Lycian salamanders (genus Lyciasalamandra) constitute an exceptional case of microendemism of an amphibian species on the Asian Minor mainland. These viviparous salamanders are confined to karstic limestone formations along the southern Anatolian coast and some islands. We here study the genetic differentiation within and among 118 populations of all seven Lyciasalamandra species across the entire genus’ distribution. Based on circa 900 base pairs of fragments of the mitochondrial 16SrDNA and ATPase genes, we analysed the spatial haplotype distribution as well as the genetic structure and demographic history of populations. We used 253 geo-referenced populations and CHELSA climate data to infer species distribution models which we projected on climatic conditions of the Last Glacial Maximum (LGM). Within all but one species, distinct phyloclades were identified, which only in parts matched current taxonomy. Most haplotypes (78%) were private to single populations. Sometimes population genetic parameters showed contradicting results, although in several cases they indicated recent population expansion of phyloclades. Climatic suitability of localities currently inhabited by salamanders was significantly lower during the LGM compared to recent climate. All data indicated a strong degree of isolation among Lyciasalamandra populations, even within phyloclades. Given the sometimes high degree of haplotype differentiation between adjacent populations, they must have survived periods of deteriorated climates during the Quaternary on the spot. However, the alternative explanation of male biased dispersal combined with a pronounced female philopatry can only be excluded if independent nuclear data confirm this result.

In order to discuss potential sustainability issues of expanding silage maize cultivation in Rhineland-Palatinate, spatially explicit monitoring is necessary. Publicly available statistical records are often not a sufficient basis for extensive research, especially on soil health, where risk factors like erosion and compaction depend on variables that are specific to every site, and hard to generalize for larger administrative aggregates. The focus of this study is to apply established classification algorithms to estimate maize abundance for each independent pixel, while at the same time accounting for their spatial relationship. Therefore, two ways to incorporate spatial autocorrelation of neighboring pixels are combined with three different classification models. The performance of each of these modeling approaches is analyzed and discussed. Finally, one prediction approach is applied to the imagery, and the overall predicted acreage is compared to publicly available data. We were able to show that Support Vector Machine (SVM) classification and Random Forests (RF) were able to distinguish maize pixels reliably, with kappa values well above 0.9 in most cases. The Generalized Linear Model (GLM) performed substantially worse. Furthermore, Regression Kriging (RK) as an approach to integrate spatial autocorrelation into the prediction model is not suitable in use cases with millions of sparsely clustered training pixels. Gaussian Blur is able to improve predictions slightly in these cases, but it is possible that this is only because it smoothes out impurities of the reference data. The overall prediction with RF classification combined with Gaussian Blur performed well, with out of bag error rates of 0.5% in 2009 and 1.3% in 2016. Despite the low error rates, there is a discrepancy between the predicted acreage and the official records, which is 20% in 2009 and 27% in 2016.

It is well-known that katabatic winds can be detected as warm signatures in the surface temperature over the slopes of the Antarctic ice sheets. For appropriate synoptic forcing and/or topographic channeling, katabatic surges occur, which result in warm signatures also over adjacent ice shelves. Moderate Resolution Imaging Spectroradiometer (MODIS) ice surface temperature (IST) data are used to detect warm signatures over the Antarctic for the winter periods 2002–2017. In addition, high-resolution (5 km) regional climate model data is used for the years of 2002 to 2016. We present a case study and a climatology of wind-induced IST anomalies for the Ross Ice Shelf and the eastern Weddell Sea. The IST anomaly distributions show maxima around 10–15K for the slopes, but values of more than 25K are also found. Katabatic surges represent a strong climatological signal with a mean warm anomaly of more than 5K on more than 120 days per winter for the Byrd Glacier and the Nimrod Glacier on the Ross Ice Shelf. The mean anomaly for the Brunt Ice Shelf is weaker, and exceeds 5K on about 70 days per winter. Model simulations of the IST are compared to the MODIS IST, and show a very good agreement. The model data show that the near-surface stability is a better measure for the response to the wind than the IST itself.

