Feyrer et al. 2015 Splittail Ecology

ARTICLE
Metapopulation structure of a semi-anadromous fish in a
dynamic environment
Frederick Feyrer, James Hobbs, Shawn Acuna, Brian Mahardja, Lenny Grimaldo, Melinda Baerwald,
Rachel C. Johnson, and Swee Teh
Abstract: The Sacramento splittail (Pogonichthys macrolepidotus) is a relatively large (400 mm), long-lived (8 years) demersal
cyprinid of conservation importance endemic to the San Francisco Estuary (SFE), California, USA. It exhibits a semi-anadromous
life cycle spending adult life in low to moderate salinity (0–12) habitat with migrations into upstream freshwater rivers and
floodplains for spawning during winter–spring. The species persists as two genetically distinguishable populations — one
dominant and one subordinate — separated by discrete spawning habitats that we suggest resemble an island–mainland
metapopulation structure. The populations overlap in distribution in the SFE, yet segregation is maintained with individuals
tending to aggregate or school with others of similar population heritage and natal origin. The populations are spatially
connected via dispersal of the dominant population into the subordinate population’s spawning habitat when climate patterns
produce freshwater outflow sufficient to form a bridge of suitable low salinity habitat across the upper SFE. Habitat affinities of
the two populations, hydrodynamic modeling studies, and historical outflow records together suggest such conditions occur in
approximately 1/3 of years overall with an irregular frequency. This dynamic pattern of spatial connectivity controlled by climate
variability may be an important driver of gene flow between the two populations.
Résumé : Pogonichthys macrolepidotus est un cyprinidé démersal longévif (8 ans) relativement grand (400 mm) d’importance pour
la conservation et endémique de l’estuaire de San Francisco (SFE; Californie, États-Unis). Il présente un cycle biologique semi-
anadrome, passant sa vie adulte dans des habitats de salinité faible a` modérée (0–12) avec des migrations dans des rivières d’eau
douce et des plaines alluviales situées plus en amont pour frayer a` l’hiver et au printemps. L’espèce persiste en deux populations
génétiquement distinctes, une dominante et l’autre subordonnée, séparées par des habitats de frai distincts qui ressemblent,
selon nous, a` une structure de métapopulation de type île-continent. Si les aires de répartition des populations se chevauchent
dans le SFE, une ségrégation est maintenue, les individus tendant a` se regrouper ou former des bancs avec d’autres individus
provenant de la même population et de la même origine natale. Les populations sont connectées dans l’espace par la dispersion
de la population dominante dans l’habitat de frai de la population subordonnée quand les aléas du climat produisent des débits
sortants d’eau douce assez importants pour former un pont d’habitats d’assez faible salinité de part en part du SFE supérieur. La
combinaison de l’affinité des habitats des deux populations, d’études de modélisation hydrodynamique et des registres histo-
riques des débits sortants indiquerait que de telles conditions se produisent environ une année sur trois, a` une fréquence
irrégulière. Ce motif dynamique de connectivité spatiale contrôlée par la variabilité du climat pourrait être une importante
cause de flux génétique entre les deux populations. [Traduit par la Rédaction]
Introduction
The extent to which discrete populations are connected by mi-
gration of individuals can substantially influence local and overall
population dynamics, as well as the evolution and risk of extinction
of a species. There is a great diversity of dispersal mechanisms
supporting population connectivity across taxonomic groups and
habitats. For example, freshwater invertebrates disperse actively as
adults or passively in other life stages by water or animal vectors
(Bilton et al. 2001), and marine populations are frequently connected
by dispersal of planktonic larvae transported by ocean currents
(Cowen and Sponaugle 2009). Understanding the mechanisms,
scales, and outcomes of population connectivity under present and
future climate conditions are crucial for guiding policy and manage-
ment decisions, especially for at-risk species.
Metapopulation theory serves as a useful framework for eval-
uating how spatial structures function to influence local and
overall population dynamics (Hanski and Simberloff 1997), es-
pecially in aquatic environments (Dunham and Rieman 1999;
Kritzer and Sale 2004). Yet, it is challenging to collect the necessary
Received 25 September 2014. Accepted 18 December 2014.
Paper handled by Associate Editor Aaron Fisk.
F. Feyrer.* Bay Delta Office, Bureau of Reclamation, 801 I Street, Sacramento, CA 95814, USA.
J. Hobbs. University of California, Davis, Department of Wildlife, Fish, and Conservation Biology, One Shields Avenue, Davis, CA 95616, USA.
S. Acuna. Metropolitan Water District of Southern California, 1121 L Street, Suite 900 Sacramento, CA 95814, USA.
B. Mahardja† and M. Baerwald. University of California, Davis, Department of Animal Science, One Shields Avenue, Davis, CA 95616, USA.
L. Grimaldo. ICF International, 620 Folsom Street, Suite 200, San Francisco, CA 94107, USA.
R.C. Johnson. Fisheries Ecology Division, Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA, 110 Shaffer Road, Santa Cruz,
CA 95060, USA; and University of California Davis, Department of Animal Science, One Shields Avenue, Davis, CA 95616, USA.
S. Teh. Aquatic Health Program, Department of Anatomy, Physiology and Cell Biology, School of Veterinary Medicine at the University of California
Davis, Davis, CA 95616, USA.
Corresponding author: Frederick Feyrer (e-mail: ffeyrer@usgs.gov).
*Present address: US Geological Survey, California Water Science Center, 6000 J Street, Placer Hall, Sacramento, CA 95819-6129, USA.
†Present address: Aquatic Ecology Section, California Department of Water Resources, 3500 Industrial Blvd., West Sacramento, CA 95691, USA.
Pagination not final (cite DOI) / Pagination provisoire (citer le DOI)
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Can. J. Fish. Aquat. Sci. 72: 1–13 (2015) dx.doi.org/10.1139/cjfas-2014-0433 Published at www.nrcresearchpress.com/cjfas on 8 January 2015.
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demographic data to elucidate that populations are in fact
functioning as metapopulations. The majority of empirical stud-
ies have been demonstrated in terrestrial systems, though some
studies on aquatic systems have emerged in recent years (Hanksi
and Gaggiotti 2004). Historically, a substantial impediment to
understanding and quantifying population connectivity and dis-
persal has been the inability to track the position, movements,
and origins of individuals, especially in aquatic environments.
