Net depth response of a depth-controllable (towed) gillnet for fish sampling

SUMMARY: Flume-tank experiments were performed to examine the depth response of a new type of depth-controlled gillnet. Variations of net depth were investigated as the warp was paid out and wound up for different changes of warp length, main sinker weights, and winch speeds. In most experiments, when the warp finished paying out, the net continued to descend and then ascended slightly to an equilibrium depth (overshoot phenomenon). The overshoot distance was nearly constant when the warp was wound up and increased linearly with increasing winch speed when the warp was paid out. An increase in winch speed reduced net settling time, which converged on a constant value for both paying out and winding up.     

尼勒克县春小麦田杂草调查及防治策略

运用倒置“W”9点取样法对新疆尼勒克县春小麦田杂草调查结果表明:尼勒克县春小麦田杂草有15种,隶属11个科,其中豆科4种,菊科2种,禾本科、十字花科、旋花科、唇形花科、蓼科、藜科、木贼科、桑科、紫草科各1种。其中块茎香豌豆、野燕麦和苦苣菜几种杂草的相对多度分别为54.9%、52.3%和46%,为优势种群。根据其杂草分布特点,采取农业、物理机械及化学防治措施,能有效控制草害发生与危害。     

沙尘暴应急监测方法研究

在沙尘暴应急监测方法研究中,通过对总悬浮颗粒物采样仪器及各种采样参数的研究确定和降尘采样器的研制,制定出沙尘暴应急监测方法。     

当归茎线虫病田间分布型及抽样技术研究

为提高当归茎线虫病(Ditylenchus destructor)田间抽样的准确度,用7种聚集指标判断了当归茎线虫病的田间分布型.结果表明,当归茎线虫病在田间呈聚集分布,其中奈曼分布(核心分布)的适合率为100%,嵌纹分布(负二项分布)的适合率为77.8%.理论抽样数量约820株.4种抽样方法差异均不显著,在保证抽样数量合理的情况下,4种方法均可采用.     

Evaluation of sampling methods and assessment of the sample size to estimate the weed seedbank in soil, taking into account spatial variability

As field sampling is time consuming, it is necessary to develop efficient sampling techniques to obtain accurate estimates of the weed seedbank in soil. The relative efficiency between sampling schemes depends on the spatial variability in weed seed density across agricultural fields. Spatial variability of the weed seed density was characterized by theoretical correlograms. A systematic sampling (square grill) scheme was considered and it was found that, taking into account spatial variability, this sampling scheme was more efficient than simple random sampling. As a result, the sample size can be reduced in comparison with that given in previous studies, where spatial correlation was ignored. The reduction depends on the correlation structure defined as a function of the ratio, τ, between the nugget effect and the sill of the variogram. The maximum reduction of the sample size, without loss of either precision or confidence level corresponds to the case where there is no nugget effect, τ = 0. The opposite extreme case, where the reduction is nil, corresponds to the case of a pure nugget effect τ = 1. The abaci based on given expressions are provided to determine the sample size in species whose spatial pattern can be fitted either to a Poisson or to a negative binomial distribution.     

应用MODIS-NDVI对草原植被变化监测研究--以锡林郭勒盟为例

利用新一代卫星遥感数据MODIS,进行草原植被专题信息的提取,同时结合地面调查数据,分析2002、2003年5月30日归一化植被指数(NDVI),并根据其分级图,对天然草原植被长势的时间和空间变化特征和变化规律进行研究,从而对引起草原植被发生变化的可能原因,特别是由于禁牧、休牧的影响进行分析评价.     

Heritability and genetic correlations between rumination time and production traits in Holstein dairy cows during different lactation phases

So far, rumination has been used as a proxy for monitoring dairy cow health at farm level. However, investigating its genetic aspects as well as its correlation with other important productive traits may turn this management tool into a new informative selection criterion. However, scientific evidences on genetic correlation among rumination time (RT) and milk production and milk composition are still scarce. Therefore, the objective of this study was to estimate the heritability of RT across three lactation phases and its genetic correlation with milk production, milk composition and somatic cell count (SCC). Results of our study showed that heritability for RT was 0.34 and was constant across lactation. The mean genetic correlations between RT and milk production and composition traits were 0.07 (milk production), ?0.07 (protein yield), ?0.31 (fat yield), and ?0.32 (fat/protein ratio). The mean genetic correlation between RT and the SCC was 0.05.     

Simulation of future dissolved oxygen distribution in pond culture based on sliding window-temporal convolutional network and trend surface analysis

Dissolved oxygen (DO) is a key ecological factor to measure the quality of water in the aquaculture. As the pond water body is affected by the breeding environment, the spatial distribution of DO shows a certain law in the entire pond. Therefore, to simulate the distribution of DO in aquaculture waters and grasp the temporal and spatial variation of DO is the key to achieving precise regulation of DO. For this purpose, this paper proposed a method for simulating the temporal and spatial distribution of DO in pond culture based on a sliding window-temporal convolutional network together with trend surface analysis (SW-TCN-TSA). This paper first utilized SW to construct DO data sets with different prediction durations, and then used the improved TCN model to realize one-dimensional time series prediction for DO at single monitoring point. Based on the prediction results of DO, a TSA method was performed on the predicted values of DO at the extreme moments of all discrete monitoring points, so as to realize the simulation of the temporal and spatial distribution of DO in the pond. Experimental results show that the SW-TCN model has better prediction performance for one-dimensional time series prediction of DO. Compared with traditional deep networks, such as CNN, GRU, LSTM, CNN-GRU and CNN-LSTM, the values of evaluation indicators (MSE, MAE and RMSE) have been greatly improved. In the process of trend surface fitting, all fitting R² of DO at different water depths are higher than 0.9, indicating that the TSA can accurately reflect the temporal and spatial distribution of DO. This method can provide a basis for the prediction and early warning of DO in the three-dimensional space of the pond and has high practicability in aquaculture.     

The research in processing fMRI data using temporal-spatial model based on CCA

In the analysis of cognition of human brain,the fMRI is often used.Corelation is a common method in fMRI data detecting,but its ability should be improved.Based on the Canonical Correlation Analysis(CCA),the temporal correlation and spatial correlation are used together to detect the activated area in the fMRI data.By the application of the method in simulation data and fMRI data,it shows that this method is effective in the detecting.