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Estuaries and Coasts
https://doi.org/10.1007/s12237-021-01019-9
Spatiotemporal Variability inEnvironmental Conditions Influences
thePerformance andBehavior ofJuvenile Steelhead inaCoastal
California Lagoon
RosealeaM.Bond1 · JosephD.Kiernan2,3 · Ann‑MarieK.Osterback1 · CynthiaH.Kern1· AlexanderE.Hay1·
JoshuaM.Meko1· MilesE.Daniels1 · JereyM.Perez1
Received: 16 February 2021 / Revised: 13 October 2021 / Accepted: 20 October 2021
© The Author(s) 2021
Abstract
In California (USA), seasonal lagoons provide important oversummer rearing habitat for juvenile steelhead trout (anadromous
Oncorhynchus mykiss). However, key water quality parameters such as temperature and dissolved oxygen concentration can
periodically approach or exceed the physiological tolerances of steelhead during the protracted dry season. A field study
employing distributed temperature sensing technology, water quality monitoring, habitat mapping, and mark-recapture
sampling was conducted to examine how shifting environmental conditions affected the performance and behavior of juve-
nile steelhead in the Scott Creek estuary/lagoon (Santa Cruz County). Abiotic conditions were driven by episodic inputs of
seawater to the typically freshwater lagoon. During midsummer, the water column was vertically stratified which reduced
suitable lagoon rearing habitat by approximately 40%. Nevertheless, steelhead abundance, growth, and condition factor were
high during the summer and decreased in autumn following lagoon destratification and cooling. Unlike previous work, this
study identified limited emigration from the lagoon to riverine habitat during the summer. Instead, juvenile steelhead exhib-
ited crepuscular movement patterns within the lagoon, with peaks in upstream (to upper lagoon habitat) and downstream (to
lower lagoon habitat) movement occurring at dawn and dusk, respectively. This study underscores that habitat complexity
and connectivity are critical for juvenile steelhead production and persistence and provides insight into steelhead habitat
use and behavior in seasonal lagoons.
Keywords Bar-built estuary· Distributed temperature sensing· Critical habitat· Endangered species· Climate change
Introduction
In many areas of the world, coastal estuaries periodically
lose connectivity with the marine environment due to the
formation of seasonal sandbars (barrier beaches) at their
tidal mouths (Lill etal. 2013). Termed bar-built estuaries
(Emmett etal. 2000), sandbar formation predominantly
occurs during the dry season when reduced fluvial discharge
coincides with increased ocean swell intensity and longshore
sand deposition (Behrens etal. 2013; Clark and O’Connor
2019). Freshwater discharge from the drainage network is
subsequently impounded behind the sandbar and the estu-
ary converts to a seasonal lagoon. Although the timing and
duration of river mouth closures are highly variable from
year to year, lagoonal conditions can persist for weeks to
months until the sandbar is eroded by high energy waves and
(or) elevated streamflow, and connectivity with the marine
Communicated by Ronald Baker
Rosealea M. Bond and Joseph D. Kiernan contributed equally to
this work.
* Rosealea M. Bond
lea.bond@noaa.gov
1 Fisheries Collaborative Program, Institute ofMarine
Sciences, University ofCalifornia, Santa Cruz, Affiliated
With Southwest Fisheries Science Center, National Marine
Fisheries Service, National Oceanic andAtmospheric
Administration, 110 McAllister Way, SantaCruz, CA95060,
USA
2 Fisheries Ecology Division, Southwest Fisheries Science
Center, National Marine Fisheries Service, National Oceanic
andAtmospheric Administration, 110 McAllister Way,
SantaCruz, CA95060, USA
3 Institute ofMarine Sciences, University ofCalifornia, Santa
Cruz, 1156 High Street, SantaCruz, CA95064, USA
Estuaries and Coasts
1 3
environment is reestablished (Smith 1990; Behrens etal.
2013; Nylen 2015).
In California (USA), nearly half of the state’s coastal
river mouths are influenced by seasonal sandbar formation
to varying degrees (Heady etal. 2015; Clark and O’Connor
2019). Following mouth closure, estuaries often transition
through multiple ecological states due to episodic changes in
key environmental parameters such as lagoon volume, water
temperature, dissolved oxygen (DO) concentration, and salin-
ity (Shapovalov and Taft 1954; Boughton etal. 2017). While
freshwater predominates, conditions can become brackish
when occasional large waves overtop the beach crest and
deliver seawater into the lagoon (Smith 1990; Nylen 2015;
Osterback etal. 2018). Episodic overtopping events can sub-
stantially alter lagoon water chemistry and result in strati-
fied conditions (both vertical and longitudinal) which can
last days to months at a time depending on lagoon bathym-
etry and the volume of freshwater inflow delivered from the
watershed (Behrens etal. 2013, 2016; Nylen 2015). Con-
sequently, abiotic conditions can periodically approach or
exceed the physiological tolerances of some lagoon-rearing
organisms. There is growing concern that periods of extreme
environmental conditions may become increasingly common-
place due to habitat alteration and climate warming (Richards
etal. 2018; Crozier etal. 2019), with adverse consequences
for native fishes that use estuaries and lagoons as part of their
life history strategies (Moyle etal. 2013; National Marine
Fisheries Service 2012, 2016).
For juvenile steelhead trout (anadromous Oncorhyn-
chus mykiss), seasonal lagoons have been characterized as
high-risk, high-reward rearing habitat (Satterthwaite etal.
2012). Despite representing a small fraction of the oversum-
mer rearing habitat in most coastal California watersheds
(Bond etal. 2008), lagoon rearing may confer significant
fitness advantages due to abundant prey resources and high
growth potential. Hayes etal. (2008) reported that summer
and autumn weekly growth rates were significantly (6- to
17-fold) higher for lagoon-rearing juvenile steelhead relative
to conspecifics rearing in upstream riverine habitat. Addi-
tionally, empirical studies have demonstrated that lagoon-
rearing juvenile steelhead often attain critical size for ocean
entry (fork lengths > 150 mm) at a relatively early age, expe-
rience enhanced marine survival, and disproportionately
recruit to the adult breeding population (Bond etal. 2008;
Hayes etal. 2011). However, lagoons may expose juvenile
steelhead to elevated predation risk (Hayes etal. 2011;
Frechette etal. 2013; Osterback etal. 2013) and periods of
physiological stress due to degraded water quality (Smith
1990; Boughton etal. 2017; Osterback etal. 2018).
Recently, Osterback etal. (2018) provided evidence that
juvenile salmonids (both steelhead and the more thermally
sensitive coho salmon, Oncorhynchus kisutch) were able to
survive and add substantial body mass in the Scott Creek
(Santa Cruz County, CA, USA) lagoon during an extended
(> 7 months) drought-related closure event, despite periods
of high water temperature (> 20 °C) and hypoxia (DO < 5
mg L−1). It remains unclear, however, how juvenile salmo-
nids cope with such extremes when they occur. Based on
previous works (e.g., Bond etal. 2007; Hayes etal. 2011)
and additional data, Osterback etal. (2018) hypothesized
that juvenile salmonid persistence was likely facilitated by
alternating upstream movement to cooler riverine habitat
and downstream movement to the prey-rich lower lagoon.
