A model for ecological assessment to pesticide pollution management

Applying the relational analysis in the Grey System Theory and Method, the comprehensive evaluation on five pesticide pollution controlling techniques in the vegetable production has been made and a comprehensive profit (cp–comprehensive cost (cc) evaluation system (composed of 15 comprehensive cost indices and 14 comprehensive profit indices) has been established, with a index optimization matrix of comprehensive cost indices and comprehensive profit indices obtained and a ratio model of comprehensive cost to comprehensive profit (R_cc/cp) built. Results show that the R_cc/cp value of vegetables intercropping soybeans in insect-proof thin film greenhouses is the smallest and the R_cc/cp value of vegetables intercropping taros in insect-proof net greenhouses, pheromones in insect-proof thin film greenhouses, pheromones in insect-proof thin film greenhouses and ground planting (only using chemical pesticide for insect-proof without covering materials and synthetic sex pheromone) other four techniques are 0.6268, 0.6393, 0.6407, 0.9809 respectively. In accordance with the R_cc/cp value, vegetables intercropping soybeans in insect-proof thin film greenhouses can be the most optimized pesticide pollution controlling technique in the vegetable growing.     

Performance of a Bayesian state-space model of semelparous species for stock-recruitment data subject to measurement error

Measurement errors in spawner abundance create problems for fish stock assessment scientists. To deal with measurement error, we develop a Bayesian state-space model for stock-recruitment data that contain measurement error in spawner abundance, process error in recruitment, and time series bias. Through extensive simulations across numerous scenarios, we compare the statistical performance of the Bayesian state-space model with that of standard regression for a traditional stock-recruitment model that only considers process error. Performance varies depending on the information content in data, as determined by stock productivity, types of harvest situations, and amount of measurement error. Overall, in terms of estimating optimal spawner abundance S_MSY, the Ricker density-dependence parameter β, and optimal harvest rate h_MSY, the Bayesian state-space model works best for informative data from low and variable harvest rate situations for high-productivity salmon stocks. The traditional stock-recruitment model (TSR) may be used for estimating α and h_MSY for low-productivity stocks from variable and high harvest rate situations. However, TSR can severely overestimate S_MSY when spawner abundance is measured with large error in low and variable harvest rate situations. We also found that there is substantial merit in using h_MSY (or benchmarks derived from it) instead of S_MSY as a management target.     

Assessing spatial uncertainty of the Portuguese fire risk through direct sequential simulation

Forest fires have a significant economic, social, and environmental impact in Portugal. For that its fire risk was assessed through Bayes Formalism, where the main component of the risk of fire was assessed by the conditional probability of fire I(u,t) given a class of the daily severity rating (DSR) for a specific period of time—P[I(u,t)|R(u,t)]. The evaluation of this a posterior probability, P[I(u,t)|R(u,t)], was based on the update of marginal local probability of fire in each chosen region u (Durão, 2006).DSR values were used to calculate fire's risk, taking into account historical data, I(s,t), in a given region s, and also to define DSR's local thresholds in order to have P [I(u,t)|R(u,t)] ≥ 0.65.In this paper we characterize these posterior probabilities using direct sequential simulation models (DSS models) to obtain the spatial distribution of these probabilities over the entire Portugal, in order to assess the risk of fire and associated spatial uncertainty. Local probability density functions (pdfs) and spatial uncertainty are evaluated by a set of equiprobable simulated images of these posterior probabilities.Results are presented and discussed for the Portuguese fire seasons of the 2-year period, 2003-2004. The conditional probabilities reproduced reasonably well what was officially published for the studied fire seasons. We expect that a better understanding of both spatial and temporal patterns of fire in Portugal together with uncertainty measures constitutes an important tool for managers, helping to improve the effectiveness of fire prevention, detection and fire fighting resources allocation in critical social and environmental areas.     

