Stochastic gravity models for modeling lake invasions

Freshwater aquatic systems in North America are being invaded by many different species, ranging from fish, mollusks, cladocerans to various bacteria and viruses. These invasions have serious ecological and economic impacts. Human activities such as recreational boating are an important pathway for dispersal. Gravity models are used to quantify the dispersal effect of human activity. Gravity models currently used in ecology are deterministic. This paper proposes the use of stochastic gravity models in ecology, which provides new capabilities both in model building and in potential model applications. These models allow us to use standard statistical inference tools such as maximum likelihood estimation and model selection based on information criteria. To facilitate prediction, we use only those covariates that are easily available from common data sources and can be forecasted in future. This is important for forecasting the spread of invasive species in geographical and temporal domain. The proposed model is portable, that is it can be used for estimating relative boater traffic and hence relative propagule pressure for the lakes not covered by current boater surveys. This makes our results broadly applicable to various invasion prediction and management models.     

湖泊沉积物对磷酸盐的负吸附研究

分别在高、低两种磷酸盐质量浓度下，研究了6个湖泊沉积物对磷酸盐的负吸附。结果表明，(1)污染严重的湖泊沉积物不仅在上覆水体水质好转时，可能向上覆水体释放磷，即使上覆水体水质没有好转，在一定条件也可能释放；而较为清洁的湖泊沉积物，在上覆水体水质下降时，可能从上覆水体中吸附磷。在水质好转情况下，也可能向上覆水体中释放磷。(2)湖泊沉积物吸附磷酸盐过程中存在负吸附，吸附研究中使用较高质量浓度磷溶液是负吸附现象被掩盖的原因；在吸附研究中不仅要重视负吸附，而且初始磷酸盐质量浓度不能太高。(3)沉积物对磷酸盐的吸附／解吸平衡质量浓度与其有机质、CEC、总氮、总磷以及各形态磷含量均有显著的正相关关系，相比而言。与总磷以及各形态磷含量的相关性最高。污染较为严重的沉积物对磷酸盐的吸附／解吸平衡质量浓度也较高。     

Use of individual-based models for population parameters estimation

A method for parameters estimation of stage-specific mortality and fecundity rate functions in poikilotherm organisms, and in particular for arthropod structured population, is proposed. The application of this method requires three types of information: stage-frequency data of a sampled population, development rate function and time evolution of forcing variables affecting the rate functions. By means of an individual-based model (a microscopic model) the number of eggs produced by the adults is generated starting from the number of individuals collected at each sampling time. Using a compartmental model (a macroscopic model) a stage-structured population dynamics is described and compared with observations. Non-linear regression methods based on least square principle are used to estimate the optimal parameters of the mortality and fecundity rate functions combining microscopic and macroscopic models. As a case study, the parameter estimation of the temperature-dependent mortality function of olives fruit fly Bactrocera oleae is presented.     

Functional clustering of varved lake sediment to reconstruct past seasonal climate

Annually laminated (varved) lake sediments constitutes excellent environmental archives, and have the potential to play an important role for understanding past seasonal climate with their inherent annual time resolution and within-year seasonal patterns. We propose to use functional data analysis methods to extract the relevant information with respect to climate reconstruction from the rich but complex information in the varves, including the shapes of the seasonal patterns, the varying varve thickness, and the non-linear sediment accumulation rates. In particular we analyze varved sediment from lake Kassjön in northern Sweden, covering the past 6400 years. The properties of each varve reflect to a large extent weather conditions and internal biological processes in the lake the year that the varve was deposited. Functional clustering is used to group the seasonal patterns into different types, that can be associated with different weather conditions. The seasonal patterns were described by penalized splines and clustered by the k-means algorithm, after alignment. The observed (within-year) variability in the data was used to determine the degree of smoothing for the penalized spline approximations. The resulting clusters and their time dynamics show great potential for seasonal climate interpretation, in particular for winter climate changes.     

湖泊沉积物孔隙水溶解性有机质组成与光谱特性

应用紫外-可见光谱和荧光光谱分析乌梁素海沉积物孔隙水中溶解性有机质(DOM)的组成和来源信息,揭示不同来源污染物对孔隙水DOM结构及地球化学行为的影响.研究结果表明,类蛋白物质含量相对较高的区域,其污染相对较重;沉积物孔隙水DOM的生物指数BIX值都大于0.6,预示沉积物孔隙水中DOM微生物来源贡献较大;在类蛋白荧光物质较高的区域,DOM的腐殖化程度相对较低,其结构相对简单,稳定性较弱;腐殖化指数HIX254分析结果也表明,受污程度较高的区域,DOM的腐殖化程度较低;紫外吸收光谱的斜率能够反映沉积物孔隙水中类腐殖酸的变化,而光谱斜率S350—400比S275—295更能够反应沉积物孔隙水中类腐殖酸的变化,随着S350—400升高,DOM中类蛋白物质的含量呈下降趋势,类腐殖酸含量逐渐增加.     