Background In light of the current biodiversity crisis, DNA barcoding is developing into an essential tool to quantify state shifts in global ecosystems. Current barcoding protocols often rely on short amplicon sequences, which yield accurate identification of biological entities in a community but provide limited phylogenetic resolution across broad taxonomic scales. However, the phylogenetic structure of communities is an essential component of biodiversity. Consequently, a barcoding approach is required that unites robust taxonomic assignment power and high phylogenetic utility. A possible solution is offered by sequencing long ribosomal DNA (rDNA) amplicons on the MinION platform (Oxford Nanopore Technologies). Findings Using a dataset of various animal and plant species, with a focus on arthropods, we assemble a pipeline for long rDNA barcode analysis and introduce a new software (MiniBar) to demultiplex dual indexed Nanopore reads. We find excellent phylogenetic and taxonomic resolution offered by long rDNA sequences across broad taxonomic scales. We highlight the simplicity of our approach by field barcoding with a miniaturized, mobile laboratory in a remote rainforest. We also test the utility of long rDNA amplicons for analysis of community diversity through metabarcoding and find that they recover highly skewed diversity estimates. Conclusions Sequencing dual indexed, long rDNA amplicons on the MinION platform is a straightforward, cost-effective, portable, and universal approach for eukaryote DNA barcoding. Although bulk community analyses using long-amplicon approaches may introduce biases, the long rDNA amplicons approach signifies a powerful tool for enabling the accurate recovery of taxonomic and phylogenetic diversity across biological communities.

In the context of accelerated global socio-environmental change, the Water-Energy-Food Nexus has received increasing attention within science and international politics by promoting integrated resource governance. This study explores the scientific nexus debates from a discourse analytical perspective to reveal knowledge and power relations as well as geographical settings of nexus research. We also investigate approaches to socio-nature relations that influence nexus research and subsequent political implications. Our findings suggest that the leading nexus discourse is dominated by natural scientific perspectives and a neo-Malthusian framing of environmental challenges. Accordingly, the promoted cross-sectoral nexus approach to resource governance emphasizes efficiency, security, future sustainability, and poverty reduction. Water, energy, and food are conceived as global trade goods that require close monitoring, management and control, to be achieved via quantitative assessments and technological interventions. Within the less visible discourse, social scientific perspectives engage with the social, political, and normative elements of the Water-Energy-Food Nexus. These perspectives criticize the dominant nexus representation for itsmanagerial, neoliberal, and utilitarian approach to resource governance. The managerial framing is critiqued for masking power relations and social inequalities, while alternative framings acknowledge the political nature of resource governance and socio-nature relations. The spatial dimensions of the nexus debate are also discussed. Notably, the nexus is largely shaped by western knowledge, yet applied mainly in specific regions of the Global South. In order for the nexus to achieve integrative solutions for sustainability, the debate needs to overcome its current discursive and spatial separations. To this end, we need to engage more closely with alternative nexus discourses, embrace epistemic pluralism and encourage multi-perspective debates about the socio-nature relations we actually intend to promote.

