Software Product Lines (SPLs) and Software Ecosystems (SECOs) are approaches to capturing families of closely related software systems in terms of common and variable functionality (variability in space). SPLs and especially SECOs are subject to software evolution to adapt to new or changed requirements resulting in different versions of the software family and its variable assets (variability in time). Both dimensions may be interconnected (e.g., through version incompatibilities) and, thus, have to be handled simultaneously as not all customers upgrade their respective products immediately or completely. However, there currently is no integrated approach allowing variant derivation of features in different version combinations. In this thesis, remedy is provided in the form of an integrated approach making contributions in three areas: (1) As variability model, Hyper-Feature Models (HFMs) and a version-aware constraint language are introduced to conceptually capture variability in time as features and feature versions. (2) As variability realization mechanism, delta modeling is extended for variability in time, and a language creation infrastructure is provided to devise suitable delta languages. (3) For the variant derivation procedure, an automatic version selection mechanism is presented as well as a procedure to derive large parts of the application order for delta modules from the structure of the HFM. The presented integrated approach enables derivation of concrete software systems from an SPL or a SECO where both features and feature versions may be configured.:I. Context and Preliminaries 1. The Configurable TurtleBot Driver as Running Example 1.1. TurtleBot: A Domestic Service Robot 1.2. Configurable Driver Functionality 1.3. Software Realization Artifacts 1.4. Development History of the Driver Software 2. Families of Variable Software Systems 2.1. Variability 2.1.1. Variability in Space and Time 2.1.2. Internal and External Variability 2.2. Manifestations of Configuration Knowledge 2.2.1. Variability Models 2.2.2. Variability Realization Mechanisms 2.2.3. Variability in Realization Assets 2.3. Types of Software Families 2.3.1. Software Product Lines 2.3.2. Software Ecosystems 2.3.3. Comparison of Software Product Lines and Software Ecosystems 3. Fundamental Approaches and Technologies of the Thesis 3.1. Model-Driven Software Development 3.1.1. Metamodeling Levels 3.1.2. Utilizing Models in Generative Approaches 3.1.3. Representation of Languages using Metamodels 3.1.4. Changing the Model-Representation of Artifacts 3.1.5. Suitability of Model-Driven Software Development 3.2. Fundamental Variability Management Techniques of the Thesis 3.2.1. Feature Models as Variability Models 3.2.2. Delta Modeling as Variability Realization Mechanism 3.2.3. Variant Derivation Process of Delta Modeling with Feature Models 3.3. Constraint Satisfaction Problems 3.4. Scope 3.4.1. Problem Statement 3.4.2. Requirements 3.4.3. Assumptions and Boundaries II. Integrated Management of Variability in Space and Time 4. Capturing Variability in Space and Time with Hyper-Feature Models 4.1. Feature Models Cannot Capture Variability in Time 4.2. Formal Definition of Feature Models 4.3. Definition of Hyper-Feature Models 4.4. Creation of Hyper-Feature Model Versions 4.5. Version-Aware Constraints to Represent Version Dependencies and Incompatibilities 4.6. Hyper-Feature Models are a True Extension to Feature Models 4.7. Case Study 4.8. Demarcation from Related Work 4.9. Chapter Summary 5. Creating Delta Languages Suitable for Variability in Space and Time 5.1. Current Delta Languages are not Suitable for Variability in Time 5.2. Software Fault Trees as Example of a Source Language 5.3. Evolution Delta Modules as Manifestation of Variability in Time 5.4. Automating Delta Language Generation 5.4.1. Standard Delta Operations Realize Usual Functionality 5.4.2. Custom Delta Operations Realize Specialized Functionality 5.5. Delta Language Creation Infrastructure 5.5.1. The Common Base Delta Language Provides Shared Functionality for all Delta Languages 5.5.2. Delta Dialects Define Delta Operations for Custom Delta Languages 5.5.3. Custom Delta Languages Enable Variability in Source Languages 5.6. Case Study 5.7. Demarcation from Related Work 5.8. Chapter Summary 6. Deriving Variants with Variability in Space and Time 6.1. Variant Derivation Cannot Handle Variability in Time 6.2. Associating Features and Feature Versions with Delta Modules 6.3. Automatically Select Versions to Ease Configuration 6.4. Application Order and Implicitly Required Delta Modules 6.4.1. Determining Relevant Delta Modules 6.4.2. Forming a Dependency Graph of Delta Modules 6.4.3. Performing a Topological Sorting of Delta Modules 6.5. Generating Variants with Versions of Variable Assets 6.6. Case Study 6.7. Demarcation from Related Work 6.8. Chapter Summary III. Realization and Application 7. Realization as Tool Suite DeltaEcore 7.1. Creating Delta Languages 7.1.1. Shared Base Metamodel 7.1.2. Common Base Delta Language 7.1.3. Delta Dialects 7.2. Specifying a Software Family with Variability in Space and Time 7.2.1. Hyper-Feature Models 7.2.2. Version-Aware Constraints 7.2.3. Delta Modules 7.2.4. Application-Order Constraints 7.2.5. Mapping Models 7.3. Deriving Variants 7.3.1. Creating a Configuration 7.3.2. Collecting Delta Modules 7.3.3. Ordering Delta Modules 7.3.4. Applying Delta Modules 8. Evaluation 8.1. Configurable TurtleBot Driver Software 8.1.1. Variability in Space 8.1.2. Variability in Time 8.1.3. Integrated Management of Variability in Space and Time 8.2. Metamodel Family for Role-Based Modeling and Programming Languages 8.2.1. Variability in Space 8.2.2. Variability in Time 8.2.3. Integrated Management of Variability in Space and Time 8.3. A Software Product Line of