NUTRIENT ADDITION EFFECTS ON VERNAL POOL COMMUNITIES
Carrie Lee Lessin
B.S., University of California, Irvine, 2005
THESIS
Submitted in partial satisfaction of
the requirements for the degree of
MASTER OF SCIENCE
in
BIOLOGICAL SCIENCES
at
CALIFORNIA STATE UNIVERSITY, SACRAMENTO
SPRING
2010
NUTRIENT ADDITION EFFECTS ON VERNAL POOL COMMUNITIES
A Thesis
by
Carrie Lee Lessin
Approved by:
__________________________________, Committee Chair
Dr. Jamie Kneitel
__________________________________, Second Reader
Dr. William Avery
__________________________________, Third Reader
Dr. Ronald Coleman
Date:____________________
ii
Student: Carrie Lee Lessin
I certify that this student has met the requirements for format contained in the
University format manual, and that this thesis is suitable for shelving in the Library
and credit is to be awarded for the thesis.
___________________________, Graduate Coordinator
Dr. James W. Baxter
Department of Biological Sciences
iii
_________________
Date
Abstract
of
NUTRIENT ADDITION EFFECTS ON VERNAL POOL COMMUNITIES
by
Carrie Lee Lessin
As the human population grows, there is an influx of nutrients to aquatic
systems due to urbanization, agricultural practices and other sources of pollution.
Therefore resource availability, which drives productivity, also changes. Whether
species diversity is a function of productivity has eluded researchers; however,
aquatic systems show a trend towards a unimodal relationship. There have been
several hypotheses which attempt to describe the underlying mechanisms of a
unimodal curve. The More Individuals Hypothesis (MIH) predicts that
communities supporting more individuals will have higher species richness since
extinctions due to stochastic events are less likely within any given trophic level.
The Oksanen, Fretwell, Arruda, and Niemala (or OFAN) hypothesis states that new
trophic levels can only be added once a biomass threshold controlled by resources
is reached. The OFAN model is unique in that it uses a “bottom-up” approach to
predict how species within each of the trophic levels will respond to an increase in
productivity.
iv
While the patterns predicted by the OFAN hypothesis have been observed in
many systems, it is unknown whether these patterns and mechanisms operate in the
threatened ecosystem of California vernal pools. Therefore this experiment
assessed how species richness and abundance changes over a nutrient gradient and
investigated whether the patterns were consistent with the OFAN model.
Mesocosms lined with vernal pool soil received one of five treatments, a
control and four nutrient addition treatments, creating a gradient for nitrogen and
phosphorus levels. Macro-invertebrates, microorganisms, and abiotic variables
were collected and recorded every two weeks for three months. Repeated measures
ANOVA were used to compare treatments to test for the effects of resource
treatments on the abundance and species richness.
Organismal abundance increased species richness in accordance to the MIH,
however abiotic variables affected species richness. The prey trophic level was not
affected by nutrients while the predator trophic level increased with nutrients as
predicted by the OFAN model. Nutrient addition did not affect abundance of vernal
pool organisms, nor did nutrient treatments significantly affect the total number of
trophic levels. The effects of nutrient addition were partially consistent with the
predictions made by the OFAN model in vernal pool mesocosms.
__________________________________, Committee Chair
Dr. Jamie Kneitel
___________________________
Date
v
ACKNOWLEDGMENTS
This project would not have been possible without the guidance and
expertise of my thesis advisor, Jamie Kneitel. I knew I was entering the right
graduate program, when I met Jamie. I wanted to work with aquatic
microorganisms and invertebrates living in vernal pools, and his excitement toward
my area of research was exciting. I have appreciated his positive attitude, patience
and friendly demeanor throughout my project. His intuitive insight, helpful
feedback and accessibility have guided me through the writing process. Throughout
my graduate career, his eagerness for me to excel has been encouraging and
heartening. He has shaped me into a better ecologist.
I would also like to thank my committee members Bill Avery and Ron
Coleman. Bill Avery provided me with friendly guidance while I learned the ropes
of teaching biology. Ron Coleman’s dedication to science is an inspiration and he
encourages students to explore the broader impacts of their findings. Both William
and Ron were open and friendly and provided me with valuable comments
throughout my thesis drafts.
I would like to take this opportunity to thank my family and friends for all
of their love, support and encouragement. Thank you, dad, for encouraging me to
take a sample of water from our Koi pond in middle school to see what kind of
vi
interesting creatures I could find. Thank you, mom, for procuring a microscope for
me to use and encouraging me in my love of nature. Thank you both for your
patience when I continuously called for you to come upstairs and see what kind of
interesting microorganism I had found. Without your encouragement none of this
would have been possible.
In addition, I want to give a special thanks to CalTrans whose permission to
access vernal pool soil opened up this avenue of research.
vii
TABLE OF CONTENTS
Page
Acknowledgments.....................................................................................................vi
List of Tables.............................................................................................................ix
List of Figures............................................................................................................x
INTRODUCTION......................................................................................................1
Study System………………………………………………………………..4
Objectives…………………………………………………………………...7
METHODS.................................................................................................................9
Statistical Analysis.......................................................................................14
RESULTS.................................................................................................................16
Treatment Effects on Abiotic Variables………..….………………………16
Fauna of Mesocosms………………………………………………………16
Treatment Effects on Biotic Variables…..………………………………...16
More Individuals Hypothesis (MIH)………………………………………21
OFAN Hypothesis………………………………….….…………………..21
DISCUSSION..........................................................................................................32
Literature Cited........................................................................................................38
viii
LIST OF TABLES
Page
Table 1. Nutrient addition levels added to each treatment every two weeks...……12
Table 2. Statistical summary of ANOVAR results for between-subject
effects of treatment for each dependent variable from week two
through week 12.........................................................................................17
Table 3. Species were divided into predator and prey categories for each
treatment level……………………………………….…………………...18
Table 4. Species were divided into predator and prey categories for each
treatment level…………………………………………..………….…….19
.
