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The unprecedented increase in atmospheric concentrations of carbon dioxide (CO2) and other greenhouse gases (GHG) by anthropogenic activities since the Industrial Revolution impacts on various earth system processes, commonly referred to as `climate change´ (CC). CC faces aquatic ecosystems with extreme abiotic perturbations that potentially alter the interrelations between functional autotrophic and heterotrophic plankton groups. These relations, however, modulate biogeochemical cycling and mediate the functioning of aquatic ecosystems as C sources or sinks to the atmosphere. The aim of this thesis was therefore to investigate how different aspects of CC influence community composition and functioning of pelagic heterotrophic bacteria. These organisms constitute a major component of biogeochemical cycling and largely determine the balance between autotrophic and heterotrophic processes.
Due to the vast amount of potential CC impacts, this thesis focuses on the following two aspects: (1) Increased exchange of CO2 across the atmosphere-water interface and reaction of CO2 with seawater leads to profound shifts in seawater carbonate chemistry, commonly termed as `ocean acidification´ (OA), with consequences for organism physiology and the availability of dissolved inorganic carbon (DIC) in seawater. (2) The increase in atmospheric GHG concentration impacts on the efficiency with which the Earth cools to space, affecting global surface temperature and climate. With ongoing CC, shifts in frequency and severity of episodic weather events, such as storms, are expected that in particular might affect lake ecosystems by disrupting thermal summer stratification. Both aspects of CC were studied at the ecosystem-level in large-volume mesocosm experiments by using the Kiel Off-shore Mesocosms for Future Ocean Simulations (KOSMOS) deployed at different coastal marine locations, and the LakeLab facility in Lake Stechlin.
We evaluated the impact of OA on heterotrophic bacterial metabolism in a brackish coastal ecosystem during low-nutrient summer months in the Baltic Sea. There are several in situ experiments that already assessed potential OA-induced changes in natural plankton communities at diverse spatial and seasonal conditions. However, most studies were performed at high phytoplankton biomass conditions, partly provoked by nutrient amendments. Our study highlights potential OA effects at low-nutrient conditions that are representative for most parts of the ocean and of particular interest in current OA research. The results suggest that during extended periods at low-nutrient concentrations, increasing pCO2 levels indirectly impact the growth balance of heterotrophic bacteria via trophic bacteria-phytoplankton interactions and shift the ecosystem to a more autotrophic system.
Further work investigated how OA affects heterotrophic bacterial dissolved organic matter (DOM) transformation in two mesocsom studies, performed at different nutrient conditions. We observed similar succession patterns for individual compound pools during a phytoplankton bloom and subsequent accumulation of these compounds irrespective of the pCO2 treatment. Our results indicate that OA-induced changes in the dynamics of bacterial DOM transformation and potential impacts on DOM quality are unlikely. In addition, there have been no indications that in dependence of nutrient conditions, different amounts of photosynthetic organic matter are channelled into the more recalcitrant DOM pool. This provides novel insights into the general dynamics of the marine DOM pool.
A fourth enclosure experiment in oligo-mesotrophic Lake Stechlin assessed the impact of a severe summer storm on lake bacterial communities during thermal stratification by artificially mixing. Mixing disrupted and lowered the thermocline, increasing the upper mixed layer and substantially changed water physical-chemical variables. Deep water entrainment and associated changes in water physical-chemical variables significantly affected relative bacterial abundances for about one week. Afterwards a pronounced cyanobacterial bloom developed in response to mixing which affected community assembly of heterotrophic bacteria. Colonization and mineralization of senescent phytoplankton cells by heterotrophic bacteria largely determined C-sequestration to the sediment. About six weeks after mixing, bacterial communities and measured activity parameters converged to control conditions. As such, summer storms have the potential to affect bacterial communities for a prolonged period during summer stratification. The results highlight effects on community assembly and heterotrophic bacterial metabolism that are associated to entrainment of deep water into the mixed water layer and assess consequences of an episodic disturbance event for the coupling between bacterial metabolism and autochthonous DOM production in large volume clear-water lakes.
Altogether, this doctoral thesis reveales substantial sensitivities of heterotrophic bacterial metabolism and community structure in response to OA and a simulated summer storm event, which should be considered when assessing the impact of climate change on marine and lake ecosystems.
Weather extremes pose a persistent threat to society on multiple layers. Besides an average of ~37,000 deaths per year, climate-related disasters cause destroyed properties and impaired economic activities, eroding people's livelihoods and prosperity. While global temperature rises – caused by anthropogenic greenhouse gas emissions – the direct impacts of climatic extreme events increase and will further intensify without proper adaptation measures. Additionally, weather extremes do not only have local direct effects. Resulting economic repercussions can propagate either upstream or downstream along trade chains causing indirect effects. One approach to analyze these indirect effects within the complex global supply network is the agent-based model Acclimate. Using and extending this loss-propagation model, I focus in this thesis on three aspects of the relation between weather extremes and economic repercussions.
