Description du livre
This book provides the background, knowledge, and tools to model and assess the health of freshwater ecosystems. For more than 100 years, freshwater scientists have used the biota living in an ecosystem to assess the effects of human activity (bioassessment), and in the last 50 years, in jurisdictions around the world, bioassessment of freshwater ecosystems has been embedded in legislation. In the 1990s, there was general acceptance of the so-called “Reference Condition Approach" to bioassessment - the biota in a given type of healthy ecosystem (e.g., wadable stream, inland lake) vary in space and time so any judgement of ecosystem health or sickness has to take this variability into account.
This volume brings all of this together, as author Robert Bailey first provides a brief synopsis of the variety of approaches used over the last century to distinguish healthy and unhealthy ecosystems (Chapter One), then demonstrates with two datasets (one simulated, one real) how to distinguish Reference and Test sites based on their natural and human activity environments (Chapter Two). In Chapter Three, Bailey uses the two datasets to demonstrate a new, causal modeling approach with Bayesian fitting to assess whether or not a test ecosystem is healthy. Many bioassessments are considered complete once a decision is made about a test site, but Bailey goes on to use the same modelling approach to try to understand why a site is unhealthy (Chapter Four), and then consider the often vexing issue about assessing changes in both healthy and unhealthy ecosystems through time in the face of large scale stressors like climate change (Chapter Five).
This book aims to stimulate the transformation of bioassessment programs to efficient and powerful tools that influence protection and management of freshwater ecosystems. In doing so, the author shows how to make the best use of relevant data from expensive, site-visit scale biological samples to “big” datasets available from satellite and land cover mapping programs.