Agent-based modeling of climate change adaptation in agriculture : a case study in the Central Swabian Jura

Using the MPMAS multi-agent software, the present thesis implements an agro-economic agent-based model to analyze climate change adaptation of agricultural production in the Central Swabian Jura. It contributes to the DFG PAK 346 FOR 1695 research projects dedicated to improve the understanding of processes that shape structure and functions of agricultural landscapes in the context of climate change at regional scale. In the context of this example, this thesis discusses, develops and tests novel approaches to deal with four notorious challenges that have so far hampered the empirical use of agent-based models for applied economic analysis: data availability, process uncertainty, model validity and computational requirements. The model is used to examine climatic effects on agriculture, changes in agricultural price responses and biogas support and agri-environmental policies illustrating the applicability of the model to adaptation analysis. The first part of the thesis is dedicated to a methodological discussion of the use of mathematical programming-based multi-agent systems, such as MPMAS, for the analysis of agricultural adaptation to climate change. It synthesizes knowledge about the potential impacts of climate change and processes of farmer adaptation and reviews existing agent-based models for their potential contribution to adaptation analysis. The major focus of the first part is a discussion of available approaches to model validation, calibration and uncertainty analysis and their suitability for the use with mathematical programming-based agent-based models. This discussion is based on four principles required to ensure the validity of conclusions drawn from modeling studies: (i) a transparent model documentation, (ii) that the invariant elements of the model can really be expected to be invariant between scenarios assessed, (iii) that empirical calibration of the model is limited to the extent warranted by available observation and knowledge about the expected error distribution, and (iv) that the effect of process uncertainty on the conclusions is evaluated and communicated. Based on these conclusions, generic extensions of the MPMAS toolbox are developed to allow the application of suitable approaches for validation and uncertainty analysis. The second part of the thesis describes the application of the newly developed methodology in the construction and use of the Central Swabian Jura model. The model focuses on an endogenous representation of heterogeneity in agent behavior, an empirical parameterization of the model, and an incorporation of climate effects on possible crop rotations and suitable days for field work besides the expected effects on yields. It extends the demographic, investment and land market components of MPMAS to improve the simulation of structural change over time. The model was used to analyze potential effects of climate change adaptation on agricultural production and land use in the study area. The results show that besides effects on yields also other climate change-induced effects on the conditions of agricultural production may have important impacts on land use decisions of farmers and deserve more attention in climate change impact analysis. Potential impacts of changes in the time slots suitable for field work and an additional rotation option are predicted to be comparable to the impact of the changes in yields predicted by a crop growth model. Results point to an expansion of wheat and silage maize areas at the expense of barley areas. The partial crowding out of summer barley by wheat area held for current price relations and is less strong at higher relative prices for summer barley. Price response analysis indicated that winter wheat production enters into a substitutive relationship with summer barley production under climate change conditions, while competition with winter barley area diminishes. This leads also to a higher elasticity of the wheat area with respect to relative summer barley prices. The model was then used to analyze biogas support through the Renewable Energy Act (EEG) and the support for grassland extensification and crop rotation diversification through the MEKA scheme. Especially simulated participation in crop rotation diversification is strongly reduced in the climate change scenarios, while the investments in biogas plants are slightly increased. The conditions established by the latest EEG revision imply that further development of biogas capacity will crucially depend on the existence of demand for excess process heat, because the alternative option of using high manure shares seems to be rather unattractive for farmers in the area according to the simulation results.In der vorliegenden Arbeit wird mithilfe der Modellierungssoftware