First, extreme weather events cause direct impacts on local economic performance. I compute daily local direct output loss time series of heat stress, river floods, tropical cyclones, and their consecutive occurrence using (near-future) climate projection ensembles. These regional impacts are estimated based on physical drivers and local productivity distribution. Direct effects of the aforementioned disaster categories are widely heterogeneous concerning regional and temporal distribution. As well, their intensity changes differently under future warming. Focusing on the hurricane-impacted capital, I find that long-term growth losses increase with higher heterogeneity of a shock ensemble.
Second, repercussions are sectorally and regionally distributed via economic ripples within the trading network, causing higher-order effects. I use Acclimate to identify three phases of those economic ripples. Furthermore, I compute indirect impacts and analyze overall regional and global production and consumption changes. Regarding heat stress, global consumer losses double while direct output losses increase by a factor 1.5 between 2000 – 2039. In my research I identify the effect of economic ripple resonance and introduce it to climate impact research. This effect occurs if economic ripples of consecutive disasters overlap, which increases economic responses such as an enhancement of consumption losses. These loss enhancements can even be more amplified with increasing direct output losses, e.g. caused by climate crises.
Transport disruptions can cause economic repercussions as well. For this, I extend the model Acclimate with a geographical transportation route and expand the decision horizon of economic agents. Using this, I show that policy-induced sudden trade restrictions (e.g. a no-deal Brexit) can significantly reduce the longer-term economic prosperity of affected regions. Analyses of transportation disruptions in typhoon seasons indicate that severely affected regions must reduce production as demand falls during a storm. Substituting suppliers may compensate for fluctuations at the beginning of the storm, which fails for prolonged disruptions.
Third, possible coping mechanisms and adaptation strategies arise from direct and indirect economic responses to weather extremes. Analyzing annual trade changes due to typhoon-induced transport disruptions depict that overall exports rise. This trade resilience increases with higher network node diversification. Further, my research shows that a basic insurance scheme may diminish hurricane-induced long-term growth losses due to faster reconstruction in disasters aftermaths. I find that insurance coverage could be an economically reasonable coping scheme towards higher losses caused by the climate crisis. Indirect effects within the global economic network from weather extremes indicate further adaptation possibilities. For one, diversifying linkages reduce the hazard of sharp price increases. Next to this, close economic interconnections with regions that do not share the same extreme weather season can be economically beneficial in the medium run. Furthermore, economic ripple resonance effects should be considered while computing costs. Overall, an increase in local adaptation measures reduces economic ripples within the trade network and possible losses elsewhere. In conclusion, adaptation measures are necessary and potential present, but it seems rather not possible to avoid all direct or indirect losses.
As I show in this thesis, dynamical modeling gives valuable insights into how direct and indirect economic impacts arise from different categories of weather extremes. Further, it highlights the importance of resolving individual extremes and reflecting amplifying effects caused by incomplete recovery or consecutive disasters.
This thesis describes the development and application of the impacts module of the ICLIPS model, a global integrated assessment model of climate change. The presentation of the technical aspects of this model component is preceded by a discussion of the sociopolitical context for model-based integrated assessments, which defines important requirements for the specification of the model. Integrated assessment of climate change comprises a broad range of scientific efforts to support the decision-making about objectives and measures for climate policy, whereby many different approaches have been followed to provide policy-relevant information about climate impacts. Major challenges in this context are the large diversity of the relevant spatial and temporal scales, the multifactorial causation of many climate impacts', considerable scientific uncertainties, and the ambiguity associated with unavoidable normative evaluations. A hierarchical framework is presented for structuring climate impact assessments that reflects the evolution of their practice and of the underlying theory. Integrated assessment models of climate change (IAMs) are scientific tools that contain simplified representations of the relevant components of the coupled society-climate system. The major decision-analytical frameworks for IAMs are evaluated according to their ability to address important aspects of the pertinent social decision problem. The guardrail approach is presented as an inverse' framework for climate change decision support, which aims to identify the whole set of policy strategies that are compatible with a set of normatively specified constraints (guardrails'). This approach combines, to a certain degree, the scientific rigour and objectivity typical of predictive approaches with the ability to consider virtually all decision options that is at the core of optimization approaches. The ICLIPS model is described as the first IAM that implements the guardrail approach. The representation of climate impacts is a key concern in any IAM. A review of existing IAMs reveals large differences in the coverage of impact sectors, in the choice of the impact numeraire(s), in the consideration of non-climatic developments, including purposeful adaptation, in the handling of uncertainty, and in the inclusion of singular events. IAMs based on an inverse approach impose specific requirements to the representation of climate impacts. This representation needs to combine a level of detail and reliability that is sufficient for the specification of impact guardrails with the conciseness and efficiency that allows for an exploration of the complete domain of plausible climate protection strategies. Large-scale singular events can often be represented by dynamic reduced-form models. This approach, however, is less appropriate for regular impacts where the determination of policy-relevant results generally needs to consider the heterogeneity of climatic, environmental, and socioeconomic factors at the local or regional scale. Climate impact response functions (CIRFs) are identified as the most suitable reduced-form representation of regular climate impacts in the ICLIPS model. A CIRF depicts the aggregated response of a climate-sensitive system or sector as simulated by a spatially explicit sectoral impact model for a representative subset of plausible futures. In the CIRFs presented here, global mean temperature and atmospheric CO2 concentration are used as predictors for global and regional impacts on natural vegetation, agricultural