浅谈GAM与GM（1,1）模型

对ＧＡＭ水环境预测模型提出了四点不同看法，与有关作者商榷，指出ＧＭ（１，１）模型与ＧＡＭ模型二者并无优劣之差，精度亦相当。     

Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images

We have used Landsat-5 TM and Landsat-7 ETM+ images together with simultaneous ground-truth data at sample points in the Doñana marshes to predict water turbidity and depth from band reflectance using Generalized Additive Models. We have point samples for 12 different dates simultaneous with 7 Landsat-5 and 5 Landsat-7 overpasses. The best model for water turbidity in the marsh explained 38% of variance in ground-truth data and included as predictors band 3 (630–690 nm), band 5 (1550–1750 nm) and the ratio between bands 1 (450–520 nm) and 4 (760–900 nm). Water turbidity is easier to predict for water bodies like the Guadalquivir River and artificial ponds that are deep and not affected by bottom soil reflectance and aquatic vegetation. For the latter, a simple model using band 3 reflectance explains 78.6% of the variance. Water depth is easier to predict than turbidity. The best model for water depth in the marsh explains 78% of the variance and includes as predictors band 1, band 5, the ratio between band 2 (520–600 nm) and band 4, and bottom soil reflectance in band 4 in September, when the marsh is dry. The water turbidity and water depth models have been developed in order to reconstruct historical changes in Doñana wetlands during the last 30 years using the Landsat satellite images time series.     

Testing hypotheses on shape and distribution of ecological response curves

Niche theory with hypotheses on shape and distribution of ecological response curves is used in the studies of resource sharing of competing plant species. Predictions based on theory should be applicable when, e.g., effects of competing species on the ecological tolerances are assessed or species’ diversity along a resource gradient is evaluated. We studied the ecological response curves of competing plant species along a resource gradient in boreal forests. The study was based on nation-wide soil and vegetation data collected from 455 sample plots on boreal forests in Finland. Species response curves along a soil fertility gradient (in terms of C/N ratio) were estimated using generalized additive models. Distribution of species optima and the relationship of niche width and skewness to the location of the optimum were analyzed with new bootstrap tests. The developed tests can account for the effects of truncation observed in the response curves of several species and for the uneven distribution of observations on the gradient.The estimated response curves of the major field layer species of boreal forests were not evenly distributed along soil C/N gradient. The density of optima peaked with relatively high nitrogen availability. Species with optima at low nitrogen availability had relatively broad realized niches. Niche width was negatively correlated with the density of optima. Species optima were packed and niches were narrow at high resource levels. This result suggests that a greater number of more specialized species can occur and interspecific competition decreases niche widths at high resource levels. Species were packed in the gradient where the C/N ratio was lower than 25, i.e., in conditions where nitrification can take place. This indicates that the majority of the vascular plants of boreal forests are favoured by the availability of NO₃⁻. Those few species thriving at high C/N ratios have broader realized niches.     

A heuristic approach to predicting water beetle diversity in temporary and fluctuating waters

An understanding of the causal mechanisms and processes that shape macroinvertebrate communities at a local scale has important implications for the management and conservation of freshwater biodiversity. Here we compare the performance of linear and non-linear statistics to explore diversity-environment relationships using data from 76 temporary and fluctuating ponds in two regions of southern England. We focus on aquatic beetle assemblages, which have been shown to be excellent surrogates of wider freshwater macroinvertebrate diversity. Ponds in the region contained a rich coleopteran fauna, totaling 68 species, which provided an excellent model system with which to compare the performance of two non-linear procedures (artificial neural networks—ANNs and generalised additive models—GAMs) and one more traditional linear approach (Multiple linear regression—MLR) to modelling diversity-environment relationships. Of all approaches employed, the best fit was obtained using an ANN model with only four input variables (conductivity, turbidity, magnesium concentration and depth). This model accounted for 82% of the observed variability in Shannon diversity index across ponds. In contrast, the best GAM and MLR models only explained 50% and 14% of this variation, respectively. Contribution profile analysis of conductivity, turbidity, magnesium concentration and depth, obtained from the best fit ANN through a hierarchical cluster analysis, allowed the identification of direct and proxy effects in relation to the environmental variables measured in this study. In each case, distinct clusters of ponds were identified in contribution profile analysis, suggesting that ponds across the two regions fall into a number of discrete groups, whose beetle faunas respond in subtly yet significantly different ways to key environmental variables. Aquatic coleopteran diversity in ponds in the two regions appears to be driven at a local scale by changes in relatively few physicochemical gradients, which are related to diversity in a clearly non-linear manner.     