Table 5. Species were divided into functional groups…………………………….20
Table 6. Summary of backward stepwise multiple regressions used to
assess the relationship dependent variables to the parameter....................27
Table 7. Statistical summary of ANOVAR results for between-subject
effects of treatment for each dependent variable from week two
through week 12.……………...….………………………………...…….30
Table 8. Statistical summary of MANOVA results for between-subject
effects of treatment for each dependent variable……………...................31
ix
LIST OF FIGURES
Page
Figure 1. The Oksanen, Fretwell, Arruda, and Niemala (or OFAN) model
predicts species richness or the abundance of individuals within each
trophic level (y-axis) across a productivity gradient (x-axis)
(Modified from Power 1992)......................................................................8
Figure 2. Site map of donor vernal pool located southeast of Sacramento,
California, United States of America…......…………………………….10
Figure 3. Mean total species richness in vernal pool mesocosms through the
experimental period..................................................................................22
Figure 4. Mean total abundance of organisms in vernal pool mesocosms
through the experimental period..............................................................23
Figure 5. Prey abundance in vernal pool mesocosms significantly positively
influenced prey species richness in accordance with the MIH
(Week 12)…………………..……………………………………………25
Figure 6. Mean prey abundance in vernal pool mesocosms through the
experimental period…………………………………………………….26
Figure 7. Mean predator species richness in vernal pool mesocosms through
the experimental period……………………...........................................28
Figure 8. Mean prey species richness in vernal pool mesocosms through the
Experimental period…………………….................................................29
x
1
INTRODUCTION
Nutrient effects on ecosystems have long been a focal point of ecological
research (Elton 1927, Lindeman 1942, Heathwaite et al. 1996, Smith and Schindler
2009). These effects are also becoming a conservation concern as the human
population grows: nitrogen and phosphorous concentrations have increased to up to
twenty times background concentrations in some areas due to human activities
(Heathwaite et al. 1996, Schindler 2006, Smith and Schindler 2009). Both
urbanization and agricultural practices are nonpoint sources that can contaminate
watersheds when runoff occurs, creating eutrophication (nutrient overloading of
aquatic systems) (Vitousek et al. 1997, Paerl 1998). Therefore, it is crucial to study
how nutrient addition will affect community composition and ecosystems
functioning.
Resource availability can regulate productivity (the rate of energy flow),
species abundance, the number of trophic levels, and species diversity (Elton 1927,
Lindeman 1942, Abrams 1993). The relationship between productivity and species
diversity (as measured by the total number of species) has been the focus of
research for decades (Tilman 1993, Declerck et al. 2007). Productivity can
increase, decrease, have a unimodal relationship, or not affect species diversity
(Waide et al. 1999, Mittelbach et al. 2001). Waide et al. (1999) offers mechanisms
such as the species energy theory and interspecific competition in heterogeneous
habitats to explain how productivity increases species diversity. Waide et al. (1999)
2
also offers mechanisms to explain decreases such as evolutionary immaturity,
homogenization of habitat, and instability.
A unimodal relationship is the most common pattern found in nature
(Waide et al. 1999, Mittelbach et al. 2001) and there are several underlying
mechanisms to explain why it exists (Abrams 1995, Mittelbach et al. 2001). For
example, the More Individuals Hypothesis (MIH) predicts that as productivity is
increased, more individuals can inhabit a given system. Therefore, the abundance
of rare species is enhanced (Abrams 1995, Srivastava and Lawton 1998) which
decreases extinction rates resulting from stochastic events (Srivastava and Lawton
1998). As a result, more species can then persist in highly productive systems
(Abrams 1995, Srivastava and Lawton 1998). However, when extreme levels of
productivity reach a threshold, a dominate competitor is expected to competitively
exclude all other species causing species richness to fall (Gause 1934, Abrams
1995). Other hypotheses proposed to explain the unimodal relationship between
productivity and species diversity are disturbances (Kondoh 2001), tradeoffs
between competitiveness and resistance to predators (Leibold 1996), and an
increase in spatial heterogeneity (Peterson and Grimm 1992, Moore et al. 2004).
Most mechanisms attempting to explain the unimodal relationship between
productivity and species diversity, like MIH, operate at a singe trophic level
(Abrams 1995, Srivastava and Lawton 1998, Kondoh 2001). An increase in
productivity can result in the community’s ability to support additional trophic
3
levels. This is because an average organism utilizes about ten percent of the energy
they gain from consuming their prey and higher productivity can translate to more
prey for a consumer (Elton 1927). With the addition of trophic levels, the effects of
predators (“top-down” processes) are then introduced and can alter lower trophic
levels in a variety of ways. The Hairston, Smith, and Slobodkin (or HSS)
hypothesis predicts that the grazers (the middle trophic level) are never resource
limited and their population densities are controlled by predators (Hairston et al.
1960, Power 1992). The predators are therefore indirectly controlling the plant
population densities (Hairston et al. 1960).
The Oksanen, Fretwell, Arruda, and Niemala (or OFAN) hypothesis
(Oksanen et al. 1981) modified the HSS hypothesis by predicting that the addition
of a new trophic level only occurs when a biomass threshold controlled by
resources is reached (Oksanen et al. 1981; Figure 1). Biomass of the primary
producer increases with an increase of productivity. Once the productivity
threshold is reached, a consumer trophic level invades and prevents the primary
producers from further increases in biomass due to herbivory (Figure 1). The
consumer increases until a secondary consumer trophic level is introduced. The
secondary consumer and the primary producers (now released from the primary
consumer) increase in biomass while the primary consumer’s biomass stabilizes
due to carnivory (Oksanen et al 1981, Power 1992). The OFAN hypothesis
4
highlights the importance of the interactions between productivity and predation in
a given system (Polis and Strong 1996).