This thesis is focused on improving the knowledge on a group of threatened species, the European cave salamanders (genus Hydromantes). There are three main sections gathering studies dealing with different topics: Ecology (first part), Life traits (second part) and Monitoring methodologies (third part). First part starts with the study of the response of Hydromantes to the variation of climatic conditions, analysing 15 different localities throughout a full year (CHAPTER I; published in PEERJ in August 2015). After that, the focus moves on identify which is the operative temperature that these salamander experience, including how their body respond to variation of environmental temperature. This study was conducted using one of the most advanced tool, an infrared thermocamera, which gave the opportunity to perform detailed observation on salamanders body (CHAPTER II; published in JOURNAL OF THERMAL BIOLOGY in June 2016). In the next chapter we use the previous results to analyse the ecological niche of all eight Hydromantes species. The study mostly underlines the mismatch between macro- and microscale analysis of ecological niche, showing a weak conservatism of ecological niches within the evolution of species (CHAPTER III; unpublished manuscript). We then focus only on hybrids, which occur within the natural distribution of mainland species. Here, we analyse if the ecological niche of hybrids shows divergences from those of parental species, thus evaluating the power of hybrids adaptation (CHAPTER IV; unpublished manuscript). Considering that hybrids may represent a potential threat for parental species (in terms of genetic erosion and competition), we produced the first ecological study on an allochthonous mixed population of Hydromantes, analysing population structure, ecological requirements and diet. The interest on this particular population mostly comes by the fact that its members are coming from all three mainland Hydromantes species, and thus it may represent a potential source of new hybrids (CHAPTER V; accepted in AMPHIBIA-REPTILIA in October 2017). The focus than moves on how bioclimatic parameters affect species within their distributional range. Using as model species the microendemic H. flavus, we analyse the relationship between environmental suitability and local abundance of the species, also focusing on all intermediate dynamics which provide useful information on spatial variation of individual fitness (CHAPTER VI; submitted to SCIENTIFIC REPORTS in November 2017). The first part ends with an analysis of the interaction between Hydromantes and Batracobdella algira leeches, the only known ectoparasite for European cave salamanders. Considering that the effect of leeches on their hosts is potentially detrimental, we investigated if these ectoparasites may represent a further threat for Hydromantes (CHAPTER VII; submitted to INTERNATIONAL JOURNAL FOR PARASITOLOGY: PARASITES AND WILDLIFE in November 2017). The second part is related to the reproduction of Hydromantes. In the first study we perform analyses on the breeding behaviour of several females belonging to a single population, identifying differences and similarities occurring in cohorting females (CHAPTER VIII; published in NORTH-WESTERN JOURNAL OF ZOOLOGY in December 2015). In the second study we gather information from all Hydromantes species, analysing size and development of breeding females, and identifying a relationship between breeding time and climatic conditions (CHAPTER IX; submitted to SALAMANDRA in June 2017). In the last part of this thesis, we analyse two potential methods for monitoring Hydromantes populations. In the first study we evaluate the efficiency of the marking method involving Alpha tags (CHAPTER X; published in SALAMANDRA in October 2017). In the second study we focus on evaluating N-mixtures models as a methodology for estimating abundance in wild populations (CHAPTER XI; submitted to BIODIVERSITY & CONSERVATION in October 2017).

The availability of data on the feeding habits of species of conservation value may be of great importance to develop analyses for both scientific and management purposes. Stomach flushing is a harmless technique that allowed us to collect extensive data on the feeding habits of six Hydromantes species. Here, we present two datasets originating from a three-year study performed in multiple seasons (spring and autumn) on 19 different populations of cave salamanders. The first dataset contains data of the stomach content of 1,250 salamanders, where 6,010 items were recognized; the second one reports the size of the intact prey items found in the stomachs. These datasets integrate considerably data already available on the diet of the European plethodontid salamanders, being also of potential use for large scale meta-analyses on amphibian diet.

