Application of Bayesian regularized BP neural network model for analysis of aquatic ecological data-A case study of chlorophyll-a prediction in Nanzui water area of Dongting Lake

Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of the network were obtained. After the selection of input variables using stepwise/multiple linear regression method in SPSS i1.0 software, the BRBPNN model was established between chlorophyll-α and environmental parameters, biological parameters. The achieved optimal network structure was 3-11-1 with the correlation coefficients and the mean square errors for the training set and the test set as 0.999 and 0.000？8426, 0.981 and 0.0216 respectively. The sum of square weights between each input neuron and the hidden layer of optimal BRBPNN models of different structures indicated that the effect of individual input parameter on chlorophyll- α declined in the order of alga amount 〉 secchi disc depth（SD） 〉 electrical conductivity （EC）. Additionally, it also demonstrated that the contributions of these three factors were the maximal for the change of chlorophyll-α concentration, total phosphorus（TP） and total nitrogen（TN） were the minimal. All the results showed that BRBPNN model was capable of automated regularization parameter selection and thus it may ensure the excellent generation ability and robustness. Thus, this study laid the foundation for the application of BRBPNN model in the analysis of aquatic ecological data（chlorophyll-α prediction） and the explanation about the effective eutrophication treatment measures for Nanzui water area in Dongting Lake.     

氯代芳香族化合物结构-电化学还原电位定量关系的贝叶斯规整化BP神经网络模型

将贝叶斯规整化误差反向传播神经网络(BRBPNN)应用于环境领域的 QSPR模型.采用ChemOffice2004内置的MOPAC 2000计算了6种量子化学参数(分子最高占据能EHOMO、分子最低占据能ELUMO、分子生成热HF、分子偶极矩DIP、分子的电子能量EE和分子的核核排斥能CCR)以及氯原子数(Cl)和分子量(MW),建立了87种氯代芳香族化合物结构与电化学还原电位定量关系的BRBPNN模型.最优网络模型结构为6-20-1,其电化学还原电位的拟合及预测能力明显优于逐步线性回归模型,其训练集和预测集的相关系数平方和均方根误差(MSE)分别达到0.999和0.000105,0.965和 0.00159.最优模型输入节点到隐含层权重平方和的分布规律揭示出各种描述符对还原电位的影响大小依次为: E_LUMO>E_HOMO>HF>CCR>EE>DIP.由散点图揭示出影响为正有EE;影响为负有E_LUMO,HF,DIP;影响无明显正负性的有E_LUMO,CCR.结果表明,贝叶斯规整化大大方便了网络规整化参数选择,保证了网络的优良概括能力和稳健性.本研究对氯代芳香族化合物采用电化学处理的适用性以及分析相应电化学降解机理提供了依据.     

基于空间尺度效应的西南地区植被NPP影响因子探测

植被净初级生产力(NPP)是评价陆地生态系统质量的重要参数,研究植被NPP时空演变特征及其驱动力对区域生态环境保护和可持续发展具有重大意义.基于MODIS NPP数据、气象数据、 DEM数据、人口密度数据、 GDP数据和土地利用类型数据,采用一元线性回归分析、 R/S分析和地理探测器模型,分析西南地区及其六大地貌单元植被NPP时空演变特征及未来变化趋势,探究植被NPP空间分异的影响因子.结果表明,2000～2020年西南地区植被NPP整体呈极显著上升趋势.地貌单元中,除青藏高原南部外,其余地貌单元植被NPP均表现为改善态势,其中四川盆地和云贵高原表现为极显著改善.西南地区的植被NPP变化斜率整体呈现“东高西低”的分布格局.西南地区及各地貌单元植被NPP呈上升趋势的区域面积均大于呈下降趋势的区域面积,但未来植被NPP变化趋势均以下降为主.地理探测器结果表明,除云贵高原植被NPP空间分异主要受气温影响外,海拔是西南地区及各地貌单元植被NPP空间分异的主导因子.交互探测结果表明,影响因子之间的交互作用均表现为双因子增强或非线性增强,其中,海拔∩温度对西南地区植被NPP空间分异的解释力最大.地...     

