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Pollinators May Not Limit Native Seed Viability for Puget Lowland Prairie Restoration
By
Jennie F. Husby
A Thesis
Submitted in partial fulfillment
of the requirements for the degree
Masters of Environmental Studies
The Evergreen State College
December 2012
© 2012 by Jennie F. Husby. All rights reserved.
This Thesis for the Master of Environmental Studies Degree
by
Jennie F. Husby
has been approved for
The Evergreen State College
By
_____________________
Carri LeRoy
Member of the Faculty
_____________________
Date
ABSTRACT
Pollinators May Not Limit Native Seed Viability for Puget Lowland Prairie Restoration
Jennie F. Husby
Reproductive success of plants can be influenced by the rate of visitation by insects to
flowers. Land managers often rely on large-scale production of native seeds in nurseries
for replanting into natural environments as part of restoration strategies. This study
investigated pollination of deltoid balsamroot (Balsamorhiza deltoidea Nutt.) and
sicklekeel lupine (Lupinus albicaulis Douglas) at a restoration nursery compared to a
Puget lowland prairie to determine if inadequate insect visitation restricts viable seed
production. In 2011 and 2012, insect visitation rates and community composition were
recorded for each plant species at each site. In 2012, seeds were collected from handpollinated and naturally-pollinated inflorescences and tested for viability. Overall
visitation rates were significantly higher at the nursery than the prairie for both plant
species and visiting insect communities differed between sites and years. However,
pollinator limitation was not evident for either plant species at either site and visitation
rate was not found to significantly influence the number of viable seeds produced. It is
possible that factors other than pollinator visitation are influencing seed viability and
further studies will address other factors, such as soil nutrients and seed handling
practices. This study is important for land managers because it shows that although
pollinator communities are different at a restoration nursery compared to a natural prairie
site, overall pollination processes were not different. In fact, natural pollination by both
assemblages of pollinators did not differ from forced pollination by hand. Increasing
insect visitation may not significantly increase seed viability at this restoration nursery. In
terms of monitoring the insect communities at both locations, weather conditions can
influence visiting insect community composition so long-term data collection will be
necessary to make broader generalizations about pollinator visitation at either site.
TABLE OF CONTENTS
List of Figures……………………………………………………………….
vi
List of Tables………………………………………………………………..
vii
Acknowledgements………………………………………………………….
viii
Chapter 1: Introduction and Literature Review…………………………
1
Introduction………………………………………………………….
1
Pollinator Specialization…………………………………………….
4
Pollinator Diversity Influences………………………………………
8
Pollinator Behavior………………………………………………….
10
Pollinator Effectiveness and Efficiency……………………………...
12
Chapter 2: Manuscript formatted for Journal of Pollination Ecology…
17
INTRODUCTION…………………………………………………..
17
MATERIAL AND METHODS…………………………………….
20
Study Plants………………………………………………….
Study Sites……………………………………………………
Visitation Rates………………………………………………
Visiting Insect Communities…………………………………
Pollinator Limitation………………………………………..
Visitation Rate vs. Viable Seed Production…………………
20
21
22
24
25
27
RESULTS……………………………………………………………
Visitation Rates………………………………………………
Visiting Insect Communities…………………………………
Pollinator Limitation………………………………………..
Visitation Rate vs. Viable Seed Production…………………
27
27
29
38
41
DISCUSSION……………………………………………………….
42
ACKNOWLEDEMENTS…………………………………………..
46
LITERATURE CITED……………………………………………...
46
iv
Chapter 3: Interdisciplinary Connections………………………………..
52
PUGET LOWLAND PRAIRIE STAKEHOLDER VIEWS……….
Federal Agencies…………………………………………….
State Agencies........................................................................
Regional Agencies…………………………………………...
52
52
55
56
WHY CONSERVE BIODIVERSITY?.............................................
58
POLLINATION AS AN ECOSYSTEM SERVICE………………..
59
CONCLUSION……………………………………………………...
61
References…………………………………………………………………..
62
v
List of Figures
Figure 1: The study plants found on Puget lowland prairies,
Thurston Co., 2011……………………………………………….
20
Figure 2: Webster Nursery, Tumwater, WA, 2011…………………………
21
Figure 3: Johnson Prairie, Thurston Co., 2012……………………………..