Ziel der Dissertation ist es, den Hochwasserschutz und das Management extremer Hoch-wasser für das Einzugsgebiet der Isar zu verbessern mit Hinblick darauf, wie sich vorhandene und neu zu schaffende Retentionsräume mit optimaler Wirkung für das gesamte Flusssystem einsetzen lassen. Dafür sind Kenntnisse über extreme Ereignisse und deren Auswirkung auf die betrachteten Einzugsgebiete notwendig. Großskalige Niederschläge in Mitteleuropa werden überwiegend durch Vb-artige Zugbahnen ausgelöst. Die Relevanz für Bayern zeigt die Auswertung des neuesten Kataloges der Vb-Zugbahnen für den Zeitraum 1959 bis 2015. In den Monaten April bis Oktober haben Vb-Zugbahnen zu ca. 30 % der beobachten Hochwasser beigetragen. Im Sommer führt sogar jedes zweite Vb-Tief zu Hochwasser. Im Donaueinzugsgebiet können 50 % der 20 größten Hochwasser direkt auf Vb-Zugbahnen zurückgeführt werden, weitere 25 % durch ähnliche Zugbahnen oder auf eine Vb aktiven Phase. Über die Hälfe der größten Hochwasser traten dabei in Bezug zu einer Serie von Vb-Tiefs auf. 60 % der Vb-Zugbahnen sind Teil einer Serie von Vb-Tiefs. Aus wiederkehrenden Niederschlägen persistenter Zugbahnen resultieren mehrgipflige Hochwasserwellen, die insbesondere für Rückhalteräume betrachtet werden müssen (DIN 19700). Die Detailuntersuchung erfolgt unter besonderer Beachtung der Untersuchungen zu den Vb-Zugbahnen. Das Isareinzugsgebiet mit 8900 km-² besitzt mit den Seen im Voralpenland große natürliche Retentionsräume und mit dem Sylvensteinspeicher im alpinen Einzugsgebiet den größten staatlichen Speicher Bayerns. Für die Wirkungsanalyse von gekoppelten Hoch-wasserrückhalteräumen in komplexen Einzugsgebieten müssen Ganglinien mit einem Nie-derschlag-Abfluss-Modell generiert werden, die den Wellenablauf des Hochwassers im ge-samten Einzugsgebiet repräsentieren. Die Dissertation analysiert, wie sich der Einsatz ver-schiedener Verfahren zur Vorgabe der Eingangsniederschläge auswirkt. Dabei liegt der Schwerpunkt der Untersuchung auf dem Niederschlagsverlauf. Es wird ein Verfahren zur Ableitung von Ganglinien aus standardisierten beobachteten Niederschlagsverläufen entwi-ckelt. Die Hochwasserganglinien, generiert aus synthetischen Niederschlagsverläufen der Bemessung, werden am Beispiel des Sylvensteinspeichers mit den drei größten abgelaufe-nen Hochwasserereignissen verglichen und diskutiert, ob mit dem neuen Verfahren die Cha-rakteristik der beobachten Hochwasser besser wiedergeben wird. Der Fokus liegt dabei auf der Wellenüberlagerung. Es kann für das ganze Gebiet gezeigt werden, dass die mit der neuen Methode standardisierten beobachteten Niederschlagsverläufe besser geeignet sind, die Wellenüberlagerung wiederzugeben, da zeitliche Unterschiede durch die Staueffekte an den Alpen berücksichtigt werden, wie sie bei Vb-Zugbahn geprägten Niederschlägen entste-hen. Es kann daher bei ähnlichen Fragestellungen empfohlen werden, diese Methode in der Praxis als Variante hinzuzuziehen, um die natürlichen Prozesse repräsentativer zu beschrei-ben. Für die Simulation mit dem N-A-Modell LARSIM werden die Unsicherheiten durch Varianten-rechnungen gezeigt. Es hat sich herausgestellt, dass nicht nur der Niederschlagsverlauf und die Vorbedingungen des Ereignisses eine große Auswirkung auf die Kalibrierung der Ab-flussbeiwerte im N-A-Modell haben, sondern auch das gewählte Flood-Routing-Verfahren und die Gerinnerauheit. Schließlich wird die Bewertung der potenziellen Standorte durchgeführt. Es wird berechnet, wo das Hochwasser zurückgehalten werden muss, um sowohl eine lokale Reduktion des Hochwasserscheitels, als auch gleichzeitig eine möglichst große Schutzwirkung für das Ge-samtsystem zu ermöglichen. Priorisiert werden Rückhaltestandorte, die praktisch umsetzbar sind und den größten Nutzen haben. Die Untersuchung einer Doppelwelle, die durch eine Serie von Vb-Zugbahnen entstehen kann, zeigt, wie die Einschätzung potenzieller Standorte verändern kann. Der alpine und zum Teil der voralpine Raum reagieren mit kurzen steilen Ganglinien und sind gegenüber Doppelwellen weniger sensitiv, weil kaum Wellenüberlagerung entsteht. Für den Sylvensteinspeicher, der im alpinen Raum liegt, können daher kurze Niederschlagspausen für eine schnelle Entlastung des Speicherraumes genutzt werden. Un-terhalb von Seen mit einem großen Retentionsvermögen erzeugen Doppelwellen aufgrund der langen Retentionsäste durch die Wellenüberlagerung deutlich höhere Abflüsse als Ein-zelwellen. Rückhalt an der oberen Isar ist unter diesen Kriterien am optimalsten. Empfohlene Maßnahmen - ohne Bauaufwand - konnten bereits umgesetzt werden und verbessern den Hochwasserschutz und das Hochwassermanagement an der Isar. Die Auswertungen zeigen, dass in den Monaten April, Mai, September und Oktober die Hochwasserereignisse in Folge von Vb-Zugbahnen im Zuge der Klimaveränderung häufiger und in den Sommermonaten extremer werden könnten.

