AQUATOX: Modeling environmental fate and ecological effects in aquatic ecosystems

AQUATOX combines aquatic ecosystem, chemical fate, and ecotoxicological constructs to obtain a truly integrative fate and effects model. It is a general, mechanistic ecological risk assessment model intended to be used to evaluate past, present, and future direct and indirect effects from various stressors including nutrients, organic wastes, sediments, toxic organic chemicals, flow, and temperature in aquatic ecosystems. The model has a very flexible structure and provides multiple analytical tools useful for evaluating ecological effects, including uncertainty analysis, nominal range sensitivity analysis, comparison of perturbed and control simulations, and graphing and tabulation of predicted concentrations, rates, and photosynthetic limitations. It can represent a full aquatic food web, including multiple genera and guilds of periphyton, phytoplankton, submersed aquatic vegetation, invertebrates, and fish and associated organic toxicants. It can model up to 20 organic chemicals simultaneously. (It does not model metals.) Modeled processes for organic toxicants include chemodynamics of neutral and ionized organic chemicals, bioaccumulation as a function of sorption and bioenergetics, biotransformation to daughter products, and sublethal and lethal toxicity. It has an extensive library of default biotic, chemical, and toxicological parameters and incorporates the ICE regression equations for estimating toxicity in numerous organisms. The model has been implemented for streams, small rivers, ponds, lakes, reservoirs, and estuaries. It is an integral part of the BASINS system with linkage to the watershed models HSPF and SWAT.     

Estimating soil carbon turnover using radiocarbon data: A case-study for European Russia

Turnover rates of soil carbon for 20 soil types typical for a 3.7 million km² area of European Russia were estimated based on ¹⁴C data. The rates are corrected for bomb radiocarbon which strongly affects the topsoil ¹⁴C balance. The approach is applied for carbon stored in the organic and mineral layers of the upper 1 m of the soil profile. The turnover rates of carbon in the upper 20 cm are relatively high for forest soils (0.16–0.78% year⁻¹), intermediate for tundra soils (0.25% year⁻¹), and low for grassland soils (0.02–0.08% year⁻¹) with the exception of southern Chernozems (0.32% year⁻¹). In the soil layer of 20–100 cm depth, the turnover rates were much lower for all soil types (0.01–0.06% year⁻¹) except for peat bog soils of the southern taiga (0.14% year⁻¹). Combined with a map of soil type distribution and a dataset of several hundred soil carbon profiles, the method provides annual fluxes for the slowest components of soil carbon assuming that the latter is in equilibrium with climate and vegetation cover. The estimated carbon flux from the soil is highest for forest soils (12–147 gC/(m² year)), intermediate for tundra soils (33 gC/(m² year)), and lowest for grassland soils (1–26 gC/(m² year)). The approach does not distinguish active and recalcitrant carbon fractions and this explains the low turnover rates in the top layer. Since changes in soil types will follow changes in climate and land cover, we suggest that pedogenesis is an important factor influencing the future dynamics of soil carbon fluxes. Up to now, both the effect of soil type changes and the clear evidence from ¹⁴C measurements that most soil organic carbon has a millennial time scale, are basically neglected in the global carbon cycle models used for projections of atmospheric CO₂ in 21st century and beyond.     

人因失误的机理及其可靠性研究

随着科技的发展 ,在系统安全中 ,机器设备可靠性越来越高 ,由于人本身的复杂性 ,人因失误变得愈来愈严重。本文基于人行为的原理 ,对人因失误的机理、影响人失误的因素、人行为的模型和失误模型及其可靠性的量化进行了分析 ,建立了计算人可靠性的威布尔分布模型 ,并对其参数进行了讨论 ,可用此来评价人的可靠性。     

A comparison of simulated and observed ozone mixing ratios for the summer of 1998 in Western Europe