Feature Modeling Notations and Constraint Languages 8.3.1. Variability in Space 8.3.2. Variability in Time 8.3.3. Integrated Management of Variability in Space and Time 8.4. Results and Discussion 8.4.1. Results and Discussion of RQ1: Variability Model 8.4.2. Results and Discussion of RQ2: Variability Realization Mechanism 8.4.3. Results and Discussion of RQ3: Variant Derivation Procedure 9. Conclusion 9.1. Discussion 9.1.1. Supported Evolutionary Changes 9.1.2. Conceptual Representation of Variability in Time 9.1.3. Perception of Versions as Incremental 9.1.4. Version Numbering Schemes 9.1.5. Created Delta Languages 9.1.6. Scalability of Approach 9.2. Possible Future Application Areas 9.2.1. Extend to Full Software Ecosystem Feature Model 9.2.2. Model Software Ecosystems 9.2.3. Extract Hyper-Feature Model Versions and Record Delta Modules 9.2.4. Introduce Metaevolution Delta Modules 9.2.5. Support Incremental Reconfiguration 9.2.6. Apply for Evolution Analysis and Planning 9.2.7. Enable Evolution of Variable Safety-Critical Systems 9.3. Contribution 9.3.1. Individual Contributions 9.3.2. Handling Updater Stereotypes IV. Appendix A. Delta Operation Generation Algorithm B. Delta Dialects B.1. Delta Dialect for Java B.2. Delta Dialect for Eclipse Projects B.3. Delta Dialect for DocBook Markup B.4. Delta Dialect for Software Fault Trees B.5. Delta Dialect for Component Fault Diagrams B.6. Delta Dialect for Checklists B.7. Delta Dialect for the Goal Structuring Notation B.8. Delta Dialect for EMF Ecore B.9. Delta Dialect for EMFText Concrete Syntax Files

Diese Dissertation beschäftigt sich mit der passiven Probenahme von hydrophoben organischen Schadstoffen in Oberflächengewässern: Polyaromatische Kohlenwasserstoffe (PAK), polychlorierte Biphenyle (PCB), polybromierte Biphenylether (PBDE), Organochlorpestizide (u. a. HCH, DDX) und weitere hydrophobe Pestizide. Die Zielstellung dieser Arbeit lag bei der Validierung des Silikonstabs als Alternativmethode im Gewässermonitoring zu konventionellen Probenahmetechniken wie Schöpf- und Wochenmischproben der Wasserphase sowie Schwebstoffanalysen. Die Probenahme mit dem Silikonstab erfolgte durch dessen Exposition im Gewässer für einen Zeitraum zwischen einer Woche und mehreren Monaten. Nach Einholung wurden die im Silikonstab akkumulierten Schadstoffe (Analyten) mittels instrumenteller Analytik quantifiziert. Die Probenaufgabe erfolgte ohne vorherige Lösungsmittelextraktion durch direktes Erhitzen des Silikonstabs, wodurch die Analyten vom Polymer desorbieren (Thermodesorption). Die durch Hitze freigesetzten Analyten wurden direkt auf eine chromatographische Trennsäule gegeben und massenspektroskopisch quantifiziert. Nach Erhalt der Ergebnisse der Silikonstab-Analytik gibt es verschiedene Herangehensweisen für die Berechnung der zeitgemittelten Analytkonzentrationen im Gewässer, die in dieser Arbeit vorgestellt und diskutiert werden. Dazu gehören die Verwendung von experimentellen Daten aus Kalibrierversuchen und Berechnungen auf Grundlage von physikochemischen Eigenschaften der Analyten wie dem Sammler-Wasser-Verteilungskoeffizienten. Im Zuge dieser Arbeit wurde die Aufnahmekinetik des Silikonstabs bei verschiedenen Temperaturen und Fließgeschwindigkeiten mit Hilfe von Kalibrierversuchen untersucht. Die gewonnenen experimentellen Daten wurden für die Entwicklung von Rechenmodellen herangezogen, mit denen das Aufnahmeverhalten vorgesagt werden soll. Es wurden Sammler-Wasser-Verteilungskoeffizienten für den Silikonstab u. a. mit der Kosolvenzmethode bestimmt und als Parameter für die Berechnung von zeitgemittelten Analytkonzentrationen des Gewässers verwendet. Für die Validierung wurde der Silikonstab in zwei Gewässergütemessstationen der Fließgewässer Mulde (Dessau) und Elbe (Magdeburg) in Durchflussbehältern exponiert und die zeitgemittelten Analytkonzentrationen mit verschiedenen Rechenmodellen bestimmt. Die erhaltenen Werte werden mit gleichzeitig entnommenen Wochenmischproben der Wasserphase sowie monatlichen Schwebstoffproben verglichen und die Eignung des Silikonstabs als alternative Probenahmemethode für das Umweltmonitoring von Oberflächengewässern diskutiert.:I ZUSAMMENFASSUNG ...................................................................................................... 2 II INHALTSVERZEICHNIS .................................................................................................. 3 III ABBILDUNGSVERZEICHNIS .......................................................................................... 5 IV TABELLENVERZEICHNIS ................................................................................................ 6 V GLEICHUNGSVERZEICHNIS ............................................................................................ 7 VI ABKÜRZUNGSVERZEICHNIS........................................................................................... 9 0 VIELEN DANK AN … ...................................................................................................... 11 1. EINLEITUNG ................................................................................................................ 12 1.1 Wasser, seine Nutzung und Verschmutzung ............................................................ 12 1.2 Das Wasser und seine Schadstoffe .......................................................................... 15 1.3 Monitoring von Oberflächengewässern .................................................................... 17 1.3.1 Entnahme konventioneller Schöpfproben .............................................................. 17 1.3.2 Entnahme von Mischproben (integrative oder Kompositproben) ........................... 18 1.3.3 Probenahme des Schwebstoffanteils in der Wasserphase .................................... 