Institut für Geographie und Geologie
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Sacred water canals or lakes, which provided water for all kinds of purification rites and other activities, were very specific and important features of temples in ancient Egypt. In addition to the longer-known textual record, preliminary geoarchaeological surveys have recently provided evidence of a sacred canal at the Temple of Bastet at Bubastis. In order to further explore the location, shape, and course of this canal and to find evidence of the existence of a second waterway, also described by Herodotus, 34 drillings and five 2D geoelectrical measurements were carried out in 2019 and 2020 near the temple. The drillings and 2D ERT surveying revealed loamy to clayey deposits with a thickness of up to five meters, most likely deposited in a very low energy fluvial system (i.e., a canal), allowing the reconstruction of two separate sacred canals both north and south of the Temple of Bastet. In addition to the course of the canals, the width of about 30 m fits Herodotus’ description of the sacred waterways. The presence of numerous artefacts proved the anthropogenic use of the ancient canals, which were presumably connected to the Nile via a tributary or canal located west or northwest of Bubastis.
Background
Breast cancer (BC), which is most common in elderly women, requires a multidisciplinary and continuous approach to care. With demographic changes, the number of patients with chronic diseases such as BC will increase. This trend will especially hit rural areas, where the majority of the elderly live, in terms of comprehensive health care.
Methods
Accessibility to several cancer facilities in Bavaria, Germany, was analyzed with a geographic information system. Facilities were identified from the national BC guideline and from 31 participants in a proof‐of‐concept study from the Breast Cancer Care for Patients With Metastatic Disease registry. The timeframe for accessibility was defined as 30 or 60 minutes for all population points. The collection of address information was performed with different sources (eg, a physician registry). Routine data from the German Census 2011 and the population‐based Cancer Registry of Bavaria were linked at the district level.
Results
Females from urban areas (n = 2,938,991 [ie, total of females living in urban areas]) had a higher chance for predefined accessibility to the majority of analyzed facilities in comparison with females from rural areas (n = 3,385,813 [ie, total number of females living in rural areas]) with an odds ratio (OR) of 9.0 for cancer information counselling, an OR of 17.2 for a university hospital, and an OR of 7.2 for a psycho‐oncologist. For (inpatient) rehabilitation centers (OR, 0.2) and genetic counselling (OR, 0.3), women from urban areas had lower odds of accessibility within 30 or 60 minutes.
Conclusions
Disparities in accessibility between rural and urban areas exist in Bavaria. The identification of underserved areas can help to inform policymakers about disparities in comprehensive health care. Future strategies are needed to deliver high‐quality health care to all inhabitants, regardless of residence.
Park−People Relationships: The Socioeconomic Monitoring of National Parks in Bavaria, Germany
(2021)
Questions about park–people relationships and the understanding and handling of the conflicts that may result from the creation and management of national parks in the surrounding area are prerequisites for both successful park management and sustainable rural tourism development. This paper analyzes the roles that research may play in relation to park–people relationships in the context of the two oldest German national parks located in Bavaria. The different fields of action of national parks are used to identify the potential for conflict, using detailed case studies from the Bavarian Forest and Berchtesgaden National Parks using quantitative population surveys carried out in 2018. The overall attitude towards both national parks is overwhelmingly positive, with trust towards park administrations and the perceived economic benefits from rural tourism being the attitudes most strongly correlated to the overall level of park–people relationships. Nevertheless, some points of contention still exist, like the ecological integrity approach towards strict nature conservation and related landscape changes (e.g., deadwood cover). A comparison over time shows in both cases that the spatial proximity to the protected area negatively influences people’s attitudes towards the parks, but less so than in the past. Recommendations for national park management include communicating proactively and with greater transparency with locals and decision-makers, to identify conflicts earlier and, where possible, to eliminate them. Furthermore, developing a standardized method to monitor park–people relationships in Germany is a must and would benefit integrated approaches in research and management based on conservation social science.