This study describes and evaluates the newly developed European scale Eulerian chemistry transport model CHIMERE-continental. The model is designed for seasonal simulations and real time forecasts without the use of super-computers. For the purpose of model evaluation simulated ozone mixing ratios for the period between 1 May 1998 and 30 September 1998 are compared to observational data from 115 European surface sites. In order to facilitate the interpretation of future forecasts a statistic is established to estimate the reliability of a simulated pollution level. Besides this, the comparison is done by means of time series, scatter plots, a spectral analysis and the calculation of RMS-errors and biases of the model results corresponding to each observation site. It turns out that the mean RMS-error of the simulated daily maximum ozone mixing ratio for the sites considered a priori as well suited for a model comparison is about 10 ppb. For the same period but a reduced number of sites observed concentrations of NO₂ and ethene are compared to simulated values. Difficulties encountered with the representativeness of observations when trying to evaluate a mesoscale air pollution model are discussed.     

Numerical simulation of a fine-grained denitrification layer for removing septic system nitrate from shallow groundwater

One of the most common methods to dispose of domestic wastewater involves the release of septic effluent from drains located in the unsaturated zone. Nitrogen from such systems is currently of concern because of nitrate contamination of drinking water supplies and eutrophication of coastal waters. It has been proposed that adding labile carbon sources to septic distribution fields could enhance heterotrophic denitrification and thus reduce nitrate concentrations in shallow groundwater. In this study, a numerical model which solves for variably saturated flow and reactive transport of multiple species is employed to investigate the performance of a drain field design that incorporates a fine-grained denitrification layer. The hydrogeological scenario simulated is an unconfined sand aquifer. The model results suggest that the denitrification layer, supplemented with labile organic carbon, may be an effective means to eliminate nitrogen loading to shallow groundwater. It is also shown that in noncalcareous aquifers, the denitrification reaction may provide sufficient buffering capacity to maintain near neutral pH conditions beneath and down gradient of the drain field. Leaching of excess dissolved organic carbon (DOC) from the denitrification layer is problematic, and causes an anaerobic plume to develop in simulations where the water table is less than 5-6 m below ground surface; this anaerobic plume may lead to other down gradient changes in groundwater quality. A drain field and denitrification layer of smaller dimensions is shown to be just as effective for reducing nitrate, but has the benefit of reducing the excess DOC leached from the layer. This configuration will minimize the impact of wastewater disposal in areas where the water table is as shallow as 3.5 m.     

Spatial impacts of climate factors on regional agricultural and forestry biomass resources in north-eastern province of China

The dynamics of agricultural and forestry biomass are highly sensitive to climate change, particularly in high latitude regions. Heilongjiang Province was selected as research area in North-east China. We explored the trend of regional climate warming and distribution feature of biomass resources, and then analyzed on the spatial relationship between climate factors and biomass resources. Net primary productivity (NPP) is one of the key indicators of vegetation productivity, and was simulated as base data to calculate the distribution of agricultural and forestry biomass. The results show that temperatures rose by up to 0.37°C/10a from 1961 to 2013. Spatially, the variation of agricultural biomass per unit area changed from -1.93 to 5.85 t·km^–2·a^–1 during 2000–2013. More than 85% of farmland areas showed a positive relationship between agricultural biomass and precipitation. The results suggest that precipitation exerts an overwhelming climate influence on agricultural biomass. The mean density of forestry biomass varied from 10 to 30 t·km^–2. Temperature had a significant negative effect on forestry biomass in Lesser Khingan and northern Changbai Mountain, because increased temperature leads to decreased Rubisco activity and increased respiration in these areas. Precipitation had a significant positive relationship with forestry biomass in south-western Changbai Mountain, because this area had a warmer climate and stress from insufficient precipitation may induce xylem cavitation. Understanding the effects of climate factors on regional biomass resources is of great significance in improving environmental management and promoting sustainable development of further biomass resource use.

