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PHYSICAL AND CHEMICAL CORRELATES OF SACRAMENTO COUNTY
VERNAL POOL CRUSTACEANS
by
Phillip A. Poirier
A Thesis Submitted to the
Faculty of the Office of Research and Graduate Studies
In Partial Fulfillment of the
Requirements for the Degree of
MASTERS OF SCIENCE
College of the Pacific
Biological Sciences
University of the Pacific
Stockton, California
2012
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PHYSICAL AND CHEMICAL CORRELATES OF SACRAMENTO COUNTY
VERNAL POOL CRUSTACEANS
by
Phillip A. Poirier
APPROVED BY:
Thesis Advisor: _______________________________________
Stacy Luthy, Ph.D.
Committee Member: _______________________________________
Mark Brunell, Ph.D.
Committee Member: _______________________________________
Steven Slater, MS
Department Chair: _______________________________________
Craig Vierra, Ph.D.
Interim Dean of
Graduate Studies: _______________________________________
Bhaskara R. Jasti, Ph.D.
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ACKNOWLEDGEMENTS
I would simply like to take this time to thank those that helped me during this study. Of
course thanks to my thesis committee Stacy Luthy, Steve Slater, and Mark Brunell. I
appreciate greatly all your help, guidance, and most of all your patience. Big thanks to
Carol Witham and Jaymee Marty, who helped me get started and gave me great ideas and
advice. To Janet Reid and Christopher Rogers, I thank you for your taxonomic advice to
someone who didn’t quite know what he was getting into. I must of course thank
University of the Pacific and the Biology Department for giving me the opportunity and
financial help. Finally I must thank all my friends who helped me get through it all, the
list of course is too long, but if you’ve ever vented with me, distracted me from work, or
just stopped by to chat you know who you are.
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Physical and Chemical Correlated of Sacramento County Vernal Pool Crustaceans
Abstract
by Phillip A. Poirier
University of the Pacific
2012
Vernal pools are temporary aquatic habitats that can be home to dozens of
invertebrate species. Unfortunately, over 90 percent of California vernal pool habitat has
been destroyed. To better understand the remaining habitat, this study focused on the
species community structure of the pools, determined similarity among sites, and the pool
characteristics important to survival of these organisms. Vernal pools at four distinct
sites in the Sacramento Valley during winter 2012 were sampled for crustaceans and
water characteristics every 2 weeks for 14 weeks. Twenty-two species of crustaceans
were identified, 13 of which are possibly new species. In this dry, late rainfall year, fairy
shrimp and copepods were the first species to emerge in large numbers. Ostracods,
Cladocera and clam shrimp experienced large populations later in the season.
Temperature showed strong correlations with most species and likely affected growth
rates and emergence; conductivity, depth, and surface area were also positively correlated
with several species abundance. Understanding the emergence and distribution of these
crustaceans is necessary to protection of remaining habitat.
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TABLE OF CONTENTS
LIST OF TABLES .............................................................................................................. 7
LIST OF FIGURES ............................................................................................................ 8
CHAPTER
1. Introduction ..................................................................................................... 10
2. Methods........................................................................................................... 17
Sites ........................................................................................................... 17
Rainfall ...................................................................................................... 24
Environmental Conditions ........................................................................ 25
Sampling ................................................................................................... 26
Identification and Emergence Pattern ....................................................... 27
Statistical Analysis .................................................................................... 28
3. Results ............................................................................................................. 31
Rainfall Patterns and Pool Inundation ...................................................... 31
Environmental Conditions ........................................................................ 34
2012 Species Composition ........................................................................ 37
2012 Emergence Pattern ........................................................................... 39
2012 Species Richness .............................................................................. 43
Distance Between Sites - Cluster Analysis ............................................... 46
Species abundance with physical and chemical variables – Canonical
Correspondence Analysis.......................................................................... 48
4. Discussion ....................................................................................................... 54
Rainfall Pattern and Pool Inundation ........................................................ 54
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Vernal Pool Temperatures ........................................................................ 55
Seasonal Species Composition ................................................................. 57
Seasonal Emergence Pattern ..................................................................... 58
Seasonal Species Richness ........................................................................ 63
Community Similarity .............................................................................. 65
Environmental Correlates ......................................................................... 67
5. Conclusions ..................................................................................................... 72
REFERENCES ................................................................................................................. 73
APPENDIX ....................................................................................................................... 79
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LIST OF TABLES
Table Page
1. Rainfall information for November 18th through April 30th of the 2011 and 2012
vernal pool seasons. .............................................................................................. 32
2. The total number of hydrated pools and pools with hatched residents for each
survey.. .................................................................................................................. 32
3. Taxonomic identification of the 22 crustacean species from 2012.. ...................... 38
4. Species richness of inundated pools over the 2012 season.. .................................. 45
Supplemental Table Page
1. Species catch per unit effort (count/m3) for surveys 1-4.. ..................................... 79
2a. Species catch per unit effort for Survey 5 on 3/30/2012. ...................................... 80
2b. Species catch per unit effort for Survey 5 on 3/30/2012.. .................................... 81
3a. Species catch per unit effort for survey 6 on 4/14/2012. ...................................... 82
3b. Species catch per unit effort for survey 6 on 4/14/2012.. ..................................... 83
4. Species catch per unit effort for survey 7 on 4/30/2012.. ...................................... 84
5. Species catch per unit effort for copepod species counts for the 2011 survey ...... 85
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LIST OF FIGURES
Figure Page
1. Aerial map of the four sites and surrounding area of Sacramento, CA.. ............... 17
2. Werre Preserve site map with pool numbers.. ....................................................... 19
3. Kiefer Landfill Wetlands Preserve site map with pool numbers.. ......................... 21
4. Mather Fields site map with pool numbers.. .......................................................... 23
5. Montelena site map with pool numbers.. ............................................................... 24
6. Cumulative rainfall for the 2011 and 2012 rain seasons and long-term averages for
dry and wet years.. .................................................................................................. 31
7. Rainfall events for the 2011 and 2012 seasons.. .................................................... 33
8. Box plots for measured variables across the entire 2012 season.. ......................... 35
9. Box plots for conductivity across the entire 2012 season.. .................................... 35
10. Water and air temperature for typical deep water pool (Kiefer 13B) for 24 hour
period from March 18, 2012 to March 19, 2012. ................................................ 37
11. The relative abundances of four crustacean groups for each 2012 survey. ......... 39
12. Species presence across the 14 week long 2012 survey.. .................................... 41
13. Seasonal abundance of crustacean groups in KF204.. ......................................... 43
14. Hierarchical cluster analysis dendrogram of presence-absence data.. ................. 47
15. Species biplots resulting from a Canonical Correspondence Analysis for surveys
5, 6, and 7.. .......................................................................................................... 51
16. Sample biplots resulting from a Canonical Correspondence Analysis for surveys
5, 6, and 7.. .......................................................................................................... 52
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17. CCA and output from combined data from surveys 5-7. ..................................... 53
Supplemental Figure Page
1. Draftsman plot for depth, conductivity, and surface area for survey 5 on
3/30/2012.. .............................................................................................................. 86
2. Normal probability graphs for depth, conductivity, and surface area for survey 5
on 3/30/2012.. ......................................................................................................... 87
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Chapter 1: Introduction
Vernal pools may be temporary in nature, but are invaluable to the lives of
freshwater invertebrates, amphibians, migrating birds, and annual plants (McKinney &
Paton, 2009). These oases are formed by seasonal rains collecting above an impervious
layer of soil. Partway through the rainy season the water collects enough to breach the
soil surface and form temporary ponds, which give life to a diverse wetland habitat of
annual plants (King et al., 1996). Flying insects are attracted by the flowering plants and
lush aquatic habitat, which are followed soon after by birds using it as a convenient stop.
The water triggers the hatching of dormant cysts of freshwater invertebrates and
phytoplankton, as well as subterranean amphibians looking to reproduce in a safe, moist
environment. By early spring a dry prairie has been transformed into a vibrant field
teeming with life. Spring’s end marks the end of the rain and end of the line for those
that rely on the water. The plants and other pool occupants shrivel, leaving a dry prairie
where life once thrived; however, seeds, cysts, or eggs are deposited to insure that come
winter rain next year, their ecological legacy is not lost, but repeated.
Scattered throughout the world, with the exception of Antarctica, are the rich and
diverse ecosystems known as ephemeral, or temporary, ponds. When these pools persist
in the spring time, as is common for Mediterranean climates, they are called vernal pools
(Bauder, 2005). Typically they are found in complexes with pools close in proximity to
each other. Individual complexes can be kilometers apart from each other and often
differ greatly in soil chemistry (Gonzalez et al., 1996; Simovich, 2005). California has a
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wide range of vernal pool habitat distributed from Northern California to Southern
California. Along this broad range of pools is a spectrum of varying soil types; Northern
pools arecomposed of either transmontane soils or volcanic mudflow while Southern
California and Central Valley pools are primarily hardpan or claypan (King et al., 1996).
Unfortunately this habitat is also valued for its agricultural and urban development
potential.
It is estimated that loss of vernal pool habitat ranges from 90-97% in California.
Vernal pools at one time covered one-third of the central valley, mostly along the
perimeter of the foothills and down the middle of the valley (Holland, 1978; Stone,
1990). As the Sacramento-San Joaquin Delta was channelized, farms built on top of the
rich soil, and urban areas expanded, the destruction rate of vernal pools increased. Two
laws, though not specifically designed for vernal pool conservation, would become useful
in the protection of ephemeral habitat: The Clean Water Act (CWA) and Federal
Endangered Species Act (ESA). The former law controls the quality of our watersheds
and the latter protects habitats with endangered species. But, neither of these laws
actually prevents temporary ponds from being destroyed. Mitigation efforts, which are
either the creation of artificial pools or the purchase of a conservation easement on other
pools, are in place to protect the habitats, but there is little evidence that artificial habitat
can actually support the diversity of natural pools (King et al., 1996). It is important that
the limited remaining habitat be studied and understood for proper management and
protection.
Despite the large loss of habitat and numerous endangered plants and animals,
most vernal pools that remain are almost completely untouched by scientific study.
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Floral communities are often the focus of research due to the ease of collection and
speciation (Simovich, 2005). Communities like the California Native Plant Society and
Master Gardeners have spent a great deal of time both protecting the habitat and insuring
the survival of endemic plants. Faunal communities on the other hand, which include a
number of invertebrate and vertebrate groups, are largely ignored; the permits and
training required to handle endangered species dissuades many researchers from making
an effort despite the vast amounts of potential research (Simovich, 2005).
Estimates based on vernal pool surveys are that about 50% of extant vernal pool
crustaceans are undescribed (Simovich, 2005), and habitat loss models estimate that 30%
of all California pool crustacean species have gone extinct before being discovered (King
et al., 1996). Despite these losses, surveys still reveal an incredibly rich habitat;
researchers can identify as many as 27 different species of crustaceans from one pool
(King et al., 1996). When you combine the fact that pools in different locations or of
different soil types can significantly differ in their species richness and composition
(King et al., 1996), there is great potential for the discovery of new species and
elucidating the life history and ecology of living species. Even communities within a
complex of pools can be vastly different if the physical pool characteristics vary enough.
Rare species are limited to few pools by these same characteristics and are in special need
of conservation (King et al., 1996). Several types of crustaceans appear only in the early
parts of the season when water is abundant and temperatures are cool; their life history
limits them to a defined set of conditions. In a 5 year study in San Diego coastal mesa
vernal pools, there were 4 crustacean species that were found at only one pool during
specific times of the year (Ripley & Simovich, 2008); this same pattern is also seen in
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vernal pool plant communities (Holland, 1987). So of the remaining vernal pool habitat
in California, it is important to sample a wide variety of pool types over an entire season
to capture rare organisms.
Thanks in no small part to private cattle ranches and the federal government, a
significant number of vernal pool sites have been saved from development in the
Sacramento Valley. Lands belonging to ranchers and the United States Air Force have
for years been private, but recent conservation easements have opened the land to the
public and to science. The Sacramento Valley Conservancy owns easements for
numerous sites in the Sacramento Valley, three of which are included in this study:
Kiefer Landfill Wetlands Preserve, Werre Preserve, and Montelena Preserve. These
preserves were historically sampled every 1-3 years for the presence of vernal pool fairy
shrimp (Branchinecta lynchi), tadpole shrimp (Lepidurus packardi), and California tiger
salamander (Ambystoma californiense) for continued conservation, but that is the extent
of any research for most sites. Given the vast differences in species composition among
vernal pools, it is important to increase sampling effort in these areas. Also to predict
suitable habitat for all the discovered organisms, the pools themselves need to be studied.