Biological soil crusts (BSCs) are thin microbiological vegetation layers that naturally develop in unfavorable higher plant conditions (i.e., low precipitation rates and high temperatures) in global drylands. They consist of poikilohydric organisms capable of adjusting their metabolic activities depending on the water availability. However, they, and with them, their ecosystem functions, are endangered by climate change and land-use intensification. Remote sensing (RS)-based studies estimated the BSC cover in global drylands through various multispectral indices, and few of them correlated the BSCs’ activity response to rainfall. However, the allocation of BSCs is not limited to drylands only as there are areas beyond where smaller patches have developed under intense human impact and frequent disturbance. Yet, those areas were not addressed in RS-based studies, raising the question of whether the methods developed in extensive drylands can be transferred easily. Our temperate climate study area, the ‘Lieberoser Heide’ in northeastern Germany, is home to the country’s largest BSC-covered area. We applied a Random Forest (RF) classification model incorporating multispectral Sentinel-2 (S2) data, indices derived from them, and topographic information to spatiotemporally map the BSC cover for the first time in Central Europe. We further monitored the BSC response to rainfall events over a period of around five years (June 2015 to end of December 2020). Therefore, we combined datasets of gridded NDVI as a measure of photosynthetic activity with daily precipitation data and conducted a change detection analysis. With an overall accuracy of 98.9%, our classification proved satisfactory. Detected changes in BSC activity between dry and wet conditions were found to be significant. Our study emphasizes a high transferability of established methods from extensive drylands to BSC-covered areas in the temperate climate. Therefore, we consider our study to provide essential impulses so that RS-based biocrust mapping in the future will be applied beyond the global drylands.
This study investigates circulation types (CTs) in Africa, south of the equator, that are related to wet and dry conditions in the Western Cape, the statistical relationship between the selected CTs and the Southern Annular Mode (SAM), and changes in the frequency of occurrence of the CTs related to the SAM under the ssp585 scenario. Obliquely rotated principal component analysis applied to sea level pressure (SLP) was used to classify CTs in Africa, south of the equator. Three CTs were found to have a high probability of being associated with wet days in the Western Cape, and four CTs were equally found to have a high probability of being associated with dry days in the Western Cape. Generally, the dry/wet CTs feature the southward/northward track of the mid-latitude cyclone, adjacent to South Africa; anti-cyclonic/cyclonic relative vorticity, and poleward/equatorward track of westerlies, south of South Africa. One of the selected wet CTs was significantly related to variations of the SAM. Years with an above-average SAM index correlated with the below-average frequency of occurrences of the wet CT. The results suggest that through the dynamics of the CT, the SAM might control the rainfall variability of the Western Cape. Under the ssp585 scenario, the analyzed climate models indicated a possible decrease in the frequency of occurrence of the aforementioned wet CT associated with cyclonic activity in the mid-latitudes, and an increase in the frequency of the occurrence of CT associated with enhanced SLP at mid-latitudes.
Strategies in Times of Pandemic Crisis — Retailers and Regional Resilience in Würzburg, Germany
(2021)
Research on the COVID-19 crisis and its implications on regional resilience is still in its infancy. To understand resilience on its aggregate level it is important to identify (non)resilient actions of individual actors who comprise regions. As the retail sector among others represents an important factor in an urban regions recovery, we focus on the resilience of (textile) retailers within the city of Würzburg in Germany to the COVID-19 pandemic. To address the identified research gap, this paper applies the concept of resilience. Firstly, conducting expert interviews, the individual (textile) retailers’ level and their strategies in coping with the crisis is considered. Secondly, conducting a contextual analysis of the German city of Würzburg, we wish to contribute to the discussion of how the resilience of a region is influenced inter alia by actors. Our study finds three main strategies on the individual level, with retailers: (1) intending to “bounce back” to a pre-crisis state, (2) reorganising existing practices, as well as (3) closing stores and winding up business. As at the time of research, no conclusions regarding long-term impacts and resilience are possible, the results are limited. Nevertheless, detailed analysis of retailers’ strategies contributes to a better understanding of regional resilience.
