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Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
Anomalous diffusion is frequently described by scaled Brownian motion (SBM){,} a Gaussian process with a power-law time dependent diffusion coefficient. Its mean squared displacement is ?x2(t)? [similar{,} equals] 2K(t)t with K(t) [similar{,} equals] t[small alpha]-1 for 0 < [small alpha] < 2. SBM may provide a seemingly adequate description in the case of unbounded diffusion{,} for which its probability density function coincides with that of fractional Brownian motion. Here we show that free SBM is weakly non-ergodic but does not exhibit a significant amplitude scatter of the time averaged mean squared displacement. More severely{,} we demonstrate that under confinement{,} the dynamics encoded by SBM is fundamentally different from both fractional Brownian motion and continuous time random walks. SBM is highly non-stationary and cannot provide a physical description for particles in a thermalised stationary system. Our findings have direct impact on the modelling of single particle tracking experiments{,} in particular{,} under confinement inside cellular compartments or when optical tweezers tracking methods are used.
Anomalous diffusion is frequently described by scaled Brownian motion (SBM){,} a Gaussian process with a power-law time dependent diffusion coefficient. Its mean squared displacement is ?x2(t)? [similar{,} equals] 2K(t)t with K(t) [similar{,} equals] t[small alpha]-1 for 0 < [small alpha] < 2. SBM may provide a seemingly adequate description in the case of unbounded diffusion{,} for which its probability density function coincides with that of fractional Brownian motion. Here we show that free SBM is weakly non-ergodic but does not exhibit a significant amplitude scatter of the time averaged mean squared displacement. More severely{,} we demonstrate that under confinement{,} the dynamics encoded by SBM is fundamentally different from both fractional Brownian motion and continuous time random walks. SBM is highly non-stationary and cannot provide a physical description for particles in a thermalised stationary system. Our findings have direct impact on the modelling of single particle tracking experiments{,} in particular{,} under confinement inside cellular compartments or when optical tweezers tracking methods are used.
Spin precession in magnetic materials is commonly modelled with the classical phenomenological Landau-Lifshitz-Gilbert (LLG) equation. Based on a quantized three-dimensional spin + environment Hamiltonian, we here derive a spin operator equation of motion that describes precession and includes a general form of damping that consistently accounts for memory, coloured noise and quantum statistics. The LLG equation is recovered as its classical, Ohmic approximation. We further introduce resonant Lorentzian system-reservoir couplings that allow a systematic comparison of dynamics between Ohmic and non-Ohmic regimes. Finally, we simulate the full non-Markovian dynamics of a spin in the semi-classical limit. At low temperatures, our numerical results demonstrate a characteristic reduction and flattening of the steady state spin alignment with an external field, caused by the quantum statistics of the environment. The results provide a powerful framework to explore general three-dimensional dissipation in quantum thermodynamics.
In order to tailor solution-phase chemical reactions involving transition metal complexes, it is critical to understand how their valence electronic charge distributions are affected by the solution environment. Here, solute-solvent interactions of a solvatochromic mixed-ligand iron complex were investigated using X-ray absorption spectroscopy at the transition metal L-2,L-3-edge. Due to the selectivity of the corresponding core excitations to the iron 3d orbitals, the method grants direct access to the valence electronic structure around the iron center and its response to interactions with the solvent environment. A linear increase of the total L-2,L-3-edge absorption cross section as a function of the solvent Lewis acidity is revealed. The effect is caused by relative changes in different metal-ligand-bonding channels, which preserve local charge densities while increasing the density of unoccupied states around the iron center. These conclusions are corroborated by a combination of molecular dynamics and spectrum simulations based on time-dependent density functional theory. The simulations reproduce the spectral trends observed in the X-ray but also optical absorption experiments. Our results underscore the importance of solute-solvent interactions when aiming for an accurate description of the valence electronic structure of solvated transition metal complexes and demonstrate how L-2,L-3-edge absorption spectroscopy can aid in understanding the impact of the solution environment on intramolecular covalency and the electronic charge distribution.