crop production, and water availability. Application of a pattern scaling technique makes it possible to consider the regional and seasonal patterns in the climate anomalies simulated by several general circulation models while ensuring the efficiency of the dynamic model components. Efforts to provide quantitative estimates of future climate impacts generally face a trade-off between the relevance of an indicator for stakeholders and the exactness with which it can be determined. A number of non-monetary aggregated impact indicators for the CIRFs is presented, which aim to strike the balance between these two conflicting goals while taking into account additional constraints of the ICLIPS modelling framework. Various types of impact diagrams are used for the visualization of CIRFs, each of which provides a different perspective on the impact result space. The sheer number of CIRFs computed for the ICLIPS model precludes their comprehensive presentation in this thesis. Selected results referring to changes in the distribution of biomes in different biogeographical regions, in the agricultural potential of various countries, and in the water availability in selected major catchments are discussed. The full set of CIRFs is accessible via the ICLIPS Impacts Tool, a graphical user interface that provides convenient access to more than 100,000 impact diagrams developed for the ICLIPS model. The technical aspects of the software are described as well as the accompanying database of CIRFs. The most important application of CIRFs is in inverse' mode, where they are used to translate impact guardrails into simultaneous constraints for variables from the optimizing ICLIPS climate-economy model. This translation is facilitated by algorithms for the computation of reachable climate domains and for the parameterized approximation of admissible climate windows derived from CIRFs. The comprehensive set of CIRFs, together with these algorithms, enables the ICLIPS model to flexibly explore sets of climate policy strategies that explicitly comply with impact guardrails specified in biophysical units. This feature is not found in any other intertemporally optimizing IAM. A guardrail analysis with the integrated ICLIPS model is described that applies selected CIRFs for ecosystem changes. So-called necessary carbon emission corridors' are determined for a default choice of normative constraints that limit global vegetation impacts as well as regional mitigation costs, and for systematic variations of these constraints. A brief discussion of recent developments in integrated assessment modelling of climate change connects the work presented here with related efforts.
Species respond to environmental change by dynamically adjusting their geographical ranges. Robust predictions of these changes are prerequisites to inform dynamic and sustainable conservation strategies. Correlative species distribution models (SDMs) relate species’ occurrence records to prevailing environmental factors to describe the environmental niche. They have been widely applied in global change context as they have comparably low data requirements and allow for rapid assessments of potential future species’ distributions. However, due to their static nature, transient responses to environmental change are essentially ignored in SDMs. Furthermore, neither dispersal nor demographic processes and biotic interactions are explicitly incorporated. Therefore, it has often been suggested to link statistical and mechanistic modelling approaches in order to make more realistic predictions of species’ distributions for scenarios of environmental change. In this thesis, I present two different ways of such linkage. (i) Mechanistic modelling can act as virtual playground for testing statistical models and allows extensive exploration of specific questions. I promote this ‘virtual ecologist’ approach as a powerful evaluation framework for testing sampling protocols, analyses and modelling tools. Also, I employ such an approach to systematically assess the effects of transient dynamics and ecological properties and processes on the prediction accuracy of SDMs for climate change projections. That way, relevant mechanisms are identified that shape the species’ response to altered environmental conditions and which should hence be considered when trying to project species’ distribution through time. (ii) I supplement SDM projections of potential future habitat for black grouse in Switzerland with an individual-based population model. By explicitly considering complex interactions between habitat availability and demographic processes, this allows for a more direct assessment of expected population response to environmental change and associated extinction risks. However, predictions were highly variable across simulations emphasising the need for principal evaluation tools like sensitivity analysis to assess uncertainty and robustness in dynamic range predictions. Furthermore, I identify data coverage of the environmental niche as a likely cause for contrasted range predictions between SDM algorithms. SDMs may fail to make reliable predictions for truncated and edge niches, meaning that portions of the niche are not represented in the data or niche edges coincide with data limits. Overall, my thesis contributes to an improved understanding of uncertainty factors in predictions of range dynamics and presents ways how to deal with these. Finally I provide preliminary guidelines for predictive modelling of dynamic species’ response to environmental change, identify key challenges for future research and discuss emerging developments.
Long-term bacteria-fungi-plant associations in permafrost soils inferred from palaeometagenomics
(2024)
The arctic is warming 2 – 4 times faster than the global average, resulting in a strong feedback on northern ecosystems such as boreal forests, which cover a vast area of the high northern latitudes. With ongoing global warming, the treeline subsequently migrates northwards into tundra areas. The consequences of turning ecosystems are complex: on the one hand, boreal forests are storing large amounts of global terrestrial carbon and act as a carbon sink, dragging carbon dioxide out of the global carbon cycle, suggesting an enhanced carbon uptake with increased tree cover. On the other hand, with the establishment of trees, the albedo effect of tundra decreases, leading to enhanced soil warming. Meanwhile, permafrost thaws, releasing large amounts of previously stored carbon into the atmosphere. So far, mainly vegetation dynamics have been assessed when studying the impact of warming onto ecosystems. Most land plants are living in close symbiosis with bacterial and fungal communities, sustaining their growth in nutrient poor habitats. However, the impact of climate change on these subsoil communities alongside changing vegetation cover remains poorly understood. Therefore, a better understanding of soil community dynamics on multi millennial timescales is inevitable when addressing the development of entire ecosystems. Unravelling long-term cross-kingdom dependencies between plant, fungi, and bacteria is not only a milestone for the assessment of warming on boreal ecosystems. On top, it also is the basis for agriculture strategies to sustain society with sufficient food in a future warming world.