To test this upstream–downstream movement hypoth-
esis, we intensively monitored a 1.5-km segment of lower
Scott Creek through the full period of creek mouth closure
and lagoon formation during the 2018 dry season (late
June–November). Our study area encompassed the estu-
ary/lagoon, lagoon-river transition zone, and lower main-
stem riverine habitat, thus permitting an assessment of how
spatiotemporal patterns in abiotic conditions related to the
behavior and performance of juvenile steelhead during the
annual dry period. Our goals were to (1) characterize fine-
grained spatiotemporal dynamics of key physical habitat and
water quality parameters throughout the lagoon and lower
mainstem creek; (2) quantify the response of lagoon-rearing
juvenile steelhead in terms of monthly abundance, growth,
and condition; and (3) quantify the response of juvenile
steelhead in terms of movement within and among estuary/
lagoon and riverine habitats.
Methods
Study Site
The Scott Creek watershed is a small (watershed area = 70
km2) coastal drainage located approximately 90 km south
of San Francisco (CA, USA; 37° 02′ 26″ N, 122° 13′ 44″
W; Fig.1). The climate is cool Mediterranean with mean
air temperatures ranging from approximately 10 °C during
the winter to 17 °C during the summer. Summer tempera-
tures are tempered by recurrent coastal fog and low cloud
cover. Rainfall patterns produce an annual hydrograph char-
acterized by episodic spates (> 35 m3 s−1) during winter
and spring, followed by a protracted period of low stream-
flow (< 0.1 m3 s−1) throughout summer and autumn. While
instantaneous water temperatures rarely exceed 20 °C in
lotic portions of the watershed, the small exposed estuary
at the terminus of the drainage network is prone to summer
heating and water temperatures can exceed 24 °C (Hayes
etal. 2008; Osterback etal. 2018). The Scott Creek freshwa-
ter fish assemblage is entirely native and composed of coho
salmon, steelhead, threespine stickleback (Gasterosteus acu-
leatus), prickly sculpin (Cottus asper), and coastrange scul-
pin (Cottus aleuticus). Pacific staghorn sculpin (Leptocottus
Estuaries and Coasts
1 3
armatus) and tidewater goby (Gobius newberryi) are estua-
rine residents, and juvenile starry flounder (Platichthys
stellatus) are occasionally present. Both tidewater goby and
coho salmon (central California coast evolutionarily signifi-
cant unit) are listed as endangered under the US Endangered
Species Act (ESA), while steelhead (central California coast
distinct population segment) is listed as a threatened species.
Scott Creek is representative of most small coastal water-
sheds in California, in that its estuary converts to a lagoon
for many months during the annual dry season due to the
formation of a sandbar at the creek mouth that severs con-
nectivity with the Pacific Ocean. Between 2003 and 2017,
the average annual dates of creek mouth closure (i.e., sand-
bar formation) and reopening were 17 July (day of year
[DOY] = 198) and 29 November (DOY = 333), respectively.
Data collection in support of this study was initiated on 20
June 2018, prior to mouth closure on 5 July (DOY = 186)
and was terminated on 20 November 2018 prior to the first
major rainfall event (the sandbar naturally breached due to
elevated discharge on 30 November, DOY = 334). Thus, our
study characterized nearly the full range of environmental
conditions in the Scott Creek estuary/lagoon immediately
preceding and during mouth closure in a typical annual
open-close cycle.
Study Design
We focused on a 1.5-km segment of lower Scott Creek
that encompassed both estuarine and riverine habitat. The
study segment was partitioned into four contiguous sample
reaches based on salient changes in geomorphic and (or)
environmental conditions: (1) the lower lagoon sample reach
extended from the California State Route 1 bridge (desig-
nated as river kilometer [rkm] 0.0 in our study) upstream to
where adjacent wetland vegetation transitioned from marsh
plants to low scrub (~ rkm 0.17); (2) the middle lagoon sam-
ple reach extended from rkm 0.17 to the confluence with
an ephemeral tributary known locally as Queseria Creek
(~ rkm 0.48); (3) the upper lagoon sample reach extended
from Queseria Creek to the lagoon-river transition zone; and
(4) the riverine sample reach extended from the lagoon-river
transition zone upstream to rkm 1.48 (Figs.1, 2). We defined
the extent of lagoon inundation as the distance upstream
from rkm 0.0 to the first riffle in which there was a break in
water surface elevation; this location ranged from rkm 0.72
to 0.83 during the study period.
Field Methods
Physical Habitat Characterization
To quantify physical habitat conditions within the estuary/
lagoon, we established 28 sampling transects oriented per-
pendicular to the longitudinal axis of the stream channel.
Transects began at rkm 0.0 and extended upstream (inland)
at irregularly spaced intervals (interval range = 25–40 m) to
the maximum extent of inundation during the study period
(rkm 0.83; Fig.1). At each lagoon transect, we measured
wetted width (± 0.1 m), maximum depth (± 0.1 m), and
determined percentage shading (± 1.0%) using a Solar
Pathfinder™ (Solar Pathways, Colorado Springs, CO, USA)
positioned at the water surface directly above the point of
maximum depth.
To characterize physical habitat conditions within the
riverine sample reach, up to 31 mesohabitat units were des-
ignated as riffle, run, or pool according to water depth and
surface velocity. The number of riverine habitat units like-
wise varied during the study due to changes in the upstream
extent of lagoon inundation. For each riverine habitat unit,
we quantified unit length (± 0.1 m), mean wetted width
(± 0.1 m), and maximum depth (± 0.1 m). Percentage shad-
ing was measured every 25 m along the thalweg. For riv-
erine pool habitats, we report depth as residual pool depth,
Fig. 1 Location map of the Scott Creek (Santa Cruz County, CA,
USA) watershed and a detailed view of the four sample reaches in
the 1.5-km study segment. Numbers refer to the Lagoon (1), Interface
(2), and Riverine PIT tag antenna arrays (3). Water downstream of
the California State Route 1 bridge was too shallow for sampling and
was excluded from the study. Satellite image credit: Google Earth; 9
August 2018
Estuaries and Coasts
1 3
calculated as the difference in streambed elevation between
the deepest point in the pool and the downstream riffle crest
(Lisle 1987). Physical habitat sampling was conducted
monthly within 48 h of each fish sampling event (see Meth-
ods: “Fish Capture and Tagging”).
Water Quality
We continuously measured water temperature (°C) in each
of the four sample reaches (Fig.1) using TidbiT® v2 data
loggers (Onset Computer Corporation, Bourne, MA, USA).
The temperature loggers were positioned in the water col-
umn at a height 0.3 m above the bottom and programmed to
record every 15 min. To determine longitudinal and vertical
patterns in water quality, we generated monthly vertical pro-
files of temperature, DO (mg L−1), and salinity (‰) at each
lagoon transect, using a YSI 556 handheld multi-probe sys-
tem (Yellow Springs Instruments Inc., Yellow Springs, OH,
USA). Vertical profile sampling was conducted from down-
stream to upstream at the point of maximum depth along
each transect and characterized the entire water column at
10-cm intervals. Profile sampling was conducted from a
kayak during daytime hours (10:00–15:00 h) over a 1–2-day
period and occurred just prior to each fish sampling event.