The competitive exclusion principle is one of the oldest ideas in ecology and states that without additional self-limitation two predators cannot coexist on a single prey. The search for mechanisms allowing coexistence despite this has identified niche differentiation between predators as crucial: without this, coexistence requires the predators to have exactly the same R* values, which is considered impossible. However, this reasoning misses a critical point: predators' R* values are not static properties, but affected by defensive traits of their prey, which in turn can adapt in response to changes in predator densities. Here I show that this feedback between defense and predator dynamics enables stable predator coexistence without ecological niche differentiation. Instead, the mechanism driving coexistence is that prey adaptation causes defense to converge to the value where both predators have equal R* values ("fitness equalization"). This result is highly general, independent of specific model details, and applies to both rapid defense evolution and inducible defenses. It demonstrates the importance of considering long-standing ecological questions from an eco-evolutionary viewpoint, and showcases how the effects of adaptation can cascade through communities, driving diversity on higher trophic levels. These insights offer an important new perspective on coexistence theory.
Nonstationary coherence-incoherence patterns in nonlocally coupled heterogeneous phase oscillators
(2020)
We consider a large ring of nonlocally coupled phase oscillators and show that apart from stationary chimera states, this system also supports nonstationary coherence-incoherence patterns (CIPs). For identical oscillators, these CIPs behave as breathing chimera states and are found in a relatively small parameter region only. It turns out that the stability region of these states enlarges dramatically if a certain amount of spatially uniform heterogeneity (e.g., Lorentzian distribution of natural frequencies) is introduced in the system. In this case, nonstationary CIPs can be studied as stable quasiperiodic solutions of a corresponding mean-field equation, formally describing the infinite system limit. Carrying out direct numerical simulations of the mean-field equation, we find different types of nonstationary CIPs with pulsing and/or alternating chimera-like behavior. Moreover, we reveal a complex bifurcation scenario underlying the transformation of these CIPs into each other. These theoretical predictions are confirmed by numerical simulations of the original coupled oscillator system.
Modeling random crawling, membrane deformation and intracellular polarity of motile amoeboid cells
(2018)
Amoeboid movement is one of the most widespread forms of cell motility that plays a key role in numerous biological contexts. While many aspects of this process are well investigated, the large cell-to-cell variability in the motile characteristics of an otherwise uniform population remains an open question that was largely ignored by previous models. In this article, we present a mathematical model of amoeboid motility that combines noisy bistable kinetics with a dynamic phase field for the cell shape. To capture cell-to-cell variability, we introduce a single parameter for tuning the balance between polarity formation and intracellular noise. We compare numerical simulations of our model to experiments with the social amoeba Dictyostelium discoideum. Despite the simple structure of our model, we found close agreement with the experimental results for the center-of-mass motion as well as for the evolution of the cell shape and the overall intracellular patterns. We thus conjecture that the building blocks of our model capture essential features of amoeboid motility and may serve as a starting point for more detailed descriptions of cell motion in chemical gradients and confined environments.
Ultrafast heat transport in nanoscale metal multilayers is of great interest in the context of optically induced demagnetization, remagnetization and switching. If the penetration depth of light exceeds the bilayer thickness, layer-specific information is unavailable from optical probes. Femtosecond diffraction experiments provide unique experimental access to heat transport over single digit nanometer distances. Here, we investigate the structural response and the energy flow in the ultrathin double-layer system: gold on ferromagnetic nickel. Even though the excitation pulse is incident from the Au side, we observe a very rapid heating of the Ni lattice, whereas the Au lattice initially remains cold. The subsequent heat transfer from Ni to the Au lattice is found to be two orders of magnitude slower than predicted by the conventional heat equation and much slower than electron-phonon coupling times in Au. We present a simplified model calculation highlighting the relevant thermophysical quantities.
The looping of polymers such as DNA is a fundamental process in the molecular biology of living cells, whose interior is characterised by a high degree of molecular crowding. We here investigate in detail the looping dynamics of flexible polymer chains in the presence of different degrees of crowding. From the analysis of the looping–unlooping rates and the looping probabilities of the chain ends we show that the presence of small crowders typically slows down the chain dynamics but larger crowders may in fact facilitate the looping. We rationalise these non-trivial and often counterintuitive effects of the crowder size on the looping kinetics in terms of an effective solution viscosity and standard excluded volume. It is shown that for small crowders the effect of an increased viscosity dominates, while for big crowders we argue that confinement effects (caging) prevail. The tradeoff between both trends can thus result in the impediment or facilitation of polymer looping, depending on the crowder size. We also examine how the crowding volume fraction, chain length, and the attraction strength of the contact groups of the polymer chain affect the looping kinetics and hairpin formation dynamics. Our results are relevant for DNA looping in the absence and presence of protein mediation, DNA hairpin formation, RNA folding, and the folding of polypeptide chains under biologically relevant high-crowding conditions.
