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Oligotrophic catchments with short spatey streams, upland lakes and peaty soils characterise northwest European Atlantic coastal regions. These catchments are important biodiversity refuges, particularly for sensitive diadromous fish populations but are subject to changes in land use and land management practices associated with afforestation, agriculture and rural development. Quantification of the degree of catchment degradation resulting from such anthropogenic impacts is often limited by a lack of long-term baseline data in what are generally relatively isolated, poorly studied catchments. This research uses a combination of palaeolimnological (radiometrically-dated variations in sedimentary geochemical elements, pollen, diatoms and remains of cladocera), census, and instrumental data, along with hindcast estimates to quantify environmental changes and their aquatic impacts since the late 19th century. The most likely drivers of any change are also identified. Results confirm an aquatic biotic response (phyto- and zooplankton) to soil erosion and nutrient enrichment associated with the onset of commercial conifer afforestation, effects that were subsequently enhanced as a result of increased overgrazing in the catchment and, possibly, climate warming. The implications for the health of aquatic resources in the catchment are discussed Environmental Protection Agency in Ireland (ILLUMINATE 2005-W-MS-40, P.McGinnity was supported by the Beaufort Marine Research Award in Fish Population Genetics funded by the Irish Government under the Sea Change Programme.

The SmartBay NIAP fund was made available in 2012 through Dublin City University over a two year period to enable researchers to access the SmartBay Ireland National Test and Demonstration Facility in Galway Bay. Research proposals were invited for funding under a number of activity types that are in line with the objectives of the SmartBay PRTLI Cycle 5 programme. This fund provided small awards (typically €2-25K) to research teams through a national competitive process, which was open to all higher education institutions on the island of Ireland. There were both open and biannual calls. The SmartBay NIAP fund was established to enable researchers in academia and industry to access the SmartBay Ireland national test and demonstration infrastructure. Proposals to access the infrastructure were brief and required information on the researcher(s), a description of the proposed research and its potential impact to the research team arising from the access to SmartBay Ireland. Marine Institute

Research in the field of precision agriculture is becoming increasingly important due to the growing world population whilst area for cultivation remains constant or declines. In this context, methods of monitoring in?season plant development with high resolution and accuracy are necessary. Studies show that terrestrial laser scanning (TLS) can be applied to capture small objects like crops. In this contribution, the results of multi-temporal field campaigns with the terrestrial laser scanner Riegl LMS-Z420i are shown. Four surveys were carried out in the growing period 2012 on a field experiment where various barley varieties were cultivated in small-scale plots. In order to measure the plant height above ground, the TLS-derived point clouds are interpolated to generate Crop Surface Models with a very high resolution of 1 cm. For all campaigns, a common reference surface, representing the Digital Elevation Model was used to monitor plant height in the investigated period. Manual plant height measurements were carried out to verify the results. The very high coefficients of determination (R² = 0.89) between both measurement methods show the applicability of the approach presented. Furthermore, destructive biomass sampling was performed to investigate the relation to plant height. Biomass is an important parameter for evaluating the actual crop status, but non-destructive methods of directly measuring crop biomass do not exist. Hence, other parameters like reflectance are considered. The focus of this study is on non-destructive measurements of plant height. The high coefficients of determination between plant height and fresh as well as dry biomass (R² = 0.80, R² = 0.77) support the usability of plant height as a predictor. The study presented here demonstrates the applicability of TLS in monitoring plant height development with a very high spatial resolution. Proceedings of the Workshop on UAV-based Remote Sensing Methods for Monitoring Vegetation Kölner geographische Arbeiten, 94 ISSN:0454-1294

Modern conceptions of progress, based on the dominant Cartesian reductionist paradigm, are associated with a linear drive towards ever greater ascendancy, order, organisation, homogeneity, hegemony, performance, efficiency, and control. Similarly modern conceptions of progress are associated with positivist approaches to overcoming and extinguishing disorder, inchoateness, uncertainty, redundancy and risk. In this framework, diversity is conceived as a threat to system organisation, efficiency and control. Many contemporary conceptions of sustainability and sustainable development, framed within this paradigm, envisage sustainability as aligning with such ideas of progress. By this narrative, sustainable systems are achievable through ever greater efficiency, through for example, technological prowess, improved organisational structure/control, taming of “big data” and through risk reduction/extinction. Similarly, corporate sustainability would be advanced through growth, mergers and acquisitions, rationalisation, pruning of smaller operations/sites within firms, layoffs, increased corporate control, accountability and managerialism. “Bigger is better” is the apposite maxim. From a complex systems perspective however, a very different picture is evident. In the ecological domain, sustainable ecosystems have been quantitatively shown to be those which maintain an appropriate (context, time and space dependent) dynamic