窑河水体中DO与NH_3-N、COD_(Mn)相关性

本文应用两年来窑河水体的监测数据对DO与NH3-N、CODMn进行一元线回归 ,得到两个回归方程 :NH3-N= -0.89DO +9.25 ,CODMn= -1.08DO +13.30并经相关系数和回归系数显著性检验 ,表明在99.9%的置信水平下DO与NH3-N、CODMn 线性相关均极其显著。

Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982–2010

Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.

Influencing Factors of Seed Long-distance Dispersal on a Fragmented Forest Landscape on Changbai Mountains,China

Seed long-distance dispersal(LDD) events are typically rare, but are important in the population processes that determine large-scale forest changes and the persistence of species in fragmented landscapes. However, previous studies focused on species dispersed via animal-mediated LDD, and ignored those dispersed by wind. The aim of this study was to assess the effects of canopy openness, edge, seed source, and patch tree density on the LDD of seeds by wind in forest. We collected birch seeds, a typical wind-dispersed species, throughout a larch plantation. We then assessed the relationship between birch LDD and each factor that may influence LDD of seeds by wind including distance to edge, canopy openness size, distance to mature forest, and the tree density of the larch plantation. We used univariate linear regression analysis to assess the influence of those factors on birch LDD, and partial correlations to calculate the contribution of each factor to LDD. The results showed that both canopy openness and edge had significant influences on birch LDD. Specifically, a negative relationship was observed between distance to edge and birch LDD, whereas there was a positive correlation between canopy openness size and LDD. In contrast, the distance to the mature forest was not correlated with birch LDD. Our results suggest that patch tree density could potently affect the probability of LDD by wind vectors, which provides novel and revealing insights regarding the effect of fragmentation on wind dynamics. The data also provide compelling evidence for the previously undocumented effect of habitat fragmentation on wind-dispersed organisms. As such, these observations will facilitate reasonable conservation planning, which requires a detailed understanding of the mechanisms by which patch properties hamper the delivery of seeds of wind-dispersed plants to fragmented areas.

Application of Grey System GM (1,1) model and unary linear regression model in coal consumption of Jilin Province

The data on the coal production and consumption in Jilin Province for the last ten years were collected,and the Grey System GM( 1,1) model and unary linear regression model were applied to predict the coal consumption of Jilin Production in 2014 and 2015. Through calculation,the predictive value on the coal consumption of Jilin Province was attained,namely consumption of 2014 is 114. 84 × 106 t and of 2015 is 117. 98 ×106t,respectively. Analysis of error data indicated that the predicted accuracy of Grey System GM( 1,1) model on the coal consumption in Jilin Province improved 0. 21% in comparison to unary linear regression model.

Mapping methods for output-based objective speech quality assessment using data mining

Objective speech quality is difficult to be measured without the input reference speech.Mapping methods using data mining are investigated and designed to improve the output-based speech quality assessment algorithm.The degraded speech is firstly separated into three classes(unvoiced,voiced and silence),and then the consistency measurement between the degraded speech signal and the pre-trained reference model for each class is calculated and mapped to an objective speech quality score using data mining.Fuzzy Gaussian mixture model(GMM)is used to generate the artificial reference model trained on perceptual linear predictive(PLP)features.The mean opinion score(MOS)mapping methods including multivariate non-linear regression(MNLR),fuzzy neural network(FNN)and support vector regression(SVR)are designed and compared with the standard ITU-T P.563 method.Experimental results show that the assessment methods with data mining perform better than ITU-T P.563.Moreover,FNN and SVR are more efficient than MNLR,and FNN performs best with 14.50% increase in the correlation coefficient and 32.76% decrease in the root-mean-square MOS error.

Analysis of Factors Determining the Demand for Water： A Case Study of Sabie Administrative Post, Moamba District, Mozambique

Water is an important resource for human being. However, it has been increasingly becoming the limited resource. Therefore, the debate of water issues has been centered in mechanisms to implement sustainable water management. Hence, understanding the determinants of water demand might help design appropriate water management policies, however, they are not known in Mozambique. Due to the lack of knowledge about the determinants of water demand in Mozambique in general and in Sabi6 in particular, the present study was conducted to analyse the factors determining the water demand for irrigation and domestic use using a linear regression model and travel cost method, respectively. The results show that an increase in 1 h of irrigation time increases the quantity demanded of irrigation water by 362.04 m3 and an increase in one irrigation per week increases the quantity demanded of irrigation water by 1,065.61 m3. Additionally, the results show that an increase in 1% of time spent in water collection decreases the number of trips by 0.3% and an increase in 1% in the number of household members involved in water collection decreases the number of the water collection trips by 0.23%. Household having private taps have less number of trips collecting water compared to those collecting water from public taps and boreholes as well as rivers. Therefore, the water demand for irrigation is determined by time spent for irrigation per day and the number of irrigations per week, and water demand for domestic use is determined by time spent for water collection, number of household members involved in water collection, the volumes of the containers used to collect water, the number of containers used to collect water, the quantity of water consumed by the household as well as the main source of water （river, boreholes and public tap）.