The first objective of this thesis was to assess ancient DNA as a proxy for reconstructing the soil microbiome (Manuscripts I, II, III, IV). Research findings across these projects enable a comprehensive new insight into the relationships of soil microorganisms to the surrounding vegetation. First, this was achieved by establishing (Manuscript I) and applying (Manuscript II) a primer pair for the selective amplification of ancient fungal DNA from lake sediment samples with the metabarcoding approach. To assess fungal and plant co-variation, the selected primer combination (ITS67, 5.8S) amplifying the ITS1 region was applied on samples from five boreal and arctic lakes. The obtained data showed that the establishment of fungal communities is impacted by warming as the functional ecological groups are shifting. Yeast and saprotroph dominance during the Late Glacial declined with warming, while the abundance of mycorrhizae and parasites increased with warming. The overall species richness was also alternating. The results were compared to shotgun sequencing data reconstructing fungi and bacteria (Manuscripts III, IV), yielding overall comparable results to the metabarcoding approach. Nonetheless, the comparison also pointed out a bias in the metabarcoding, potentially due to varying ITS lengths or copy numbers per genome.
The second objective was to trace fungus-plant interaction changes over time (Manuscripts II, III). To address this, metabarcoding targeting the ITS1 region for fungi and the chloroplast P6 loop for plants for the selective DNA amplification was applied (Manuscript II). Further, shotgun sequencing data was compared to the metabarcoding results (Manuscript III). Overall, the results between the metabarcoding and the shotgun approaches were comparable, though a bias in the metabarcoding was assumed. We demonstrated that fungal shifts were coinciding with changes in the vegetation. Yeast and lichen were mainly dominant during the Late Glacial with tundra vegetation, while warming in the Holocene lead to the expansion of boreal forests with increasing mycorrhizae and parasite abundance. Aside, we highlighted that Pinaceae establishment is dependent on mycorrhizal fungi such as Suillineae, Inocybaceae, or Hyaloscypha species also on long-term scales.
The third objective of the thesis was to assess soil community development on a temporal gradient (Manuscripts III, IV). Shotgun sequencing was applied on sediment samples from the northern Siberian lake Lama and the soil microbial community dynamics compared to ecosystem turnover. Alongside, podzolization processes from basaltic bedrock were recovered (Manuscript III). Additionally, the recovered soil microbiome was compared to shotgun data from granite and sandstone catchments (Manuscript IV, Appendix). We assessed if the establishment of the soil microbiome is dependent on the plant taxon and as such comparable between multiple geographic locations or if the community establishment is driven by abiotic soil properties and as such the bedrock area. We showed that the development of soil communities is to a great extent driven by the vegetation changes and temperature variation, while time only plays a minor role. The analyses showed general ecological similarities especially between the granite and basalt locations, while the microbiome on species-level was rather site-specific. A greater number of correlated soil taxa was detected for deep-rooting boreal taxa in comparison to grasses with shallower roots. Additionally, differences between herbaceous taxa of the late Glacial compared to taxa of the Holocene were revealed.
With this thesis, I demonstrate the necessity to investigate subsoil community dynamics on millennial time scales as it enables further understanding of long-term ecosystem as well as soil development processes and such plant establishment. Further, I trace long-term processes leading to podzolization which supports the development of applied carbon capture strategies under future global warming.
Die Elbe und ihr Einzugsgebiet sind vom Klimawandel betroffen. Um die Wirkkette von projizierten Klimaveränderungen auf den Wasserhaushalt und die daraus resultierenden Nährstoffeinträge und -frachten für große Einzugsgebiete wie das der Elbe zu analysieren, können integrierte Umweltmodellsysteme eingesetzt werden. Fallstudien, die mit diesen Modellsystemen ad hoc durchgeführt werden, repräsentieren den Istzustand von Modellentwicklungen und -unsicherheiten und sind damit statisch.
Diese Arbeit beschreibt den Einstieg in die Dynamisierung von Klimafolgenanalysen im Elbegebiet. Dies umfasst zum einen eine Plausibilitätsprüfung von Auswirkungsrechnungen, die mit Szenarien des statistischen Szenariengenerators STARS durchgeführt wurden, durch den Vergleich mit den Auswirkungen neuerer Klimaszenarien aus dem ISI-MIP Projekt, die dem letzten Stand der Klimamodellierung entsprechen. Hierfür wird ein integriertes Modellsystem mit "eingefrorenem Entwicklungsstand" verwendet. Die Klimawirkungsmodelle bleiben dabei unverändert. Zum anderen wird ein Bestandteil des integrierten Modellsystems – das ökohydrologische Modell SWIM – zu einer "live"-Version weiterentwickelt. Diese wird durch punktuelle Testung an langjährigen Versuchsreihen eines Lysimeterstandorts sowie an aktuellen Abflussreihen validiert und verbessert.
