Biotope map of the German Baltic Sea

Schiele, Kerstin S.; Darr, Alexander; Zettler, Michael L.; Friedland, René; Tauber, Franz; Weber, Mario von; Voß, Joachim

doi:10.1016/j.marpolbul.2015.05.038

Cited by 29 publications

(25 citation statements)

References 20 publications

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“…Although overfitting has been recognized as an issue in machine learning techniques that reduce model's generality [29,38], Zaki and Meira [39] stated that some overfit is actually helpful, especially for those classes that might go underrepresented. Futhermore, we followed Schiele et al [11] and ran models separately to keep the number of classes at each run relatively low.…”

Section: Thematic and Continuous Modelsmentioning

confidence: 99%

“…The HUB classification (Table 1), a relatively new classification scheme with few existing maps [11], has been developed to be compatible with EUNIS and is specifically designed to create a common understanding of the Baltic Sea habitats, biotopes and communities [6]. HUB is a hierarchical classification scheme that consists of six levels with biotopes defined by applying split rules similar to a dichotomous key.…”

Section: Introductionmentioning

confidence: 99%

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How Do Continuous High-Resolution Models of Patchy Seabed Habitats Enhance Classification Schemes?

et al. 2019

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Predefined classification schemes and fixed geographic scales are often used to simplify and cost-effectively map the spatial complexity of nature. These simplifications can however limit the usefulness of the mapping effort for users who need information across a different range of thematic and spatial resolutions. We demonstrate how substrate and biological information from point samples and photos, combined with continuous multibeam data, can be modeled to predictively map percentage cover conforming with multiple existing classification schemes (i.e., HELCOM HUB; Natura 2000), while also providing high-resolution (5 m) maps of individual substrate and biological components across a 1344 km2 offshore bank in the Baltic Sea. Data for substrate and epibenthic organisms were obtained from high-resolution photo mosaics, sediment grab samples, legacy data and expert annotations. Environmental variables included pixel and object based metrics at multiple scales (0.5 m–2 km), which improved the accuracy of models. We found that using Boosted Regression Trees (BRTs) to predict continuous models of substrate and biological components provided additional detail for each component without losing accuracy in the classified maps, compared with a thematic model. Results demonstrate the sensitivity of habitat maps to the effects of spatial and thematic resolution and the importance of high-resolution maps to management applications.

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Section: Thematic and Continuous Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

How Do Continuous High-Resolution Models of Patchy Seabed Habitats Enhance Classification Schemes?

et al. 2019

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“…Vice versa, the oxygen conditions determined whether phosphate was bound to iron in the sediment (oxic situation) or was released (during anoxia). The basic equations and assumptions as well as some validation are given by Neumann (2000), Radtke et al (2012), and Schiele et al (2015).…”

Section: Setup Of the Hydrodynamical-biogeochemical Model Of The Westmentioning

confidence: 99%

Eddies: Fluid Dynamical Niches or Transporters?–A Case Study in the Western Baltic Sea

et al. 2019

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“…Thus, especially small and remote habitats are presumably overlooked, although they might be of high ecological importance as a refuge or ‘stepping stone’ for larval dispersion and wider seafloor colonization. Even in the relatively small, enclosed Baltic Sea, the existing benthic habitat maps are based on point observations and reveal only broad‐scale biotope types (Gogina et al, ; Schiele et al, ). It is only recently that new developments in acoustic survey technologies and high‐resolution full‐coverage imagery of the seafloor have become available for surveys over extensive areas (Anderson et al, ; Brown, Smith, Lawton, & Anderson, ; Buhl‐Mortensen et al, ).…”

Section: Introductionmentioning

confidence: 99%

The potential exceptional role of a small Baltic boulder reef as a solitary habitat in a sea of mud

Beisiegel

Tauber

Gogina

et al. 2019

Aquatic Conservation

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1. In this study, non-destructive seafloor imaging techniques were employed to assess the benthic community structure of a recently discovered boulder reef within the central Arkona Basin of the Baltic Sea.2. Data indicate that geographical isolation, water column stratification and temporary oxygen deficiency create an exceptional reef habitat in a sea of mud. 3. The reef forms a saline refuge for the deepest and easternmost known population of the plumose sea anemones (Metridium dianthus Ellis, 1768) in the Baltic Sea. 4. Limited connectivity to other reefs and dominance of the aggressively colonizing and planktivorous M. dianthus hamper the recruitment of other species and lead to an overall low invertebrate richness. 5. Large boulders attract ecologically and economically important fish like Baltic cod (Gadus morhua Linnaeus, 1758) that find shelter in the otherwise heavily fished Arkona Basin.6. Despite this very first exploration being only a snapshot of the observed community, findings imply a potential conservation importance of this Germany's deepest known natural habitat type 1170 ('reefs').

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Biotope map of the German Baltic Sea

Cited by 29 publications

References 20 publications

How Do Continuous High-Resolution Models of Patchy Seabed Habitats Enhance Classification Schemes?

How Do Continuous High-Resolution Models of Patchy Seabed Habitats Enhance Classification Schemes?

Eddies: Fluid Dynamical Niches or Transporters?–A Case Study in the Western Baltic Sea

The potential exceptional role of a small Baltic boulder reef as a solitary habitat in a sea of mud

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