Several factors have been shown to affect the hatching and survival of vernal pool
zooplankton. The most universally accepted predictor of both hatch and survival is
precipitation; pools of course cannot even form without adequate rainfall. But, volume
alone is not responsible for the success of a season. Clustered rainfall events play an
equally important role, as this can affect how long a pool will remain hydrated over a
season. Organisms that take longer to develop are limited by their life history, so they
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cannot survive short ponding durations brought on by limited clustered rainfall events
(Bauder, 2005).
Most of the first ephemeral pond studies concerning the hatching mechanisms of
organisms were qualitative natural history observations. Bishop (1976) observed that one
particular species of the order Conchostraca (clam shrimp) in Australia, Limnadia
stanleyana, would only hatch soon after the filling of pools. The presence of new cohorts
throughout the season was not observed. Coopey (1946) noted that hatching of several
Oregon species of the class Branchiopoda (cladocera, fairy shrimp, and clam shrimp)
was triggered by the mere presence of water in the frozen seasonal pools during the
spring thaw. Barclay (1966) and Bishop (1976) have both noted the significance of day
length as a factor at controlling early hatch in several species. But these non-pool
variables could just be directly affecting the water chemistry of the pool and in and of
themselves are not responsible for the hatching of some species over others. Ecologists
quickly moved away from these qualitative observations and attempted to show
quantitative correlations with physical variables like pH, conductivity, dissolved oxygen,
and temperature (Barclay, 1966).
Water quality affects the hatching, survival, and development of vernal pool
organisms; however, it is unclear whether these characteristics play a role independently,
or together form a complex suite of variables controlling species survival (Lanway,
1974). It is argued that of all water quality variables, temperature plays the largest role in
predicting the hatching and survival of temporary pool organisms (Mattox & Velardo,
1950; Prophet, 1963; Barclay, 1966; Horne, 1967 & 1971; Brown & Carpelan, 1971). In
a series of studies by Horne (1967, 1971) he found the disappearance of branchiopods
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greater than 17 degrees Celsius (C), followed by the reemergence when temperatures
cooled. Yet there are a number of results that suggest temperature may not be a single
controlling factor. In the same study, Horne noted that while temperature appeared
related to survival and hatching, salinity showed a strong correlation with initial hatching.
Brown and Carpelan (1971) observed that a desert species or order Anostraca (fairy
shrimp), Bachnchinecta mackini, hatched in the presence of low salinity and high
dissolved oxygen. As salinity increased and oxygen decreased, the emergence of new
cohorts ceased. The authors noted that a study on non-desert pools resulted in a similar
conclusion, but with temperature and oxygen rather than salinity and oxygen. Moore
(1959) observed a similar pattern with temperature and oxygen concentration in
Louisiana; two species of fairy shrimp would seldom be found together due to different
requirements for egg hatching and survival. Brewer (1964) theorized that a negative
correlation of egg hatching and dissolved oxygen in some species seen in his study has to
do with the anaerobic conditions created by bacteria, which signals favorable food
conditions for hatching crustaceans. Recent studies have continued to explain species
survival, richness, and hatching by physical and environmental variables (Ebert & Balko,
1987; Gonzalez et al., 1996; Ripley & Simovich, 2008), but it is still entirely likely that
vernal pool populations have each adapted to their own region and their own set of
variables.
The purpose of this thesis work at the University of the Pacific was to describe the
crustacean community of several vernal pools sites in Sacramento County, California. In
addition, associated environmental (physical and chemical) variables of the habitat were
documented. Because these communities differ drastically between sites and pools, the
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three Sacramento Valley Conservancy sites listed above as well as a fourth site located
near Mather Fields Air Force Base were sampled for species richness and abundance. To
control for the occurrence of rare species, pools of varying sizes and depths were sampled
for an entire season. To determine how rainfall affected these complexes, the rainfall and
inundation days of the pools were recorded. Also, because physical characteristics of the
pools are significant to the hatching and survival of these organisms, several pool
characteristics were measured. Specifically, the following questions were addressed:
1) What is the seasonal composition of vernal pool crustacean species at the four sites?
2) Does distance (kilometers) between sites play a role in crustacean community
similarity?
3) Does crustacean species abundance show correlations with physical and chemical
variables?
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Chapter 2: Methods
Sites
Sampling was conducted on Sacramento Valley, California pools (n=24) among
four sites (Figure 1) that have not had extensive community study. The four sampling
sites were: Werre Preserve (5 pools), Kiefer Landfill Wetland Preserve (7 pools), Mather
Fields (5 pools), and Montelena Preserve (7 pools).
Figure 1: Aerial map of the four sites and surrounding area of Sacramento, CA.
Werre Preserve is the farthest south and is 12-14 kilometers (Google Earth ruler tool)
away from the other three sites. Mather Fields, Kiefer, and Montelena Preserve are 4-7
kilometers away from each other.
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Werre Preserve. Werre Preserve is a 17 hectare (42 acres) site located just east
of Dierks Road and Excelsior Road in Sacramento, California. Separated into North and
South by property boundaries, only the South part of the complex is currently monitored
as a condition of the conservation easement held by the Sacramento Valley Conservancy.
Werre Preserve is a private cattle ranch with a large amount of pools on site (60 are
numbered by Carol Witham, consultant with Sacramento Valley Conservancy); the
majority of these pools are relatively shallow and small. For this study, “small” was in
reference to pools less than 500 square meters (m2) and “shallow” was in reference to
pools no deeper than 26 centimeters (cm). These small ponds overflow into each other
with abundant rainfall, forming a large connected complex of pools and rivulets spanning
the entirety of the site, which was observed in 2011. Stratified random sampling based
on pool connectivity was used to identify pools 10, 26, 43, 55, and 59/60 for study; this
resulted in a range of depths and sizes across the length of the preserve (Figure 2).
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Figure 2: Werre Preserve site map with pool numbers. The map and pool numbers
were provided by Carol Witham and Sacramento Valley Conservancy.
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Kiefer Landfill Wetlands Preserve. Kiefer Preserve is directly adjacent to
Kiefer Landfill, the primary municipal solid waste disposal for Sacramento County. It
runs parallel to Grant Line Road, which is a highly trafficked road that runs from
Highway 99 Northeast through Sloughouse, California. The land is owned by the City of
Sacramento, with a conservation easement held by the Sacramento Valley Conservancy.
At upwards of 140 hectares, it is the largest of the four sites, and also contains some of
the largest and deepest pools. The total number of pools is somewhat unclear, as several
nearby pools can become one larger pool with adequate rainfall, but a consistent subset of
32 relatively large and deep pools are monitored by Carol Witham. While it is possible
for many of the pools to overflow into each other, rolling hills throughout the site in most
cases makes this an unlikely scenario. The more likely scenario is that there are subsets
of pools that can overflow into each other, but not into other subsets within Kiefer,
though neither scenario has been observed. This could possibly limit the amount species
dispersal at this site. At this site stratified random sampling was used to select pools 2,
13B, 49, 56, 84, 123, and 204 for monitoring. This selection provided a set of pools with
varying degrees of depths and surface areas among different clusters (Figure 3).
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Figure 3: Kiefer Landfill Wetlands Preserve site map with pool numbers. The map
and pool numbers were provided by Carol Witham and Sacramento Valley Conservancy.
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Mather Fields. Mather Fields Air Force Base (MFAFB) is located in Rancho
Cordova, California just south of Highway 50. The land began as a pilot training site in
1918. The base was active until it was decommissioned in 1993 and its land was divided
among several agencies. It was reopened as Sacramento Mather Airport by Sacramento
County, and other land was used for urban development and regional parks. Because of
this, pools in this site are often separated by roads or housing developments. Many pools
are located on MFAFB; however, not all of them are accessible due to the division of
land. Pools were monitored based on what was easily accessible: Dog’s pool, Carol’s
Pool, UCD1, UCD2, and UCD3 (Figure 4).
Montelena Preserve. Montelena Preserve is a small site (upwards of 20
hectares) located within a housing development in Rancho Cordova, California, directly
east of Sunrise Elementary School. It sits on a fenced off terrace with the surrounding
land used as flood control. Random sampling was used to select pools 3, 6, 10, 19, 21,
25, and 26 for monitoring. With the exception of a very large pond (number 26), the
vernal pools of Montelena Preserve do not vary as much in surface area and depth
compared to the other sites (Figure 5).
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Figure 4: Mather Fields site map with pool numbers. The map and pool numbers
were created using Google Earth.
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Figure 5: Montelena site map with pool numbers. The map and pool numbers were
provided by Carol Witham and Sacramento Valley Conservancy.
Rainfall
Rainfall information was collected online from the California Department of
Water Resources’ (DWR) California Data Exchange Center (CDEC: accessed at
http://www.water.ca.gov/floodmgmt/hafoo/hb/cdecs/). Station ID PRC (Prairie City),
located 4 northeast of Kiefer Landfill, was used to query daily rainfall amounts from
October through April for all available years, 1996 through 2012. Once adequate rainfall
had inundated the pools to at least 2.5 cm, sampling began.
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Environmental Conditions
Prior to each crustacean sampling event, physical measurements of the pools were
taken. Standing at the edge of the pool, a YSI85 (YSI Inc., Yellow Springs, OH) was
used to take dissolved oxygen measurements in percent saturation at the center and edge
of the pools. An Oakton CON10 (Oakton Instruments, Vernon Hills, IL) was used in the
same manner to measure conductivity in microsiemens per cm (µS/cm), temperature in
degrees Celsius (C), and pH. All measurements were taken the second the display read
“Ready” as readings naturally drifted up and down. Each instrument was calibrated
according to its user manual the morning of sampling. The YSI was calibrated with the
calibration chamber attached to the instrument, and the pH probe was calibrated with 4
and 7 pH calibration solutions.
Thermochron iButton temperature probes were placed at the center of several
pools to record temperatures. Water temperature was recorded every twelve minutes for
two weeks by staking the probes to the pools bottom in a rubber balloon, to protect from
water damage, at the center of each pool. In a few deeper pools, probes were placed at
the center and also towards the edge to determine if deeper pools have temperature
differentials. Corresponding air temperatures were collected using another iButton
temperature probe protected by a box staked to the ground. The iButtons were calibrated
in ice water and room temperature water. Air temperature for the years 2010-2012 was
obtained from CDEC Station PRC.
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Sampling
Crustacean sampling was conducted during the winters of 2011 and 2012. The
2011 season consisted of a single sample date on February 12th
, 2011 of 24 pools (n=25
samples). By that date the pools were inundated completely for several months. The
2012 season included 24 pools surveyed every 2 weeks (February 3rd until April 27th
), in
the 2012 season (Supplemental table 1-4). Pools were sampled as soon as they began
consistently holding water (n=104 samples), as cysts often do not reanimate until after
being exposed to water for a certain time or until a specified number of wet-dry cycles.
Sites were monitored for inundation starting December 2011, but the first survey did not
occur until February 3rd
, 2012. Each of the 24 pools was visited every two weeks after
that.
In 2012, a 10x13 cm rectangular mouth net with a 250 µm mesh was swept 2.4 m
at the edge and center of each pool, and sweeps were separated into plastic tubs for
observation and removal of endangered species. Volume of water swept was calculated
by multiplying length of the sweep by the area of the net. In shallow water, the
calculated area of the net was smaller due to the shallow depth. After the sweep, the
same transect was walked to record average depth using 2 cm tick marks on the rubber
boots worn by the sampler. Each sorting tub was then transferred into a 250 milliliter
(ml) wide mouth jar, topped off with 10% buffered formalin for preservation, and labeled
inside and outside with waterproof tags for record keeping.
The 2011 survey differed slightly in procedure from 2012 surveys, as it was under
Carol Witham’s permit. Her equipment, personnel, and sampling procedures were used
and a total of five sweeps were combined into one sample. Conductivity, surface area,
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and edge and center measurements were not taken. Because of this the 2011 species data
is not quantitatively accurate and will not be used in statistical analyses, but will be used
to make comments on species presence.
The size of pools was determined to calculate surface area. A rough outline of
each pool was drawn on the data sheet during each sampling event. The direction and
location of each sweep were sketched as well as any large obstructions, objects,
vegetation or other features of interest. Smaller pools were measured with a 30 m
measuring tape at their widest and longest points for calculations of surface area. Larger
pools had estimated lengths and widths, and area was later calculated based off of aerial
imagery. Surface area and volume were estimated using either an ellipsoidal or circular
surface area equation depending on the overall shape of the pool.
Identification and Emergence Pattern
Sample processing began with addition of a small amount of rose bengal dye to
the preserved samples; this made identification and sorting easier. The samples were
rinsed with tap water in a 200 µm sieve before being emptied into a large plastic sorting
tray. All copepods, cladocera, fairy shrimp, and ostracods were separated out for
identification, leaving all remaining eggs, insect larvae, terrestrial insects, and
amphibians as “other zooplankton”, which were represerved. Crustaceans were identified
using dissecting and compound microscopes to the lowest possible taxonomic level using
Dodson et al. (2010) and Smith and Delorme (2010). In the event that a crustacean was
deemed to be an undescribed species, it was given a letter designation (ex: Cladocera A,
Copepod A, etc.). Janet Reid (Smithsonian Institution) and Christopher Rogers
28
(University of Kansas) assisted in the authentication of copepods and branchiopods.