Historical record of anthropogenic polycyclic aromatic hydrocarbons in a lake sediment from the southern Tibetan Plateau

High-altitude lake sediments can be used as natural archives to reconstruct the history of pollutants. In this work, the temporal distribution of polycyclic aromatic hydrocarbons (PAHs) was determined in a sediment core collected from the southern Tibetan Plateau (TP), which was dated by using the ²¹⁰Pb dating method and validated with the ¹³⁷Cs fallout peak. The concentrations of the anthropogenic PAHs (Σ₈PAH) in the sediment core ranged from 0.83 to 12 ng/g dw, and the fluxes of the Σ₈PAH were in the range of 2.1–27 g/cm²/year. The temporal variations in the concentration and input flux of anthropogenic PAHs were low with little variability before the 1950s, and then gradually increased from the 1950s to the 1980s, and an accelerated increase was observed after the early 1980s. The content of total organic carbon played an insignificant role in affecting the time trends of PAHs in the sediment core. Diagnostic concentration fractions of PAH components indicate PAHs in the lake sediment of the southern TP which are mainly from biomass burning and/or from long-range atmospheric transport.     

Vertical profiles of organochlorine pesticides in sediment core from Nile river and Manzala lake,Egypt

Residue levels of organochlorine pesticides (DDTs, HCHs, HCB and chlordane compounds) were determined in core samples collected from Nile River near by Cairo and Manzala Lake, Egypt in 1994. Regional difference and vertical profiles were discussed in view of historical reconstruction of environmental pollution by these chemicals. On the basis of estimated sedimentation rate (0.5 to 0.7 cm/year) in Manzala Lake, it seems that discharge of DDTs and CHLs into Egyptian environment increased rapidly from early 1960's and the maximum discharge was recorded in 1980's. However, concentration of HCHs increased continuously up to the present in spite of decreasing of DDTs and CHLs after 1980's. It was revealed that vertical profiles of organochlorine pesticides in sediment core from Manzala Lake are useful to estimate a temporal trend of pesticide use in Egypt.     

A new algorithm for estimating the parameters of the spatial generalized linear mixed models

Non-Gaussian spatial responses are usually modeled using a spatial generalized linear mixed model with location specific latent variables. The likelihood function of this model cannot usually be given in a closed form, thus the maximum likelihood approach is very challenging. So far, several numerical algorithms to solve the problem of calculating maximum likelihood estimates of this model have been presented. In this paper to estimate the parameters an approximate method is considered and a new algorithm is introduced that is much faster than existing algorithms but just as accurate. This is called the Approximate Expectation Maximization Gradient algorithm. The performance of the proposed algorithm and is illustrated with a simulation study and on a real data set.     

乌梁素海沉积物重金属生物活性及环境污染评估

为阐明乌梁素海沉积物重金属生物活性及理化性质对重金属形态变化的影响,对湖泊重金属污染修复治理方面提供科学依据,2011年1月在乌梁素海9个站点采集表层沉积物样品,采用改进BCR逐级提取法分析Cu、Zn、Pb、Cr、Cd、Hg、As等7种重金属元素的形态,利用活性系数与迁移系数对重金属生物活性进行研究;结合沉积物理化性质,系统探讨影响重金属化学形态与生物活性的因素;应用次生相与原生相比值法,从重金属形态学角度对沉积物重金属状况进行评估.结果表明,(1)沉积物中重金属活性系数的大小顺序为 Cd>Hg>Zn>Cu>Pb >As>Cr;重金属的迁移系数为 Cd>Hg>Zn>Cu>As>Pb>Cr.(2)沉积物物理化学性质和重金属总量对各种化学形态重金属含量影响程度明显不同.重金属总量对残渣态影响较大;pH对酸可提取态、有机物和硫化物结合态影响较大;有机质与酸可提取态、有机物和硫化物结合态有较大相关性;盐度与酸可提取态、有机物和硫化物结合态有一定的相关性.总氮、总磷与有机物和硫化物结合态有一定的相关性.(3)从重金属形态角度评价,7种重金属除Cd外,污染程度并不大,全湖KRSP的平均值大小顺序为Cd(1.66)>Cu(0.84)>Hg(0.72)>Zn(0.42)>Cr(0.15)>Pb(0.14)>As(0.06).结合总量、生物可利用性与形态学评价,乌梁素海重金属 Cd 是生物活性最强、污染最严重的金属,Hg污染次之,应该对Cd与Hg给予特别关注.     

