Environmental control of natural gap size distribution in tropical forests

Natural disturbances are the dominant form of forest regeneration and dynamics in unmanaged tropical forests. Monitoring the size distribution of treefall gaps is important to better understand and predict the carbon budget in response to land use and other global changes. In this study, we model the size frequency distribution of natural canopy gaps with a discrete power law distribution. We use a Bayesian framework to introduce and test, using Monte Carlo Markov chain and Kuo–Mallick algorithms, the effect of local physical environment on gap size distribution. We apply our methodological framework to an original light detecting and ranging dataset in which natural forest gaps were delineated over 30 000 ha of unmanaged forest. We highlight strong links between gap size distribution and environment, primarily hydrological conditions and topography, with large gaps being more frequent on floodplains and in wind-exposed areas. In the future, we plan to apply our methodological framework on a larger scale using satellite data. Additionally, although gap size distribution variation is clearly under environmental control, variation in gap size distribution in time should be tested against climate variability

CoEvolution of Effective Observers and Observed Multi-agents System

SCOPUS: cp.kinfo:eu-repo/semantics/publishe

Understanding RRAM endurance, retention and window margin trade-off using experimental results and simulations

International audienceIn this paper we clarify for the first time the correlation between endurance, window margin and retention of Resistive RAM. To this aim, various classes of RRAM (OXRAM and CBRAM) are investigated, showing high window margin up to 10 10 cycles or high 300°C retention. From first principle calculations, we analyze the conducting filament composition for the various RRAM technologies, and extract the key filament features. We then propose an analytical model to calculate the dependence between endurance, window margin and retention, linking material parameters to memory characteristics

A global reference dataset for remote sensing of forest biomass. The Forest Observation System approach

Forest biomass is an essential indicator for monitoring the Earth’s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities. Live, most up-to-date dataset is available at https://forest-observation-system.net

Additional file 3: of Computational analysis of mRNA expression profiling in the inner ear reveals candidate transcription factors associated with proliferation, differentiation, and deafness

Deafness genes. Genes associated with deafness compiled from www.hereditaryhearingloss.org (updated 3/13/17), and the differential expression results for the mouse orthologs of the deafness genes. (XLSX 37 kb