The looping of polymers such as DNA is a fundamental process in the molecular biology of living cells, whose interior is characterised by a high degree of molecular crowding. We here investigate in detail the looping dynamics of flexible polymer chains in the presence of different degrees of crowding. From the analysis of the looping–unlooping rates and the looping probabilities of the chain ends we show that the presence of small crowders typically slows down the chain dynamics but larger crowders may in fact facilitate the looping. We rationalise these non-trivial and often counterintuitive effects of the crowder size on the looping kinetics in terms of an effective solution viscosity and standard excluded volume. It is shown that for small crowders the effect of an increased viscosity dominates, while for big crowders we argue that confinement effects (caging) prevail. The tradeoff between both trends can thus result in the impediment or facilitation of polymer looping, depending on the crowder size. We also examine how the crowding volume fraction, chain length, and the attraction strength of the contact groups of the polymer chain affect the looping kinetics and hairpin formation dynamics. Our results are relevant for DNA looping in the absence and presence of protein mediation, DNA hairpin formation, RNA folding, and the folding of polypeptide chains under biologically relevant high-crowding conditions.
In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.
The availability of commercial 3D printers and matching 3D design software has allowed a wide range of users to create physical prototypes – as long as these objects are not larger than hand size. However, when attempting to create larger, "human-scale" objects, such as furniture, not only are these machines too small, but also the commonly used 3D design software is not equipped to design with forces in mind — since forces increase disproportionately with scale.
In this thesis, we present a series of end-to-end fabrication software systems that support users in creating human-scale objects. They achieve this by providing three main functions that regular "small-scale" 3D printing software does not offer: (1) subdivision of the object into small printable components combined with ready-made objects, (2) editing based on predefined elements sturdy enough for larger scale, i.e., trusses, and (3) functionality for analyzing, detecting, and fixing structural weaknesses. The presented software systems also assist the fabrication process based on either 3D printing or steel welding technology.
The presented systems focus on three levels of engineering challenges: (1) fabricating static load-bearing objects, (2) creating mechanisms that involve motion, such as kinematic installations, and finally (3) designing mechanisms with dynamic repetitive movement where power and energy play an important role.
We demonstrate and verify the versatility of our systems by building and testing human-scale prototypes, ranging from furniture pieces, pavilions, to animatronic installations and playground equipment. We have also shared our system with schools, fablabs, and fabrication enthusiasts, who have successfully created human-scale objects that can withstand with human-scale forces.
Drainage divide networks
(2020)
Drainage divides are organized into tree-like networks that may record information about drainage divide mobility. However, views diverge about how to best assess divide mobility. Here, we apply a new approach of automatically extracting and ordering drainage divide networks from digital elevation models to results from landscape evolution model experiments. We compared landscapes perturbed by strike-slip faulting and spatiotemporal variations in erodibility to a reference model to assess which topographic metrics (hillslope relief, flow distance, and chi) are diagnostic of divide mobility. Results show that divide segments that are a minimum distance of similar to 5 km from river confluences strive to attain constant values of hillslope relief and flow distance to the nearest stream. Disruptions of such patterns can be related to mobile divides that are lower than stable divides, closer to streams, and often asymmetric in shape. In general, we observe that drainage divides high up in the network, i.e., at great distances from river confluences, are more susceptible to disruptions than divides closer to these confluences and are thus more likely to record disturbance for a longer time period. We found that across-divide differences in hillslope relief proved more useful for assessing divide migration than other tested metrics. However, even stable drainage divide networks exhibit across-divide differences in any of the studied topographic metrics. Finally, we propose a new metric to quantify the connectivity of divide junctions.