Multi-metric evaluation of the models WARM,CropSyst, and WOFOST for rice

WARM (Water Accounting Rice Model) simulates paddy rice (Oryza sativa L.), based on temperature-driven development and radiation-driven crop growth. It also simulates: biomass partitioning, floodwater effect on temperature, spikelet sterility, floodwater and chemicals management, and soil hydrology. Biomass estimates from WARM were evaluated and compared with the ones from two generic crop models (CropSyst, WOFOST). The test-area was the Po Valley (Italy). Data collected at six sites from 1989 to 2004 from rice crops grown under flooded and non-limiting conditions were split into a calibration (to estimate some model parameters) and a validation set. For model evaluation, a fuzzy-logic based multiple-metrics indicator (MQI) was used: 0 (best) ≤ MQI ≤ 1 (worst). WARM estimates compared well with the actual data (mean MQI = 0.037 against 0.167 and 0.173 with CropSyst and WOFOST, respectively). On an average, the three models performed similarly for individual validation metrics such as modelling efficiency (EF > 0.90) and correlation coefficient (R > 0.98). WARM performed best in a weighed measure of the Akaike Information Criterion: (worst) 0<wk<1$0<w_k<1$ (best), considering estimation accuracy and number of parameters required to achieve it (mean wk=0.983$w_k=0.983$ against 0.007 and ∼0.000 with CropSyst and WOFOST, respectively). WARM results were sensitive to 30% of the model parameters (ratio being lower with both CropSyst, <10%, and WOFOST, <20%), but appeared the easiest model to use because of the lowest number of crop parameters required (10 against 15 and 34 with CropSyst and WOFOST, respectively). This study provides a concrete example of the possibilities offered using a range of assessment metrics to evaluate model estimates, predictive capabilities, and complexity.     

Prediction of high-density polyethylene pyrolysis using kinetic parameters based on thermogravimetric and artificial neural networks

● Reducting the sampling frequency can enhance the modelling process. ● The pyrolysis of HDPE was investigated at three different heating rates. ● The average E_a and k₀ were calculated by Friedman, KAS, FWO, and CR methods. ● ANN was employed to predict the HDPE weight loss with the optimal MSE and R². Pyrolysis is considered an attractive option and a promising way to dispose waste plastics. The thermogravimetric experiments of high-density polyethylene (HDPE) were conducted from 105 °C to 900 °C at different heating rates (10 °C/min, 20 °C/min, and 30 °C/min) to investigate their thermal pyrolysis behavior. We investigated four methods including three model-free methods and one model-fitting method to estimate dynamic parameters. Additionally, an artificial neural network model was developed by providing the heating rates and temperatures to predict the weight loss (wt.%) of HDPE, and optimized via assessing mean squared error and determination coefficient on the test set. The optimal MSE (2.6297 × 10⁻²) and R² value (R² > 0.999) were obtained. Activation energy and pre-exponential factor obtained from four different models achieves the acceptable value between experimental and predicted results. The relative error of the model increased from 2.4 % to 6.8 % when the sampling frequency changed from 50 s to 60 s, but showed no significant difference when the sampling frequency was below 50 s. This result provides a promising approach to simplify the further modelling work and to reduce the required data storage space. This study revealed the possibility of simulating the HDPE pyrolysis process via machine learning with no significant accuracy loss of the kinetic parameters. It is hoped that this work could potentially benefit to the development of pyrolysis process modelling of HDPE and the other plastics.     

An empirical evaluation of the insurance hypothesis in diversity-stability models

An important stabilizing mechanism in most diversity stability models is the insurance hypothesis, which involves correlation/covariance relationships among species. These models require that species do not fluctuate synchronously over time: that is, the correlation between pairs of species does not equal 1.0. However, the strength of this stabilizing mechanism increases as correlations decline away from 1.0, especially as they become more negative and also as the summed covariance across all species pairs becomes more negative. We evaluated the importance of the insurance hypothesis as a stabilizing mechanism by examining a variety of terrestrial assemblages using long-term data from the Global Population Dynamics Database, the Breeding Bird Survey, and a long-term site in southeastern Arizona, USA. We identified co-occurring assemblages of species and calculated the Spearman rank correlations of all pairs of species and the summed covariance of the entire assemblage. We found that, in most assemblages, positive correlations were two to three times more common than negative and that the magnitude of the positive correlations tended to be stronger than the negative correlations. For all but three assemblages, the summed covariance was positive. Data from larger spatial scales tended to exhibit more positive correlations, but even at the smallest spatial scales, positive correlations outnumbered negative. We suggest that species often covary positively because coexisting species respond similarly to fluctuations in their resource base driven by climatic fluctuations. As such, our review suggests that the insurance hypothesis may not be a strong mechanism stabilizing fluctuations in natural terrestrial communities.     