balance between opposing tendencies of ascendancy and efficiency on one hand and diversity and redundancy on the other (Ulanowicz, 2009; Goerner et al., 2009). Ecological biodiversity is an absolute requirement for ecosystem endurance since it facilitates system resilience in the event of significant perturbation (whether sudden shock or longer term stress). For example, a species which can feed on a selection of available prey species is more resilient against partial ecosystem destruction/prey extinction than one which relies on a single species for food. While the latter scenario represents a situation of greater efficiency, it is also more rigid and less resilient. Moreover, while the tendencies of complex systems towards ascendancy (organisation, efficiency) and disorder (redundancy, diversity) are antagonistic at local levels, they are in fact mutually dependent at higher levels (Ulanowicz et al, 2009): “A requisite for the increase in effective orderly performance (ascendency) is the existence of flexibility (reserve) within the system. Conversely, systems that are highly constrained and at peak performance (in the second law sense of the word) dissipate external gradients at ever higher gross rates”. This model has been mirrored across techno-economic and social domains wherein similar sustainability models have been proposed (e.g. Stirling, 2011). This framework has manifested itself in research outputs across virtually every discipline, where in different guises sustainable and persistent systems have been shown to require a balance between tendencies of control, structure and organisation and those of diversity and disorder.

Organic soils develop under waterlogged conditions, leading to a reduced decomposition of biomass. Over the last millennia this led to the development of a large carbon (C) pool in the global C cycle. Drainage, necessary for agriculture and forestry, triggers rapid decomposition of soil organic matter (SOM). While undisturbed organic soils are C-sinks, drainage transforms them into C-sources. Climate, drainage depth and land-use are considered the main factors controlling SOM decomposition. However, there is still a large variation in decomposition rates among organic soils, even when climate, drainage and land-use conditions are similar. This thesis investigates the role of SOM composition on peat decomposability in a variety of differently managed drained organic soils. Peat samples from 21 organic soils managed as cropland, grassland and forest soils situated in Switzerland were incubated at 10 and 20 °C for more than 6 months. During incubation, we monitored CO2 emissions and related them to soil characteristics, including bulk density, soil pH, soil organic carbon (SOC) content, and elemental ratios (C/N, H/C and O/C). The incubated samples lost between 0.6 to 1.9% of their SOC at 10 °C and between 1.2 to 42% at 20 °C over the course of 10,000 h (>1 yr). This huge variation occurring under controlled conditions suggests that, besides drainage depth, climate and management, SOM composition is an underestimated factor that determines CO2 fluxes measured in field experiments. In contrast, correlations between the investigated soil characteristics and CO2 emissions were weak. Furthermore, there were no land-use effects. Such effects were expected based on the measured SOM characteristics and IPCC data. Temperature sensitivity of decomposition decreased with depth, indicating an enrichment of recalcitrant SOM in topsoils. This finding stands in contrast to findings in studies of undisturbed organic soils and Further it suggests that future C loss from agriculturally managed organic soils will be similar considering warmer climate conditions. Cultivation of organic soils is accompanied by inputs of young organic carbon (YOC) from plant residues. The amount of YOC inputs, their potential to compensate for oxidative peat loss as well as their lability are unknown. Studying the δ13C signatures in the topsoil of a managed organic soil revealed that at least 19 ± 2.4% of the SOC originate from YOC being accumulated recently. Yet, the accumulation rates are substantially smaller than average peat loss rates on the studied soils. Remarkably, the percentage of YOC in decomposing SOC was 53 ± 0.1%, indicating that YOC is more labile than bulk SOC. These findings are supported by the 14C age of emitted CO2 being younger than that of SOC. Inputs of fresh organic matter (FOM) to soil are known to induce priming effects, i.e. an altered decomposition of resident SOM. The effect of FOM addition on peat decomposition of agriculturally used organic soils has seldom been quantified experimentally. Therefore, we incubated soil samples from managed organic soils over three weeks with and without adding corn straw as FOM. The 13C and 14C signatures of SOC and emitted CO2 enabled us to apportion the amount of decomposed corn, as well as to estimate relative effects of corn addition on the decomposition of SOC from old peat and from YOC. FOM addition induced negative, positive and neutral priming of SOC decomposition. Further, the relative contribution of peat SOC to the overall CO2 release consistently decreased after FOM addition, suggesting that young and old C pools in managed organic soils respond differently to the addition of fresh plant residues. A combination of those two findings indicates that FOM addition can effectively reduce the decomposition of old peat. The results of this thesis suggest that agricultural use of organic soils has a tremendous effect on the composition and decomposability of SOC in organic soils. Furthermore, they show that also crop species known for their carbon sequestration potential are not likely to counteract peat losses caused by drainage. Therefore, agricultural management of organic soils without the risk of losing vast amounts of SOC seems unrealistic and thus, CO2 emissions from organic soils are not likely to decrease in the future. This means that they remain a big issue of concern for future generations in order to counteract climate change.

