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The reduction of information contained in model time series through the use of aggregating statistical performance measures is very high compared to the amount of information that one would like to draw from it for model identification and calibration purposes. It is readily known that this loss imposes important limitations on model identification and -diagnostics and thus constitutes an element of the overall model uncertainty as essentially different model realizations with almost identical performance measures (e.g. r-² or RMSE) can be generated. In three consecutive studies the present work proposes an alternative approach towards hydrological model evaluation based on the application of Self-Organizing Maps (SOM; Kohonen, 2001). The Self-Organizing Map is a type of artificial neural network and unsupervised learning algorithm that is used for clustering, visualization and abstraction of multidimensional data. It maps vectorial input data items with similar patterns onto contiguous locations of a discrete low-dimensional grid of neurons. The iterative training of the SOM causes the neurons to form a discrete, data-compressed representation of the high-dimensional input data. Using appropriate visualization techniques, information on distributions, patterns and relationships in complex data sets can be extracted. Irrespective of their potential, SOM applications have earned very little attention in hydrological modelling compared to other artificial neural network techniques. Therefore, the aim of the present work is to demonstrate that the application of Self-Organizing Maps has very high potential to address fundamental issues of model evaluation: It is shown that the clustering and classification of model time series by means of SOM can provide useful insights into model behaviour. In combination with the diagnostic properties of Signature Indices (Gupta et al., 2008; Yilmaz et al., 2008) SOM provides a novel tool for interpreting the model parameters in the hydrological context and identifying parameter sets that simultaneously meet multiple objectives, even if the corresponding model realizations belong to different models. Moreover, the presented studies and reviews also encourage further studies on the application of SOM in hydrological modelling.
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.
This cumulative thesis encompass three studies focusing on the Weddell Sea region in the Antarctic. The first study produces and evaluates a high quality data set of wind measurements for this region. The second study produces and evaluates a 15 year regional climate simulation for the Weddell Sea region. And the third study produces and evaluates a climatology of low level jets (LLJs) from the simulation data set. The evaluations were done in the attached three publications and the produced data sets are published online.
In 2015/2016, the RV Polarstern undertook an Antarctic expedition in the Weddell Sea. We operated a Doppler wind lidar on board during that time running different scan patterns. The resulting data was evaluated, corrected, processed and we derived horizontal wind speed and directions for vertical profiles with up to 2 km height. The measurements cover 38 days with a temporal resolution of 10-15 minutes. A comparisons with other radio sounding data showed only minor differences.
The resulting data set was used alongside other measurements to evaluate temperature and wind of simulation data. The simulation data was produced with the regional climate model CCLM for the period of 2002 to 2016 for the Weddell Sea region. Only smaller biases were found except for a strong warm bias during winter near the surface of the Antarctic Plateau. Thus we adapted the model setup and were able to remove the bias in a second simulation.
This new simulation data was then used to derive a climatology of low level jets (LLJs). Statistics of occurrence frequency, height and wind speed of LLJs for the Weddell Sea region are presented along other parameters. Another evaluation with measurements was also performed in the last study.
Considering actual climatic and land use changes the problem of available water resources or the estimation of potential flood risks gain eco-political and economical relevance. Adequate assessments, thus, require precise process-based hydrological knowledge. Spatially distributed hydrological modelling enables a both abstractive and realistic description of hydrological processes, and therefore contributes to the understanding of the hydrological system- responses. Referring to the example of the mesoscale Ruwer basin (a tributary to the Mosel river), a modified version of the distributive modelling system PRMS/MMS (Precipitation Runoff Modeling System/Modular Modeling System) is applied to calculate spatially and temporally explicit water budgets. To achieve modelling results as precise as possible, integration of detailed land use information (spatial distribution of the existing land use classes, crop- and site-specific growth patterns) is necessary. This information is derived here by analysis of multitemporal, geometrically and radiometrically pre-processed Landsat TM-data. This enables separation of different land use classes and differentiated quantification of the leaf area index (LAI). The LAI is estimated by a spectral unmixing approach using statistically optimized endmember sets, referring to the example of winter grain and grassland plots. As a result, numerical inputs (coefficients for calculating evapotranspiration, interception storages) and extracted non-numerical (classified) information can be provided for hydrological modelling. The version of PRMS applied in this study allows important land use terms to be parameterized in high temporal resolution. Using model input derived from the available satellite data, simulation results are obtained that prove to be realistic compared to gauge data and with respect to their spatial differentiation. Results differ significantly from those obtained by using parameters from literature or by experience without distinguishing specific and site-dependent growth patterns. It can be concluded that the quality of modelling results notably improves by integration and quantitative analysis of remote sensing data; thus, these methods are a significant contribution to physically-based hydrological modelling.