A number of technologically advanced tools are now available
to researchers for studying population connectivity. These in-
clude actively observing animal movements by monitoring marked
or tagged individuals and passively reconstructing animal move-
ments through the use of physical, chemical, or molecular
markers.
In aquatic habitats, there has been substantial development of
the application of genetic and otolith microchemical markers as
tandem tools for understanding movements and dynamic spatial
structures in fish populations (Milton and Chenery 2001; Miller
et al. 2005; Barnett-Johnson 2007). Genetic markers are useful for
understanding population structure on an evolutionary time
scale as indicated by gene flow and also to address questions at a
contemporary scale by providing real-time estimates of individual
movements (Paetkau et al. 2004; Manel et al. 2005; Lowe and
Allendorf 2010). Otolith microchemical markers are useful at eco-
logical time scales because of how otolith elemental composition
reflects that of the water in which fish grow (Campana 1999). In
this study, we combine the application of genetic and otolith
markers in a complementary fashion to discern the temporal and
spatial scales of population connectivity (spatial overlap) of a semi-
anadromous migratory fish species of concern, the Sacramento split-
tail (Pogonichthys macrolepidotus; hereinafter referred to as splittail) in
the San Francisco Estuary (SFE), California, USA (Fig. 1).
The splittail and SFE are a model species and system to study the
role of connectivity on population dynamics, evolution, and risk
of extinction. The species is endemic to the SFE, which offers an
exceptional opportunity to exhaustively study the populations
that contribute to the status of the entire species. Splittail has
previously been listed as threatened under the US Endangered
Species Act and is presently listed as a Species of Concern by the
State of California (Sommer et al. 2007). There is an urgent need to
better understand splittail population connectivity and dynamics
because (i) it is the only extant member of its genus following the
extinction of the Clear Lake splittail (Pogonichthys ciscoides) (Moyle
2002), and (ii) the information is needed to guide species manage-
ment associated with contentious water development and habitat
restoration activities in the SFE (Sommer et al. 2007).
The splittail is a relatively large demersal cyprinid (maximum
fork length ϳ400 mm), which exemplifies the periodic strategist
life history type under the Winemiller and Rose (1992) triangular
life history model (Sommer et al. 1997; Moyle et al. 2004; Feyrer
et al. 2005). The species exhibits a semi-anadromous life cycle in
that it spends the majority of its adult life in low to moderate
salinity (0–12, all salinity values reported as practical salinity
units) habitats of the SFE and migrates into upstream freshwater
rivers and inundated floodplains for spawning during late winter
and spring. Some splittail may remain in the spawning grounds
year-round. This is especially true in the Napa and Petaluma rivers
because elevated salinity in these rivers can constrain suitable
habitat to the upstream regions where spawning also occurs. Pro-
duction is strongly tied to hydrology as wet winters trigger mass
upstream migrations and spawning on inundated floodplains
(Sommer et al. 1997; Moyle et al. 2004). Offspring move from natal
freshwater habitats downstream to the brackish SFE on the de-
scending limb of the seasonal hydrograph during late spring and
summer (Feyrer et al. 2006, 2007b). Juvenile splittail rear in the SFE
for approximately 2 years until reaching sexual maturity and then
begin spawning migrations (Daniels and Moyle 1983). Splittail are
iteroparous with a life-span of approximately 8 years (Daniels and
Moyle 1983).
There are two genetically distinguishable populations of split-
tail (Baerwald et al. 2006), one that spawns in western tributaries
(the Petaluma and Napa rivers; hereinafter referred to as the PN
Fig. 1. Map of the upper San Francisco Estuary showing the study area. The Sacramento–San Joaquin Delta is not shown and is located
immediately upstream (to the east) of the area depicted on the map. SR = Sacramento River; SJR = San Joaquin River.
2 Can. J. Fish. Aquat. Sci. Vol. 72, 2015
Published by NRC Research Press
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population) and another that spawns in eastern tributaries lo-
cated within California’s Central Valley (hereinafter referred to as
the CV population). Although the absolute sizes are uncertain,
genetic evidence suggests that the CV population is several orders
of magnitude larger than the PN population (Mahardja et al. 2014).
Although the very existence of two genetically distinguishable
populations suggests at least some degree of isolation, the dynam-
ics of how the two populations are connected is unknown and has
important implications for how the species as a whole is managed.
Given that the two populations (i) exhibit genetic differentiation,
(ii) are substantially different in size, and (iii) exhibit spatial isolation
with discrete spawning habitats, we hypothesized that there was
minimal connectivity and that the two populations represented sep-
arate evolutionarily significant units (ESUs) or demes (Waples 1991;
Waples and Gaggiotti 2006). The alternative hypothesis is that there
is nontrivial connectivity and the two groups function as some type
of metapopulation. The case for metapopulation dynamics in split-
tail is analogous to that of anadromous fishes such as salmonids
(Schtickzelle and Quinn 2007), though on a different spatial scale.
Both splittail and anadromous salmonids spawn in distinct breeding
habitats, for which they appear locally adapted (salmonids: e.g.,
Quinn 2004, Carlson and Seamons 2008; splittail: N. Fangue, De-
partment of Fish, Wildlife, and Conservation Biology, University
of California, Davis, unpublished data). For splittail, high salinity
regions of the SFE physically separate the two populations during
the breeding season and could be considered the functional equiv-
alent of the ocean for anadromous salmonids during the non-
breeding season where the populations co-occur (Baerwald et al.
2008).
At least three basic conditions are required to suggest the oc-
currence of metapopulation dynamics: (1) populations inhabit dis-
crete breeding habitat patches separated by unsuitable habitat,
(2) populations are connected through dispersal, and (3) popula-
tion dynamics and traits are not perfectly synchronous (Hanski
et al. 1995). Although extinction has historically been an impor-
tant aspect of metapopulation dynamics (Levins 1969; Hanski and
Simberloff 1997; Hanski 1999), we agree with others (Kritzer and
Sale 2004) that presence–absence data alone is sometimes too
coarse for modern metapopulation dynamic applications in fisheries
and other ecological considerations, especially in cases involving
the conservation of threatened and endangered species. The first
of the key metapopulation dynamic criteria is fulfilled in splittail,
as the saline region of SFE is not suitable breeding habitat and sepa-
rates the two populations during breeding. However, the extent to
which the populations are connected through the exchange of indi-
viduals and the level of demographic or trait independences remain
largely untested and represent the primary foci of our study.