The OFAN model assumes that each trophic level as a whole behaves like a
single species. The argument is that organisms face a trade-off between adaptations
which specialize in efficient nutrient uptake (be it photosynthesis, herbivore or
carnivory) and the ability to uptake nutrients using multiple strategies (Oksanen et
al. 1981). Since the presence of an omnivore, adaptive foraging, predation
resistance and density-effects on the top trophic level are not taken into account,
they can lead to patterns other than those predicted by the OFAN model (Abrams
1993). In addition, few studies have tested whether the same model can be applied
to species diversity (Yee et al. 2007). While the patterns predicted by the OFAN
hypothesis have been observed in many systems, it is still unclear whether they can
be generalized to all ecosystems, including the threatened ecosystem of California
vernal pools.
Study System
Vernal pools are ephemeral wetlands found in shallow depressions with an
underlying impermeable substrate which prevents water from percolating through
the soil (Stuhr et al. 1994). Vernal pools, as a habitat, have four phases (Zelder
1987, Stuhr et al. 1994). The first is the wetting phase which comes with the onset
of the winter rains, usually in November and continuing through March. The
second is the aquatic phase, which occurs when the pools are inundated with
5
increasing rainfall. The third is the drying phase, usually occurring in April. Plants
flower forming concentric rings around the pool in accordance to the individual
species’ adaption to reside at a particular depth and inundation period (Zelder 1987,
Stuhr et al. 1994). Many fauna species release dormant cysts during this phase. The
fourth is the drought phase which lasts from approximately May to November
when there is no rainfall. The soil dries and the plants within the vernal pool set
seed and die (Zelder 1987, Stuhr et al. 1994).
Obligate vernal pool species must be adapted to complete their lifecycle
during the inundation phase of the vernal pool (Blaustein and Schwartz 2001,
Calhoun and deMaynadier 2008). One of the survival strategies employed by
zooplankton and some small invertebrates is the creation of cyst banks (storage
effect). Species of copepods, Daphnia, and fairy shrimp produce cysts that can
survive during unfavorable conditions, including but not limited to the drying of the
pool. Once the pool fills with water, the portion of the egg bank which receives the
correct environmental cues undergoes hatching. Studies have shown that the
photoperiod, temperature, and changes in the osmotic and oxygen values act as
important environmental cues for some species (Brendonck and De Meester 2003).
Due to frequent spatial fragmentation and limited dispersal by species,
vernal pools contain many endemic species (Keeley and Zedler 1998). Spatial
fragmentation and limited dispersal make vernal pool species especially vulnerable
to local extinctions due to competitors, environmental stochasticity, or predation
6
and allopatric speciation as species adapt to individual vernal pools (King et al.
1996). One study on the diversity of aquatic invertebrates which sampled 58 vernal
pools found an average of 9.6 species within each pool. However, 50.7% (34 out of
67) of the species found in the study were endemic to California (Simovich 1998).
Endemic species contribute to the high β diversity among vernal pools (Keeley and
Zedler 1998, De Meester et al. 2005), making vernal pools critical habitat for a
disproportionately large number of species within a region (De Meester et al.
2005). In addition, distance among pools does not predict vernal pool community
similarity (King et al. 1996). Therefore, local conditions, rather than dispersal,
appear to be the primary factor affecting species diversity patterns. Few studies,
however, have examined this experimentally.
Vernal pools have discrete borders and small size, compared to other
ecosystems, making vernal pools useful model systems for studying food webs
(Blaustein and Schwartz 2001, De Meester et al. 2005). In addition, their
inundation cycle makes vernal pools difficult for pest species to invade (Dittes and
Guardino 2006). Therefore, they can offer a unique outlook into how ecosystems
work. However, there is a gap in the literature as nothing is known about the roles
bottom-up or top-down regulation play in this system or about their food web
interactions in general (Kneitel and Lessin 2010, in press).
Mesocosms (artificial containers) offer a unique opportunity to exploit the
benefits of both field and laboratory experiments. They permit the manipulation of
7
nutrients which allows a more detailed glimpse into the mechanisms controlling
community regulation without endangering pristine vernal pools or their threatened
inhabitants. Since mesocosms are open systems and are influenced by abiotic and
biotic conditions, mesocosms more closely mimic a vernal pool’s environment than
laboratory counterparts. They also allow data to be collected on population and
ecosystems as a whole (Odum 1984).
Objectives
Up until now most studies in vernal pools have been observational. This
study is unique in that it will attempt to quantify how bottom-up regulation, via
nutrients, affects vernal pools by using a manipulative experimental design. This
study assesses how species richness and abundance changes over a nutrient
gradient and determine whether or not the patterns are consistent with the OFAN
model. Specifically, I tested four hypotheses. The first hypothesis was that nutrient
addition would result in abundance patterns that depend upon trophic level number
(Figure 1). The second hypothesis was that nutrient addition would increase species
diversity within each trophic level and reflects the abundance patterns predicted by
the OFAN model (Figure 1). The third hypothesis was that an increase of nutrients
would increase the number of trophic levels within vernal pools (Figure 1). The last
hypothesis was that as abundance increases species richness would also increase in
accordance to the MIH.
Species Richness or
Abundance
8
Figure 1. The Oksanen, Fretwell, Arruda, and Niemala (or OFAN) model predicts
species richness or the abundance of individuals within each trophic level (y-axis)
across a productivity gradient (x-axis) (Modified from Power 1992).
9
METHODS
In the fall of 2007, thirty mesocosms were established in the California
State University, Sacramento arboretum. Circular troughs (38 liters) held the
mesocosms, or miniature man-made vernal pools.
The troughs were lined with soil removed from a vernal pool within the
Elder Creek Watershed in Sacramento County (Figure 2). Soil was collected from
random points within the vernal pool while covering the range of depth within the
vernal pool. The top six centimeters of soil were collected from the donor vernal
pool in order to ensure the presence of the egg bank (Brendonck and De Meester
2003).
