Ecologists are increasingly tackling difficult issues like global change, loss of biodiversity and sustainability of ecosystem services. These and related topics are enormously challenging, requiring unprecedented multidisciplinary collaboration and rapid synthesis of large amounts of diverse data into information and ultimately knowledge. New sensors, computers, data collection and storage devices and analytical and statistical methods provide a powerful tool kit to support analyses, graphics and visualizations that were unthinkable even a few years ago. New and increased emphasis on accessibility, management, processing and sharing of high-quality, well-maintained and understandable data represents a significant change in how scientists view and treat data. These issues are complex and despite their importance, are typically not addressed in database, ecological and statistical textbooks. <br><p>This book addresses these issues, providing a much needed resource for those involved in designing and implementing ecological research, as well as students who are entering the environmental sciences. Chapters focus on the design of ecological studies, data management principles, scientific databases, data quality assurance, data documentation, archiving ecological data and information and processing data into information and knowledge. The book stops short of a detailed treatment of data analysis, but does provide pointers to the relevant literature in graphics, statistics and knowledge discovery. The central thesis of the book is that high quality data management systems are critical for addressing future environmental challenges. This requires a new approach to how we conduct ecological research, that views data as a resource and promotes stewardship, recycling and sharing of data. <br><p><i>Ecological Data</i> will be particularly useful to those ecologists and information specialists that actively design, manage and analyze environmental databases. However, it will also benefit a wider audience of scientists and students in the ecological and environmental sciences.
1. Research Design: Translating Ideas to Data.
2. Data Management Principles, Implementation.
3. Scientific Databases.
4. Data Quality Assurance.
6. Archiving Ecological Data and Information.
7. Transforming Data into Information and Knowledge.
8. Ecological Knowledge and Future Data Challenges