Water-deficit stress, usually shortened to water- or drought stress, is one of the most critical abiotic stressors limiting plant growth, crop yield and quality concerning food production. Today, agriculture consumes about 80-90% of the global freshwater used by humans and about two thirds are used for crop irrigation. An increasing world population and a predicted rise of 1.0-2.5-°C in the annual mean global temperature as a result of climate change will further increase the demand of water in agriculture. Therefore, one of the most challenging tasks of our generation is to reduce the amount water used per unit yield to satisfy the second UN Sustainable Development Goal and to ensure global food security. Precision agriculture offers new farming methods with the goal to improve the efficiency of crop production by a sustainable use of resources. Plant responses to water stress are complex and co-occur with other environmental stresses under natural conditions. In general, water stress causes plant physiological and biochemical changes that depend on the severity and the duration of the actual plant water deficit. Stomatal closure is one of the first responses to plant water stress causing a decrease in plant transpiration and thus an increase in plant temperature. Prolonged or severe water stress leads to irreversible damage to the photosynthetic machinery and is associated with decreasing chlorophyll content and leaf structural changes (e.g., leaf rolling). Since a crop can already be irreversibly damaged by only mild water deficit, a pre-visual detection of water stress symptoms is essential to avoid yield loss. Remote sensing offers a non-destructive and spatio-temporal method for measuring numerous physiological, biochemical and structural crop characteristics at different scales and thus is one of the key technologies used in precision agriculture. With respect to the detection of plant responses to water stress, the current state-of-the-art hyperspectral remote sensing imaging techniques are based on measurements of thermal infrared emission (TIR; 8-14 -µm), visible, near- and shortwave infrared reflectance (VNIR/SWIR; 0.4-2.5 -µm), and sun-induced fluorescence (SIF; 0.69 and 0.76 -µm). It is, however, still unclear how sensitive these techniques are with respect to water stress detection. Therefore, the overall aim of this dissertation was to provide a comparative assessment of remotely sensed measures from the TIR, SIF, and VNIR/SWIR domains for their ability to detect plant responses to water stress at ground- and airborne level. The main findings of this thesis are: (i) temperature-based indices (e.g., CWSI) were most sensitive for the detection of plant water stress in comparison to reflectance-based VNIR/SWIR indices (e.g., PRI) and SIF at both, ground- and airborne level, (ii) for the first time, spectral emissivity as measured by the new hyperspectral TIR instrument could be used to detect plant water stress at ground level. Based on these findings it can be stated that hyperspectral TIR remote sensing offers great potential for the detection of plant responses to water stress at ground- and airborne level based on both TIR key variables, surface temperature and spectral emissivity. However, the large-scale application of water stress detection based on hyperspectral TIR measures in precision agriculture will be challenged by several problems: (i) missing thresholds of temperature-based indices (e.g., CWSI) for the application in irrigation scheduling, (ii) lack of current TIR satellite missions with suitable spectral and spatial resolution, (iii) lack of appropriate data processing schemes (including atmosphere correction and temperature emissivity separation) for hyperspectral TIR remote sensing at airborne- and satellite level.