The soil from the donor vernal pool was homogenized by mixing the soil in a
cement mixer. Mixing the soil, randomly distributed the cyst bank prior to
dispensing it to the mesocosms. Soil (7.5 liters) was distributed to each mesocosm
and then filled by rainfall.
The aquatic communities were allowed to establish before the addition of
nutrients. The experimental design consisted of five nutrient addition treatments,
and each was replicated six times. The treatments were randomly assigned to
mesocosms and assigned to blocks to prevent potential temporal effects due to
staggered design (Hurlbert 1984).
Due to time constraints because of the number of dependent variables,
measurements were collected one block (five mesocosms) a day. The experiment
10
Figure 2. Site map of donor vernal pool located southeast of Sacramento,
California, United States of America. Vernal pool (marked A) is located where
Excelsior Road intersects Jackson Highway (Highway 16). The GPS coordinates
are Latitude: 38.5194458 and Longitude: -121.2999984.
11
was maintained for three months from the end of winter through spring February to
May 2008, which approximated the natural length of vernal pool’s aquatic phase.
Each mesocosm received one of five nutrient-addition treatments (Table 1).
Nitrogen and phosphorus were added to nutrient addition treatments via an aqueous
solution of NaNO3 and KH2PO4 (Jardillier et al. 2005). In addition to a control with
no nutrients added, three treatments consisted of low, medium, and high levels of
nutrients, which reflected the natural gradient of nitrogen and phosphorus levels
found in local vernal pools (Yolo County Planning and public works department
and ESA 2005). The fifth treatment had an exaggerated amount of nutrients to
mimic urban runoff. Nutrient levels only approach this value when they are almost
dry (Yolo County Planning and public works department and ESA 2005).
Nutrient treatments were added twice a month to replace the nitrogen and
phosphorus back into the water column (Garg and Bhatnagar 2000). Nutrients were
added after the mesocosms were sampled. Water was also added as needed to
mesocosms to counter evaporation after the mesocosms were sampled. Abiotic
measurements were staggered a week and performed on odd weeks. These
measurements included: dissolved oxygen (DO, measured in mg/L), percent
dissolved oxygen (%), temperature (Celsius), and pH (using Oakton’s Portable
Waterproof pH/Dissolved Oxygen Meter 35632-Series). Conductivity (μS) and
total dissolved solids (tds, measured in ppm) were also measured (using
pH/Conductivity/TDS/C/F Meter/pH/CON 300 Series by Oakton). Nutrient levels
12
Table 1. Nutrient addition levels added to each treatment every two weeks.
Control
Low
Medium
High
Very High
Nitrate(mg/L)
None
0.25
0.5
1
2
Phosphate (mg/L)
None
0.25
1
2
4
13
were measured using HACH DREL/2800 Complete Water Quality Lab (HACH)
included mg/L phosphate (PO4), mg/L phosphorus (P), mg/L phosphorus pentoxide
(P2O5), mg/L nitrate-nitrogen (NO3-N), and mg/L nitrate (NO3).
Macro-invertebrates were sampled at the start of the experiment and every
other week for the duration of the experiment. Macro-invertebrates were quantified
by sweeping the surface and depth of the mesocosm with a 1mm mesh dipping net
(Chase 2003). Sweeping was standardized by using the same sweep pattern for the
same duration of time (ten seconds) to ensure comparability of macro-invertebrate
counts. The macro-invertebrates caught in the net were placed in a tray, identified,
and returned to the mesocosm. Unknown macro-invertebrates were photographed
to be identified in the lab. Macro-invertebrates that could not be identified by
photography and were caught on a subsequent day were placed in alcohol.
Dissecting scopes and identification keys were used for further identification.
A 20 mL sample of each treatment was processed for microscopic
organisms the same day. First, the sample was homogenized and a 1 mL subsample
was pipetted into a gridded Sedgewick Rafter Slide. The slide was scanned for all
protozoa and microbial species richness and abundance was recorded. After
analysis of the sample, it was returned to the appropriate mesocosm the same day.
Organisms were grouped into predator or prey categories. These categories
were further split into large predators, small predators, deposit feeders, filter
14
feeders, nonselective feeders, detritivores, and algivores (Pratt and Cairns 1985,
Colburn 2004).
Statistical Analysis
The mean species richness and abundance were calculated for all the
replicates within a treatment. The mean species richness and abundance for
predators and prey were calculated for all the replicates within a treatment. The
number of trophic levels and the abundance of each were calculated for all the
replicates within a treatment. Data were log-transformed to normalize data when
appropriate and square-root transformation was used to normalize phosphorus data.
Repeated-measures Analysis of Variance (ANOVAR) was used to test
treatment effects over time on abiotic variables including phosphorus, nitrogen,
temperature, pH, dissolved oxygen, and conductivity. An ANOVAR was conducted
to predict if prey species richness, prey abundance, predator species richness,
predator abundance, mosquito larvae abundance, and the number of trophic levels
differed among resource treatments over time. For all ANOVARs, a Hunyh-Feldt
test was to test compound symmetry (Mauchley’s test P<0.001) (Potvin et al. 1990,
Kneitel and Miller 2002). The symmetry assumption’s violation was small for most
variables (phosphorus, e=0.96; pH, e=0.87; conductivity, e=0.83; number of
trophic levels, e=1.00; total species richness, e=0.96; total abundance, e=0.89; prey
species richness, e=1.00; predator species richness, e=1.00; prey abundance,
e=0.73; predator abundance, e=0.75). Caution should be used when interpreting the
15
results for nitrogen (e=0.63), temperature (e=0.49), and dissolved oxygen (e=0.54)
because the e-values were lower indicating the symmetry assumption was violated.