Grasslands cover one third of the earth’s terrestrial surface and are mainly used for livestock production. The usage type, use intensity and condition of grasslands are often unclear. Remote sensing enables the analysis of grassland production and management on large spatial scales and with high temporal resolution. Despite growing numbers of studies in the field, remote sensing applications in grassland biomes are underrepresented in literature and less streamlined compared to other vegetation types. By reviewing articles within research on satellite-based remote sensing of grassland production traits and management, we describe and evaluate methods and results and reveal spatial and temporal patterns of existing work. In addition, we highlight research gaps and suggest research opportunities. The focus is on managed grasslands and pastures and special emphasize is given to the assessment of studies on grazing intensity and mowing detection based on earth observation data. Grazing and mowing highly influence the production and ecology of grassland and are major grassland management types. In total, 253 research articles were reviewed. The majority of these studies focused on grassland production traits and only 80 articles were about grassland management and use intensity. While the remote sensing-based analysis of grassland production heavily relied on empirical relationships between ground-truth and satellite data or radiation transfer models, the used methods to detect and investigate grassland management differed. In addition, this review identified that studies on grassland production traits with satellite data often lacked including spatial management information into the analyses. Studies focusing on grassland management and use intensity mostly investigated rather small study areas with homogeneous intensity levels among the grassland parcels. Combining grassland production estimations with management information, while accounting for the variability among grasslands, is recommended to facilitate the development of large-scale continuous monitoring and remote sensing grassland products, which have been rare thus far.
This study compares the performance of the five widely used crop growth models (CGMs): World Food Studies (WOFOST), Coalition for Environmentally Responsible Economies (CERES)-Wheat, AquaCrop, cropping systems simulation model (CropSyst), and the semi-empiric light use efficiency approach (LUE) for the prediction of winter wheat biomass on the Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site, Germany. The study focuses on the use of remote sensing (RS) data, acquired in 2015, in CGMs, as they offer spatial information on the actual conditions of the vegetation. Along with this, the study investigates the data fusion of Landsat (30 m) and Moderate Resolution Imaging Spectroradiometer (MODIS) (500 m) data using the spatial and temporal reflectance adaptive reflectance fusion model (STARFM) fusion algorithm. These synthetic RS data offer a 30-m spatial and one-day temporal resolution. The dataset therefore provides the necessary information to run CGMs and it is possible to examine the fine-scale spatial and temporal changes in crop phenology for specific fields, or sub sections of them, and to monitor crop growth daily, considering the impact of daily climate variability. The analysis includes a detailed comparison of the simulated and measured crop biomass. The modelled crop biomass using synthetic RS data is compared to the model outputs using the original MODIS time series as well. On comparison with the MODIS product, the study finds the performance of CGMs more reliable, precise, and significant with synthetic time series. Using synthetic RS data, the models AquaCrop and LUE, in contrast to other models, simulate the winter wheat biomass best, with an output of high R2 (>0.82), low RMSE (<600 g/m\(^2\)) and significant p-value (<0.05) during the study period. However, inputting MODIS data makes the models underperform, with low R2 (<0.68) and high RMSE (>600 g/m\(^2\)). The study shows that the models requiring fewer input parameters (AquaCrop and LUE) to simulate crop biomass are highly applicable and precise. At the same time, they are easier to implement than models, which need more input parameters (WOFOST and CERES-Wheat).
The detrimental impacts of climate variability on water, agriculture, and food resources in East Africa underscore the importance of reliable seasonal climate prediction. To overcome this difficulty RARIMAE method were evolved. Applications RARIMAE in the literature shows that amalgamating different methods can be an efficient and effective way to improve the forecasts of time series under consideration. With these motivations, attempt have been made to develop a multiple linear regression model (MLR) and a RARIMAE models for forecasting seasonal rainfall in east Africa under the following objectives:
1. To develop MLR model for seasonal rainfall prediction in East Africa.
2. To develop a RARIMAE model for seasonal rainfall prediction in East Africa.
3. Comparison of model's efficiency under consideration
In order to achieve the above objectives, the monthly precipitation data covering the period from 1949 to 2000 was obtained from Climate Research Unit (CRU). Next to that, the first differenced climate indices were used as predictors.
In the first part of this study, the analyses of the rainfall fluctuation in whole Central- East Africa region which span over a longitude of 15 degrees East to 55 degrees East and a latitude of 15 degrees South to 15 degrees North was done by the help of maps. For models’ comparison, the R-squared values for the MLR model are subtracted from the R-squared values of RARIMAE model. The results show positive values which indicates that R-squared is improved by RARIMAE model. On the other side, the root mean square errors (RMSE) values of the RARIMAE model are subtracted from the RMSE values of the MLR model and the results show negative value which indicates that RMSE is reduced by RARIMAE model for training and testing datasets.