Folgende Forschungsfragen werden bearbeitet: (i) Welche Effekte haben unterschiedliche Klimaszenarien auf den Wasserhaushalt im Elbegebiet und ist eine Neubewertung der Auswirkung des Klimawandels auf den Wasserhaushalt notwendig?, (ii) Was sind die Auswirkungen des Klimawandels auf die Nährstoffeinträge und -frachten im Elbegebiet sowie die Wirksamkeit von Maßnahmen zur Reduktion der Nährstoffeinträge?, (iii) Ist unter der Nutzung (selbst einer sehr geringen Anzahl) verfügbarer tagesaktueller Witterungsdaten in einem stark heterogenen Einzugsgebiet eine valide Ansprache der aktuellen ökohydrologischen Situation des Elbeeinzugsgebiets möglich?
Die aktuellen Szenarien bestätigen die Richtung, jedoch nicht das Ausmaß der Klimafolgen: Die Rückgänge des mittleren jährlichen Gesamtabflusses und der monatlichen Abflüsse an den Pegeln bis Mitte des Jahrhunderts betragen für das STARS-Szenario ca. 30 %. Die Rückgänge bei den auf dem ISI-MIP-Szenario basierenden Modellstudien liegen hingegen nur bei ca. 10 %. Hauptursachen für diese Divergenz sind die Unterschiede in den Niederschlagsprojektionen sowie die Unterschiede in der jahreszeitlichen Verteilung der Erwärmung. Im STARS-Szenario gehen methodisch bedingt die Niederschläge zurück und der Winter erwärmt sich stärker als der Sommer. In dem ISI-MIP-Szenario bleiben die Niederschläge nahezu stabil und die Erwärmung im Sommer und Winter unterscheidet sich nur geringfügig.
Generell nehmen die Nährstoffeinträge und -frachten mit den Abflüssen in beiden Szenarien unterproportional ab, wobei die Frachten jeweils stärker als die Einträge zurückgehen. Die konkreten Effekte der Abflussänderungen sind gering und liegen im einstelligen Prozentbereich. Gleiches gilt für die Unterschiede zwischen den Szenarien. Der Effekt von zwei ausgewählten Maßnahmen zur Reduktion der Nährstoffeinträge und -frachten unterscheidet sich bei verschiedenen Abflussverhältnissen, repräsentiert durch unterschiedliche Klimaszenarien in unterschiedlich feuchter Ausprägung, ebenfalls nur geringfügig.
Die Beantwortung der ersten beiden Forschungsfragen zeigt, dass die Aktualisierung von Klimaszenarien in einem ansonsten "eingefrorenen" Verbund von ökohydrologischen Daten und Modellen eine wichtige Prüfoption für die Plausibilisierung von Klimafolgenanalysen darstellt. Sie bildet die methodische Grundlage für die Schlussfolgerung, dass bei der Wassermenge eine Neubewertung der Klimafolgen notwendig ist, während dies bei den Nährstoffeinträgen und -frachten nicht der Fall ist.
Die zur Beantwortung der dritten Forschungsfrage mit SWIM-live durchgeführten Validierungsstudien ergeben Diskrepanzen am Lysimeterstandort und bei den Abflüssen aus den Teilgebieten Saale und Spree. Sie lassen sich zum Teil mit der notwendigen Interpolationsweite der Witterungsdaten und dem Einfluss von Wasserbewirtschaftungsmaßnahmen erklären. Insgesamt zeigen die Validierungsergebnisse, dass schon die Pilotversion von SWIM-live für eine ökohydrologische Ansprache des Gebietswasserhaushaltes im Elbeeinzugsgebiet genutzt werden kann. SWIM-live ermöglicht eine unmittelbare Betrachtung und Beurteilung simulierter Daten. Dadurch werden Unsicherheiten bei der Modellierung direkt offengelegt und können infolge dessen reduziert werden. Zum einen führte die Verdichtung der meteorologischen Eingangsdaten durch die Verwendung von nun ca. 700 anstatt 19 Klima- bzw. Niederschlagstationen zu einer Verbesserung der Ergebnisse. Zum anderen wurde SWIM-live beispielhaft für einen Zyklus aus punktueller Modellverbesserung und flächiger Überprüfung der Simulationsergebnisse genutzt.
Die einzelnen Teilarbeiten tragen jeweils zur Dynamisierung von Klimafolgenanalysen im Elbegebiet bei. Der Anlass hierfür war durch die fehlerhaften methodischen Grundlagen von STARS gegeben. Die Sinnfälligkeit der Dynamisierung ist jedoch nicht an diesen konkreten Anlass gebunden, sondern beruht auf der grundlegenden Einsicht, dass Ad-hoc-Szenarienanalysen immer auch pragmatische Vereinfachungen zugrunde liegen, die fortlaufend überprüft werden müssen.