Ostracods and cyclopoid copepods were not identified to species level, but were observed
for an estimated number of species. Non-crustacean organisms were counted but not
speciated or included in the analysis. These include beetle and insect larvae, terrestrial
and aquatic insects, leeches, large rotifers, volvox, snails, water mites, and tadpoles. All
specimens were saved for possible future work.
Surveys were processed chronologically to detect emergence patterns of
crustacean species. Emergence for this study is defined as the reanimation from cysts
after inundation from rainwater.
Statistical Analysis
Statistical analyses were limited to the 2012 sample data. All recorded
measurements and observations were entered into a Microsoft Access (2002) database for
organization and backup. An Access query extracted environmental and species data and
was imported into Microsoft Excel (2002) to check for outliers and errors. Box-plots
(Figure 8) and scatterplots (Supplemental Figure 1) were used to check for outliers. An
overall shape of the data distribution was visualized with a frequency histogram of each
environmental variable. Any unusual data point appearing several bins away from the
rest of the data points was double checked. Box-plots of each environmental variable
were constructed to discover any abnormal deviations in data points. Draftsman plots
were plotted for each included variable to look for correlations among variables.
Normality was checked through use of normal probability plots, and were natural log
transformed if not conforming to a normal distribution (r-squared values <0.5).
29
Cluster Analysis. Physical distance and species information from all seven
surveys conducted in 2012 was incorporated into a presence-absence table of vernal pools
species. The data were imported into R version 2.14.1 (www.r-project.org) for
hierarchical cluster analysis using the Vegan package. The presence-absence table was
analyzed for dissimilarity using the built in vegdist( ) function using a Jaccard measure of
dissimilarity and then plotted using the hclust( ) function with complete linkage. The
dendrogram was then used to compare similarity among near and far pools.
A Mantel test of significance was performed using latitude and longitude
information from each pool. The table of latitudes and longitudes was analyzed using the
vegdist( ) function using a Euclidean measure of dissimilarity. This as well as the species
presence-absence dissimilarity matrix was used with the mantel.rtest( ) function with
9999 Monte Carlo permutations. The null hypothesis for this test was that there is no
association between distance between pools and crustacean species similarity among
pools.
Canonical Correspondence Analysis (CCA). For the CCA, six variables
(conductivity, inundation days, pool depth, pool surface area, edge sample, and center
sample) were tested as potential indicators of species abundance. These variables from
each pool, along with associated species data, were analyzed using a CCA with the
analysis program CANOCO (ver. 4.5). There were four analyses performed, one for each
of surveys 5, 6 and 7, and a combined dataset of surveys 5-7 to observe the effects of
changing temperature. Inundation was excluded from the combined analysis and
30
replaced with average daily temperature, because over a long period depth and inundation
days become highly correlated. Surveys 1-4 did not have enough data points for analysis.
The data sets were checked for outliers, normality, and unimodality. The mean,
variance, standard deviation, skewness, and kurtosis were calculated for the raw
environmental data.
Catch per unit effort (CPUE) was calculated for each species by taking the
counted catch from each sweep and dividing by the volume of water swept. The volume
of water was calculated by multiplying the surface area of the net by the length of the
sweep. If the depth of the pool was shallower than the height of the net, a new net
surface area was calculated for that sweep to accommodate the shallow depth.
CANOCO 4.5 was used to run a CCA on the species and normalized
environmental data. Environmental data from each survey were normalized by
subtracting the mean and dividing by the standard deviation of each variable. Each
analysis of Surveys 5-7 of 2012 consisted of two files: species and environmental data.
Hill’s scaling was used to characterize the short gradients, and this scaling was focused
on Inter-species distances. Variables were not forward selected, and the significance was
calculated using 100 unrestricted Monte Carlo permutations. Biplots using principal
component axes 1 and 2 were produced for species-environment and sample-environment
interactions.
31
Chapter 3: Results
Rainfall Patterns and Pool Inundation
The two years of vernal pool monitoring had substantial differences in total
rainfall (Figure 6). For most of the 2012 season, the total rainfall was greater than or
equal to 1/3 that of the previous year for any date. The frequency and duration of storm
events also varied between the two years.
0
5
10
15
20
25
30
35
10/1 10/31 11/30 12/30 1/29 2/28 3/30 4/29To
tal
Pre
cip
itat
ion
(in
ches
)
Date
2012
2011
Wet Year Average
Dry Year Average
Figure 6: Cumulative rainfall for the 2011 and 2012 rain seasons and long-term
averages for dry and wet years. Data was collected from the California Data Exchange
Center (CDEC) station PRC for hourly rainfall from October through April 1996-2012.
Wet year averages were determined from years with greater than 18 inches of rain and
dry year averages were determined from years with fewer than 18 inches of rain. Station
PRC is located 4 miles northeast of Kiefer Landfill Wetlands Preserve.
The 2011 season was characterized by abundant early rain, unusual for the region,
in late November (Figure 7). By late December, most if not all vernal pools were at
capacity. In 2011, 27.13 inches of rain fell, far exceeding the annual average of 17.93
32
inches. The clustered rainfall events and cool temperatures kept the pools at their capacity
for an extended period of time, resulting in very dense algal mats and large densities of
zooplankton. A large number of rainy days were also recorded, with 59 days out of the
150 day long study; the area on average receives 59 days of rain in an entire year. This
gives an average rainfall per rainy day of 0.4 inches, and an even spread of rainfall events
resulted in 4 days of sun between each rainy day (Table 1). There was a brief period of
drought during the last three weeks of January, but this did little to the water level of the
pools. It was not until mid to late April; once the rain slowed; the temperature increased;
and plants began to grow; that the pools started to dry. This rainfall pattern is indicative
of the strong La Niña year that characterized the 2011 season. In contrast, the 2012
season was a much weaker La Nina year.
Table 1 : Rainfall information for
November 18th through April 30th of
the 2011 and 2012 vernal pool seasons.
Nov 18 was the first significant rainfall
of both years, and Apr 30th was the last
survey for both years. Information
obtained from CDEC station PRC
2011 2012
Cummulative Rainfall
(in.)27.17 16.96
# of rainy days 59 33
Average rainfall per
rainy day (in.)0.4 0.4
Average # days
between each rainy day4 10
Table 2 : The total number of
hydrated pools and pools with hatched
residents for each survey. Each of the
24 pools that held water during a survey
was sampled, but a pool was considered
empty if both the edge and center
samples were devoid of aquatic life.
Survey Date# of Pools
With Residents
# of Inundated
Pools2/3/2012 1 12/17/2012 4 43/2/2012 1 13/16/2012 1 63/30/2012 17 194/14/2012 16 164/27/2012 15 15
33
0.00
0.50
1.00
1.50
11/7 11/27 12/17 1/6 1/26 2/15 3/7 3/27 4/16
Pre
cipit
atio
n (
inch
es)
Date
Rainfall Pattern for 2011 Season
0.00
0.50
1.00
1.50
11/7 11/27 12/17 1/6 1/26 2/15 3/6 3/26 4/15
Pre
cip
itat
ion
(in
ches
)
Date
Rainfall Pattern for 2012 Season
Figure 7 : Rainfall events for the 2011 and 2012 seasons. The dates of occurrence as
well as rainfall amount for each single event are shown. Data was collected from CDEC
station PRC for daily rainfall. Station is located 4 miles northeast of Kiefer Landfill
Wetlands Preserve. Dotted lines indicate sampling dates.
The 2012 vernal pool season was in many aspects the complete opposite of the
2011 season in that rain events were few and far between, rather than common and
regular (Figure 7). In 2012, there were 33 days of rain during the 150 day long survey,
which resulted in a 16.96 inches of cumulative rainfall. Early November rain was hardly
enough to saturate the soil, and any effect it had was nullified by the almost two months
of drought that followed. The first significant rain was late January; despite being the
largest single rainfall event of the two seasons, it was barely enough to saturate the soil
34
and pond a few pools (Table 2). Despite the differences in number of rainy days, and the
clustered pattern of rainfall resulting in a 10 day gap between rain events, the average
rainfall per rain day was equivalent to the previous year 0.4 inches per rain day. All but
one pool at all sites quickly dried out due to the clustered rainfall, and did not rehydrate
until March. KF204 was inundated during the first survey and remained until the end of
the study. It
was not until the end of March that the rest of the pools were hydrated and successfully
hatched residents. The limited and dispersed rain was enough to keep the pools filled,
though the decrease in total volume was noticeable with each successive survey.
Environmental Conditions
Dissolved oxygen, pH, conductivity, and temperature were recorded from all
pools during the 2012 season (Figure 8). The pH of pools ranged from 6 to 7.2, with a
median at 6.9; dissolved oxygen ranged from 78% to 118% with a median 98%;
conductivity ranged from 60 to 350 µS/cm (median = 75), and temperature ranged from 8
to 24 °C (median = 12). Conductivity was the only variable that differed greatly
between sites (Figure 9).
35
6.0
6.2
6.4
6.6
6.8
7.0
7.2
7.4
pH
pH
Sca
le
0
20
40
60
80
100
120
140
Dissolved Oxygen
% S
atu
rati
on
050
100150200250300350400
Conductivity
Mic
rosi
emen
s
05
10152025303540
TemperatureD
egre
es C
elsi
us
Figure 8: Box plots for measured variables across the entire 2012 season.
Measurements were taken at the center of pools before each sampling. The box plots
show the median, 25th and 75th percentiles, minimum and maximum measurements from
all pools across all surveys.
0
50
100
150
200
250
300
350
WR
0
50
100
150
200
250
300
350
MF
0
50
100
150
200
250
300
350
MT0
50
100
150
200
250
300
350
KF
Mic
rosi
emen
s
Figure 9: Box plots for conductivity across the entire 2012 season. Measurements
were taken at the center of pools before each sampling. The box plots show the median,
25th and 75th percentiles, minimum and maximum measurements from all pools across
all surveys.
36
Conductivity was highest Werre Preserve. Early in the season the recorded
conductivities at Werre Preserve were roughly the same as the other three sites, but each
subsequent survey recorded higher conductivity readings at Werre Preserve while other
sites changed little. Mather Fields and Montelena Preserve also experienced higher
conductivity measurements in some pools, but only during the last survey of the season.
Temperature data for several pools using i-button temperature was unusable due
to erroneous recordings, loss of information and failure to record data. But, there were
several days of continuous recording in a number of pools that were used to describe
some general aspects of vernal pools.
Temperature probes measuring air, edge water, and deep water for KF13B were
deployed for 24 hour periods to monitor differences in edge and water temperatures
(Figure 10). For most shallow pools and edge water of deep pools, the temperature
closely matched the air temperature, with a slight lag time in water and air temperature.
This same general pattern was seen in deeper parts of pools as well but with less
correlation to air temperature and a greater lag time. For most of daylight, the deep water
was about 5 degrees Celsius cooler than the air and edge water temperature. Close to
sunset, when the water was shaded, the deeper water held on to heat longer and would
actually be warmer than the edge and air temperatures until the water equilibrated.
37
0
5
10
15
20
25
4:00 8:00 12:00 16:00 20:00 0:00 4:00
Tem
per
ature
(C
) Deep
Center
Shallow
Edge
Air
Figure 10: Water and air temperature for typical deep water pool (Kiefer 13B) for
24 hour period from March 18, 2012 to March 19, 2012. I-button temperature probes
were placed at the center of the pool (76 cm deep at time of placement), edge of the pool
(10 cm deep at time of placement) and on the rim of the pool. Vertical black lines
indicate sunrise and sunset.
2012 Species Composition
There were 22 species of crustaceans identified during the 2012 season
comprising 7 orders (Table 3): 2 Anostraca, 4 Copepoda, 12 Cladocera, 1 Laevicaudata, 1
Notostraca, 1 Ostracoda, and 1 Spinicaudata. It should be noted that cyclopoids
(Copepoda:Cyclopoida) and ostracods were not speciated due to lack of information or
difficulty in identification, though there are an estimated 3 species of cyclopoids and 6-8
species of ostracods. Several of these species have never been documented in this area of
California.
38
Table 3 : Taxonomic identification of the 22 crustacean species from 2012. Species
name is the result of identification to the lowest possible taxonomic level, and study
name indicates the name it was given for data analysis and data entry. Also listed is
whether or not the indicated species is possibly undescribed and warrants further research
and if these sites represent a new location they were discovered in. 1 Cyclopoids and ostracods were not speciated but a likely number of species was
estimated based on observation during sorting. 2 Endangered and threatened species were caught but returned to the pools and not
included in the analysis.