In this study, we took an interdisciplinary approach using em-
pirical data collected from both the field and laboratory to answer
the question of whether the two splittail populations represent
distinct ESUs or function as metapopulations. These data were
used to quantify the extent of spatial overlap between the two
populations, characterize differences in demographic traits, and
assess the health and condition of splittail at multiple scales. To
examine spatial dynamics, we intensively sampled adult splittail
in the SFE when they reside on foraging grounds during the non-
breeding season and also in the PN population’s breeding habitat
and applied previously developed genetic (Baerwald et al. 2006)
and otolith microchemistry (Feyrer et al. 2007a) tools to identify
from which genetic population and natal regions individual split-
tail originated. We assessed demographic traits and health and
condition by examining a suite of size, growth, morphometric,
and nutritional indicators. We addressed three specific study
questions and integrate the results to address our hypothesis on
splittail population structure: (i) Are individuals from the two
populations found disproportionately in specific geographic for-
aging regions or habitats of the estuary? (ii) Do individuals within
aggregations or schools in their foraging grounds originate from
the same population or natal region? (iii) Do individuals within a
population or within a geographic region exhibit differences in
demographic or health metrics relative to others?
Study area
The SFE is located on the Pacific Coast of the United States in
central California (Fig. 1). It has an open water surface area of
approximately 1235 km2, a mean depth of 4.6 m, and a volume of
approximately 5.8 × 109 m3. From its relatively narrow connection
to the Pacific Ocean at the Golden Gate, the estuary opens up into
several relatively large embayments, including South Bay, Central
Bay, and San Pablo Bay. South Bay is generally considered to be a
marine lagoon environment, while the rest of the system is much
more affected by seasonal and annual variations in outflow from
the watershed. Within San Pablo Bay and upstream into Suisun
Bay, Grizzly Bay, and Honker Bay, the system typically exhibits a
range of conditions intermediate between marine and freshwater
environments. The system ultimately becomes dominantly a fresh-
water environment in the Sacramento–San Joaquin Delta, an expan-
sivemazeoftidalchannelsencapsulatingdryandinundatedtractsof
land, which is formed at the confluence of the Sacramento and
San Joaquin rivers, the two longest rivers in California.
Physical and biological properties of the SFE are controlled by
complex interactions of processes that operate at varying frequen-
cies and scales. Key primary external factors include climatic driv-
ers that manifest through conditions in the watershed and the
northeastern Pacific Ocean. The prevailing Mediterranean climate
is generally characterized by a warm and dry summer–fall period
and a cool and wet winter–spring period, which controls the
amount outflow entering the estuary from the watershed.
Methods
Field sampling
Field work was conducted in splittail foraging grounds in the
SFE during November and December in 2010 and 2011 under a
stratified random sampling design targeting full coverage of split-
tail estuarine distribution. The upper SFE from San Pablo Bay
upstream to the confluence of the Sacramento and San Joaquin
rivers was divided into six approximately equal area strata, and
random sampling sites within them were generated using Arc-
MAP GIS software (ESRI, Redlands, California, USA). During 2011,
random sampling sites were stratified equally between offshore
and littoral zones, whereas in 2010 there was no such stratifica-
tion between these two habitat zones. Random sampling was sup-
plemented with nonrandom targeted collections of splittail in the
SFE within the strata framework in an attempt to increase the
number of individual splittail available for assessing individual
health and fitness.
Targeted sampling of splittail in their spawning habitat within
the Petaluma and Napa rivers was also conducted to collect indi-
viduals for health and fitness, assess the overall spatial distribu-
tion of splittail within these two rivers, and to test the extent to
which adults originated from each population. In the Petaluma
and Napa rivers, sampling was initiated in downstream locations
in habitats considered too saline for splittail occupancy and pro-
gressed to the upstream-most accessible freshwater spawning
habitat, covering all representative offshore and littoral zones.
The relatively small size of the channels in the Petaluma River and
Napa River systems resulted in efficient sampling and accurate
characterization of the spatial distribution of splittail. A total of
178 random samples and 209 targeted collection samples were
completed.
Sampling was conducted with multimesh gill nets that mea-
sured 1.8 m in height × 45.7 m in length with five equal length
Feyrer et al. 3
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panels of 38, 51, 64, 76, and 89 mm mesh. Mesh sizes were selected
to effectively sample all age groups of adult splittail and were
chosen based upon the results of previous unpublished studies
with experimental gill nets (R. Baxter, California Department of
Fish and Wildlife, Stockton, California). We used the “gillnetfunc-
tions” package for R (https://www.stat.auckland.ac.nz/ϳmillar/
selectware/R/, accessed on 13 August 2013) to fit relative retention
curves to evaluate the selectivity of our gill nets (Millar and Holst
1997). Counts of splittail fork lengths (FL; grouped into 10 mm
increments) captured in each mesh were used in the analysis. A
log-linear model that assumed equal sampling effort for each
mesh was used to estimate the selectivity curves based on
662 individual splittail that were collected in 387 gill net sets. The
resulting selectivity curves (available upon request) indicated that
while individual mesh sizes were selective for particular size
ranges of splittail, together they effectively sampled splittail
ranging in size from approximately 150 to 400 mm FL, which
corresponds to ages 1–8. Splittail become sexually mature at
approximately 180 mm FL as they near age 2, and few records of
splittail >400 mm FL exist; thus, our collections generated a
good representation of the adult splittail population.
Because the splittail is a demersal fish, the gill nets featured a
heavy lead line and a floating top line to maintain position on the
bottom of the water column and to ensure they were stretched
vertically. The gill nets were stretched horizontally with the aid of
anchors attached to the ends of the lead line. The gill nets were set
during daylight hours for a duration targeting 60 min; set times
were based upon the effective collection of splittail in a previous
study (Nobriga et al. 2005). Relatively short 60 min set times were
required to ensure that collected splittail remain alive immedi-
ately prior to laboratory processing (described below) and to min-
imize the incidental catch of other state and federally listed
endangered fish species. In practice, under variable field condi-
tions, set time averaged 58 min and ranged from 25 to 127 min.
Catches were standardized for effort (set time) for data analyses as
described below.
