Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

Types of narrow-skulled vole (<Emphasis Type="Italic">Lasiopodomys gregalis</Emphasis>) colonies in Northern Kulunda and seasonal dynamics of their demographic composition

Demographic structure and its seasonal dynamics have been studied in colonies of narrow-skulled voles (Lasiopodomys gregalis Pall.) in Northern Kulunda. Three types of colonies have been distinguished: (I) true colonies (large, complex families), (II) simple families (nuclear or incomplete), and (III) all-male colonies. Changes in their sex, age, and functional composition (based on animal migration activity) during the breeding season have been analyzed.     

Analytic framework for assessing participation processes and outcomes of climate change adaptation tools

The assumptions and empirical evidence linking climate change adaptation to development cooperation have led to the emergence of a range of climate change adaptation tools aiming at improving the quality of development cooperation initiatives in times of global change. In order to assess the quality of these tools, we develop an analytic framework to critically assess the social learning and sustainable development outcomes of climate change adaptation tools. The analytic framework defines project objectives, participation typology, participation tools, participation stages, scenarios development, modelling exercises, stakeholder analysis and risk communication strategies that support quality participation outcomes.     

Bioanalytical screening methods for dioxins and dioxin-like compounds a review of bioassay/biomarker technology.

Determination of environmental pollutants utilizing biodetectors such as bioassays, biomarkers, enzyme immunoassays (EIAs), or other bioanalytical tools is a continuously growing area. The present literature review describes the principles and advantages/limitations of several bioanalytical detection methods (BDMs) for the screening and diagnosis of dioxin and dioxin-like compounds. This study characterizes briefly the family of dioxin and dioxin-like compounds, discusses potential Ah receptor (AhR) ligands and cytochrome P-450 (CYP) 1A1-enzyme-inducing compounds. 'Milestones' in the development of BDMs are summarized and explained in detail for a number of bioanalytical tools that can be used to detect these classes of dioxin-like persistent bioaccumulative toxicants (PBTs). The design of a screening profile with a battery of bioassays/biomarkers coupled with the chemical analysis is evaluated. The relative potencies (REPs) to 2,3,7,8-TCDD for dioxin-like compounds are reviewed for various BDMs and the differences are noted.     

Analysis of microcystins in cyanobacteria blooms and surface water samples from Meiliang Bay,Taihu Lake,China

Taihu Lake is the third largest freshwater lake in China. In recent years, the water pollution of cyanobacteria blooms has become a severe problem in this area. Microcystins (MCs) are an important group of toxic compounds mainly produced by some cyanobacteria species and have both acute and chronic hepatotoxic effects on animals and humans. This paper presents the first data on the identification and detection of MCs in both natural occurring cyanobacteria blooms and surface water samples (0-0.5 m), collected from Meiliang Bay, Taihu Lake, China. A conventional method for extraction and isolation of MCs from cyanobacteria blooms was applied. High-performance liquid chromatography (HPLC) analysis showed that the main toxic component in the cyanobacteria materials was MC-LR. The monoclonal antibody (mAb) against MC-LR produced by hybridoma technique was employed for direct competitive ELISA to detect the concentrations of MCs in bloom and water samples collected in 2001. The results not only revealed the presence of MCs but also temporal variations of MCs levels of three sampling stations in Meiliang Bay in 1 year. It is obvious that the MC contents were relatively higher during warm months and related with the status of eutrophication. Our study indicates the threat associated with MCs in water body of Taihu Lake. To prevent the MCs potential hazard on public health in this area, some necessary measures of monitoring and control of growth of cyanobacteria are urgently needed.