Incorporating Estimates of Survival, Biological Diversity and Spatial Distribution Into Salmonid Life-Cycle Models

Considerable effort is being expended on life cycle modeling to assist with the recovery of salmonid fishes. Many of these models have suggested that various life stages are limiting salmonid production (e.g., Karieva et al.2000; Greene et al. 2005; Honea et al. 2009). These models are also highly desirable for estimating salmonid carrying capacities and/or escapement goals. However, the modeling efforts are only as good as the data that populate them and sometimes those constructing the models do not fully understand the limitations of the data. Similarly, field scientists often do not collect the type of data needed to populate or improve life cycle models and the limiting life stage is often the one for which little data exists. Fortunately, several recent ongoing studies are quantifying life-stage specific survival, biological diversity, and other factors influencing production. These new findings are being used to improve models. Further, researchers are engaged in technical investigations that are advancing understanding of the number and diversity of salmonids needed to fill their various habitats by integrating statistical relationships with habitat-template approaches to more accurately model salmonid populations. The objective of this symposium is to bring together modelers and those making empirical estimates of survival and diversity to foster collaboration and determine future research needs. This symposium will include 28 presentations from a variety of scientists working on life cycle modeling or field estimates of survival or diversity for salmonids. The symposium will include sub-sessions focusing on modeling approaches, empirical survival estimates, and integrating survival, movement, and capacity estimates into models. We will close the symposium by summarizing the key research needs identified by each speaker and ways to improve survival estimates, life cycle models, and their use in management.