For the second part of this study, the area which is considered covers a longitude of 31.5 degrees East to 41 degrees East and a latitude of 3.5 degrees South to 0.5 degrees South. This region covers Central-East of the Democratic Republic of Congo (DRC), north of Burundi, south of Uganda, Rwanda, north of Tanzania and south of Kenya. Considering a model constructed based on the average rainfall time series in this region, the long rainfall season counts the nine months lead of the first principal component of Indian sea level pressure (SLP_PC19) and the nine months lead of Dipole Mode Index (DMI_LR9) as selected predictors for both statistical and predictive model. On the other side, the short rainfall season counts the three months lead of the first principal component of Indian sea surface temperature (SST_PC13) and the three months lead of Southern Oscillation Index (SOI_SR3) as predictors for predictive model. For short rainfall season statistical model SAOD current time series (SAOD_SR0) was added on the two predictors in predictive model. By applying a MLR model it is shown that the forecast can explain 27.4% of the total variation and has a RMSE of 74.2mm/season for long rainfall season while for the RARIMAE the forecast explains 53.6% of the total variation and has a RMSE of 59.4mm/season. By applying a MLR model it is shown that the forecast can explain 22.8% of the total variation and has a RMSE of 106.1 mm/season for short rainfall season predictive model while for the RARIMAE the forecast explains 55.1% of the total variation and has a RMSE of 81.1 mm/season.
From such comparison, a significant rise in R-squared, a decrease of RMSE values were observed in RARIMAE models for both short rainfall and long rainfall season averaged time series. In terms of reliability, RARIMAE outperformed its MLR counterparts with better efficiency and accuracy. Therefore, whenever the data suffer from autocorrelation, we can go for MLR with ARIMA error, the ARIMA error part is more to correct the autocorrelation thereby improving the variance and productiveness of the model.
The natural cyclical development of palsas makes it difficult to use visible signs of decay as reference points for environmental change. Thus, to determine the actual development stage of a palsa, investigations of the internal structure are crucial. Our study presents 2‐D and 3‐D electrical resistivity imaging (ERI) and 2‐D ground‐penetrating radar (GPR) results, measurements of surface and subsurface temperatures, and of the soil matric potential from Orravatnsrústir Palsa Site in Central Iceland. By a joint interpretation of the results, we deduce the internal structure (i.e., thickness of thaw zone and permafrost, ice/water content) of five palsas of different size and shape. The results differentiate between initial and mature development stages and show that palsas of different development stages can exist in close proximity. While internal characteristics indicate undisturbed development of four palsas, one palsa shows indications of environmental change. Our study shows the value of the multimethod geophysical approach and introduces measurements of the soil matric potential as a promising method to assess the current state of the subsurface.
In vielen mediterranen Küstenniederungen entstand seit 1950 infolge von Gebirgsentvölkerung, Infrastrukturausbau, neuer Gewerbe sowie illegaler Bautätigkeit ein fast lückenloses Verstädterungsband. Am Golf von Neapel konnte dieser Landschaftswandel über eine lange Zeit beobachtet und durch zahlreiche Vergleichsfotos, Kartierungen, Luft- und Satellitenbilder und Interviews dokumentiert werden. Horst-Günter Wagner zeigt in diesem Band die Veränderungen der Küstenebene und erläutert ihre Ursachen.
In den letzten drei Jahrzehnten expandierten Supermarktketten aus dem Globalen Norden in Länder des Globalen Südens. Insbesondere Länder mit einem raschen wirtschaftlichen Wachstum und damit neuen Marktpotentialen waren dabei Expansionsziele. Zugleich zeigt sich innerhalb der Länder des Globalen Südens eine Ausbreitung von regionalen Supermarktketten. Mittlerweile gehört frisches Obst und Gemüse fast immer zum Sortiment dieser Einzelhandelsunternehmen.