Order Species Name Study NamePossibly
Undescribed
New
Locality
Anostraca (2)
Branchinecta lynchi N/A2
Linderialla occidentalis L.Occ
Copepoda (6)
Hesperodiaptomus caducus H.Cad x
Hesperodiaptomus eiseni H.Eise x
Leptodiaptomus tyrrelli L.tyrr x
Cyclopoida spp .(31) Cyclopoid x x
Cladocera(12)
Alona sp. CladG x x
Ceriodaphnia sp. CladK x x
Chydoridae sp . CladL x x
Chydorus sp. CladH x x
Daphnia mendotae CladC x x
Macrothricidae sp. Dumo x x
Karualona sp. CladI x x
Moina micrura Moina x
Pleuroxus sp. CladF x x
Scapholebris sp. CladE x x
Simocephalus sp. Simo x x
Sididae sp . CladJ x x
Laevicaudata(1)
Lynceus brachyurus L.Brac
Notostraca(1)
Lepidurus packardi N/A2
Ostracoda(6-81)
Ostracoda spp . Ostr x x
Spinicaudata(1)
Cyzicus spp. Cyz
39
2012 Emergence Pattern
The 2012 season started with the fairy shrimp, Linderiella occidentalis, as the
largest initial hatch in the only inundated pool during the first survey, KF204, with a
relative abundance of about 50% (Figure 11). Juvenile copepods, mostly the calanoid
Leptodiaptomus sp., but also a few cyclopoid copepods, and ostracods were both slightly
higher than 20% relative abundance each. The cladocera Simocephalus sp. was the
lowest abundance at around 4%.
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Rel
ativ
e A
bu
nd
ance
Survey Date
Copepod
Cladocera
Ostracod
Other
Branchiopod
166 (1)
86403 (15)
11934 (16)
1090 (17)
1012(1)
613 (1)
12343 (4)
Figure 11 : The relative abundances of four crustacean groups for each 2012 survey.
Categorical counts include adults and juveniles, but not naupliar stages. The total
organismal count for each survey is located at the top of each survey’s highest abundance
bar. The numbers in parentheses represent the total number of pools for that survey that
had a catch.
40
The second survey consisted of three additional pools to sample from: KF13B,
KF49, and MT26. All four pools experienced a very large hatch of new cohorts, about an
8 fold increase in total organism counts, and this included a larger copepodid of the genus
Hesperodiaptomus spp. At a relative abundance of about 93%, copepods were the vast
majority of the new cohort. While ostracods, cladocera, and other branchiopods did not
decrease in abundance, they didn’t hatch near as many individuals as copepods and thus
were each at about a 3% relative abundance.
The third survey consisted only of KF204; the other three pools seen in survey
two had since dried. Copepods remained dominant at around 83% abundance. Large
branchiopods, now with two species of clam shrimp (Cyzicus sp. and Lynceus
brachyurus), increased only slightly in abundance to about 15%; however, this was a
great increase in total biomass considering their large size.
Survey 4 too consisted only of KF204. The abundance of copepods, ostracods,
and cladocera increased during survey 4, while large branchiopods saw a decrease in
abundance. During this survey several previously unseen species of cladocera were
observed (Figure 12), as well as adults of all previously collected crustacean groups.
Survey 5 consisted of 19 pools, 2 had no catch, which left 17 pools for data
analysis. While total abundance did not change much, the relative abundance of each
group changed quite dramatically. Copepods dropped to about 25%, while cladocera
increased to about 25%. Ostracods saw the biggest increase to about 43%, and large
branchiopods increased to about 7%. This survey also documented several more
previously unseen cladocera species of which Moina micrura was noticeably more
abundant than the other newly seen species.
41
0 1 2 3 4 5 6 7
Simocephalus sp.
Ostracod
Linderiella occidentalis
Leptodiaptomus copepodid
cyclopoid
lynceus brachyurus
Macrothricidae sp.
Hesperodiaptomus copepodid
Cladocera F
Cladocera D
Cyzicus sp.
Leptodiaptomus tyrrelli
Hesperodiaptomus eiseni
Cladocera H
Cladocera G
Moina sp.
Cladocera E
Cladocera K
Cladocera J
Cladocera I
Cladocera L
Cladocera C
Hesperodiaptomus caducus
Feb-3 Apr-13Mar-30Mar-16Mar-2Feb-17 Apr-27
Figure 12 : Species presence across the 14 week long 2012 survey. A blue bar indicates that the species was present at least once
among all pools during that survey. Species are sorted vertically in decreasing frequency.
41
42
Survey 6 saw a 10 fold increase in total abundance and a shift to cladocera
dominance at around 46% relative abundance. All crustacean groups saw an increase in
abundance, but the large increase was primarily due to two cladocera that had been
present since survey 1: Macrothricidae sp. and Simocephalus sp. The populations of
these two experienced a twenty fold increase each, an increase not seen in these two
species any survey prior.
Survey 7 saw over a 7 fold increase over survey 6 in total abundance. Cladocera
dominated at about 94% relative abundance due mainly to Moina micrura making up
almost 60% of the cladocera abundance. Copepods saw a decrease in relative abundance,
but an increase in absolute abundance, while large branchiopods and ostracods
experienced a dramatic drop in abundance.
KF204 was inundated the entire 2012 season and showed a similar pattern in
abundance patterns seen in all pools with relative abundance (Figure 13). Large
branchiopods showed low numbers of early hatch upon first inundation. Their population
reached its peak during survey 3, but decreased gradually to zero catch by survey 6 and 7.
Ostracods and cladocera were also very low in abundance until survey 6, where they both
saw a large increase in total abundance; cladocera saw a larger increase in abundance
relative to ostracods. Both groups experienced a decrease during survey 7. The copepod
population fluctuated throughout the season, though they were by far the most abundant
during most surveys. The average air temperature for surveys 1 through 7 was between
10 and 12 degrees Celsius; survey 7 experienced higher temperatures with an average
around 18 degrees.
43
0
2
4
6
8
10
12
14
16
18
20
0
4,000
8,000
12,000
16,000
20,000
2/3/12 2/17/12 3/2/12 3/16/12 3/30/12 4/13/12 4/27/12
Average
Temp. (C)
Spec
ies
Abundan
ce
Survey date
Cladocera
Copepods
LargeBranch.
Ostracods
Temp
Figure 13: Seasonal abundance of crustacean groups in KF204. This pool was
inundated throughout the entire season. Catch per unit effort (count/m3) was calculated
for each species group across each of the seven surveys. Average temperature was
calculated from CDEC station PRC for the 14 days preceding each survey.
2012 Species Richness
Though it was not inundated for most of the season, Kiefer 13B had the highest
species richness of any pool; there were 20 species of crustaceans observed throughout
the 14 week study (Table 4). Kiefer landfill overall was the most diverse site, with three
of the four pools sampled having over 18 different species. Werre Preserve was the
second most diverse site, with pool richness ranging from 10-15. Montelena Preservewas
moderate in diversity, with species richness ranging from 2-15; however, MT3 and MT25
both were inundated for only 1 survey. Mather Fields was relatively low in diversity,
with pool richness ranging from 8-11.
Macrothricidae sp. was the most widespread species; it was present in 19 of the
20 pools sampled and in relatively high numbers throughout the season. Ostracods and
the cladocera Simocephalus sp. were the second most widespread species; both were
44
present in 17 of the 20 sampled pools. The rarest species was Cladocera L; only one
individual was caught in KF13B throughout the entire season.
45
Table 4 : Species richness of inundated pools over the 2012 season. A 1 indicates that the indicated species was found at least once
during the whole study. Abbreviations are as follows: Dumo: Macrothricidae sp.; Ostr = Ostracod; Simo = Simocephalus sp.; cycl =
cyclopoid copepod; L.Cop = Leptodiaptomus copepodid; L.Occ = Linderiella occidentalis; Ltyrr = Leptodiaptomus tyrrelli; H.Eise =
Hesperodiaptomus eiseni; H.Cop = Hesperodiaptomus copepodid; Moina = Moina sp.; L.brac. = Lynceus brachyurus; Cyz. = Cyzicus
sp.; H.cad = hesperodiaptomus caducus; CladD-L = Cladocera sp. D-L.
Site Pool
Depth
(cm)
Surface
Area(m2) Dumo Ostr Simo Cycl
L.
Cop
L.
Occ
L.
tyr
Clad
E
H.
Eis
H.
cop Moin
L.
bra
Clad
H
Clad
G
Clad
F
Clad
K Cyz.
Clad
J
Clad
I
H.
cad
Clad
C
Clad
L Total
KF 13B 66 1,600 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 20
KF 204 56 1,000 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 18
KF 49 25 2,900 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 16
MT 26 13 11,000 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 15
WR 10 36 1,400 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 15
KF 56 13 300 1 1 1 1 1 1 1 1 1 1 1 1 1 13
WR 55 20 700 1 1 1 1 1 1 1 1 1 1 1 1 1 13
WR 26 20 70 1 1 1 1 1 1 1 1 1 1 1 1 12
MF UCD3 25 350 1 1 1 1 1 1 1 1 1 1 1 11
WR 59 10 200 1 1 1 1 1 1 1 1 1 1 1 11
WR 43 15 200 1 1 1 1 1 1 1 1 1 1 10
MT 19 25 450 1 1 1 1 1 1 1 1 1 9
MF CP 61 2,150 1 1 1 1 1 1 1 1 8
MF DP 51 1,300 1 1 1 1 1 1 1 1 8
MT 21 20 250 1 1 1 1 1 1 1 1 8
MF UCD2 25 350 1 1 1 1 1 1 1 7
MF UCD1 20 500 1 1 1 1 4
MT 3 3 900 1 1 1 1 4
MT 25 8 250 1 1 2
Totals 18 17 17 16 15 14 12 11 11 11 10 9 8 6 5 5 4 3 3 2 2 1
% Pools 95 89 89 84 79 74 63 58 58 58 53 47 42 32 26 26 21 16 16 11 11 5
45
46
Distance Between Sites - Cluster Analysis
Werre Preserve is the furthest site away from any other site; it is 8-9 kilometers
away from the other three sites. Mather Fields, Kiefer Preserve, and Montelena Preserve
are all 2-4 kilometers away from each other in a triangular distribution pattern, forming a
kite-like pattern with Were Preserve at the base (Figure 1).
The results of the cluster analysis formed three main groups of pools (Figure 14).
While each step of the diagram can be considered a separate cluster, when the species
information (Table 4) is taken into consideration, there are three apparent clusters based
on overall species similarity. The first cluster includes most of the pools from Mather
Fields along with one pool from Montelena Preserve. These pools all are relatively low
in species richness to begin with, but specifically are lacking the rare cladocera species
(F-L). They are also devoid of the relatively abundant cladocera E, which was found in
almost every pool not in that cluster.
The second cluster of pools had higher species richness in general than the first
cluster of pools. The rare species Cladocera H, J, G, and K were observed, making them
more similar to each other than the first cluster.
Cluster three contains the pools with the highest species richness. For the most
part, they all at some point in the season contained the most common species, so the
relationships seen within that cluster are mostly due to variations in which rare species
are present.
The Mantel test resulted in a weak observation of 0.09. Observation is the
calculated correlation between the latitude and longitude dissimilarity matrix and the
47
species dissimilarity matrix. A P-value of 0.15 (α = 0.05 ) fails to reject the null that
there is no relationship between distance between pools and crustacean similarity among
pools.
Figure 14 : Hierarchical cluster analysis dendrogram of presence-absence data.
Species presence was combined for each pool across the 2012 season. Pools MT3 and
MT25 were excluded due to their limited inundation time. The Y-axis (height) is the
Jaccard dissimilarity measure. User defined clusters are indicated by boxes. A mantel
test for significant was performed with associated pool latitude and longitude values.
48
Species abundance with physical and chemical variables – Canonical
Correspondence Analysis
Data collected in surveys 5, 6, and 7 were analyzed using Canonical
Correspondence Analyses with the program CANOCO. Surveys 1-4 did not have enough
samples to be included in this analysis.
The results of a CCA are eigenvalues, of which there will be as many as there are
environmental variables included in the analysis; in this analysis there are 6. An
eigenvalue (ranging from 0-1) indicates the proportion of variance explained in the
species data. There will also be an equivalent number of canonical axes, which are the
products of a linear combination of environmental variables and their corresponding
loading (Gotelli & Ellison, 2004). The loadings of each variable can be visualized by the
length of the arrow on the CCA plots. Each plot in this analysis is constructed using the
first two canonical axes; even though there are 6 total axes, the first two usually explain
most of the variance in the data. Thus, the strength of which a variable is correlated with
an axis is indicated by the position and length of the arrow. From this we can determine
correlations with the species data points and the environmental variables.