Individual splittail collected in each set were carefully extracted
from the gill net and kept alive in large containers filled with
water taken at the site of collection. Gill net mesh size and splittail
FL were recorded for each individual collected. Individuals were
marked (unique fin clips) corresponding to the specific net set in
which they were collected and transported to the laboratory at the
end of the day with aeration and salt added to the water to mini-
mize stress. Travel time from the field to the laboratory was
approximately 60 min, and splittail were processed immediately
upon arrival.
Habitat characteristics recorded in the field included water
temperature (°C), salinity, turbidity (NTU), and chlorophyll con-
centration (␮g·L−1), all of which were measured for each sampling
event at the depth of the gill net. Secchi depth (cm) and total water
depth were also recorded. Offshore distance (km) of each sample
was obtained by plotting sample coordinates (latitude and longi-
tude) in Google Earth and using its ruler tool to estimate the
shortest direct distance to land.
Genetic population assignments
DNA was extracted from caudal fin tissue using the QIAGEN
DNEasy 96 kit (QIAGEN Inc.). Nineteen microsatellite markers were
used for the study: CypG3, CypG4, CypG23, CypG25, CypG28, CypG35,
CypG39, CypG40, CypG43, CypG45, CypG48, CypG52, CypG53, Pmac1,
Pmac4, Pmac19, Pmac24, Pmac25, and Pmac35 (Baerwald and May
2004; Mahardja et al. 2012). Methods for PCR and allele genotyping
followed Mahardja et al. (2014).
Genetic assignment of individuals to their respective popula-
tion was conducted using STRUCTURE 2.3.3 (Pritchard et al. 2000).
We selected q value of 0.8 as the threshold for distinguishing
between purebred individuals and potential hybrids or unas-
signed based on the efficiency and accuracy scores found in Vähä
and Primmer (2006). Age-0 splittail collected in Baerwald et al.
(2006) and Mahardja et al. (2014) were used as references for the
populations. Ten iterations of K = 2 were performed with all indi-
viduals and references included, no prior location information,
500 000 burn-in period, and 1 000 000 Markov chain Monte Carlo
repetitions under the assumption of admixture and correlated
allele frequencies. Replicate runs were averaged in CLUMPP 1.1.2
(Jakobsson and Rosenberg 2007) with the FullSearch algorithm.
Otolith microchemistry natal origin assignments
Strontium isotopic composition in otoliths (molar ratios of 87Sr/
86Sr) has previously been used to determine the natal origins of
individual splittail within the CV population (Feyrer et al. 2010).
Specifically, individuals born within the upper Sacramento River
region above the city of Sacramento can be differentiated from
those born downstream in the Yolo Bypass and other regions,
including the Delta and the San Joaquin River. For simplicity, we
refer to this differentiation as the upper Sacramento River versus
the Delta. Otolith 87Sr/86Sr values ≤ 0.706 indicate individuals
with natal origins in the upper Sacramento River, while higher
values indicate individuals with natal origins in the Delta at a
97% accuracy rate (Feyrer et al. 2010). Existing otolith chemistry
markers are unable to differentiate whether individuals in the PN
were born in the Petaluma or Napa river with any reasonable
degree of accuracy nor can it differentiate PN from individuals
born in the San Joaquin River in the Central Valley (Feyrer et al.
2010). Methods used for otolith preparation and chemistry analy-
ses followed Feyrer et al. (2010).
Demographic and health metrics
We used a suite of metrics to characterize key aspects of splittail
demographics and health: size structure (length of individuals),
mass at length, length at age, sex composition, Fulton’s condition
factor (K), hepatosomatic index (HSI), gonadosomatic index (GSI),
and muscle protein, lipid, and ash content.
Splittail age was obtained from interpreting information con-
tained within otolith microstructures. Thin sections of otolith
were digitally imaged using an American Optical (AO) dissec-
ting scope fitted with an ocular digital camera (AM Scope: http://
www.amscope.com) at 10× magnification. Annual age increments
were quantified and measured using Image-J (NIH Imaging: http://
rsb.info.nih.gov/ij/). Each otolith was aged by two readers. Otoliths
with discrepancies in annual age determination between the two
readers were read a third time by each reader. Otoliths that had
discrepancies between multiple age readings greater than 1 year
were discarded from the study.
We calculated K as 100 × (total body mass/standard length3), HSI
as 100 × (liver mass/total body mass), and GSI as 100 × (gonad
mass/total somatic mass). Muscle lipid, protein, and ash content
were obtained from splittail muscle samples that were frozen and
stored in a −80 °C freezer. All muscle samples were freeze-dried
and ground into a fine powder. The percent crude protein was
calculated by determining the nitrogen content of the muscle.
The ground muscle was weighed and combusted as detailed by
AOAC Method 990.03 (AOAC 2006a) using a TruSpec CN Analyzer,
which quantifies the amount of nitrogen in the muscle. The
amount of nitrogen was converted to protein by the standard
conversion factor for fish of 6.25 (AOAC 2006a). The percent crude
protein was reported as percentage of protein (converted from
nitrogen) in the dried sample. The percent crude lipid was calcu-
lated by determining the total lipid content of the muscle. The
ground muscle was weighed, and crude fat was extracted by the
Soxhlet extraction method as detailed by AOAC Method 2003.05
(AOAC 2006b). Lipids were extracted from the sample using the
solvent ethyl ether. The solvent was evaporated by heat and recov-
ered by condensation. The amount of crude lipid residue was
determined gravimetrically after drying. The percent crude fat
was reported as the percentage of crude fat residue in the dried
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sample. Crude percent ash was calculated by determining the
inorganic content of the muscle. The ground muscle was weighed
and combusted as detailed by AOAC Method 942.05 (AOAC 2006c)
using a muffle furnace at 550 °C for at least 3 h. The amount of ash
remaining was determined gravimetrically after drying. The per-
cent ash was reported as percentage of ash determined gravimet-
rically in the dried sample.
Data analyses
Study question (i): Are individuals from the two populations
found disproportionately in specific geographic foraging regions
or habitats of the estuary?