Der Einfluss der Dynamik auf die stratosphärische Ozonvariabilität über der Arktis im Frühwinter
(2010)
Der frühwinterliche Ozongehalt ist ein Indikator für den Ozongehalt im Spätwinter/Frühjahr. Jedoch weist dieser aufgrund von Absinkprozessen, chemisch bedingten Ozonabbau und Wellenaktivität von Jahr zu Jahr starke Schwankungen auf. Die vorliegende Arbeit zeigt, dass diese Variabilität weitestgehend auf dynamische Prozesse während der Wirbelbildungsphase des arktischen Polarwirbels zurückgeht. Ferner wird der bisher noch ausstehende Zusammenhang zwischen dem früh- und spätwinterlichen Ozongehalt bezüglich Dynamik und Chemie aufgezeigt. Für die Untersuchung des Zusammenhangs zwischen der im Polarwirbel eingeschlossenen Luftmassenzusammensetzung und Ozonmenge wurden Beobachtungsdaten von Satellitenmessinstrumenten und Ozonsonden sowie Modellsimulationen des Lagrangschen Chemie/Transportmodells ATLAS verwandt. Die über die Fläche (45–75°N) und Zeit (August-November) gemittelte Vertikalkomponente des Eliassen-Palm-Flussvektors durch die 100hPa-Fläche zeigt eine Verbindung zwischen der frühwinterlichen wirbelinneren Luftmassenzusammensetzung und der Wirbelbildungsphase auf. Diese ist jedoch nur für die untere Stratosphäre gültig, da die Vertikalkomponente die sich innerhalb der Stratosphäre ändernden Wellenausbreitungsbedingungen nicht erfasst. Für eine verbesserte Höhendarstellung des Signals wurde eine neue integrale auf der Wellenamplitude und dem Charney-Drazin-Kriterium basierende Größe definiert. Diese neue Größe verbindet die Wellenaktivität während der Wirbelbildungsphase sowohl mit der Luftmassenzusammensetzung im Polarwirbel als auch mit der Ozonverteilung über die Breite. Eine verstärkte Wellenaktivität führt zu mehr Luft aus niedrigeren ozonreichen Breiten im Polarwirbel. Aber im Herbst und Frühwinter zerstören chemische Prozesse, die das Ozon ins Gleichgewicht bringen, die interannuale wirbelinnere Ozonvariablität, die durch dynamische Prozesse während der arktischen Polarwirbelbildungsphase hervorgerufen wird. Eine Analyse in Hinblick auf den Fortbestand einer dynamisch induzierten Ozonanomalie bis in den Mittwinter ermöglicht eine Abschätzung des Einflusses dieser dynamischen Prozesse auf den arktischen Ozongehalt. Zu diesem Zweck wurden für den Winter 1999–2000 Modellläufe mit dem Lagrangesche Chemie/Transportmodell ATLAS gerechnet, die detaillierte Informationen über den Erhalt der künstlichen Ozonvariabilität hinsichtlich Zeit, Höhe und Breite liefern. Zusammengefasst, besteht die dynamisch induzierte Ozonvariabilität während der Wirbelbildungsphase länger im Inneren als im Äußeren des Polarwirbels und verliert oberhalb von 750K potentieller Temperatur ihre signifikante Wirkung auf die mittwinterliche Ozonvariabilität. In darunterliegenden Höhenbereichen ist der Anteil an der ursprünglichen Störung groß, bis zu 90% auf der 450K. Innerhalb dieses Höhenbereiches üben die dynamischen Prozesse während der Wirbelbildungsphase einen entscheidenden Einfluss auf den Ozongehalt im Mittwinter aus.
Trait-based approaches have broadened our understanding of how the composition of ecological communities responds to environmental drivers. This research has mainly focussed on abiotic factors and competition determining the community trait distribution, while effects of trophic interactions on trait dynamics, if considered at all, have been studied for two trophic levels at maximum. However, natural food webs are typically at least tritrophic. This enables indirect interactions of traits and biomasses among multiple trophic levels leading to underexplored effects on food web dynamics. Here, we demonstrate the occurrence of mutual trait adjustment among three trophic levels in a natural plankton food web (Lake Constance) and in a corresponding mathematical model. We found highly recurrent seasonal biomass and trait dynamics, where herbivorous zooplankton increased its size, and thus its ability to counter phytoplankton defense, before phytoplankton defense actually increased. This is contrary to predictions from bitrophic systems where counter-defense of the consumer is a reaction to prey defense. In contrast, counter-defense of carnivores by size adjustment followed the defense of herbivores as expected. By combining observations and model simulations, we show how the reversed trait dynamics at the two lower trophic levels result from a "trophic biomass-trait cascade" driven by the carnivores. Trait adjustment between two trophic levels can therefore be altered by biomass or trait changes of adjacent trophic levels. Hence, analyses of only pairwise trait adjustment can be misleading in natural food webs, while multitrophic trait-based approaches capture indirect biomass-trait interactions among multiple trophic levels.