19 2. PASSIVSAMMLER IN DER WASSERANALYTIK ................................................................ 21 2.1 Theoretische Grundlagen ......................................................................................... 21 2.1.1 Allgemeiner Aufbau von Passivsammlern ............................................................... 23 2.1.2 Die einzelnen Schritte von der Wasser- in die Sammelphase ................................ 25 2.1.3 Adsorptive und absorptive Akkumulation des Analyten in der Sammelphase ........ 26 2.2 Passivsammlersysteme in der Wasseranalytik ......................................................... 28 2.2.1 Absorbierende Passivsammler für hydrophobe Analyten ....................................... 28 2.2.1.1 Semipermeable membrane device (SPMD) .......................................................... 28 2.2.1.2 LDPE-Streifen (LDPE strips) ................................................................................ 29 2.2.1.3 Silikonplatten (silicone sheets) ........................................................................... 30 2.2.1.4 Chemcatcher ...................................................................................................... 31 2.2.1.5 Lösungsmittelfreie Passivsammler (MESCO / Silikonstab) .................................. 32 2.2.2 Absorbierende Passivsammler für polare Analyten ............................................... 35 2.2.2.1 Polar organic integrative Sampler (POCIS) ......................................................... 35 2.2.2.2 Chemcatcher ...................................................................................................... 35 2.3 Auswertung von Passivsammlerdaten ..................................................................... 35 2.3.1 Gleichgewichtssammler ......................................................................................... 36 2.3.2 Laborkalibrierung .................................................................................................. 37 2.3.3 In-situ-Kalibrierung mit Performance Reference Compounds (PRC) ...................... 38 2.3.4 Validierung von Passivsammlern............................................................................ 39 3. LÖSLICHKEIT UND THERMODYNAMISCHES GLEICHGEWICHT ...................................... 41 3.1 Freie Enthalpie und chemisches Potential ................................................................ 41 3.2 Lineare freie Energie-Beziehungen (LFER) für die Abschätzung von KSW ................ 41 3.3 Kosolvenzmodelle für die Modellierung von KSW ...................................................... 43 3.3.1 Log-Linear-Modell von Yalkowsky .......................................................................... 43 3.3.2 Freie Enthalpie-Ansatz (Khossravi-Connors-Modell) .............................................. 44 3.3.3 Jouyban-Acree-Modell ............................................................................................ 44 4. MATERIAL UND METHODEN ......................................................................................... 45 4.1 Präparation der verwendeten Passivsammler .......................................................... 45 4.2 Laborkalibrierung zur Bestimmung von Sammelraten ............................................... 45 4.2.1 Beschreibung der Versuche für die Silikonstab-Kalibrierung .................................. 45 4.3 Experimentelle Bestimmung von Sammler-Wasser-Verteilungskoeffizienten KSW ... 48 4.3.1 Zeitabhängige KSW-Bestimmung in der Wasserphase .......................................... 48 4.3.2 KSW-Bestimmung mit der Kosolvenzmethode ....................................................... 50 4.4 Validierung des Silikonstabs an limnischen Gewässergütemessstationen ............... 52 5. ERGEBNISSE UND DISKUSSION ................................................................................... 55 5.1 Sammelraten RS für den Silikonstab aus Kalibrierversuchen .................................... 55 5.1.1 Temperaturabhängigkeit ....................................................................................... 58 5.1.2 Einfluss der Hydrodynamik auf die Aufnahmekinetik von PAK ................................ 59 5.1.3 Modellierung von Sammelraten .............................................................................. 62 5.1.3.1 Polynomisches Modell nach Vrana [137] ............................................................. 62 5.1.3.2 Diffusionsmodell nach Booij [71] ......................................................................... 64 5.1.3.3 Diffusionsmodell nach Rusina [85] ...................................................................... 66 5.1.4 Wahl der geeigneten In-situ-Kalibrierung am Beispiel eines Kalibrierversuchs ..... 67 5.1.4.1 Berechnung von In-situ-Sammelraten mit RS-Modellen ...................................... 68 5.1.4.2 Berechnung von In-situ-Sammelraten über Eliminierung von PRCs .................... 69 5.1.4.3 Vergleich Modelle und PRCs mit experimentellen Sammelraten .......................... 70 5.2 Experimentelle Bestimmung des Sammler-Wasser-Verteilungskoeffizienten KSW ... 73 5.2.1 Zeitabhängige KSW-Bestimmung in der Wasserphase .......................................... 73 5.2.2 Zusammenfassung KSW(t)-Versuche in der Wasserphase .................................... 81 5.2.3 KSW-Bestimmung mit der Kosolvenzmethode ....................................................... 81 5.2.3.1 Kosolvenzmodelle ............................................................................................... 83 5.2.4 Zusammenfassung ................................................................................................ 90 5.3 Empirische Modelle zur Abschätzung von KSW-Werten ............................................ 92 5.3.1 Lineare Korrelation des KSW mit physikochemischen und Molekülparametern ...... 