Modelling plant trait variability in changing arid environments

Modellierung der Variabilität von Pflanzen-Traits auf Populations- und Lebensgemeinschaftsebene in ariden Gebieten mit Umweltveränderungen. Lebensgemeinschaften in ariden Gebieten sind angesichts globaler Umweltveränderungen besonders anfällig, da sie höchst unvorhersagbaren Umweltbedingungen ausgesetzt sind. Das Schicksal von Gemeinschaften in einer ungewissen Zukunft kann durch das Verständnis der Triebkräfte dieser Gemeinschaften aufgeklärt werden. Das Zusammenspiel der Triebkräfte der Gemeinschaften kann mit Hilfe von Ansätzen entschlüsselt werden, die auf funktionalen Merkmalen (Traits) basieren, weil sie Pflanzenstrategien und die Reaktionen der Gemeinschaften auf Umweltveränderungen beschreiben können. Darüber hinaus liefert die inter- und intraspezifische Variabilität der Traits die notwendigen Anhaltspunkte für die Identifizierung von Überlebensstrategien von Wüstenpflanzen unter wechselhaften Umweltbedingungen. Die Erforschung von Wüstenpflanzengemeinschaften könnte jedoch aufgrund der räumlichen und zeitlichen Heterogenität der ariden Umweltbedingungen eine Herausforderung darstellen. Modellierungsansätze unterstützen und ergänzen empirische, trait-basierte Ansätze bei der Erforschung von Wüstenpflanzengemeinschaften und ihrer Triebkräfte und Dynamik in sich verändernden ariden Gebieten. Das Gesamtziel dieser Arbeit war es, die intra- und interspezifische Variabilität der funktionalen Traits in ariden Umgebungen zu erforschen und zu untersuchen, wie sich diese Variabilität auf die Fähigkeit von Pflanzen auswirkt, Trockenstress zu tolerieren und in der Konkurrenz mit ihren Nachbarn erfolgreich zu sein. Um dieses Ziel zu erreichen, habe ich ein räumlich-explizites individuen- und trait-basiertes Simulationsmodell entwickelt, implementiert und analysiert, ein Simulationsexperiment durchgeführt, Daten aus empirischen Experimenten analysiert und einen Überblick der Literatur zu trait-basierten Modellen und Metamodellierungsansätzen zusammengestellt. Meine Forschung basiert auf Daten zu annuellen Pflanzengemeinschaften in der Wüste Negev in Israel, die von der Echte Rose von Jericho (Anastatica hierochuntica) dominiert werden. Die Literaturzusammenschau in Kapitel 1 offenbart, dass trait-basierte Modelle eine geeignete Methode sind, um Veränderungen in den Mustern von Gemeinschaften unter globalen Veränderungen vorherzusagen und die zugrunde liegenden Mechanismen der Zusammensetzung und Dynamik von Lebensgemeinschaften zu verstehen. Durch die Kombination von Modellierung und trait-basierten Ansätzen lassen sich technische Herausforderungen, Skalierungsprobleme und Datenknappheit überwinden. Insbesondere wurde eine Kombination aus trait-basierten Ansätzen und individuenbasierter Modellierung empfohlen, um die Parametrisierung der Modelle zu vereinfachen, Interaktionen zwischen Pflanzen auf individueller Ebene zu erfassen und die Gemeinschaftsdynamik zu erklären. Eine Forderung aus Kapitel 1 umsetzend wurde in Kapitel 2 das räumlich-explizite, trait- und individuenbasierte ATID-Modell entwickelt, implementiert und analysiert, um zu untersuchen, wie Gemeinschaftsdynamiken aus Pflanzentraits und Interaktionen von Pflanzen untereinander und mit ihrer Umwelt entstehen. Die Sensitivitätsanalyse des Modells hob die funktionalen Traits von Pflanzen als Schlüsselfaktoren der Gemeinschaftsdynamik hervor, wobei den Umweltfaktoren im Modell eine relativ geringere Bedeutung zugewiesen wurde. Die sensitivitätverursachenden Traits umfassten sowohl solche Traits, die an den Pflanze-Pflanze-Interaktionen beteiligt waren, wie zum Beispiel die relative Wachstumsrate und maximale Biomasse, als auch solche, die die Toleranz gegenüber abiotischem Stress fördern, wie die Keimruhe und Keimungswahrscheinlichkeit. Unter den Umweltfaktoren waren die Verfügbarkeit von Bodenwasser und Niederschlag die einflussreichsten Faktoren. Die besondere Rolle von funktionalen Traits in der Gemeinschaftsdynamik einjähriger Wüstenpflanzen zeigt die Bedeutung trait-basierter Strategien als Anpassung an die harschen Bedingungen in ariden Gebieten. Kapitel 3 befasst sich mit den Ergebnissen eines Simulationsexperiments, das mit dem ATID-Modell durchgeführt wurde. Dieses Experiment untersuchte den Einfluss funktionaler Traits auf die Gemeinschaftsdynamik, die bei zwei Überlebensstrategien eine Rolle spielen, die in der Studie in einem neuen Strategiekonzept als "Schutz-Konkurrenz"- und "Flucht-Kolonisierungs"-Strategien definiert