Multiple Analysis of Variance (MANOVA) was used to test treatment
effects on species richness and abundance of predators and prey for week six and
week twelve. A linear regression was performed on predator abundance and
predator species richness and again on prey abundance and prey species richness
for week six and week twelve. Four backward stepwise multiple regressions were
performed for week six and twelve to predict which abiotic and biotic conditions
explained species richness and abundance of predators and prey. Abiotic variables,
predator species richness and predator abundance were independent variables for
prey species richness and abundance, while abiotic variables, prey species richness
and prey abundance were independent variables for predator species richness and
abundance.
An Analysis of Variance (ANOVA) was performed to test for differences
among resource treatments for the maximum number of trophic levels which
included large predators, small predators, deposit feeders, filter feeders,
nonselective feeders, detritivores, and algivores for both week six and week twelve.
A MANOVA was used to test treatment effects on the individual trophic levels for
week six and week twelve. Data were analyzed using SPSS 17.0 software.
16
RESULTS
Treatment Effects on Abiotic Variables
Nutrient addition significantly increased phosphorus within the water
column (P<0.001), while nitrogen levels were not significantly affected by nutrient
treatments (P=0.78, Table 2). Phosphorus also increased within the water column
through time (P<0.001) and had a significant time-treatment interaction (P=.005).
Nutrient addition did not significantly affect dissolved oxygen (P=0.59),
conductivity (P=0.92), temperature (P>0.99), and pH (P=0.78) through time. As the
season progressed, time did significantly affect phosphorus, nitrogen, temperature,
pH, dissolved oxygen, and conductivity (P<0.01, Table 2). Block effects were
found to be significant in most analyses.
Fauna of Mesocosms
Fauna was categorized as predator or prey (Table 3 and 4). These categories
were further split into large predators, small predators, deposit feeders, filter
feeders, nonselective feeders, detritivores, and algivores (Table 5, Pratt and Cairns
1985, Colburn 2004).
Treatment Effects on Biotic Variables
Treatments did not affect total species richness or abundance over the
course of the experiment (ANOVAR: df=4, F=1.04, P=0.41 and ANOVAR: df=4,
F=0.85, P=0.51, Figure 3). Total abundance declined through time (ANOVAR,
df=4.44, F=4.37, P=0.002, Figure 4). However, oviposited species, such as
17
Table 2. Statistical summary of ANOVAR results for between-subject effects of
treatment for each dependent variable from week two through week twelve.
Significant P-values are in italics.
Treatment
Dependent
variable
Phosphorus
Nitrogen
Temperature
pH
Dissolved
Oxygen
Conductivity
Mosquito
Larvae
Trophic Levels
TreatmentXTime
Interaction
Time
F(4,20)
34.12
0.44
0.01
0.44
P
<0.001
0.78
>0.99
0.78
F(5,25)
9.05
4.24
32.01
41.04
P
<0.001
0.007
<0.001
<0.001
F(20,100)
2.24
0.70
0.06
0.51
P
0.005
0.78
>0.99
0.95
0.71
0.23
0.59
0.92
8.43
1084.38
<0.001
<0.001
0.87
1.51
0.57
0.13
0.79
0.87
0.54
0.50
3.64
2.08
0.02
0.07
1.20
0.99
0.27
0.43
18
Table 3. Species were divided into predator and prey categories for each treatment
level. Abundances were totaled and the six replicates were averaged. This table
presents organisms for week six.
Red Copepod
Blond Copepod
Large Daphnia
Mesostoma
Nematode
Chaoborus (Phantom
Midge)
Chironomid sp 1
Tadpole Shrimp
Dytiscus larva
Dytiscus adult
Clam shrimp
Chironomid sp 2
Unknown oviposit
larvae
Ostracods
Small Daphnia
Small Red Copepod
Immature Copepod
Halteria
Euglena
Lepocinclis
Paramecium
Rotifer sp 1
Rotifer sp 2
Polyarthra
Bulbous Rotifer
Peranema
Litonotus
Chaetonotus sp.
(Gastrotrich)
Oxytricha
Ameoba
Filamentous ameoba
Lobopodia
Raphidophrys
Chrysomonad
Unknown Ciliates
Unknown Flagellates
Control
1.8
0.8
7.5
Low
2.3
1.2
9
0.2
0.5
1.5
3.7
0.3
0.5
3
Medium
1.3
0.2
1.2
0.2
0.2
2.2
2.3
0.2
High
1
0.3
10.2
0.7
1
1.5
1.2
0.2
0.2
0.3
0.2
6.3
53.1
59.8
4.2
0.2
Very
High
1.3
1.2
3.5
0.8
3.2
1.7
0.3
1.2
5.2
4.8
1.2
12.5
52.8
97.3
6.7
0.2
4.4
5.8
48.6
82.3
5.5
11.8
49.3
79.5
2.3
11
68.3
119.8
7.7
0.2
0.5
0.2
0.5
0.3
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.5
0.2
0.2
0.2
0.4
0.2
0.3
0.2
0.2
0.4
0.3
0.2
2.8
1.3
47.5
24.2
0.8
37
1.8
1.1
58.2
0.5
6.3
2.9
36.8
0.2
1.5
0.7
56.5
Predator/Prey
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
19
Table 4. Species were divided into predator and prey categories for each treatment
level. Abundances were totaled and the six replicates were averaged. This table
presents organisms for week twelve.
Control
Chaoborus (Phantom
Midge)
Chironomid sp 1
Chironomid sp 2
Mosquito Larva
Dytiscus larva
Dytiscus adult
Mayfly larva
Unknown oviposit
larvae
Small Daphnia
Ostracod
Halteria
Paramecium
Rotifer sp 1
Ploima (Rotifer
Filinia (Rotifer)
Bulbous Rotifer
Hexarthra (Rotifer)
Bdelliod Rotifer
Litonotus
Chaetonotus sp.