High‑resolution Distributed Temperature Sensing
We used a multi-channel distributed temperature sensing
(DTS) instrument (XT-DTS™, Silixa Ltd., Elstree, Hert-
fordshire, UK) and spliced fiber-optic cable (PS-2S2M-
3PA038-01, Silixa Ltd.) to continually characterize the
near-bottom thermal regime in the study segment. DTS
instruments function as densely spaced linear sensors via
the fiber-optic cable, producing temperature datasets with
high spatial and temporal resolution (Selker etal. 2006a,
b; Tyler etal. 2009). We deployed approximately 1.6 km of
fiber-optic cable starting at the upstream end of the riverine
sample reach (rkm 1.48) and terminating in the lower lagoon
(rkm 0.13) immediately adjacent to our fish sampling area.
The DTS was deployed in a “duplexed single-ended” config-
uration with the instrument stationed upstream (streamside
at rkm 1.48) and accompanied by two sequential calibra-
tion baths (Hausner etal. 2011; Bond etal. 2015). The DTS
instrument collected data every 10 min at 25-cm intervals
per channel along the entire length of the fiber-optic cable.
Eight TidbiT® v2 temperature data loggers were installed
along the length of the cable for calibration and validation
(Hausner etal. 2011; Bond etal. 2015).
Fish Capture andTagging
To generate monthly estimates of juvenile steelhead
abundance, growth, and condition factor, we conducted
mark-recapture sampling in the lower lagoon sample reach
(i.e., rkm 0.0–0.17) between July and November 2018. Fish
sampling occurred on two consecutive days each month,
whereby the first day served as the mark event and the sec-
ond day the recapture event. This approach resulted in 10
sampling occasions over the 5-month study period. Juve-
nile steelhead were captured using a nylon beach seine (35
m long × 2.0 m deep), following the methods described by
Osterback etal. (2018). Sampling effort was standardized
on each occasion and consisted of seven seine hauls in the
sampling area. Based on the work of Cowley and Whitfield
(2001), we assumed that fish had sufficient time to redistrib-
ute and mix between each sampling occasion; thus, capture
probabilities were homogeneous on each date. All captured
steelhead were counted, measured for fork length (FL; ± 1.0
mm), and scanned for the presence of a passive integrated
transponder (PIT) tag. Some captured individuals had been
PIT-tagged prior to our study in support of ongoing research
and monitoring, and these individuals were retained in the
dataset. A subset of previously untagged juvenile steel-
head ≥ 65 mm FL (the minimum size for PIT tagging) were
anesthetized with buffered tricaine methanesulfonate (MS-
222; Western Chemical Inc., Ferndale, WA, USA), measured
for FL and mass (± 0.1 g), and implanted with PIT tags (12
mm HDX tag; Oregon RFID Inc., Portland, OR, USA) via
intraperitoneal injection. Implicit in all PIT tagging stud-
ies is the assumption that the performance and behavior of
tagged individuals will be unbiased and representative of
the broader (untagged) population. The capture and han-
dling of ESA-listed steelhead was authorized by the National
Marine Fisheries Service under Sect.10(a)(1)(A) permit No.
17292-2A. All procedures were carried out in accordance
with approved protocols from the Institutional Animal Care
and Use Committee at University of California Santa Cruz
(Protocol No. KIERJ1604_A1).
Movement Behavior ofPIT‑Tagged Individuals
To monitor the movement behavior of PIT-tagged juvenile
steelhead during the study period, we operated three PIT tag
interrogation stations (Multi-antenna HDX readers; Oregon
RFID Inc.) within our 1.5-km study segment. The three sta-
tions, identified as the Lagoon Array, Interface Array, and
Riverine Array, were located at rkm 0.30 (near the midpoint
of the lagoon), rkm 0.72 (near the lagoon-riverine interface),
and rkm 1.42 (in mainstem riverine habitat), respectively
(Fig.1). Each array consisted of paired swim-through anten-
nas that were separated by ~ 3.0 m and spanned the entire
channel width. The clocks and scan-cycles of all stations
were synchronized over the study period; thus, we were able
to quantify the timing and extent of movement by juvenile
steelhead within and among lagoon and riverine habitats. We
hypothesized (1) the Interface Array would detect elevated
Estuaries and Coasts
1 3
rates of upstream movement (i.e., to riverine habitat) when
conditions within the estuary/lagoon became physiologically
stressful for juvenile steelhead, and (2) the timing of direc-
tional fish movement over a diel (24 h) cycle at each station
would be non-random.
Data Analysis
Temperature Datasets
Time series data generated by the temperature loggers in
each sample reach (Fig.1) were converted to 7-day mov-
ing averages of daily maximum temperature values to derive
maximum weekly maximum temperature (MWMT; i.e., the
highest mean value obtained across the entire study period).
MWMT is a common metric for characterizing differences
in thermal maxima in salmon-bearing ecosystems (e.g.,
United States Environmental Protection Agency 2003). Post-
processing of DTS data was conducted in the MATLAB®
(The MathWorks, Natrick, MA, USA) computing environ-
ment using the DTS Toolbox produced by the Center for
Transformative Environmental Monitoring Programs (https://
ctemps. org/ data- proce ssing, last accessed 1 October 2021).
We followed the "three-section explicit with step loss"
method (Hausner etal. 2011), whereby data from each chan-
nel were calibrated against two known points (calibration
baths) and validated against a third set of points (temperature
loggers affixed to the fiber-optic cable). Diagnostic statistics
indicated both validation root mean square error (0.39) and
validation bias (0.14) were within the ranges reported in other
aquatic field applications using single-ended measurements
(e.g., Hausner etal. 2011).
Steelhead Abundance, Growth, andCondition Factor
Estimates of juvenile steelhead abundance were generated for
each monthly mark-recapture event using the POPAN formu-
lation of the Jolly-Seber model (Schwarz and Arnason 1996)
within Program MARK (White and Burnham 1999). Param-
eters included in POPAN to estimate abundance at each sam-
pling occasion included (1) probability of survival (ϕ); (2)
probability of capture (p); (3) probability of entry (β); and
(4) super-population size (N*; Schwarz and Arnason 1996;
Williams etal. 2011). We initialized the model with a com-
bination of PIT-tagged and untagged fish, the latter consid-
ered losses on capture (Frechette etal. 2016). This approach
allowed us to include all captured individuals in the model
without the cost and burden of physically marking (i.e., PIT
tagging) every fish. However, because untagged individuals
may have unknowingly been handled multiple times during
the study period, the super-population estimate generated by
the POPAN model is potentially inflated (Malcolm-White
etal. 2020) and not presented herein. Rather, we focus on
the estimates of steelhead abundance generated for each sam-
pling occasion which were expected to be unbiased (Schwarz
and Arnason 1996; Frechette etal. 2016; Osterback etal.
2018). The candidate POPAN model set included four mod-
els: (1) the probabilities of survival, capture, and entry were
allowed to vary over time (ϕ(t)p(t)β(t)N*); (2) the probabilities
of capture and entry were allowed to vary over time while
the probability of survival was held constant over time
(ϕ(.)p(t)β(t)N*); (3) the probabilities of survival and entry were
allowed to vary over time while the probability of capture
was held constant over time (ϕ(t)p(.)β(t)N*); and (4) a null
model in which both survival and capture were held con-
stant over time and the probability of entry was allowed to
vary over time (ϕ(.)p(.)β(t)N*). To assess POPAN model fit, we
applied a chi-square (χ2) goodness-of-fit test to the saturated
model using Program RELEASE within Program MARK.
