10 key species modeled with random forests method.Macrozoobenthic data from 1191 sampling stations located in the German part of the Baltic Sea were analyzed (data sources: Leibniz Institute for Baltic Sea Research). Samples have been collected from 1999 to 2015. Sample data were averaged per stations and standardized to the area of 1 m².For modeling R package “Random Forest” (RF, Version 4.6–7, Liaw and Wiener, 2002), based on random forests statistical analysis (Breiman, 2001) is used.Predictors and modeling algorithm as described in Gogina, M., Morys, C., Forster, S., Gräwe, U., Friedland, R., Zettler, M.L. 2017. Towards benthic ecosystem functioning maps: Quantifying bioturbation potential in the German part of the Baltic Sea. Ecological Indicators 73: 574-588. doi.org/10.1016/j.ecolind.2016.10.025

Bioturbation potential - modelled

Distribution of community bioturbation potential BPc (log-transformed values) resulting from random forest modeling using BPc as response variable. Bioturbation potential BPc is a metric to quantitatively estimate bioturbation intensity from benthic quantitative data suggested by Solan et al. (2004). Macrozoobenthic data from 1191 sampling stations located in the German part of the Baltic Sea were analyzed (data sources: Leibniz Institute for Baltic Sea Research). Samples have been collected from 1999 to 2015. Sample data were averaged per stations and standardized to the area of 1 m². For modeling R package “Random Forest” (RF, Version 4.6–7, Liaw and Wiener, 2002), based on random forests statistical analysis (Breiman, 2001) is used. Predictors and modeling algorithm as described in Gogina, M., Morys, C., Forster, S., Gräwe, U., Friedland, R., Zettler, M.L. 2017. Towards benthic ecosystem functioning maps: Quantifying bioturbation potential in the German part of the Baltic Sea. Ecological Indicators 73: 574-588. doi.org/10.1016/j.ecolind.2016.10.025Solan, M., Cardinale, B.J., Downing, A.L., Engelhardt, K.A.M., Ruesink, J.L., Srivastava,D.S., 2004. Extinction and ecosystem function in the marine benthos. Science306, 1177–1180.Liaw, A., Wiener, M., 2002. Classification and regression by randomForest. R. News2, 18–22.Breiman, L., 2001. Random forests. Mach. Learn. 45, 5–32.

Mya arenaria - biomass (AFDW).tif

Distribution of biomass (ash free dry weight in g/m²) for 10 key species modeled with random forests method.Macrozoobenthic data from 1191 sampling stations located in the German part of the Baltic Sea were analyzed (data sources: Leibniz Institute for Baltic Sea Research). Samples have been collected from 1999 to 2015. Sample data were averaged per stations and standardized to the area of 1 m².For modeling R package “Random Forest” (RF, Version 4.6–7, Liaw and Wiener, 2002), based on random forests statistical analysis (Breiman, 2001) is used.Predictors and modeling algorithm as described in Gogina, M., Morys, C., Forster, S., Gräwe, U., Friedland, R., Zettler, M.L. 2017. Towards benthic ecosystem functioning maps: Quantifying bioturbation potential in the German part of the Baltic Sea. Ecological Indicators 73: 574-588. doi.org/10.1016/j.ecolind.2016.10.025

Hediste diversicolor - biomass (AFDW)

Distribution of biomass (ash free dry weight in g/m²) for 10 key species modeled with random forests method.Macrozoobenthic data from 1191 sampling stations located in the German part of the Baltic Sea were analyzed (data sources: Leibniz Institute for Baltic Sea Research). Samples have been collected from 1999 to 2015. Sample data were averaged per stations and standardized to the area of 1 m².For modeling R package “Random Forest” (RF, Version 4.6–7, Liaw and Wiener, 2002), based on random forests statistical analysis (Breiman, 2001) is used.Predictors and modeling algorithm as described in Gogina, M., Morys, C., Forster, S., Gräwe, U., Friedland, R., Zettler, M.L. 2017. Towards benthic ecosystem functioning maps: Quantifying bioturbation potential in the German part of the Baltic Sea. Ecological Indicators 73: 574-588. doi.org/10.1016/j.ecolind.2016.10.025

Astarte borealis - biomass (AFDW)

Distribution of biomass (ash free dry weight in g/m²) for 10 key species modeled with random forests method.Macrozoobenthic data from 1191 sampling stations located in the German part of the Baltic Sea were analyzed (data sources: Leibniz Institute for Baltic Sea Research). Samples have been collected from 1999 to 2015. Sample data were averaged per stations and standardized to the area of 1 m².For modeling R package “Random Forest” (RF, Version 4.6–7, Liaw and Wiener, 2002), based on random forests statistical analysis (Breiman, 2001) is used.Predictors and modeling algorithm as described in Gogina, M., Morys, C., Forster, S., Gräwe, U., Friedland, R., Zettler, M.L. 2017. Towards benthic ecosystem functioning maps: Quantifying bioturbation potential in the German part of the Baltic Sea. Ecological Indicators 73: 574-588. doi.org/10.1016/j.ecolind.2016.10.025

Water-Sediment flux - oxygen - seasonal mean value (summer 1990 - 2000)

Modeled 3D biogeochemical sediment fluxes in the western Baltic Sea from 1990 to 2000 using MOM ERGOM SED. A new 3d sediment model ERGOM SED has been developed in the project SECOS for the western Baltic Sea. The model is documented in Radtke et al. (2019, doi: 10.5194/gmd-12-275-2019). It is an extension of the marine biogeochemical model ERGOM and is coupled to the physical model MOM. Simulation results of an eleven-year period from 1990 to 2000 covering the western Baltic Sea are provided for download. The model grid had a spatial resolution of 3 n.m. and covered the whole Baltic Sea (boundary conditions to North Sea in the Skagerrak). Detailed sediment data were compiled and a detailed validation was performed in the SECOS project for the western Baltic Sea. Hence, only model results of that region are provided. The sediment model was spun up for 240 years on a lower resolution and then run for forty years - whereas full model output was saved only for the last eleven years.

Bioturbation mode

Different modes of the bioturbation process are displayed, particle mixing and non-local bioturbation, as measured and modelled from vertical distributions of the particle tracer chlorophyll-a in n=24 sediment cores (MUC, 10 cm diameter)

Water quality - nutrients

Nutrients (nitrogen, phosphorus, chlorophyll) in the german Baltic Sea with the measured values for the present and the orientation values (class limit good ecological status).The orientation value indicates the Median from 2001 till 2012.

Bathymetry - German Baltic Sea

Bathymetry for the German Baltic Sea in meter- 2012.

Biomass - point

Seventeen major communities with characteristic species according to hierarchal clustering (based on point data aggregated to 5 km grid cells) and Indicator species analysis based on biomass data. Crosses indicate sampled cells with no benthic infauna recorded (mainly Polish dataset). Full coverage map of biomass-based communities distribution predicted with Random Forest.

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