Fine-resolution mapping of wildfire fuel types for Canada: Fuzzy logic modeling for an Alberta pilot area

The Canadian Forest Fire Danger Rating System (CFFDRS) is used daily across Canada for evaluating forest fire danger. Fuel-type information is one of the inputs required by the models used in the CFFDRS. In this project, three fuel-type maps with a 25 m resolution were produced for a pilot study area located in Alberta using land cover only; land cover and biomass; and, land cover, biomass and leaf area index data derived from satellite imagery. The relationships between inputs and fuel types were determined mainly by the opinions of forest fire scientists and incorporated into a computer program using fuzzy set methodology. Not all the CFFDRS fuel types could be distinguished using these inputs; three of the coniferous types had to be grouped into one common fuel type. Overall accuracy was between 74 and 83% based on ground-truth comparisons. The most accurate map resulted from land cover and biomass data. Detailed accuracy assessment indicated that the overall accuracy increased up to 86% if ambiguous fuel type identification was considered. No combination of inputs was able to define a fuel type with absolute certainty, which is a reflection of differing expert opinions and the small number of inputs used to produce the maps.     

AB工艺减少污泥重金属的效果

在AB工艺中,利用A段活性吸附去除重金属从而降低B段污泥中重金属含量,使其达到农用标准（GB4284-84酸性土壤控制标准）。利用小型污水处理实验场,模拟研究了AB工艺A段中重金属的去除情况,对AB运行控制参数进行优化探讨,以使A段能有效去除大部分重金属,并尽可能降低有毒有害污泥产量。结果表明：溶解氧质量浓度控制在0.5mg·L-1,污泥质量浓度调节为约500mg·L-1时,Cu2＋去除率可达87.6%,Zn2＋的去除率为78.7%,Ni2＋去除率为51%。当污泥质量浓度在1000～1500mg·L-1时,A段处理后污泥沉降性能好转,对重金属离子的去除有较好的效果,且不过多截留污水中的有机物。且B段剩余污泥中的Cu2＋、Zn2＋、Ni2＋含量都基本达到酸性土壤污泥农用控制标准。因此,适当控制AB工艺相关参数条件,利用A段活性污泥去除大部分重金属,降低B段产泥中重金属含量,达到农业控制标准是可行的,污泥经处理后进行土地资源化利用可成为我国污泥处置与利用的一种有效途径。     

平原河网地区滨岸带外来植物入侵现状及影响研究——以上海青浦区为例

河流滨岸带作为一种典型的开放系统,在受到外界干扰的条件下极易被外来植物所入侵并受到严重影响。以上海青浦区为例,通过对河流滨岸带生态系统入侵植物分布及现状调查,以及对两种入侵植物：白花三叶草（Trifolium repens）和加拿大一枝黄花（Solidago canadensis）群落的物种多样性及其土壤特性的实证研究,探讨外来植物入侵对河流滨岸带生态系统造成的影响。结果表明：目前该地区河流滨岸带外来入侵植物共有14科24种,其科、种数分别占到该生态系统所有植物的48．3％与26．1％。入侵植物白花三叶草与加拿大一枝黄花在春、秋两季均显著降低了河流滨岸带植物群落的物种多样性。此外,两种人侵植物也对当地河流滨岸及土壤特性造成了不同程度的影响,其中对土壤含水量、pH值的影响最为显著。该研究填补了平原河网地区河流滨岸带生态系统外来植物入侵研究的空白,有助于今后开展对该生态系统的评价、恢复及管理工作。     

基于人工神经网络法的绿色建筑评价

以实际建筑物为例,介绍了用层次分析法建立绿色建筑评价模型的过程,并分别用层次分析法和人工神经网络法对实际建筑物进行了评价。评价结果显示,人工神经网络法与层次分析法相对误差不到0.5%,表明人工神经网络法作为一种客观科学的评价方法,应用于绿色建筑的评价,能有效降低主观因素带来的影响,会使结果更具有客观性。     

基于水土流失的景观格局分析方法

景观格局和生态过程是景观生态学研究的重要内容,但是很多研究只重视景观格局的研究,而忽略了生态过程的研究。文章针对水土流失这一重要生态过程,提出了基于水土流失过程的景观坡度指数和景观空间负荷对比指数,并对黄土高原泾河流域15个子流域的景观格局进行了分析,认为泾河流北部各子流域主要以水土流失的＂源＂景观为主,景观坡度指数大,空间负荷指数小,水土流失风险大;流域南部各子流域上游以＂汇＂景观为主,坡度指数大,中下游以＂源＂景观为主,景观空间分布不均衡,存在一定的水土流失风险;流域东部局部子流域主要以水土流失的＂汇＂景观为主,＂源＂景观相对较小,＂源＂-＂汇＂景观空间分布均衡,水土流失风险小。     

