Time‐varying flow–ecology relationships for an endangered fish population: Longfin Smelt in the San Francisco Estuary

TL;DR

This study examines how changing river flows affect an endangered fish population in a California estuary, finding that flow-ecology relationships are not static and can guide conservation efforts.

Contribution

The study introduces a quantitative approach to model time-varying flow-ecology relationships for endangered fish populations.

Findings

Population dynamics of Longfin Smelt are best explained by habitat structure dimensions like channels versus shoals.

Flow effects on young fish abundance are positive in shallow habitats but inconsistent for older individuals.

Time-averaged approaches may oversimplify non-stationary relationships between environment and fish populations.

Abstract

Major estuaries globally are experiencing fast‐paced changes in hydrology and ecosystem dynamics. However, connecting alteration of river flow regimes to estuarine fish population dynamics remains a challenge, partly due to the untested assumption that flow regimes, fish dynamics, and the resulting flow–ecology relationships are stationary (i.e., have no systematic changes in mean or variance over time). Here, we studied the endangered population segment of Longfin Smelt (Spirinchus thaleichthys) in the San Francisco Estuary, which depends on seasonal river flows to reproduce. We used extensive biomonitoring data (1980–2020) and two time‐series modeling techniques, namely multivariate autoregressive state‐space (MARSS) models and dynamic linear models (DLMs), to understand how population dynamics respond to interannual flow variation, and whether flow–ecology relationships have changed over time. MARSS outputs showed that population trajectories are best explained by a combination of lateral and vertical dimensions of habitat structure, that is, whether individuals were collected in channels versus shoals, and in pelagic versus benthic environments. In turn, DLMs revealed time‐varying, but often positive effects of flow on young‐of‐the‐year abundance in shallow channel and shoal habitats, but no consistent relationships for older individuals (age‐1+), likely due to other drivers influencing survival from age‐0 and age‐1+. Finally, we found that the two modeling approaches showed agreement only in about 30% of the cases. Divergence in the sign and/or magnitude of flow effects suggests that time‐averaged approaches may sometimes oversimplify non‐stationary relationships between the environment and fish population dynamics. From a conservation standpoint, the gradually weakening but positive flow–ecology relationship (as opposed to a step change in the relationship) suggests that it may still be possible to reverse the steep population declines of Longfin Smelt through a combination of flow and habitat restoration actions. While we focused on a particular endangered population, our quantitative approach is transferable to other taxa and geographies, and could help inform management of flow‐dependent resources in systems strongly affected by non‐stationarity. We contend that time‐varying flow–ecology relationships are needed to better capture ecological realism, and could help design more effective conservation strategies in fast‐changing environments.

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