Bisher untersuchte eine Reihe von Studien die Auswirkungen der Kooperation mit den Einzelhändlern auf die landwirtschaftlichen Produzierenden. Weniger ist dagegen bekannt, welche Liefersysteme und Intermediäre für die Verbindung zwischen landwirtschaftlichen Produzierenden und Supermarktketten in Ländern des Globalen Südens bestehen und sich entwickeln. Insbesondere für leicht verderbliche Frischeprodukte (Obst und Gemüse) ist die Herausbildung dieser Intermediäre eine große Herausforderung. Die vorliegende Studie betrachtet den Zusammenhang zwischen der räumlichen und zeitlichen Ausbreitung von Supermärkten und der Etablierung von Liefersystemen sowie Intermediären am Beispiel von Kenia und Tansania.
The Antarctic Ice Sheet stores ~91% of the global ice volume which is equivalent to a sea-level rise of 58.3 meters. Recent disintegration events of ice shelves and retreating glaciers along the Antarctic Peninsula and West Antarctica indicate the current vulnerable state of the Antarctic Ice Sheet. Glacier tongues and ice shelves create a safety band around Antarctica with buttressing effects on ice discharge. Current decreases in glacier and ice shelf extent reduce the effective buttressing forces and increase ice discharge of grounded ice. The consequence is a higher contribution to sea-level rise from the Antarctic Ice Sheet. So far, it is unresolved which proportion of Antarctic glacier retreat can be attributed to climate change and which part to the natural cycle of growth and decay in the lifetime of a glacier. The quantitative assessment of the magnitude, spatial extent, distribution, and dynamics of circum-Antarctic glacier and ice shelf retreat is of utmost importance to monitor Antarctica’s weakening safety band. In remote areas like Antarctica, earth observation provides optimal properties for large-scale mapping and monitoring of glaciers and ice shelves. Nowadays, the variety of available satellite sensors, technical advancements regarding spatial resolution and revisit times, as well as open satellite data archives create an ideal basis for monitoring calving front change. A systematic review conducted within this thesis revealed major gaps in the availability of glacier and ice shelf front position measurements despite the improved satellite data availability. The previously limited availability of satellite imagery and the time-consuming manual delineation of calving fronts did neither allow a circum-Antarctic assessment of glacier retreat nor the assessment of intra-annual changes in glacier front position. To advance the understanding of Antarctic glacier front change, this thesis presents a novel automated approach for calving front extraction and explores drivers of glacier retreat.
A comprehensive review of existing methods for glacier front extraction ascertained the lack of a fully automatic approach for large-scale monitoring of Antarctic calving fronts using radar imagery. Similar backscatter characteristics of different ice types, seasonally changing backscatter values, multi-year sea ice, and mélange made it challenging to implement an automated approach with traditional image processing techniques. Therefore, the present abundance of satellite data is best exploited by integrating recent developments in big data and artificial intelligence (AI) research to derive circum-Antarctic calving front dynamics. In the context of this thesis, the novel AI-based framework “AntarcticLINES” (Antarctic Glacier and Ice Shelf Front Time Series) was created which provides a fully automated processing chain for calving front extraction from Sentinel-1 imagery. Open access Sentinel-1 radar imagery is an ideal data source for monitoring current and future changes in the Antarctic coastline with revisit times of less than six days and all-weather imaging capabilities. The developed processing chain includes the pre-processing of dual-polarized Sentinel-1 imagery for machine learning applications. 38 Sentinel-1 scenes were used to train the deep learning architecture U-Net for image segmentation. The trained weights of the neural network can be used to segment Sentinel-1 scenes into land ice and ocean. Additional post-processing ensures even more accurate results by including morphological filtering before extracting the final coastline. A comprehensive accuracy assessment has proven the correct extraction of the coastline. On average, the automatically extracted coastline deviates by 2-3 pixels (93 m) from a manual delineation. This accuracy is in range with deviations between manually delineated coastlines from different experts.
For the first time, the fully automated framework AntarcticLINES enabled the extraction of intra-annual glacier front fluctuations to assess seasonal variations in calving front change. Thereby, for example, an increased calving frequency of Pine Island Glacier and a beginning disintegration of Glenzer Glacier were revealed. Besides, the extraction of the entire Antarctic coastline for 2018 highlighted the large-scale applicability of the developed approach. Accurate results for entire Antarctica were derived except for the Western Antarctic Peninsula where training imagery was not sufficient and should be included in future studies.