Comparison between linear and non-linear forms of pseudo-first-order and pseudo-second-order adsorption kinetic models for the removal of methylene blue by activated carbon

The best-fit equations of linear and non-linear forms of the two widely used kinetic models, namely pseudo-first-order and pseudo-second-order equations, were compared in this study. The experimental kinetics of methylene blue adsorption on activated carbon was used for this research. Both the correlation coefficient (R ²) and the normalized standard deviation Δq(%) were employed as error analysis methods to determine the best-fitting equations. The results show that the non-linear forms of pseudo-first-order and pseudo-second-order models were more suitable than the linear forms for fitting the experimental data. The experimental kinetics may have been distorted by linearization of the linear kinetic equations, and thus, the non-linear forms of kinetic equations should be primarily used to obtain the adsorption parameters. In addition, the Δq(%) method for error analysis may be better to determine the best-fitting model in this case.     

Occurrence and distribution of organochlorine residues and metals in sediment,water and fish in the catchment area of lake baiyangdian,china

The occurrence and distribution of metals (Al, Cd, Cr, Cu, Pb, Zn), organochlorine residues (HCH, DDT and metabolites, PCBs) and EOC1 (extractable organic bound chlorine) were monitored in 1993 and 1996 in sediment, water and fish in the catchment area of Lake Baiyangdian, China. The levels of the metals, especially Cd and Zn, were significantly higher in the sediment than those in non‐polluted areas. PCBs and chlorinated pesticides constituted only a minor part (< 8.4%) of the extractable organic bound chlorine, indicating the presence of additional, unknown, organochlorine residues. Among the pesticides, DDT was widely distributed and high levels occurred in fish despite a ban of its production and use in 1983. The low quotient of pp‐DDT/pp‐DDE in sediment and fish indicated that the input of DDT to the catchment area was not of recent origin.     

Laboratory investigations on wave attenuation characteristics of Rhizophora Mucronata poir using physical models with bottom friction

Environmental Fluid Mechanics - Species specific hydrodynamic characterization is essential for assessing the suitability of various types of mangroves in coastal protection as the dissipation of...     

Optimal control of lake pH for mercury bioaccumulation control

Mercury is recognized internationally as an important pollutant since mercury and its compounds are persistent, bioaccumulative and toxic, and pose human and ecosystem risks. A critical aspect of mercury cycling is its bioaccumulation, mainly as methylmercury, along the aquatic food web resulting in high risk of human exposure through contaminated fish consumption. Since lake acidity (pH) and mercury methylation are correlated, control of lake pH through lake liming is a possible option to mitigate mercury bioaccumulation. This work proposes to use optimal control theory to derive time-dependent lake liming strategies for a tighter control of lake pH. Since the behavior of the freshwater ecosystems such as lakes is often associated with considerable uncertainties, a robust and realistic analysis should incorporate such uncertainties. This work models the time-dependent uncertain variations in the basic lake pH value and derives the liming profiles in the presence of such seasonal pH fluctuations. Established techniques from real options theory are employed for modeling the uncertainty as a stochastic process, and stochastic optimal control is used for deriving liming profiles. The approach is critically evaluated through applications to various case study lakes. Considering the substantial costs associated with liming operations, the work formulates a multi-objective problem highlighting the tradeoff between accurate pH control and liming cost. The results of the control problem solution are also compared with heuristics based liming. The results, while highlighting the success of using time-dependent liming, put forth certain interesting aspects that might be helpful to a decision maker. The analysis is expected to make liming operation more reliable, thereby presenting one more tool to manage the harmful effects of mercury pollution.     

Population level risk assessment: practical considerations for evaluation of population models from a risk assessor's perspective

Population models are increasingly being considered as a tool for pesticide risk assessment in order to evaluate how potential effects act on the population level and population recovery. While the importance and difficulties of such models have been discussed by various authors during the past decade, mainly with a focus on how to describe or develop such models, several biological and methodological aspects have never been addressed so far, which are relevant for the application of models in risk assessment. These include a critical review of our knowledge of a species, the use of field data by taking methodological constraints into account, how to include uncertainty in model validation or how to measure effects. Although these aspects will be critical for the acceptance of population models by authorities, most of them apply not only to population models, but also to standard risk assessment. In the present article, we give practical recommendations for addressing these questions in population level risk assessments.     