The first two canonical axes of survey 5 explain 37.2% of the variation observed
in the species data (Figure 15). Both axes 1 and 2 have a strong correlation between the
species data and the environmental data with correlations of 87.0% and 77.8%
respectively. Inundation time contributes greatly to axis 1, while all other variables have
very low positive and negative loadings with axis 1. H. eiseni, L. tyrrelli, and Cladocera
E all showed strong correlations with axis 1. Depth is strongly correlated with axis 2, and
surface area also contributes moderately to axis 2. Conductivity on the other hand has a
49
strong negative loading on axis 2 (Figure 16). The clam shrimp Cyzicus sp. is moderately
correlated with axis 2.
The first two canonical axes of survey 6 explain 38.8% of the variation in the
species data. Both axes have high species environment correlations of 92.7% and 71.1 %
respectively. Surface area contributes the greatest to canonical axis 1, with most other
variables weakly negatively correlated with axis 1. H. eiseni and the cladocera Moina
micrura are both correlated well with axis 1. Depth has the highest loading on axis 2,
with inundation time and conductivity moderately negatively correlated with axis 2.
Cladocera L, Cladocera C, and the fairy shrimp L. occidentalis, all showed strong
correlations with axis 2. Cladocera E, and the copepod H. caducus both are moderately
negatively correlated with axis 2.
The first two canonical axes of survey 7 explain 44.9% of the variation in the
species data with strong correlations between the species and environment at 80.3% and
88.4% respectively. Depth and center samples have a moderate loading on axis 1, while
edge sample have a moderately negative loading. Surface area is strongly negatively
correlated with axis 1. Most species had a low to moderate correlation with axis 1.
Inundation is strongly correlated with axis 2, while conductivity is moderately negatively
correlated. Cladocera I had a strong correlation with axis 2, while L. tyrrelli, Cladocera
F, and H. eiseni all had moderate correlations with axis 2.
Because of similarities with inundation time and depth in the later surveys of the
season, inundation was removed from the combined analysis. Temperature was
substituted as it has a similar trend (increases) throughout the season, but will better show
correlations with the late season. When surveys 5-7 (Figure 17) are combined into one
50
analysis, 47.7% of the variation in species data is explained by the first two canonical
axes. The Species-environment correlations are slightly lower than any individual
analysis at 72.2% and 67.4%.
Depth, surface area, and conductivity all contribute very little to axis 1;
temperature has the strongest influence on axis 1 with a very large negative loading.
Conductivity, surface area, and temperature all have large positive loadings on axis 2. A
large portion of the species are negatively correlated with axis 2 and positively correlated
with axis 1; temperature is having a large influence on the species data. Cladocera E and
Moina micrura are both slightly negatively correlated with axis 1. Cladocera K,
Cladocera J, and Simocephalus sp. are all moderately correlated with axis 2.
51
Figure 15 : Species biplots resulting from a Canonical Correspondence Analysis for surveys 5, 6, and 7. Species-environment
correlations measure the strength of the relationship between the species and environmental axes while the eigenvalue corresponds to
the amount of species data explained by the environmental data.
51
52
Figure 16: Sample biplots resulting from a Canonical Correspondence Analysis for surveys 5, 6, and 7. Species-environment
correlations measure the strength of the relationship between the species and environmental axes while the eigenvalues corresponds to
the amount of species data explained by the environmental data.
52
53
Figure 17 : CCA and output from combined data from surveys 5-7. Species data and
environmental data were combined into two tables to be used in the analysis. Variables
were normalized after moving the raw data from the three surveys into the new combined
table. Temperatures for each survey were averages for the 14 day period preceding the
survey.
54
Chapter 4: Discussion
Rainfall Pattern and Pool Inundation
La Nina is the cool phase of the El Nino Southern Oscillation (ENSO) event,
experiencing lower than average rainfall for Southern California, and higher than average
rainfall in Northern California (Diaz & Kiladis, 1992), while the opposite occurs in an El
Nino year. These events can persist up to two years, though it is not uncommon for
ENSO events to go from a strong to a weak event in consecutive years (Diaz & Kiladis,
1992). The January-February 2011 Multivariate ENSO Index, which quantifies the
deviation from average rainfall conditions, measured at -1.56, while 2012 saw a
decreased deviation from average rainfall with a measure of -0.70. These differences in
rainfall were enough to produce two very different vernal pool seasons.
The differences in both rainfall amount and rainfall pattern produced drastically
different environments in 2011 and 2012. The large amount of rainfall and even spread
of rainy days in 2011 meant that pools were constantly receiving inputs of cool, fresh
water. As a result the organisms experienced cooler water with a lower pH, conductivity,
and total dissolved solid (TDS), but also a larger amount of plant and algae growth. The
limited 2012 rainfall produced very much the opposite habitat. In fact, according to the
Department of Land, Air, and Water Resources (2005), hydrated pools in 2012 likely
received most of their water input from underground flow from other pools on site,
producing a higher conductivity in general due to dissolved ions from the soil. It was
unfortunate that very few zooplankton samples could be taken during the 2011 season, as
55
the different in rainfall patterns could have a dramatic change in the crustacean
community (Tavernini, 2007; Boven et al., 2008).
From the few samples that were taken in 2011, it was apparent that there was a
marked difference in the abundance of the copepod Hesperodiaptomus caducus between
years. In 2011 it was roughly even in abundance to the other two calanoids copepods,
while only 32 individuals were caught in all of 2012. It is unknown as to what
specifically caused this, but as mentioned previously, rainfall has a direct effect on all
pool variables, so it is a good place to start. Ripley and Simovich (2008) confirmed that
while more rainfall indeed brings about more species, less rainfall simply brings a smaller
subset of species within each pool than seen in wet years. This was confirmed by this
study as well; several other species, like L. occidentalis and H. eiseni, were both found in
more pools during the 2011 season than in 2012. These two species were found in some
of their largest numbers at Mather Fields pools in 2011 where they were completely
absent in 2012. It would be useful in future studies to be able to compare the
composition of pools from both wet and dry years as well as years with different rain
patterns to uncover correlations in species emergence that can only be speculated on at
this point.
Vernal Pool Temperatures
While most vernal pools will be small, shallow depressions, there are plenty of
examples of pools that are at extreme values of depths and sizes and are even considered
ponds. It would be expected then that these deeper pools would have some degree of
thermal stratification, with cooler temperatures at the deepest parts of the pools. But
despite large depths this cannot be presumed, as lakes as deep as 11 meters (m) may not
56
show any sign of a thermocline if the wind, rain, and seasonal conditions are right (Kling,
1988). Vernal pools are usually not thermally stratified by the strict definition of an
abrupt temperature change, but can experience a temperature gradient as was recorded
during this study. Two pools (KF13B and KF204) saw gradual decreases in temperature
from surface to bottom; their depth of about 75 cm was significant enough to cause a
temperature gradient of 5°C between the deep center and shallow edges of the pool for
most of the day. While this information, in and of itself, is not astounding, the
differences in the edge and center sweeps hints at a significance to the ecology of several
aquatic crustaceans.
In KF13B, there was an unmistakable difference in the center and edge sweep
compositions. The fairy shrimp L. occidentalis was absent from edge sweeps but found
in high numbers in the center sweep. The two clam shrimp Cyzicus sp. and L.
brachyurus showed the opposite pattern in distribution, absent in center sweeps but
highly abundant at the pool edge. With the two microhabitats differing in temperature, it
seems possible that these two species prefer different habitats due to temperature
sensitivity or food preference. The idea of temperature sensitivity was confirmed by
Hathaway and Simovich (1996) in their study of fairy shrimp hatching, maturation, and
survival rates of warm and cold water fairy shrimp. The cold water species, found in San
Diego, showed optimum rates at around 10°C, which would be the cooler temperatures
for that region. This data alone though is not convincing, as other research has shown
opposite results in the past.
King et al. (1996) described the microhabitat utilization of vernal pools as
nonexistent. Their edge, bottom, and surface sweeps showed no significant different in
57
species; however, they make no note as to what time of day samples were taken. While
this distribution pattern makes sense for shallow pools or early morning when
temperatures are the same throughout, a 5°C difference seems too large to have no effect
on the species distribution of vernal pools.
Seasonal Species Composition
The larger branchiopods (orders: Anostraca, Laevicaudata, Notostraca, and
Spinicaudata) have all been found at these sites in the past. B. lynchi and L. packardi are
on the federal endangered species list; therefore, these sites are regularly monitored for
their presence as well as for endangered plant presence.
The copepoda of this study have not been noted in Sacramento County prior to
this study. The two species of Hesperodiaptomus spp. have been found in the western
states north to Alaska and all throughout Canada. Being extremely vulnerable to fish
predation, they are mostly found in high altitude lakes and temporary ponds.
Leptodiaptomus sp. is found in the US from the West Coast east to the Rocky Mountains,
as well as all throughout Canada. While these species have been seen in other temporary
ponds in California (King et al., 1996), so their effective range is not expanded, they have
never been described in pools from this area. The cyclopoids of this study were not
speciated due to the amount of time that would be needed to do so and uncertainty of past
attempts (Janet Reid, personal communication, September 4, 2011).
The cladocera of this study were particularly difficult to speciate due to lack of
research, incomplete taxonomy, and difficult to find species descriptions. The largest and
one of the most abundant species, Simocephalus spp., is the only species that for certain
is undescribed as it is currently being described by Christopher Rogers. It would seem
58
plausible that if the largest and most abundant cladocera is undescribed, then the smaller
and rare species would be also. Moina micrura is currently the only confirmed
speciation, and it represents a new locality for this species. The other species have been
speciated to either family or genus and cannot be taken further for a number of reasons.
In the case of Daphnia mendotae, that species epithet is a catch all term for an
undetermined number of Daphnia species. It does not describe a species, but a suite of
Daphnia that are likely all independent species; a lack of research has placed them into
one species complex (Dodson et al., 2010). Several of the rare cladocera species suffer
from a similar scenario and cannot be speciated beyond genus due to lack of research.
Finally, some of the rare species were caught in such low numbers that there are not
enough specimens to attempt to speciate beyond family. A possible thirteenth species of
cladocera was not included in the analysis because only a single specimen was caught. It
was not possible to tell if it was indeed its own species or if it represented a morphotype
of another.
The ostracods were not identified due to limited knowledge of the group and time
constraints. All ostracods were saved for possible future identification. From informal
inspection during the sorting process though, it is estimated that there are between 6 and
8 different species of ostracods from the 2012 survey.
Seasonal Emergence Pattern
The first goal of this study was to describe the phenology of the four vernal pool
sites. While the rain has mostly limited this description to a relatively dry year, it is still
an important step in fully understanding this habitat. The first residents in significant
59
numbers were fairy shrimp. This same pattern was shown in ecological studies by
Wiggins et al. (1980), Patton (1984), and Horne (1967). Some fairy shrimp desiccate as
metanauplii, which are relatively large hatchlings. An increase in oxygen content due to
the newly inundated pools is thought to be a main trigger of emergence. Early hatching
grants a selective advantage through access to abundant food resources, as rotifers and
copepods are also among the first to hatch in pools (Frisch & Green, 2007) and are at
their highest abundances after the first inundation (Tavernini et al., 2005). In addition to
abundant food and the accompanying fast growth rate, there is a complete lack of
predation as insect and amphibian larvae have not yet occupied the pools. It would seem
that fairy shrimp in general are adapted to this quick lifestyle as shown by my data as
well as by Fahd et al. (2009). In Doñana National Area in southwest Spain, large
branchiopods were found to have lower abundances in pools that experience longer
average hydroperiods. This could be due in part to the aforementioned early hatching
advantages, but also due to intolerance to high temperatures as noted by Horne (1967,
1971). While there was a significant fairy shrimp emergence in KF204 at the beginning
of the season, other pools should also see a similar pattern upon first inundation if
inundation is the only factor. The majority of pools became inundated late in the season,
where they experienced higher water temperatures than would be expected upon a
typically timed first inundation. While fairy shrimp were observed in many other pools
throughout the season, there were no more than a few per sweep in most pools. The
pools with high abundances were deeper pools, and they were only caught in the deeper,
cooler parts of the pool. KF49 and KF13B, experienced the largest fairy shrimp hatches
of the season when first inundated. Both pools dried, and when reinundated, the new
60
hatch abundances were extremely low. Patton (1984) showed that as the season
progressed and temperatures increased, the abundance of Anostraca gradually decreased
in vernal pools of Chico, CA. The rapid drop in Anostraca population along with a
steady increase in population of all other species did not support the idea of predation or
limiting resources. Patton also noted that temperatures above 20 degrees Celsius
inhibited the hatching of new cohorts. Hathaway and Simovich (1996) showed that
increased temperature affected the hatching, maturation time, and survival of two
Southern California fairy shrimp. The higher temperatures associated with the late rain
this season probably limited the hatching and survival of fairy shrimp for most of the
inundation time of pools.