(Gastrotrich)
Oxytricha
Vorticella
Nebela
Ameoba
Filamentous ameoba
Pseudodiffugia
Diffugia
Volvox
Chrysomonad
Peranema
Cyclidium
Unknown Flagellates
Unknown Ciliates
1.3
1.8
19.3
38.8
Low
Medium
2
4.5
4
46
0.2
2.2
8.8
2.4
35.2
0.2
0.3
High
3.6
4.3
3.4
45.3
0.3
2.3
53.3
9.8
12.5
0.2
0.2
0.2
3
Very
High
0.8
5.5
1.8
24
1.2
0.2
0.8
0.2
21
1.7
0.2
58.5
16.5
1.2
0.5
0.7
2.3
11.8
8.8
1
75
104
3.3
0.2
0.2
1.3
0.3
0.2
0.5
0.2
0.2
0.2
0.2
0.8
1.2
0.2
0.5
11.2
0.2
3.6
3.1
0.5
0.3
4.4
0.2
0.3
4.7
0.3
0.2
0.2
0.5
0.8
0.3
0.7
0.5
0.2
0.5
3
5.1
0.3
1.3
0.2
0.2
0.2
0.7
0.3
0.3
0.3
5.8
9.3
7.3
3.2
0.3
4.2
12.8
0.3
Predator/
Prey
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
Prey
20
Table 5. Species were divided into functional groups.
Large
Predators
Small
Predators
Deposit
Feeders
Filter Feeders
Nonselective
Omnivores
Diacyclops
Blond Copepod
Dark Copepod
Mesostoma
Chubby Flatworm
BlueGreen
Flatworm
Whipping
Nematode
Mosquito larvae
Dytiscus larva
Dytiscus adult
Chaoborus
Small Red
Copepod
Copepod in micro
Immature
Copepod
Immature
mosquito
mosquito larva
Chironomid sp
Nonselective
Omnivores
Continued
Polyarthra
Filinia sp (Rotifer)
Platyias
Bulbous Rotifer
Hexarthra
Bdelliod Rotifer
Stentor
Actinopoda
Raphidophrys
Radiolaria
Dileptus
Detritivores
and
Bacterivores
Paramecium
Litonotus
Oxytricha
Hypotrichide
Zoomastigophorea
Vorticella
Large Ostracods
Small Ostracods
brown ostracod
tiny ostracod
Chironomid sp
Nematode
Fairy Shrimp
Tadpole Shrimp
Cyzicus sp.
Large Daphnia
Small Daphnia
Daphnia micro
mosquito larvae
Nebela
Vahlkampfia
Filamentous ameoba
Myriophrys
Lithocella
Pseudodiffugia
Diffugia
Proteomyxide
Centropxis
Codosiga
Spirostomum
Peranema
Colpidium
Rotifer sp 1
Ploima sp.
(Rotifer)
Rotifer sp 2
Cyclidium
Chaetonotus sp.
(Gastrotrich)
Halteria
Algivores
21
mosquito larvae, did increase over time (ANOVAR, df=20, F=3.64, P=0.02, Table
2).
More Individuals Hypothesis (MIH)
Within trophic levels, species richness increased linearly with abundance in
accordance to the MIH (Prey: R2=0.61, y=0.16+0.12x, P<0.001, Predator: R2 =
0.63, y = 0.21 + 0.27x, P < 0.001, Figure 5).
Predator and prey species richness and abundance did respond to some
abiotic variables (Table 6). Increasing nutrients did not increase abundance of
predators (P=0.89) or prey (P=0.61, Figure 6). Predator abundance marginally
decreased with conductivity (P = 0.07), and in week 12, increased with dissolved
oxygen (P=0.03) and marginally decreased with nitrogen (P=0.057, Table 6).
Predator species richness was marginally increased by phosphorus (P=0.085) and
marginally decreased by pH (P=0.06) and conductivity (P=0.08, Table 6). At the
end of the experiment, predator species richness increased with dissolved oxygen
(P=0.004) and marginally decreased with nitrogen (P=0.06, Table 6). Prey species
richness decreased with temperature (P=0.008, Table 6). Prey abundance increased
with pH (P= 0.04) and decreased with dissolved oxygen (P = 0.03) but towards
week 12 decreased with pH (P=0.02, Table 6).
OFAN Hypothesis
Nutrient addition significantly increased predator species richness (P = 0.04,
Figure 7), while prey species richness did not respond to treatments (P=0.90, Figure
22
Species Richness (Average # of
Species/Treatment)
of
)
25
20
15
Control
Low
Medium
High
Very High
10
5
0
0
2
4
6
8
10
12
Time (weeks)
Figure 3. Mean total species richness in vernal pool mesocosms through the
experimental period. Time is on the x-axis in weekly intervals and species richness
of vernal pool mesocosms is on the y-axis. The colored bars represent the
corresponding nutrient treatment levels. Standard deviation was used for error bars
(+/- 1 SD).
23
30
20
15
Control
Low
Medium
High
Very High
(SQRT)
Abundance (SQRT)
25
10
5
0
0
2
4
6
8
10
12
Time (Weeks)
Figure 4. Mean total abundance of organisms in vernal pool mesocosms through
the experimental period. Time is on the x-axis in weekly intervals and abundance
of organisms in vernal pool mesocosms is on the y-axis. The abundance values
were transformed via the square root. The colored bars represent the corresponding
nutrient treatment levels. Standard deviation was used for error bars (+/- 1 SD).
24
8). Predator and prey abundance did not respond to treatments (Table 7). Species
richness declined through time for both trophic levels, although there were no timetreatment interactions (Table 7). The number of all trophic groups (large predators,
small predators, deposit feeders, filter feeders, nonselective feeders, detritivores
and algivores) did not respond to nutrient addition over the course of the
experiment (P=0.50, Table 5).
Nutrient treatments affected several individual trophic levels. Nutrient
addition increased algivores during week six (P=0.05, Table 8). Detritivores
significantly increased (P=0.048) and deposit feeders were marginally significant
(P=0.098) during week 12 (Table 8). Small predators, such as small copepods,
disappeared entirely by the end of the experiment.
