Conductance Model Research Articles

Spatial Connectivity Through Mountains and Deserts Drove South American Scorpions Dispersal

ABSTRACTAimThe aim of this study is to infer the geographic dispersal paths and the environmental conditions that shaped the historical biogeography of Brachistosternus scorpions in South America. We evaluated the role that altitude and aridity had on the geographic distance that each species dispersed from the location of the genus common ancestor. Based on the previous studies, we evaluated the hypothesis postulating that species geographic expansion was promoted by arid conditions in high altitudes.LocationSouth America.TaxonBrachistosternus genus.MethodsWe integrated two methodological approaches in this study, the phylogenetic Geographical model and the Conductance model, considering the uncertainty associated with the phylogenetic relationship and the species classification. The Geo model infers the locations of ancestral species in a phylogenetic tree, assuming a spherical space and using samples of georeferenced locations for every species as input data. It allows us to estimate the species dispersal routes and distances from the location of the genus common ancestor. The Conductance model is based on the circuit theory and infers the geographic route and distance of least resistance between an origin and destination point. We defined the origin as the location of the genus common ancestor obtained from the Geo model and a destination point as the current geographic location of each species. This model infers the geographic routes with the least cost of resistance for dispersal in a landscape of varying altitude and aridity. Finally, we evaluated the correlation between the two dispersal distances each species have moved from the location of the common ancestor, that is, the distance inferred from the Geo model and from the Conductance model.ResultsThe Geo model shows that Brachistosternus's geographical origin was most likely along the coast of south Peru, and central Chile. From this location, extant species dispersed thorough routes ranging from 873 to 2800 km in average. The Conductance model that considers the routes with least resistance to elevation and aridity simulated dispersal distances that are highly correlated with the species dispersal distances obtained from the Geo model.Main ConclusionsWe revealed the geographic dispersal routes, with the least resistance to the pressures imposed by changes in altitude and aridity, that 55 species of scorpions have probably followed in the last 30 million years in South America. These geographic routes that went along the Andean Mountains and the arid zones of South America shaped the current spatial distribution of the genus Brachistosternus.

Ultralow thermal conductivity in Si–Ge nanograin mixtures: A cost-effective granular material for thermoelectric applications

This paper presents a theoretical study of the thermal conductivity of Si–Ge nanograin mixtures using a multiscale computational methodology based on solving the Boltzmann transport equation for phonons with first-principles techniques. A size-dependent correction factor is developed to account for the spatial dependence of the phonon distribution function on nanograin size, with parameters derived from the phonon properties of infinite Si and Ge crystals. This approach makes it possible to accurately calculate the thermal conductivity within a single nanograin, using force constants obtained from first-principles calculations. Thermal energy transport by phonons across grain boundaries is modeled by accounting for phonon transmission by two-phonon processes, weighting specular, and diffuse transmission for each phonon mode as a function of the root-mean-square roughness of the boundary relative to the phonon wavelength. The boundary thermal conductance model, previously validated against experimental data, is implemented using first-principles techniques. This approach excludes specular transmission for phonon modes with specific symmetries while ensuring conservation of the total number of modes in each symmetry class. The study examines the influence of grain size, nanograin mixture composition, temperature, and boundary asperities on the thermal conductivity of nanograin mixtures.

Modeling electrical impedance in brain tissue with diffusion tensor imaging for functional neurosurgery applications

