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This paper studies the finite-time synchronization problem of fractional-order stochastic memristive bidirectional associative memory neural networks (MBAMNNs) with discontinuous jumps. A novel criterion for finite-time synchronization is obtained by utilizing the properties of quadratic fractional-order Gronwall inequality with time delay and the comparison principle. This criterion provides a new approach to analyze the finite-time synchronization problem of neural networks with stochasticity. Finally, numerical simulations are provided to demonstrate the effectiveness and superiority of the obtained results. [ABSTRACT FROM AUTHOR]

Mangrove forests are large pools of soil organic carbon (SOC) found across the world, and play a vital role in global carbon (C) cycling. In this study, to investigate the effects of spatial factors on SOC in mangrove forests, soil samples at different depth layers from upper estuary (UE), lower estuary (LE), and tidal inlet (TI) in the Qinglangang mangrove forest in Southern China were collected and the differences in SOC among the layers and geomorphological settings were compared. The mean SOC content showed a pattern of LE (4.63 ± 1.28%) > UE (2.94 ± 0.73%) > TI (1.44 ± 0.33%). SOC content and storage decreased with soil depth in TI, but increased in UE. The total SOC storages (0–80 cm) of sites TU, UE, and LE, were 104.41 ± 16.63, 207.14 ± 44.83, and 228.78 ± 19.37 Mg/ha, respectively. The results suggested that top- and subsoil organic C content and storage were largely dependent on their specific location, which underwent different river-sea interactions and human activities. The SOC of the soil profile varied at different sites, implying that the current C storage of mangrove ecosystems can be accurately estimated by quantifying the C of sediments at sites. [ABSTRACT FROM AUTHOR]

Diet analysis is a critical content of animal ecology and the diet analysis methods have been constantly improving and updating. Contrary to traditional methods of high labor intensity and low resolution, the next generation sequencing (NGS) approach has been suggested as a promising tool for dietary studies, which greatly improves the efficiency and broadens the application range. Here we present a framework of adopting NGS and DNA metabarcoding into diet analysis, and discuss the application in aspects of prey taxa composition and structure, intra-specific and inter-specific trophic links, and the effects of animal feeding on environmental changes. Yet, the generation of NGS-based diet data and subsequent analyses and interpretations are still challenging with several factors, making it possible still not as widely used as might be expected. We suggest that NGS-based diet methods must be furthered, analytical pipelines should be developed. More application perspectives, including nutrient geometry, metagenomics and nutrigenomics, need to be incorporated to encourage more ecologists to infer novel insights on they work. [ABSTRACT FROM AUTHOR]