If lack of fit was identified, we assumed it was due to overd-
ispersion of captures and a variance inflation factor (
̂c
) was
applied to the model set. The variance inflation factor was
calculated using the χ2 test statistic and degrees of freedom
(df) obtained from Program RELEASE (Cooch and White
2021; Sect.5.5.1) using the equation:
Model selection was performed using quasi-Akaike’s Infor-
mation Criterion adjusted for small sample size (QAICc;
Lebreton etal. 1992).
We calculated the mass-specific growth rates (MSGR)
of PIT-tagged individuals captured in consecutive months
using the formula:
where M2 is the final wet mass (g), M1 is the initial wet mass
(g), d is the growth interval (days), and b is the allometric
mass exponent for the relationship between fish growth rate
and wet mass (Ostrovsky 1995). We used b = 0.34 derived
from empirical studies of O. mykiss (Wangila and Dick
1988). MSGR standardizes growth across size ranges and is
reported as the percentage change in mass per gram of body
mass per day (% g−1 day−1). The determination of MSGR for
individuals captured in July was made possible by sampling
conducted in the lagoon in early June (6–8 June 2018), prior
to sandbar closure and the initiation of lagoon conditions.
Condition factor (K) was calculated for a subset of steel-
head captured during each sampling as:
(1)
̂c
=
𝜒2
df
(2)
MSGR
=
M
b
2−M
b
1
b×d
×
100
(3)
K
=
M×10
5
L
3
Estuaries and Coasts
1 3
where M is wet mass (g) and L is fork length (mm). Dif-
ferences in monthly K and square root transformed MSGR
were assessed using one-way analysis of variance (ANOVA)
followed by post hoc tests using Tukey’s honest significant
difference (HSD). Statistical analyses were performed in the
R statistical environment (R Development Core Team 2019).
PIT Tag Detection Data
Raw PIT tag detection data were screened and pro-
cessed following the methods described by Osterback
etal. (2018) to remove milling behavior and (or) resi-
dency, and to identify directional movement events. We
Table 1 Mean physical habitat
characteristics (± standard error)
for the four sample reaches
during monthly sampling of
Scott Creek (CA, USA), during
the 2018 dry season (July–
November)
a Variability in the number of sampling transects and reach length is due to changes in the upstream extent
of lagoon inundation (i.e., location of the lotic/lentic interface) during the study period
Variable Sample reach
Lower lagoon Middle lagoon Upper lagoon Riverine
Number of transectsa5 9 10–14 24–31
Reach length (m)a173.6 309.3 346.3 ± 28.0 655.9 ± 20.4
Reach area (m2)5,165.9 ± 86.6 5,133.7 ± 68.3 3,947.7 ± 286.4 3,816.0 ± 255.8
Wetted width (m) 28.4 ± 0.2 16.6 ± 0.1 10.5 ± 0.2 5.8 ± 0.1
Shade (%) 19.6 ± 6.7 41.2 ± 4.9 71.1 ± 3.2 87.7 ± 1.7
Maximum depth (m) 2.1 ± 0.02 1.6 ± 0.02 1.0 ± 0.04 –-
Residual pool depth (m) –- –- –- 0.7 ± 0.04
Riffle by length (%) –- –- –- 13.9 ± 0.5
Run by length (%) –- –- –- 8.7 ± 1.3
Pool by length (%) –- –- –- 77.3 ± 1.7
Fig. 2 Representative habitat
characteristics for the four sam-
ple reaches in the Scott Creek
(CA, USA) watershed (a) lower
lagoon, (b) middle lagoon, (c)
upper lagoon, and (d) riverine
sample reaches. All photos
taken facing upstream
Estuaries and Coasts
1 3
subsequently assigned “upstream” or “downstream”
directionality to each fish movement event based on
serial detections and categorized an event as “ambigu-
ous” with respect to directionality when a detection only
occurred on one of the paired antennas. To examine diel
movement patterns, we employed two statistical tests
using the circular package in R (Agostinelli and Lund
2017). First, we used the Hermans-Rasson test to assess
whether the distribution of upstream or downstream
movements differed significantly from uniformity over
a diel cycle (Landler etal. 2019). Second, we used the
non-parametric Mardia-Watson-Wheeler test (Batschelet
1981) to examine whether diel activity patterns (i.e.,
mean time of day) differed for upstream and downstream
movement during the study. Additionally, we plotted
directional movement data relative to sunlight condi-
tions, categorized as night, dawn, day, or dusk based
on local sunrise and sunset information for each day
of the study (United States Naval Observatory 2011).
We defined dawn and dusk as the periods 2.5 h before
sunrise and after sunset, respectively.
Results
Reach Scale Habitat Characteristics
The four sample reaches represented a longitudinal gra-
dient in habitat size and complexity. During the study,
the lower lagoon reach had the greatest wetted width
(mean ± SE = 28.4 ± 0.2 m) and depth (2.1 ± 0.02 m), and
these habitat parameters decreased in each successive
sample reach moving inland (Table1). Conversely, mean
shading increased fourfold in the same direction, from
19.6 ± 6.7% in the lower lagoon sample reach to 87.7 ± 1.7%
in the riverine sample reach (Table1). The gradient in shad-
ing reflected a general upstream reduction in channel width,
coupled with a shift in adjacent terrestrial plant communi-
ties from emergent marsh plants in the lower lagoon sample
reach, to coastal scrub in the middle lagoon sample reach,
and ultimately to tall woody riparian species in the upper
lagoon and riverine sample reaches (Fig.2). Pools were the
dominant mesohabitat type within the riverine sample reach
and pool units were highly variable in size (monthly mean
residual depth = 0.7 ± 0.04 m, range 0.2–1.7 m; Table1).
Spatiotemporal Variability inAbiotic Conditions
DTS, temperature logger, and vertical profile data were used
to identify four distinct environmental phases in the devel-
opment and evolution of the Scott Creek lagoon during our
154-day study. The first 23 days (20 June–12 July; phase 1)
encompassed sandbar formation on 5 July and conversion of
the tidally influenced estuary into lagoonal conditions. Dur-
ing the beginning of phase 1, mean water temperatures were
similar across the four sample reaches owing to predominantly
lotic conditions and the conveyance of cool (~ 16.0 °C) fresh-
water from upstream (Figs.3 and 4a-c, Table2). Following
sandbar formation, lagoon volume increased and there was an
inland transition to lentic conditions between rkms 0 and 0.72.
The second environmental phase lasted 27 days (13
July–8 August; Fig.3) and was characterized by intense
warming and stratification. Abiotic conditions during phase
2 were driven by wave overtopping events on 13–14 July
and 25 July that delivered large amounts of seawater to the
lagoon. Seawater inputs increased lagoon water volume and
the upstream extent of lagoon inundation by 117 m (to rkm
0.83), where it remained for the duration of the study. The
water column was vertically stratified across all three lagoon
sample reaches, with relatively cool and well-oxygenated
freshwater in the upper water column and warm saline water
at depths ≥ 1.1 m (Fig. 4d-f). DTS revealed progressive
warming of the salt water at the bottom of the lagoon dur-
ing phase 2 (Fig.3), and both the instantaneous maximum
daily temperature and the MWMT in each sample reach
were observed during this period (Fig.5).