We used a combination of mapping spatial distributions and
generalized additive modeling of habitat associations to address
this study question using the random sampling data. Splittail spa-
tial distributions were mapped with ArcMAP GIS software (ESRI,
Redlands, California, USA) to determine if individuals from each
population were found disproportionately in specific geographic
regions of the estuary. Population-structured habitat associations
of splittail were developed using generalized additive models (GAMs)
implemented with the mgcv package in the R statistical program-
ming language (Wood 2006). GAMs are nonparametric extensions of
generalized linear models useful for describing nonlinear relation-
ships between variables. They are data-driven and do not presuppose
a particular functional relationship between variables; smoothers
characterize the empirical relationships between explanatory and
response variables. Response variables were counts of splittail from
each population in each sample standardized to 100 min of sampling
effort (gill net set time). We first constructed single term models with
the independent variables offshore distance, salinity, turbidity, and
depth because existing knowledge (Moyle et al. 2004), and explor-
atory data analyses indicated the potential importance of these hab-
itat variables. We excluded two measured habitat variables from
model construction, Secchi depth and chlorophyll concentration,
because they were both correlated to turbidity (Secchi depth, r =
−0.57, P < 0.001; chlorophyll, r = 0.37, P < 0.001), and temperature was
deemed unimportant because all sampling was conducted within a
single season and did not meaningfully vary spatially. Models were
fit using a Poisson distribution with cubic regression spline smooth-
ing functions. Gamma was set to 1.4 to help avoid the models from
over-fitting the data (Wood 2006). We chose habitat variables that
produced statistically significant single-term models to build full
multiterm models. In this case, habitat variables that produced sta-
tistically significant single-term models proved to also be statistically
significant in the multiterm models; thus, no habitat variables were
removed from the multiterm models in a backwards stepwise fash-
ion. Habitat associations of the two populations were compared by
assessing independent variables included in each final model and
visually inspecting the form of their relationships to the response
variable.
Study question (ii): Do individuals within aggregations or schools
in their foraging grounds originate from the same population or
natal region?
The extent to which mixing of populations or natal regions
occurred within individual aggregations or schools was deter-
mined by testing the null hypothesis that the fractional composi-
tion (relative abundance) of individuals from each population or
natal region in an individual sample (gill net set) was as expected
by chance. This hypothesis was tested for each aggregation or
school size observed in which there were at least two individuals.
We used a resampling procedure to establish empirical sampling
distributions by randomly resampling the available popula-
tions 10 000 times. Generating empirical sampling distribu-
tions allowed us to account for uneven population sizes, sample
size variability, and non-normal distributions in the observed
data. P values were calculated as the number of simulations for
which the statistic was greater than or equal to the observed
statistic divided by the total number of simulations, the statistic
in this case being the fractional composition (relative abundance)
of the numerically dominant population or natal region in a sam-
ple. We interpreted P values < 0.50 (which indicate that the sam-
pling statistic was >50% of the 10 000 simulations) as evidence that
the fractional composition of the dominant population or natal
region was greater than what was expected by chance. This anal-
ysis explicitly assumes that an individual gill net sample provides
a suitable representation of an individual aggregation or school of
splittail. The analysis of natal origins was limited to individuals
that were genetically assigned to the CV population because of the
otolith microchemistry assignment limitations described above.
Study question (iii): Do individuals within a population or within
a geographic region exhibit differences in demographic or health
metrics relative to others?
Size structure was compared by visual examination of length-
frequency plots across populations and at spatial scales corre-
sponding to three regions: the brackish nonbreeding feeding
grounds in the estuary, Petaluma River, and Napa River. Mass at
length was evaluated by examining variability in the slope of the
length–mass relationship across the same population and spatial
scales. The length–mass relationship was expressed as a linear
function: log(mass) = ␣ × log(length) + ␤. Variability in slopes was
inferred from comparing 95% confidence limits for ␣. Variability
in K, HSI, GSI, muscle protein, lipid, and ash was assessed sepa-
rately by sex across the same population and spatial scales using
analysis of covariance (ANCOVA). For these analyses we examined
data pooled across years from individuals collected in both the
random and targeted sampling.
Results
General results
The 178 random estuary samples collected (coincidentally)
178 individual splittail. Of this total, 116 (65%) were genetically
assigned to the CV population, 56 (31%) were assigned to the PN
population, and 6 (3%) were unassigned (Table 1). Natal origins
were determined using otolith 87Sr/86Sr for 105 of 116 individuals
genetically assigned to the CV population, the majority of which
(59%) originated in the delta (Table 2).
Overall, splittail were observed in 30 of the 178 (17%) random
samples, all of which occurred well east of San Pablo Bay and in
littoral habitat (Fig. 2). Overall mean (± standard deviation) CPUE
(number of individuals per 100 min of sampling effort) was 1.6 ±
5.5. Albeit with considerable variability, overall mean CPUE of the
CV population (1.1 ± 3.6) was approximately double that of the PN
population (0.5 ± 2.2). Within the CV population, the CPUE of
individuals with natal origins in the Delta (0.59 ± 1.9) was margin-
ally higher than that of individuals with natal origins in the upper
Sacramento River (0.39 ± 1.8). Mean CPUE solely for samples in
which splittail were present was 9.5 ± 10.3.
Within the targeted sampling conducted in the Petaluma and
Napa rivers, individual splittail were only observed in the upstream-
most reaches of these rivers in which sampling occurred (Fig. 2).
The nature of these samples being targeted limits us to relatively
simple interpretations of these particular catch data. The most
notable result was that splittail were only observed in relatively
confined upstream regions where salinity was ≤12.6; for perspec-
tive, salinity gradually increased downstream to >20 in San Pablo
Bay.
Study question (i): Are individuals from the two
populations found disproportionately in specific
geographic foraging regions or habitats of the estuary?
Individual splittail from the two populations overlapped in
spatial distribution within the estuary and therefore were not
exclusively found in specific geographic regions (Fig. 3; Table 1).
Feyrer et al. 5
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Individuals from the CV and PN populations were observed in
approximately the same relative proportions in the estuary’s
embayments in both years of study. Individuals from the CV pop-
ulation were not found in the Petaluma and Napa rivers in 2010, a
dry year, but were in 2011, a wet year (Table 1). The individuals in
the Petaluma and Napa rivers that were identified as originating
from the CV population had high Q values (all >0.80), suggesting
the origin of these individuals is strongly assigned using our ge-
netic approach.