The evaluation strip: A new and robust method for plotting predicted responses from species distribution models

Increasing use is being made in conservation management of statistical models that couple extensive collections of species and environmental data to make predictions of the geographic distributions of species. While the relationships fitted between a species and its environment are relatively transparent for many of these modeling techniques, others are more ‘black box’ in character, only producing geographic predictions and providing minimal or untraditional summaries of the fitted relationships on which these predictions are based. This in turn prevents robust evaluation of the ecological sensibility of such models, a necessary process if model predictions are to be treated with confidence. Here we propose a new but simple method for visualizing modeled responses that can be implemented with any modeling method, and demonstrate its application using five common methods applied to the prediction of an Australian tree species. This is achieved by insetting an “evaluation strip” into the spatial data layers, which, after predictions have been made, can be clipped out and used for creating plots of the modelled responses. We present findings of the application strip for algorithms GLMs, GAMs, CLIM, DOMAIN and MARS. Evaluation strips can be constructed to investigate either uni-variate responses, or the simultaneous variation in predicted values in relation to two variables. The latter option is particularly useful for evaluating responses in models that allow the fitting of complex interaction terms.     

Estimating parameters of hidden Markov models based on marked individuals: use of robust design data

Development and use of multistate mark-recapture models, which provide estimates of parameters of Markov processes in the face of imperfect detection, have become common over the last 20 years. Recently, estimating parameters of hidden Markov models, where the state of an individual can be uncertain even when it is detected, has received attention. Previous work has shown that ignoring state uncertainty biases estimates of survival and state transition probabilities, thereby reducing the power to detect effects. Efforts to adjust for state uncertainty have included special cases and a general framework for a single sample per period of interest. We provide a flexible framework for adjusting for state uncertainty in multistate models, while utilizing multiple sampling occasions per period of interest to increase precision and remove parameter redundancy. These models also produce direct estimates of state structure for each primary period, even for the case where there is just one sampling occasion. We apply our model to expected-value data, and to data from a study of Florida manatees, to provide examples of the improvement in precision due to secondary capture occasions. We have also implemented these models in program MARK. This general framework could also be used by practitioners to consider constrained models of particular interest, or to model the relationship between within-primary-period parameters (e.g., state structure) and between-primary-period parameters (e.g., state transition probabilities).     

Distribution of polychlorinated dibenzo-p-dioxins,polychlorinated dibenzofurans,dioxin-like polychlorinated biphenyl and polycyclic aromatic hydrocarbons in the sediment of Temsah lake,Suez Canal,Egypt

Lake Temsah is one of the main wetlands in the Suez Canal region, and the main source for fish for the area. The lake is the end-point of several wastewater effluents. In the present study, residues of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs), dioxin-like polychlorinated biphenyl (PCB) and polycyclic aromatic hydrocarbons (PAH) were monitored in the sediment of the lake. Samples were collected from six different sampling stations around the lake using a box-corer sampler, then kept frozen. Samples were extracted and cleaned up before residue determination was conducted using an HRGC/HRMS. An HP 6890 plus gas chromatograph was coupled to a Micromass Autospec Ultima mass spectrometer operating in EI mode at 35 eV and with a resolution of 10.000 (5% valley). PCDDs and PCDFs were detected in all sediment samples collected from various sampling stations. Results showed some progressive increase in PCDDs concentrations relevant to increase in chlorination. In the PCDD group of congeners, 1, 2, 3, 4, 6, 7, 8, 9 octa-CDD had the highest detected concentrations in all samples, while 2, 3, 7, 8 tetra-CDD showed the lowest concentrations. The World Health Organization toxicity equivalents ranged from 0.387 to 11.20 ng kg^?1 d.w. For PCDD homologues, hexa-CDD was the most dominant homologue in all sediment samples analysed. Regarding dioxin-like PCBs, results showed that IUPAC No. 118 congener, 2, 3, 4, 4, 5, pentachlorobiphenyl was the most concentrated of all detected congeners, with concentrations ranging between 0.039 and 43.201 µg kg^?1. For polycyclic aromatic hydrocarbons, benzo(b+k+j)fluoranthene had the highest concentrations in almost all sampling stations. However, fluorene was the smallest detected concentration in almost all stations. This result would indicate that PAH contamination of the lake seems to be coming from one main source in all sampling stations. The present work is the first record of PCCDs, PCCFs, and dioxin-like PCBs in the Temsah lake. The concentrations of the contaminants monitored in this study, especially those of PAHs, are rather alarming. Efforts should be made to stop point sources that contaminate the lake.