Wood was a crucial resource for prehistoric societies, for instance, as timber for house construction and as fuel. In the case of the exceptionally large Chalcolithic Tripolye ‘mega-sites’ in central Ukraine, thousands of burnt buildings, indicating huge population agglomerations, hint at such a massive use of wood that it raises questions about the carrying capacity of the sensitive forest-steppe environment. In this contribution, we investigate the wood demand for the mega-site of Maidanetske (3990–3640 BCE), as reconstructed based on wood charcoal data, wood imprints on daub and the archaeo-magnetometry-based settlement plan. We developed a regional-scale model with a fuzzy approach and applied it in order to simulate the potential distribution and extent of woodlands before and after Chalcolithic occupation. The model is based upon the reconstructed ancient land surface, soil information derived from cores and the potential natural woodland cover reconstructed based on the requirements of the prevailing ancient tree species. Landscape scenarios derived from the model are contrasted and cross-checked with the archaeological empirical data. We aim to understand whether the demand for wood triggered the site development. Did deforestation and consequent soil degradation and lack of resources initiate the site’s abandonment? Or, alternatively, did the inhabitants develop sustainable woodland management strategies? Starting from the case study of Maidanetske, this study provides estimates of the extent of human impact on both carrying capacity and landscape transformations in the sensitive transitional forest-steppe environment. Overall, the results indicate that the inhabitants of the Chalcolithic site did not suffer from a significant shortage in the wood resource at any time of inhabitation in the contexts of the different scenarios provided by the model. An exception is given by the phase of maximum house construction and population within a scenario of dry climatic conditions.

No abstract

How did socio-cultural transformation processes change land-use patterns? Throughout the last 50 years, outstanding comprehensive geographic, archaeobiological, and archaeological data have been produced for the area of Oldenburger Graben, Schleswig-Holstein, Germany. Based on this exceptional data set, we are able to study the land-use patterns for a period ranging from the Final Mesolithic until the Late Neolithic (4600–1700 BCE). By application of fuzzy modeling techniques, these patterns are investigated diachronically in order to assess the scale of transformations between the different archaeological phases. Based on nutrient requirements and proposed dietary composition estimates derived from empirical archaeobotanical, archaeozoological, and stable isotope data, the required extent of the areas for different land-use practices are modeled. This information is made spatially explicit using a fuzzy model that reconstructs areas of potential vegetation and land-use for each transformation phase. Pollen data are used to validate the type and extent of land-use categories. The model results are used to test hypotheses on the dynamics of socio-cultural transformations: can we observe a diversification of land-use patterns over time or does continuity of land-use practices prevail? By integrating the different lines of evidence within a spatially explicit modeling approach, we reach a new quality of data analysis with a high degree of contextualization. This allows testing of hypotheses about Neolithic transformation processes by an explicit adjustment of our model assumptions, variables, and parameters.

Real-time identification of the occurrence of dangerous pathogens is of crucial importance for the rapid execution of countermeasures. For this purpose, spatial and temporal predictions of the spread of such pathogens are indispensable. The R package papros developed by the authors offers an environment in which both spatial and temporal predictions can be made, based on local data using various deterministic, geostatistical regionalisation, and machine learning methods. The approach is presented using the example of a crops infection by fungal pathogens, which can substantially reduce the yield if not treated in good time. The situation is made more difficult by the fact that it is particularly difficult to predict the behaviour of wind-dispersed pathogens, such as powdery mildew (Blumeria graminis f. sp. tritici). To forecast pathogen development and spatial dispersal, a modelling process scheme was developed using the aforementioned R package, which combines regionalisation and machine learning techniques. It enables the prediction of the probability of yield- relevant infestation events for an entire federal state in northern Germany at a daily time scale. To run the models, weather and climate information are required, as is knowledge of the pathogen biology. Once fitted to the pathogen, only weather and climate information are necessary to predict such events, with an overall accuracy of 68% in the case of powdery mildew at a regional scale. Thereby, 91% of the observed powdery mildew events are predicted.

Conservation agriculture may lead to increased penetration resistance due to soil compaction. To loosen the topsoil and lower the compaction, one-time inversion tillage (OTIT) is a measure frequently used in conservation agriculture. However, the duration of the positive effects of this measure on penetration resistance is sparsely known. Therefore, the aim of this study was to analyze the spatio-temporal behavior of penetration resistance after OTIT as an indicator for soil compaction. A field subdivided into three differently tilled plots (conventional tillage with moldboard plough to 30 cm depth (CT), reduced tillage with chisel plough to 25 cm depth (RT1) and reduced tillage with disk harrow to 10 cm depth (RT2)) served as study area. In 2014, the entire field was tilled by moldboard plough and penetration resistance was recorded in the following 5 years. The results showed that OTIT reduced the penetration resistance in both RT-plots and led to an approximation in all three plots. However, after 18 (RT2) and 30 months (RT1), the differences in penetration resistance were higher (p < 0.01) in both RT-plots compared to CT. Consequently, OTIT can effectively remove the compacted layer developed in conservation agriculture. However, the lasting effect seems to be relatively short.