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This much revised and expanded edition provides a valuable and detailed summary of the many uses of diatoms in a wide range of applications in the environmental and earth sciences. Particular emphasis is placed on the use of diatoms in analysing ecological problems related to climate change, acidification, eutrophication, and other pollution issues. The chapters are divided into sections for easy reference, with separate sections covering indicators in different aquatic environments. A final section explores diatom use in other fields of study such as forensics, oil and gas exploration, nanotechnology, and archaeology. Sixteen new chapters have been added since the first edition, including introductory chapters on diatom biology and the numerical approaches used by diatomists. The extensive glossary has also been expanded and now includes over 1,000 detailed entries, which will help non-specialists to use the book effectively.
The Twelfth International Diatom Symposium stressed how diatoms can be used to assess the human impact on natural waters, without neglecting other important fields of research. As the frustules of many diatom species are relatively resistant to dissolution they are preserved in freshwater and marine sediments and provide a record of past environments on earth. In past decades they have been successfully used to reconstruct changes in water bodies evoked by changes in salinity, acidification and eutrophication. In the last few years diatom-inferred predictions of environmental variables have become much more quantitative. In the most recent research reports the strong separation between palaeolimnological and neolimnological diatom research is fading, as palaeolimnologists are increasingly using modern calibration sets to infer past states of the environment. This quantitative approach is also very suitable for prediction of future changes in the biota of surface waters. Also ecological changes due to climatic modification have been investigated more thoroughly recently. A very important new research topic is the occurrence of toxic diatoms, particularly along the coasts of North America. These proceedings are intended to be a balanced view of such modern developments in diatom research. They should also be of interest to non-specialists in diatoms, who can use the results of diatom research as a tool in a more general taxonomic, ecological and geological context.
Timely synopsis of applications in environment and industry using ubiquitous microscopic algae.
Vegetation communities in Australia's riverine landscapes are ecologically, economically and culturally significant. They are also among the most threatened ecosystems on the continent and have been dramatically altered as a result of human activities and climate change. Vegetation of Australian Riverine Landscapes brings together, for the first time, the results of the substantial amount of research that has been conducted over the last few decades into the biology, ecology and management of these important plant communities in Australia. The book is divided into four sections. The first section provides context with respect to the spatial and temporal dimensions of riverine landscapes in Australia. The second section examines key groups of riverine plants, while the third section provides an overview of riverine vegetation in five major regions of Australia, including patterns, significant threats and management. The final section explores critical issues associated with the conservation and management of riverine plants and vegetation, including water management, salinity, fire and restoration. Vegetation of Australian Riverine Landscapes highlights the incredible diversity and dynamic nature of riverine vegetation across Australia, and will be an excellent reference for researchers, academics and environmental consultants.
Freshwater Algae of North America: Ecology and Classification, Second Edition is an authoritative and practical treatise on the classification, biodiversity, and ecology of all known genera of freshwater algae from North America. The book provides essential taxonomic and ecological information about one of the most diverse and ubiquitous groups of organisms on earth. This single volume brings together experts on all the groups of algae that occur in fresh waters (also soils, snow, and extreme inland environments). In the decade since the first edition, there has been an explosion of new information on the classification, ecology, and biogeography of many groups of algae, with the use of molecular techniques and renewed interest in biological diversity. Accordingly, this new edition covers updated classification information of most algal groups and the reassignment of many genera and species, as well as new research on harmful algal blooms. - Extensive and complete - Describes every genus of freshwater algae known from North America, with an analytical dichotomous key, descriptions of diagnostic features, and at least one image of every genus. - Full-color images throughout provide superb visual examples of freshwater algae - Updated Environmental Issues and Classifications, including new information on harmful algal blooms (HAB) - Fully revised introductory chapters, including new topics on biodiversity, and taste and odor problems - Updated to reflect the rapid advances in algal classification and taxonomy due to the widespread use of DNA technologies
This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Through presenting the optimal attacks in wireless sensor networks, array signal processing, principal component analysis, etc, the authors reveal the robustness of the signal processing algorithms against adversarial attacks. Since data quality is crucial in signal processing, the adversary that can poison the data will be a significant threat to signal processing. Therefore, it is necessary and urgent to investigate the behavior of machine learning algorithms in signal processing under adversarial attacks. The authors in this book mainly examine the adversarial robustness of three commonly used machine learning algorithms in signal processing respectively: linear regression, LASSO-based feature selection, and principal component analysis (PCA). As to linear regression, the authors derive the optimal poisoning data sample and the optimal feature modifications, and also demonstrate the effectiveness of the attack against a wireless distributed learning system. The authors further extend the linear regression to LASSO-based feature selection and study the best strategy to mislead the learning system to select the wrong features. The authors find the optimal attack strategy by solving a bi-level optimization problem and also illustrate how this attack influences array signal processing and weather data analysis. In the end, the authors consider the adversarial robustness of the subspace learning problem. The authors examine the optimal modification strategy under the energy constraints to delude the PCA-based subspace learning algorithm. This book targets researchers working in machine learning, electronic information, and information theory as well as advanced-level students studying these subjects. R&D engineers who are working in machine learning, adversarial machine learning, robust machine learning, and technical consultants working on the security and robustness of machine learning are likely to purchase this book as a reference guide.