长江经济带二氧化碳净排放时空演变特征及脱钩效应

研究区域CO₂净排放,对“碳中和”战略的实现具有重要意义.以长江经济带为例,在揭示1999～2018年长江经济带CO₂净排放时空演变特征的基础上,分析长江经济带不同区域社会发展与CO₂净排放的脱钩效应,以期为差异化区域产业发展和碳减排路径提供支持.结果表明：(1)1999～2012年长江经济带CO₂排放量上升了2 244.23×10⁶ t,碳汇量在研究时间段增长了148.07×10⁶ t;(2)长江经济带呈现“变绿”趋势,2013～2018年中高碳汇量区域(NPP>800 g·m^-2,以C计)面积较1999～2012年上升了23.25%;(3)长江经济带下游经济社会发展与CO₂净排放脱钩效应较强,上、中和下游强脱钩城市占长江经济带强脱钩城市的比例分别为12%、34%和54%.     

中国碳排放及影响因素的市域尺度分析

评估区域碳排放及其与社会经济状况的关系对于制定碳减排措施至关重要.以中国339个地级及以上城市(不含新疆部分城市和港澳台地区)为研究对象,探究了非化石能源占比、土地开发度、常住人口城镇化率、第二产业占比、人均GDP和人均建设用地面积对人均CO₂排放量的影响.通过构建模拟人均CO₂排放量的贝叶斯信念网络,识别各因素对人均CO₂排放量的全局影响;采用多尺度地理加权回归模型,分析各因素对人均CO₂排放量的局部影响.结果表明：(1)2020年,中国地级及以上城市人均CO₂排放量呈现出由南向北递增,东部沿海向内陆递减的格局.(2)从全局来看,人均CO₂排放量对各因素的敏感性从高到低依次为：人均建设用地面积>人均GDP>常住人口城镇化率>土地开发度>第二产业占比>非化石能源占比.(3)从局部来看,各因素与人均CO₂排放量的空间关系方向与全局关系一致,关系强度上存在空间异质性.(4)清洁能源、脱碳技术、土地节约集约利用...     

Sex‐specific and dose‐response relationships of urinary cobalt and molybdenum levels with glucose levels and insulin resistance in U.S. adults

Growing studies have linked metal exposure to diabetes risk. However, these studies had inconsistent results. We used a multiple linear regression model to investigate the sex-specific and dose-response associations between urinary metals (cobalt (Co) and molybdenum (Mo)) and diabetes-related indicators (fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), homeostasis model assessment for insulin resistance (HOMA-IR), and insulin) in a cross-sectional study based on the United States National Health and Nutrition Examination Survey. The urinary metal concentrations of 1423 eligible individuals were stratified on the basis of the quartile distribution. Our results showed that the urinary Co level in males at the fourth quartile (Q4) was strongly correlated with increased FPG (β = 0.61, 95% CI: 0.17–1.04), HbA1c (β = 0.31, 95% CI: 0.09–0.54), insulin (β = 8.18, 95% CI: 2.84–13.52), and HOMA–IR (β = 3.42, 95% CI: 1.40–5.44) when compared with first quartile (Q1). High urinary Mo levels (Q4 vs. Q1) were associated with elevated FPG (β = 0.46, 95% CI: 0.17–0.75) and HbA1c (β = 0.27, 95% CI: 0.11–0.42) in the overall population. Positive linear dose-response associations were observed between urinary Co and insulin (P_nonlinear = 0.513) and HOMA–IR (P_nonlinear = 0.736) in males, as well as a positive linear dose-response relationship between urinary Mo and FPG (P_nonlinear = 0.826) and HbA1c (P_nonlinear = 0.376) in the overall population. Significant sex-specific and dose-response relationships were observed between urinary metals (Co and Mo) and diabetes-related indicators, and the potential mechanisms should be further investigated.     

Human appropriation of net primary production as determinant of avifauna diversity in Austria

The relationship between land-use induced changes in production ecology and avifauna diversity was analysed using a GIS land cover dataset on a 0.25 km × 0.25 km grid covering Austria's national territory. Considering only aboveground processes, the “human appropriation of net primary production” (HANPP = potential NPP − NPP_t), actual NPP (NPP_act), harvest (NPP_h) and NPP_t (= NPP_act − harvest) were recalculated based on existing datasets. Elevation as well as indicators of land cover heterogeneity and landscape heterogeneity were also considered. Correlation analyses were performed between these potential determinants of avifauna diversity and breeding bird species richness data as well as the percentage of endangered breeding birds included in the Austrian red list. Four spatial scales—0.25 km × 0.25 km, 1 km × 1 km, 4 km × 4 km and 16 × 16 km, were analysed. It was shown that breeding bird species richness was more strongly correlated with production ecological indicators and elevation than with heterogeneity indicators. A residual analysis in which the effect of elevation (a proxy for climate) on species richness and its potential determinants was removed confirmed the importance of the availability of trophic energy (NPP) for bird diversity patterns. The results support the species-energy hypothesis, thus confirming the notion that HANPP could be a useful pressure indicator for biodiversity loss.     