Die in einem Einzugsgebiet herrschende räumliche Inhomogenität wird im Wasserhaushaltsmodell LARSIM (Large Area Runoff Simulation Modell) in den einzelnen Modellkomponenten unterschiedlich stark berücksichtigt. Insbesondere die räumliche Verteilung der Abflussprozesse wurde bisher nicht berücksichtigt, weil keine flächenhaft verfügbare Information über eben diese Verteilung vorlag. Für das Einzugsgebiet der Nahe liegt nun seit dem Jahr 2007 eine Bodenhydrologische Karte vor, die flächenhaft den bei ausreichenden Niederschlägen zu erwartenden Abflussprozess ausweist. In der vorliegenden Dissertation wird die Nutzung dieser Prozessinformation bei der Parametrisierung des Bodenmoduls von LARSIM beschrieben: Für drei Prozessgruppen " gesättigter Oberflächenabfluss, Abfluss im Boden, Tiefenversickerung " werden mittels zweier neuer Parameter P_Bilanz und P_Dämpfung inhomogene Parametersätze aus empirisch ermittelten Kennfeldern gewählt, um die Prozessinformation bei der Abflussbildung im Modell zu berücksichtigen. Für die Abbildung der Prozessintensitäten in den Gebietsspeichern werden zwei unterschiedliche Ansätze vorgestellt, die sich in ihrer Komplexität unterscheiden. In der ersten Variante werden fünf Oberflächenabflussspeicher für unterschiedlich schnell reagierende Prozessgruppen eingeführt, in der zweiten Variante wird der erste Ansatz mit dem ursprünglichen Schwellenwert zur Aufteilung in schnelle und langsame Oberflächenabflusskomponenten kombiniert. Es wird gezeigt, dass die Parametrisierung mit den beiden neuen Parametern P_Bilanz und P_Dämpfung einfacher, effektiver und effizienter ist, da beide Parameter minimale Interaktionen aufweisen und in ihrer Wirkungsweise leicht verständlich sind, was auf die ursprünglichen Bodenparameter nicht zutrifft. Es wird ein Arbeitsfluss vorgestellt, in dem die neuen Parameter in Kombination mit Signature Measures und unterschiedlichen Darstellungen der Abflussdauerlinie gemeinsam genutzt werden können, um in wenigen Arbeitsschritten eine Anpassung des Modells in neuen Einzugsgebieten vorzunehmen. Die Methode wurde durch Anwendung in drei Gebieten validiert. In den drei Gebieten konnte in wenigen Kalibrierungsschritten die Simulationsgüte der ursprünglichen Version erreicht und " je nach Zielsetzung " übertroffen werden. Hinsichtlich der Gütemaße zeigte sich bei der Variante, in der die Gebietsspeicher nicht modifiziert wurden, aber kein eindeutiges Bild, ob die ursprüngliche Parametrisierung oder die neue grundsätzlich überlegen ist. Neben der Auswertung der Validierungszeiträume wurden dabei auch die simulierten Ganglinien in geschachtelten Gebieten betrachtet. Die Version, in der die Gebietsspeicher modifiziert wurden, zeigt hingegen vor allem im Validierungszeitraum tendenziell bessere Simulationsergebnisse. Hinsichtlich der Abbildung der Abflussprozesse ist das neue Verfahren dem alten deutlich überlegen: Es resultiert in plausiblen Anteilen von Abflusskomponenten, deren Verteilung und Abhängigkeit von Speicherkapazitäten, Landnutzungen und Eingangsdaten systematisch ausgewertet wurden. Es zeigte sich, dass vor allem die Speicherkapazität des Bodens einen signifikanten Einfluss hat, der aber im hydrologischen Sinn richtig und hinsichtlich der Modellannahmen plausibel ist. Es wird deutlich gemacht, dass die Einschränkungen, die sich ergeben haben, aufgrund der Modellannahmen zustande kommen, und dass ohne die Änderung dieser Annahmen keine bessere Abbildung möglich ist. Für die Zukunft werden Möglichkeiten aufgezeigt, wie die Annahmen modifiziert werden können, um eine bessere Abbildung zu erzielen, indem der bereits bestehende Infiltrationsansatz in die Methode integriert wird.