Objective.Decades ago, neurosurgeons used electrical impedance measurements in the brain for coarse intraoperative tissue differentiation. Over time, these techniques were largely replaced by more refined imaging and electrophysiological localization. Today, advanced methods of diffusion tensor imaging (DTI) and finite element method (FEM) modeling may permit non-invasive, high-resolution intracerebral impedance prediction. However, expectations for tissue-impedance relationships and experimentally verified parameters for impedance modeling in human brains are lacking. This study seeks to address this need.Approach.We used FEM to simulate high-resolution single- and dual-electrode impedance measurements along linear electrode trajectories through (1) canonical gray and white matter tissue models, and (2) selected anatomic structures within whole-brain patient DTI-based models. We then compared intraoperative impedance measurements taken at known locations along deep brain stimulation (DBS) surgical trajectories with model predictions to evaluate model accuracy and refine model parameters.Main results.In DTI-FEM models, single- and dual-electrode configurations performed similarly. While only dual-electrode configurations were sensitive to white matter fiber orientation, other influences on impedance, such as white matter density, enabled single-electrode impedance measurements to display significant spatial variation even within purely white matter structures. We compared 308 intraoperative single-electrode impedance measurements in five DBS patients to DTI-FEM predictions at one-to-one corresponding locations. After calibration of model coefficients to these data, predicted impedances reliably estimated intraoperative measurements in all patients (R=0.784±0.116,n=5). Through this study, we derived an updated value for the slope coefficient of the DTI conductance model published by Tuchet al,k=0.0649 S⋅smm-3 (originalk=0.844), for use specifically in humans at physiological frequencies.Significance.This is the first study to compare impedance estimates from imaging-based models of human brain tissue to experimental measurements at the same locationsin vivo. Accurate, non-invasive, imaging-based impedance prediction has numerous applications in functional neurosurgery, including tissue mapping, intraoperative electrode localization, and DBS.

First operation and validation of simulations for the divertor cryo-vacuum pump in Wendelstein 7-X

Ten cryo-vacuum pumps (CVPs) were installed in the subdivertor region of each island divertor in the stellarator Wendelstein 7-X (W7-X) and operated for the first time during the recently completed plasma campaign OP2.1. A pumping speed of 70 ± 1m3s was measured during dedicated tests with known hydrogen gas injection. Based on a conductance model, the estimated pumping speed ranges from 86-93m3s for different sticking coefficients between 0.6 and 0.8. After completion of the initial tests the CVPs were operated successfully throughout the campaign, with regeneration performed once a week. Neutral gas pressures in the subdivertor in the range of 10−4mbar are well within the molecular flow regime and limit the particle exhaust capabilities of the CVPs. Simulations of the neutral gas pressure in the three-dimensional complex geometry of the subdivertor were performed using the DIVGAS code based on the direct simulation Monte Carlo method and a model implemented in the steady-state thermal package in ANSYS, which are in agreement with the measured values during plasma operation.

The response of mesophyll conductance to short-term CO2 variation is related to stomatal conductance.

The response of mesophyll conductance (gm) to CO2 plays a key role in photosynthesis and ecosystem carbon cycles under climate change. Despite numerous studies, there is still debate about how gm responds to short-term CO2 variations. Here we used multiple methods and looked at the relationship between stomatal conductance to CO2 (gsc) and gm to address this aspect. We measured chlorophyll fluorescence parameters and online carbon isotope discrimination (Δ) at different CO2 mole fractions in sunflower (Helianthus annuus L.), cowpea (Vigna unguiculata L.), and wheat (Triticum aestivum L.) leaves. The variable J and Δ based methods showed that gm decreased with an increase in CO2 mole fraction, and so did stomatal conductance. There were linear relationships between gm and gsc across CO2 mole fractions. gm obtained from A-Ci curve fitting method was higher than that from the variable J method and was not representative of gm under the growth CO2 concentration. gm could be estimated by empirical models analogous to the Ball-Berry model and the USO model for stomatal conductance. Our results suggest that gm and gsc respond in a coordinated manner to short-term variations in CO2, providing new insight into the role of gm in photosynthesis modelling.

Improved Conductance Blockage Modeling of Cylindrical Nanopores, from 2D to Thick Membranes.

The ionic current blockage from a nanopore sensor is a fundamental metric for characterizing its dimensions and identifying molecules translocating through it. Yet, most analytical models predicting the conductance of a nanopore in both open and obstructed states remain inaccurate. Here, using an oblate spheroidal coordinate framework to study the electrical response of nanopore access regions, we reveal that the widely used model from Kowalczyk et al. significantly overestimates access region contributions when blocked by a cylindrical object, like DNA. To address this, we present an improved analytical model for the obstructed access resistance, which we establish as highly accurate through finite-element simulations, especially for ultrathin membranes and long narrow channels. Equipped with an improved nanopore conductance model, this work provides tools for more accurate calculation of the pore size and for the expected blockade from DNA, of high practical value for many biosensing applications.