Fuzzy experts on recreational vessels, a risk modelling approach for marine invasions

Understanding risks from the human-mediated spread of non-indigenous species (NIS) is a critical component of marine biosecurity management programmes. Recreational boating is well-recognised as a NIS pathway, especially at a regional scale. Assessment of risks from this pathway is therefore desirable for coastal environments where recreational boating occurs. However, formal or quantitative risk assessment for the recreational vessel pathway is often hampered by lack of data, hence often relies on expert opinion. The use of expert opinion itself is sometimes limited by its inherent vagueness, which can be an important source of uncertainty that reduces the validity and applicability of the assessment. Fuzzy logic, specifically interval type-2 fuzzy logic, is able to model and propagate this type of uncertainty, and is a useful technique in risk assessment where expert opinion is relied upon. The present paper describes the implementation of a NIS fuzzy expert system (FES) for assessing the risk of invasion in marine environments via recreational vessels. The FES was based on expert opinion gathered through systematic elicitation exercises, designed to acknowledge important uncertainty sources (e.g., underspecificity and ambiguity). The FES, using interval type-2 fuzzy logic, calculated an invasion risk value (integrating NIS infection and detection probabilities) for a range of invasion scenarios. These scenarios were defined by all possible combinations of two vessel types (moored and trailered), five vessel components (hull, deck, internal spaces, anchor, fishing gear), two infection modes (fouling, water/sediment retention) and six frequently visited marine habitats (marina, mooring, farm, ramp, wharf, anchorage). Although invasion risk values determined using the FES approach was scenario-specific, general patterns were identified. Moored vessels consistently showed higher invasion risk values than trailered vessels. Invasion risk values were higher for anchorages, moorings and wharves. Similarly, hull-fouling was revealed as the highest infection risk mode after pooling results across all habitats. The NIS fuzzy expert system presented here appears as a valuable prioritising and decision-making tool for NIS research, prevention and control activities. Its easy implementation and wide applicability should encourage the development and application of this type of system as an integral part of biosecurity, and other environmental management plans.     

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.     

Multiple structural modifications to dendritic ecological networks produce simple responses

Structural modifications to landscapes affect the ability of organisms to access different habitat patches. There exist, however, very few general methods by which to relate modifications to expectations of effects, and even fewer that enable understanding of how multiple modifications may interact. In the absence of any guiding principles, ecologists have assumed that interactions will result in complex landscape-scale effects. One way of understanding such effects is through rendering a landscape as a graph or network, among the simplest of which are dendritic networks typified by stream systems. Yet even for stream networks, there are no known general principles concerning the nature of interactions between multiple modifications. We developed a model to describe the ability of fish to access and use different habitat patches within dendritic networks. We used mathematical and numerical analyses of the model to investigate how the habitat value of a network is affected by changes in connectivity and habitat quality, and then to examine interactions between multiple modifications. Rather than showing complex interactions, our analytic and simulation-based results show that the combined effect of multiple modifications approximately equals the sum of individually predicted effects. Dendritic networks thus appear to respond far more simply to multiple modifications than has previously been assumed. These results have implications for stream management planning, and offer a firm foundation from which to better understand population processes within dendritic networks.     

Application of a temperature-dependent von Bertalanffy growth model to bullhead (Cottus gobio)

The most studied and commonly applied model of fish growth is the von Bertalanffy model. However, this model does not take water temperature into account, which is one of the most important environmental factors affecting the life cycle of fish, as many physiological processes that determine growth, e.g. metabolic rate and oxygen supply, are directly influenced by temperature. In the present study we propose a version of the von Bertalanffy growth model that includes mean annual water temperatures by correlating the growth coefficient, k, explicitly and the asymptotic length, L_∞, implicitly to water temperature. All relationships include parameters with an obvious biological relevance that makes them easier to identify. The model is used to fit growth data of bullhead (Cottus gobio) at different locations in the Bez River network (Drme, France). We show that temperature explains much of the growth variability at the different sampling sites of the network.     

长江上游典型区域丰枯转换期水资源变化分析

针对长江上游金沙江下游区域近几年6月和10月出现的较剧烈的水资源丰枯转换现象,以2018年金沙江下游来水过程作为研究案例,考虑金沙江下游流域来水组成及水利工程建设情况,从区间流量分析及上游水库群调蓄影响分析两方面开展了研究工作。研究结果表明:金沙江下游流域丰枯转换主要影响因素为三堆子流量变化,三堆子至溪洛渡区间流量变化影响较小。在6月,上游水库群调蓄对金沙江下游流域丰枯转换影响较大,10月影响相对较小。相关研究成果可为溪洛渡-向家坝梯级水库调度计划制订及实际调度工作提供参考。