The full multiterm GAMs explained 80% and 61% of the abun-
dance variation (deviance) in the CV and PN populations, respec-
tively. The CV GAM included all four available habitat variables:
offshore distance, salinity, turbidity, and depth as statistically signif-
icant predictors of splittail abundance (P < 0.001). The PN GAM was
similar except that offshore distance was not statistically significant
(P > 0.05) and was therefore not included in the model. Deviance
plots of partial responses showed that the two populations exhibited
similar responses to turbidity and depth but different responses to
salinity (Fig. 4). With regards to turbidity, the response of both pop-
ulations increased up to values of approximately 7–8 NTU and re-
mained essentially flat thereafter. The response of both populations
todepthdroppedsharplyatapproximately7–8m.Asmentioned,the
two populations had different responses to salinity. Abundance of
individuals from the CV population dropped when salinity reached
approximately 9–10, while for the PN population it dropped when
salinity reached approximately 15. The response to offshore distance
for the CV population resembled a steep linear negative relationship;
the response of the PN population was similar but, as mentioned, not
statistically significant.
Study question (ii): Do individuals within aggregations or
schools in their foraging grounds originate from the same
population or natal region?
For the analysis on populations, there were 24 instances in the
set of random estuary samples in which more than one individual
splittail was collected (Table 3). In 18 of the 24 samples (75%) the
fractional composition (relative abundance) of the dominant pop-
ulation was higher than what was expected by chance. Instances
of the fractional composition of the dominant population being
higher than expected by chance were insensitive to aggregation
size.
For the analysis on natal origins, there were 17 instances in the
set of random estuary samples in which more than one individual
splittail was collected (Table 4). In 11 of the 17 samples (65%) the
fractional composition (relative abundance) of the dominant na-
tal origin was higher than what was expected by chance. Instances
of the fractional composition of the dominant natal origin being
higher than expected by chance decreased as aggregation size
increased.
Study question (iii): Do individuals within a population or
within a geographic region exhibit differences in
demographic or health metrics relative to others?
Overall splittail size structure was generally consistent across
populations and varied similarly by sex within each population
(Fig. 5). Splittail mass at length expressed over all individuals
observed was described by the function: log(mass) = 3.20 ×
log(length) − 5.22 (P < 0.001, R2 = 98.9). Slopes of the length–mass
relationship (␣) varied from 2.94 to 3.32 across all possible combi-
nations of comparison; 95% confidence limits suggested consid-
erable overlap in the slopes of the length–mass relationship,
regardless of how the fish were grouped (Table 5).
Splittail ranged in age from 1 to 8 in our samples. Splittail from
both populations and sexes exhibited indeterminate growth in
length with age (Fig. 6). ANCOVA results indicated that splittail
length varied significantly as a function of age (P < 0.001) and sex
(P = 0.001), with females longer than males at all ages, but we did
not find evidence for variation in length at age across populations
(P = 0.45). Regionally, however, there was a complete absence of
individuals older than age 3 in the Petaluma River.
There was notable variability in K, HSI, GSI, muscle protein, lipid,
and ash (Fig. 7). ANCOVA results indicated statistically significant
population differences in male GSI (PN > CV; P = 0.015) and spatial
differences in female lipid (estuary > Napa; P = 0.006), female ash
(Napa > estuary; P = 0.021), male K (estuary > Napa; P = 0.031), female
GSI (estuary and Napa > Petaluma, P = 0.006), male GSI (Petaluma and
Napa > estuary, P < 0.001), female HSI (Petaluma > Napa > estuary;
P < 0.001), and male HSI (Petaluma > Napa > estuary; P < 0.001).
Discussion
Splittail population structure best matches our alternative
hypothesis of a metapopulation, consisting of a dominant and a
subordinate population that we suggest resembles the mainland-
island structure in metapopulation ecology (Harrison et al. 1988).
All three key conditions for metapopulation dynamics appear to
be fulfilled in splittail: (1) populations inhabit discrete breeding
habitat patches separated by saline habitat unsuitable for spawn-
ing, (2) populations are spatially connected through dispersal of
the dominant population into the subordinate population’s spawn-
ing grounds, and (3) population dynamics and traits are not perfectly
synchronous. No data presently exist, genetic or otherwise, to sug-
gest finer-scale population structure may exist in splittail, i.e., each
Table 1. Counts (and rounded percentages in parentheses) of genetically derived population
assignments of individual splittail observed in 2010 and 2011 in the estuary, Petaluma River,
and Napa River.
2010 2011
Region CV PN Unassigned CV PN Unassigned
Estuary 49 (67%) 21 (29%) 3 (4%) 67 (64%) 35 (33%) 3 (3%)
Petaluma River 0 5 (100%) 0 1 (3%) 37 (95%) 1 (3%)
Napa River 0 36 (97%) 1 (3%) 7 (14%) 39 (76%) 5 (10%)
Note: CV = Central Valley population; PN = Petaluma–Napa population.
Table 2. Counts (and rounded percentages in parentheses) of otolith
chemistry derived natal areas of individual splittail observed in 2010
and 2011 in the estuary, Petaluma River, and Napa River.
2010 2011
Region
Sacramento
River Delta
Sacramento
River Delta
Estuary 16 (43%) 21 (57%) 27 (40%) 41 (60%)
Petaluma River — — — 1 (100%)
Napa River — — 5 (63%) 3 (38%)
Note: The data pertain to individual splittail genetically assigned to the Cen-
tral Valley population. Sacramento River refers to individuals born in upper
Sacramento River upstream of Yolo Bypass, while Delta refers to individuals born in
the Yolo Bypass and other downstream regions, including the Sacramento–
San Joaquin Delta and the San Joaquin River. Dashes indicate that no Central
Valley splittail were observed in the Petaluma and Napa rivers in 2010.
Forpersonaluseonly.

CV or PN population could potentially be composed of sets of popu-
lations. For example, there is no evidence that splittail within each
population home to speciﬁc natal sites for spawning. Thus, until new
data emerge to demonstrate otherwise, we feel it is appropriate at
this time to use the term population to refer to the two groups.
The CV population is numerically larger and occupies a larger
habitat area of likely better quality than the PN population, lend-
ing credence to the mainland–island type of structure. Similar to
the mainland–island metapopulation model where dispersal
from the larger mainland dominates the direction of connectivity
to the smaller island population preventing extinction, here the
CV population likely plays the mainland role to the smaller PN
population as evidenced by CV origin ﬁsh occurring in the Peta-
luma and Napa rivers in the wet year (2011). Mahardja et al. (2014)
estimated the effective size of the CV population to be orders of
magnitude greater than the PN population. Based on geography
alone, surface area of the occupied habitat in the Petaluma and
Napa rivers is just a fraction of that in the Central Valley; the
relative proportion of available habitat skews even further when
water of suitable salinity is considered. Our observation that the
health of individual splittail in terms of lipid stores and condition
was less favorable in the Petaluma and Napa rivers (Fig. 7) provides
indirect evidence of meaningful differences in habitat quality.