wurden. Diese Strategien unterschieden sich nicht nur in der Samengröße und der Anzahl der Samen, sondern auch in bestimmten Pflanzentraits, die mit Konkurrenz und Überleben zusammenhängen und die in der Sensitivitätsanalyse des Modells aus Kapitel 2 hervorgehoben worden waren. Die Integration der Konzepte des Kolonisierung-Konkurrenz-Trade-offs und des Entkommens in Zeit und Raum in einem neuen Strategiekonzept ergab eine realistischere Darstellung der Arten, da die integrierten Strategien den gesamten Lebenszyklus der Pflanze berücksichtigen. Um ein besseres Verständnis empirischer Trait-Verteilungen zu erlangen, wurden in Kapitel 4 Daten zur intraspezifischen Traitvariabilität und zu Trait-Räumen der annuellen Wüstenpflanze A. hierochutica aus einem Gewächshausversuch analysiert. Hohe Salzkonzentrationen hatten signifikante Auswirkungen auf die Durchschnittswerte der funktionalen Traits der Pflanzen. Zusätzlich beeinflusste Salzstress die intraspezifischen Trait-Räume unterschiedlich in Bezug auf die Umweltbedingungen des Ursprungsortes der Pflanzen. Die Trait-Räume der Populationen, die vom gleichen Standort stammten, aber unterschiedlichen Salzstress-Niveaus ausgesetzt waren, wurden mit zunehmender Aridität unähnlicher. Daher erwiesen sich die intraspezifische Trait-Variabilität und die Salzeffekte als wesentlich für die Aufdeckung von Prozessen auf Populations- und Lebensgemeinschaftsebene in Wüsten und sollten in zukünftigen Versionen des ATID-Modells berücksichtigt werden. Zur Unterstützung der zukünftigen Entwicklung des in Kapitel 2 entwickelten ATID-Modells wurden in Kapitel 5 Metamodelltypen und ihre Anwendungsbereiche in der individuenbasierten Modellierung überprüft und bewertet. Die Überprüfung berücksichtigte 40 Metamodelle, die für die Sensitivitätsanalyse, Kalibrierung, Vorhersage und Skalierung von individuenbasierten Modellen eingesetzt werden können und als Leitfaden für die Implementierung und Validierung von Metamodellen dienen können. Insgesamt beleuchtet diese Arbeit und insbesondere die Analysen des ATID-Modells, wie trait-basierte Modellierungsansätze zum Verständnis des Zusammenspiels der Schlüsseltriebkräfte von Wüstenpflanzengemeinschaften in ariden Umgebungen beitragen können. Die begleitende Analyse des Gewächshausexperiments und die kritischen Literaturübersichten dienen als Grundlage für zukünftige Erweiterungen des Modells und die in dieser Arbeit identifizierten Wege zur Überwindung technischer Herausforderungen und Datenknappheit. Darüber hinaus empfiehlt diese Dissertation eine intensivere Untersuchung der Strategien annueller Wüstenpflanzen für das Überleben unter zeitlich und räumlich heterogenen Umweltbedingungen mit besonderem Schwerpunkt auf funktionalen Pflanzen-Traits. Somit bietet das in dieser Arbeit vorgestellte Grundmodell die Basis für zukünftige Forschungen über das Schicksal von Lebensgemeinschaften in ariden Gebieten unter dem Einfluss globaler Umweltveränderungen.Communities in arid environments are especially vulnerable to global change because they experience highly unpredictable environmental conditions. The fate of communities in an uncertain future may be elucidated by understanding the drivers of these communities. The interplay between community drivers may be unravelled by using approaches based on functional traits because traits describe plant strategies and the responses of communities to environmental changes. Furthermore, inter- and intraspecific trait variability provides the necessary cues to identify survival strategies of desert plants under fluctuating environmental conditions. However, studying desert plant communities is challenging due to the spatial and temporal heterogeneity of arid environments. Modelling approaches support and complement empirical trait-based approaches in exploring desert plant communities and their drivers and dynamics in changing arid environments. The overarching aim of this thesis was to explore intra- and inter-specific variability of functional traits in arid environments and to investigate how this variability affects the ability of plants to tolerate aridity stress and succeed in competition with their neighbours. To address this aim, I developed, implemented and analysed a spatially explicit individual- and trait-based simulation model, conducted a simulation experiment, analysed data from model simulations and empirical experiments and synthesized the literature on trait-based models and metamodelling approaches. My research was focused on annual