DOI: 10.6078/d16f0m
title: Disentangling abiotic and biotic controls of age-0 Pacific herring population stability across the San Francisco Estuary

description: Pacific herring (Clupea pallasii) is an ecologically and commercially
 valuable forage fish in the North Pacific Ocean. However, knowledge gaps
 exist around the abiotic and biotic drivers behind its variable population
 dynamics–as well as on the ability of the species to show spatially
 structured trends that stabilize population portfolios in the face of
 environmental change. Here we examined how historical hydroclimatic
 variability in the San Francisco Estuary (California) has driven age-0
 Pacific herring population dynamics over 35 years. First, we used wavelet
 analyses to examine spatio-temporal variation and synchrony in the
 environment, focusing on two key variables: salinity and temperature.
 Next, we fitted Multivariate Autoregressive State-Space models to
 environmental and abundance time series to test for spatial structure and
 to parse out abiotic (salinity and temperature) from biotic influences
 (spawning and density dependence). Finally, we examined the stabilizing
 effects of spatially asynchronous population fluctuations (i.e., portfolio
 effects) across the estuary. Our results showed that temperature, but not
 salinity, fluctuated synchronously across regions on seasonal and decadal
 timescales. The top-ranked model showed strong evidence of regional
 population structure and regional variation in population responses to the
 environment. As expected, age-0 herring were generally associated with
 cooler, saltier conditions in spring. Density dependence was strong in all
 regions, suggesting that local factors influencing rearing conditions
 limited juvenile population growth across the estuary. Notably, age-0
 abundance fluctuations were on average 15% more stable across the estuary
 than in individual regions, demonstrating that portfolio effects arising
 from population asynchrony have been helping to stabilize recruitment
 across the estuary over the past four decades. We contend that
 ecosystem-based fishery management strategies to restore eelgrass and
 tidal-marsh-rearing habitats could increase the carrying capacity of the
 estuary, further stabilizing the herring population and reducing the risk
 of fishery closures.
description: These data were derived from the following resources available in
 the public domain: (1) Department of California Fish and Wildlife (CDFW)
 San Francisco Bay Study (URL: https://filelib.wildlife.ca.gov/Public/BayStudy/) and (2) Department of California Fish and Wildlife (CDFW) Pacific Herring Team (public data available upon request - submit request here: https://wildlife.ca.gov/Regions/Marine/Contact/Ask-Marine). These derived data were processed according to the following steps. For the age-0 catch-per-unit-effort (CPUE) data extracted from the San Francisco Bay Study midwater trawl from 1981–2015, stations where sampling yielded catch &gt;0 in 50% of the time steps were retained, to ensure convergence of the MARSS models. This resulted in 30 stations (4 regions). For the spawning stock biomass (SSB) index, no filtering occurred because it represents a single estimate for the entire estuary. All values were log-transformed and z-score transformed prior to modeling. Variables used in analysis and provided in attached data files. Region codes: C, Central Bay; S, South Bay; SP, San Pablo Bay; SU, Suisun Bay. <strong>Variable</strong> <strong>Survey name</strong> <strong>Gear type</strong> <strong>Spatial extent</strong> <strong>Period</strong> <em><strong>Pacific herring</strong></em>         Mean CPUE: Age 0 CDFW SF Bay Study Midwater trawl S, C, SP, SU April to June Spawning stock biomass (SSB) index: Age 2+ CDFW Herring Team Egg deposition and spawner surveys Estuary (S, C, SP combined) October to April <em><strong>Environmental</strong></em>         Mean salinity (PSU) CDFW SF Bay Study Water quality sonde: mean of surface and bottom profiles S, C, SP, SU October to June Mean temperature (°C) CDFW SF Bay Study Water quality sonde: mean of surface and bottom profiles S, C, SP, SU October to June
description: Please see the README document
 ("README_Dataset-PacificHerringSFBay_v1.0.1.txt") and the
 accompanying article: Pak, N., D. Colombano, T. Greiner, J. Hobbs, S.
 Carlson, and A. Ruhi. 2023. Disentangling abiotic and biotic controls of
 age-0 Pacific herring population stability across the San Francisco
 Estuary. Ecosphere. Accepted. R Markdown script is
 provided to reproduce model results based on the derived datasets:
 Multivariate autoregressive state space (MARSS) model script specifies
 model structures, fits, diagnostics, AICc comparisons, and
 coefficients.