Fig. 3 Mean daily watertemperature profile in the Scott Creek (CA,
USA) estuary/lagoon and lower mainstem creek between 21 June and
20 November 2018 determined using distributed temperature sensing
technology. The direction of streamflow is from top to bottom (y-axis)
and time is from left to right (x-axis). Environmental phases were
20 June–12 July (phase 1), 13 July–8 August (phase 2), 9 August–7
September (phase 3), and 8 September–20 November (phase 4) 2018.
River kilometer is distance upstream from the California State Route
1 bridge
Estuaries and Coasts
1 3
By 9 August, continual seepage of trapped saltwa-
ter through the sandbar (driven by a pressure differential
between the lagoon and the Pacific Ocean) was sufficient
to break down the strong vertical density differences that
maintained stratification of the water column. This marked
the onset of phase 3 (9 August–7 September, 30 days) and
allowed wind-driven vertical mixing to freshen and cool
nearly the entire water column (Table2). While DTS data
indicated persistent pockets of warm saltwater during this
environmental phase (horizontal bands of warm temperature
in Fig.3), these pockets were relatively small and generally
restricted to the deepest locations in the lagoon (depths > 2.0
m; Fig.4g-i).
By 8 September, warm saline water was largely absent
from the lagoon for the first time since sandbar formation on
5 July (65 days earlier). This marked the beginning of phase
4 (8 September–20 November), a protracted 74-day period
of cooling aided by progressively shorter photoperiod,
cooler weather conditions, and frequent wind-driven mixing
of the water column. During this final environmental phase,
there was a steady transition to relatively homogeneous
thermal conditions throughout the study segment (Figs.3
and 4j-l). A period of wave overtopping during late phase 4
(24 October) delivered modest amounts of saltwater to the
lagoon (Fig.3) and a single pocket of saline and hypoxic
water accumulated at depths > 1.7 m in the lower and middle
lagoon sample reaches (rkm 0.07–0.20). Nevertheless, the
vast majority of the lagoon remained fresh, well-oxygenated,
and cool (Fig.4m-o, Table2).
Steelhead Abundance, Growth, andCondition
Factor
We PIT-tagged 1,475 juvenile steelhead across the five
monthly seining events and captured an additional 455
individuals in the lagoon that were tagged (by us) prior to
this study. Approximately 44% (n = 843) of these fish were
captured on two or more sampling occasions resulting in
5,163 total captures of PIT-tagged individuals. An additional
6,022 juveniles ≥ 65 mm FL (53.8% of the total captures)
were captured and subsequently released without receiving
a PIT tag. Capture histories from PIT-tagged individuals
were used to construct four POPAN models. Before rank-
ing candidate models, we performed a χ2 goodness-of-fit
test which indicated a modest lack of model fit (χ2 = 69.54,
df = 39, p = 0.0019); therefore, a variance inflation factor (
̂c
Fig. 4 Vertical profiles of
temperature (left column),
dissolved oxygen concentration
(center column), and salinity
(right column) collected in the
Scott Creek (CA, USA) estuary/
lagoon during the 2018 dry sea-
son. Vertical profiling occurred
on 28–29 June (phase 1), 2–3
August (phase 2), 4 September
(phase 3), 9 October (early
phase 4), and 1 November (late
phase 4). Measurements for
each parameter were collected
at irregularly spaced sampling
transects (see Methods: “Water
Quality”) and values were inter-
polated between transects. River
kilometer is distance upstream
from the California State Route
1 bridge
Estuaries and Coasts
1 3
= 1.78) was applied to the model set to correct for over-
dispersion. The top POPAN model had the lowest QAICc
score, received 99.9% of the model weight, and had time-
dependent probabilities of survival, capture, and entry ((ϕ
(t)p(t)β(t)N*); Table3).
An estimated 2,183 (95% CI = 2,010–2,371) juvenile
steelhead were present in the estuary just before sandbar
formation in early July, and the abundance of lagoon-
rearing steelhead increased over the next two months,
reaching a high of 3,065 (95% CI = 2,857–3,289) indi-
viduals in early September (Fig.6a). Following this peak,
there was an abrupt 34% decline in steelhead abundance
in October (NOct = 2,017; 95% CI = 1,830–2,223) and the
population remained at approximately this level for the
remainder of the study (Fig.6a). We found differences in
both steelhead MSGR (ANOVA, F4, 1755 = 283, p < 0.001;
Fig.6b) and condition factor (ANOVA, F4, 5067 = 167,
p < 0.001; Fig.6c) across the five monthly sample events.
Mean steelhead growth rates were positive during every
month of the study (Fig.6b) and there was a stepwise
monthly increase in mean fork length (Electronic Sup-
plemental Material #1, Fig.S1). Although temporal pat-
terns differed somewhat for steelhead growth rate versus
condition factor, the lowest mean monthly values for each
metric occurred in October for MSGR (0.52 ± 0.03% g−1
day−1; Fig.6b), and in October and November for condi-
tion factor (K = 1.06 ± 0.01 both months; Fig.6c).
Movement Behavior ofPIT‑Tagged Individuals
After removing fish milling behavior, a total of 17,797 dis-
tinct movement events were generated by 1,572 PIT-tagged
juvenile steelhead across the study period. Most (93.9%)
fish movement occurred at the Lagoon Array (n = 16,716
events generated by 1,521 different individuals). Markedly
fewer steelhead were detected moving past the Interface
Array (5.5%; n = 983 events produced by 412 individuals)
or the Riverine Array (0.6%; n = 98 events generated by
40 individuals), and the bulk of detections at these two
stations occurred during the last five days of the study
(Electronic Supplemental Material #2, Fig.S2). Although
daily operational status was variable at each station, over-
all estimates of antenna efficiency across the study period
were 99.4% and 88.3% at the Interface and Riverine
arrays, respectively. We were unable to derive a compa-
rable estimate of antenna efficiency at the Lagoon Array
Table 2 Vertical profile means and ranges (min = minimum, max = maximum) for water temperature, dissolved oxygen concentration, and salin-
ity by sample reach during each environmental phase
a Vertical profile data were not collected in the riverine sample reach. riverine water temperature was derived from DTS measurements collected
during the same periods that vertical profiling occurred
Period Profile date(s) Sample reach Temperature (°C) Dissolved oxygen
(mg L−1)
Salinity (‰)
Mean Min Max Mean Min Max Mean Min Max
Phase 1 (20 Jun–12 Jul) 28–29 Jun Lower lagoon 16.6 14.2 26.2 8.7 6.8 18.1 3.04 0.15 24.77
Middle lagoon 15.2 13.9 24.9 9.6 8.6 18.4 1.19 0.12 24.75
Upper lagoon 15.9 14.8 18.5 9.1 7.5 10.3 0.50 0.11 16.10
Riverinea16.2 14.0 17.3 –- –- –- < 0.1 –- –-
Phase 2 (13 Jul–8 Aug) 2–3 Aug Lower lagoon 21.6 17.8 27.8 6.9 0.3 11.3 7.75 0.43 25.71
Middle lagoon 19.0 15.6 27.3 6.6 3.0 10.7 3.96 0.15 19.77
Upper lagoon 17.8 15.6 24.9 7.5 3.3 12.0 2.09 0.12 18.16
Riverinea17.7 15.0 20.0 –- –- –- < 0.1 –- –-
Phase 3 (9 Aug–7 Sept) 4 Sept Lower lagoon 17.7 16.6 22.6 5.8 0.3 6.8 1.35 0.16 25.28
Middle lagoon 17.3 15.5 18.3 6.1 4.3 7.0 0.19 0.15 2.54
Upper lagoon 16.4 15.4 17.9 6.8 1.1 7.9 0.29 0.14 13.99
Riverinea16.2 14.8 18.3 –- –- –- < 0.1 –- –-
Phase 4 Early (8 Sept–24 Oct) 9 Oct Lower lagoon 16.1 15.4 16.4 6.0 4.1 7.3 0.16 0.15 0.26
Middle lagoon 16.0 14.8 16.5 5.8 4.4 7.1 0.16 0.15 0.17
Upper lagoon 15.3 14.6 16.4 5.9 4.4 6.9 0.15 0.14 0.16
Riverinea15.3 14.5 17.7 –- –- –- < 0.1 –- –-
Phase 4 Late (25 Oct–20 Nov) 1 Nov Lower lagoon 14.1 13.1 18.5 7.4 1.2 8.9 2.02 0.26 17.49
Middle lagoon 13.1 12.4 16.9 6.8 1.8 7.6 0.53 0.16 14.17
Upper lagoon 13.0 12.3 14.3 7.1 5.8 8.4 0.16 0.16 0.17
Riverinea13.4 12.5 14.5 –- –- –- < 0.1 –- –-
Estuaries and Coasts
1 3
(see Electronic Supplemental Material #2, TableS1). It is
instructive to note that 81.5% of the 1,930 PIT-tagged juve-
nile steelhead captured in the lagoon during fish sampling
were subsequently detected at one or more antenna arrays
during the study period.