plant communities dominated by the True Rose of Jericho (Anastatica hierochuntica L.) in the Negev desert in Israel. According to the review in chapter 1, trait-based models are a suitable method to predict changes in community patterns under global change and to understand the underlying mechanisms of community assembly and dynamics. Combining modelling and trait-based approaches overcomes technical challenges, scaling problems, and data scarcity. Specifically, a combination of trait-based approaches and individual-based modelling was recommended to simplify the parameterization of models and to capture plant-plant interactions at the individual level, and to explain community dynamics. In chapter 2, in line with the major claim of chapter 1, the spatially explicit trait- and individual-based ATID-model was developed, implemented and analysed to explore how community dynamics arise from plant traits and the interactions among plants and with their environment. The sensitivity analysis of the model highlighted plant functional traits as key drivers of community dynamics and indicated that environmental factors were less important in the model. The outlined traits included both those traits that are involved in plant-plant interactions, such as relative growth rate and maximum biomass, and those that promote tolerance to abiotic stress, such as dormancy and germination probability. Among the environmental factors, the most influential factors were soil water availability and precipitation. The special role of functional traits in the community dynamics of desert annual plants indicates the importance of trait-based strategies as an adaptation to the stressful arid environment. Chapter 3 addresses the results from a simulation experiment that was conducted in the ATID-model. This experiment explored the influence of functional traits involved in two survival strategies defined in the study as ‘protective-competition’ and ‘escape-colonization’ strategies on community dynamics. These strategies differed not only in seed size and the number of seeds, but also in the plant functional traits related to competition and survival, which were highlighted in the sensitivity analysis of the model from chapter 2. Merging the colonization-competition trade-off with escape in time and space into one strategy set provided a more realistic representation of species because the merged strategies related to the entire plant life cycle. To gain more understanding on empirical trait distributions, in chapter 4 data on intraspecific trait variability and trait spaces of the desert annual plant A. hierochutica from a nethouse experiment were analysed. High salinity had significant effects on the average values of plant functional traits. Additionally, salinity stress affected the intraspecific trait spaces differentially with respect to the environmental conditions of the site of origin. Trait spaces of the populations originating from the same site but exposed to different salt stress levels became more dissimilar with increasing environmental aridity. Thus, intraspecific trait variability and salinity effects turned out to be essential in revealing population- and community-level processes in deserts and should be considered in future versions of the ATID-model. In support of the future development of the ATID-model developed in chapter 2, common metamodel types and the purposes of their usage for individual-based models were reviewed and evaluated in chapter 5. The review considered 40 metamodels applied for sensitivity analysis, calibration, prediction and scaling-up of individual-based models and can be used as a guide for the implementation and validation of metamodels. Overall, this thesis, and particularly the ATID-model analyses, highlights how trait-based modelling approaches can contribute to understanding the interplay between key drivers of desert plant communities in arid environments. The accompanying analysis of the nethouse experiment and critical literature reviews outline future extensions of the model and the ways to overcome the technical challenges and data scarcity identified in this thesis. Moreover, this thesis advocates for more intensive studies of the strategies of desert annual plants to survive in temporally and spatially heterogeneous environments with a focus on plant functional traits. Thus, the modelling framework presented in this thesis provides the basis for future research on the fate of communities in arid environments under global change