92 5.3.2 Berechnung mit Mehrparameter-Regression (LSER) .............................................. 95 5.3.3 Zusammenfassung Abschätzung von KSW-Werten für den Silikonstab ................. 97 5.4 Freilandvalidierung des Silikonstab-Passivsammlers ................................................ 97 5.4.1 Ausbringung an Gewässergütemessstationen....................................................... 97 5.4.1.1 Validierung des Silikonstabs mit Wasserproben ............................................... 100 5.4.1.2 Validierung des Silikonstabs mit Sedimentproben ............................................ 102 5.4.2 Validierung des Silikonstabs bei Laborvergleichsstudien ..................................... 105 6. ERGEBNISSE UND AUSBLICK ..................................................................................... 105 VII LITERATURVERZEICHNIS ......................................................................................... 107 VIII ANHANG ................................................................................................................. 116

Despite the negative effects of fossil fuels on the environment, these remain as the primary contributors to the energy sector. In order to mitigate global warming risks, many countries aim at reducing greenhouse gas emissions. Bioenergy crops are being used as a substitute for fossil fuels and short rotation forestry is a prime example. In order to examine the sustainability of energy crops for fuel, typical European short rotation forestry (SRF) biomass, willow (Salix spp.) and poplar (Populus spp.) are examined and compared to rapeseed (Brassica napus L.) in respect to various aspects of soil respiration and combustion heat obtained from the extracted products per hectare. Various approaches are used to look at an As-contaminated site not only in the field but also in a soil-column experiment that examines the fate of trace elements in SRF soils, and in an analysis using MICMAC to describe the driving factors for SRF crop production. Based on the cause-effect chain, the impacts of land-use change and occupation on ecosystem quality are assessed when land-use is changed from degraded land (grassland) to willow and poplar SRF. A manual opaque dynamic closed chamber system (SEMACH-FG) was utilized to measure CO2 emissions at a willow/poplar short rotation forest in Krummenhennersdorf, Germany during the years 2013 and 2014, and at a rapeseed site in 2014. Short rotation forest soils showed higher CO2 emission rates during the growing season than the dormant season – with a CO2 release of 5.62±1.81 m-2 s-1 for willows and 5.08±1.37 µmol CO2 m-2 s-1 for poplars in the growing season. However, during the dormant season the soil sites with willow emitted 2.54±0.81 µmol CO2 m-2 s-1 and with poplar 2.07±0.56 µmol CO2 m-2 s-1. The highest emission rates for the studied plantations were observed in July for both years 2013 and 2014, during which the highest air and soil temperatures were recorded. Correlations between soil emission of CO2 and some meteorological parameters and leaf characteristics were investigated for the years 2013 and 2014. For example, for the willow clone (Jorr) and poplar clone (Max 3), high correlations were found for each between their soil emission of CO2 and both soil temperature and moisture content. Fitted models can explain about 77 and 75% of the results for Jorr and Max 3 clones, respectively. Moreover, a model of leaf area (LA) can explain about 68.6% of soil CO2 emission for H275. Estimated models can be used as a gap-filling method, when field data is not available. The ratio between soil respiration and the combustion heat calculated from the extracted products per hectare was evaluated and compared for the study’s willow, poplar and rapeseed crops. The results show that poplar and willow SRF has a very low ratio of 183 kg CO2 GJ 1 compared to rapeseed, 738 kg CO2 GJ 1. The soil-column experiment showed that by continuing the SRF plantation at the As-contaminated site, remediation would need only about 3% of the time needed if the site was left as a fallow field. In order to understand the complex willow and poplar short rotation forestry production system, 50 key variables were identified and prioritized to describe the system as a step to enhance the success of such potentially sustainable projects. The MICMAC approach was used in order to find the direct and the indirect relationships between those parameters and to classify them into different clusters depending on their driving force and interdependency. From this, it can be summarized that in order to enhance the success of a SRF system, decision makers should be focussing on: ensuring a developed wood-fuel market, increasing farmers’ experience/training, improving subsidy regulations and recommending a proper harvesting year cycle. Finally, the impacts of land-use change and occupation on the ecosystem quality were assessed. Results show that establishing SRF plantations on degraded lands improved the ecosystem structural quality (ESQ) by about 43% and ecosystem functional quality (EFQ) by about 12%. Based on overall results, poplar and willow SRF biomass can be recommended as renewable and sustainable sources for bioenergy.:Table of Contents Acknowledgements VI Abstract VII List of Figures IX List of Tables XI List of Appendix Tables XII List of Abbreviations XIII List of Abbreviations ...continued XIV 1. Background 1 1.1. General introduction 1 1.2. Soil organic carbon (SOC) 2 1.3. Soil respiration 4 1.4. Energy and bioenergy crops 5 1.5. Willow and poplar short rotation forestry 8 1.6. Degraded lands 10 1.8. Challenges 17 1.9. Objectives of this study 18 2. Methodology 19 2.1. Site Description 19 2.2. Environmental variables 22 2.3. Measuring CO2 emissions 