Spinicaudata and Laevicaudata, two large clam shrimp, may not be as temperature
or predator sensitive as fairy shrimp. Also known as clam shrimp, they have been
observed high in numbers later in the season, usually once fairy shrimp have started to
decline (Kenk, 1949; Wiggins et al., 1980). Temperature seems to be the main
constraint, as clam shrimp do not survive well in temperatures lower than 10°C. This
project confirms that observation since both L. brachyurus and Cyzicus sp. were not seen
in significant numbers until survey 6 when the temperature was warmer and many other
crustaceans were decreasing in abundance. Clam shrimp may be taking advantage of
higher temperatures to insure a quick maturation time; Rzoska (1961) noted that clam
shrimp from Sudan can reach sexual maturity in as little as 5 days. It is possible that
clam shrimp are simply adapted to the late phase of vernal pools and may even be able to
survive in the last drops of a pools life; clam shrimp have been shown to survive in
oxygen concentrations less than 9% (Dodson et al., 2010).
61
Ostracods were the second most abundant crustacean group to hatch upon
inundation. Different shapes, sizes, and colors of ostracods were found during various
surveys and each may have a different life history pattern as well as hatching and survival
traits. Wiggins et al. (1980) observed several different life histories in vernal and
autumnal pool ostracods. Temporary and permanent water species were observed
hatching early from torpid cysts; these cysts were nearly adults when formed which
would explain the appearance of adults almost immediately upon inundation. Other
species were seen emerging later in the season as early stage nauplii from encysted eggs.
The ostracods seen in the first survey were all of the same species; other ostracod species
began emerging as the season went on, and others disappeared. When it comes to
tolerances, ostracods can survive the worst of what vernal pools can bring. They can
survive temperatures to about 30°C and have even been observed survive freezing,
dissolved oxygen levels as low as 25%, and all ranges of salinity. With tolerances of
such extreme physical conditions, it is thought that ostracods are more chemically limited
if anything (Smith & Delorme, 2010). Freshwater ostracods are thought to be limited by
bicarbonate, calcium, and magnesium due to the thick shell they grow during their life.
In future studies, it would be beneficial to include water ion analysis to better understand
ostracods and other shelled species. Ostracods are also thought to be substrate limited;
sandy or gritty substrate and water devoid of detritus will limit the growth and survival of
ostracods (Smith & Delorme, 2010). The pools of this study were variable in their levels
of silt, rocks, pebbles, plants, and detritus; however, only observations were recorded
with no attempt to quantify or measure differences. But because ostracods were present
in almost every pool, the idea of being substrate limited is not supported by this study.
62
Copepods are the most commonly seen first colonizers of ephemeral pools of
many parts of the world (Tavernini et al., 2005; Frisch & Green, 2007; Fahd et al., 2009).
In this study they were slightly lower in abundance than ostracods; however, this may be
due to the small sample size associated with the first survey. The most abundant
copepods by far were copepodites of the calanoid Leptodiaptomus tyrrelli. It is not
known whether this species encysts as a juvenile or if they lay desiccation resistant eggs,
but the appearance of copepodites late into the season leaves both open as possibilities.
The copepods from this study are likely limited the same way fairy shrimp are, though to
a lesser extent. They rely on mass early hatching to avoid predation and take advantage
of food resources, and see decreasing abundances later in the season as temperature and
predators increase (Wiggins et al., 1980). The same pattern seen in fairy shrimp in re-
inundated pools was seen in copepods; there was a massive hatch during the first
inundation, but a much smaller hatch during second inundation. The literature shows that
cyclopoid copepods usually appear first, as many species are known to encyst as late
copepodite instars (Wiggins et al., 1980; Frisch & Santer, 2004; Frisch & Green, 2007).
Cyclopoids, however, showed quite the opposite pattern during this study; they occurred
in low abundance early in the season and highest abundance during the last two surveys
with no signs of their population growth slowing down. While the results from this study
do not agree with other field studies, they do with lab studies by Frisch and Santer
(2004). Cyclopoid development, hatching, and diapause survival were shown to be
closely correlated with temperature.
Cladocerans are often not found in vernal pools for several months into the season
(Frisch & Green, 2007). There is no documented lethal low temperature for cladocera,
63
but at low temperatures their individual growth rate is extremely limited (Dodson et al.,
2010). Simocephalus sp. was found during the first surveys when temperatures were
cool, but catches were very low until survey 6, after 10 weeks of inundation. It was not
until survey 6 that most of the 12 species of cladocera were even observed. Eitam et al.
(2004) saw this same pattern in cladoceran species richness in vernal pools from Israel;
there was an increase in species richness as the pool inundation time increased, and Fahd
et al. (2009) saw an almost four fold increase in total abundance in pools with higher
average inundation time. Cladocera do have a recorded upper temperature tolerance at
around 30°C (Dodson et al., 2010), though it would be rare for a vernal pool to exceed
this temperature for an extended period of time. The mass cladocera hatching occurred
between surveys 6 and 7 between when the average temperature increased to around
20°C for the first time. It is possible that this temperature maximizes their metabolic rate,
but more research would be needed to say for certain whether temperature is the only
factor. Increases in day length and temperature could have also caused an increase in
cladoceran food resources. Because copepods also increased in abundance during that
same time frame, that seems like a likely scenario.
Seasonal Species Richness
Of the four studied sites, Kiefer had the highest average richness followed by
Werre Preserve, Mather Fields, and Montelena Preserve. In general, the deepest and
largest pools supported a higher number of total species. This is no surprise, as almost
every vernal pool survey uncovers the same pattern with depth (Ebert & Balko, 1987;
King et al., 1996; Eitam et al., 2004; Tavernini et al., 2005; Ripley & Simovich, 2008),
though surface area remains debatable (Eitam et al., 2004; Marrone et al., 2006; Ripley &
64
Simovich, 2007). It is also unclear if inundation time plays just as significant a role
(Fahd et al., 2009) as it is affected by both depth and surface area. These are general
patterns though as KF56, which would remain shallow even with plenty of rain, had a
relatively high richness of 15 species. Conversely, the large and deep Mather Field
Dog’s Pool and Carol’s Pool experienced only 8 species each. Depth may be a
contributing factor to the species richness of a pool, but not the determining factor.
One interesting set of pools was the chain of interconnected pools MFUCD1,
MFUCD2, and MFUCD3. These pools are similar in depth, surface area, substrate
composition, and even vegetation coverage and type that produces dark brown water.
They are less than 10 m apart and are connected in a cascade of underground water flow
from UCD3 into UCD2 and ending at UCD1 (Department of Land, Air, and Water
Resources, 2005). The only recorded difference between the pools, except for species
richness, was conductivity. Because UCD3 is a headwater pool, it gets most of its input
from rainfall, whereas UCD2 and UCD1 get inputs from rainfall as well as underground
flow from UCD3. In 2011 it was also observed that UCD3 had a higher species richness
than either of the other two, with no differences in inundation time. This again shows
that depth is not the only factor contributing to the species richness of pools, but as the
sites are all similar based on the recorded variable, it seems the answer is beyond the
scope of this study.
The four sites when taken as a whole are all very similar in terms of the measured
variables. The largest difference was Werre Preserve and the higher than average
conductivity recorded there. Dissolved oxygen and pH, though not included in the
analysis, showed no large deviations between sites either. While there were a few species
65
only found at Werre Preserve, due to their rarity, it is uncertain if that was indeed the
only site in which they were actually present.
The main difference in species composition between pools of low or moderate
richness and pools of high richness is the presence of rare species. It is possible that this
season did not produce adequate conditions for the survival of these species, and we are
seeing a smaller subset of the species that would normally exist in each pool. It is also
possible that they were simply not adequately sampled. Because these cladocera are so
small and so few, they could have been missed by the net, as was probably the case in the
2011 samples with the larger mesh size. Several of the genera are known to be bottom
dwellers and surface skimmers, and may not be consistently caught. Also, given their
small size (0.3-0.5mm) just barely bigger than the net, it is also possible that they
squeezed through and only the largest individuals were actually caught. To alleviate this
problem, there are water column samplers that can be used in future studies that do not
discriminate based on size.
Community Similarity
There are three different clusters of pools formed from the cluster analysis, but
there does not seem to be any pattern with distance (p-value =0.15). It would be expected
that since Werre Preserve is the furthest away, that it would be different from the other
three sites; however, this is not the case since it contains some of the most diverse pools
that are similar to pools on Kiefer and Montelena Preserve. Mather Fields actually had
the most unique pools this year; despite being only 3-5 kilometers away from Montelena
Preserve and Kiefer, its pool compositions were devoid of some of the most common
66
species. But, this does not necessarily mean that there is no dispersal to or from this site;
the pools at Mather Fields could have experienced unfavorable hatching conditions due to
a variable not included in this study. It seems likely that all four sites are within close
enough proximity that dispersal is actively maintained.
The three widely accepted dispersal mechanisms of vernal pool crustaceans are
wind dispersal of cysts during the dry phase, overflow of water during the wet phase, and
animal assisted dispersal during the wet phase. There are several other means that exist,
like a burrowing amphipod, but these are rare and only short distance (Harris et al.,
2002). Wind dispersal is still not well understood, and the actual significance of it is yet
to be determined. Many scientists believe that microscopic organisms (rotifers, ciliates,
etc.) use wind as one of their main dispersal methods (Maguire, 1963). Puschkarew
(1913) found as many as 2.5 protozoans per cubic meter (m3) of air after filtering it, and
cultured 13 species from collected rainwater. Vanschoenwinkel et al. (2009) discovered
by using glue traps and wind socks that microcrustacean wind dispersal had a limit of
about 30 m, which would make wind dispersal really only contribute to within site
diversity. Flood mediated dispersal only affects neighboring pools, and only in years
where rain is much higher than average. Animal mediated dispersal is a little more
understood and is believed to be responsible for long distance dispersal.
There are several different animals that contribute to the dispersal of vernal pool
crustaceans. Over a small spatial scale, amphibians, mammals, and insects have been
documented transporting microorganisms in fur, hoofs, and intestines. More documented
though is the dispersal through water fowl. Both local and migrating birds use temporary
ponds for food and resting, all the while microorganisms are getting caught in feathers,
67
especially during preening. Crustaceans have been shown to survive long flights, and
ostracods have even been known to survive in the digestive tract of birds (Wiggins et al.,
1980), eliminating the necessity of the bird to even stop.
The results show that the most distant site is similar in composition to the other
three sites. While the 2012 samples show that Mather Fields pools are quite different
from the other three sites, the 2011 samples show that the species absent in 2012 are
indeed in the cyst bank, but just did not hatch in 2012. The distance between the four
sites is not significant enough to prevent dispersal among sites.
Environmental Correlates
The ultimate goal of this question was to determine if there was a pool
characteristic that one or more species were correlated with. Because this habitat is
scarce and still declining, it is important for mitigation and conservation efforts to know
what characteristics are important to the survival of these organisms. The species-
environment correlations from each surveys CCA showed that there was indeed a strong
correlation between the environmental variables, but the low eigenvalues indicate that
there are few species that actually show this correlation. Indeed, most of the organisms
throughout all the surveys were clustered around the center of the biplots. There are
some important correlations between certain species and environmental variables.
As a season progresses from rainfall filled pools to shrinking pools due to
evaporation, the chemistry of the pools will change. Rainfall in general will lower the
pH, conductivity, and TDS, and desiccation will raise those. There is also a daily cycle
of pH and dissolved oxygen increasing throughout the day and decreasing at night. It
68
was thought that the increasing conductivity as a pool dries would show some pattern
with emergence of late and early season species. But, while variables decreased and
increased as expected, their correlations with the species data was not as expected.
Conductivity had more of a correlation with sites than with any species. Werre
Preserve had a higher than average conductivity for all of its pools, but it does not seem
that conductivity at that level, which was sometimes 10 times more than any other site,
was significant enough to exclude or include any species based on that alone. The
conductivity at Kiefer Landfill was much lower than the pools at Werre Preserve, but
with the exception of a few rare species, the presence at the two sites were the same. The
only time there seemed to be any correlation with conductivity was during survey 6
where several rare cladocera and H. caducus showed a positive correlation. But, with
low numbers caught and the absences of them in the previous and subsequent surveys, it
is more probable that it is just a coincidence and not causation. So the only chemical
variable that was included in the analysis seemed to be insignificant for the data from this
year, but some of the non-chemical variables indeed show some correlation with species
richness.
Surface area had a significant correlation with several species: H. eiseni, M.
micrura, and Cladocera E all showed higher population densities in larger pools. This
correlation was not seen in survey 5 as their populations were still very low and they
were mostly found in KF204, thus the inundation aspect of that pool turned out to be a
more significant factor in that analysis. It is unfortunate though that the largest pools of
this project are also the most easily inundated. These pools are large and have a long
inundation time, which becomes a confounding factor in determining which is most
69
affecting species presence. It does not seem possible with these pools and the single year
of data to determine exactly why these species have a tendency to occur in larger pools.