Unambiguous upstream or downstream directional-
ity was assigned to 25.8% (n = 4,595) of all fish movement
events; again the majority of which occurred at the Lagoon
Array (n = 4,021, 87.5%; Fig.S2). Statistical inference was
restricted to juvenile steelhead movement data generated at
the Lagoon Array due to a highly skewed temporal distribu-
tion of movement events at the Interface array and inadequate
sample size (too few events) at the Riverine Array. Direc-
tional movement at the Lagoon Array was non-uniformly
distributed throughout a 24-h period (Hermans-Rasson test,
TDownstream = 1251.8, p < 0.001; TUpstream = 1348.5, p < 0.001)
with most directional movement occurring during crepuscular
periods. We compared mean directional movements within
the four environmental phases and further partitioned phase
4 into early and late periods due to the protracted length of
this environmental phase (see Results: “Spatiotemporal Vari-
ability in Abiotic Conditions”). The mean time of day for
upstream and downstream movement by PIT-tagged steelhead
differed within each environmental phase (Mardia-Watson-
Wheeler test, p < 0.001 in all cases) except during phase 2
(p = 0.426). Specifically, a peak in downstream movement
events (i.e., fish moving into the lower lagoon) occurred at
dusk (40.2%, n = 777), whereas a peak in upstream movement
events (i.e., moving inland from the lower lagoon) occurred at
dawn (46.2%, n = 966; Fig.7). Although the movement pat-
terns exhibited by individual steelhead were highly variable,
our results suggested a broad pattern in which lagoon-rearing
steelhead often retreated from the lower lagoon at dawn,
resided between the Lagoon and Interface Arrays (~ 400 m
Fig. 5 Seven-day movingaver-
age of daily maximum water
temperatures measured in each
sample reach (Scott Creek,
CA, USA), during the study
period. The maximum value in
each time series represents the
maximum weekly maximum
temperature (MWMT). The
dates (2018) of MWMT in each
sample reach were 3 August in
the lower lagoon, 30 July in
the middle lagoon, and 27 July
in both the upper lagoon and
riverine sample reaches
Table 3 Comparison of four candidate POPAN models used to esti-
mate the probability of survival (ϕ), probability of capture (p), prob-
ability of entry (β), and super-population size (N*) for juvenile steel-
head in the Scott Creek (CA, USA) lagoon
a A variance inflation factor (
̂c
= 1.78) was applied to the model set to
correct for overdispersion
b Key to model subscripts: (t) = parameter varied with time; and
(.) = parameter was estimated as the mean value and was held con-
stant over time
c Super-population size (N*) is included in the model notion by con-
vention. However, the super-population estimate was potentially
biased due to our sampling protocols (i.e., multiple captures of
untagged fish; see Methods: “Steelhead Abundance, Growth, and
Condition Factor”) and not reported herein
Modela,b,c QAICcΔQAICcModel weight
ϕ(t)p(t)β(t)N* 6707.92 0.00 0.999
ϕ(.)p(t)β(t)N* 6727.26 19.34 < 0.001
ϕ(t)p(.)β(t)N* 7170.91 462.99 0.000
ϕ(.)p(.)β(t)N* 7409.83 701.91 0.000
Estuaries and Coasts
1 3
distance) during the day, and returned to the lower lagoon
around sunset regardless of environmental phase.
Discussion
Persistent Stratification andReduced Habitat
Suitability
Seawater delivered during episodic wave overwash events
strongly influenced ecological conditions in the shallow
(max. depth = 2.8 m) Scott Creek lagoon during much
of our 154-day study. High-resolution DTS and vertical
profile measurements identified multiple inputs of sea-
water following sandbar formation that resulted in haline
stratification and facilitated the development of distinct
vertical gradients in water temperature and DO concen-
tration across much of the lagoon (Figs.3 and 4). Strong
stratification inhibited wind-driven mixing of the water
column and allowed warm and hypoxic conditions to per-
sist within the lower water column, particularly at the
deepest points of the lagoon (Fig.4). We documented an
extensive lower saline layer extending inland to rkm 0.7
which persisted in some (deep) locations for up to 65 days
(Figs.3 and 4).
A large literature on the temperature preferences and
requirements of juvenile O. mykiss suggests that growth
is optimized between 14 and 19 °C depending on food
availability (Hokanson etal. 1977; Hicks 2000; Richter
and Kolmes 2005), and that temperatures above 22–24
°C induce cellular stress (e.g., production of heat shock
proteins; Viant etal. 2003; Werner etal. 2005), alter fish
behavior (e.g., reduce agonistic and foraging activity;
Sloat and Osterback 2013), and reduce various proxy
measures of fitness (e.g., growth, body size, and lipid
storage; Kammerer and Heppell 2013). Consequently,
elevated water temperatures (≥ 21 °C) generally elicit
thermoregulatory strategies in steelhead—principally
emigration to cool-water refuges when such habitats are
available (Nielsen etal. 1994; Ebersole etal. 2001; Baird
and Krueger 2003). Additionally, juvenile steelhead are
sensitive to low DO concentration (< 5.0 mg L−1; Carter
2005) and have limited salinity tolerance (osmoregulatory
ability) prior to the parr-smolt transformation (Boughton
etal. 2017). Hence, the presence of warm saline water
at the bottom of the Scott Creek lagoon during the first
half (~ 80 days) of the study period reduced the amount
of suitable freshwater habitat for juvenile steelhead to
varying degrees. At its most extreme during midsummer
(e.g., 13 July–8 August, phase 2), strong vertical strati-
fication and heating likely restricted juvenile steelhead
to the top ~ 1.0 m of the water column and reduced the
volume of suitable lagoon habitat by approximately 40%
relative to unstratified conditions in autumn (after 8 Sep-
tember, phase 4; Fig.4). However, thermal conditions
were likewise periodically stressful in the upper water
Fig. 6 Estimated (a) abundance, (b) mass-specific growth rate
(MSGR), and (c) condition factor of juvenile steelhead in the Scott
Creek (CA, USA) estuary/lagoon during each monthly sample event
(July–November 2018). For panel (a), abundance point estimates
(diamonds) reflect the best-approximating POPAN model and are
shown with 95% confidence intervals. In panels (b) and (c), each box
denotes the 25th and 75th percentiles with the median value shown as
a horizontal line. The whiskers denote the 10th and 90th percentiles
and outliers appear as open circles. The mean value is represented by
a solid circle. Parenthetical numbers indicate sample sizes. Differ-
ent lowercase letters denote significant differences between sampling
events (ANOVA followed by Tukey’s HSD test)
Estuaries and Coasts
1 3
column during stratification (temperatures reaching 21.0
°C) with potential negative physiological and ecological
consequences (Smith 1990; Sullivan etal. 2000; Werner
etal. 2005) for lagoon-rearing individuals.
