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Understanding the effects of hydrology on fish populations is essential to managing for native fish conservation. However, despite decades of research illustrating streamflow influences on fish habitat, reproduction, and survival, biologists remain challenged when tasked with predicting how fish populations will respond to changes in flow regimes. This uncertainty stems from insufficient understanding of the context‐dependent mechanisms underlying fish responses to, for example, periods of reduced flow or altered frequency of high‐flow events. We aim to address this gap by drawing on previous research to hypothesize mechanisms by which low and high flows influence fish populations and communities, identifying challenges that stem from data limitations and ecological complexity, and outlining research directions that can advance an empirical basis for prediction. Focusing flow ecology research on testing and refining mechanistic hypotheses can help narrow management uncertainties and better support species conservation in changing flow regimes.

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Time‐series data offer wide‐ranging opportunities to test hypotheses about the physical and biological factors that influence species abundances. Although sophisticated models have been developed and applied to analyze abundance time series, they require information about species detectability that is often unavailable. We propose that in many cases, simpler models are adequate for testing hypotheses. We consider three relatively simple regression models for time series, using simulated and empirical (fish and mammal) datasets. Model A is a conventional generalized linear model of abundance, model B adds a temporal autoregressive term, and model C uses an estimate of population growth rate as a response variable, with the option of including a term for density dependence. All models can be fit using Bayesian and non‐Bayesian methods. Simulation results demonstrated that model C tended to have greater support for long‐lived, lower‐fecundity organisms (K life‐history strategists), while model A, the simplest, tended to be supported for shorter‐lived, high‐fecundity organisms (r life‐history strategists). Analysis of real‐world fish and mammal datasets found that models A, B, and C each enjoyed support for at least some species, but sometimes yielded different insights. In particular, model C indicated effects of predictor variables that were not evident in analyses with models A and B. Bayesian and frequentist models yielded similar parameter estimates and performance. We conclude that relatively simple models are useful for testing hypotheses about the factors that influence abundance in time‐series data, and can be appropriate choices for datasets that lack the information needed to fit more complicated models. When feasible, we advise fitting datasets with multiple models because they can provide complementary information.

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There is inconsistent evidence that stream restoration projects lead to recovery of ecosystem attributes, especially stream biota. While some assessments have documented desired changes in fish community metrics in the first years following restoration, longer‐term studies have not always corroborated these findings. In this study, we used data and monitoring reports submitted to federal regulators by stream mitigation consultants to examine whether in‐stream restoration activities led to changes in fish community attributes at 23 compensatory mitigation projects representing 53 sampling sites in Georgia, United States over 7 years of post‐restoration monitoring. Modeling results indicated that abundance and species richness of fishes generally increased in the first years after restoration before decreasing to baseline levels by the seventh year. This pattern was consistent for models considering sensitive fish taxa, as well as at sites across a range of agricultural and forested land cover percentages. However, the effect of restoration on species richness was dampened in larger streams and at more urbanized locations. A community trajectory analysis supported the findings that fish community change was transitory at most sites. Remote estimation of canopy cover change at restoration sites suggested that the hump‐shaped response may be driven by increased light availability during the immediate‐post restoration period, followed by subsequent re‐shading of stream channels by riparian plantings. Our analysis indicates that reach‐level manipulation of streams should not be expected to induce long‐term changes in fish communities, and that publicly available monitoring reports may be leveraged to address questions of stream restoration efficacy.

Accidental spills of chemicals and other pollutants can decimate populations of stream-dwelling species. Recovery from such accidents can be relatively fast and complete when the affected stream reaches can be recolonized from upstream and downstream sources. However, faunal recoveries from accidental spills that extirpate populations from entire headwater streams have not been extensively documented, and understanding resilience of headwater-stream biota is relevant for assessing threats to at-risk species. We assessed recovery of fish populations in a 5.7-km-long headwater stream in the southeastern United States following a complete, or nearly complete, fish-kill caused by a chemical spill near the source of the stream. We sampled for fishes at five stream locations, two downstream and three upstream from a perched, culverted road-crossing located 2.4 km upstream from the stream mouth, over a period of 18.5 mo following the poisoning event. We observed 11 fish species, representing ≤65% of the fish species expected based on occurrences in nearby tributary streams. In postpoisoning sampling, only three of these taxa were observed upstream of the culvert; all 11 species, including the federally threatened Cherokee Darter Etheostoma scotti, were found downstream of the culvert but were mostly represented by a few, large individuals. In contrast, dead individuals of at least eight taxa including the Cherokee Darter were observed upstream of the culvert at the time of the fish-kill. These observations provide evidence of slow recovery of a headwater fish fauna, and especially upstream of a barrier to fish movement, where the recolonization sources are primarily downstream. Additional case studies may reveal whether this result applies generally to headwater streams. Slow recovery could make species that primarily inhabit or maintain greatest abundances in headwaters, including multiple at-risk fishes, particularly vulnerable to the threat of accidental spills that result in local population extirpation.