Animal movement is a crucial aspect of life, influencing ecological and evolutionary processes. It plays an important role in shaping biodiversity patterns, connecting habitats and ecosystems. Anthropogenic landscape changes, such as in agricultural environments, can impede the movement of animals by affecting their ability to locate resources during recurring movements within home ranges and, on a larger scale, disrupt migration or dispersal. Inevitably, these changes in movement behavior have far-reaching consequences on the mobile link functions provided by species inhabiting such extensively altered matrix areas. In this thesis, I investigate the movement characteristics and activity patterns of the European hare (Lepus europaeus), aiming to understand their significance as a pivotal species in fragmented agricultural landscapes. I reveal intriguing results that shed light on the importance of hares for seed dispersal, the influence of personality traits on behavior and space use, the sensitivity of hares to extreme weather conditions, and the impacts of GPS collaring on mammals' activity patterns and movement behavior.
In Chapter I, I conducted a controlled feeding experiment to investigate the potential impact of hares on seed dispersal. By additionally utilizing GPS data of hares in two contrasting landscapes, I demonstrated that hares play a vital role, acting as effective mobile linkers for many plant species in small and isolated habitat patches. The analysis of seed intake and germination success revealed that distinct seed traits, such as density, surface area, and shape, profoundly affect hares' ability to disperse seeds through endozoochory. These findings highlight the interplay between hares and plant communities and thus provide valuable insights into seed dispersal mechanisms in fragmented landscapes.
By employing standardized behavioral tests in Chapter II, I revealed consistent behavioral responses among captive hares while simultaneously examining the intricate connection between personality traits and spatial patterns within wild hare populations. This analysis provides insights into the ecological interactions and dynamics within hare populations in agricultural habitats. Examining the concept of animal personality, I established a link between personality traits and hare behavior. I showed that boldness, measured through standardized tests, influences individual exploration styles, with shy and bold hares exhibiting distinct space use patterns. In addition to providing valuable insights into the role of animal personality in heterogeneous environments, my research introduced a novel approach demonstrating the feasibility of remotely assessing personality types using animal-borne sensors without additional disturbance of the focal individual.
While climate conditions severely impact the activity and, consequently, the fitness of wildlife species across the globe, in Chapter III, I uncovered the sensitivity of hares to temperature, humidity, and wind speed during their peak reproduction period. I found a strong response in activity to high temperatures above 25°C, with a particularly pronounced effect during temperature extremes of over 35°C. The non-linear relationship between temperature and activity was characterized by contrasting responses observed for day and night. These findings emphasize the vulnerability of hares to climate change and the potential consequences for their fitness and population dynamics with the ongoing rise of temperature.
Since such insights can only be obtained through capturing and tagging free-ranging animals, I assessed potential impacts and the recovery process post-collar attachment in Chapter IV. For this purpose, I examined the daily distances moved and the temporal-associated activity of 1451 terrestrial mammals out of 42 species during their initial tracking period. The disturbance intensity and the speed of recovery varied across species, with herbivores, females, and individuals captured and collared in relatively secluded study areas experiencing more pronounced disturbances due to limited anthropogenic influences.
Mobile linkers are essential for maintaining biodiversity as they influence the dynamics and resilience of ecosystems. Furthermore, their ability to move through fragmented landscapes makes them a key component for restoring disturbed sites. Individual movement decisions determine the scale of mobile links, and understanding variations in space use among individuals is crucial for interpreting their functions. Climate change poses further challenges, with wildlife species expected to adjust their behavior, especially in response to high-temperature extremes, and comprehending the anthropogenic influence on animal movements will remain paramount to effective land use planning and the development of successful conservation strategies.
This thesis provides a comprehensive ecological understanding of hares in agricultural landscapes. My research findings underscore the importance of hares as mobile linkers, the influence of personality traits on behavior and spatial patterns, the vulnerability of hares to extreme weather conditions, and the immediate consequences of collar attachment on mammalian movements. Thus, I contribute valuable insights to wildlife conservation and management efforts, aiding in developing strategies to mitigate the impact of environmental changes on hare populations. Moreover, these findings enable the development of methodologies aimed at minimizing the impacts of collaring while also identifying potential biases in the data, thereby benefiting both animal welfare and the scientific integrity of localization studies.
The relationship between climate and forest productivity is an intensively studied subject in forest science. This Thesis is embedded within the general framework of future forest growth under climate change and its implications for the ongoing forest conversion. My objective is to investigate the future forest productivity at different spatial scales (from a single specific forest stand to aggregated information across Germany) with focus on oak-pine forests in the federal state of Brandenburg. The overarching question is: how are the oak-pine forests affected by climate change described by a variety of climate scenarios. I answer this question by using a model based analysis of tree growth processes and responses to different climate scenarios with emphasis on drought events. In addition, a method is developed which considers climate change uncertainty of forest management planning.
As a first 'screening' of climate change impacts on forest productivity, I calculated the change in net primary production on the base of a large set of climate scenarios for different tree species and the total area of Germany. Temperature increases up to 3 K lead to positive effects on the net primary production of all selected tree species. But, in water-limited regions this positive net primary production trend is dependent on the length of drought periods which results in a larger uncertainty regarding future forest productivity. One of the regions with the highest uncertainty of net primary production development is the federal state of Brandenburg.