Steelhead Abundance andPerformance
Despite highly dynamic abiotic conditions and periods of
diminished habitat suitability, juvenile steelhead benefited
from lagoon rearing as evidenced by high abundance, posi-
tive growth, and robust condition factors. Our monthly
mark-recapture seining events revealed a temporal pattern
of steelhead recruitment to the lagoon during phases 1 and
2 (July and August), peak abundance during phases 2 and 3
(August and September), and then a decrease in abundance,
mean mass-specific growth rate, and mean condition factor
during phase 4 (October and November; Fig.6). Interest-
ingly, high juvenile steelhead abundance and growth rates
were observed during phase 2 despite strong stratification
gradients and a substantial reduction in favorable freshwater
rearing habitat—conditions that would be expected to limit
fish growth via increased per capita competition (Gregory
and Wood 1999; Keeley 2001) and bioenergetic stress
(Boughton etal. 2017).
Bioenergetics studies have shown that the net effect of
elevated water temperature on juvenile salmonid growth is
dependent upon food consumption rates (Boughton etal.
2007; Myrvold and Kennedy 2015; although see Viant
etal. 2003) and the variability in metabolic costs associated
with accessing habitats with abundant prey (Armstrong
etal. 2013; Brewitt etal. 2017). While we did not quantify
temporal changes in prey availability or consumption rates
by lagoon-rearing steelhead, community and food habit
investigations conducted in nearby Pescadero Creek estu-
ary/lagoon (San Mateo County, CA, USA) demonstrated
that both invertebrate density and richness (Robinson
1993) and juvenile steelhead stomach fullness (Martin
1995) were high in the lower lagoon following sandbar
Fig. 7 Histograms of directional
movement detected at the Scott
Creek (CA, USA) Lagoon PIT
tag antenna array (Lagoon
Array) relative to sunrise (left
panels) and sunset (right panels)
during each environmental
phase (panel rows). Blue bars
denote upstream movement and
orange bars denote downstream
movement (bin width = 0.25 h).
Dark background shading in
each panel denotes nighttime,
light shading indicates dawn or
dusk, and the unshaded region
represents daylight hours. Envi-
ronmental phase dates (2018)
were 20 June–12 July (phase 1),
13 July–8 August (phase 2), 9
August–7 September (phase 3),
and 8 September–20 November
(phase 4)
Estuaries and Coasts
1 3
formation and subsequently declined following stratifica-
tion of the water column. We propose that high rates of sec-
ondary production in the Scott Creek lagoon during sum-
mer (phases 1 and 2) may have helped mitigate the negative
effects of high water temperature on steelhead growth in
the short term, as recently demonstrated for juvenile coho
salmon rearing in a northern California river (Lusardi etal.
2020).
Oversummer Lagoon Fidelity
Spatiotemporal patterns of movement and habitat use by juve-
nile steelhead in coastal California watersheds are thought
to be driven by dynamic trade-offs between water quality,
resource availability, and predation risk (Satterthwaite etal.
2012). Based on previous research in the Scott Creek estuary/
lagoon (e.g., Bond etal. 2007; Hayes etal. 2011; Osterback
etal. 2018), we expected juvenile steelhead would attempt
to exploit abundant trophic resources in the lower lagoon
and retreat upstream to riverine habitat when abiotic condi-
tions became physiologically stressful. While we documented
substantial movement of PIT-tagged steelhead in and out of
the lower lagoon (relative to the Lagoon Array at rkm 0.3),
consistent with the findings of Osterback etal. (2018), the
vast majority of fish moving upstream during our study ulti-
mately took refuge in the middle or upper lagoon sample
reaches (Fig.S2). Contrary to previous reports, few fish were
detected moving beyond the lagoon-riverine Interface Array
(rkm 0.7) during our study until late in phase 4 immediately
prior to the onset of the first rainfall event (Fig.S2). Our
results highlight that interannual variability in hydrology and
lagoon physiochemistry may result in different patterns of
fish behavior and habitat use.
Notably, while our study was conducted during a “below
normal” water year in California (https:// cdec. water. ca.
gov/ repor tapp/ javar eports? name= WSIHI ST, last accessed
1 October 2021), the Scott Creek lagoon maintained con-
siderable volume during the dry season and lentic/lagoonal
conditions existed upstream to rkm 0.83. High sandbar eleva-
tion and adequate freshwater inflow substantially increased
the amount of potential salmonid rearing habitat relative to
previous low water years (e.g., water year 2015; Osterback
etal. 2018), especially in the upper lagoon sample reach—
an area characterized by comparatively high habitat com-
plexity (Fig.2) and available cover from avian predators
(Frechette etal. 2016). Importantly, water quality parameters
in the upper lagoon sample reach were often similar to con-
ditions in the adjacent mainstem riverine sample reach dur-
ing the study period, particularly at the head of the lagoon
where ~ 117 m of lentic habitat was unaffected by saltwater
intrusion (due to streambed elevation) or vertical stratifica-
tion (Figs.3 and 4). Maximum weekly maximum tempera-
ture in the upper lagoon sample reach was 18.3 °C, nearly
6 °C lower than MWMT values in the lower and middle
lagoon sample reaches (Fig.5), and well below the 20.5 °C
upper threshold recommended by Sullivan etal. (2000) to
protect juvenile steelhead rearing. Thus, a portion of the
upper lagoon potentially served as a critical cool-water ref-
uge (Quiñones and Mulligan 2005; Torgersen etal. 2012) and
provided opportunities for juvenile steelhead to behaviorally
thermoregulate when water temperatures in the lower lagoon
were unfavorable.
Few PIT-tagged juvenile steelhead were detected crossing
the lagoon-riverine interface (i.e., emigrating from the lagoon)
during our 154-day investigation until 15 November, where-
upon there was a salient spike in inland movement during
the final five days of the study (27 PIT-tagged emigrants in
phases 1–3 combined versus 389 during phase 4; Fig.S2b).
A retreat by lagoon-rearing steelhead to riverine habitat has
been reported elsewhere (Shapovalov and Taft 1954; Hayes
etal. 2011; Osterback etal. 2018) and attributed to lagoon
water quality degradation late in the dry season (Hayes etal.