Furthermore, this dissertation presents an unprecedented record of circum-Antarctic calving front change over the last two decades. The newly extracted coastline for 2018 was compared to previous coastline products from 2009 and 1997. This revealed that the Antarctic Ice Sheet shrank 29,618±1193 km2 in extent between 1997-2008 and gained an area of 7,108±1029 km2 between 2009-2018. Glacier retreat concentrated along the Antarctic Peninsula and West Antarctica. The only East Antarctic coastal sector primarily experiencing calving front retreat was Wilkes Land in 2009-2018. Finally, potential drivers of circum-Antarctic glacier retreat were identified by combining data on glacier front change with changes in climate variables. It was found that strengthening westerlies, snowmelt, rising sea surface temperatures, and decreasing sea ice cover forced glacier retreat over the last two decades. Relative changes in mean air temperature could not be identified as a driver for glacier retreat and further investigations on extreme events in air temperature are necessary to assess the effect of atmospheric forcing on frontal retreat. The strengthening of all identified drivers was closely connected to positive phases of the Southern Annular Mode (SAM). With increasing greenhouse gases and ozone depletion, positive phases of SAM will occur more often and force glacier retreat even further in the future.
Within this thesis, a comprehensive review on existing Antarctic glacier and ice shelf front studies was conducted revealing major gaps in Antarctic calving front records. Therefore, a fully automated processing chain for glacier and ice shelf front extraction was implemented to track circum-Antarctic calving front fluctuations on an intra-annual basis. The large-scale applicability was certified by presenting two decades of circum-Antarctic calving front change. In combination with climate variables, drivers of recent glacier retreat were identified. In the future, the presented framework AntarcticLINES will greatly contribute to the constant monitoring of the Antarctic coastline under the pressure of a changing climate.
Pre‐Klondikean oxidation prepared the ground for Broken Hill‐type mineralization in South Africa
(2021)
New Cu isotope data obtained on chalcopyrite from the Black Mountain and the Broken Hill deposits in the medium‐ to high‐grade metamorphic Aggeneys‐Gamsberg ore district (South Africa) require a revision of our understanding of the genesis of metamorphic Broken Hill‐type massive sulphide deposits. Chalcopyrite from both deposits revealed unusually wide ranges in δ\(^{65}\)Cu (−2.41 to 2.84‰ NIST 976 standard) in combination with distinctly positive mean values (0.27 and 0.94‰, respectively). This is interpreted to reflect derivation from various silicate and oxide precursor minerals in which Cu occurred in higher oxidation states. Together with the observation of a typical supergene base metal distribution within the deposits and their spatial association with an unconformity only meters above the ore horizon, our new data are best explained by supergene oxidation of originally possibly SEDEX deposits prior to metamorphic sulphide formation, between the Okiepian (1,210–1,180 Ma) and Klondikean (1,040–1,020 Ma) orogenic events.
Climate change and associated Arctic amplification cause a degradation of permafrost which in turn has major implications for the environment. The potential turnover of frozen ground from a carbon sink to a carbon source, eroding coastlines, landslides, amplified surface deformation and endangerment of human infrastructure are some of the consequences connected with thawing permafrost. Satellite remote sensing is hereby a powerful tool to identify and monitor these features and processes on a spatially explicit, cheap, operational, long-term basis and up to circum-Arctic scale. By filtering after a selection of relevant keywords, a total of 325 articles from 30 international journals published during the last two decades were analyzed based on study location, spatio-
temporal resolution of applied remote sensing data, platform, sensor combination and studied environmental focus for a comprehensive overview of past achievements, current efforts, together with future challenges and opportunities. The temporal development of publication frequency, utilized platforms/sensors and the addressed environmental topic is thereby highlighted. The total
number of publications more than doubled since 2015. Distinct geographical study hot spots were revealed, while at the same time large portions of the continuous permafrost zone are still only sparsely covered by satellite remote sensing investigations. Moreover, studies related to Arctic greenhouse gas emissions in the context of permafrost degradation appear heavily underrepresented.