扬州市河网大型底栖动物群落结构及其生境特征研究

构建适用于城市大型底栖动物的生境适宜性模型,探究大型底栖动物与生境因子间的响应关系,对城市河流生态系统恢复具有重要指示意义.本文以长江下游北岸扬州市城市河网为研究对象,基于丰水期（2018年8月）和枯水期（2019年1月）的大型底栖动物调查数据,利用典范对应分析与相关性分析筛选城市河网生态健康的关键生境因子,采用GAM模型拟合关键生境因子与大型底栖动物优势种的关系,构建城市大型底栖动物生境特征研究模型.结果表明,本次调查共获得大型底栖动物48个物种,隶属3门6纲13目20科40属,其中,水生昆虫为优势类群,霍甫水丝蚓（Limnodrilus hoffmeisteri）为研究区域优势种.影响优势种霍甫水丝蚓的主要生境因子为溶解氧（DO）、COD_Mn、NH₃-N、电导率（Cond）,当霍甫水丝蚓生境适宜度为1.0时,水体中NH₃-N含量界限值为0.554 mg·L^-1,COD_Mn界限值为2.23 mg·L^-1,DO界限值为7.87 mg·L^-1,Cond界限值为272.5 S·m^-1.GAM模型能识别城市水环境关键问题,有效解释城市大型底栖动物与生境因子间的响应关系,可为城市河网水生态修复提供参考依据.     

Indoor air particles in research vessel from Shanghai to Antarctic: Characteristics, influencing factors, and potential controlling pathway

Despite millions of seafarers and passengers staying on ships each year, few studies have been conducted on the indoor air quality inside ship hulls. In this study, we investigated the levels and size distribution of indoor particulate matter during two cruises of the research vessel “Xuelong” from Shanghai to Antarctica. The results showed that the particle size less than 2.5 µm (PM_2.5), and particle size less than 10 µm (PM₁₀) concentrations in different rooms of the ship widely varied. We observed high particulate matter (PM) levels in some of the rooms. The mass concentration distribution was dominated by 1–4 µm particles, which may have been caused by the hygroscopic growth of fine particles. The dominant factors influencing PM concentrations were indoor temperature, relative humidity, and human activity. We quantified contributions of these factors to the levels of indoor particles using a generalized additive model. In clean rooms, the levels of indoor particles were controlled by temperature and relative humidity, whereas in polluted rooms, the levels of indoor particles were mainly influenced by temperature and human activity, which implied that controlling temperature and human activity would efficiently reduce the levels of indoor particles.     

Long-term declining in carbon monoxide(CO) at a rural site of Beijing during 2006–2018 implies the improved combustion efficiency and effective emission control

Carbon monoxide(CO) is primarily the result of incomplete combustion, which has important impacts on the atmospheric chemical cycle and climate. Improved quantitative characterization of long-term CO trends is important for both atmospheric modeling and the design and implementation of policies to efficiently control multiple pollutants. Due to the limitations of high time-resolution and high-quality long-term observational data, studies on long-term trends in the CO concentration in China are q...     

The influences of climate and hydrology on population dynamics of waterbirds in the lower Murrumbidgee River floodplains in Southeast Australia: Implications for environmental water management

Restoration of waterbird diversity and abundance is a key objective of river system management in Australia. Therefore, understanding the effects of climatic and hydrological variables on waterbird population dynamics is fundamental for successful river restoration programs. We investigated the population dynamics of waterbirds (total abundance) and seven functional waterbird groups in the floodplains of lower Murrumbidgee River. We found a general declining abundance trend from 1983 to 2007, except for the deep water foragers. We modelled the relative contribution of the climatic and hydrological factors to waterbird population decrease using the generalized additive model (GAM) framework after identifying the negative binomial distribution. Most of the seven functional groups were positively related to both annual rainfall and water usage, defined as the total water volume intercepted by the river reach, and the models indicated that rainfall was slightly more important. Temperature also played a role in waterbird abundance: the maximum summer temperature negatively influenced the abundance of dabbling ducks, shoreline foragers and fish eaters, while the minimum winter temperature positively affected the abundance of dabbling ducks and shoreline foragers. Overall, our results support the practice of providing environmental water for sustaining waterbird populations. However, environmental water provision is likely to be most effective when timed to coincide with antecedent rainfall.     

崇明北湖叶绿素a浓度与环境因子的GAM回归分析

以崇明北湖为例,采用广义加性模型(GAM)对该湖的叶绿素a浓度与相关环境因子进行分析.结果表明,叶绿素a浓度与总氮、总磷和水温之间存在较好的非线性关系(P<0.05),叶绿素a浓度与总磷之间的关系先为单调递增,当总磷浓度达到0.12mg/L时,变为单调递减;不同总氮浓度区间上,总氮对叶绿素a浓度的影响不同,氮浓度为0.6~1.8mg/L时,对叶绿素a浓度的影响不大;水温在24~26℃时,叶绿素a浓度最高.叶绿素a浓度与氮磷比之间也存在较好的非线性关系(P<0.1),氮限制时,叶绿素浓度与氮磷比呈反比;磷限制时,叶绿素a浓度随着氮磷比单调递减.