双酚A类似物雌激素干扰效应的定量结构-活性关系模型

由于双酚A(BPA)具有内分泌干扰等毒性效应,有些国家已经开始限制其在部分工业品生产中使用。一些双酚A类似物因用于替代BPA而被大量使用。因其与双酚A具有相似的分子结构,双酚A类似物是否也具有内分泌干扰等毒性效应受到越来越多的关注。采用逐步多元线性回归(MLR)方法,构建了可预测双酚A类似物雌激素效应的定量结构-活性关系模型。模型的决定系数R~2=0.899,去一法交叉验证系数Q_(LOO)~2=0.868,Bootstrapping验证系数Q_(BOOT)~2=0.755,均方根误差RMSE=0.339,表明模型具有较好的拟合优度、稳健性;验证集决定系数Q_(EXT)~2=0.921,外部验证系数Q_(EXT)~2=0.810,均方根误差RMSE=0.638,表明模型具有较好的预测能力。采用欧几里德距离方法和Wil iams图表征了模型应用域,依据分子描述符对模型进行了机理解释,并用所建模型,填补了22种其他双酚A类似物缺失的雌激素干扰效应数据。     

Different proxies for the reactivity of aquatic sediments towards oxygen: A model assessment

Information on benthic carbon mineralization rates is often derived from the analysis of oxygen microprofiles in sediments. To enable a direct comparison of different sediment environments, it is often desirable to characterize sediments by a single proxy that expresses their “reactivity” towards oxygen. For this, there are three commonly used proxies: the oxygen penetration depth (OPD), the oxygen flux at the sediment-water interface (DOU), and the maximum volumetric oxygen consumption rate (R_max). The OPD can be directly determined from the oxygen depth profile, while the DOU is usually obtained by a linear fit to the oxygen gradient either in diffusive boundary layer. The oxygen consumption rate R_max requires the fitting of a reactive-transport model to the data profile. This article shows that the OPD alone is a suboptimal proxy, because it shows a strong dependence on the half-saturation constant K_s, and secondly, because it is sensitive to the particular re-oxidation conditions right above the oxic-anoxic interface. Similarly, the volumetric oxygen consumption rate R_max is rather strongly dependent on the kinetic model formulation employed. To show this we fitted three different (Bouldin, Blackman and Monod) kinetics to the same oxygen data profiles. When fitting these models, the R_max values obtained differed by 20% for exactly the same oxygen profile. Accordingly, if one reports R_max values, it is crucial to specify the kinetic model alongside. Overall, DOU emerges as sediment reactivity proxy which is the least model dependent.     

Voltage-clamp measurements on single split lamellae of posterior gills of the shore crab Carcinus maenas

Single split lamella preparations of posterior gills of low-salt adapted shore crabs Carcinus maenas (collected from the Kiel Bay, Baltic Sea in 1991) were mounted in a micro Ussing-chamber. With NaCl salines on both sides we found an outside positive potential difference (PD) of 6.6±1.3 mV, a short-circuit current (I_sc) of-240±65 Acm^-2 and a resistance (R_t) of 25±3 cm² (n=8). Substitution of Cl^- (gluconate) on both sides of the preparation resulted in a decrease of I_sc by more than 90% at constant R_t. I_sc disappeared and R_t increased after substitution of Na⁺ (choline). When ouabain (2 mmol l^-1) was applied to the internal NaCl-saline, I_sc decreased and R_t remained unchanged. Internal addition of 0.1 mmol l^-1 acetazolamide left I_sc and R_t unaffected. Application of amiloride to the external NaCl saline resulted in a increase of both inward negative I_sc and R_t. The dose dependence of the diuretic showed a maximal effect between 50 and 200 mol l^-1 with a half-maximal blocker concentration (K_AMI) of ca. 10 mol l^-1. The results show that the split lamella preparation of posterior gills of C. maenas is a low resistance epithelium which is able to effect a massive, electrogenic and coupled absorption of Na⁺ and Cl^-.     

