Recent challenges of the ecosystems services approach from an interdisciplinary point of view

The ecosystem services approach has attracted tremendous attention from policymaking, planning and interdisciplinary sciences over the last decades. Despite its broad acknowledgement worldwide, there are a number of well-known conceptual and methodological limitations that impair its use and practical operationalisation. A brief discussion of these deficits is conducted from the integrated perspective of natural and social sciences. The paper then critically addresses the question of whether and to what extent the diversity, complexity and hybridity of the human-nature context should be shaped into a uniform scheme, disregarding the differing scales of the social, economic and ecological processes, functions and the trade-offs between them.Das Konzept der Ökosystemdienstleistungen hat in den letzten Jahrzehnten in beachtlichem Maße Eingang in die politische Entscheidungsfindung, die räumliche Planung und in die interdisziplinär ausgerichteten Wissenschaftsdisziplinen gefunden. Trotz seiner weltweiten Wahrnehmung und verbreiteten Anerkennung weist dieser Ansatz bekanntermaßen eine Reihe konzeptioneller und methodische Defizite auf, die seine Anwendung und Operationalisierbarkeit erschweren. Neben einer kurzen Diskussion der aus einer integrativen natur- und sozialwissenschaftlichen Perspektive heraus beleuchteten Limitierungen wirft der vorliegende Beitrag die Frage auf, ob und inwieweit es sinnvoll ist, die Vielfalt, Komplexität und Hybridität von Mensch-Umwelt-Systemen in ein einheitliches Bewertungsschema einzupassen und dabei die verschiedenen Ebenen der sozialen, wirtschaftlichen und ökologischen Prozesse, Funktionen und Zielkonflikte zu ignorieren

Spatio-Temporal High-Resolution Subsoil Compaction Risk Assessment for a 5-Years Crop Rotation at Regional Scale

Soil compaction results whenever applied soil stress by machinery exceed the soil strength. Both, soil strength and stress, are spatially and temporally highly variable, depending on the weather situation, the current crop type, and the machinery used. Thus, soil compaction risk is very dynamic, changes from day to day and from fi eld to fi eld. The objective of this study was to analyze the spatio-temporal dynamics of soil compaction risk and to identify hot-spot areas of high soil compaction risk at regional scale. Therefore, we selected a study area (~2,000 km) with intensive arable farming in Northern Germany, having a high share of cereals, maize and sugar beets. Sentinel-2 images were used to derive the crop types for a 5-years crop rotation (2016 – 2020). We calculated the soil compaction risk using an updated version of the SaSCiA-model (Spatially explicit Soil Compaction risk Assessment) for each single day of the period, with a spatial resolution of 20 m. The results showed the dynamic changes of soil compaction risk within a year and throughout the entire crop rotation. The relatively dry years 2016 and 2018 – 2020 reduced the soil compaction risk even at high wheel loads applied to soil during maize and sugar beet harvest. Contrary, high precipitation in 2017 increased the soil compaction risk considerably

Improving GIS-Based Heat Demand Modelling and Mapping for Residential Buildings with Census Data Sets at Regional and Sub-Regional Scales

Heat demand of buildings and related CO2 emissions caused by energy supply contribute to global climate change. Spatial data-based heat planning enables municipalities to reorganize local heating sectors towards efficient use of regional renewable energy resources. Here, annual heat demand of residential buildings is modeled and mapped for a German federal state to provide regional basic data. Using a 3D building stock model and standard values of building-type-specific heat demand from a regional building typology in a Geographic Information Systems (GIS)-based bottom-up approach, a first base reference is modeled. Two spatial data sets with information on the construction period of residential buildings, aggregated on municipality sections and hectare grid cells, are used to show how census-based spatial data sets can enhance the approach. Partial results from all three models are validated against reported regional data on heat demand as well as against gas consumption of a municipality. All three models overestimate reported heat demand on regional levels by 16% to 19%, but underestimate demand by up to 8% on city levels. Using the hectare grid cells data set leads to best prediction accuracy values at municipality section level, showing the benefit of integrating this high detailed spatial data set on building age

Modellierung und Quantifizierung von winderosionsbedingten Auswehungs- und Akkumulationsbereichen mit WEPS in PCRaster

Zur flächenhaften Abschätzung der Winderosionsgefährdung wird in der Bundesrepublik Deutschland als Standardverfahren die DIN 19706 eingesetzt. Sie gestattet eine qualitative Einordnung der Erosions-gefährdung in ordinal skalierte Gefährdungsklassen, liefert aber keine Angaben über Austragsmengen. Darüber hinaus erfasst sie die feldinterne Variabilität des an der Oberfläche befindlichen Bodens nicht. Der Abtrags- und Depositionsprozess innerhalb eines Schlages wird von dieser jedoch wesentlich beeinflusst (DUTTMANN und BACH 2006). Die vorliegende Arbeit geht der Frage nach, in welchem Maße die Heterogenität des Oberflächensubstrates Einfluss auf die Modellierung des feldinternen Transportgeschehens hat.\ud Es wird die durch den dynamischen Prozess hervorgerufene räumliche Differenzierung von Auswehungs- und Akkumulationsflächen aufgezeigt. Zu diesem Zweck wurde das Modellsystem WEPS in PCRaster eingesetzt

