Imperfect detection and the determination of environmental flows for fish: challenges, implications and solutions. (30th September 2015) - Gwinn, Daniel C.; Beesley, Leah S.; Close, Paul; Gawne, Ben; Davies, Peter M.
Summary: Relationships between river flow characteristics and fish community/population dynamics (i.e. flow–ecology relationships) underpin methods to determine and monitor environmental water allocations. Quantifying these relationships can be difficult, and consequently, most environmental flow strategies for fish conservation in Australian rivers are based on general flow–ecology relationships as opposed to statistical predictions. Of those studies that have investigated relationships between flow and fish, most have not accounted for incomplete and variable detection of fish by the sampling methods, thus making the implicit assumption that sampling efficiency is invariant. This important assumption is rarely met, leading to inconsistent research findings and spurious results, and a reliance on generic flow–ecology principles for defining flow management strategies. We illustrate how and when detection probability varies when sampling freshwater fish and the consequences to scientific inference about fish–flow relationships. Methods for accounting for imperfect detection of fish are identified and tools to increase the efficiency of experimental designs while reducing sampling cost are discussed. These tools include methods for borrowing information among experimental components and simulation techniques to optimise sampling designs. We argue that, due to the very nature of sampling designs to quantify flow–ecology relationships (e.g. sampling at different flow magnitudes/regimes), the challenge of imperfect detectability is particularly relevant to environmental flow science. We encourage the broader adoption of methods that account for imperfect detection to improve inference about fish–flow relationships and increase the successful application of environmental flows for managing fish communities.