To enhance the understanding and ability of model based analysis of tree growth sensitivity to drought stress two water uptake approaches in pure pine and mixed oak-pine stands are contrasted. The first water uptake approach consists of an empirical function for root water uptake. The second approach is more mechanistic and calculates the differences of soil water potential along a soil-plant-atmosphere continuum. I assumed the total root resistance to vary at low, medium and high total root resistance levels. For validation purposes three data sets on different tree growth relevant time scales are used. Results show that, except the mechanistic water uptake approach with high total root resistance, all transpiration outputs exceeded observed values. On the other hand high transpiration led to a better match of observed soil water content. The strongest correlation between simulated and observed annual tree ring width occurred with the mechanistic water uptake approach and high total root resistance. The findings highlight the importance of severe drought as a main reason for small diameter increment, best supported by the mechanistic water uptake approach with high root resistance. However, if all aspects of the data sets are considered no approach can be judged superior to the other. I conclude that the uncertainty of future productivity of water-limited forest ecosystems under changing environmental conditions is linked to simulated root water uptake.
Finally my study aimed at the impacts of climate change combined with management scenarios on an oak-pine forest to evaluate growth, biomass and the amount of harvested timber. The pine and the oak trees are 104 and 9 years old respectively. Three different management scenarios with different thinning intensities and different climate scenarios are used to simulate the performance of management strategies which explicitly account for the risks associated with achieving three predefined objectives (maximum carbon storage, maximum harvested timber, intermediate). I found out that in most cases there is no general management strategy which fits best to different objectives. The analysis of variance in the growth related model outputs showed an increase of climate uncertainty with increasing climate warming. Interestingly, the increase of climate-induced uncertainty is much higher from 2 to 3 K than from 0 to 2 K.
The evolution of life on Earth has been driven by disturbances of different types and magnitudes over the 4.6 million years of Earth’s history (Raup, 1994, Alroy, 2008). One example for such disturbances are mass extinctions which are characterized by an exceptional increase in the extinction rate affecting a great number of taxa in a short interval of geologic time (Sepkoski, 1986). During the 541 million years of the Phanerozoic, life on Earth suffered five exceptionally severe mass extinctions named the “Big Five Extinctions”. Many mass extinctions are linked to changes in climate
(Feulner, 2009). Hence, the study of past mass extinctions is not only intriguing, but can also provide insights into the complex nature of the Earth system. This thesis aims at deepening our understanding of the triggers of mass extinctions and how they affected life. To accomplish this, I investigate changes in climate during two of the Big Five extinctions using a coupled climate model.
During the Devonian (419.2–358.9 million years ago) the first vascular plants and vertebrates evolved on land while extinction events occurred in the ocean (Algeo et al., 1995). The causes of these formative changes, their interactions and their links to changes in climate are still poorly understood. Therefore, we explore the sensitivity of the Devonian climate to various boundary conditions using an intermediate-complexity climate model (Brugger et al., 2019). In contrast to Le Hir et al. (2011), we find only a minor biogeophysical effect of changes in vegetation cover due to unrealistically high soil albedo values used in the earlier study. In addition, our results cannot support the strong influence of orbital parameters on the Devonian climate, as simulated with a climate model with a strongly simplified ocean model (De Vleeschouwer et al., 2013, 2014, 2017). We can only reproduce the changes in Devonian climate suggested by proxy data by decreasing atmospheric CO2. Still, finding agreement between the evolution of sea surface temperatures reconstructed from proxy data (Joachimski et al., 2009) and our simulations remains challenging and suggests a lower δ18O ratio of Devonian seawater. Furthermore, our study of the sensitivity of the Devonian climate reveals a prevailing mode of climate variability on a timescale of decades to centuries. The quasi-periodic ocean temperature fluctuations are linked to a physical mechanism of changing sea-ice cover, ocean convection and overturning in high northern latitudes.
In the second study of this thesis (Dahl et al., under review) a new reconstruction of atmospheric CO2 for the Devonian, which is based on CO2-sensitive carbon isotope fractionation in the earliest vascular plant fossils, suggests a much earlier drop of atmo- spheric CO2 concentration than previously reconstructed, followed by nearly constant CO2 concentrations during the Middle and Late Devonian. Our simulations for the Early Devonian with identical boundary conditions as in our Devonian sensitivity study (Brugger et al., 2019), but with a low atmospheric CO2 concentration of 500 ppm, show no direct conflict with available proxy and paleobotanical data and confirm that under the simulated climatic conditions carbon isotope fractionation represents a robust proxy for atmospheric CO2. To explain the earlier CO2 drop we suggest that early forms of vascular land plants have already strongly influenced weathering. This new perspective on the Devonian questions previous ideas about the climatic conditions and earlier explanations for the Devonian mass extinctions.