23 2.3.1. Soil emission of CO2 23 2.3.2. Sensitivity of soil respiration to temperature (Q10) 25 2.4. Willow and poplar leaf traits 26 2.4.1. Measuring leaf area 26 2.4.2. Leaf Area Index (LAI) 27 2.4.3. Leaf sensitivity to high and low temperatures 28 2.5. Soil characteristics 30 2.5.1. Soil sampling 30 2.5.2. Soil Moisture Content % (SMC) by gravimetric method 31 2.5.3. Soil pH 31 2.5.4. Soil Cation Exchange Capacity (CEC) 31 2.5.5. Soil content of C, N, S, heavy metals and trace elements 31 2.5.6. Soil porosity 31 2.5.7. Soil pore water 32 2.5.8. Soil hydraulic conductivity (Kf) 32 2.6. Soil-column experiment 34 2.6.1. Experiment set-up 35 2.6.2. Distribution coefficients (Kd) 35 2.7. MICMAC approach 36 2.7.1. Selection of variables 36 2.7.2. Description of direct relationships 36 2.7.3. Classification of variables 37 2.8. Impacts of land-use change on the ecosystem quality 38 2.9. Computer software 40 3. Results and Discussion 41 3.1. Environmental conditions 41 3.1.1. Photosynthetically active radiation (PAR) 41 3.1.2. Soil temperature 42 3.1.3. Soil moisture content 43 3.2. Soil emission of CO2 46 3.2.1. CO2 emission from soil at the short rotation forestry site 46 3.2.2. Soil emission of CO2 during the day and the night 48 3.2.3. Cumulative emission of CO2 49 3.2.4. Comparison with other bioenergy crops 50 3.3. Q10 52 3.4. Willow and poplar Leaf Characteristics 54 3.4.1. Leaf Area Index (LAI) 54 3.4.2. Specific leaf area (SLA) 56 3.4.3. Leaf sensitivity to temperature 57 3.5. Correlations of soil CO2 emission with soil temperature and moisture content 59 3.6. Correlations of soil CO2 emission with plant parameters 65 3.7. Insights into soil respiration and combustion heat per area 67 3.7.1. Cumulative seasonal CO2 emission (CE) 68 3.7.2. Output energy 69 3.7.3. CO2(soil respiration) / Energy ratio 70 3.7.4. Global-warming potential (GWP) 72 3.8. Trace elements in soil 73 3.8.1. Solid-liquid partition coefficients (Kd) 74 3.8.2. Estimating time of remediation 78 3.9. Identification and Prioritization of Key Parameters for Willow and Poplar Short Rotation Forestry (SRF) Production System 82 3.9.1. Based on direct influence/dependence map: 85 3.9.2. Based on indirect influence/dependence map: 87 3.10. Impacts of Land-use Change on the Ecosystem Quality 93 4. Conclusions and Recommendations 101 5. References 102 Appendix 118

Technical complexities and the high cost of satellite images have hindered the adoption of remote sensing technology and tools for nature conservation works in Ethiopia as in many developing countries. The terrestrial and aquatic ecosystems in Abijjata Shala Lakes National Park (ASLNP) and the Important Bird Areas (IBAs) around the park are considered to be one of the most important home ranges for birds. However, little is known about the effect of land use/land cover (LULC) dynamics, due to lack of technical know how and logistical problems. However, it has been shown in this study that sophisticated image management works are not always relevant. Instead a simple method of utilizing the thermal band has been demonstrated. A new approach of long-term dynamics analysis method has also been suggested. A successful classification of images was achieved after such simple enhancement tests. It has been discovered that, there were more active LULC change processes in the area in the first study period (1973 to 1986) than during the second study period (1986-2000). In the first period nearly half of the landscape underwent land cover change processes with more than 26% of the entire landscape experiencing forest or land degradation. In the second period the extent of the change process was limited to only 1/3 of the total area with a smaller amount of degradation processes than before. During the entire study period, agriculture was responsible for the loss of more than 4/5 of the total terrestrial productive ecosystem. More than 37.6% of the total park area has been experiencing this loss for the past 3 decades. Only 1/5 of this area has a chance to revive, the remaining has undergone a permanent degradation. Lake Abijjata lost half of its size during the past 30 years. In the Zeway-Awassa basin 750 km², 2428km² and 3575km² of terrestrial lands and water bodies are within a distance of 10km, 20km and 30km from IBAs respectively. There are ecologically important areas where two or more IBAs overlap. In areas where more than two to five IBAs overlap, up to 85km² of areas have been recently degraded. High livestock density is one of the reasons for degradation. Using a monthly MODIS data from 2000-2005 and a series of interpolation techniques, the productivity of the area as well as the standing biomass were estimated. Moreover, a new method of spatially accurate livestock density assessment was developed in this study. Only 0.3% of the park area is found to be suitable for productive livestock development but nearly all inhabitants think the area is suitable. Feed availability in ASLNP is scarce even during rainy seasons. Especially the open woodlands are subject to overgrazing. Such shortage forces the inhabitants to cut trees for charcoal making to buy animal feed and non-food consumables. While more than 95% of the inhabitants in the park expanded their agriculture lands, only 13.3% of the farmers managed to produce cereals for market. The application of low cost remote sensing and GIS methods provided ample information that enables to conclude that low productivity and household food insecurity are the main driving forces behind land cover changes that are negatively affecting the natural and semi-natural ecosystems in the central and southern Rift Valley of Ethiopia. The restoration of natural ecosystems or conservation of biodiversity can be achieved only if those driving forces are tackled sustainably.

