Shifting variance structure as a potential indicator of fish-population responses to large-scale perturbation

Abstract

Fishery-independent surveys are widely used to provide essential information for the restoration and management of fish populations. It is generally assumed that these monitoring surveys produce representative data on how fish populations vary over space and time. For example, observed fish-population metrics may vary among repeated samples from a single location, from site-to-site within a lake, from lake-to-lake, and among sampling years. We will discuss the use of mixed models to quantify how the total variability of a response variable can be partitioned among spatial and temporal components. Further, we expect that the structure of variation (i.e., variance components themselves), not just the total variance, can be responsive to severe large-scale perturbation. For fish populations, large-scale perturbations may be influential via either direct (e.g., new sources of predation) or more indirect pathways (e.g., system changes following establishment of invasive species). In either case, a resulting shift in variance structure could have implications for monitoring programs (e.g., influencing the power to detect long-term trends from standardized sampling). We analyzed long-term survey data to explore the notion that an ecological perturbation may induce a shift in a population's underlying variance structure