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基于DEM的山地丘陵区土地利用/覆被研究——以青海湖流域为例

研究地形对土地利用空间分布格局的影响,对探讨不同地貌部位自然因素和人文因素在土地利用变化过程中的作用具有重要意义。论文以青海湖流域为例,对比各土地利用类型的投影面积与地表真实面积的差异,并从地形(高程、坡度、坡向)角度分析了流域内土地利用的空间分布格局。结果表明:流域投影面积与地表真实面积相差754.79 km²。耕地、居民地、水域、沙地主要分布在3 500 m以下,且坡度小于2°的平地上,耕地和居民地多分布在南坡和西南坡上;林地主要分布在3 500~4 000 m且坡度多在6~25°的缓地和斜坡上,各坡向分布较均匀;草地主要分布在4 500 m以下且坡度小于25°的坡地上;沼泽多分布在3 500~4 500 m且坡度小于25°的河源地区,多分布在北坡和东北坡上;其它用地主要分布在4 000~4 500 m的坡度较大的斜坡或陡坡上。随高度、坡度增加,土地利用程度综合指数呈下降趋势;土地利用综合指数在坡向上呈现:平地＞阳坡＞阴坡。说明地形在很大程度上影响着青海湖流域的土地利用分布,且这种影响比较符合当地的自然规律和社会经济规律。     

植物根系固土护坡机理的研究进展及展望

在综合国内外相关研究成果的基础上,详细介绍了近几年来植物根系固土护坡机理的研究进展。文章分别从水文效应和力学效应2个方面对根系固土护坡机理进行了介绍,并着重从根增强的理论模型、根-土相互作用等方面论述了植物根系固土护坡的力学效应。首先介绍了根增强理论的先驱模型Wu和Waldron模型,文章从多方面论证了Wu和Waldron模型假定穿过剪切面的所有根在受力时同时破坏高估了根的增强作用,详细介绍了国外学者对Wu和Waldron模型改进后,最新提出的2种考虑根系逐渐破坏的力学模型——纤维束增强模型FBM和根束增强模型RBM。FBM模型用动态纤维束来模拟根系的渐进破坏,假设荷载被分配给束中的每个根,当载荷增加到其值超过了某单根的抗拉强度时,该根被拉断,而被该根分担的载荷被重新分配到剩下的完好的根中,直到所有的根都拉断。该模型使用应力控制的加载过程,不能得到完整的力-位移关系曲线;且该模型中没有考虑根的直径分布、几何性质、力学性质等的影响。为了克服上述缺陷Schwarz在FBM模型的基础上,又提出了RBM模型。RBM模型是一个以位移控制加载过程的纤维束模型,该模型考虑整个根束的拔出力是位移的函数,并被表示成单根的拔出力之和。文章最后详细论述了根系的拔出机理,探讨了植物根系固土护坡研究的发展方向。     

Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?

Species distribution models (SDMs) based on statistical relationships between occurrence data and underlying environmental conditions are increasingly used to predict spatial patterns of biological invasions and prioritize locations for early detection and control of invasion outbreaks. However, invasive species distribution models (iSDMs) face special challenges because (i) they typically violate SDM's assumption that the organism is in equilibrium with its environment, and (ii) species absence data are often unavailable or believed to be too difficult to interpret. This often leads researchers to generate pseudo-absences for model training or utilize presence-only methods, and to confuse the distinction between predictions of potential vs. actual distribution. We examined the hypothesis that true-absence data, when accompanied by dispersal constraints, improve prediction accuracy and ecological understanding of iSDMs that aim to predict the actual distribution of biological invasions. We evaluated the impact of presence-only, true-absence and pseudo-absence data on model accuracy using an extensive dataset on the distribution of the invasive forest pathogen Phytophthora ramorum in California. Two traditional presence/absence models (generalized linear model and classification trees) and two alternative presence-only models (ecological niche factor analysis and maximum entropy) were developed based on 890 field plots of pathogen occurrence and several climatic, topographic, host vegetation and dispersal variables. The effects of all three possible types of occurrence data on model performance were evaluated with receiver operating characteristic (ROC) and omission/commission error rates. Results show that prediction of actual distribution was less accurate when we ignored true-absences and dispersal constraints. Presence-only models and models without dispersal information tended to over-predict the actual range of invasions. Models based on pseudo-absence data exhibited similar accuracies as presence-only models but produced spatially less feasible predictions. We suggest that true-absence data are a critical ingredient not only for accurate calibration but also for ecologically meaningful assessment of iSDMs that focus on predictions of actual distributions.