Existing ecotoxicity data for chemicals vary to a high extent between the environmental compartments water and sediment, since the evaluation of contaminants has historically focused on water exposition. Many anthropogenic chemicals and waste materials, including toxic organic and inorganic chemicals, adsorb to particulate matter and accumulate in sediments, and may thus be a threat to organisms living in the sediment. The invertebrates Chironomus riparius and Lumbriculus variegatus were selected as representatives of endobenthic living organisms. Acute toxicity tests, via water-only exposure, and sediment toxicity tests were conducted with the two endobenthic invertebrates. In sediment toxicity tests, organisms are mainly exposed to sediment- and particle-bound chemicals and dissolved chemical in the pore water. Toxicity data for algae, daphnids, and fish (via water-only exposure) are available for many substances, whereas the existing sediment toxicity data are rather rare. Thus, the interest arises to predict sediment toxicity for sediment-dwelling invertebrates from existing acute toxicity data of tests with water-only exposure. The main emphasis of this work was placed on one metal compound and seven organic chemicals. The objective of this study was fivefold: (1) develop methods and improve existing procedures on acute and sediment toxicity testing of the two invertebrates; (2) conduct both acute toxicity tests via water exposure and long-term sediment toxicity tests for the selected model substances to generate data for comparative discussion; (3) assess correlations among acute toxicity data of the organisms exposed via water-only and correlations among sediment toxicity data of the two endobenthic invertebrates for the eight tested chemicals; (4) assess possible forecasting for sediment toxicity from acute toxicity (via water-only exposure) and (5) assess exposure effects to determine the main exposure route. Acute toxicity data of the eight tested chemicals of D. magna significantly correlated with data of L. variegatus and C. riparius (p<0.05). However, a prediction of toxicity based on D. magna data bears high uncertainty, due to the small data set and high variation in sensitivity of the organisms. Existing sediment toxicity test methods were improved to meet the demand for artificial sediments containing organic matter that serves sufficiently as internal food source for the test organisms, and thus representing natural exposure conditions. However, the sediments that were used for the two organisms to test the selected model substances differed in sediment composition. Therefore, a sediment with the same sediment composition and the same water-to-sediment ratio for both invertebrates was developed, to have similar exposure conditions. In sediment toxicity tests, C. riparius was observed to be more sensitive than L. variegatus and no correlation was observed among data of the invertebrates. For the selected substances, lowest effect concentrations were observed for 3,4-dichloroaniline, whereas effect concentrations were the highest for benzo[a]pyrene. No correlations were found between the acute toxicity data of exposure via the water phase and sediment toxicity data, thus making a prediction of sediment toxicity data impossible. From analytical measurements of chemicals concentration in the compartments overlying, pore water, and bulk sediment, partition coefficients on sediment water partitioning were calculated. The highest partition coefficient ratios for sediment water partitioning were found for the high lipophilic organic substances 4,4-dichlorodiphenyltrichloroethan (DDT) and benzo[a]pyrene. Further, it was found that the main exposure routes in the 28-day sediment toxicity tests were not only chemical but species-dependent. As a result of very differing exposure routes for the tested chemicals and the absence of correlations from the acute to sediment toxicity data, sediment toxicity tests are necessary to assess the toxicity of chemicals on sediment inhabiting organisms. / In den meisten standardisierten ökotoxikologischen Untersuchungen zur Abschätzung des Gefährdungspotentials