Time-varying flow-ecology relationships for an endangered fish population: Longfin Smelt in the San Francisco Estuary
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Major estuaries globally are experiencing steep changes in hydrology and ecosystem dynamics. However, connecting alteration of river flow regimes to 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., with no systematic changes in mean or variance over time). Here, we studied the endangered population segment of the 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, Multivariate Autoregressive State-Space models (MARSS) and Dynamic Linear models (DLM), 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 ..., , , # Time-varying flow-ecology relationships for an endangered fish population: Longfin Smelt in the San Francisco Estuary
## Provenance for this README
* File name: README_Dataset-LFS-models_v1.0.0.txt
* Authors: Parsa Saffarinia
* Other contributors: Albert Ruhi, Stephanie Carlson, Jim Hobbs
* Date created: 2024-11-06
## Dataset Version and Release History
* Current Version:
* Number: 1.0.0
* Date: 2024-11-06
* Persistent identifier: n/a
* Summary of changes: n/a
* Embargo Provenance: n/a
* Scope of embargo: n/a
* Embargo period: n/a
## Dataset Attribution and Usage
* Dataset Title: Data for the article \"Time-varying flow-ecology relationships for an endangered fish population: Longfin Smelt in the San Francisco Estuary\"
* Persistent Identifier:
* Dataset Contributors:
* Creators: Parsa Saffarinia, James Hobbs, Stephanie Carlson, and Albert Ruhi
* Date of Issue: n/a
* Publisher: n/a
* License: Use of these data is covered by the following license:
* Title: CC0 1.0 U...,
创建时间:
2025-10-11