MPMAS ein agrarökonomisches Multiagentenmodell entwickelt, um die Anpassung der Landwirtschaft auf der Mittleren Schwäbischen Alb zu untersuchen. Vor dem Hintergrund dieser Anwendung werden neue Ansätze diskutiert, entwickelt und getestet, um vier typischen Problemen zu begegnen, die sich bei der empirischen Anwendung agentenbasierter Modelle für ökonomische Analysen ergeben: Datenverfügbarkeit, Prozessunsicherheit, Modellvalidierung und benötigte Rechenkapazität. Mithilfe des erstellten Modells untersucht die Arbeit Klimaeffekte auf die Landwirtschaft, Veränderungen landwirtschaftlicher Angebotsfunktionen sowie Auswirkungen von Fördermaßnahmen für erneuerbare Energieproduktion und Agrarumweltmaßnahmen und demonstriert auf diese Weise seine Anwendbarkeit in der Anpassungsforschung. Der erste Teil der Arbeit diskutiert methodische Aspekte der Nutzung agentbasierter Modelle wie MPMAS, die Entscheidungen als mathematischer Optimierungprobleme darstellen, in der landwirtschaftlichen Anpassungsforschung: Bisherige Erkenntnisse zu den Auswirkungen des Klimawandels auf die Landwirtschaft und den sich daraus ergebenden Anpassungsprozessen werden zusammengefasst und bestehende agentenbasierte Modelle hinsichtlich ihres potentiellen Beitrags zur Anpassungsforschung untersucht. Der Hauptfokus des ersten Teils liegt dann auf der Diskussion bestehender Ansätze zur Modellvalidierung, -kalibrierung und Unsicherheitsanalyse und ihrer Anwendbarkeit auf optimierungsorientierte, agentenbasierte Modelle. Die Diskussion orientiert sich an vier Prinzipien, die die Validität der aus der Modellierung gezogenen Schlussfolgerungen sicherstellen sollen: (i) eine transparente Modelldokumentation, (ii) dass als konstant angenommene Modellelemente tatsächlich nicht zwischen den untersuchten Szenarien variieren, (iii) dass das Modell nicht stärker kalibriert wird als es die verfügbaren Beobachtungen und die erwartete Fehlerverteilung erlauben, und (iv) dass etwaige Auswirkungen der Prozessunsicherheit auf Ergebnisse und Schlussfolgerungen untersucht und kommuniziert werden. Für die Umsetzung dieses Ansatzes der Validierung und Umsicherheitsanalyse waren generische Erweiterungen des MPMAS Softwarepakets notwendig, die in dieser Arbeit entwickelt wurden. Der zweite Teil der Arbeit beschreibt die Anwendung der neuentwickelten Verfahren bei der Erstellung und Nutzung eines Multiagentenmodells für die Mittlere Schwäbische Alb. Der Schwerpunkt der Modellentwicklung lag hierbei auf der Abbildung der Heterogenität des Agentenverhaltens, der empirischen Parametrisierung, und der Berücksichtigung klimatischer Effekte auf mögliche Fruchtfolgen und zur Feldarbeit geeignete Arbeitstage -- neben den klimatischen Auswirkungen auf Ernteerträge. Darüberhinaus wurde die Modellierung von Demographie, Investitionsentscheidungen und Pachtmärkten in MPMAS ergänzt, um die Simulation des landwirtschaftlichen Strukturwandels über die Zeit zu verbessern. Mithilfe des Modells wurden potentielle Anpassungsreaktionen der Landwirte auf den Klimawandel hinsichtlich ihrer Auswirkungen auf landwirtschaftliche Produktion und Landnutzung in der Untersuchungsregion analysiert. Die Ergebnisse zeigen, dass neben Ertragsveränderungen auch andere klimainduzierte Veränderungen der landwirtschaftlichen Produktionsbedingungen bedeutende Auswirkungen auf die Landnutzungsentscheidungen der Landwirte haben können: Potentielle Klimaeffekte auf Feldarbeitstage und zusätzliche Fruchtfolgeoptionen zeigten ähnliche Auswirkungen wie die von einem Pflanzenwachstumsmodell vorhergesagten Ertragsveränderungen. Die Ergebnisse deuten auf eine Ausweitung der Weizen- und Silomaisanbaufläche auf Kosten des Gersteanbaus hin. Die Verdrängung von Sommergerstefläche durch Weizenfläche gilt allerdings für momentane Preisrelationen und ist bei höheren Relativpreisen für Sommergerste weniger stark ausgeprägt. Eine Analyse der Angebotsreaktionen zeigte, dass die Winterweizenfläche unter Klimawandelbedingungen in ein Substitutionsverhältnis mit der Sommergersteproduktion tritt, während die Konkurrenz mit Wintergerste abnimmt. Das Modell wurde außerdem genutzt, um die Förderung der Biogaserzeugung durch das Erneuerbare-Energien-Gesetz (EEG) und die Förderung der Grünlandextensivierung und Fruchtfolgediversifizierung durch das MEKA-Programm zu untersuchen. Speziell die Beteiligung an der Fruchtfolgediversifizierung zeigte einen starken Rückgang in den Klimawandelszenarien, während die Investition in Biogasanlagen leicht stieg. Nach der letzten Änderung des EEG, die die Nutzung von Prozessabwärme zur Voraussetzung für eine Förderung macht, muss davon ausgegangen werden, dass weitere Investitionen in Biogasanlagen stark von der lokalen Vermarktbarkeit von Überschusswärme abhängen werden, da die Alternativoption erhöhter Güllenutzung nach den Simulationsergebnissen für die Landwirte eher unattraktiv erscheint