22
Figure 4: Visiting insect morphotype richness for A) Balsamorhiza
deltoidea and B) Lupinus albicaulis at Webster nursery and
Johnson prairie in 2011 and 2012…………………………………
30
Figure 5: Total number of visits (from all observations summed) made to
Balsamorhiza deltoidea by each insect morphotype……………..
33
Figure 6: Total number of visits (from all observations summed) made to
Lupinus albicaulis by each insect morphotype. …………………
33
Figure 7: A representative NMDS ordination plot of influence of site
differences on visiting insect community structure for Lupinus
albicaulis in 2012………………………………………………….
34
Figure 8: A) Percent and B) number of viable seeds produced by naturally
pollinated and hand-cross pollinated Balsamorhiza deltoidea
inflorescences at Webster nursery and Johnson prairie in 2012….
38
Figure 9: A) Number and B) percentage of viable seeds, C) number of
seeds per flower, D) seeds per ovule, E) seeds per pod, and F) pods
per flower produced by Lupinus albicaulis for each treatment.. …..
40
Figure 10: Inflorescence diameter vs. number of viable seeds produced by
Balsamorhiza deltoidea…………………………………………….
42
Figure 11: Plant volume vs. number of viable seeds produced by
Balsamorhiza deltoidea……………………………………………… 42
vi
List of Tables
Table 1: Results of two-sample Wilcoxon tests comparing insect visitation
rates at Webster nursery and Johnson prairie for B. deltoidea…….
28
Table 2: Results of two-sample Wilcoxon tests comparing insect visitation
rates at Webster nursery and Johnson prairie for L. albicaulis…….
29
Table 3: Results of Evenness, Shannon’s Diversity (H’) and Simpson’s
Diversity (D) indices for visiting insect morphotypes at Webster
nursery and Johnson prairie……………………………………….
32
Table 4: perMANOVA Results for Influence of Location (Webstery
nursery and Johnson prairie) on Community Structure of Visiting
Insects………………………………………………………………
34
Table 5: Indicator Species and Morphotype P Values for Location
(Webster Nursery or Johnson Prairie)……………………………..
35
Table 6: Indicator Species and Morphotype P Values for Wind Speed…….
36
Table 7: Indicator Species and Morphotype P Values for Cloud Cover……
36
Table 8: Indicator Species and Morphotype P Values for Temperature……
37
Table 9: MRPP Results for Influence of Temperature, Wind Speed, and
Cloud Cover on Community Structure of Visiting Insects………..
37
Table 10: Results of Linear Regressions Comparing Insect Visitation Rates
(# Visiting per Inflorescence per Hour) to Various Measures of
Reproduction……………………………………………………..
41
Table 11: Results of Linear Regressions Comparing Inflorescence
Diameter or Plant Volume to Seed Production for Balsamorhiza
deltoidea…………………………………………………………..
41
vii
Acknowledgments
Many thanks to all who helped me with this project. I thank Carri LeRoy for all her
support as my thesis reader. I thank the Center for Natural Lands Management and in
particular, Cheryl Fimbel for her suggestions, guidance, and support. I thank H. Elizabeth
Kirkpatrick, University of Puget Sound, for her suggestions on designing this pollinator
experiment. I thank Joint Base Lewis-McChord for permission to conduct research on
their lands. I thank Greg Dasso,The Evergreen State College, for helping me get set-up in
the lab for tetrazolium testing. I also thank The Evergreen State College Foundation and
the Evergreen Sustainability Fellowship committee for their financial support. Finally, a
special thank you to my grandma, Polly Robinson, for her help with sewing pollinator
exclusion bags.
viii
Chapter 1: Introduction and Literature Review
Introduction
This chapter is a review of the scientific literature on several aspects of pollination
ecology: pollinator specialization, diversity influences, behavior, and effectiveness. Each
aspect of pollination ecology selected serves as a valuable community-level component
for understanding the pollination web, a composition of all the plant-pollinator
interactions in an ecosystem. Little is known about the pollination web of Puget lowland
prairies, and understanding these components could help land managers make decisions
for maintaining prairie floral diversity.
The Puget lowland prairie ecosystem itself is threatened. Only three percent of the
original Puget lowland prairie habitat remains in highly fragmented patches (South Sound
Prairies Working Group 2012), and represents Washington State’s rarest ecosystem. Land
surrounding these prairie fragments has been converted by urban development,
agriculture, and coniferous forest encroachment. Isolation limits species dispersal in this
insular habitat. Numerous stakeholders—the Center for Natural Lands Management
(CNLM), Washington Department of Fish and Wildlife, Washington Department of
Natural Resources, U.S. Department of Defense, Thurston County, Wolf Haven
Sanctuary, and private land owners (among others) attempt to keep advancing forests
along prairie edges and invasive species at bay.