Nonlocal operators are used in a wide variety of models and applications due to many natural phenomena being driven by nonlocal dynamics. Nonlocal operators are integral operators allowing for interactions between two distinct points in space. The nonlocal models investigated in this thesis involve kernels that are assumed to have a finite range of nonlocal interactions. Kernels of this type are used in nonlocal elasticity and convection-diffusion models as well as finance and image analysis. Also within the mathematical theory they arouse great interest, as they are asymptotically related to fractional and classical differential equations.
The results in this thesis can be grouped according to the following three aspects: modeling and analysis, discretization and optimization.
Mathematical models demonstrate their true usefulness when put into numerical practice. For computational purposes, it is important that the support of the kernel is clearly determined. Therefore nonlocal interactions are typically assumed to occur within an Euclidean ball of finite radius. In this thesis we consider more general interaction sets including norm induced balls as special cases and extend established results about well-posedness and asymptotic limits.
The discretization of integral equations is a challenging endeavor. Especially kernels which are truncated by Euclidean balls require carefully designed quadrature rules for the implementation of efficient finite element codes. In this thesis we investigate the computational benefits of polyhedral interaction sets as well as geometrically approximated interaction sets. In addition to that we outline the computational advantages of sufficiently structured problem settings.
Shape optimization methods have been proven useful for identifying interfaces in models governed by partial differential equations. Here we consider a class of shape optimization problems constrained by nonlocal equations which involve interface-dependent kernels. We derive the shape derivative associated to the nonlocal system model and solve the problem by established numerical techniques.
Auf der Grundlage von bodenphysikalischen Standortdaten wurden mit dem physikalisch basierten Modell CATFLOW Bodenwassergehalte und Abflussprozesse von verschiedenen Standorten im Mesozoikum der Trierer Bucht auf der Plotskale simuliert. Die Standorte unterscheiden sich durch das Ausgangssubstrat der Bodenbildung (lehmig-tonig, schluffig-sandig) und die Landnutzung (Acker, Grünland, Wald). Für die Modellvalidierung standen wöchentliche Bodenwassergehaltsmessungen, monatliche Sickerwassersummen aus Lysimetermessungen und Oberflächen- und Zwischenabflusskurven von Beregnungsversuchen zur Verfügung. Ziel der Arbeit ist es zu untersuchen, inwieweit Retentionseigenschaften, Abflussprozesse und Abflussmengen aus Standortdaten ohne eine weitere Kalibrierung des Modells abgeleitet werden können. Besonderer Wert wird dabei auf die Parametrisierung des Bodens gelegt. Das Modell simuliert den Wassertransport in der Bodenmatrix über die zweidimensionale Richardsgleichung und den schnellen Wassertransport in Makroporen über ein einfaches Bulk-Modell. Daneben werden Oberflächenrauhigkeit, Durchwurzelungstiefe und Vegetationsbedeckung im Jahresgang berücksichtigt. Um den Einfluss von unterschiedlichen Parametrisierungen des Bodens aufzuzeigen, werden verschiedene Parametrisierungsvarianten untersucht. Die van Genuchten/Mualem-Parameter, welche die Retentions- und Leitfähigkeitseigenschaften der einzelnen Bodenhorizonte beschreiben, wurden zum einen über die Bodenart und Trockenrohdichte bestimmt und zum anderen über die Anpassung von Retentionskurven an im Labor bestimmte Punkte der Wasserspannungskurve ermittelt. Die Ergebnisse der Simulationen für die Standorte mit Bodenfeuchtemessung zeigen, dass mit dem Modell der Jahresgang der Bodenfeuchte prinzipiell nachvollzogen werden kann. Jedoch führt keine der drei Parametrisierungsvarianten zu einer eindeutigen Überlegenheit bei der Simulationsgüte. Um neben den üblichen Gütemaßen ein weiteres Kriterium für den Erfolg oder Misserfolg einer Standortsimulation zu gewinnen, wurden die Simulationsergebnisse mit den Messwerten der anderen Standorte verglichen. An vier von zehn Standorten führt der Vergleich der Messwerte mit den Simulationen von anderen Standorten zu einer deutlich besseren Übereinstimmung als die Simulation für diesen Standort. Die Ergebnisse der Simulationen der Lysimeterstandorte zeigen, dass mit dem Makroporenansatz ein schneller Wasserfluss im Sommer nicht simuliert werden kann, da das "Anspringen" der Makroporen im Modellkonzept