Ecological filtering shapes the impacts of agricultural deforestation on biodiversity.

The biodiversity impacts of agricultural deforestation vary widely across regions. Previous efforts to explain this variation have focused exclusively on the landscape features and management regimes of agricultural systems, neglecting the potentially critical role of ecological filtering in shaping deforestation tolerance of extant species assemblages at large geographical scales via selection for functional traits. Here we provide a large-scale test of this role using a global database of species abundance ratios between matched agricultural and native forest sites that comprises 71 avian assemblages reported in 44 primary studies, and a companion database of 10 functional traits for all 2,647 species involved. Using meta-analytic, phylogenetic and multivariate methods, we show that beyond agricultural features, filtering by the extent of natural environmental variability and the severity of historical anthropogenic deforestation shapes the varying deforestation impacts across species assemblages. For assemblages under greater environmental variability-proxied by drier and more seasonal climates under a greater disturbance regime-and longer deforestation histories, filtering has attenuated the negative impacts of current deforestation by selecting for functional traits linked to stronger deforestation tolerance. Our study provides a previously largely missing piece of knowledge in understanding and managing the biodiversity consequences of deforestation by agricultural deforestation.

Study on nonlinear dynamics characteristics of dual speed dual clutch transmission system based on bond graph.

The variable speed transmission system employs compound planetary gear trains and clutches. Compared to traditional aviation transmission systems, the added control parts in the variable transmission system result in a stronger coupling between components and more complex dynamic response characteristics. Modeling using the central mass method is complex and abstract. This study proposes a bond graph-based method for modeling and analyzing the dynamic behavior of the variable transmission system. The transmission system is divided into multiple component-level real-time dynamic models, and obtain a nonlinear multi-energy domain shift dynamic models based on energy flow paths coupling. The mathematical model is numerically solved using the Runge-Kutta method. Simulation results show that there is a delay in the speed response during the shifting process. Further analysis reveals that this "give and take" phenomenon is related to the mechanical structure and passive working principle of the one-way clutch. Subsequently, the time-domain response of the output speed under the hydraulic loading characteristic curves of linear, exponential, S-shaped, and composite functions, as well as the clutch torque, were studied. The impact of different hydraulic loading durations based on the exponential curve on component speed and torque was also analyzed. The simulation results provide a theoretical basis for designing low-shift impact, high-reliability, and high-performance variable transmission systems.

Quantifying the kinetic stability of hyperstable proteins via time-dependent SDS trapping.

Globular proteins are usually in equilibrium with unfolded conformations, whereas kinetically stable proteins (KSPs) are conformationally trapped by their high unfolding transition state energy. Kinetic stability (KS) could allow proteins to maintain their activity under harsh conditions, increase a protein's half-life, or protect against misfolding-aggregation. Here we show the development of a simple method for quantifying a protein's KS that involves incubating a protein in SDS at high temperature as a function of time, running the unheated samples on SDS-PAGE, and quantifying the bands to determine the time-dependent loss of a protein's SDS resistance. Six diverse proteins, including two monomer, two dimers, and two tetramers, were studied by this method, and the kinetics of the loss of SDS resistance correlated linearly with their unfolding rate determined by circular dichroism. These results imply that the mechanism by which SDS denatures proteins involves conformational trapping, with a trapping rate that is determined and limited by the rate of protein unfolding. We applied the SDS trapping of proteins (S-TraP) method to superoxide dismutase (SOD) and transthyretin (TTR), which are highly KSPs with native unfolding rates that are difficult to measure by conventional spectroscopic methods. A combination of S-TraP experiments between 75 and 90 °C combined with Eyring plot analysis yielded an unfolding half-life of 70 ± 37 and 18 ± 6 days at 37 °C for SOD and TTR, respectively. The S-TraP method shown here is extremely accessible, sample-efficient, cost-effective, compatible with impure or complex samples, and will be useful for exploring the biological and pathological roles of kinetic stability.