The second mass extinction investigated in this thesis is the end-Cretaceous mass extinction (66 million years ago) which differs from the Devonian mass extinctions in terms of the processes involved and the timescale on which the extinctions occurred. In the two studies presented here (Brugger et al., 2017, 2021), we model the climatic effects of the Chicxulub impact, one of the proposed causes of the end-Cretaceous extinction, for the first millennium after the impact. The light-dimming effect of stratospheric sulfate aerosols causes severe cooling, with a decrease of global annual mean surface air temperature of at least 26◦C and a recovery to pre-impact temperatures after more than 30 years. The sudden surface cooling of the ocean induces deep convection which brings nutrients from the deep ocean via upwelling to the surface ocean. Using an ocean biogeochemistry model we explore the combined effect of ocean mixing and iron-rich dust originating from the impactor on the marine biosphere. As soon as light levels have recovered, we find a short, but prominent peak in marine net primary productivity. This newly discovered mechanism could result in toxic effects for marine near-surface ecosystems. Comparison of our model results to proxy data (Vellekoop et al., 2014, 2016, Hull et al., 2020) suggests that carbon release from the terrestrial biosphere is required in addition to the carbon dioxide which can be attributed to the target material. Surface ocean acidification caused by the addition of carbon dioxide and sulfur is only moderate. Taken together, the results indicate a significant contribution of the Chicxulub impact to the end-Cretaceous mass extinction by triggering multiple stressors for the Earth system.
Although the sixth extinction we face today is characterized by human intervention in nature, this thesis shows that we can gain many insights into future extinctions from studying past mass extinctions, such as the importance of the rate of change (Rothman, 2017), the interplay of multiple stressors (Gunderson et al., 2016), and changes in the carbon cycle (Rothman, 2017, Tierney et al., 2020).
International migration has been an increasing phenomenon during the past decades and has involved all the regions of the globe. Together with fertility and mortality rates, net migration rates represent the components that fully define the demographic evolution of the population in a country. Therefore, being able to capture the patterns of international migration flows and to produce projections of how they might change in the future is of relevant importance for demographic studies and for designing policies informed on the potential scenarios. Existing forecasting methods do not account explicitly for the main drivers and processes shaping international migration flows: existing migrant communities at the destination country, termed diasporas, would reduce the costs of migration and facilitate the settling for new migrants, ultimately producing a positive feedback; accounting for the heterogeneity in the type of migration flows, e.g. return and transit Ćows, becomes critical in some specific bilateral migration channels; in low- to middle- income countries economic development could relax poverty constraint and result in an increase of emigration rates.
Economic conditions at both origin and destination are identified as major drivers of international migration. At the same time, climate change impacts have already appeared on natural and human-made systems such as the economic productivity. These economic impacts might have already produced a measurable effect on international migration flows. Studies that provide a quantification of the number of migration moves that might have been affected by climate change are usually specific to small regions, do not provide a mechanistic understanding of the pathway leading from climate change to migration and restrict their focus to the effective induced flows, disregarding the impact that climate change might have had in inhibiting other flows.
Global climate change is likely to produce impacts on the economic development of the countries during the next decades too. Understanding how these impacts might alter future global migration patterns is relevant for preparing future societies and understanding whether the response in migration flows would reduce or increase population's exposure to climate change impacts.
This doctoral research aims at investigating these questions and fill the research gaps outlined above. First, I have built a global bilateral international migration model which accounts explicitly for the diaspora feedback, distinguishes between transit and return flows, and accounts for the observed non-linear effects that link emigration rates to income levels in the country of origin. I have used this migration model within a population dynamic model where I account also for fertility and mortality rates, producing hindcasts and future projections of international migration flows, covering more than 170 countries. Results show that the model reproduces past patterns and trends well. Future projections highlight the fact that,depending on the assumptions regarding future evolution of income levels and between-country inequality, migration at the end of the century might approach net zero or be still high in many countries. The model, parsimonious in the explanatory variables that includes, represents a versatile tool for assessing the impacts of different socioeconomic scenarios on international migration.
I consider then a counterfactual past without climate change impacts on the economic productivity. By prescribing these counterfactual economic conditions to the migration model I produce counterfactual migration flows for the past 30 years. I compare the counterfactual migration flows to factual ones, where historical economic conditions are used to produce migration flows. This provides an estimation of the recent international migration flows attributed to climate change impacts. Results show that a counterfactual world without climate change would have seen less migration globally. This effect becomes larger if I consider separately the increase and decrease in migration moves: a Ągure of net change in the migration flows is not representative of the effective magnitude of the climate change impact on migration. Indeed, in my results climate change produces a divergent effect on richer and poorer countries: by slowing down the economic development, climate change might have reduced international mobility from and to countries of the Global South, and increased it from and to richer countries in the Global North.
I apply the same methodology to a scenario of future 3℃ global warming above pre-industrial conditions. I Ąnd that climate change impacts, acting by reorganizing the relative economic attractiveness of destination countries or by affecting the economic growth in the origin, might produce a substantial effect in international migration flows, inhibiting some moves and inducing others.
Overall my results suggest that climate change might have had and might have in the future a significant effect on global patterns of international migration. It also emerges clearly that, for a comprehensive understanding of the effects of climate change on international migration, we need to go beyond net effects and consider separately induced and inhibited flows.