an den Bodenwassergehalt geknüpft ist. Auch hier wurden die Simulationsergebnisse mit den Messwerten der anderen Standorte verglichen. Für fünf von acht Standorten konnte mit den simulierten Sickerwassermengen von anderen Standorten eine bessere Übereinstimmung erzielt werden. Die Simulation der Sickerwassermenge aus Lysimetern scheint daher auf Grundlage der vorliegenden Datenbasis den jeweiligen Standort nicht in seiner Einzigartigkeit charakterisieren zu können. Die mit den Beregnungsversuchen bestimmten Abflussprozesse konnten für die Mehrheit der 18 Standorte mit dem Modell abgebildet werden. Der Oberflächenabfluss konnte für Standorte, die nicht zur Verschlämmung neigen, unter Berücksichtigung von Infiltrationsdaten sehr gut nachgezeichnet werden. Zwischenabfluss wird zwar simuliert, bleibt aber auf der Plotskale in Dynamik und Abflussmenge hinter dem Realsystem zurück. Mit der Untersuchung konnte gezeigt werden, dass sich sowohl die zeitliche Entwicklung des Bodenwassergehaltes, als auch die gemessenen Abflussprozesse allein über die Standortdaten, ohne eine weitere Kalibrierung des Modells, abbilden lassen. Die Trennschärfe der Modellierung ist bei Standorten mit relativ ähnlicher bodenphysikalischer Ausstattung begrenzt. Andererseits müssen aber auch Messungenauigkeiten, besonders bei der thermogravimetrischen Bestimmung des Bodenwassergehaltes, berücksichtigt werden. Eine standortbezogene Aussage über Retentions- und Abflussverhalten ist über eine Simulation möglich, jedoch bleibt die quantitative Aussagekraft begrenzt.
This thesis considers the general task of computing a partition of a set of given objects such that each set of the partition has a cardinality of at least a fixed number k. Among such kinds of partitions, which we call k-clusters, the objective is to find the k-cluster which minimises a certain cost derived from a given pairwise difference between objects which end up the same set. As a first step, this thesis introduces a general problem, denoted by (||.||,f)-k-cluster, which models the task to find a k-cluster of minimum cost given by an objective function computed with respect to specific choices for the cost functions f and ||.||. In particular this thesis considers three different choices for f and also three different choices for ||.|| which results in a total of nine different variants of the general problem. Especially with the idea to use the concept of parameterised approximation, we first investigate the role of the lower bound on the cluster cardinalities and find that k is not a suitable parameter, due to remaining NP-hardness even for the restriction to the constant 3. The reductions presented to show this hardness yield the even stronger result which states that polynomial time approximations with some constant performance ratio for any of the nine variants of (||.||,f)-k-cluster require a restriction to instances for which the pairwise distance on the objects satisfies the triangle inequality. For this restriction to what we informally refer to as metric instances, constant-factor approximation algorithms for eight of the nine variants of (||.||,f)-k-cluster are presented. While two of these algorithms yield the provably best approximation ratio (assuming P!=NP), others can only guarantee a performance which depends on the lower bound k. With the positive effect of the triangle inequality and applications to facility location in mind, we discuss the further restriction to the setting where the given objects are points in the Euclidean metric space. Considering the effect of computational hardness caused by high dimensionality of the input for other related problems (curse of dimensionality) we check if this is also the source of intractability for (||.||,f)-k-cluster. Remaining NP-hardness for restriction to small constant dimensionality however disproves this theory. We then use parameterisation to develop approximation algorithms for (||.||,f)-k-cluster without restriction to metric instances. In particular, we discuss structural parameters which reflect how much the given input differs from a metric. This idea results in parameterised approximation algorithms with parameters such as the number of conflicts (our name for pairs of objects for which the triangle inequality is violated) or the number of conflict vertices (objects involved in a conflict). The performance ratios of these parameterised approximations are in most cases identical to those of the approximations for metric instances. This shows that for most variants of (||.||,f)-k-cluster efficient and reasonable solutions are also possible for non-metric instances.