Salinity, which is generally elevated in the Petaluma and Napa
rivers, can also be viewed as a driver of habitat quality. Splittail
inhabit elevated salinity sooner in life in the Petaluma and Napa
rivers compared with the Central Valley (Feyrer et al. 2010), and
emerging data suggest that splittail populations exhibit differen-
tial physiological performance traits in response to elevated
Fig. 2. Spatial distribution of splittail catch per unit effort (CPUE; number of individuals per 100 min of sampling effort). The size of the CPUE
data points is scaled according to the legend. Data points within the Petaluma and Napa rivers, including zero catches indicated by +, are
targeted nonrandom sampling locations. All other data points outside of the Napa and Petaluma rivers, including zero catches indicated by ×,
are random sampling locations within the nonbreeding rearing grounds.
Fig. 3. Spatial distribution of splittail population assignments in random samples located within the estuary nonbreeding rearing grounds.
Pie chart sizes are scaled to the number of individuals in a sample (range = 1–34), and jitter was introduced to the sample locations to avoid
pie chart superimposition.
Feyrer et al. 7
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Fig. 4. Plots showing habitat associations of individual splittail from each population. Plots are fitted smooths and 95% confidence intervals for partial responses from generalized
additive models. Units on the y axis are centered on zero, and the number in the label is the estimated degrees of freedom of the smooth. Tick marks along the x axis represent
observations.
Paginationnotfinal(citeDOI)/Paginationprovisoire(citerleDOI)
8Can.J.Fish.Aquat.Sci.Vol.72,2015
PublishedbyNRCResearchPress
Forpersonaluseonly.

salinity (N. Fangue, Department of Fish, Wildlife, and Conserva-
tion Biology, University of California, Davis, unpublished data).
Splittail populations appear spatially connected by dispersal,
yet segregation is maintained at multiple scales. In the SFE, indi-
vidual splittail tend to aggregate or school with others of similar
population heritage and natal origin. Generally similar behavior
has been observed at various scales in other migratory fishes (e.g.,
McKinnel et al. 1997; Fraser et al. 2005; Barnett-Johnson 2007;
Weitkamp 2010). Associating with kin in splittail could potentially
function to maintain population structure by exerting pressure
on mate selection. It is unclear, however, if individual splittail
obtain fitness benefits from such a pattern of segregation. For an
analogous situation, genetic diversity benefits were shown to out-
weigh the benefits of kin association in a study of Atlantic salmon
(Salmo salar) (Griffiths and Armstrong 2001). With the exception of
male GSI, none of the health and condition metrics we examined
were statistically different between populations; the only appar-
ent differences in health and condition were those mentioned
above that varied according to geographic location. The range of
possibilities driving the observed level of segregation range from
simple chance encounter with no resulting benefits to complex
social behaviors that could result in individual or group benefits
not addressed in our study. Kin identification is not unprecedented,
as it has been demonstrated in other migratory fish species (Brown
and Brown 1992). The two splittail populations further maintained
segregation at the habitat scale, with the PN population generally
occupying a higher salinity than the CV population, which reduces
the likelihood that chance encounter is the driving force of segrega-
tion at the individual aggregation or school level.
The concept of synchrony requires special consideration and
further study in the case of splittail because of the existence of
dominant and subordinate populations. Further, some aspects of
splittail life history traits suggest variable levels of synchrony,
which may be unusual in classical metapopulation theory. Syn-
chrony is typically assessed with time series abundance data,
which, as with many ecological systems, is not available for the
two splittail populations. Thus, we examined traits that could be
indicators of demographic processes; results show that there were
no meaningful differences in the traits we measured. This sup-
ports the idea that while there are two genetic populations, there
is sufficient dispersal to maintain these traits in the two popula-
tions. The two splittail populations are clearly not synchronous
with respect to absolute size. However, the relative abundances of
age-0 production of the two populations may fluctuate synchro-
nously in response to environmental forcing, a condition known
as the Moran effect (Moran 1953). This seems reasonable because
age-0 production of the CV population is strongly tied to hy-
drology (Sommer et al. 1997; Moyle et al. 2004), and available data
indicate that interannual fluctuations in outflow are similar in
the Petaluma–Napa and Central Valley basins, albeit with consid-
erable differences in absolute flow volume. Increased synchrony
is generally thought to correspond with increased extinction risk
to the metapopulation (Earn et al. 2000). Modeling studies have
suggested that the CV population is resilient to environmental
conditions and has a low risk of extinction (Moyle et al. 2004).
However, similar efforts should be made to model extinction risks
for the PN population, which may be particularly vulnerable to
localized catastrophic events.
Table 3. Splittail population composition in random samples col-
lected in the nonbreeding feeding grounds in the San Francisco estu-
ary (see Fig. 3 for locations).
Size of
aggregation
or school
Numerically
dominant
population
Fractional composition
of numerically dominant
population P value
2 PN 1.00 0.12*
2 PN 1.00 0.12*
2 PN 1.00 0.12*
2 CV 1.00 0.43*
2 CV 1.00 0.43*
2 CV 1.00 0.43*
2 CV 1.00 0.43*
3 CV 0.67 0.29*
3 CV 1.00 0.29*
4 Even 0.50 0.89
4 CV 0.75 0.59
4 CV 0.75 0.59
4 CV 0.75 0.59
4 CV 1.00 0.19*
5 CV 0.80 0.45*
5 CV 0.80 0.45*
8 CV 0.88 0.04*
8 CV 1.00 0.04*
10 CV 0.60 0.78
10 CV 1.00 0.01*
11 CV 0.64 0.46*
16 PN 0.56 0.14*
19 PN 0.58 0.29*
34 CV 0.62 0.66
Note: Data are provided for each sample in which at least two individuals
were observed. Data shown include the size of the aggregation or school ob-
served (total number of individuals observed), the numerically dominant popu-
lation (PN = Petaluma–Napa, CV = Central Valley), the fractional composition
(relative abundance expressed as a fraction) of the numerically dominant pop-
ulation in the aggregation or school, and P values associated with a test of the
null hypothesis that the fractional composition was as expected by chance (see
Methods for details). Asterisks indicate samples in which there were more indi-
viduals of the numerically dominant population observed than what was ex-
pected by chance.