Vegetation of the Puget lowland prairies is a regionally unique, Idaho fescuewhite-top aster community type (Chappell and Crawford 1997) dominated by mostly
perennial forbs (Dunwiddie et al. 2006). The Washington Natural Heritage Program
monitors six plant species known to be rare in this landscape. Castilleja levisecta
Greenm., the hemi-parasitic endangered golden paintbrush with only 12 remaining
1
populations, is most notable. Conservation efforts to protect floral diversity focus on
maintaining suitable habitat for plants but managers have only begun to consider giving
attention to restoration of historical functional components such as pollination.
Several plant species are grown in nurseries for seed to replant into the prairies to
boost native plant populations including Puget balsamroot (Balsamorhiza deltoidea Nutt.)
and sickle-keel lupine (Lupinus albicaulis Douglas). Balsamorhiza deltoidea can be
found on the west coast of North America along the western slopes of the Cascade and
Sierra Nevada mountain ranges (Douglas & Ryan 2001), though only 10 known
populations remain in Washington State (Fazzino et al. 2011). The Washington Natural
Heritage Program (2012) has listed this species as a potential species of concern.
Populations of B. deltoidea are threatened by habitat destruction, invasive species
(Douglas & Ryan 2001), and habitat fragmentation and isolation (Fazzino et al 2011).
Increasing the size of the remaining populations could help B. deltoidea resist these
threats.
Lupinus albicaulis is not listed as a species of concern, but is nonetheless an
important plant species for Puget lowland prairie restoration. The Puget blue butterfly
(Icaricia icarioides blackmorei) is a Washington State species of concern that uses L.
albicaulis as a larval host plant (Schultz et al. 2009). Lupinus species are also important
contributors to soil nitrogen dynamics which can shape plant communities after
disturbance (Elliott et al. 2011), such as the Puget lowland prairies after natural fires.
Little is known about pollinators in the Puget lowland prairies. The Nature
Conservancy and the CNLM (Fimbel and McKinley 2010) have begun to identify the
most abundant insect species. Four of the most common floral visitors at the prairies are
2
bees (of the order Hymenoptera). ‘Sweat bees’ Halictus tripartitus and Lasioglossum
nevadense are tiny and solitary (individual bees that construct their own nests without the
help of others; Michener 2006). Bombus vosnesenskii (the yellow-faced bumblebee) and
Bombus mixtus (the brown-tailed bumblebee) are large, social, colony-forming bees most
commonly seen pollinating local flowers. Most research attention has been given to
studying and conserving rare butterfly species (Hays et al. 2000; Chramiec 2004; Stinson
2005; Hanson et al. 2010; Schultz et al. 2011), including Taylor’s Checkerspot
(Euphydryas editha taylori), that pollinate prairie plants while feeding on them. Flies,
beetles, and wasps comprise most of the other floral visitors. Animals other than insects,
such as hummingbirds, have been seen visiting Puget lowland prairie flowers, though
they have been observed much less often (Fimbel and McKinley 2010). In this thesis,
insects are assumed to be the main pollinators of plants at the prairies.
Why is it important to understand the biology of pollinators when protecting the
floral diversity of an ecosystem? Pollination is the process that facilitates sexual
reproduction in plants. More than 67% of plant species are estimated to be dependent
upon animals to transfer pollen from the anthers of one plant to the stigmas of another
(Kearns and Inouye 1997). Some species of plants can self-pollinate, though this results
in unmixed genes and often far fewer viable seeds. The ability to evolve and survive in a
changing environment requires genetic diversity, which is generally increased due to
insect pollination. Insufficient pollination can be a limiting factor for seed production and
thus the survival of plant species.
Land managers must take into account many habitat considerations for
preserving floral composition, in addition to the protection of pollinators (Tepedino et al.
3
2011). Natural pollinator limitation has been found to be evident in most plants studied
(Buchmann and Nabhan 1996). By understanding the role pollinators play in the Puget
lowland prairies, obstacles to pollination may be identified and then managed to promote
successful reproduction of target plant species.
