Investigation of Interrelations Between Sediment and Near-Bottom Environmental Parameters And

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Investigation of Interrelations Between Sediment and Near-Bottom Environmental Parameters And Investigation of interrelations between sediment and near-bottom environmental parameters and macrozoobenthic distribution patterns for the Baltic Sea I n a u g u r a l d i s s e r t a t i o n zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften der Mathematisch-Naturwissenschaftlichen Fakultät der Ernst-Moritz-Arndt-Universität Greifswald vorgelegt von Mayya Gogina geboren am 21.05.1982 in Moskau Greifswald, 08 Januar 2010 Dekan: Prof. Dr. Klaus Fesser 1. Gutachter : Prof. Dr. Jan Harff 2. Gutachter: Prof. Dr. Gerhard Graf Tag der Promotion: 3 Juni 2010 A doctoral thesis at the Ernst Moritz Arndt University of Greifswald can be produced either as a monograph or, recently, as a collection of papers. In the latter case, the introductory part constitutes the formal thesis, which summarizes the accompanying papers. These have either been published or are manuscripts at various stages (in press, accepted, submitted). i ii Erklärung Nach § 4 Abs. 1 der Promotionsordnung der Mathematisch-Naturwissenschaftlichen Fakultät der Ernst-Moritz-Arndt-Universität Greifswald vom 24. April 2007 (zuletzt geändert durch Änderungssatzung vom 26. Juni 2008): Hiermit erkläre ich, dass diese Arbeit bisher von mir weder an der Mathematisch- Naturwissenschaftlichen Fakultät der Ernst-Moritz-Arndt-Universität Greifswald noch einer anderen wissenschaftlichen Einrichtung zum Zwecke der Promotion eingereicht wurde. Ferner erkläre ich, daß ich diese Arbeit selbständig verfasst und keine anderen als die darin angegebenen Hilfsmittel benutzt habe. Greifswald, den iii Abbreviations AIC Akaike’s information criterion BSH Bundesamt für Schiffahrt und Hydrographie (Federal Maritime and Hydrographic Agency) BTA biological trait analysis CCA canonical correspondence analysis DEM digital elevation model DYNAS Dynamics of natural and anthropogenic sedimentation GIS geographic information system GAM generalized additive model GLM generalized linear model HELCOM Helsinki Commission IOW Institut für Ostseeforschung Warnemünde (The Leibniz Institute for Baltic Sea Research, Warnemünde) LAEA Lambert Azimuthal Equal Area projection nMDS non-metric multidimensional scaling PCA principal component analysis UTM Universal Transversal Mercator WGS84 World Geographic System 84 iv Summary (Zusammenfassung) The objectives of the present work are to relate the spatial distribution of benthic macrofauna in the Baltic Sea to patterns in environmental variables describing near-bottom hydrographical conditions and sediment characteristics, analyzing the data for two various spatial extents. It is mainly based on the data included in the Benthos Databank of the IOW. Other data considered originated from various available database and historical data on distribution of macrobenthic species (such as data provided by the Institut für Angewandte Ökologie, HELCOM monitoring data, Baltic Sea Alien Species Database). The external sources of abiotic data used included the data from BSH, Baltic Sea bathymetry datasets, modelled hydrographical data, sedimentological database of the IOW, and seabed sediments map produced by the EU- BALANCE project. The first case study is devoted to an exploratory statistical description of the prevailing ecological structure within the limited area attached to the region of the Mecklenburg Bight. By defining the study area, we aimed to lessen the dominance of near-bottom salinity and oxygen concentration (known to be the dominating factors defining the Baltic Sea biodiversity) in the analysis to illuminate the impact of others. Detection of the induced spatial dependencies, examination of the environmental framework and isolation of abiotic predictors of species distribution were executed by means of various statistical methods (e.g. rank correlation, hierarchical clustering, nMDS, BIOENV, CCA). Thus, key environmental descriptors of spatial distribution of macrofaunal communities were disclosed. Within the area of investigation, these were: water depth, regarded as a proxy for other environmental factors (it determines food quality, food availability, light penetration; partial correlation analysis for the considered abiotic variables revealed depth to be the primary descriptor for total organic content, salinity and median grain size) and total organic content. Distinct benthic assemblages that are discriminated by particular species (Hydrobia ulvae–Scoloplos armiger, Lagis koreni–Mysella bidentata and Capitella capitata–Halicryptus spinulosus) were defined. Each assemblage is related to different spatial subarea and is characterized by a certain variability of environmental factors. This study represented the basis for the predictive modelling