New tools (e.g., Google Earth Engine (GEE)), methodologies (e.g., deep learning or data fusion etc.)and satellite data (e.g., the Methane Remote Sensing LiDAR Mission (Merlin) and the Sentinel-fleet)will thereby enable future studies to further investigate the distribution of permafrost, its thermal state and its implications on the environment such as thermokarst features and greenhouse gas emission rates on increasingly larger spatial and temporal scales.
Maize cropping systems mapping using RapidEye observations in agro-ecological landscapes in Kenya
(2017)
Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms in agro-ecological landscapes. In this study, high spatial and temporal resolution RapidEye bio-temporal data were utilized within a novel 2-step hierarchical random forest (RF) classification approach to map areas of mono- and mixed maize cropping systems. A small-scale maize farming site in Machakos County, Kenya was used as a study site. Within the study site, field data was collected during the satellite acquisition period on general land use/land cover (LULC) and the two cropping systems. Firstly, non-cropland areas were masked out from other land use/land cover using the LULC mapping result. Subsequently an optimized RF model was applied to the cropland layer to map the two cropping systems (2nd classification step). An overall accuracy of 93% was attained for the LULC classification, while the class accuracies (PA: producer’s accuracy and UA: user’s accuracy) for the two cropping systems were consistently above 85%. We concluded that explicit mapping of different cropping systems is feasible in complex and highly fragmented agro-ecological landscapes if high resolution and multi-temporal satellite data such as 5 m RapidEye data is employed. Further research is needed on the feasibility of using freely available 10–20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models.
Statistical modeling of phenology in Bavaria based on past and future meteorological information
(2020)
Plant phenology is well known to be affected by meteorology. Observed changes in the occurrence of phenological phases arecommonly considered some of the most obvious effects of climate change. However, current climate models lack a representationof vegetation suitable for studying future changes in phenology itself. This study presents a statistical-dynamical modelingapproach for Bavaria in southern Germany, using over 13,000 paired samples of phenological and meteorological data foranalyses and climate change scenarios provided by a state-of-the-art regional climate model (RCM). Anomalies of severalmeteorological variables were used as predictors and phenological anomalies of the flowering date of the test plantForsythiasuspensaas predictand. Several cross-validated prediction models using various numbers and differently constructed predictorswere developed, compared, and evaluated via bootstrapping. As our approach needs a small set of meteorological observationsper phenological station, it allows for reliable parameter estimation and an easy transfer to other regions. The most robust andsuccessful model comprises predictors based on mean temperature, precipitation, wind velocity, and snow depth. Its averagecoefficient of determination and root mean square error (RMSE) per station are 60% and ± 8.6 days, respectively. However, theprediction error strongly differs among stations. When transferred to other indicator plants, this method achieves a comparablelevel of predictive accuracy. Its application to two climate change scenarios reveals distinct changes for various plants andregions. The flowering date is simulated to occur between 5 and 25 days earlier at the end of the twenty-first century comparedto the phenology of the reference period (1961–1990).
The new ellipsocephaloid trilobite species Kingaspidoides spinirecurvatus has a spectacular morphology because of a unique set of two long and anteriorly recurved spines on the occipital ring and the axial ring of thoracic segment 8. Together with the long genal spines this whimsical dorsally directed spine arrangement is thought to act as a non-standard protective device against predators. This is illustrated by the body posture during different stages of enrolment, contrasting with the more sophisticated spinosities seen in later trilobites, which are discussed in brief. Kingaspidoides spinirecurvatus from the lower–middle Cambrian boundary interval of the eastern Anti-Atlas in Morocco has been known for about two decades, with specimens handled as precious objects on the fossil market. Similar, but far less spectacular, spine arrangements on the thoracic axial rings are known from other ellipsocephaloid trilobites from the Anti-Atlas of Morocco and the Franconian Forest region of Germany. This suggests that an experimental phase of spine development took place within the Kingaspi-doides clade during the early–middle Cambrian boundary interval.
Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties–sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen–in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models–multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)–were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.
Surveys by the Universities of Wuerzburg and Berlin, starting in the 1970´s have revealed the existence of palaeolakes in remote areas in Niger. Initial research has shown that the sediments found are suitable for reconstructing its late quaternary palaeoenvironment. Although a high number of investigations focused on the succession of climatological conditions in the Central Sahara, some uncertainties still exist as the results show discontinuities and mostly are of low temporal and spatial
resolution.