Pollinator Specialization
Plant-pollinator relationships can vary from site to site at the community level.
Understanding the types of relationships that can occur and the frequencies at which they
typically occur can help focus research attention on keystone pollinator species.
Modeling the relationships at a site is one way to direct conservation efforts, though there
are many factors that can complicate this method.
Specialization refers to the number of degrees of connectivity existing between
each pollinator species and each plant species. A pollinator is a generalist if the insect
visits and forms mutualistic relationships with many different flower species. If an insect
only uses resources from one plant species, it is considered a specialist. The same
“generalist” and “specialist” terms may be applied to plants depending on whether many
species of animals or only one pollinates the flowers.
Combinations of pollinator and plant relationships tend to occur at different
frequencies. Generalist pollinators commonly visit either generalist or specialist plants
creating redundancy in the food web (Jordano et al. 2006). For example, honey bees
collect pollen from more plant species than any other animal pollinator. Honey bees can
easily find another resource to use if one of these plants becomes extinct, to continue
their own survival (Buchmann and Nabhan 1996). Specialist-specialist relationships are
4
rarer. Ficus carica L. (fig trees) are only pollinated by Blastophaga spp. wasps and
Blastophaga spp. only pollinate Ficus carica. If either the fig trees or the wasps became
extinct, so would the other (Buchmann and Nabhan 1996). It is unknown if specialistspecialist relationships exist in the Puget lowland prairies. Knowledge of which
mutualistic relationships are more vulnerable could provide a criterion for determining
which plants and pollinators are the most important to protect when designing
conservation plans.
Several studies have been conducted to determine which type of pollinators, if
removed from an ecosystem, would cause a cascade of plant species extinctions.
Anderson et al. (2011) found reduced seed production and plant density in a population
of New Zealand gloxinia (Rhabdothamnus solandri A. Cunn.) where this specialist plant
species had lost its bird pollinators, but no change in other populations of R. solandri
where there had not been a functional extinction of the bird species this plant depended
on. When plant species react to habitat destruction, asymmetric networks appear to be
ideal for specialist plants. When specialist plants have generalist pollinators, the specialist
plants have been found to preserve more connections to their pollinators, and therefore
resist disturbance better than specialist plants with specialist pollinators (Abramson et al.
2011).
Pauw (2007) researched an orchid-pollinating generalist bee (Rediviva
peringueyi) in South Africa. He found a decline in R. peringueyi populations correlated
with a decline in viable seeds of the specialist orchid species that depended on this bee
for pollination. However, the number of viable seeds did not decline in a generalist orchid
pollinated by many insect species other than R. peringueyi (Pauw 2007). If the goal of a
5
restoration project is to conserve plant biodiversity, these experiments provide evidence
that protection of generalist pollinators with a higher degree of connectivity may be
decided to be more critical than conserving specialist pollinators, particularly when a
plant community is dominated by specialist plant species depending on pollination from a
single generalist pollinator.
In Puget lowland prairies, bees appear to be the most generalized pollinators,
visiting the largest variety of flowers. This indicates that they should be protected to
conserve rare plants. Research has not yet been performed to determine the critical
animal species pollinators for the endangered C. levisecta though researchers have
observed bumblebees visiting these flowers (Wentworth 1997). If C. levisecta turns out to
be a specialist depending on only bumblebees for maintaining genetic diversity in the
twelve remaining populations, bumblebee conservation strategies will be important to
include in any C. levisecta conservation plan. If many other plant species also depend on
bumblebees, then their protection becomes even more critical.
Memmott et al. (2004) used a computer model of simulated pollinator extinctions
to test the robustness of floral communities. Simplifying the real world ecosystem down
to types of mutualistic relationships between the plant species and their respective
pollinators allowed these scientists to identify the insects whose extinctions would
precipitate the fastest decline in floral diversity. When researchers removed the generalist
pollinators first, plant diversity declined most rapidly and the opposite became true when
the modelers removed the specialist pollinator species first (Memmott et al. 2004). The
results of these models can help land managers make general guidelines for conserving
pollinators with the goal of protecting the greatest number of flower species; however
6
managers must be aware that real life pollination webs are much more complex than their
models.