of species distribution in the selected investigation area, which constituted the next part of the investigation. Species-specific models predicting the probability of occurrence relative to environmental and sedimentological characteristics were developed for 29 representative macrofaunal species using a logistic regression modelling approach. This way, for most species a good description of their occurrence along gradients of single environmental variables was obtained. Overall, the results showed moderate to high concordance (e.g., 64.1-93.5% for models considering the water depth as predictor, 57.4-94.3% for models predicting the probability of species occurrence relative to total organic content). Subsequently, the technique for a predictive v modelling of species distributions in response to abiotic parameters based on single-factor logistic regression models, utilizing Akaike’s information criterion (AIC) and Akaike weights for multimodel inference, was used. Thus, probabilities of occurrence for selected exemplary species (Arctica islandica, Hediste diversicolor, Pygospio elegans, Tubificoides benedii and Scoloplos armiger) were modelled and mapped. The very similar approach was used to model the benthic species’ response of their physical environment in the Pomeranian Bay (southern Baltic Sea). In the scheme of the dominance of strong salinity gradient over the brackish system, consistently small patches of comparatively higher or lower benthic diversity (the Shannon–Wiener diversity index ranges in various areas of the Pomeranian Bay approximately from 1 to 3.9) do emerge in areas where either environmental or anthropogenic impacts on the benthic habitat change drastically over short spatial distances. Hence, spatial diversity of ecological factors creates diversity among benthic colonization and community structures. The possibility to predict thereby induced benthic colonization areas and community structures inside the broad scheme of a brackish water habitat is shown through a logistic modelling approach. The study represents one of the first applications of this technique to benthic habitats of the Baltic Sea. Finally, the investigation proceeded on a large spatial scale. The discriminating ability of such factors as salinity, bathymetry (as indirect variable replacing a combination of different recourses and direct gradients - a primary descriptor for other abiotic factors) and sediment characteristics (considered only generally due to the lack of more detailed data) to explain the occurrence of typical macrozoobenthic species on the Baltic Sea-wide extend was tested. Full coverage macrofauna distribution maps, though being increasingly demanded, are generally lacking, with information being merely restricted to point observations. In contrast to spatial interpolation, periled by presence of short distance changes in community structure and dependence of the result on density of the samples, predictive habitat suitability modelling allows to objectively produce distribution maps at a level of detail limited only by the availability and resolution of the environmental data. Various literature sources and available databases were analyzed in respect to the information on macrozoobenthos distribution in the Baltic Sea, resulting in the compilation of an extensive list of taxa and an inventory dataset on species distribution for the whole Baltic Sea. The study demonstrates the need to analyze species’ relationships in gradient systems such as the Baltic Sea and provides a basis for a tool to predict natural and anthropogenic forced changes in species distribution. vi Table of contents Part A: Scientific Framework Erklärung iii Abbreviations iv Summary (Zusammenfassung) v Table of contents vii 1 Introduction 1 1.1 Objectives and aims of the thesis 2 1.2 Causes of changes in benthic habitats and communities 4 1.3 Successive steps of predictive geographical modelling 6 1.4 Exploring the prevailing ecological structure 6 1.5 Quantifying species response 8 1.6 Interactions between hydrography, sediments and benthic fauna 9 2 Materials and methods 11 2.1 Study area 11 2.2 Data acquisition 13 2.2.1 Sampling macrofauna 14 2.2.2 Sampling sediments, analysis and calculation of sediment parameters 15 2.2.3 Hydrographic measurements 16 2.2.4 Environmental data 17 2.3 Statistical methods and data treatment 18 2.3.1 General basics 18 2.3.2 Steps of the causal analysis 20 2.3.3 Steps of the regional-scale predictive modelling 22 2.3.4 Technique used for the large-scale modelling 24 3 Results 26 3.1 Causal analysis 26 3.2 Regional scale predictive modelling 32 3.3 Large scale predictive modelling 34 4 Discussion 37 4.1 Ecosystem engineers, BTA 39 4.2 Influence of benthic organisms on transport of sedimentary material 41 5 Concluding remarks 46 6 Future challenges 47 7 Acknowledgements 49 8 References
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