Experimental validation of 4D log file-based proton dose reconstruction for interplay assessment considering amplitude-sorted 4DCTs

Purpose The unpredictable interplay between dynamic proton therapy delivery and target motion in the thorax can lead to severe dose distortions. A fraction-wise four-dimensional (4D) dose reconstruction workflow allows for the assessment of the applied dose after patient treatment while considering the actual beam delivery sequence extracted from machine log files, the recorded breathing pattern and the geometric information from a 4D computed tomography scan (4DCT). Such an algorithm capable of accounting for amplitude-sorted 4DCTs was implemented and its accuracy as well as its sensitivity to input parameter variations was experimentally evaluated. Methods An anthropomorphic thorax phantom with a movable insert containing a target surrogate and a radiochromic film was irradiated with a monoenergetic field for various 1D target motion forms (sin, sin(4)) and peak-to-peak amplitudes (5/10/15/20/30 mm). The measured characteristic film dose distributions were compared to the respective sections in the 4D reconstructed doses using a 2D gamma-analysis (3 mm, 3%); gamma-pass rates were derived for different dose grid resolutions (1 mm/3 mm) and deformable image registrations (DIR, automatic/manual) applied during the 4D dose reconstruction process. In an additional analysis, the sensitivity of reconstructed dose distributions against potential asynchronous timing of the motion and machine log files was investigated for both a monoenergetic field and more realistic 4D robustly optimized fields by artificially introduced offsets of +/- 1/5/25/50/250 ms. The resulting dose distributions with asynchronized log files were compared to those with synchronized log files by means of a 3D gamma-analysis (1 mm, 1%) and the evaluation of absolute dose differences. Results The induced characteristic interplay patterns on the films were well reproduced by the 4D dose reconstruction with 2D gamma-pass rates >= 95% for almost all cases with motion magnitude

Climate-related land use policies in Brazil: How much has been achieved with economic incentives in agriculture?

Until 2019, the Brazilian federal government employed a number of policy measures to fulfill the pledge of reducing greenhouse gas emissions from land use change and agriculture. While its forest law enforcement strategy was partially successful in combating illegal deforestation, the effectiveness of positive incentive measures in agriculture has been less clear. The reason is that emissions reduction from market-based incentives such as the Brazilian Low-Carbon Agriculture Plan cannot be easily verified with current remote sensing monitoring approaches. Farmers have adopted a large variety of integrated land-use systems of crop, livestock and forestry with highly diverse per-hectare carbon balances. Their responses to policy incentives were largely driven by cost and benefit considerations at the farm level and not necessarily aligned with federal environmental objectives. This article analyzes climate-related land-use policies in the state of Mato Grosso, where highly mechanized soybean–cotton and soybean–maize cropping systems prevail. We employ agent-based bioeconomic simulation together with life-cycle assessment to explicitly capture the heterogeneity of farm-level costs, benefits of adoption, and greenhouse gas emissions. Our analysis confirms previous assessments but suggests a smaller farmer policy response when measured as increase in area of integrated systems. In terms of net carbon balances, our simulation results indicate that mitigation effects at the farm level depended heavily on the exact type of livestock and grazing system. The available data were insufficient to rule out even adverse effects. The Brazilian experience thus offers lessons for other land-rich countries that build their climate mitigation policies on economic incentives in agriculture

