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Complex ecological interactions are widely utilized to deliver conservation benefits but their efficacy is often debated. Using a coral reef trophic cascade as an example, we reveal that outcomes can be surprisingly difficult to detect. Even important impacts of marine reserves can go undetected (20% more coral with power < 0.5). This evidentiary challenge is compounded by misinterpretation of "nonsignificant" results as evidence of failed conservation practice. We illustrate a more appropriate analytical approach using a Bayesian Region of Practical Equivalence (ROPE) whereby many tests of conservation practice would be interpreted correctly as "undecided" rather than "negative." Practitioners working with ecological cascades will increasingly be faced with "undecided" evidence of conservation benefits. Since one solution is to consider a wider diversity of evidence, we provide a hierarchy of evidentiary quality. In this way, even reductionist evidence of the component ecological interactions can be utilized, which is far easier to collect and evaluate. [ABSTRACT FROM AUTHOR]

Project prioritization protocols are an important tool for allocating conservation resources efficiently, and have been applied to a range of species and ecosystems. Current approaches are inadequate when applied to species with distinct threats impacting different and/or multiple life history stages, such as sea turtles. We develop a model that integrates the benefit of any management project on a population by way of its expected population growth rate, including projects targeting different and/or multiple life history stages. To illustrate its utility, we prioritize projects for investment relevant to Australia's eastern population of Flatback turtle ( Natator depressus). We rely upon expert-elicitation to estimate individual benefit parameters, feasibility, and cost, and calculate the cost-effectiveness of each project. The most cost-effective project was not the most feasible, cheapest, or most beneficial. Our approach will help managers make efficient decisions that account for the full range of threats operating on a population. [ABSTRACT FROM AUTHOR]