Cladocera E, which belongs to the genus Scapholebris sp., is a surface skimmer, so there
is a possible explanation as to their surface area correlation; however, M. micrura and H.
eiseni are both associated with the water column. What can be said from this study is
simply that these three species show a positive correlation with surface area, there are
consistently smaller densities in smaller pools.
Depth is widely accepted as the most significant variable in determining species
richness in a vernal pool. This is most likely due to a number of factors; deeper pools
will have cooler temperatures, longer inundation times, and more microhabitat. This all
leads to the ability to support multiple species with different life histories. Despite
deeper pools having a higher species richness, the only two species that showed a
consistent correlation with depth were L. occidentalis and Cyzicus sp. As mentioned
earlier, fairy shrimp are temperature sensitive and were found mostly in the deeper parts
of pools. The clam shrimp Cyzicus sp. showed a somewhat inconsistent correlation with
depth; it showed a strong correlation during survey 5, but a low correlation in survey 6
and 7. Cyzicus was only caught in deeper pools, but in very low numbers at times; it is
unclear if this same pattern with depth would remain true in a year with more rain.
The final analysis took all surveys and combined them into one CCA with the
goal to uncover any long term patterns that can only been seen across an entire season.
Because only one pool was available for most of the surveys, this was creating unusually
strong correlations for species present in that one pool. Instead, the average air
70
temperature for the two weeks preceding each survey was used. This created a more
consistent variable that was still at least relatable to inundation time.
Of the 22 total species in the analysis, 14 of them were negatively correlated with
temperature. The species include juvenile copepods, H. eiseni, all large branchiopods,
ostracods, and several rare cladocera. During the last survey, when temperatures were
highest, these species saw dramatic reductions in abundance, as much as 95% in some.
Because of this, it could very well be that the temperatures experienced during survey 7
were at the high end of the temperature tolerances of these organisms.
Dumontia sp., cyclopoids, L. tyrrelli, Moina sp., and Cladocera E, while all seeing
increases in populations survey to survey, were also very frequent among most pools.
Their populations did not tend to be much more or less in deeper, larger, or more
conductive pools, so these species are more or less clustered around the center of the
biplots. Cladocera K, J, and Simocephalus sp. were all correlated with surface area.
Simocephalus sp. by survey 7 is abundant and present in just about every pool, regardless
of size. But during the early parts of the season and during surveys 5 and 6, they were
only ever abundant in the large pools. Cladocera J and K both saw about 20 fold
increases in population during the last survey, though considering they were rare to begin
with, this is not much of an increase. But, their increases were only in the largest pools,
which would explain their placement more on the surface area axis rather than the
temperature axis.
There are many more pool characteristics that are thought to be important to the
hatching and survival of crustaceans. Correlations have been found with TDS, sediment
depth, animal disturbance, plant abundance, chlorophyll, and all types of dissolved ions
71
like ammonium, magnesium, phosphates, carbonates, and nitrates. It was beyond the
ability of this study to measure all of these variables, thus the most easily measurable
characteristics were selected. Unfortunately though, pH and dissolved oxygen were easy
to measure but difficult to include in the analysis. Because they changed throughout the
day it would require a deployable sonde to accurately measure the differences between
pools. For future studies, it would be extremely valuable have data logging sondes for as
many variables as possible. Of course there is a monetary limitation to an idea like that,
but if possible, it would overcome many of the limitations of this study.
Despite the loss of over 90% of the historic vernal pool habitat, there are still
great opportunities for research of what remains. This habitat not only supports dozens
of crustacean species, but also numerous plants, birds, mammals, reptiles, and
microorganisms. This study barely scratched the surface of potential research, but there
are important results that are now added to the collective knowledge that can be used to
further protect this vulnerable and vanishing habitat. With artificial vernal pools
becoming an increasingly popular mitigation effort it is especially important to
understand the seasonal variation in the community as well as what water characteristics
are important to the survival of pool residents.
72
Chapter 5: Conclusions
This study found that despite the loss of over 90% of the historic vernal pool
habitat, there are still great opportunities for research of what remains for management.
This habitat not only supports dozens of crustacean species, but also provides habitat and
food for numerous plants, birds, mammals, reptiles, and microorganisms. This study
focused on the crustacean community, which has provided important results that are now
added to the collective knowledge that can be used to further protect this vulnerable and
vanishing habitat. Twenty two species of crustaceans were discovered, eleven of which
are new to science. These species demonstrated various life histories that are important
to understand if vernal pools are to be protected. The four sites included in the study
were found to contain similar species, meaning that dispersal has been maintained
between sites. While most measured variables were similar among sites, conductivity
differed. Conductivity, as well as depth, surface area, and temperature, showed positive
and negative correlations with several species. This information is again important to the
protection of the diminishing vernal pool habitat.
73
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79
APPENDIX
Supplemental Table 1: Species catch per unit effort (count/m3) for surveys 1-4. Catch per unit effort was calculated using the
surface area of the net, depth of the water, and length of the sweep to calculate a total water volume sampled. Species catch was
divided by volume swept to calculate species count per m3 of water. Use the species CPUE and volume swept in the table to back
calculate original counts. Abbreviations follow those of Table 4.
Date Site Pool Sweep
Volume
Swept
(m^3)
Dumo Ostr Simo CyclL.
Cop
L.
Occ
L.
tyr
H.
Eis
H.
cop
L.
brac
Clad
H
Clad
GCladF Cyz Total
2/3/2012 KF 204 Center 0.0268 0 174 47 47 0 63 0 0 0 0 0 0 0 0 331
KF 204 Edge 0.0201 0 457 47 32 521 1,230 0 0 0 0 0 0 0 0 2,287
Total 0 631 95 79 521 1,293 0 0 0 0 0 0 0 0 2,618
2/17/2012 KF 13B Center 0.0806 37 385 12 0 893 806 0 0 19,007 25 0 0 0 0 21,166
KF 13B Edge 0.0402 236 310 0 25 658 385 0 0 4,504 0 0 0 0 0 6,117
KF 204 Center 0.0806 0 434 12 0 248 50 0 0 1,104 0 0 0 0 0 1,849
KF 204 Edge 0.0645 161 1,700 62 0 670 360 0 0 4,057 0 0 0 0 0 7,010
KF 49 Center 0.0806 868 1,956 0 0 1,703 1,625 0 0 37,603 16 0 0 63 0 43,833
KF 49 Edge 0.031 757 521 32 0 1,830 315 0 0 21,136 0 0 0 0 0 24,590
MT 26 Edge 0.01 124 590 93 0 8,199 466 0 0 152,050 0 0 0 0 0 161,522
Total 2,183 5,895 212 25 14,201 4,006 0 0 239,460 41 0 0 63 0 266,086
3/2/2012 KF 204 Edge 0.0167 6 422 6 0 1,123 546 0 0 1,681 12 0 0 0 6 3,803
3/16/2012 KF 204 Center 0.0806 205 1,136 0 79 1,009 79 5,047 189 599 0 16 16 79 0 8,454
KF 204 Edge 0.0402 79 584 142 126 0 126 3,880 820 1,640 32 0 0 79 0 7,508
Total 284 1,719 142 205 1,009 205 8,927 1,009 2,240 32 16 16 158 0 15,962
79
80
Supplemental Table 2 : Species catch per unit effort for Survey 5 on 3/30/2012. Catch per unit effort was calculated using the
surface area of the net, depth of the water, and length of the sweep to calculate a total water volume sampled. Species catch was
divided by volume swept to calculate species count per m3 of water. Use the species CPUE and volume swept in the table to back
calculate original counts. Abbreviations follow those of Table 4.
Site Pool SweepVolume
Swept Dumo Ostr Simo Cycl
L.Co
p
L.
Occ
L.
tyr
clad
E
H.
Eis
H.
copMoina
L.
bra
Clad
H
Clad
G
Clad
FCyz Total
KF 13B Center 0.0268 37 970 0 0 149 37 0 0 37 0 0 75 0 0 0 75 1,381
KF 13B Edge 0.0201 0 498 0 0 199 0 0 0 0 0 0 50 0 0 0 149 896
KF 204 Center 0.0268 709 1,828 1,045 37 112 75 634 0 299 0 0 187 0 0 0 0 4,925
KF 204 Edge 0.0201 597 2,488 1,144 348 0 50 199 597 846 0 0 0 50 0 0 0 6,318
KF 49 Center 0.0268 75 522 0 0 0 410 0 0 0 1,194 0 37 0 0 0 187 2,425
KF 49 Edge 0.0100 200 100 100 200 0 0 0 0 0 100 0 0 0 0 0 0 700
KF 56 Edge 0.0067 299 448 0 149 299 299 0 0 0 149 0 0 0 149 0 0 1,791
MF UCD1 Center 0.0067 149 0 2,239 149 0 0 0 0 0 0 0 0 0 0 0 0 2,537
MF UCD1 Edge 0.0067 149 0 299 0 0 0 0 0 0 0 0 0 0 0 0 0 448
MF UCD2 Center 0.0201 0 398 498 0 0 0 0 0 0 0 0 0 0 0 0 0 896
MF UCD2 Edge 0.0100 0 100 700 100 0 0 0 0 0 0 0 0 0 0 0 0 900
MT 19 Center 0.0201 50 100 50 50 0 100 0 0 0 0 0 0 0 0 0 0 348
MT 19 Edge 0.0067 0 896 0 0 299 0 0 0 0 0 0 0 0 0 0 0 1,194
MT 21 Center 0.0201 0 0 149 0 0 0 0 0 0 0 0 0 0 0 0 0 149
MT 26 Center 0.0268 0 1,600 300 0 600 0 0 0 0 0 0 0 0 0 0 0 2,500
MT 26 Edge 0.0100 0 112 75 37 0 0 0 0 0 0 37 0 0 0 0 0 261
MT 3 Center 0.0268 75 0 0 187 0 0 0 0 0 0 0 0 0 0 75 0 336
MT 3 Edge 0.0268 37 0 0 0 37 0 0 0 0 0 0 0 0 0 37 0 112
WR 10 Center 0.0268 0 933 37 37 970 37 0 0 0 224 0 0 0 0 0 37 2,276
WR 10 Edge 0.0201 149 547 100 0 299 50 0 0 0 0 100 0 0 0 0 50 1,294 8
0
81
Supplemental Table 3Cont’d : Species catch per unit effort for Survey 5 on 3/30/2012. Catch per unit effort was calculated using
the surface area of the net, depth of the water, and length of the sweep to calculate a total water volume sampled. Species catch was
divided by volume swept to calculate species count per m3 of water. Use the species CPUE and volume swept in the table to back
calculate original counts. Abbreviations follow those of Table 4.
Site Pool Sweep
Volume
Swept
(m^3)
Dumo Ostr Simo CyclL.Co
p
L.
Occ
L.
tyr
clad
E
H.
Eis
H.
copMoina
L.
bra
Clad
H
Clad
G
Clad
FCyz Total
WR 26 Center 0.0268 75 373 37 37 75 75 0 0 0 0 37 187 0 0 0 0 896
WR 26 Edge 0.0067 299 1,642 0 0 149 149 0 0 0 0 0 1,045 0 299 0 0 3,582
WR 43 Center 0.0268 410 634 75 112 0 0 0 0 0 0 0 0 37 0 0 0 1,269
WR 43 Edge 0.0067 448 299 149 0 0 0 0 0 0 0 0 0 0 0 0 0 896
WR 55 Center 0.0268 224 112 75 0 672 37 0 0 0 187 0 0 0 0 0 0 1,306
WR 55 Edge 0.0167 1,796 1,377 240 0 3,353 60 0 0 0 0 0 419 60 0 0 0 7,305
WR 59 Center 0.0134 1,418 7,388 224 373 0 149 0 0 0 0 0 75 0 0 0 0 9,627
WR 59 Edge 0.0033 2,424 26,061 606 3,333 1,818 0 0 303 0 1,515 0 303 0 303 0 0 36,667
9,620 49,424 8,140 5,151 9,030 1,528 833 900 1,182 3,369 174 2,376 147 751 112 498 93,234
81
82
Supplemental Table 4 : Species catch per unit effort for survey 6 on 4/14/2012. Catch per unit effort was calculated using the
surface area of the net, depth of the water, and length of the sweep to calculate a total water volume sampled. Species catch was
divided by volume swept to calculate species count per m3 of water. Use the species CPUE and volume swept in the table to back
calculate original counts. Abbreviations follow those of Table 4.
Site Pool Sweep
Volume
Swept
(m^3)
Dumo Ostr Simo CyclL.
Cop
L.
Occ
L.
tyr
Clad
E
H.