How to Keep it Adequate: A Validation Protocol for Agent-Based Simulation

Agent-based models are used in a huge diversity of contexts, which complicates the establishment of a shared understanding of model validity and adequate methods for model construction, inference and validation. Starting from the tenet that model validity can only be judged with respect to a well-defined purpose and context, we conceptualise validation as systematically substantiating the premises on which conclusions from simulation analysis for a specific context are built. We revisit the premises of empirical and structural validation and argue that validation should not be understood as an isolated step in the modelling process. Rather, sound conclusions from simulation analysis require context-adequate choices at all steps of simulation analysis. To facilitate communication, we develop a protocol of guiding questions to analyse the modelling context, choose appropriate methods at each step, document the premises involved in a specific simulation analysis, and demonstrate the adequacy of the model for its context

How to keep it adequate: A protocol for ensuring validity in agent-based simulation

There has so far been no shared understanding of validity in agent-based simulation. We here conceptualise validation as systematically substantiating the premises on which conclusions from simulation analysis for a particular modelling context are built. Given such a systematic perspective, validity of agent-based models cannot be ensured if validation is merely understood as an isolated step in the modelling process. Rather, valid conclusions from simulation analysis require context-adequate method choices at all steps of the simulation analysis including model construction, model and parameter inference, uncertainty analysis and simulation. We present a twelve-step protocol to highlight the (often hidden) premises for methodological choices and their link to the modelling context. It is designed to aid modelers in understanding their context and in choosing and documenting context-adequate and mutually consistent methods throughout the modelling process. Its purpose is to assist reviewers and the community as a whole in assessing and discussing context-adequacy

Plasma Zonulin Levels in Childhood Nephrotic Syndrome

Objective: We conducted this study to test the hypothesis that plasma zonulin levels are elevated in pediatric patients with nephrotic syndrome compared to healthy controls.Study Design: Plasma zonulin levels were measured by ELISA in 114 children enrolled in the NEPTUNE study. Clinical and laboratory data were retrieved from the NEPTUNE database.Results: The median age of the patients was 10 (IQR = 5 to 14) years, 59 were male, 64 had minimal change disease, 47 focal segmental glomerulosclerosis, median eGFR was 96 (IQR = 80 to 114) ml/min/1.73 m2, and median urine protein:creatinine ratio was 0.5 (IQR = 0.1 to 3.4) (g:g). The plasma zonulin level was 14.2 ± 5.0 vs. 10.2 ± 2.5 ng/ml in healthy adults in a report using the same assay kit, P = 0.0025. These findings were confirmed in an independent cohort of children with nephrotic syndrome compared to healthy age-matched controls, P = 0.01. Zonulin concentrations did not differ in children with minimal change disease vs. focal segmental glomerulosclerosis, frequently relapsing vs. steroid-dependent vs. steroid-resistant clinical course, and were not influenced by the immunosuppressive treatment regimen. There was no relationship between plasma zonulin levels and the absolute or percentage change in proteinuria from enrollment until the time of the zonulin assay.Conclusion: Plasma zonulin levels are elevated in childhood nephrotic syndrome regardless of level of proteinuria or specific treatment. The cause of the high plasma zonulin levels and whether zonulin contributes to glomerular injury requires further study

Investigation of tumor hypoxia using a two-enzyme system for in vitro generation of oxygen deficiency