Pollution indices as useful tools for the comprehensive evaluation of the degree of soil contamination–A review

The paper provides a complex, critical assessment of heavy metal soil pollution using different indices. Pollution indices are widely considered a useful tool for the comprehensive evaluation of the degree of contamination. Moreover, they can have a great importance in the assessment of soil quality and the prediction of future ecosystem sustainability, especially in the case of farmlands. Eighteen indices previously described by several authors (I_geo, PI, EF, C_f, PI_sum, PI_Nemerow, PLI, PI_ave, PI_Vector, PIN, MEC, CSI, MERMQ, C_deg, RI, mCd and ExF) as well as the newly published Biogeochemical Index (BGI) were compared. The content, as determined by other authors, of the most widely investigated heavy metals (Cd, Pb and Zn) in farmland, forest and urban soils was used as a database for the calculation of all of the presented indices, and this shows, based on statistical methods, the similarities and differences between them. The indices were initially divided into two groups: individual and complex. In order to achieve a more precise classification, our study attempted to further split indices based on their purpose and method of calculation. The strengths and weaknesses of each index were assessed; in addition, a comprehensive method for pollution index choice is presented, in order to best interpret pollution in different soils (farmland, forest and urban). This critical review also contains an evaluation of various geochemical backgrounds (GBs) used in heavy metal soil pollution assessments. The authors propose a comprehensive method in order to assess soil quality, based on the application of local and reference GB.     

The effect of estimated PAR uncertainties on the physiological processes of biosphere models

Photosynthetically active radiation (PAR) energy reaching on the vegetated surface is a key determinant of plant physiological processes. Most of biosphere or crop models use the ratio of PAR to incoming solar radiation (R_s), PAR/R_s, to convert R_s into PAR in order to reduce weather data-input requirements. Several existing models simply specify a constant ratio, PAR/R_s = 0.5. However, some field experiments have reported that the ratio PAR/R_s may not be constant. Previous empirical equations of PAR/R_s were derived based on the data of monthly or daily timescales collected from only a few measurement sites, hence they may not be appropriate to be used in current global biosphere models usually with hourly simulation time steps. Here, we represent the exponential correlation between PAR/R_s and sky clearness index (0-1) using hourly data from 54 Ameriflux measurement sites. It is found that PAR/R_s increases up to 0.6 in cloudy conditions when the clearness index (CI) is below ∼0.2, whereas it is nearly constant at ∼0.42 when CI is above 0.2. When the identified empirical equation is used in the model simulation, it results in −4 to 2% difference in the stomatal conductance compared to that using the constant ratio PAR/R_s = 0.5.     

Sensitivity of modelled gross primary productivity to topographic effects on surface radiation: A case study in the Cotter River Catchment, Australia

Gross primary productivity (GPP) is a critical response variable for many environmental problems, including terrestrial carbon accounting and the calculation of catchment water balances. Various approaches for modelling GPP have been developed and applied at continental and landscapes scales, but little attention has been given to the sensitivity of GPP to the spatial scale of its driving variables. A key driving variable is surface radiation (R_s) which is influenced by both meso-scale factors (latitude, time of year, cloudiness) and the topographic variables of slope, aspect and horizon shading. We compared the sensitivity of modelled GPP to two different sources of surface radiation (R_s): (1) the ANUCLIM method which only captures the meso-scaled factors; and (2) the SRAD method which incorporates the topographic effects GPP was calculated using the radiation use efficiency (RUE) model (Roderick et al., 2001) to discern general patterns of vegetation productivity at a sub-catchment (i.e. sub-water shed) scale. The radiation use efficiency approach uses the normalized difference vegetation index (NDVI) derived from satellite data (MODIS TERRA), along with estimates of solar radiation at the top of the atmosphere (R_o) and canopy (R_s). In this approach, R_o and R_s capture the influence of diffuse irradiance in canopy photosynthesis and vegetation productivity respectively. This research showed that R_s calculated using the SRAD program provides important discrimination of GPP regimes at a sub-catchment scale, as the result of minimum and maximum daily radiation varying between shaded and exposed surfaces. However, mean daily radiation at a whole-of-catchment scale did not differ between the two sources as the differences in the minimum and maximum daily values tend to cancel each other out. Applications of GPP models therefore need to consider whether topographic factors are important and select the appropriate source of R_s values. GPP models should also reflect understanding of radiation use efficiency. However, further research is required especially with respect to the influence of water stress on plant response.     