人类活动净氮输入时空变化特征及其影响因素——以香溪河流域为例

为了阐明人类活动对三峡库区第一大支流香溪河流域氮输入的影响程度,基于人类活动净氮输入（NANI）模型估算了2001~2015年间香溪河流域乡镇水平的人类活动净氮输入,分析了氮输入的主要来源及其动态变化.结果表明：时间尺度上,香溪河流域人类活动净氮输入（NANI）因氮素施用的变化而呈现先上升后下降最后上升的趋势,但2015年相对2001年的NANI下降了143kg N/（km²·a）;空间尺度上,香溪河流域NANI整体呈现北低南高的分布格局,其中NANI输入强度差异较大的区域主要有昭君镇、峡口镇和黄粮镇.从人类活动净氮输入的组成上来看,氮肥施用仍然是最主要的来源（40.06%）,其次为大气氮沉降（29.98%）和食品/饲料净氮输入（27.75%）,作物固氮仅占净氮输入总量的2.21%.香溪河流域的NANI与人口密度和耕地面积比例极显著相关（P<0.001）;而NANI与河流氮输出的相关性不显著,香溪河流域河流氮输出占NANI的比例仅为24.28%.因此,可以通过减少氮素施用降低流域尺度氮素净输入量,但该流域NANI与河流氮输出无直接的响应关系.     

草地退化对三江源区高寒草甸生态系统CO2通量的影响及其原因

为了揭示草地退化对三江源地区高寒草甸生态系统碳通量的影响,利用涡度相关技术,于2006年12月1日~2007年11月30日对三江源地区的退化高寒草甸生态系统的碳通量及生物和环境因子进行观测.结果发现:草地退化对高寒草甸生态系统的碳通量产生了深刻影响,与未退化的高寒草甸生态系统相比,退化高寒草甸生态系统全年总初级生产力(GPP)下降了36.6%,全年生态系统呼吸(Reco)下降了7.9%,全年净生态系统CO2交换(NEE)也由退化前的负值(碳吸收)转变为正值(碳排放),二者相差132.5gC/(m2·a),生态系统由原来的碳汇转变为目前的碳源.这些变化与高寒草甸退化后,生态系统植物地上生物量锐减、植物生长期缩短(NEE<0的天数)、植物多样性下降、土壤含水量降低等因素密切相关.     

植被净初级生产力对气候变化的响应研究——以黄土高原燕沟流域为例

Vegetation net primary productivity (NPP) is a sensitive indicator to characterize the response of terrestrial ecosystems to the climate change. Projections of the NPP changes of the Loess Plateau under future climate scenarios have great significances in revealing the interactions among terrestrial ecosystems and climatic systems, as well as instructing future vegetation construction of this region. Here, we carried out a case study on the Yangou watershed in the Loess Plateau. Using the vegetation-producing process model (VPP) established for such small watersheds, we simulated the NPP of the Yangou watershed under different scenarios of climate changes. The results showed that the NPP significantly increased with the precipitation increasing and evidently decreased with the temperature increasing where the climate change occurred in the whole year or in the summer half year. However, where the climate change occurred in the winter half year, the increased precipitation had little effect on the NPP, and the increased temperature significantly reduced the NPP. There were clear differences among the response sensitivities of different vegetation types with trees and shrubs were more sensitive to the changes in temperature and precipitation than crops and grasses. Currently, the most favourable climate change scenario to the NPP in the Yangou watershed was T0P15 under which the precipitation increased by 15% and the temperature did not changed, in the whole year; in the meantime, the most unfavourable climate change scenarios was T2P-15 under which the precipitation declined by 15% and the temperature increased by 2℃, in the whole year.