Species Richness
25
Abundance
Figure 5. Prey abundance in vernal pool mesocosms significantly positively
influenced prey species richness within the mesocosms in accordance with the
More Individuals Hypothesis (or MIH). This linear regression depicts prey
abundance and prey species richness during week 12 of the experiment. R2 = 0.61,
y = 0.16 + 0.12x, P < 0.001.
.
26
25
15
10
Control
Low
Medium
High
Very High
(SQRT)
Abundance (SQRT)
20
5
0
0
2
4
6
8
10
12
Time (Weeks)
Figure 6. Mean prey abundance in vernal pool mesocosms through the
experimental period. Time is on the x-axis in weekly intervals and abundance of
prey organisms within the mesocosm is on the y-axis. The abundance values were
transformed via the square root. The colored bars represent the corresponding
nutrient treatment levels. Standard deviation was used for error bars (+/- 1 SD).
27
Table 6. Summary of backward stepwise multiple regressions used to assess the
relationship dependent variables to the parameter. Significant P-values are in
italics.
Dependent
variable
Prey Species
Richness
Week
5
12
Prey
Abundance
5
12
Predator
Species
Richness
5
12
Predator
Abundance
5
12
Parameter
None
Predator
Abundance
(PredAb)
Temperature
(Temp)
Predator
Species
Richness
(PredSp)
pH
Dissolved
Oxygen
(DO)
Predator
Abundance
(PredAb)
pH
Phosphorus
(P)
pH
Conductivity
(C)
Nitrogen (N)
DO
Prey Species
Richness
(PreySp)
Conductivity
(C)
Prey
Abundance
(PreyAb)
Nitrogen (N)
DO
R
0.57
Fvalue
6.37
Pvalue
0.05
Model
y=0.07 x PredAb –
0.93x Temp + 2.04
0.008
0.52
3.26
0.04
0.04
y=1.04 x PredSp +
10.50 x pH - 4.22 x
DO - 4.07
0.03
0.74
0.5
15.97
2.91
<0.001
0.02
0.09
0.06
y=0.52 x PredAb
- 5.71 x pH + 6.60
y=0.27 x P - 3.32 x
pH - 1.06 x C +
6.58
0.08
0.56
6.22
0.06
0.004
0.47
3.83
0.05
y=0.45 x DO - 0.22
x N – 0.03
y=1.26 x PreySp 2.49 x C + 7.22
0.07
0.76
11.89
<0.001
0.06
0.03
y=0.76 x PreyAb 0.90 x N + 1.32 x
DO – 0.89
28
6
5
Control
Low
Medium
High
Very High
4
3
2
Species)
Species Richness (# of Species)
7
1
0
0
2
4
6
8
10
12
Time (Weeks)
Figure 7. Mean predator species richness in vernal pool mesocosms through the
experimental period. Time is on the x-axis in weekly intervals and species richness
of vernal pool mesocosms is on the y-axis. The colored bars represent the
corresponding nutrient treatment levels. Standard deviation was used for error bars
(+/- 1 SD).
29
8
7
6
Control
Low
Medium
High
Very High
5
4
3
Species)
Species Richness (# of Species)
9
2
1
0
0
2
4
6
8
10
12
Time (Weeks)
Figure 8. Mean prey species richness in vernal pool mesocosms through the
experimental period. Time is on the x-axis in weekly intervals and species richness
of vernal pool mesocosms is on the y-axis. The colored bars represent the
corresponding nutrient treatment levels. Standard deviation was used for error bars
(+/- 1 SD).
30
Table 7. Statistical summary of ANOVAR results for between-subject effects of
treatment for each dependent variable from week two through week 12. Significant
P-values are in italics.
Treatment
Dependent variable
Prey Species
Richness
Prey Abundance
Predator Species
Richness
Predator
Abundance
F(4,25)
P
TreatmentXTime
Interaction
Time
F(5,25)
P
F(20,100)
P
0.27
0.69
0.89
0.61
3.49
8.98
0.006
<0.001
0.81
0.81
0.70
0.70
2.93
0.04
40.53
<0.001
0.62
0.89
0.28
0.89
2.78
0.04
0.63
0.85
31
Table 8. Statistical summary of MANOVA results for between-subject effects of
treatment for each dependent variable. Significant P-values are in italics.
Dependent variable
Large Predators
Small Predators
Deposit Feeders
Filter Feeders
Nonselective
Omnivores
Detritivores
Algivores
Week
6
12
6
6
12
6
12
F(4)
0.95
0.25
0.5
0.25
2.21
0.70
0.34
P value
0.45
0.91
0.74
0.91
0.1
0.60
0.85
6
12
6
12
6
12
0.85
0.31
0.59
2.79
2.85
0.27
0.51
0.87
0.67
0.05
0.05
0.90
32
DISCUSSION
Using the aquatic phase of California vernal pool ecosystem, I tested the
effects of nutrient (nitrogen and phosphorus) addition on invertebrate abundance
and richness. Organismal abundance (of aquatic invertebrates) increased with
species diversity in accordance with the More Individuals Hypothesis (MIH),
which predicts that an increase of nutrients will sustain higher abundances of each
species and therefore lead to a more diverse community (Abrams 1995, Srivastava
and Lawton 1998). In agreement with previous studies, species abundance
increased species diversity within both the predator and prey trophic levels (Hector
et. al. 1999, Findley and Findley 2001).
Contrary to the MIH predictions, nutrient addition did not increase
abundance in the predator and prey trophic levels, indicating that the MIH alone is
not the only mechanism explaining aquatic species richness in California vernal
pools. This is not the first study to find limited support for the MIH hypothesis.