Global change, i.e. climate and land use changes, severely impact natural ecosystems at different scales. Poikilothermic animals as butterflies, amphibians and reptiles have proven to be useful indicators for global change impacts as their phenology, spatial distribution, individual fitness and survival strongly depend on external environmental factors. In this aspect, phenological changes in terms of advanced flight or breeding periods, immigrations of foreign species, range shifts concomitant with temperature increases and even local population declines have been observed in both species groups. However, to date much attention has been paid to global change impacts on the species or population level and analyses concerning entire ecosystems are scarce. Applying a novel statistical modelling algorithm we assessed future changes in the extent and composition of terrestrial ecoregions as classified by the World Wide Fund for Nature (WWF). They are defined as coarse-scale conservation units containing exceptional assemblages of species and ecological dynamics. Our results demonstrate dramatic geographical changes in the extent and location of these ecoregions across all continents and even imply a repriorisation of conservation efforts to cope with future climate change impacts on biodiversity. On the local scale, climate change impacts become unequivocal. Comparing historical to contemporary butterfly assemblages on vineyard fallows of the Trier Region, a significant decline in butterfly richness, but also a severe depletion in trait diversity was observed. Comparisons of community temperature indices reveal a striking shift in community composition leading to a replacement of sedentary and monophagous habitat specialists by ubiquitous species. Similar changes have been observed in nature reserves in the Saar-Mosel-area. Monitoring data reveal strong losses of species diversity and remarkable shifts of community compositions at the expense of habitat specialists. Besides climatic variability, these findings are largely attributed to changes in habitat structures, mostly due to eutrophication and monotonisation. Management activities are unlikely to counterbalance these effects, thus severely questioning current conservation strategies. Most dramatic global change impacts are suspected on closely associated species and disruptions of biotic interactions are often hold responsible for species declines. A strong host-parasite association has developed in Myrmica ants and Maculinea butterflies, the later crucially depending on specific host ants for their larval survival. Applying environmental niche models we determined considerable niche dynamics in the observed parasite-host relation with a pronounced niche plasticity in the butterfly species adapting to previous evasive niche shifts in their host ants. Moreover, the new emergence of species continuously expanding their northernmost range borders concomitant with global warming like the Short-tailed blue (Cupido argiades) is attributed to climate change. However, species distribution models predict a severe habitat loss and shifts of potentially suitable habitats of this species towards north-eastern Europe and higher altitudes under several IPCC scenarios making the presence of this species in the Trier region a contemporary phenomenon. Species distribution models have emerged as powerful tools to predict species distributions over spatial and temporal scales. However, not only the presence of a species, but also its abundance have significant implications for species conservation. The ability to deduce spatial abundance patterns from environmental suitability might more efficiently guide field surveys or monitoring programs over large geographical areas saving time and money. Although the application of species distribution models to deduce vertebrate abundances is well recognized, our results indicate that this method is not an adequate approach to predict invertebrate abundances. Structural and ecological factors as well as climatic patterns acting at the microscale are key drivers of invertebrate occurrence and abundances limiting conclusions drawn from modeling approaches. Population declines should be interpreted with care as in butterflies and amphibians various reasons are debated. Both species groups are acknowledged to be highly susceptible to land use changes and variations in landscape structure. Moreover, climate and land use are not independently operating factors. The combined impact of both is demonstrated in our study linking climate-driven changes in amphibian phenologies to temporal advanced applications of pesticides and fertilizers. Both environmental factors already represent severe threats to amphibians when standing alone, but linking their combined impacts may result in an potentiated risk for amphibian populations. As all amphibians and numerous butterfly species are legally protected under the Federal Nature Conservation Act, intensifications of agricultural land use in large parts of Germany as well as new agrarian practices (including genetically manipulated plants accompanied by new herbicide technologies) might severely challenge regional conservation activities in the future.