Extended metric validation of a semi-physical Space Weather Modeling Framework conductance model on field-aligned current estimations

In this study, a detailed metric survey on the “Galaxy 15” (April 2010) space weather event is conducted to validate MAGNetosphere–Ionosphere–Thermosphere (MAGNIT), a semi-physical auroral ionospheric conductance model characterizing four precipitation sources, against AMPERE measurements via field-aligned current (FAC) characteristics. As part of this study, the comparative performance of three ionosphere electrodynamic specifications involving auroral conductance models, MAGNIT, Ridley Legacy Model (RLM) (empirical), and Conductance Model for Extreme Events (CMEE) (empirical), within the Space Weather Modeling Framework (SWMF), is demonstrated. Overall, MAGNIT exhibits marginally improved predictions; root mean square error values in upward and downward FACs of MAGNIT predictions compared to AMPERE data are smaller than those of CMEE and Ridley Ionosphere Model (RIM) by ∼12.7% and ∼6.24% before the storm, ∼4.52% and ∼2.13% better during the main phase, ∼1.98% and ∼1.27% worse during the second minimum, and better by ∼1.84% and ∼1.49% by the beginning of the recovery, respectively. In all three model configurations, the dusk and night magnetic local time (MLT) sectors over-predict throughout the storm, while the day and dawn MLT sectors under-predict in response to interplanetary magnetic field (IMF) conditions. In addition to accuracy and bias, similar results and conclusions are drawn from additional metrics, including in the categories of correlation, precision, extremes, and skill, and recommendations are made for the best-performing model configuration in each metric category. Visual data–model comparisons conducted by studying the FAC location and latitude/MLT spread throughout various phases of the storm suggest that the spatial extent of the FACs is captured relatively well in the night-side auroral oval, unlike in the day-side oval. The spread in latitude of the FACs matches that in the previous literature on other model performances. This information on auroral precipitation sources and their weight on FACs, along with metrics from model–data comparisons, can be used to modify MAGNIT settings to optimize SWMF model performance.

Computation of biological conductance with Liouville quantum master equation

Recent experiments have revealed that single proteins can display high conductivity, which stays finite for low temperatures, decays slowly with distance, and exhibits a rich spatial structure featuring highly conducting and strongly insulating domains. Here, we intruduce a new formula by combining the density matrix of the Liouville-Master Equation simulating quantum transport in nanoscale devices, and the phenomenological model of electronic conductance through molecules, that can account for the observed distance- and temperature dependence of conductance in proteins. We demonstrate its efficacy on experimentally highly conductive extracellular cytochrome nanowires, which are good candidates to illustrate our new approach by calculating and visualizing their electronic wiring, given the interest in the arrangement of their conducting and insulating parts. As proteins and protein nanowires exhibit significant potential for diverse applications, including energy production and sensing, our computational technique can accelerate the design of nano-bioelectronic devices.

Transient behaviour and heat transfer characteristics in debris beds: Simulation and analysis of the LIVEJ2 experiment

Multiple uncertainties still exist about the state of the debris in Fukushima Daiichi Nuclear Power Station (1F). In the past, the attention of the nuclear safety community was focused on the heat transfer characteristics in the case of an homogeneous pool, but little attention was given to address the melting and heat transfer in the presence of a debris bed constituted of materials with different melting points. This condition represents a challenge for CFD analyses, because it includes multi-physics conditions, such as a low melting point fluid convecting into a debris bed surrounded by a crust on the vessel wall which has received little attention compared to classical CFD analyses. Even though a comprehensive analysis of a related experiment (i.e. LIVE-J2) has been performed recently by Madokoro et al. (2023) little attention on the results has been paid to the effect of debris bed porosity and the existence of a gap between the vessel wall and the crust. In the paper we have modified the porosity resistance based on the Ergun equation and proposed a simple model for the gap conductance in the lower part of the crust. The results show an improvement in the prediction of the thermal stratification and the vessel temperature in the lower locations. In addition, highlight that such phenomena constitute key parameters to keep into consideration in the simulation of prototypical cases both for CFD and lumped parameter codes (e.g. MELCOR, MAAP).