<p>Abstract</p> <p>Background</p> <p>Oxygen deficiency in tumor tissue is associated with a malign phenotype, characterized by high invasiveness, increased metastatic potential and poor prognosis. Hypoxia chambers are the established standard model for <it>in vitro </it>studies on tumor hypoxia. An enzymatic hypoxia system (GOX/CAT) based on the use of glucose oxidase (GOX) and catalase (CAT) that allows induction of stable hypoxia for <it>in vitro </it>approaches more rapidly and with less operating expense has been introduced recently. Aim of this work is to compare the enzymatic system with the established technique of hypoxia chamber in respect of gene expression, glucose metabolism and radioresistance, prior to its application for <it>in vitro </it>investigation of oxygen deficiency.</p> <p>Methods</p> <p>Human head and neck squamous cell carcinoma HNO97 cells were incubated under normoxic and hypoxic conditions using both hypoxia chamber and the enzymatic model. Gene expression was investigated using Agilent microarray chips and real time PCR analysis. ¹⁴C-fluoro-deoxy-glucose uptake experiments were performed in order to evaluate cellular metabolism. Cell proliferation after photon irradiation was investigated for evaluation of radioresistance under normoxia and hypoxia using both a hypoxia chamber and the enzymatic system.</p> <p>Results</p> <p>The microarray analysis revealed a similar trend in the expression of known HIF-1 target genes between the two hypoxia systems for HNO97 cells. Quantitative RT-PCR demonstrated different kinetic patterns in the expression of carbonic anhydrase IX and lysyl oxidase, which might be due to the faster induction of hypoxia by the enzymatic system. ¹⁴C-fluoro-deoxy-glucose uptake assays showed a higher glucose metabolism under hypoxic conditions, especially for the enzymatic system. Proliferation experiments after photon irradiation revealed increased survival rates for the enzymatic model compared to hypoxia chamber and normoxia, indicating enhanced resistance to irradiation. While the GOX/CAT system allows independent investigation of hypoxia and oxidative stress, care must be taken to prevent acidification during longer incubation.</p> <p>Conclusion</p> <p>The results of our study indicate that the enzymatic model can find application for <it>in vitro </it>investigation of tumor hypoxia, despite limitations that need to be considered in the experimental design.</p

Shared heritability of attention-deficit/hyperactivity disorder and autism spectrum disorder

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are both highly heritable neurodevelopmental disorders. Evidence indicates both disorders co-occur with a high frequency, in 20–50% of children with ADHD meeting criteria for ASD and in 30-80% of ASD children meeting criteria for ADHD. This review will provide an overview on all available studies [family based, twin, candidate gene, linkage, and genome wide association (GWA) studies] shedding light on the role of shared genetic underpinnings of ADHD and ASD. It is concluded that family and twin studies do provide support for the hypothesis that ADHD and ASD originate from partly similar familial/genetic factors. Only a few candidate gene studies, linkage studies and GWA studies have specifically addressed this co-occurrence, pinpointing to some promising pleiotropic genes, loci and single nucleotide polymorphisms (SNPs), but the research field is in urgent need for better designed and powered studies to tackle this complex issue. We propose that future studies examining shared familial etiological factors for ADHD and ASD use a family-based design in which the same phenotypic (ADHD and ASD), candidate endophenotypic, and environmental measurements are obtained from all family members. Multivariate multi-level models are probably best suited for the statistical analysis

Molecular imaging of hypoxia with radiolabelled agents

Tissue hypoxia results from an inadequate supply of oxygen (O2) that compromises biological functions. Structural and functional abnormalities of the tumour vasculature together with altered diffusion conditions inside the tumour seem to be the main causes of tumour hypoxia. Evidence from experimental and clinical studies points to a role for tumour hypoxia in tumour propagation, resistance to therapy and malignant progression. This has led to the development of assays for the detection of hypoxia in patients in order to predict outcome and identify patients with a worse prognosis and/or patients that would benefit from appropriate treatments. A variety of invasive and non-invasive approaches have been developed to measure tumour oxygenation including oxygen-sensitive electrodes and hypoxia marker techniques using various labels that can be detected by different methods such as positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), autoradiography and immunohistochemistry. This review aims to give a detailed overview of non-invasive molecular imaging modalities with radiolabelled PET and SPECT tracers that are available to measure tumour hypoxia