A comet is a highly dynamic object, undergoing a permanent state of change. These changes have to be carefully classified and considered according to their intrinsic temporal and spatial scales. The Rosetta mission has, through its contiguous in-situ and remote sensing coverage of comet 67P/Churyumov-Gerasimenko (hereafter 67P) over the time span of August 2014 to September 2016, monitored the emergence, culmination, and winding down of the gas and dust comae. This provided an unprecedented data set and has spurred a large effort to connect in-situ and remote sensing measurements to the surface. In this review, we address our current understanding of cometary activity and the challenges involved when linking comae data to the surface. We give the current state of research by describing what we know about the physical processes involved from the surface to a few tens of kilometres above it with respect to the gas and dust emission from cometary nuclei. Further, we describe how complex multidimensional cometary gas and dust models have developed from the Halley encounter of 1986 to today. This includes the study of inhomogeneous outgassing and determination of the gas and dust production rates. Additionally, the different approaches used and results obtained to link coma data to the surface will be discussed. We discuss forward and inversion models and we describe the limitations of the respective approaches. The current literature suggests that there does not seem to be a single uniform process behind cometary activity. Rather, activity seems to be the consequence of a variety of erosion processes, including the sublimation of both water ice and more volatile material, but possibly also more exotic processes such as fracture and cliff erosion under thermal and mechanical stress, sub-surface heat storage, and a complex interplay of these processes. Seasons and the nucleus shape are key factors for the distribution and temporal evolution of activity and imply that the heliocentric evolution of activity can be highly individual for every comet, and generalisations can be misleading.
Coarse-grained molecular model for the Glycosylphosphatidylinositol anchor with and without protein
(2020)
Glycosylphosphatidylinositol (GPI) anchors are a unique class of complex glycolipids that anchor a great variety of proteins to the extracellular leaflet of plasma membranes of eukaryotic cells. These anchors can exist either with or without an attached protein called GPI-anchored protein (GPI-AP) both in vitro and in vivo. Although GPIs are known to participate in a broad range of cellular functions, it is to a large extent unknown how these are related to GPI structure and composition. Their conformational flexibility and microheterogeneity make it difficult to study them experimentally. Simplified atomistic models are amenable to all-atom computer simulations in small lipid bilayer patches but not suitable for studying their partitioning and trafficking in complex and heterogeneous membranes. Here, we present a coarse-grained model of the GPI anchor constructed with a modified version of the MARTINI force field that is suited for modeling carbohydrates, proteins, and lipids in an aqueous environment using MARTINI's polarizable water. The nonbonded interactions for sugars were reparametrized by calculating their partitioning free energies between polar and apolar phases. In addition, sugar-sugar interactions were optimized by adjusting the second virial coefficients of osmotic pressures for solutions of glucose, sucrose, and trehalose to match with experimental data. With respect to the conformational dynamics of GPI-anchored green fluorescent protein, the accessible time scales are now at least an order of magnitude larger than for the all-atom system. This is particularly important for fine-tuning the mutual interactions of lipids, carbohydrates, and amino acids when comparing to experimental results. We discuss the prospective use of the coarse-grained GPI model for studying protein-sorting and trafficking in membrane models.
Coarse-grained molecular model for the Glycosylphosphatidylinositol anchor with and without protein
(2020)
Glycosylphosphatidylinositol (GPI) anchors are a unique class of complex glycolipids that anchor a great variety of proteins to the extracellular leaflet of plasma membranes of eukaryotic cells. These anchors can exist either with or without an attached protein called GPI-anchored protein (GPI-AP) both in vitro and in vivo. Although GPIs are known to participate in a broad range of cellular functions, it is to a large extent unknown how these are related to GPI structure and composition. Their conformational flexibility and microheterogeneity make it difficult to study them experimentally. Simplified atomistic models are amenable to all-atom computer simulations in small lipid bilayer patches but not suitable for studying their partitioning and trafficking in complex and heterogeneous membranes. Here, we present a coarse-grained model of the GPI anchor constructed with a modified version of the MARTINI force field that is suited for modeling carbohydrates, proteins, and lipids in an aqueous environment using MARTINI's polarizable water. The nonbonded interactions for sugars were reparametrized by calculating their partitioning free energies between polar and apolar phases. In addition, sugar-sugar interactions were optimized by adjusting the second virial coefficients of osmotic pressures for solutions of glucose, sucrose, and trehalose to match with experimental data. With respect to the conformational dynamics of GPI-anchored green fluorescent protein, the accessible time scales are now at least an order of magnitude larger than for the all-atom system. This is particularly important for fine-tuning the mutual interactions of lipids, carbohydrates, and amino acids when comparing to experimental results. We discuss the prospective use of the coarse-grained GPI model for studying protein-sorting and trafficking in membrane models.