Structural Constraints in Current Stomatal Conductance Models Preclude Accurate Prediction of Evapotranspiration

AbstractEvapotranspiration (ET) plays a critical role in water and energy budgets at regional to global scales. ET is composed of direct evaporation (E) and plant transpiration (T) where the latter is regulated via stomatal conductance (gsc), which depends on a multitude of plant physiological processes and hydrometeorological forcings. In recent years, significant advances have been made toward estimating gsc using a variety of models, ranging from relatively simple empirical models to more complex and data‐intensive plant hydraulic models. Using machine learning (ML) and eddy covariance flux tower data of 642 site years across 84 sites distributed across 10 land covers globally, here we show that structural constraints inherent in current empirical and plant hydraulic models of gsc limit their effectiveness for predicting ET. These constraints also prevent the models from fully utilizing the available hydrometeorological data at eddy covariance sites. Even if these gsc models are calibrated locally, structural simplifications inherent in them limit their capability to accurately capture gsc dynamics. In contrast, a ML approach, wherein the model structure is learned from the data, outperforms traditional models, thus highlighting that there still is significant room for improvement in the structure of traditional models for predicting ET. These results underscore the need to prioritize improvements in gsc models for more accurate ET estimation. This, in turn, will help reduce uncertainties in the assessments of plants' role in regulating the Earth's climate.

Phenology- and light-based parameterization of stomatal conductance model for urban woody species in northern China

Surface ozone (O3) poses a significant threat to urban vegetation health, and assessing the O3 risk across woody species is of vital importance for maintaining the health of urban infrastructure. In the present study, Jarvis-type stomatal conductance model was parameterized for ten urban species in northern China. Incorporating the effects of time of day and diurnal O3 concentration significantly enhanced the model performance. For different plant functional types (greening trees, greening shrubs, and orchard-grown trees), three parameterizations were established to estimate stomatal O3 uptake (POD1, phytotoxic O3 dose over an hourly threshold of 1 nmol m−2 s−1). The differences in POD1 between greening trees and shrubs were primarily due to the difference in their stomatal sensitivity to light. Orchard-grown trees displayed the lowest O3 removal capacity (lowest value of POD1) because of their shorter growing season despite of high stomatal conductance. These results indicated that plant phenology and light responsiveness determined stomatal O3 uptake, and the three parameterizations developed here could be applicable to various urban species in northern regions. Among climatic factors for O3 risk assessment, O3 concentration was the most important factor determining annual variation of POD1, which was primarily driven by air temperature. However, when O3 pollution decreased, O3 concentration exhibited less dependence on temperature and more dependence on light. These findings provide crucial insights for urban policy-makers and environmental scientists aiming to mitigate O3 pollution effects and enhance urban vegetation health.

Exploring the influence of pore shape on conductance and permeation

There are increasing numbers of ion channel structures featuring heteromeric subunit assembly, exemplified by synaptic α1βB glycine and α4β2 nicotinic receptors. These structures exhibit inherent pore asymmetry, but the relevance of this to function is unknown. Furthermore, molecular dynamics simulations performed on symmetrical homomeric channels often lead to thermal distortion whereby conformations of the resulting ensemble are also asymmetrical. When functionally annotating ion channels, researchers often rely on minimal constrictions determined via radius-profile calculations performed with computer programs, such as HOLE or CHAP, coupled with an assessment of pore hydrophobicity. However, such tools typically employ spherical probe particles, limiting their ability to accurately capture pore asymmetry. Here, we introduce an algorithm that employs ellipsoidal probe particles, enabling a more comprehensive representation of the pore geometry. Our analysis reveals that the use of nonspherical ellipsoids for pore characterization provides a more accurate and easily interpretable depiction of conductance. To quantify the implications of pore asymmetry on conductance, we systematically investigated carbon nanotubes with varying degrees of pore asymmetry as model systems. The conductance through these channels shows surprising effects that would otherwise not be predicted with spherical probes. The results have broad implications not only for the functional annotation of biological ion channels but also for the design of synthetic channel systems for use in areas such as water filtration. Furthermore, we make use of the more accurate characterization of channel pores to refine a physical conductance model to obtain a heuristic estimate for single-channel conductance. The code is freely available, obtainable as pip-installable python package and provided as a web service.

