Tree transpiration plays a determining role in the water balance of forest stands and in seepage water yields from forested catchments, especially in arid and semiarid regions where climatic conditions are dry with severe water shortage, forestry development is limited by water availability. To clarify the response of water use to climatic conditions, sap flow was monitored by heat pulse velocity method from May to September, 2014, in a 40–year–old Pinus tabulaeformis Carr. plantation forest stands in the semiarid Loess Plateau region of Northwest China. We extrapolated the measurements of water use by individual plants to determine the area–averaged transpiration of the woodlands. The method used for the extrapolation assumes that the transpiration of a tree was proportional to its sapwood area. Stand transpiration was mainly controlled by photosynthetically active radiation and vapor pressure deficit, whereas soil moisture had more influence on monthly change in stand transpiration. The mean sap flow rates for individual P. tabulaeformis trees ranged from 9 to 54 L d−1. During the study period, the mean daily stand transpiration was 1.9 mm day–1 (maximum 2.9 and minimum 0.8 mm day–1) and total stand transpiration from May to September was 294.1 mm, representing 76% of the incoming precipitation over this period. Similar results were found when comparing transpiration estimated with sap flow measurements to the Penman–Monteith method (relative error: 16%), indicating that the scaling procedure can be used to provide reliable estimates of stand transpiration. These results suggested that P. tabulaeformis is highly effective at utilizing scarce water resources in semiarid environments.
The proposed article deals with uncertain description of permanent-magnet DC motor Maxon RE 35 via parametric uncertainty and H-infinity controller design. There was analyzed influence of uncertainties of the particular motor parameters on the model behavior. Consequently there was designed an H-infinity controller via Matlab functions. The behavior of the obtained controller was analyzed on the step responses and course tracking of the closed loop with the nominal system and the system with perturbed parameters. and Obsahuje seznam literatury
The Global Navigation Satellite System (GNSS) can provide the daily position time series for the geodesy and geophysical studies. However, due to various unpredictable factors, such as receiver failure or bad observation conditions, missing data inevitably exist in GNSS position time series. Most traditional time series analysis methods require the time series should be completed. Therefore, filling the missing data is a valuable step before analyzing the GNSS time series. In this study, a new method named Iteration Empirical Mode Decomposition (Iteration EMD) is proposed to fill the missing data in GNSS position time series. The simulation experiments are performed by randomly removing different missing percentages of the synthetic time series, with the added different types noise. The results show that Iteration EMD approach performs well regardless of high or low missing percentage. When the missing percentage increases from 5 % to 30 % with a step of 5 %, all the Root Mean Square Errors (RMSE) and Mean Absolute Errors (MAE) of Iteration EMD are smaller than Interpolation EMD. The relative improvements at different percentages of Iteration EMD relative to Interpolation EMD are significant, especially for the high missing percentage. The real GNSS position time series of eight stations were selected to further evaluate the performance of Iteration EMD with an average missing percentage 8.15 %. Principal Component Analysis (PCA) was performed on the filled time series, which is used to assess the interpolation performance of Iteration EMD and Interpolation EMD. The results show that Iteration EMD can preserve variance 75.9 % with the first three Principal Components (PC), more than 66.5% of interpolation EMD. Therefore, we can conclude that Iteration EMD is an efficient interpolation method for GNSS position time series, which can make full use of available information in existing time series to fill the missing data.
The aim of this study was to explore how the mitochondrial alternative oxidase (AOX) pathway alleviates photoinhibition in chilled tomato (Solanum lycopersicum) seedlings. Chilling induced photoinhibition in tomato seedlings despite the increases in thermal energy dissipation and cyclic electron flow around PSI (CEF-PSI). Chilling inhibited the function of PSII and blocked electron transport at the PSII acceptor side, however, it did not affect the oxygen-evolving complex on the donor side of PSII. Upregulation of the AOX pathway protects against photoinhibition by improving PSII function and photosynthetic electron transport in tomato seedlings under chilling stress. The AOX pathway maintained the open state of PSII and the stability of the entire photosynthetic electron transport chain. Moreover, the protective role of the AOX pathway on PSII was more important than that on PSI. However, inhibition of the AOX pathway could be compensated by increasing CEF-PSI activity under chilling stress.