Pacific Salmon Environmental and Life History Models: Advancing Science for Sustainable Salmon in the Future
What Are We Missing? Butterflies, Flowers, and Salmon Models
Peter W. Lawson
Abstract.—We understand our environment through our senses and tend to interpret the behavior of other animals in the context of the world we understand. Butterflies and flowers sometimes show distinctive patterns in ultraviolet light that are important to them but invisible to us. Likewise, the senses of fish and their experience of the world are very different from ours. Many aspects of a salmon’s environment, such as olfactory stimuli, are completely invisible to us. Other factors, like certain aspects of habitat alteration, are visible but unnoticed because they occurred gradually or long ago. Like Poe’s purloined letter they are cryptic—there for us to see if we only knew what to look for. As we build salmon models we base them on what we understand is important to the fish. However, our anthropocentric bias may cause us to overlook or misinterpret factors of importance. In addition, our necessarily simplified models, when applied to management, may result in a pernicious simplification of the salmon populations we wish to preserve. For example, if we model and manage for a dominant (or highly visible or easily monitored) salmon life history we may inadvertently eliminate other life histories of equal importance, or reduce diversity in ways that affect population viability. We should actively seek to identify important factors missing from our models and be aware of critical assumptions. Recognizing that our models are tools used to understand and manage salmon, we should try to understand the broader implications of these models to the future of the salmon we hope to preserve. In this essay, I offer speculation about what we may be missing in freshwater habitat, life history diversity, metapopulation dynamics, ocean survival, and water chemistry. I also consider the question of scale, and the effect our philosophical viewpoint may have on the direction and application of our modeling efforts and the likelihood of successful outcomes.