Development of a multi-layer canopy model for E3SM Land Model with support for heterogeneous computing

The vertical structure of vegetation canopies creates micro-climates. However, the land components of most Earth System Models, including the Energy Exascale Earth System Model (E3SM), typically neglect vertical canopy structure by using a single layer big-leaf representation to simulate water, CO2, and energy exchanges between the land and the atmosphere. In this study, we developed a Multi-Layer Canopy Model for the E3SM Land Model to resolve the micro-climate created by vegetation canopies. The model developed in this study re-implements the CLM-ml_v1 to support heterogeneous computing architectures consisting of CPUs and GPUs and includes three additional optimization-based stomatal conductance models. The use of Portable, Extensible Toolkit for Scientific Computation provides a speedup of 25–50 times on a GPU relative to a CPU. The numerical implementation of the model was verified against CLM-ml_v1 for a month-long simulation using data from the Ameriflux US-University of Michigan Biological Station site. Model structural uncertainty was explored by performing control simulations for five stomatal conductance models that exclude and include the control of plant hydrodynamics (PHD) on photosynthesis. The bias in simulated sensible and latent heat fluxes was lower when PHD was accounted for in the model. Additionally, six idealized simulations were performed to study the impact of three environmental variables (i.e. air temperature, atmospheric CO2, and soil moisture) on canopy processes (i.e. net CO2 assimilation, leaf temperature, and leaf water potential). Increasing air temperature reduced net CO2 assimilation and increased air temperature. Net CO2 assimilation increased at higher atmospheric CO2, while decreasing soil moisture resulted in lower leaf water potential.

A Reinterpretation of the Relationship between Persistent and Resurgent Sodium Currents.

The resurgent sodium current (INaR) activates on membrane repolarization, such as during the downstroke of neuronal action potentials. Due to its unique activation properties, INaR is thought to drive high rates of repetitive neuronal firing. However, INaR is often studied in combination with the persistent or noninactivating portion of sodium currents (INaP). We used dynamic clamp to test how INaR and INaP individually affect repetitive firing in adult cerebellar Purkinje neurons from male and female mice. We learned INaR does not scale repetitive firing rates due to its rapid decay at subthreshold voltages and that subthreshold INaP is critical in regulating neuronal firing rate. Adjustments to the voltage-gated sodium conductance model used in these studies revealed INaP and INaR can be inversely scaled by adjusting occupancy in the slow-inactivated kinetic state. Together with additional dynamic clamp experiments, these data suggest the regulation of sodium channel slow inactivation can fine-tune INaP and Purkinje neuron repetitive firing rates.

Explicit Consideration of Plant Xylem Hydraulic Transport Improves the Simulation of Crop Response to Atmospheric Dryness in the U.S. Corn Belt

AbstractAtmospheric dryness (i.e., high vapor pressure deficit, VPD), together with soil moisture stress, limits plant photosynthesis and threatens ecosystem functioning. Regions where rainfall and soil moisture are relatively sufficient, such as the rainfed part of the U.S. Corn Belt, are especially prone to high VPD stress. With globally projected rising VPD under climate change, it is crucial to understand, simulate, and manage its negative impacts on agricultural ecosystems. However, most existing models simulating crop response to VPD are highly empirical and insufficient in capturing plant response to high VPD, and improved modeling approaches are urgently required. In this study, by leveraging recent advances in plant hydraulic theory, we demonstrate that the VPD constraints in the widely used coupled photosynthesis‐stomatal conductance models alone are inadequate to fully capture VPD stress effects. Incorporating plant xylem hydraulic transport significantly improves the simulation of transpiration under high VPD, even when soil moisture is sufficient. Our results indicate that the limited water transport capability from the plant root to the leaf stoma could be a major mechanism of plant response to high VPD stress. We then introduce a Demand‐side Hydraulic Limitation Factor (DHLF) that simplifies the xylem and the leaf segments of the plant hydraulic model to only one parameter yet captures the effect of plant hydraulic transport on transpiration response to high VPD with similar accuracy. We expect the improved understanding and modeling of crop response to high VPD to help contribute to better management and adaptation of agricultural systems in a changing climate.

A Reinterpretation of the Relationship Between Persistent and Resurgent Sodium Currents.