PIXGRO: A model for simulating the ecosystem CO2 exchange and growth of spring barley

A model, PIXGRO, developed by coupling a canopy flux sub-model (PROXEL_NEE; PROcess-based piXEL Net Ecosystem CO₂ Exchange) to a vegetation structure submodel (CGRO), for simulating both net ecosystem CO₂ exchange (NEE) and growth of spring barley is described. PIXGRO is an extension of the stand-level CO₂ and H₂O-flux model PROXEL_NEE, that simulates the NEE on a process basis, but goes further to include the dry matter production, partitioning, and crop development for spring barley. Dry matter partitioned to the leaf was converted to leaf area index (LAI) using relationships for the specific leaf area (SLA). The canopy flux component, PROXEL_NEE was calibrated using information from the literature on C3 plants and was tested using CO₂ flux data from an eddy-covariance (EC) method in Finland with long-term observations. The growth component (CGRO) was calibrated using data from the literature on spring barley as well as data from the Finland site. It was then validated against field data from two sites in Germany and partly via the use of MODIS remotely sensed LAI from the Finland site.Both the diurnal and the seasonal patterns of gross CO₂ uptake were very well simulated (R² = 0.92). A slight seasonal bias may be attributed to leaf ageing. Crop growth was also well simulated; simulated dry matter agreed with field observed data from Germany (R² = 0.90). For LAI, the agreement between the simulated and observed was good (R² = 0.80), giving an indication that functions describing the conversion of fixed CO₂ to dry matter and the subsequent partitioning leaf dry matter and LAI simulation were robust and provided reliable estimates.The MODIS LAI at a resolution of 1000 m agreed poorly (R² = 0.45) with the PIXGRO simulated LAI and the observed LAI at the Finland site in 2001. We attributed this to the coarse resolution of the image and/or the small size of the barley field (about 17 ha or 0.25 km²) at the Finland site. By deriving a regression relation between the observed LAI and NDVI from a higher resolution MODIS (500 m resolution), the MODIS-recalculated LAI agreed better with the PIXGRO-simulated LAI (R² = 0.86).PIXGRO provides a prototype model bridging the disciplines of plant physiology, crop modeling and remote sensing, for use in a spatial context in evaluating carbon balances and plant growth at stand level, landscape, regional, and with some care, continental scales. Since almost 50% of the European land surface is covered by crops, such a model is needed for the dynamic estimation of LAI and NEE of croplands.     

Estimation of algal growth parameters from vertical primary production profiles

Phytoplankton maximum growth rate and the saturation light intensity, I_s, can be estimated from vertical profiles of primary production by non-linear least-squares estimation. Solution through the normal equations leads to formulae which are relatively simple and easy to implement. The computation of confidence contours is demonstrated, and the results are contrasted to the confidence limits on the parameters individually. These can be quite misleading due to model non-linearity and correlation between parameter estimation.The procedure has been applied to primary production data from Lake Balaton, a shallow lake in Hungary. The growth rate-temperature relation is analysed by separating the parameters into two groups characteristic for “warm” and “cold” water phytoplankton, respectively. A bell-shaped curve is found for “cold” water communities, with an optimum at about 7–9°C, whereas the “warm” water phytoplankton exhibits a strong exponential dependency in the temperature range of interest (up to 25°C). I_s also appears to be related to temperature except for the “cold” water group, where I_s is essentially constant. However, a roughly linear relation with considerably less scatter is obtained when I_s is plotted directly versus day-averaged solar radiation. This apparent fast adaptation is attributed to the extremely short turnover time in Lake Balaton. Maximum growth rates of 10–20 d^?1 have been found for temperatures between 20 and 25°C. These results and a critical appraisal of available literature suggest that the common notion of maximum growth rates being in the order of 1–3 d^?1 needs revision, at least for lakes with relatively high summer temperatures.     

Equivalence of the realized input and output oriented indirect effects metrics in Ecological Network Analysis

A new understanding of the consequences of how ecosystem elements are interconnected is emerging from the development and application of Ecological Network Analysis. The relative importance of indirect effects is central to this understanding, and the ratio of indirect flow to direct flow (I/D) is one indicator of their importance. Two methods have been proposed for calculating this indicator. The unit approach shows what would happen if each system member had a unit input or output, while the realized technique determines the ratio using the observed system inputs or outputs. When using the unit method, the input oriented and output oriented ratios can be different, potentially leading to conflicting results. However, we show that the input and output oriented I/D ratios are identical using the realized method when the system is at steady state. This work is a step in the maturation of Ecological Network Analysis that will let it be more readily testable empirically and ultimately more useful for environmental assessment and management.     