Plant extinction rates may vary due to other pollination web processes not
accounted for in the Memmott et al. (2004) models. The number of pollinator species
present typically outnumbers plant species and their interactions are nested so the
pollinator that is the second most generalized visits a subset of plant species that the most
generalized pollinator uses, the third most generalized pollinator visits a subset that the
second most generalized visits, and so on (Memmott et al. 2004; Fang & Huang 2012).
This overlap allows for more redundancy in the system and therefore, slower declines in
plant diversity (Memmott et al. 2004). Nevertheless, James et al. (2012) argue that
nestedness is a less important indicator of food web stability than simply the general
connectivity of the network (i.e. the number of partners a species has).
Extinction of a pollinator species may not precipitate a collapse of the food web if
the other pollinator species in the web adapt their foraging strategies (Kaiser-Bunbury
2010). If a plant becomes extinct, a pollinator may choose to forage on a different plant
species. If a plant species’ pollinator becomes extinct, other pollinator species may begin
foraging on the plant. Fang and Huang (2012) observed in a four-year study that highly
diverse pollinator networks were relatively stable even while the pollinator assemblage
varied year to year. Kaiser-Bunbury et al. (2010) found that random extinctions do not
affect the stability of a plant-pollinator network due to foraging adaptability, but removal
of the strongest interactors may cause a sudden collapse of the pollination web.
Anthropogenic disturbance more often leads to the extinction of keystones in a food web,
such as bumblebees, than natural disturbance (Kaiser-Bunbury et al. 2010).
7
Plant extinction rates may also be faster if a floral community includes rare plants
at a high risk for extinction due to other factors than pollinator limitation such as
population fragmentation, climate change, nutrient limitation, small population size, etc.
Roberts et al. (2011) modeled the effects of predicted climate change on generalist and
specialist bee species. All species were found be at risk, though the most specialized bee
species was at the highest risk (Roberts et al. 2011).The plant-pollinator relationships that
exist at a site depend on the diversity of plants and animals present.
Pollinator Diversity Influences
The species of pollinators that can be present at a site depends on what floral resources
exist. Floral diversity therefore influences pollinator diversity, and spatial arrangement
and range of floral resources also matter.
Plants often depend on the services of animal pollinators and pollinators, in turn,
depend on floral resources. Because animals more or less co-evolved with certain plants
(becoming specialists or generalists), the distinctive morphology and energy requirements
of the different taxa require varied flower types to forage from. For example, Potts et al.
(2003) found increased bee diversity to be strongly related to an increase in variety of
floral resources available to support the nutrition and feeding requirements of the
different species. Hines and Hendrix (2005) developed a landscape resource index for
floral resource diversity, and abundance of flowering ramets for their study sites, and
found this tool to be a useful predictor of bumblebee diversity. Competition for nectar
between different taxa, such as bees and butterflies, may also influence the pollinator
8
diversity at a site (Davis et al. 2008). Finally, nesting resources also often indicate
whether or not a high diversity of pollinating insects will be found in a region.
Animals require special places to rear their young. Solitary bees need suitable
soils to build ground nests and social bees often build homes under dry, dense vegetation
(Hines and Hendrix 2005, Davis et al. 2008). Butterflies look for certain plant species to
be larval hosts. Davis et al. (2008) discovered pollinator conservation strategies may need
to vary by taxa due to dissimilar habitat needs and arrangements.
For pollinator diversity, spatial arrangement of floral resources and habitat
substrate matter. Hines and Hendrix (2005) studied bumblebees and found the abundance
of these animals to be correlated with the size of the area of prairie habitat around their
nesting sites. Narrow grassy areas may be important for providing connectivity between
habitat patches (Hines and Hendrix 2005). Some pollinators that are critical for a certain
plant population may migrate, so habitat protection is therefore essential all along the
route the migratory animal takes during its lifecycle (Buchmann and Nabhan 1996). The
more different kinds of microhabitats existing at a site, the more pollinator diversity there
can be.
Pollinator habitat range is wider than the area of the protected Puget lowland
prairies. Management of the surrounding land may be necessary, making landowners also
a part of the greater pollination web. Managers may need to plant more early, late, and
long-blooming flowering plants as food resources to sustain pollinators when their main
food sources wilt. Fimbel and McKinley (2010) experimented with putting artificial
nesting blocks out on some of the prairie sites and had success with attracting insects,
though more research is needed to determine if the insects inhabiting the blocks benefit
9
the pollination web or not. Many solutions can be found for altering and conserving
pollinator diversity at the prairies as the pollination web becomes understood. Diversity is
an important consideration because each insect species behaves uniquely.