Heart failure and diabetes mellitus: insight into comorbidity

Diabetes mellitus (DM) and heart failure (HF) are frequent comorbidities with a bidirectional relationship. Patients with HF have increased risk of developing DM, and those with DM are at greater risk of developing HF. HF does not fit clearly into the microangiopathy and macroangiopathy groups. It is known that coronary artery disease and arterial hypertension are the major causes of HF; however, it has been shown that DM can trigger functional and structural abnormalities in the myocardium via diabetic cardiomyopathy, a condition with either restrictive or dilated phenotype. While HF treatment is equally effective and safe in patients with and without DM, this statement is not applicable for antidiabetic treatment. Several antidiabetic drugs, such as rosiglitazone, pioglitazone and saxagliptin increase the risk of hospitalisation for HF, therefore these antidiabetic drugs are contraindicated in patients with DM and HF or patients at risk of developing HF. Despite a large number of clinical evidence, uncertainty about the safety of antidiabetic drugs in patients with HF always exists. In this review, the issues of DM treatment in patients with HF are addressed in detail

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Optimal leaf water status regulation of plants in drylands

Abstract Leaf water potential regulation is a key process in whole plant and ecosystem functioning. While low water potentials induced by open stomata may initially be associated with greater CO2 supply and a higher water flux from the rhizosphere to the canopy, they also inhibit cell growth, photosynthesis and ultimately water supply. Here, we show that plants regulate their leaf water potential in an optimal manner under given constraints using a simple leaf water status regulation model and data from a global dryland leaf water potential database. Model predictions agree strongly with observations across locations and species and are further supported by experimental data. Leaf water potentials non-linearly decline with soil water potential, underlining the shift from maximizing water supply to avoiding stress with declining water availability. Our results suggest that optimal regulation of the leaf water status under varying water supply and stress tolerance is a ubiquitous property of plants in drylands. The proposed model moreover provides a novel quantitative framework describing how plants respond to short- and long-term changes in water availability and may help elaborating models of plant and ecosystem functioning

The evidence of metabolic-improving effect of metformin in Ay/a mice with genetically-induced melanocortin obesity and the contribution of hypothalamic mechanisms to this effect.

In diet-induced obesity, metformin (MF) has weight-lowering effect and improves glucose homeostasis and insulin sensitivity. However, there is no information on the efficiency of MF and the mechanisms of its action in melanocortin-type obesity. We studied the effect of the 10-day treatment with MF at the doses of 200, 400 and 600 mg/kg/day on the food intake and the metabolic and hormonal parameters in female C57Bl/6J (genotype Ay/a) agouti-mice with melanocortin-type obesity, and the influence of MF on the hypothalamic signaling in obese animals at the most effective metabolic dose (600 mg/kg/day). MF treatment led to a decrease in food intake, the body and fat weights, the plasma levels of glucose, insulin and leptin, all increased in agouti-mice, to an improvement of the lipid profile and glucose sensitivity, and to a reduced fatty liver degeneration. In the hypothalamus of obese agouti-mice, the leptin and insulin content was reduced and the expression of the genes encoding leptin receptor (LepR), MC3- and MC4-melanocortin receptors and pro-opiomelanocortin (POMC), the precursor of anorexigenic melanocortin peptides, was increased. The activities of AMP-activated kinase (AMPK) and the transcriptional factor STAT3 were increased, while Akt-kinase activity did not change from control C57Bl/6J (a/a) mice. In the hypothalamus of MF-treated agouti-mice (10 days, 600 mg/kg/day), the leptin and insulin content was restored, Akt-kinase activity was increased, and the activities of AMPK and STAT3 were reduced and did not differ from control mice. In the hypothalamus of MF-treated agouti-mice, the Pomc gene expression was six times higher than in control, while the gene expression for orexigenic neuropeptide Y was decreased by 39%. Thus, we first showed that MF treatment leads to an improvement of metabolic parameters and a decrease of hyperleptinemia and hyperinsulinaemia in genetically-induced melanocortin obesity, and the specific changes in the hypothalamic signaling makes a significant contribution to this effect of MF

Insulin and α-Tocopherol Enhance the Protective Effect of Each Other on Brain Cortical Neurons under Oxidative Stress Conditions and in Rat Two-Vessel Forebrain Ischemia/Reperfusion Injury

Clinical trials show that insulin administered intranasally is a promising drug to treat neurodegenerative diseases, but at high doses its use may result in cerebral insulin resistance. Identifying compounds which could enhance the protective effects of insulin, may be helpful to reduce its effective dose. Our aim was thus to study the efficiency of combined use of insulin and α-tocopherol (α-T) to increase the viability of cultured cortical neurons under oxidative stress conditions and to normalize the metabolic disturbances caused by free radical reaction activation in brain cortex of rats with two-vessel forebrain ischemia/reperfusion injury. Immunoblotting, flow cytometry, colorimetric, and fluorometric techniques were used. α-T enhanced the protective and antioxidative effects of insulin on neurons in oxidative stress, their effects were additive. At the late stages of oxidative stress, the combined action of insulin and α-T increased Akt-kinase activity, inactivated GSK-3beta and normalized ERK1/2 activity in cortical neurons, it was more effective than either drug action. In the brain cortex, ischemia/reperfusion increased the lipid peroxidation product content and caused Na+,K+-ATPase oxidative inactivation. Co-administration of insulin (intranasally, 0.25 IU/rat) and α-T (orally, 50 mg/kg) led to a more pronounced normalization of the levels of Schiff bases, conjugated dienes and trienes and Na+,K+-ATPase activity than administration of each drug alone. Thus, α-T enhances the protective effects of insulin on cultured cortical neurons in oxidative stress and in the brain cortex of rats with cerebral ischemia/reperfusion injury

