Data for: Mimicking functional elements of the natural flow regime promotes native fish recovery in a regulated river

Environmental flows are essential to the conservation of riverine biodiversity, and are increasingly designed to protect components of the flow regime that support critical ecosystem functions. Yet, few studies have quantified biological responses to individual components of environmental flows. We used multivariate autoregressive state-space (MARSS) models to analyze 25 years of fish assemblage data collected before and after court-ratified environmental flows were implemented in Putah Creek, a dammed stream in California, USA. We quantified functional components of the flow regime that have been identified for Mediterranean climate regions of western North America and identified changes in these components from before to after the environmental flow regime was implemented. Additionally, we compared these values to their predicted natural ranges and modeled the probability of native and non-native fish assemblages declining by > 80% (quasi-extinction risk) under alternative management scenarios spanning the observed range of flow conditions. We found that as individual functional flow metrics became more similar to the ranges expected under natural, unaltered conditions, the quasi-extinction risk for the native fish assemblage decreased. Three functional flow metrics that shifted towards natural ranges following environmental flow implementation, fall pulse flow magnitude, wet season timing, and dry season duration, each corresponded with a 40% or greater decrease in native assemblage quasi-extinction risk. However, decreased spring recession flows and greater dry season baseflows post-flow modification shifted these metrics further from their natural ranges, increasing quasi-extinction risk for the native assemblage. Flow management scenarios revealed that the non-native fish assemblage quasi-extinction risk increased as flow metrics became more natural and decreased under more altered flow conditions. Few functional flow metrics were restored to their natural ranges following environmental flow implementation, yet even the modest changes towards more natural flows were found to suppress non-native and benefit native fish assemblages. Our findings illustrate that mimicking functional components of the natural flow regime is an important tool for designing environmental flows to conserve freshwater biodiversity.Funding provided by: California Department of Fish and WildlifeCrossref Funder Registry ID: http://dx.doi.org/10.13039/100006238Award Number: Agreement #P2083003Fish dataset The fish assemblage of Putah Creek was sampled annually by TRPA Fish Biologists and Normandeau Associates between 1993 and 2019 (with the exception of 2009 and 2011) using single-pass tote barge electrofishing. Fish were sampled at six locations downstream of the Putah Creek diversion dam. For these analyses, we restricted the sites considered to only the four sites closest to the diversion dam. These sites (site codes PDD, I505, STEVE, and PED) were approximately 0, 6, 16, and 21 km downstream of the diversion dam (respectively). Previous research found that the lower two sites (25 and 30 km downstream of the dam) were minimally affected by environmental flows implementation due to degraded habitat conditions (Kiernan et al. 2012). Functional flow metric calculations Discharge data from the Putah Creek diversion dam were provided by the US Bureau of Reclamation for 7/1/1975 – 8/31/202. All functional flow metrics were calculated on 40 years of streamflow data, spanning the 20 years before (pre) or 20 years after (post) environmental flow implementation, using the ffcAPIClient package (Santos et al. 2021, version 0.9.8.3) in R (R Core Team 2019). However, signal-processing algorithms in this version of the ffcAPIClient package do not always correctly identify the timing of seasonal transitions in highly modified hydrographs (Patterson et al. 2020). To improve the accuracy of flow metrics, we developed a ruleset to manually identify seasonal timing metrics (Baruch et al., in review). This ruleset was applied to all years, and all other metrics were re-calculated following Patterson et al. (2020) using the updated timing metrics. Additionally, the fall pulse does not occur every year but was an important component of the new environmental flow regime. To better understand changes in fall pulse flows, we calculated the fall pulse magnitude as the difference between dry season median flow magnitude and the maximum magnitude of the first discharge event greater than 1.5 times the dry season baseflow that occurred between October 1 and December 15th. Years with no fall pulse therefore have a magnitude of 0. Predictions of natural, unimpaired streamflow conditions were calculated by Grantham et al. ( 2022; additional information available at https://rivers.codefornature.org/). Streamflow data for Upper Putah Creek was obtained from the USGS (gauge 11453500) to create a hydrograph of natural streamflow conditions upstream of all major water impoundments and diversions for comparison to the downstream flow conditions. Missing flow data at the Upper Putah Creek gauge were modeled from the nearby Bear Creek gauge (USGS 11451715). The same manual ruleset for functional flow metric calculation was applied to the Upper Putah Creek streamflow data for consistency with the downstream data. References Grantham, T. E., D. M. Carlisle, J. Howard, B. Lane, R. Lusardi, A. Obester, S. Sandoval-Solis, B. Stanford, E. D. Stein, K. T. Taniguchi-Quan, S. M. Yarnell, and J. K. H. Zimmerman. 2022. Modeling functional flows in California's rivers. Frontiers in Environmental Science 10. Kiernan, J. D., P. B. Moyle, and P. K. Crain. 2012. Restoring native fish assemblages to a regulated California stream using the natural flow regime concept. Ecological Applications 22:1472–1482. Patterson, N. K., B. A. Lane, S. Sandoval-Solis, G. B. Pasternack, S. M. Yarnell, and Y. Qiu. 2020. A hydrologic feature detection algorithm to quantify seasonal components of flow regimes. Journal of Hydrology 585:124787. R Core Team. 2019. R: a language and environment for statistical computing. Vienna, Austria. https://www.r-project.org/. Santos, N., R. Peek, and A. Obester. 2022. ffcAPIClient: Functional Flows Calculator API Client. R package version 0.9.8.3