Two expeditions in 2005 and 2006 headed to the northeastern parts of Niger to investigate the known remains of palaeolakes and search some new and undetected ones. Samples were taken at several study sites in order to receive a complete picture of the Late Quaternary environmental settings and to produce high-resolution proxies for palaeoclimate modelling.
The most valuable and best-investigated study site is the sebkha of Seggedim, where a core of 15 meters length could be extracted which revealed a composition of high-resolution sections. Stratigraphical, structural and geochemical investigations as well as the analysis of thin sections allow the characterization of different environmental conditions from Early to Mid Holocene. Driven by climate and hydrogeological influence, the water body developed from a water pond of several metres depth within a stable, grass and shrub vegetated landscape, to an alternating freshwater lake in a more dynamic environmental setting. Radiocarbon dates set the beginning of the stage at about 10.6 ka cal BP, with an exceptionally stable regime to 6.6 ka cal BP (at 12.6 metres’ depth), when a major change in the sedimentation regime of the basin is recorded in the core. Increased erosion, likely due to decreased vegetation cover within the basin, led to the siltation/filling of the lake within a few hundred years and the subsequent development of a sebkha/salt pan due to massive evaporation. Due to the lack of dateable material in the upper core section, the termination of the lake stage and the onset of the subsequent sebkha stage cannot be determined precisely but can be narrowed to a period around 6 ka BP.
The results obtained from the core are compared with those from terrestrial and lacustrine sediments from outside the depression, situated a few hundred kilometres further to the north. These supplementary study sites are required to validate the information obtained from the coring. Within the plateau landscape of Djado, Mangueni and Tchigai, two depressions and a valley containing lacustrine deposits, were investigated for palaeoenvironmental reconstruction. Depending on modifying local factors, these sediment archives were of shorter existence than IX the lake, but reveal additional information about the landscape dynamics from Early to Mid Holocene.
A damming situation within a small tributary at Enneri Achelouma led to lacustrine sedimentation conditions at Early Holocene in the upper reaches of the valley. The remnants of the lacustrine accumulations show distinct changes in the environmental conditions within the small catchment, as the archive immediately responded to local climate-induced changes of precipitation. Radiocarbon dating of the deposited sediments revealed ages from 8780 ± 260 cal a BP to 9480 ± 80 cal a BP.
The sites of Yoo Ango and Fabérgé show a completely different sedimentation milieu as they consist of basins within the foothills of the Tchigai. The study sites show increased catchment sizes, probably extending towards the Tchigai massif and are most likely influenced by groundwater charge. The widespread occurrence of wind shaped relicts and the limited amount of lacustrine remnants indicate a generally high aeolian activity in both areas. Only in wind sheltered spots, parts of the lacustrine sequences were preserved, that show ages spanning from Early to Mid Holocene (9440 ± 140 cal a BP – 6810 ±140 cal a BP) and give additional evidence of fires from pre-LGM periods. Although intensively weathered, all profiles indicate distinct changes in the sedimentation conditions by alternating geochemical values and the mineralogical composition.
The information obtained from the records investigated in this work confirms the heterogeneity of reconstructed environmental succession in the Central Sahara. The Mid Holocene rapid (within decades) and uniform development from more humid to extremely arid environmental conditions cannot be confirmed for the Central Sahara. In addition, a division of Early and Mid Holocene wet periods cannot be confirmed, either. Actually, the evidences obtained from the palaeoenvironmental reconstructions revealed major variations in the timing and extend of lacustrine and aeolian periods. Evidently, a transitional time has existed between 7 to 5 ka BP where alternating influences prevailed. This is indicated by the varying sedimentation conditions in the Seggedim depression as well as the evidence of soil properties on a fossil dune, with a time of deposition dated to 6200 ± 400 cal a BP and the removal of lacustrine Sediments at the Seeterrassental at Mid Holocene. In respect to provide a complete picture of landscape succession and to avoid misinterpretation, the investigation of several dissimilar spots within a designated study area is prerequisite for further investigations.