von Chemikalien für Gewässer erfolgt die Exposition der Organismen über die Wasserphase. Viele Schadstoffe, die in die aquatische Umwelt gelangen, adsorbieren aufgrund ihrer physikalisch-chemischen Eigenschaften an die Oberflächen von Schwebstoffen, sedimentieren und erreichen Sedimentkonzentrationen, die möglicherweise eine Gefahr für sedimentbewohnende Organismen darstellen. Im Rahmen dieser Arbeit wurden für benthische Invertebraten Testverfahren etabliert, bei denen eine Exposition der Organismen über das Sediment, hier hauptsächlich über die an ingestierte Sedimentbestandteile gebundene oder über die im Porenwasser gelöste Chemikalie (28-Tage Sedimenttoxizitätstest), und über dieWasserphase (Akuttoxizitätstest) erfolgte. Die Invertebraten Chironomus riparius und Lumbriculus variegatus wurden als typische Vertreter endobenthischer Organismen ausgewählt. Für viele Chemikalien liegen Daten zur akuten Toxizität für Algen, Daphnien und Fische für die Wasserexposition vor. Demgegenüber sind nur wenige Daten zur Toxizität für benthische Organismen weder mit einer Wasser- noch mit einer Sedimentexposition vorhanden. Als Modellsubstanzen wurden eine anorganische und sieben organische Substanzen für die Untersuchungen ausgewählt. Ziele dieser Arbeit waren: (1) die Entwicklung und Verbesserung von bestehenden Methoden zur Bestimmung der akuten Toxizität mitWasserexposition und der Sedimenttoxizität für die beiden Invertebraten; (2) die Durchführung der Tests mit den acht ausgewählten Modellsubstanzen zur vergleichenden Betrachtung; (3) die Beurteilung einer Korrelation der Daten zur Akuttoxizität innerhalb der verschiedenen Organismen mit Wasserexposition und einer Korrelation der Daten zwischen den beiden benthischen Organismen bei Sedimentexposition; (4) die Beurteilung einer Korrelation zwischen Daten der benthischen Invertebraten zur Akuttoxizität mit Wasserexposition und Sedimenttoxizität und (5) die Ermittlung und Bewertung der Expositionspfade. Die Akuttoxizitätsdaten von D. magna korrelieren significant (p<0.05) mit den Daten der beiden Invertebraten. Jedoch ist eine Vorhersage aufgrund des kleinen Datensatzes und der großen Unterschiede in der Empfindlichkeit der Arten abzulehnen. Um einer möglichst natürlichen Expositionssituation in Sedimenten zu entsprechen, wurden künstliche Sedimente mit interner Futterquelle, die auch mit der zu testenden Chemikalie kontaminiert wurde, entwickelt und für die Tests mit den Modellsubstanzen verwendet. Ein Nachteil war die unterschiedliche Sedimentzusammensetzung für die beiden Organismen. Um gleiche Expositionsbedingungen für beide Testorganismen zu gewährleisten, wurde ein artifizielles Sediment mit gleicher Zusammensetzung und gleichem Volumenverhältnis zwischen Sediment und Überstandswasser entwickelt. In den Sedimenttoxizitätstests reagierte C. riparius empfindlicher als L. variegatus. Die Effektkonzentrationen waren am niedrigsten für 3,4-Dichloraniline und am höchsten für Benzo[a]pyren. Die Korrelationen zwischen den Ergebnissen aus Akut- und Sedimenttoxizitstests waren nicht signifikant (p>0.05). Folglich läßt sich die Sedimenttoxizität nicht aus Daten zur akuten Toxizität mit Wasserexposition abschätzen. Aus den analytischen Messungen von Sediment-, Porenwasser- und Überstandswasserproben wurden die Koeffizienten für die Verteilung zwischen Sediment und Wasser berechnet. Für die stark lipophilen Stoffe, 4-Dichlorodiphenyltrichloroethan (DDT) und Benzo[a]pyren wurden die höchsten Koeffizienten errechnet. Weiterhin wurde festgestellt, daß die Hauptexpositionspfade in Sedimenttoxizitätstests einerseits von der Chemikalie und andererseits von der verwendeten Spezies abhängen. Aufgrund der Ergebnisse dieser Arbeit und der Tatsache, daß Sedimente “Senken” für viele Schadstoffe sind, müssen zur Erfassung und Bewertung des Gefährdungspotentials von Chemikalien gegenüber Sedimentbewohnern weiterhin Sedimenttoxizitätstests durchgeführt werden.

Die Konzentrationen der Treibhausgase (THG) Kohlendioxid (CO2), Methan (CH4) und Lachgas (N2O) haben ein Niveau erreicht, welches mit sehr hoher Wahrscheinlichkeit seit 800.000 Jahren nicht vorgekommen ist (Stocker et al. 2013).