Tree mortality is a key factor for understanding forest dynamics. So far, however, only few studies have focused on the mortality of tree regeneration. Thus, more research is needed in this context to better understand the underlying ecological processes and predict more reliably how forest ecosystems will respond to ongoing climate change. As the current and future changes are expected to either favor or impair the growth and survival of large trees, it is pivotal to investigate the effects on the next generation, i.e. young and small trees. A better understanding of tree regeneration allows to extend or adapt the findings from the already well-studied adult, large trees to small-sized trees, for which sparse empirical data are available. Particularly relevant questions relate to the drivers of survival probabilities and of horizontal spatial patterns (i.e. the distribution in space) of tree regeneration. The aims of this PhD thesis therefore were (i) to improve the understanding of natural mortality processes of tree regeneration at different developmental stages and spatio-temporal scales, (ii) to investigate the effect of various abiotic and biotic factors on the mortality of tree regeneration, and (iii) to study the relationship between mortality, growth and site conditions. For this purpose, I assessed 1) the effect of emergence time, height and number of leaves of seedlings, light availability, temperature, precipitation, seedbed and microsite conditions on the survival time of seedlings; 2) the effect of light availability on the growth of saplings and its relationship with mortality; and 3) the effect of topography and of large neighboring trees on the spatial pattern of living and dead small trees. These effects were investigated for small-sized trees (diameter at breast height < 10 cm) of both conifer and deciduous species at several study sites in Switzerland across elevational gradients that represent distinct climate regimes and growth conditions. In Chapter 1, I studied the effects of emergence time on the mortality of seedlings. The underlying rationale was that global warming is expected to advance the timing of germination, leading the seedlings to potentially experience more severe damage and mortality due to late frost events in spring. Thus, I monitored the emergence, characteristics, and survival of seedlings across ten tree species in temperate mixed deciduous forests around Zurich (Switzerland) over one and a half years. For each seedling, I recorded characteristics such as height, number of cotyledons and euphylls, cause and severity of possible damages, and extent of missing foliar tissue due to herbivory. Moreover, I documented the seedbed type of each seedling and that of the microsite at the plot level. For each plot, I also determined light availability using hemispherical canopy photographs, logged the temperature curve, and measured soil moisture. Based on the empirical data, I conducted a survival analysis using the Kaplan-Meier method to estimate survival curves and Cox’s proportional hazards model to assess the effects of the explanatory variables on survival time. I tested whether the timing of emergence represents a trade‐off for seedling survival between minimizing frost risk and maximizing the length of the growing period. Seedlings that emerged early faced a severe late frost event. Nevertheless, they benefited from the overall longer growing period, resulting in increased overall survival. Larger seedling height and higher number of leaves positively influenced survival. Seedlings growing on moss had higher survival compared to those growing on mineral soil, litter, or in herbaceous vegetation. Since almost two‐thirds of the monitored seedlings died during the first growing season and early-emerging seedlings were more likely to survive, this chapter highlights how the first months of life together with an early emergence time of seedlings are decisive for successful tree regeneration, which will ultimately have an impact on the future development of forest stands. In Chapter 2, I investigated whether radial and vertical growth rates are suitable indicators of impending mortality in young trees, as previous research on adult, large trees had suggested, and whether light availability and tree size have an influence on mortality probability. Thus, I sampled an equal number of living and dead saplings of four conifer species (Swiss stone pine, European larch, Norway spruce and silver fir) in nine mountain forests along an elevational gradient of the Swiss Alps. I performed a tree-ring analysis, calculated both radial and vertical growth rates and compared them between living and dead saplings based on tree-ring widths reconstructed from stem disks at multiple tree heights. I observed a divergent pattern in radial growth of living and dead saplings, with reduced growth of dead saplings starting several years prior to death, which emphasizes the importance of long-term predisposing factors for tree mortality. Then, I quantified the combined effects of light availability, growth and tree size on mortality, using species- and site-specific conditional logistic regression models, by previously matching living and dead saplings of similar ages. Light availability influenced positively the survival probabilities of conifer saplings in mountain forests, although the positive effect decreased with increasing elevation. Recent radial growth rate and diameter had only minor effects on sapling mortality. By highlighting the importance of long-term predisposing factors for the mortality of conifer saplings in mountain forests, this chapter extends well-established findings of the adult stage to the so far little investigated sapling stage. In Chapter 3, I analyzed the horizontal spatial patterns of small living