Eis
H.
copMoina
L.
bra
Clad
H
Clad
G
Clad
F
Clad
KCyz
Clad
J
Clad
I
H.
cad
Clad
C
Clad
LTotal
KF 13B Center 0.0634 158 1,104 79 221 741 268 1,451 0 189 0 268 142 0 0 0 0 95 32 16 0 284 16 5,063
KF 13B Edge 0.0634 284 5,410 442 284 757 0 3,438 0 205 0 284 1,215 0 0 16 79 678 32 0 0 47 0 13,170
KF 204 Center 0.0634 6,845 5,410 5,710 0 3,470 0 4,101 95 237 0 0 0 473 16 394 0 0 0 158 0 0 0 26,909
KF 204 Edge 0.0634 6,404 7,413 3,912 221 1,025 0 315 505 252 0 205 0 142 32 142 0 0 0 63 0 0 0 20,631
KF 49 Center 0.0634 252 4,590 63 95 63 63 773 0 284 0 32 32 16 0 47 0 47 0 0 0 32 0 6,388
KF 49 Edge 0.0634 2,918 5,694 1,656 741 32 32 1,183 0 473 0 237 0 0 0 142 0 158 0 0 0 63 0 13,328
KF 56 Center 0.0619 388 162 808 0 194 16 210 0 48 0 0 0 16 0 16 0 0 0 0 0 0 0 1,858
KF 56 Edge 0.0372 591 134 672 0 403 0 349 0 0 0 0 0 0 0 27 0 0 0 0 0 0 0 2,177
MF CP Edge 0.1268 142 1,569 402 0 55 166 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2,334
MF DP Edge 0.01268 481 718 79 55 0 268 0 0 8 16 0 0 0 0 0 0 0 0 0 47 0 0 1,672
MF UCD1 Center 0.0634 32 599 16 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 662
MF UCD1 Edge 0.0248 0 282 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 282
MF UCD2 Center 0.0634 347 5,221 0 32 63 126 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5,804
MF UCD2 Edge 0.0495 727 4,646 2,000 121 121 81 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7,697
MF UCD3 Center 0.0634 379 2,145 946 79 0 126 205 0 0 0 0 0 32 0 0 0 0 0 16 0 0 0 3,927
MF UCD3 Edge 0.0495 606 889 1,030 0 0 20 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2,566
MT 19 Center 0.0634 536 505 505 0 521 63 158 0 79 47 0 0 0 0 0 0 0 0 0 0 0 0 2,413
MT 19 Edge 0.0372 349 806 134 0 54 0 81 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1,425
MT 21 Edge 0.1268 32 252 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 284
MT 25 Center 0.0372 0 538 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 538
MT 25 Edge 0.0248 0 121 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 161
82
83
Supplemental Table 5 Cont’d : Species catch per unit effort for survey 6 on 4/14/2012. Catch per unit effort was calculated using
the surface area of the net, depth of the water, and length of the sweep to calculate a total water volume sampled. Species catch was
divided by volume swept to calculate species count per m3 of water. Use the species CPUE and volume swept in the table to back
calculate original counts. Abbreviations follow those of Table 4.
Site Pool Sweep
Volume
Swept
(m^3)
Dumo Ostr Simo CyclL.
Cop
L.
Occ
L.
tyr
Clad
E
H.
Eis
H.
copMoina
L.
bra
Clad
H
Clad
G
Clad
F
Clad
KCyz
Clad
J
Clad
I
H.
cad
Clad
C
Clad
LTotal
MT 26 Center 0.0619 372 808 3,974 194 178 0 792 0 4,814 16 2,730 65 0 0 0 0 0 0 0 0 0 0 13,942
MT 26 Edge 0.0495 141 202 4,141 40 20 0 20 0 182 40 101 0 0 0 0 0 0 0 0 0 0 0 4,889
WR 10 Center 0.0634 1,861 2,098 1,562 63 2,666 63 2,792 0 63 47 615 221 32 16 0 0 0 0 0 0 0 0 12,098
WR 10 Edge 0.0372 1,882 914 1,263 0 780 0 511 0 134 161 1,344 54 0 0 0 0 27 0 0 0 0 0 7,070
WR 26 Center 0.0634 2,050 110 1,893 79 0 0 0 0 0 0 158 174 0 0 0 0 0 0 0 347 0 0 4,811
WR 26 Edge 0.031 1,935 323 516 32 0 0 0 0 0 32 32 32 0 0 0 0 0 0 0 129 0 0 3,032
WR 43 Center 0.0634 1,514 126 536 0 0 0 0 0 0 0 0 0 0 0 0 0 0 32 0 0 0 0 2,208
WR 43 Edge 0.0248 2,661 0 1,371 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4,032
WR 55 Center 0.0634 7,476 489 2,539 0 2,082 63 4,606 0 221 0 0 694 0 0 0 0 0 0 0 0 0 0 18,170
WR 55 Edge 0.0248 4,113 121 2,379 0 81 0 444 0 121 0 0 0 0 0 0 0 0 0 0 0 0 0 7,258
WR 59 Center 0.0495 1,273 343 2,747 20 0 0 0 0 0 0 0 0 0 0 0 81 0 0 0 0 0 0 4,465
WR 59 Edge 0.0248 0 1,492 0 81 0 0 0 0 0 0 0 0 0 0 0 161 0 0 0 0 0 0 1,734
46,750 55,236 41,417 2,373 13,305 1,355 21,464 599 7,311 361 6,006 2,627 710 63 784 321 1,005 95 252 523 426 16 202,999
83
84
Supplemental Table 6: Species catch per unit effort for survey 7 on 4/30/2012. Catch per unit effort was calculated using the
surface area of the net, depth of the water, and length of the sweep to calculate a total water volume sampled. Species catch was
divided by volume swept to calculate species count per m3 of water. Use the species CPUE and volume swept in the table to back
calculate original counts. Abbreviations follow those of Table 4.
Site Pool SweepVolume
Swept Dumo Ostr Simo Cycl
L.
Cop
L.
Occ
L.
tyr
Clad
E
H.
EisMoina
L.
bra
Clad
H
Clad
G
Clad
F
Clad
KCyz
Clad
J
Clad
ITotal
KF 13B Center 0.0806 25 310 62 12 397 136 1,179 0 87 2,618 124 0 0 0 732 12 310 0 6,005
KF 13B Edge 0.0806 844 2,084 546 0 1,290 0 3,176 50 50 36,179 99 0 0 0 2,432 0 0 0 46,749
KF 204 Center 0.0806 3,275 2,084 6,005 199 74 0 7,692 1,042 25 2,382 0 12 12 62 12 0 0 25 22,903
KF 204 Edge 0.0806 1,030 558 1,861 62 223 0 5,310 707 74 1,514 0 0 0 0 0 0 0 0 11,340
KF 49 Center 0.0806 248 248 3,375 0 99 0 2,730 0 0 36,328 0 0 0 50 0 0 0 0 43,077
KF 49 Edge 0.0806 1,228 248 4,839 87 0 0 620 161 25 9,045 0 0 0 0 0 0 0 0 16,253
KF 56 Edge 0.0322 16,646 2,857 31,180 0 0 0 870 0 0 1,863 0 0 62 93 0 0 0 0 53,571
MF CP Center 0.0806 447 943 12,457 2,730 0 37 0 0 50 2,084 0 0 0 0 0 0 0 0 18,747
MF CP Edge 0.0806 744 596 11,911 4,516 0 50 0 0 0 13,548 0 0 0 0 0 0 0 0 31,365
MF DP Edge 0.0806 186 99 2,283 87 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2,655
MF UCD1 Edge 0.0483 0 1,739 83 1,242 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3,064
MF UCD2 Center 0.0806 7,097 844 41,538 298 0 12 0 0 0 0 0 0 0 0 0 0 0 0 49,789
MF UCD2 Edge 0.0645 3,287 434 8,124 186 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12,031
MF UCD3 Center 0.0806 2,382 1,290 32,407 347 0 0 0 248 50 0 0 0 50 0 0 0 0 0 36,774
MF UCD3 Edge 0.0645 4,589 1,364 26,233 558 0 0 0 434 0 0 0 0 0 0 0 0 0 0 33,178
MT 21 Center 0.0806 471 25 695 0 0 0 385 149 0 0 12 0 0 0 0 0 0 0 1,737
MT 21 Edge 0.0645 2,016 124 3,287 0 16 0 605 527 0 0 16 47 0 0 0 0 0 0 6,636
MT 26 Center 0.0645 50 1,290 3,672 0 0 0 993 298 0 63,375 0 0 0 0 248 0 744 0 70,670
MT 26 Edge 0.0806 16 1,488 4,713 0 0 0 248 107,783 0 96,992 0 0 0 0 372 0 0 0 211,612
WR 10 Center 0.0806 6,055 993 2,581 1,141 1,439 0 2,481 0 0 32,357 0 0 0 0 0 12 0 0 47,060
WR 10 Edge 0.0645 15,008 1,178 4,403 2,295 0 0 1,612 62 0 39,070 0 0 0 0 0 0 0 0 63,628
WR 26 Edge 0.0806 7,047 298 695 0 0 0 0 6,055 0 187,990 0 0 0 0 0 0 0 0 202,084
WR 43 Edge 0.0806 6,948 596 1,687 199 298 0 50 298 0 12,407 0 0 0 0 0 0 0 0 22,481
WR 55 Center 0.0645 11,535 372 4,341 0 124 0 2,605 15,814 0 29,209 0 0 0 0 558 0 0 0 64,558
WR 55 Edge 0.0483 25,590 0 6,874 0 83 0 1,739 14,244 0 127,536 0 0 0 0 0 0 0 0 176,066
Total 116,763 22,064 215,850 13,958 4,044 236 32,294 147,872 360 694,497 251 59 124 205 4,355 25 1,055 25 1,254,035 8
4
85
Supplemental Table 7: Species catch per unit effort for copepod species counts for the 2011 survey. Copepods were the only
group counted after the 2011 season; all other groups were examined for species presence. Catch per unit effort was calculated using
the surface area of the net, depth of the water, and length of the sweep to calculate a total water volume sampled. Species catch was
divided by volume swept to calculate species count per m3 of water. Use the species CPUE and volume swept in the table to back
calculate original counts. Abbreviations follow those of Table 4.
Site PoolVolume
Swept (m^3)Depth (m) pH
DO
(% O2)L.Cop L.tyrr H.Eise H.cop H.cad Total
KF 2 0.2015 0.1016 7.85 118.7 0 233 417 0 0 650
KF 13B 0.2015 0.1524 8.35 146.3 84 1,067 60 164 596 1,970
KF 204 0.2015 7.85 81.0 0 635 486 10 491 1,623
KF 49 0.2015 0.9144 7.92 96.8 0 114 119 20 313 566
KF 56 0.2015 7.82 116.9 25 60 35 35 20 174
MF CP 0.2015 0.1270 9.00 140.0 0 0 0 0 0 0
MF DP 0.2015 7.63 0 268 94 20 0 382
MF UCD1 0.2015 7.60 104.7 114 1,067 342 184 218 1,926
MF UCD2 0.2015 0.2286 7.80 120.0 0 531 184 30 20 764
MF UCD3 0.2015 0.2032 7.80 116.0 0 0 0 0 0 0
MT 3 0.2015 0.1778 8.10 117.0 0 0 0 0 74 74
MT 19 0.2015 0.2286 8.93 128.3 0 0 0 0 1,846 1,846
MT 21 0.2015 0.0762 8.04 149.9 0 0 337 0 0 337
MT 25 0.2015 0.1778 8.86 137.2 0 0 0 0 65 65
MT 26 0.2015 0.5334 8.16 101.9 0 0 581 0 0 581
WR 10 0.2015 6.90 0 65 1,136 25 620 1,846
WR 26 0.2015 0.2286 6.92 89.3 0 0 0 0 675 675
WR 43 0.2015 0.1524 11.20 92.0 1,385 397 30 45 308 2,164
WR 55 0.2015 0.2032 7.95 123.0 258 109 223 20 89 700
Total 1,866 4,546 4,045 551 5,335 16,342
85
86
R² = 1
R² = 1
R² = 0.0097
R² = 0.0099 R² = 0.09
R² = 1
Depth Conductivity Surface Area
Dep
thC
onduct
ivit
yS
urf
ace
Are
a
Supplemental Figure 1: Draftsman plot for depth, conductivity, and surface area for survey 5 on 3/30/2012. The draftsman plot
was used to check for correlations of variables with each other for preparation of CCA. All data has been natural log transformed.
86
87
R² = 0.8435
Z-
Score
Depth
R² = 0.857
Conductivity
R² = 0.5717
Surface Area
Supplemental Figure 2: Normal probability graphs for depth, conductivity, and surface area for survey 5 on 3/30/2012. The
normal probability plots were used to check for data normality for preparation of CCA. All data has been natural log transformed.
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