Protected Species – Research Permits and the Value of Basic Research

The complexities involved in obtaining permits for field research using protected species continue to increase. In October 1988, Congress amended the Marine Mammal Protection Act (MMPA) to increase the documentation required to obtain a scientific research permit (PL 100-711). Applicants for scientific research permits must now submit “information indicating that the taking is required to further a bona fide scientific purpose and does not involve unnecessary duplication of research.”

Review of Global Warming in the 21st Century. Volume 1: Our Evolving Climate Crisis; Volume 2: Melting Ice and Warming Seas; Volume 3: Plants and Animals in Peril by Bruce E. Johansen

There is compelling evidence that Planet Earth is on the path to an era of global warming that has serious implications for the well-being of both people and nature. This three-volume synthesis of literature will be a marvelous place for both the public and new scholars interested in global warming to begin their pursuit of the subject. The author captures the best of the scientific literature and press materials appearing in recent years. The utility of these volumes as a resource for gaining a broad background or pursuing a particular aspect of global warming is enhanced by Johansen's talent for explaining with clarity a vast and rapidly growing subject.

Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.