Other variables play important roles in species diversity of a community
(Srivastava and Lawton 1998, Hurlbert 2004). Srivastava and Lawton (1998) found
productivity increased species richness but did not increase individuals within
treehole communities. Oviposited species, such as mosquitoes, influenced the
community composition by producing a variance in the number of larvae found
within productivity levels (Srivastava and Lawton 1998). The mesocosms of the
present study also had ovipositors. However, mosquito larvae abundance, the most
33
numerous ovipositor, was not statistically different among nutrient treatments. In
addition, ovipositing insects can affect competitive environment and other
interactions in a community that will ultimately affect species diversity patterns
(Spencer et. al. 1999, Resetarits 2005).
The Oksanen, Fretwell, Arruda, and Niemala (or OFAN) hypothesis
(Oksanen et al. 1981) was successful in predicting species richness patterns across
trophic levels. Prey species richness was not related to nutrients, while predator
species richness increased with nutrients. Several previous studies have reported
similar results supporting OFAN predictions. Yee et al. (2007) found species
richness of predators (consumers) increased with productivity while prey
(protozoan) species richness was not related to productivity in tree holes. In a
manipulative experiment, Kneitel and Miller (2002) similarly found that nutrients
did not affect bacteria species richness while protozoan species richness increased
with resource addition. This study did find evidence of bottom-up community
regulation and the lack of a significant increase of bacteria species richness may
have been due to high turn over in bacteria. Prey species within this study may also
have had high turnover. These results together support the general pattern of
resource effects alternating among trophic levels and the OFAN model is also
relevant to species richness.
While the OFAN model held predictive power for determining species
richness patterns, the number of trophic levels and abundance patterns did not
34
follow the predictions. Increasing nutrients did not affect the number of trophic
levels within the vernal pools. The OFAN model assumes that all species within
each trophic level behave homogeneously and argues that organisms face a tradeoff
between adaptations that specialize in efficient nutrient uptake and the ability to
uptake nutrients using multiple strategies (Oksanen et al. 1981). In reality, the
presence of omnivores (Kneitel 2007, Namba et al. 2008), size refugia (Chase
1999), adaptive foraging (Kondoh and Ninomiya 2009), within trophic-level trait
heterogeneity (Kneitel 2007), predation resistance (Thelaus et al. 2008) and
density-effects on the highest trophic level (Abrams 2009) can change how
resources affect trophic levels leading to patterns other than those predicted by the
OFAN model (Abrams 1993). Kondoh and Ninomiya (2009) found that resource
addition may not affect trophic levels and, in some cases, can decrease trophic
levels when adaptive foraging was included in a theoretical model. Species found
in the vernal pool mesocosms, like Chironomus species, have been documented to
use adaptive foraging in response to predator or resource abundance (Holker and
Stief 2005).
Predator and prey richness and abundance responses to abiotic
measurements were highly variable. However, there were some clear and consistent
patterns within predator richness and abundance. Other studies have found
decreased dissolved oxygen can result from increased resources (Kneitel and Miller
2004) and that predator species diversity and abundance declines with dissolved
35
oxygen (Long and Seitz 2008). In this study, predators decreased with lower
dissolved oxygen. Predator response to dissolved oxygen may be due to a trade-off
between respiration and foraging behavior. Predators are more susceptible to lower
dissolved oxygen as their mobility and speed creates higher oxygen demands (Long
and Seitz 2008). As a result of decreased oxygen, predator activity levels are
reduced leading to lower predation rates (Sagasti et al. 2001, Long and Seitz 2008).
This study successfully mimicked vernal pool communities using
mesocosms, which are commonly used for aquatic ecosystems. Vernal pools are a
unique model system, as their communities can be transferred relatively easily to
mesocosms which can then be manipulated and replicated. For example, vernal
pools have naturally defined areas, few invasive species, and egg banks which can
seed mesocosms (Blaustein and Schwartz 2001, DeMeester et al. 2005). Using
mesocosms allows us to answer scientific questions while preserving pristine pools
which are currently reduced to approximately 3-10% of their original distribution
largely due to human activity (Gerhardt and Collinge 2003). In addition,
mesocosms can be effective tools to conduct manipulative studies in a threatened
ecosystem that supports numerous threatened species.
This study can enhance conservation efforts of remaining pristine vernal
pools by providing concrete insight on how to manage the nutrient dynamics in
vernal pools. This study showed that nutrients can alter biotic and abiotic variables
and modify community dynamics. Therefore, management strategies involving
36
vernal pools should monitor water chemistry and nutrients, as well as the species
diversity and abundance. This study indicates that an increase of nutrient input,
specifically nitrogen and phosphorus, will lead to the increase of the predator
trophic levels and some functional groups. Recent work by Kneitel and Lessin
(2010, in press) described how phosphorus input increased algae cover during the
aquatic phase of vernal pools, leading to an algal crust in the dry phase which
decreased vascular plant cover and species diversity. This exploration between the
link between aquatic eutrophication and the shift of the vascular plant community
during the terrestrial stage of the vernal pool cycle illustrated how eutrophication
affects more than the aquatic phase (Kneitel and Lessin 2010, in press).
While this study lends hope that vernal pool communities may be able to
handle nutrient addition over a season without damaging the aquatic community, it
is unknown how long term nutrient input will affect vernal pool communities. To
decrease long term nutrient input, studies can determine the optimum amount of
fertilizer for residential lawns, golf courses, and agricultural fields which would
decrease urban runoff, sources of nonpoint pollution, into neighboring vernal pools
(Calhoun and deMaynadier 2008). Calhoun and deMaynadier (2008) suggested
long term nutrient pollution can create shifts in species composition in vernal pools.
In addition, it is likely vernal pools have a nutrient threshold that once crossed will
lead to a reduction of species as predicted by unimodal relationship between
nutrients and species richness (Scheffer and Carpenter 2003). It is also unknown if
37
vernal pools can shift between alternative stable states as do some shallow lakes
(Scheffer and van Nes 2007, van Nes et. al. 2007) and whether the drying phase
resets the ecosystems. Future work can also explore how nutrient addition will
affect specific endangered species and the role of native vernal pool predators as
compared to predaceous ovipositors.
38
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