卤代有机化合物生物富集因子的定量结构-活性关系模型

依据经济合作与发展组织(OECD)关于定量结构-活性关系(QSAR)模型构建和使用导则,通过多元线性回归(MLR)方法建立了一个包含9个描述符的卤代有机化合物鱼类生物富集因子(BCF)的QSAR模型。QSAR模型的调整决定系数R²_adj = 0.877,去一法交叉验证系数Q²_LOO= 0.873,外部验证系数Q²_EXT= 0.757,表明模型具有较好的拟合优度、稳健性和预测能力。采用欧几里德距离方法表征了模型应用域,并对模型进行了机理解释。所构建的模型,可以用于预测应用域内卤代化合物的BCF。     

外源化合物在鱼体内生物半减期的QSAR模型

生物半减期(t1/2)是评价外源化合物在鱼体内蓄积效应的重要参数。实验测定t_(1/2)的速度慢、成本高,难以满足化学品生态风险评价的需求,需要发展替代实验的模型预测方法。本研究搜集了653种化合物t1/2实测值,采用多元线性回归(MLR)和支持向量机(SVM) 2种方法,建立了鱼体logt1/2的定量构效关系(QSAR)预测模型。MLR模型的校正决定系数(R(adj)~2)为0.751,均方根误差(RMSE_(train))为0.587,去一法交叉验证系数(Q_(LOO)~2)为0.735,外部验证系数(Q_(ext)~2)为0.682,这表明模型具有较好的拟合度、稳健性和预测能力。SVM模型具有更好的拟合和预测能力(R_(adj)~2=0.839,RMSE_(train)=0.457,Q_(ext)~2=0.708)。采用Williams法对模型的应用域进行表征。所建模型可用于预测多环芳烃、多氯联苯、多溴联苯醚、有机磷农药、药物等典型化合物,以及其他烷烃、环烷烃、烯烃、醇、醚、酸、酯、酮、含卤素化合物、芳香族化合物、含硫、氮、磷化合物的在鱼体内的logt1/2值。     

Analysis of modified model for commercial fishing with possible extinctive fishery resources

The solution properties of a modified commercial fishing model are investigated in this paper. The results imply that fishery resources may be extincted under certain conditions. The positive invariant region, that is, the nonextinctive region, R(δ₁, δ₂), is a monotonic increasing correspondence of exiting rate of the fishing industry, δ₂, and is a monotonic decreasing correspondence of the entering rate of the fishing industry, δ₁. Also, there exist limit cycles for the system of equations of the modified model under certain conditions.     

Pesticide prediction in ground water in North Carolina domestic wells using artificial neural networks

This paper illustrates the application of artificial neural networks (ANN) for prediction of pesticide occurrence in rural domestic wells from the available limited information. Among the three ANN models (a feed-forward back propagation [BP], a radial basis function [RBF] and an adaptive neural network-based fuzzy inference system [ANFIS]) employed for this investigation, the BP neural network was found to be superior to RBF and ANFIS type networks for the detection of pesticide occurrences in wells. For improved model prediction efficiency, optimization of network structure (e.g., number of hidden layers and number of nodes in each hidden layer) and spread (the width of the radial basis function) are important for BP and RBF type of network, respectively. A four layer BP network with a 3:2 neurons ratio of the first hidden layer to the second hidden layer produced better prediction performance efficiencies in terms of the pesticide detection efficiency (E_f), the root mean square error (RMSE), and the correlation coefficient (R) and the overall E_f of the BP neural network was found greater than 85%. Sensitivity analysis was performed to measure the relative importance of one input parameter over the other in pesticide occurrence in wells. It was shown in terms of the prediction efficiencies (E_f, RMSE, and R) of a four-layer BP neural network that the time of sample collection (TSC; month of the year), the depths of wells, and pesticide travel times (PTT) were more important parameters in the prediction of the pesticide occurrences in rural domestic wells. This means that the wells having shallow ground water table are more vulnerable to pesticide occurrence.     