The resurgent sodium current (INaR) activates on membrane repolarization, such as during the downstroke of neuronal action potentials. Due to its unique activation properties, INaR is thought to drive high rates of repetitive neuronal firing. However, INaR is often studied in combination with the persistent or non-inactivating portion of sodium currents (INaP). We used dynamic clamp to test how INaR and INaP individually affect repetitive firing in adult cerebellar Purkinje neurons from male and female mice. We learned INaR does not scale repetitive firing rates due to its rapid decay at subthreshold voltages, and that subthreshold INaP is critical in regulating neuronal firing rate. Adjustments to the Nav conductance model used in these studies revealed INaP and INaR can be inversely scaled by adjusting occupancy in the slow inactivated kinetic state. Together with additional dynamic clamp experiments, these data suggest the regulation of sodium channel slow inactivation can fine-tune INaP and Purkinje neuron repetitive firing rates.

Modeling heat and mass transfer in granular flows between vertical parallel plates

Gravity-driven granular flows between vertical parallel plates at elevated temperatures are integral in the development of the next generation of particle-based heat exchangers for concentrated solar power. Efficient modeling methodologies that accurately captures the heat transfer mechanisms of temperature-dependent granular flows are essential to effectively design and evaluate these heat exchangers. Transient, pseudo-one-dimensional heat and mass transfer models were developed for inlet flow temperatures between 473 and 1073 K. The mass transfer models for the granular flows were resolved using discrete element method simulation, providing detailed temporal and spatial distributions of flow parameters in good agreement with experimental measurements. The heat transfer model employed a one-dimensional, two-phase, continuum approach, and a system of non-linear differential equations was solved via finite difference method. The particle-to-wall contact heat transfer was determined with an effective thermal conductance model. Radiative heat transfer between particles and walls was also considered. The predicted particle and wall temperatures for two different channel widths of 6.4 and 2 mm were well-correlated to previously obtained experimental measurements with Pearson’s correlation coefficients greater than 0.91. A significant disparity in particle temperature of up to 72 K was observed when radiative heat transfer was omitted, and a maximum temperature difference of 11 K was observed when temperature-dependent granular flow properties were not considered. The model revealed that radiative heat transfer potentially contributed to > 30 % of heat losses in wider channels at high inlet temperatures, and conduction was the dominated heat transfer mechanisms in narrower channels (∼70 %) due to increased particle-to-wall contact. This accurate model, leveraging discrete element method in a streamlined approach, advances the understanding and modeling of heat transfer in granular flows at elevated temperatures, enabling more efficient and reliable solar thermal energy storage and transport.

Evidence of field‐scale shifts in transpiration dynamics following bark beetle infestation: Stomatal conductance responses

AbstractAmplified eruptive outbreaks of bark beetles as a consequence of climate change can cause tree mortality that significantly affects terrestrial water and carbon fluxes. However, the lack of field‐scale observations of underlying physiological mechanisms currently hampers the expression of such ecosystem disturbances in predictive modelling. Based on a unique flux tower dataset from a subalpine forest located in the Rocky Mountains, mechanisms of stomatal response to an extensive bark beetle outbreak were investigated using various models and parametrizations. The datasets cover a decade, including the periods of pre‐infestation, infestation, and post‐infestation. Field measurements showed considerable decreases in evapotranspiration (ET), transpiration (T), and leaf area index (LAI) during the two‐year infestation period compared to the pre‐infestation period. Model interpretations of observed water and carbon fluxes indicated that the overall reductions in T were not solely due to decreased LAI, but also to changes in physiological behaviours. The summer season's canopy‐scale stomatal conductance was significantly reduced during the infestation period, from 0.0018 to 0.0011 m s−1. One primary reason for the observed variations is likely that the bark beetle infestation hampers the water transport in the xylem. The damage of xylem has important implications for water use efficiency (WUE), which also significantly influences the parameterization of stomatal conductance. When using stomatal conductance models to forecast ecosystem dynamics, it is crucial to recalibrate the model's parameters to ensure the accurate depiction of stomatal dynamics during various infestation periods. The neglect of the temporal variability of canopy‐scale stomatal conductance under ecosystem disturbances (e.g., bark beetle infestations) in current earth system models, therefore, requires specific attention in assessments of large‐scale water and carbon balances.