α-Tocopherol at Nanomolar Concentration Protects PC12 Cells from Hydrogen Peroxide-Induced Death and Modulates Protein Kinase Activities

The aim of this work was to compare protective and anti-apoptotic effects of α-tocopherol at nanomolar and micromolar concentrations against 0.2 mM H2O2-induced toxicity in the PC12 neuronal cell line and to reveal protein kinases that contribute to α-tocopherol protective action. The protection by 100 nM α-tocopherol against H2O2-induced PC12 cell death was pronounced if the time of pre-incubation with α-tocopherol was 3–18 h. For the first time, the protective effect of α-tocopherol was shown to depend on its concentration in the nanomolar range (1 nM < 10 nM < 100 nM), if the pre-incubation time was 18 h. Nanomolar and micromolar α-tocopherol decreased the number of PC12 cells in late apoptosis induced by H2O2 to the same extent if pre-incubation time was 18 h. Immunoblotting data showed that α-tocopherol markedly diminished the time of maximal activation of extracellular signal-regulated kinase 1/2 (ERK 1/2) and protein kinase B (Akt)-induced in PC12 cells by H2O2. Inhibitors of MEK 1/2, PI 3-kinase and protein kinase C (PKC) diminished the protective effect of α-tocopherol against H2O2-initiated toxicity if the pre-incubation time was long. The modulation of ERK 1/2, Akt and PKC activities appears to participate in the protection by α-tocopherol against H2O2-induced death of PC12 cells. The data obtained suggest that inhibition by α-tocopherol in late stage ERK 1/2 and Akt activation induced by H2O2 in PC12 cells makes contribution to its protective effect, while total inhibition of these enzymes is not protective

α-Tocopherol at Nanomolar Concentration Protects Cortical Neurons against Oxidative Stress

The aim of the present work is to study the mechanism of the α-tocopherol (α-T) protective action at nanomolar and micromolar concentrations against H2O2-induced brain cortical neuron death. The mechanism of α-T action on neurons at its nanomolar concentrations characteristic for brain extracellular space has not been practically studied yet. Preincubation with nanomolar and micromolar α-T for 18 h was found to increase the viability of cortical neurons exposed to H2O2; α-T effect was concentration-dependent in the nanomolar range. However, preincubation with nanomolar α-T for 30 min was not effective. Nanomolar and micromolar α-T decreased the reactive oxygen species accumulation induced in cortical neurons by the prooxidant. Using immunoblotting it was shown that preincubation with α-T at nanomolar and micromolar concentrations for 18 h prevented Akt inactivation and decreased PKCδ activation induced in cortical neurons by H2O2. α-T prevented the ERK1/2 sustained activation during 24 h caused by H2O2. α-T at nanomolar and micromolar concentrations prevented a great increase of the proapoptotic to antiapoptotic proteins (Bax/Bcl-2) ratio, elicited by neuron exposure to H2O2. The similar neuron protection mechanism by nanomolar and micromolar α-T suggests that a “more is better” approach to patients’ supplementation with vitamin E or α-T is not reasonable

Metamodels for Evaluating, Calibrating and Applying Agent-Based Models: A Review

The recent advancement of agent-based modeling is characterized by higher demands on the parameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for "easy to go" applications just mimicking the input-output behavior of such models. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modelers in the selection and application of metamodels for their own needs, we further assessed their implementation effort and performance. We performed a literature research in January 2019 using four different databases. Five different terms paraphrasing metamodels (approximation, emulator, meta-model, metamodel and surrogate) were used to capture the whole range of relevant literature in all disciplines. All metamodel applications found were then categorized into specific metamodel types and rated by different junior and senior researches from varying disciplines (including forest sciences, landscape ecology, or economics) regarding the implementation effort and performance. Specifically, we captured the metamodel performance according to (i) the consideration of uncertainties, (ii) the suitability assessment provided by the authors for the particular purpose, and (iii) the number of valuation criteria provided for suitability assessment. We selected 40 distinct metamodel applications from studies published in peer-reviewed journals from 2005 to 2019. These were used for the sensitivity analysis, calibration and upscaling of agent-based models, as well to mimic their prediction for different scenarios. This review provides information about the most applicable metamodel types for each purpose and forms a first guidance for the implementation and validation of metamodels for agent-based models