and dead Norway spruce trees in two subalpine forest reserves of Switzerland, Scatlè and Bödmerenwald, by nearest neighbor-based and distance-based analyses. I accounted for spatial inhomogeneity by investigating how the local densities of living and dead small trees depend on environmental covariates. I found that the local density of living and dead small trees is influenced by latitude, elevation and aspect. Yet, the influence of these covariates varied between the two forest reserves due to their different topography and peculiar site conditions. Then, I considered neighborhood interactions between trees based on the vicinity and size of trees, by analyzing how small trees are influenced by large neighboring trees over a range of spatial scales. Both tree vicinity and size were important for the spatial patterns of small trees in both reserves. Small living trees showed a random pattern around large dead trees over a range of distances and, at certain distances in one reserve, even dispersion. Small living trees further showed clustering around large living trees at short distances and dispersion at large distances. Small dead trees featured mainly a random pattern, even though with a tendency to cluster at short distances around large neighbors, irrespective of whether these were living or dead. Yet, the fading of clustering with increasing distance indicates that the influence of large trees on small trees varies with the distance and thus that the neighborhood interactions between trees are scale-dependent. I further found that the influence of large neighboring trees on small trees varied with topography, revealing a relationship between spatial inhomogeneity and neighborhood interactions, as I expected due to the strongly different tree sizes and environmental gradients in mountain forests. Overall, this chapter emphasizes the importance of considering both spatial inhomogeneity and neighborhood interactions when investigating the spatial ecology of mortality of small-sized trees in uneven-aged and unmanaged mountain forests. Throughout this PhD thesis, I extended well-established ecological findings from the adult, large trees to the regeneration stage of trees, which is an important bottleneck of forest dynamics. The empirical findings of my PhD thesis represent a considerable contribution towards a better understanding of the temporal and spatial patterns of mortality in tree regeneration as well as of the relationship between mortality, growth and site conditions.

Hydropower is the world’s most important renewable electricity source. More than 40% of European hydroelectric energy is produced in Alpine countries. High-head storage hydropower plants (HPP) contribute significantly to peak energy production as well as electricity grid regulation. Future plant management is faced with several challenges concerning modified availability of water resources due to climate change as well as new economic constraints associated with legal, political and electricity market issues. HPP operation results in unsteady water release to the downstream river system. Hydropeaking is the primary factor of flow regime alteration, impacting the river ecosystem. Even when the biological response to hydropeaking is not fully understood, the recently adapted law on water protection prescribes its mitigation in Switzerland. In this research project, a novel integrative approach to model and assess the impact of the operation of a complex hydropower scheme on the downstream river system is developed. It contains (1) a precipitation-runoff model extended for long-term simulations of glacierized Alpine catchment areas, (2) an operation tool for high-head storage HPP, (3) flow regime generation with cost estimation of hydropeaking mitigation measures and (4) a habitat model of reference river morphologies for a target species. The upper Aare River (Hasliaare) in Switzerland is an Alpine stream, affected by hydropeaking from a complex hydropower scheme with several storage volumes and power houses. Since the 1930s, seasonal water transfer from summer to winter and the amplitude and frequency of daily peak discharge have been continuously increased. Furthermore, the dynamic braided river network with various mesohabitats gave way to a mainly monotonous channel. Although diversity of species and biomass of aquatic biota have drastically decreased, the potential of redevelopment remains. Investigations to improve the river morphology and the flow regime are under discussion. The upper Aare River catchment is therefore an appropriate case study for analysis of the interactions between climatic, hydrological, hydraulic, economic as well as ecological parameters. The simulation of runoff in Alpine catchment areas is essential for optimal hydropower exploitation under normal flow conditions, but also for the analysis of flood events. The semi-distributed conceptual modeling approach Routing System contains a reservoir-based precipitation-runoff transformation model (GSM-SOCONT), extended by dynamic glacier simulation tool. Spatial precipitation and temperature distributions are taken into account for simulating the relevant hydrological processes, such as glacier melt, snowpack constitution and melt, soil infiltration and runoff. The model development, calibration and validation are illustrated for the 2005 flood event, where the flood reduction capacity of the HPP is discussed, as well as future long-term runoff estimations. Climate change scenarios, based on a reference climate period, take into account intra-annual temperature and precipitation variations as well as their long-term tendencies. Runoff series of daily resolution are produced by hourly updating of the meteorological, glaciological and hydrological parameters. An almost complete deglacierization