2011). However, poor water quality was clearly not the driver
of emigration from the lagoon during our study, as there was
a return to favorable abiotic conditions throughout the study
segment during phase 4 (Figs.3 and 4j–o; Table2), well before
the spike in upstream movement occurred. Instead, upstream
movement appeared to be associated with a major shift in
weather (i.e., onset of winter precipitation), and more closely
aligns with the proposition by Huber and Carlson (2020) that
emigration may be prompted by cold water temperatures and
shorter photoperiod.
Diel Patterns ofFish Movement
Although juvenile steelhead were active in the lagoon
throughout the day, there were marked peaks in upstream
and downstream movement by PIT-tagged individuals con-
current with changing light conditions at dawn and dusk,
respectively (Fig.7). Juvenile salmonids are known to exhibit
highly plastic movement behavior, shifting activity between
diurnal, nocturnal, and crepuscular periods in response to for-
aging opportunities and perceived predation risk (Hyatt 1980;
Watson etal. 2019). In the Scott Creek lagoon, the benthic
and epibenthic invertebrates that support salmonid growth
and production (primarily amphipods, isopods, and mysids)
are disproportionately concentrated in the open water habitat
of the lower lagoon (J. Kiernan, unpublished data). How-
ever, cover is scarce in the lower lagoon (Fig.2a) and avian
predation on juvenile salmonids in this reach is known to be
high (Frechette etal. 2013; Osterback etal. 2014). Hence,
crepuscular movement by juvenile steelhead is presumably
a behavioral mechanism to increase feeding success while
minimizing mortality risk, a behavior exhibited by lake-
rearing juvenile sockeye salmon (Oncorhynchus nerka, Clark
and Levy 1988; Scheuerell and Schindler 2003). Moreover,
Estuaries and Coasts
1 3
since many lentic invertebrates exhibit diel vertical migra-
tions, ascending at dusk and descending at dawn (Haney
1988; Hays 2003), steelhead movement into the prey-rich
lower lagoon at dusk and subsequent retreat at dawn may help
synchronize steelhead foraging activities with spatiotemporal
patterns in prey availability. It should be noted that the Scott
Creek estuary/lagoon is a relatively simple ecosystem with
a depauperate fish assemblage in which O. mykiss are the
apex aquatic predator. In more ecologically and structurally
complex estuaries/lagoons, juvenile steelhead movement may
differ from the patterns we observed due to different preda-
tor–prey dynamics.
The Autumn Population Paradox
Following robust steelhead abundance, growth, and con-
dition factor in late summer (phase 3, September), all fish
performance metrics examined in this study decreased dur-
ing autumn (phase 4, October and November) when abiotic
conditions were purportedly more favorable, particularly
water temperature (Figs.3 and 6). Declining fish abundance
following lagoon cooling is an emerging pattern that has
been observed in previous studies of Scott Creek and peri-
odically in other central California lagoons (e.g., Pescadero
Creek; J. Jankovitz, personal communication). However, the
mechanism(s) behind such declines are not well understood
and likely vary between systems and among years. During
our study, the Interface Array provided evidence that very
few PIT-tagged fish emigrated from the lagoon, even when
water temperatures were at a maximum. Therefore, density-
dependent processes and (or) latent stress responses likely
explain in part the declines in steelhead abundance and per-
formance observed following destratification and cooling.
It is probable that strong vertical stratification during the
summer chiefly confined juvenile steelhead to the upper
water column, and that the corresponding reduction in
habitat increased both intraspecific competition (Gregory
and Wood 1999; Keeley 2001) and predation risk (Frechette
etal. 2013; Osterback etal. 2014). Alternatively, some indi-
viduals may have retreated to the middle or upper lagoon and
were not captured during subsequent mark-recapture sam-
pling events in October and November. The decreases in
juvenile steelhead growth rate and condition factor observed
for fish captured in the lower lagoon during phase 4 may
be latent consequences of sub-lethal thermal stress and (or)
hypoxia experienced during the warm summer months. Abi-
otic conditions similar to those documented during our study
have been shown to adversely affect juvenile O. mykiss meta-
bolic rate and growth conversion efficiency (Werner etal.
2005; Feldhaus etal. 2010). It is also plausible that trophic
processes constrained fish growth and condition, as negative
bottom-up food web effects have been reported following
destratification due to lingering DO impairment and reduced
primary and secondary productivity (Smith 1990; Robinson
1993). Future study is warranted to assess the generality of
autumn salmonid population declines in coastal lagoons and
the ecological mechanisms underlying this phenomenon.
Conclusions
Bar-built estuaries are the dominant estuary type in many
regions of the world (Perissinotto etal. 2010; McSweeney
etal. 2017). These habitats often provide unique ecologi-
cal services and are particularly important as nursery areas
for estuarine-resident and freshwater fish species. Unfor-
tunately, the productivity and resiliency of many estuaries
and lagoons have been reduced by intensive habitat altera-
tion and management (Heady etal. 2015), and these habi-
tats may be especially vulnerable to climate change (Huang
etal. 2020). In coastal California, there is growing evidence
that extreme climatic events are becoming increasingly
commonplace, altering the annual timing and duration of
lagoon formation (i.e., sandbar open/close dynamics) and
diminishing the quality of lagoon rearing habitat for imper-
iled juvenile salmonids (Osterback etal. 2018; Huber and
Carlson 2020). This study found that strong vertical strati-
fication (high salinity, high water temperature, and hypoxia
in the lower water column) during midsummer substantially
reduced the total volume of suitable lagoon rearing habitat
for juvenile steelhead. Oversummer persistence of steelhead
was facilitated by a mosaic of vertical and longitudinal phys-
icochemical conditions and the recurrent movement of fish
into refuge areas when abiotic and (or) ecological condi-
tions were unfavorable. Future work examining estuary/
lagoon trophic dynamics is needed to assess the degree to
which enhanced food resources may allow fish to occupy
and persist in habitats that are physiologically suboptimal,
particularly with respect to water temperature.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s12237- 021- 01019-9.
Acknowledgements We thank Livier Enciso, Angela Garelick, Lindsay
Hansen, Keith Hanson, Katie Kobayashi, Karlee Liddy, Nate Mantua,
Erick Sturm, and numerous Scott Creek interns for field support. We
are grateful to Eric Danner for the use of DTS equipment. Christopher
Kratt and Scott Tyler from the Center for Transformative Environmen-
tal Monitoring Programs provided helpful guidance on DTS deploy-
ment and materials. Arnold Ammann, David Boughton, E.J. Dick,
Nate Mantua, and Thomas Williams provided helpful feedback during
the writing and analysis of this manuscript. We are especially grate-
ful for the time, effort, and constructive comments provided by two
anonymous reviewers and the associate editor during the peer review
process. Lastly, we thank California Polytechnic State University’s
Swanton Pacific Ranch for land access and their continued support of
our research and monitoring programs.
Estuaries and Coasts
1 3
Funding Financial support was provided by the National Marine
Fisheries Service and California Department of Fish and Wildlife’s
Fisheries Restoration Grant Program. Reference to trade names or
manufacturers is for descriptive purposes only and does not imply US
Government endorsement of commercial products.
Data Availability Data are available from the authors upon reasonable
request.
Declarations
Conflict of Interest The authors declare no competing interests.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article's Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article's Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
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