Table 4. Splittail natal regions in random samples collected in the
nonbreeding feeding grounds in the San Francisco estuary (see Fig. 3
for locations).
Size of
aggregation
or school
Dominant
natal
region
Fractional composition of
dominant natal region in
sample P value
2 Delta 1.00 0.33*
2 Delta 1.00 0.33*
2 Delta 1.00 0.33*
3 Delta 1.00 0.19*
3 Delta 1.00 0.19*
3 Delta 1.00 0.19*
3 Delta 0.67 0.19*
4 Delta 0.75 0.19*
4 Sacramento 0.75 0.19*
4 Even 0.50 0.80
7 Delta 0.57 0.68
7 Delta 0.57 0.68
8 Even 0.50 0.79
10 Delta 0.60 0.59
21 Delta 0.52 0.78
Note: Data are provided for each sample in which at least two individuals
were observed and for individuals that had been genetically assigned to the
Central Valley splittail population. Data shown include the size of the aggrega-
tion or school observed (total number of individuals observed), the numerically
dominant natal region, the fractional composition (relative abundance ex-
pressed as a fraction) of the numerically dominant natal region in the aggrega-
tion or school, and P values associated with a test of the null hypothesis that the
fractional composition was as expected by chance (see Methods for details).
Asterisks indicate samples in which there were more individuals of the numer-
ically dominant natal region observed than what was expected by chance.
Feyrer et al. 9
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A poignant example of how population structure and dynamics
play into extinction risks occurred in September 2010 when a spill
released up to 2300 L of oil in the upper Petaluma River. This spill
was concurrent with our study and may explain the observed
absence of large adult females in this area during our study. If
indeed these populations function as viable a metapopulation,
then CV population adults could supplement or colonize the Peta-
luma River (as could PN population individuals from the Napa
River). Such a process would resemble a mainland–island metapo-
pulation structure, where persistence of the PN population
depends on the existence of the more extinction-resistant CV pop-
ulation. However, given the genetic differences in the CV and PN
populations, it is unclear whether the fitness of CV populations
spawning in the Petaluma River could in fact result in meaningful
contribution to the PN population. This example illustrates that
in addition to dispersal–migration and connectivity, metapopula-
tion models need to consider fitness differences in migrants, re-
gionally correlated environmental forcing, and local processes
and events to assess extinction risks.
Climate-induced dynamic habitat fragmentation could be a key
driver of splittail metapopulation structure. Our results suggest
that the two populations are connected spatially via dispersal
of the dominant population into the subordinate population’s
spawning habitat when climate patterns produce enough rainfall
and associated freshwater outflow to form a bridge of suitable low
salinity habitat across the upper SFE. Specifically, no CV-origin
fish were observed in the Petaluma and Napa rivers in the dry
year, 2010. This is in contrast with the wetter year of 2011 where
CV individuals were found to disperse into the PN. Woods et al.
(2010) similarly used otolith chemistry and genetic tools to deter-
mine that catchment dispersal of Australian smelt (Retropinna
semoni) was mediated by changes in hydrological connectivity. Habi-
tat affinities of the two splittail populations suggest that a sustained
salinity of approximately ≤12 is needed to form such a bridge. Hydro-
dynamic modeling studies (Gross et al. 2009) and historic outflow
records together suggest such conditions occur in approximately 1/3
of years overall with an irregular frequency. The degree to which this
dynamic pattern of spatial connectivity drives gene flow remains an
important question for understanding splittail population dynam-
ics. One possibility is that this pattern of spatial connectivity
provides sufficient gene flow to maintain the existence of the two
genetically similar populations. Another possibility is that the
dynamic spatial connectivity between the two populations is suf-
ficiently low that genetic drift and (or) selection will eventually
drive the two populations to become separate species once ade-
quate evolutionary time has passed. In either case, the trajectory
of splittail evolution and population structure is likely to be
shaped by future climate conditions. It is likely that a drier future
constraining spatial connectivity could further diverge the two
populations, while a wetter future increasing spatial connectivity
could homogenize the two populations. The same general con-
cept holds for management actions that would produce such
conditions by altering the present physical configuration or
hydrodynamics of the estuary, an important consideration given
the strong interest in large-scale habitat restoration in the SFE. The
availability of detailed future climate change scenarios downscaled
for the SFE (Cloern et al. 2011) enable the trajectory of splittail
Fig. 5. Length-frequency plots showing the size structure of each splittail population separately for males and females.
Table 5. Slopes (␣) and 95% confidence limits
obtained from linear regressions of splittail log-
(mass) at log(length) aggregated across species
(all individuals), population (PN = Petaluma–
Napa population, CV = Central Valley popula-
tion), and spatial (estuary feeding grounds, Napa
River, Petaluma River) scales.
Group
Slope±95%
confidence limit
All individuals 3.20±0.04
CV population female 3.32±0.10
CV population male 3.15±0.09
PN population female 3.14±0.07
PN population male 3.13±0.10
Estuary female 3.24±0.10
Estuary male 3.13±0.08
Napa River female 3.23±0.13
Napa River male 3.17±0.17
Petaluma River female 2.94±0.26
Petaluma River male 3.14±0.01
Forpersonaluseonly.

evolution and population structure to be modeled. Such an effort
would require additional research to quantify gene flow between
the two populations. The ability to model climate-driven habitat
fragmentation and associated evolutionary and population ecol-
ogy trajectories of an aquatic species provides an unprecedented
opportunity for the testing and application of theoretical and
applied ecological science, as well as natural resource manage-
ment.
Acknowledgements
We thank M. Gingras, R. Soto, E. Santos, N. Sakata, N. van Ark,
C. Grant, D. Obegi, M. Nobriga, D. Riordon, A. Chandos, K. Gehrts,
B. Coalter, B. Harrell, A. Mueller-Solger, M. Young, A. Bibian, L. Conrad,
B. Schreier, R. Baxter, E. van Nieuwenhuyse, S. Waller, T. Foin,
N. Fangue, B. May, K. Reece, M. MacWilliams, L. Brown, R. Baxter,
T. Sommer, and many others for assistance. S. Teh, S. Acuna, and
J. Hobbs were funded by an agreement (No. R10AC20095) between
the US Bureau of Reclamation and the University of California–
Davis awarded to S. Teh. B. Mahardja and M. Baerwald were sup-
ported by Delta Science Program Grant No. 2037.
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