of the upper Aare River basin is simulated for the late 21st century. The resulting reduction of glacier melt in summer and earlier snowmelt in spring change the runoff regime from glacio-nival to nival. The implemented heuristic hydropower modeling tool in Routing System allows simulation of the operating mode of complex HPP. Within the case study of the upper Aare River catchment and despite the complexity of the HPP network, the influence of climate change, electricity market issues, plant enhancements as well as hydropeaking constraints is simulated and assessed. Despite the reduction of future runoff, increased flexibility due to new turbine and pumped-storage capacities allows compensation, especially in the case of volatile electricity prices, and could even partially restore the natural flow regime. Several operational and construction measures to reduce hydropeaking are implemented in the model. Resulting flow regimes as well as the related costs are defined. Operational constraints, such as limitation of turbine discharge, increase of residual flow or limited drawdown range, generate relatively high costs compared to their environmental effectiveness. Better ecological and economic response is achieved by construction measures, such as flow deviation systems or compensation basins installed downstream of the power house outflow where the water is temporarily stored and then released to the river by a guided system. The simulated flow regimes are rated by a river specific habitat model for representative morphologies and three life stages of the target species brown trout (Salmo trutta fario). This is based on results from a 2D hydrodynamic model and in situ investigations undertaken in the framework of a joint project of EAWAG. Steady and dynamic indicators quantify fish habitat suitability and allow comparison through economic indices of the implemented mitigation measures. For the Hasliaare River, investments for mitigation of hydropeaking are only justified by morphological improvements. The developed approach is useful for the enhancement of complex storage hydropower schemes regarding mitigation of altered flow regimes. Despite several uncertainties, it allows operators, authorities and researchers to define and rate the impact of HPP operation on the river network, to ecologically and economically assess mitigation measures and thus to address hydropeaking in a straightforward manner.

Aimed at deepening the understanding of the effects of climate variability on cocoa pro-duction in West Africa, conditions between 1959 and 2015 are analyzed based on new data sets of meteorological records, soil water content and evapotranspiration. Comparing the relationship of actual and potential evapotranspiration across the region, differences be-tween cocoa producing countries are found and discussed, affirming that cocoa producing regions in Ghana and Nigeria are the most restricted by water availability. Further, us-ing a machine learning approach (Maxent) the optimal climatic conditions for successful cultivation are determined and used in a model to assess climatic suitability. It is shown, that the precipitation during the driest month of the year is the most specific predictor of production suitability. The model overall predicts the area suitable for cocoa production with high accuracy (AUC = 0.983). Applying the model to climatic data from past years the average suitability is calculated for every county and year. Comparing its yearly vari-ability with reported yield commonalities are observed, but farming practices are found to affect the recorded yield more significantly. Further, the suitability time series shows large areas in Nigeria, Liberia and along the northern borders of the cocoa producing area being vulnerable to prolonged poor weather conditions. These areas are expected to profit most from measures aimed at increasing climate resilience.

In this study, we investigate changes in temperature and precipitation extremes over West and Central Africa (hereafter, WAF domain) as a function of global mean temperature with a focus on the implications of global warming of 1.5 °C and 2 °C according the Paris Agreement. We applied a scaling approach to capture changes in climate extremes with increase in global mean temperature in several subregions within the WAF domain: Western Sahel, Central Sahel, Eastern Sahel, Guinea Coast and Central Africa including Congo Basin. While there are several uncertainties and large ensemble spread in the projections of temperature and precipitation indices, most models show high-impact changes in climate extremes at subregional scale. At these smaller scales, temperature increases within the WAF domain are projected to be higher than the global mean temperature increase (at 1.5 °C and at 2 °C) and heat waves are expected to be more frequent and of longer duration. The most intense warming is observed over the drier regions of the Sahel, in the central Sahel and particularly in the eastern Sahel, where the precipitation and the soil moisture anomalies have the highest probability of projected increase at a global warming of 1.5 °C. Over the wetter regions of the Guinea Coast and Central Africa, models project a weak change in total precipitation and a decrease of the length of wet spells, while these two regions have the highest increase of heavy rainfall in the WAF domain at a global warming of 1.5 °C. Western Sahel is projected by 80% of the models to experience the strongest drying with a significant increase in the length of dry spells and a decrease in the standardized precipitation evapotranspiration index. This study suggests that the 'dry gets drier, wet gets wetter' paradigm is not valid within the WAF domain. Environmental Research Letters, 13 (6) ISSN:1748-9326 ISSN:1748-9318