This study aims to estimate the cotton yield at the field and regional level via the APSIM/OZCOT crop model, using an optimization-based recalibration approach based on the state variable of the cotton canopy - the leaf area index (LAI), derived from atmospherically corrected Landsat-8 OLI remote sensing images in 2014. First, a local sensitivity and global analysis approach was employed to test the sensitivity of cultivar, soil and agronomic parameters to the dynamics of the LAI. After sensitivity analyses, a series of sensitive parameters were obtained. Then, the APSIM/OZCOT crop model was calibrated by observations over a two-year span (2006-2007) at the Aksu station, combined with these sensitive cultivar parameters and the current understanding of cotton cultivar parameters. Third, the relationship between the observed in-situ LAI and synchronous perpendicular vegetation indices derived from six Landsat-8 OLI images covering the entire growth stage was modelled to generate LAI maps in time and space. Finally, the Particle Swarm Optimization (PSO) and general-purpose optimization approach (based on Nelder-Mead algorithm) were used to recalibrate four sensitive agronomic parameters (row spacing, sowing density per row, irrigation amount and total fertilization) according to the minimization of the root-mean-square deviation (RMSE) between the simulated LAI from the APSIM/OZCOT model and retrieved LAI from Landsat-8 OLI remote sensing images. After the recalibration, the best simulated results compared with observed cotton yield were obtained. The results showed that: (1) FRUDD, FLAI and DDISQ were the major cultivar parameters suitable for calibrating the cotton cultivar. (2) After the calibration, the simulated LAI performed well with an RMSE and mean absolute error (MAE) of 0.45 and 0.33, respectively, in 2006 and 0.46 and 0.41, respectively, in 2007. The coefficient of determination between the observed and simulated LAI was 0.83 and 0.97, respectively, in 2006 and 2007. The Pearson- correlation coefficient was 0.913 and 0.988 in 2006 and 2007, respectively, with a significant positive correlation between the simulated and observed LAI. The difference between the observed and simulated yield was 776.72 kg/ha and 259.98 kg/ha in 2006 and 2007, respectively. (3) Cotton cultivation in 2014 was obtained using three Landsat-8 OLI images - DOY136 (May), DOY 168 (June) and DOY 200 (July) - based on the phenological differences in cotton and other vegetation types. (4) The yield estimation after the assimilation closely approximated the field-observed values, and the coefficient of determination was as high as 0.82, after recalibration of the APSIM/OZCOT model for ten cotton fields. The difference between the observed and assimilated yields for the ten fields ranged from 18.2 to 939.7 kg/ha. The RMSE and MAE between the assimilated and observed yield was 417.5 and 303.1 kg/ha, respectively. These findings provide scientific evidence for the feasibility of coupled remote sensing and APSIM/OZCOT model at the field level. (5) Upscaling from field level to regional level, the assimilation algorithm and scheme are both especially important. Although the PSO method is very efficient, the computational efficiency is also the shortcoming of the assimilation strategy on a regional scale. Comparisons between the PSO and general-purpose optimization method (based on the Nelder-Mead algorithm) were implemented from the RSME, LAI curve and computational time. The general-purpose optimization method (based on the Nelder-Mead algorithm) was used for the regional assimilation between remote sensing and the APSIM/OZCOT model. Meanwhile, the basic unit for regional assimilation was also determined as cotton field rather than pixel. Moreover, the crop growth simulation was also divided into two phases (vegetative growth and reproductive growth) for regional assimilation. (6) The regional assimilation at the vegetative growth stage between the remote sensing derived and APSIM/OZCOT model-simulated LAI was implemented by adjusting two parameters: row spacing and sowing density per row. The results showed that the sowing density of cotton was higher in the southern part than in the northern part of the study area. The spatial pattern of cotton density was also consistent with the reclamation from 2001 to 2013. Cotton fields after early reclamation were mainly located in the southern part while the recent reclamation was located in the northern part. Poor soil quality, lack of irrigation facilities and woodland belts of cotton fields in the northern part caused the low density of cotton. Regarding the row spacing, the northern part was larger than the southern part due to the variation of two agronomic modes from military and private companies. (7) The irrigation and fertilization amount were both used as key parameters to be adjusted for regional assimilation during the reproductive growth period. The result showed that the irrigation per time ranged from 58.14 to 89.99 mm in the study area. The spatial distribution of the irrigation amount is higher in the northern part while lower in southern study area. The application of urea fertilization ranged from 500.35 to 1598.59 kg/ha in the study area. The spatial distribution of fertilization was lower in the northern part and higher in the southern part. More fertilization applied in the southern study area aims to increase the boll weight and number for pursuing higher yields of cotton. The frequency of the RSME during the second assimilation was mainly located in the range of 0.4-0.6 m2/m2. The estimated cotton yield ranged from 1489 to 8895 kg/ha. The spatial distribution of the estimated yield is also higher in the southern part than the northern study area.