Spatially Explicit Soil Compaction Risk Assessment of Arable Soils at Regional Scale: The SaSCiA-Model

Soil compaction caused by field traffic is one of the main threats to agricultural landscapes. Compacted soils have a reduced hydraulic conductivity, lower plant growth and increased surface runoff resulting in numerous environmental issues such as increased nutrient leaching and flood risk. Mitigating soil compaction, therefore, is a major goal for a sustainable agriculture and environmental protection. To prevent undesirable effects of field traffic, it is essential to know where and when soil compaction may occur. This study developed a model for soil compaction risk assessment of arable soils at regional scale. A combination of (i) soil, weather, crop type and machinery information; (ii) a soil moisture model and (iii) soil compaction models forms the SaSCiA-model (Spatially explicit Soil Compaction risk Assessment). The SaSCiA-model computes daily maps of soil compaction risk and associated area statistics for varying depths at actual field conditions and for entire regions. Applications with open access data in two different study areas in northern Germany demonstrated the model’s applicability. Soil compaction risks strongly varied in space and time throughout the year. SaSCiA allows a detailed spatio-temporal analysis of soil compaction risk at the regional scale, which exceed those of currently available models. Applying SaSCiA may support farmers, stakeholders and consultants in making decision for a more sustainable agriculture

Soil Penetration Resistance after One-Time Inversion Tillage: A Spatio-Temporal Analysis at the Field Scale

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 shor

Of Animal Husbandry and Food Production—A First Step towards a Modular Agent-Based Modelling Platform for Socio-Ecological Dynamics

Agent-based models provide detailed, bottom-up approaches to investigate complex socio-ecological systems. This study presents a first step towards a modular agent-based simulation that is based upon empirical data, as well as environmental suitability maps and an assessment of livestock units. To illustrate the capabilities of our simulation, we use a geographically explicit approach to simulate a component of the production of animal products of a rural settlement in the lower Bakırçay catchment, western Turkey. The model structurally couples various agent types representing several elements and processes of the animal husbandry and food production value chain, such as sedentary herders—practising daily, short-distance pastoralism—and their flocks of goats and sheep, as well as milking and slaughtering. The modelling tool captures the fundamental socio-ecological dynamics of animal husbandry and food production in rural settlements. Therefore, the tool is valuable as a basis to discuss hypotheses regarding the number of animals that are needed to cover the requirements of different growing populations

Of Animal Husbandry and Food Production - A First Step towards a Modular Agent-Based Modelling Platform for Socio-Ecological Dynamics

Agent-based models provide detailed, bottom-up approaches to investigate complex socio-ecological systems. This study presents a first step towards a modular agent-based simulation that is based upon empirical data, as well as environmental suitability maps and an assessment of livestock units. To illustrate the capabilities of our simulation, we use a geographically explicit approach to simulate a component of the production of animal products of a rural settlement in the lower Bakırçay catchment, western Turkey. The model structurally couples various agent types representing several elements and processes of the animal husbandry and food production value chain, such as sedentary herders—practising daily, short-distance pastoralism - and their flocks of goats and sheep, as well as milking and slaughtering. The modelling tool captures the fundamental socio-ecological dynamics of animal husbandry and food production in rural settlements. Therefore, the tool is valuable as a basis to discuss hypotheses regarding the number of animals that are needed to cover the requirements of different growing populations

Spatio-Temporal Prediction of the Epidemic Spread of Dangerous Pathogens Using Machine Learning Methods

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

Estimation of Soil Material Transportation by Wind Based on in Situ Wind Tunnel Experiments

25% and 40% of territory of Hungary is moderate to highly vulnerable to deflation. However, precise estimates about the soil loss and related losses of organic matter and nutrients due to wind erosion are missing in most cases. In order to determine magnitudes of nutrient masses removed at wind velocities that frequently occur in SE Hungary, in-situ experiments using a portable wind tunnel have been conducted on small test plots with an erosional length of 5.6 m and a width of 0.65 m. The wind tunnel experiments have been carried through on a Chernozem which is typical for this region. In order to compare the effects of soil coverage on the masses of blown soil sediment and adsorbed nutrients, two soil surface types have been tested under similar soil moisture und atmospheric conditions: (1) bare soil (dead fallow) and (2) bare soil surface interrupted by a row of maize plants directed downwind along the center line of the test plots. The results of our experiments clearly show that a constant wind velocity of 15 m s-1 (at a height of 0.3 m) lasting over a short time period of 10 minutes can already cause noticeable changes in the composition and size of soil aggregates at the top of the soil surface. Due to the grain size selectivity of the erosive forces the relative share of soil aggregates comprising diameters &gt; 1 mm increased by 5-10% compared with the unaffected soil. Moreover it has shown that short time wind erosion events as simulated in this study can result in erosion rates between 100 and 120 g m-2, where the erosion rates measured for bare soils are only slightly, but not significantly higher than those of the loosely vegetated ones. Soil samples taken from sediment traps mounted in different heights close to the outlet of the wind tunnel point to an enrichment of organic matter (OM) of about 0.6 to 1 % by mass referred to the control samples. From these findings has been calculated that the relocation of organic matter within short term wind erosion events can amount to 4.5 to 5.0 g OM m-2. With the help of portable field wind tunnel experiments we can conclude that our valuable, high quality chernozems are struck by wind erosion mainly in drought periods