Estimation of persistent sodium-current density in rat hippocampal mossy fibre boutons: Correction of space-clamp errors.

We used whole-cell patch clamp to estimate the stationary voltage dependence of persistent sodium-current density (iNaP) in rat hippocampal mossy fibre boutons. Cox's method for correcting space-clamp errors was extended to the case of an isopotential compartment with attached neurites. The method was applied to voltage-ramp experiments, in which iNaP is assumed to gate instantaneously. The raw estimates of iNaP led to predicted clamp currents that were at variance with observation, hence an algorithm was devised to improve these estimates. Optionally, the method also allows an estimate of the membrane specific capacitance, although values of the axial resistivity and seal resistance must be provided. Assuming that membrane specific capacitance and axial resistivity were constant, we conclude that seal resistance continued to fall after adding TTX to the bath. This might have been attributable to a further deterioration of the seal after baseline rather than an unlikely effect of TTX. There was an increase in the membrane specific resistance in TTX. The reason for this is unknown, but it meant that iNaP could not be determined by simple subtraction. Attempts to account for iNaP with a Hodgkin-Huxley model of the transient sodium conductance met with mixed results. One thing to emerge was the importance of voltage shifts. Also, a large variability in previously reported values of transient sodium conductance in mossy fibre boutons made comparisons with our results difficult. Various other possible sources of error are discussed. Simulations suggest a role for iNaP in modulating the axonal attenuation of EPSPs. KEY POINTS: We used whole-cell patch clamp to estimate the stationary voltage dependence of persistent sodium-current density (iNaP) in rat hippocampal mossy fibre boutons, using a KCl-based internal (pipette) solution and correcting for the liquid junction potential (2mV). Space-clamp errors and deterioration of the patch-clamp seal during the experiment were corrected for by compartmental modelling. Attempts to account for iNaP in terms of the transient sodium conductance met with mixed results. One possibility is that the transient sodium conductance is higher in mossy fibre boutons than in the axon shaft. The analysis illustrates the need to account for various voltage shifts (Donnan potentials, liquid junction potentials and, possibly, other voltage shifts). Simulations suggest a role for iNaP in modulating the axonal attenuation of excitatory postsynaptic potentials, hence analog signalling by dentate granule cells.

Optimizing seasonally variable photosynthetic parameters based on joint carbon and water flux constraints

Terrestrial biosphere models (TBMs) often adopt the Farquhar biochemical model coupled with the Ball-Berry stomatal conductance (gs) model to simulate ecosystem carbon and water fluxes. The parameters m, representing the sensitivity of gs to the photosynthetic rate, and Vcmax25, representing the leaf photosynthetic capacity, are two pivotal parameters but the two main sources of uncertainties in TBM simulations. The temporal variations of m in TBMs are still elusive, due to the lack of direct observations. It also remains unclear how accurate estimates of m and Vcmax25 can improve the simulations of carbon and water fluxes. In this study, we used a Bayesian parameter optimization approach to estimate seasonally varying m and Vcmax25 from eddy covariance observations in a mixed forest stand at the Borden Forest Research Station located in southern Ontario, Canada and used in-situ observations of m and Vcmax25 for validation. Three strategies were tested for optimizing m and Vcmax25, including the carbon, water, and carbon-water coupling scenarios. m and Vcmax25 optimized from carbon-water coupling constraints shows best correlations with the measured m (R2 = 0.70) and Vcmax25 (R2 = 0.70). By incorporating optimized m and Vcmax25with seasonal variations, we found considerable improvements in the estimated gross primary productivity (GPP) and evapotranspiration (ET) compared with constant m and Vcmax25, with R2 increasing from 0.78 to 0.85 for GPP, from 0.65 to 0.71 for ET and RMSE reducing from 2.579 g C m−2d−1 to 2.038 g C m−2d−1 for GPP, from 1.151 mm d−1 to 0.137 mm d−1 for ET. This study proposes an effective approach to retrieve m and Vcmax25 for TBMs and demonstrates the efficacy of incorporating seasonally variable m and Vcmax25 for reducing the uncertainties in GPP and ET simulations, which supports accurate quantifications of land-atmosphere exchanges.