Modeling effects of toxin exposure in fish on long-term population size, with an application to selenium toxicity in bluegill (Lepomis macrochirus)

A primary goal in ecotoxicology is the prediction of population-level effects of contaminant exposure based on individual-level response. Assessment of toxicity at the population level has predominately focused on the population growth rate (PGR), but the PGR may not be a relevant toxicological endpoint for populations at equilibrium. Equilibrium population size may be a more meaningful endpoint than the PGR because a population with smaller equilibrium size is more susceptible to the negative effects of environmental variability. We address the individual-to-population extrapolation problem with modeling utilizing classical mathematical theory. We developed and analyzed a general model applicable to many freshwater fish species, that includes density-dependent juvenile survival and additional juvenile mortality due to toxicity exposure, and we quantified effect on equilibrium population size as a means of assessing toxicity. Individual-level effects are typically greater than population-level effects until the individual effect is large, due to compensatory density-dependent relationships. These effects are sensitive to the recruitment potential of a population, in particular the low-density first-year survival rate S_b. Assuming high S_b could result in underestimating effects of population-level toxicity. The equilibrium size depends directly on S_b, the reproductive potential, the toxin concentration at which mean mortality is 50% (LC₅₀), and the rate at which individual mortality increases with increasing toxin concentration. More experimental data are needed to decrease the uncertainty in estimating these parameters. We then used existing data for selenium toxicity in bluegill sunfish to parameterize a simulation version of the model as an example to assess the effects of environmental stochasticity on toxicity response. Effects of environmental variability resulted in simulated extinctions at much lower toxin concentrations than predicted deterministically.     

Eco-physiological properties of Pontogammarus maeoticus (Amphipoda) in a salinity gradient

Quantitative indices of feeding, food assimilation, energy metabolism and growth in Pontogammarus maeoticus (Sow.) from the Azov Sea (12‰S) were studied from the salinity levels. Juveniles and males of different age groups were sampled for experiments. The relationships between feeding rate (C) and energy metabolism (R) on an energy equivalent of w, body weight were approximated by the power equations \(C = C_1 w^{b_c }\) and R=R₁w^b. To express weight growth, the Bertalanffy equation and its solution were used: $$\frac{{dw}}{{dt}} = Nw^q - kw; w(t) = W_\infty (1 - e^{ - mkt} )^{1/m}$$ Under control salinity (12‰S) the following parameters were obtained: C₁=0.73J^(1-b)d^-1; b_c=0.62; R₁=0.53J^(1-b)d^-1; b=0.67. The application of a new method suggested by the author for determining the growth parameters, N, k, m=1-q, revealed their dependence on age. For juveniles N=0.0965, k=0.0046, while for adults the respective values were 0.1540 and 0.0181. The value m=0.39 was the same for both age classes. The individuals were gradually transferred to conditions of changed salinity (～0; 4 and 18‰S). The observations lasted up to two months. Through the entire range of salinity (～0–18‰S), food assimilation alone was constant. In relation to dry matter, food assimilation was 65 and 80% in terms of caloric value. The other indices under study remain at the control level only under desalinization to 4‰S. When P. maeoticus was maintained in fresh water, the juveniles showed enhanced levels of nutrition, energy metabolism and increment, while in mature individuals the respective parameters decreased compared with the control. As a result, the parameters C₁ and R₁ in the functions C(w) and R(w) were ～2 times higher and b_c and b～2 times lower than in 12‰S. An increase in salinity to 18‰S resulted in a decline of all the processes concerned: C₁=0.61, R₁=0.36, b_c and b remained at the control level, while growth rate became 20% lower. A full compensation type acclimation for P. maeoticus is possible with the salinity range (12–4‰S) where the individual can maintain ionic balance.     

Development and application of “U.S.E.D.”: A hydroclimate lake stratification model

Two model types are currently in use to model the thermal stratification cycle in lakes and reservoirs: the eddy diffusion and the mixed layer (or integral energy) approaches. Here the former is analysed and developments are proposed to remove the empiricisms previously implicit in these models. These discussions permit the reformulation of K_H0 independently of current shear, together with an expression for R_i. The deduced formulae are in good agreement with observations. The newly formulated model (the University of Salford eddy diffusion model, U.S.E.D.) is subsequently used in simulations of lakes and reservoirs at different latitudes which are found to be in good agreement with observations without requiring inter-site calibration.