A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation

Few models exist that accurately reproduce the complex rhythms of the thalamocortical system that are apparent in measured scalp EEG and at the same time, are suitable for large-scale simulations of brain activity. Here, we present a neural mass model of the thalamocortical system during natural non-REM sleep, which is able to generate fast sleep spindles (12–15 Hz), slow oscillations (<1 Hz) and K-complexes, as well as their distinct temporal relations, and response to auditory stimuli. We show that with the inclusion of detailed calcium currents, the thalamic neural mass model is able to generate different firing modes, and validate the model with EEG-data from a recent sleep study in humans, where closed-loop auditory stimulation was applied. The model output relates directly to the EEG, which makes it a useful basis to develop new stimulation protocols

Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model

NREM sleep is characterized by two hallmarks, namely K-complexes (KCs) during sleep stage N2 and cortical slow oscillations (SOs) during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep

Putting vascular epiphytes on the traits map

Abstract: Plant functional traits impact the fitness and environmental niche of plants. Major plant functional types have been characterized by their trait spectrum, and the environmental and phylogenetic imprints on traits have advanced several ecological fields. Yet, very few trait data on epiphytes, which represent almost 10% of vascular plants, are available. We collated 76,561 trait observations for 2,882 species of vascular epiphytes and compared these to non‐epiphytic herbs and trees to test hypotheses related to how the epiphytic habit affects traits, and if epiphytes occupy a distinct region in the global trait space. We also compared variation in traits among major groups of epiphytes, and investigated the coordination of traits in epiphytes, ground‐rooted herbs and trees. Epiphytes differ from ground‐rooted plants mainly in traits related to water relations. Unexpectedly, we did not find lower leaf nutrient concentrations, except for nitrogen. Mean photosynthetic rates are much lower than in ground‐rooted plants and lower than expected from the nitrogen concentrations. Trait syndromes clearly distinguish epiphytes from trees and from most non‐epiphytic herbs. Among the three largest epiphytic taxa, orchids differ from bromeliads and ferns mainly by having smaller and more numerous stomata, while ferns differ from bromeliads by having thinner leaves, higher nutrient concentrations, and lower water content and water use efficiency. Trait networks differ among epiphytes, herbs and trees. While all have central nodes represented by SLA and mass‐based photosynthesis, in epiphytes, traits related to plant water relations have stronger connections, and nutrients other than potassium have weaker connections to the remainder of the trait network. Whereas stem‐specific density reflects mechanical support related to plant size in herbs and trees, in epiphytes it mostly reflects water storage and scales with leaf water content. Synthesis. Our findings advance our understanding of epiphyte ecology, but we note that currently mainly leaf traits are available. Important gaps are root, shoot and whole plant, demographic and gas exchange traits. We suggest how future research might use available data and fill data gaps

Baryon content in a sample of 91 galaxy clusters selected by the South Pole Telescope at 0.2 <z < 1.25

We estimate total mass (M500), intracluster medium (ICM) mass (MICM), and stellar mass (M) in a Sunyaev–Zel’dovich effect (SZE) selected sample of 91 galaxy clusters with masses M500 2.5 × 1014 M and redshift 0.2 < z < 1.25 from the 2500 deg2 South Pole Telescope SPT-SZ survey. The total masses M500 are estimated from the SZE observable, the ICM masses MICM are obtained from the analysis of Chandra X-ray observations, and the stellar masses M are derived by fitting spectral energy distribution templates to Dark Energy Survey griz optical photometry and WISE or Spitzer near-infrared photometry. We study trends in the stellar mass, the ICM mass, the total baryonic mass, and the cold baryonic fraction with cluster halo mass and redshift. We find significant departures from self-similarity in the mass scaling for all quantities, while the redshift trends are all statistically consistent with zero, indicating that the baryon content of clusters at fixed mass has changed remarkably little over the past ≈9 Gyr. We compare our results to the mean baryon fraction (and the stellar mass fraction) in the field, finding that these values lie above (below) those in cluster virial regions in all but the most massive clusters at low redshift. Using a simple model of the matter assembly of clusters from infalling groups with lower masses and from infalling material from the low-density environment or field surrounding the parent haloes, we show that the measured mass trends without strong redshift trends in the stellar mass scaling relation could be explained by a mass and redshift dependent fractional contribution from field material. Similar analyses of the ICM and baryon mass scaling relations provide evidence for the so-called ‘missing baryons’ outside cluster virial regions

Stable carbon and nitrogen isotopic composition of leaves, litter, and soils of various ecosystems along an elevational and land-use gradient at Mount Kilimanjaro, Tanzania

© Author(s) 2019. Variations in the stable isotopic composition of carbon (δ13C) and nitrogen (δ15N) of fresh leaves, litter, and topsoils were used to characterize soil organic matter dynamics of 12 tropical ecosystems in the Mount Kilimanjaro region, Tanzania. We studied a total of 60 sites distributed along five individual elevational transects (860- 4550ma.s.l.), which define a strong climatic and land-use gradient encompassing semi-natural and managed ecosystems. The combined effects of contrasting environmental conditions, vegetation, soil, and management practices had a strong impact on the δ13C and δ15N values observed in the different ecosystems. The relative abundance of C3 and C4 plants greatly determined the δ13C of a given ecosystem. In contrast, δ15N values were largely controlled by land-use intensification and climatic conditions. The large δ13C enrichment factors (δ13Clitter -δ13Csoil) and low soil C=N ratios observed in managed and disturbed systems agree well with the notion of altered SOM dynamics. Besides the systematic removal of the plant biomass characteristic of agricultural systems, annual litterfall patterns may also explain the comparatively lower contents of C and N observed in the topsoils of these intensively managed sites. Both δ15N values and calculated δ15N-based enrichment factors (δ15Nlitter -δ15Nsoil/ suggest the tightest nitrogen cycling at high-elevation (>3000ma.s.l.) ecosystems and more open nitrogen cycling both in grass-dominated and intensively managed cropping systems. However, claims about the nature of the N cycle (i.e. open or closed) should not be made solely on the basis of soil δ15N as other processes that barely discriminate against 15N (i.e. soil nitrate leaching) have been shown to be quite significant in Mount Kilimanjaro's forest ecosystems. The negative correlation of δ15N values with soil nitrogen content and the positive correlation with mean annual temperature suggest reduced mineralization rates and thus limited nitrogen availability, at least in high-elevation ecosystems. By contrast, intensively managed systems are characterized by lower soil nitrogen contents and warmer conditions, leading together with nitrogen fertilizer inputs to lower nitrogen retention and thus significantly higher soil δ15N values. A simple function driven by soil nitrogen content and mean annual temperature explained 68% of the variability in soil δ15N values across all sites. Based on our results, we suggest that in addition to land-use intensification, increasing temperatures in a changing climate may promote soil carbon and nitrogen losses, thus altering the otherwise stable soil organic matter dynamics of Mount Kilimanjaro's forest ecosystems

Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha-1yr-1. Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances