Mapping of aggregated floodplain plant communities using image fusion of CASI and LiDAR data

Combined optical and laser altimeter data offer the potential to map and monitor plant communities based on their spectral and structural characteristics. A problem unresolved is, however, that narrowly defined plant communities, i.e. plant communities at a low hierarchical level of classification in the Braun-Blanquet system, often cannot be linked directly to remote sensing data for vegetation mapping. We studied whether and how a floristic dataset can be aggregated into a few major discrete, mappable classes without substantial loss of ecological meaning. Multi-source airborne data (CASI and LiDAR) and floristic field data were collected for a floodplain along the river Waal in the Netherlands. Mapping results based on floristic similarity alone did not achieve highest levels of accuracy. Ordination of floristic data showed that terrain elevation and soil moisture were the main underlying environmental drivers shaping the floodplain vegetation, but grouping of plant communities based on their position in the ordination space is not always obvious. Combined ordination-based grouping with floristic similarity clustering led to syntaxonomically relevant aggregated plant assemblages and yielded highest mapping accuracies.     

Optimizing support vector machine learning for semi-arid vegetation mapping by using clustering analysis

In remote sensing communities, support vector machine (SVM) learning has recently received increasing attention. SVM learning usually requires large memory and enormous amounts of computation time on large training sets. According to SVM algorithms, the SVM classification decision function is fully determined by support vectors, which compose a subset of the training sets. In this regard, a solution to optimize SVM learning is to efficiently reduce training sets. In this paper, a data reduction method based on agglomerative hierarchical clustering is proposed to obtain smaller training sets for SVM learning. Using a multiple angle remote sensing dataset of a semi-arid region, the effectiveness of the proposed method is evaluated by classification experiments with a series of reduced training sets. The experiments show that there is no loss of SVM accuracy when the original training set is reduced to 34% using the proposed approach. Maximum likelihood classification (MLC) also is applied on the reduced training sets. The results show that MLC can also maintain the classification accuracy. This implies that the most informative data instances can be retained by this approach.     

Ecological quality of some Tunisian coast and lagoon locations,by using benthic community parameters and biotic indices

Three Tunisian coastal and lagoon sites, variously affected by human activities, and differing according to their degree of communication with the sea, were studied. The total organic matter content and the granulometry of the sediment were measured and the macro-invertebrates were sampled and identified. Currently due to the lack of an efficient single biotic index for quality assessment, indications from these measurements can contribute to enrich our knowledge of the southern Mediterranean areas. Several biotic indices (AMBI, BENTIX, BOPA, BOPA modified, I2EC, ITI), most of which have been used in the context of the European Water Framework Directive, and some other structural parameters were used. The results show that the Bizerte lagoon, an almost closed area characterized mainly by extreme salinity/temperature and with a strong fluctuation of nutrients, appears biologically more impoverished. The Dkhila coast, which is more open to the sea, however, appears to be less dominated by the principal species. Biotic indices showed that the most polluted areas included the region exposed to urban inputs of Bizerte, the mouth of Hamdoun wadi and the harbour areas. In these locations, benthic macrofauna is dominated by opportunistic species like Capitella capitata, Scolelepis fuliginosa, Prionospio malmgreni, Polydora sp., Cirratulus cirratus and Cirriformia tentaculata. Other stations, which are farther from the sources of disturbance such as the mouths of the principal Wadis, the south of the Bizerte ship canal and the south of the Tunis bay, appear to be in good ecological condition and hosted a variety of sensitive species, Other stations were classified differently by the biotic indices used mainly because of the lack of a real inter-calibration of the various classification methodologies used by these indices.     

Nonlinear random wave-induced drag force on a vegetation field

This paper provides a practical method by which the drag force on a vegetation field beneath nonlinear random waves can be estimated. This is achieved by using a simple drag formula together with an empirical drag coefficient given by Mendez et al. (Mendez, F.J., Losada, I.J., Losada, M.A., 1999. Hydrodynamics induced by wind waves in a vegetation field. J. Geophys. Res. 104 (C8), 18383–18396). Effects of nonlinear waves are included by using Stokes second order wave theory where the basic harmonic motion is assumed to be a stationary Gaussian narrow–band random process. An example of calculation is also presented.     

Response of BITS (a benthic index based on taxonomic sufficiency) to water and sedimentary variables and comparison with other indices in three Adriatic lagoons

The European Water Framework Directive (WFD, 2000/60/EC) recommends the development of biotic indices for assessing the ecological quality status of water bodies. The Benthic Index based on Taxonomic Sufficiency (BITS) was specifically developed for lagoonal systems, according to the tolerant/opportunistic approach. Macrobenthic data, variables indicative of eutrophication and variables indicative of sedimentary organic matter quality were collected during 18 surveys carried out between 2004 and 2005 in three Adriatic coastal lagoons (Venice Lagoon, Sacca di Goro, Lesina Lagoon). The relationship between environmental variables and biotic indices (AMBI, BENTIX, BITS, BOPA and FINE) was tested using multivariate analyses. Indices based on species classification level appeared to relate better with the variables describing organic matter quality, whereas BITS, which is based on family classification level, seemed related to eutrophication indicative variables, such as sulphide, ammonium, dissolved oxygen and orthophosphate concentrations. The BITS approach reduces the costs associated with sorting and identification of organisms. Providing a rapid assessment of ecological quality, and producing an ecologically relevant classification, BITS seems a promising tool for monitoring programs of Adriatic lagoonal ecosystems. Its sensitivity in reflecting the field conditions elsewhere, however, remains to be assessed.     

Biometric,microstructural, and high-resolution trace element studies in Crassostrea gigas of Cantabria (Bay of Biscay,Spain): Anthropogenic and seasonal influences

Living Crassostrea gigas oysters of different ages and sizes were collected in three estuaries of Cantabria (Bay of Biscay, Spain): San Vicente de la Barquera Estuary, Santander Bay, and Marismas de Santoña Estuary. The main objective was to determine different shell responses to variable environmental parameters. A shell morphological study, based on three biometric indices, indicates that oysters of Santander Bay have two significant shell anomalies: abnormal thickening of the right valve and loss of vital cavity volume. These shell abnormalities are related with the presence in these waters of the chemical tributyltin. In the other two estuaries, the oysters show no detectable anomalies. Four shell microstructures have been distinguished: Regular Simple Prismatic, Regular Foliated, cone-Complex Cross Foliated, and Chalk. In Santander Bay oysters, the Chalk forms a “root-type” framework, whereas in the other two estuaries it forms a more compact microstructure. It is proposed that exposure to tributyltin has produced this modification. High-spatial-resolution geochemical transects have been carried out on the Regular Foliated microstructure in the umbo region in order to evaluate the distribution of Mg, Sr, and Na. The elements analysed exhibit clear cyclic variations in San Vicente de la Barquera Estuary and Marismas de Santoña Estuary oysters, related with seasonal periods, and characterised by broad maxima during months in which the waters are warmer and have higher salinity. These patterns are buffered in Santander Bay oysters. Our results demonstrate that biometric, microstructural, and high-resolution trace element studies in oyster shells can provide information about contaminants and seasonal variations in the estuarine environment.     

海洋生态系统健康评价的底栖生物指数法研究进展

海洋大型底栖无脊椎动物能对自然和人为活动导致的水和沉积物质量变化做出可预测的响应,因此利用底栖生物作为海洋生态环境监测的生物指标和进行系统健康度量的生物指数已经得到了广泛的认可.本文比较分析了几种常用的和正在发展的海洋生态系统健康和生态环境质量状况评估的底栖生物指数,包括指示生物法、Shannon-Wiener多样性指数、BI指数、AMBI指数和Bentix指数,总结了这几种生物指数的应用和特性,探讨了底栖生物指数在实际应用中可能存在的问题和解决的办法,以期为我国海洋生态系统健康评估工作提供参考.     

四川省上市公司可持续发展财务问题分析

财务指标是企业盈利能力的反映。根据近几年的相关数据,通过对财务指标综合分析,探讨四川省上市公司的可持续发展状况。     

规则波在缓坡上变形与破碎数值分析

通过在二维数值水槽内用边界元法直接求解Laplace方程,对规则波在缓坡上的变形及破碎进行了数值计算。分析了不同底坡及采用不同底摩阻系数时规则波的破碎特征,并对规则波破碎的极限坡度进行了研究。重点分析了规则波破碎时海底坡度、底摩阻系数及波形不对称性对破碎指标的影响。     

ENSO事件对西北太平洋热带气旋影响的分级研究

采用1951-2006年联合台风警报中心(JTWC)最佳路径数据集和气候预测中心(CPC) ENSO资料,分析了西北太平洋不同等级热带气旋累积能量(accumulated cyclone energy,ACE)与ENSO指数之间的关系.结果表明;ACE与ENSO指数间存在正相关关系;分级热带气旋中,ENSO事件主要通过超强台风(Super TY)的活动与ACE指数联系起来的,超强台风频数在El Ni(n)o期间多于La Ni(n)a 期间,同时持续时间也更长;ENSO指数和热带气旋活跃季超强台风ACE指数的滞后相关(ENSO指数滞后5个月内)与它们的同时相关大小相当.此外,还研究了分级热带气旋持续时间、强度和频数分别对ACE指数的贡献,结果显示超强台风频数的贡献最大.接下来,利用1951-2006年不同ENSO位相情况下NCEP再分析资料,分析了ENSO影响超强台风发生发展的物理机制.主要结论为:西北太平洋存在一些SuperTY频数与源地分布在ENSO年与平常年相比有明显差异的关键区;ENSO事件改变关键区低层相对涡度以及海表温度是其影响SuperTY源地及频数变化的重要途径.