Biologische und chemische Monitoringdaten wurden im Hinblick auf insektizid wirkende Stoffe ausgewertet. Im Zeitraum 2009 bis 2017 wurden 28 Wirkstoffe nachgewiesen. Die 44 am stärksten belasteten Wasserkörper-Messstellen wurden identifiziert und tabellarisch dargestellt. Die Auswertung unterstützt den Nationalen Aktionsplan zur nachhaltigen Anwendung von Pflanzenschutzmitteln. Redaktionsschluss: 30.11.2018

Das erste Ziel dieser Arbeit ist eine umfassende Analyse der Wasserflüsse durchzuführen und Quellen und Senken des kontinentalen Niederschlags zu identifizieren. Als Analysemethode werden komplexe Netzwerke verwendet, ein Ansatz, mit dessen Hilfe das neuartige Konzept des “cascading moisture recycling'''' (CMR) eingeführt wird. CMR wird als vielfache Verdunstung von Niederschlag während des Feuchtigkeitstransports über bewaldeten Gebieten definiert. Dieses Verfahren ermöglicht es, den Anteil von CMR an der Menge des regionalen Niederschlags zu quantifizieren und Schlüsselregionen des CMR zu identifizieren. Die Analyse zeigt, dass der südliche Bereich des Amazonasbeckens nicht nur eine direkte Quelle für Niederschlag im La-Plata Becken ist, sondern auch als ``Brückenregion'''' dient, über die die verdunstete Feuchtigkeit des ganzen Amazonasbeckens auf dem Weg in die Subtropen transportiert wird. Die Ergebnisse zeigen, dass eine Neubewertung der Vulnerabilität des Amazonasregenwalds unter Umweltveränderungen unabdingbar ist. Dies ist das zweite Ziel der vorliegenden Arbeit. Durch diese Veränderungen könnten große Teile des Regenwaldes in eine Savanne umgewandelt werden. Dies würde wiederum den Niederschlag reduzieren, was sich negativ auf die Stabilität der verbleibenden Waldgebiete auswirken und ein Waldsterben verursachen kann. Für die Analyse dieser Zusammenhänge werden ebenfalls komplexe Netzwerke verwendet, um das Konzept der Ökosystem-Resilienz und CMR basierend auf Beobachtungsdaten zu kombinieren. Es werden die Schlüsselregionen, in denen Entwaldung zu einer Destabilisierung der verbleibenden Wald führt, identifiziert und die Möglichkeit eines großflächigen Absterben des Regenwaldes aufgrund von verlängerter Trockenzeit untersucht. Die Ergebnisse zeigen, dass die Diversität des Regenwaldes und die durch den Feuchtigkeitstransport gegebene Konnektivität der Waldgebiete eine wichtige Rolle für die Stabilität und ökologische Integrität dieses Ökosystems spielen. / The first aim of this thesis is to improve the understanding of vegetation-atmosphere interactions by means of complex network analysis of water fluxes from the sources to the sinks of rainfall in South America. This novel approach allows to introduce the concept of “cascading moisture recycling” defined as moisture recycling on the continent involving re-evaporation cycles along the way. A methodological framework is developed to quantify the importance of cascading moisture recycling and to identify key regions that sustain this process. It reveals, for instance, that the southern part of the Amazon basin is not only a direct source of rainfall for the La Plata basin as previously thought but also an intermediary region that re-distribute moisture evaporating from the entire Amazon basin towards the subtropics. This new concept lays the foundation for evaluating the vulnerability of the Amazon forest to environmental perturbations, which is the second aim of this thesis. Land-use and rainfall variability are expected to be intensified at the end of the twenty-first century and may push the south-eastern part of the Amazon forest towards a grass-dominated ecosystem. Such a forest loss would reduce local dry-season evapotranspiration and the resulting moisture supply for down-wind rainfall. In turn, this might erode the resilience of the remaining forest and lead to further forest losses. Using a complex network approach, the concepts of forest resilience and cascading moisture recycling are combined in a data-driven modeling framework. Key regions are identified where deforestation would greatly destabilize the remaining forest, as well as tipping points in dry-season intensification for large-scale self-amplified Amazon forest loss. The findings highlight the need to maintain the diversity and connectivity of forest patches in order to sustain the ecological integrity of the largest remaining tropical forest on Earth.

No description available.

Dissertation of Chief Fire Officer Dipl.-Ing. M. Sc. Dirk Schneider for achieving the academic degree of Dr.-Ing. of the Faculty of Forestry, Geo and Hydro Sciences of the Technical University of Dresden with the title: “Early Detection of Fires in Areas of Forests and other Vegetation” Fires threaten and destroy extensive forest and vegetation areas every year, endangering people and its settlements, leading to significant pressures on the environment and destroying considerable high value resources. The expenditures in manpower, logistics and finance for safety in general and fire suppression in particular are considerable. To minimize these varied and extensive consequences of fires, early detection is desirable, making an effective firefighting strategy possible. This early detection is particularly of importance in remote, large-scale areas and territories not under observation by the population, especially if they are subject to an increased or high vulnerability. After investigating and considering the causes, that repeatedly lead to forest fires not only in the Federal Republic of Germany but worldwide, the author describes different traditional and modern methods for early detection of fires in areas of forests and other vegetation. Furthermore the author develops a performance item catalog, basing on practical and economic experience, by which not only novel early warning systems can be developed, but the systems and methods described in the present study also are assessed and compared. The comparison of various early warning systems is guided not only by means of technical features, but also from an economic perspective. Financial calculation methods, staff costs and the peculiarities in public administration are particularly noted. The author also shows the different parameters that influence the selection of an appropriate early warning system for the detection of forest and vegetation areas. It becomes clear that it is the scene of the incident with its specific parameters that determines the most useful early warning system.