Pollinator Behavior
Animal behavior can be a critical component to the pollinator web. The spatial pattern a
pollinator chooses when moving from flower to flower can determine if genetic diversity
is spread in floral reproduction or not. If an insect too often jumps from one species to a
different species, pollen may be lost on the wrong plant and not make the journey to a
conspecific for fertilization. By staying too long on one plant, a pollinator may help the
plant to self-fertilize but hinder the genetic mixing that promotes genetic diversity.
Certain insect species are attracted to dense patches rather than isolated flowers
(Garcia-Meneses & Ramsay 2012). When plants are grouped close together, they tend to
be visited by more pollinators looking for higher reward for less effort (Garcia-Meneses
& Ramsay 2012). This could either be beneficial to the plant species or detrimental. The
presence of more flowers decreases the probability that an individual flower will be
pollinated due to increased floral competition (Sih and Baltus 1987). Patches of plants
often consist of closely related plants and pollinators have been found to lower
reproductive output by concentrating visits to a single large patch (Garcia-Meneses &
Ramsay 2012). White-top aster (Aster curtus Cronq.), a clonal Puget lowland prairie
plant, forms dense patches that may attract many pollinators. If the insects only visit
flowers within one patch among clones though, genetic diversity will not increase
because all clones within a patch produce pollen with identical genetic material. Wirth et
10
al. (2011) discovered higher seed set in arctic alpine forget-me-not (Eritrichium nanum
(Vill.) Schrid.) plants growing at low conspecific density than high conspecific density
likely due to both reduced floral competition for pollinators and more effective
outbreeding.
Some pollinator species have been found to be attracted to sparer patches of
flowers rather than denser. Nielsen et al. (2012) found that honeybees had higher
visitation rates to more dense patches of flowers, but bumblebees and hoverflies visited
sparser flower patches more frequently possibly due to reduced competition.
Pollinator competition for flowers can influence visiting insect diversity and
behavior. Predation by larger insects on small ones may deter small pollinators from
visiting a plant. Keys et al. (1995) found that by excluding large pollinators from visiting
a flower using a coarse mesh bag, they could test the effectiveness of small insects only.
However, Keys et al. (1995) noted that the abundance of small pollinators then found on
the flower may be an unnatural result if this method results in a refuge from typical
predation.
Different types of pollinators may forage at different times of the day or year.
Early visiting animals may drink all the nectar and pollinators coming to visit later will
avoid those flowers that are empty of a reward. Some pollinator species forage earlier or
later in the season than others, thus competition for floral resources may vary throughout
the year or with the number of flower species in bloom. Competition may be lessened at
times as some animals are hardier to warmer or cooler temperatures or to wind and air
moisture.
11
Introduced, non-native insect species can compete with native pollinators. In
Nielsen et al.’s (2012) research, the presence of honeybees affected visitation rates of
other pollinator species and pollinator community composition variously depending on
the plant species studied. A correlation was found between decreased coffee (Coffea
Arabica L.) fruit production and a decrease in native pollinator diversity due to
competition with honey bees (Badano & Vergara 2011). The amount of time that
different pollinator species interact with a flower can shift depending on competition, and
because different pollinators have different levels of effectiveness this can influence plant
reproductive success.
Pollinator Effectiveness and Efficiency
The basic principles of how generalist and specialist pollinators structure the pollination
web can be disrupted when examining the effectiveness or efficiency of the visiting
species. A pollinator is “effective” if a plant produces a greater number of viable seeds
after being pollinated by the animal minus the number of viable seeds the plant would
produce without any animal interaction (i.e. seeds produced by self-pollination).
Pollinator “efficiency” refers to the animal’s effectiveness divided by a measurement of
space or time (Keys et al. 1995, Spears 1983). Ecologists have used many different
methods to measure these variables.
Pollinator effectiveness can be measured indirectly or directly. Indirect methods
assume pollination success by observing floral features such as: pollination-mediated
floral color changes, the number of mechanically tripped flowers, or the number of pollen
grains on a stigma (Engel and Irwin 2003). Direct measurements investigate the number
12
of viable seeds produced. Spears (1983) published a paper offering an equation for
calculating the pollinator effectiveness (PE) of a single animal species, which is still used
by many pollination ecologists in current research (Keys et al. 1995; Perfectti et al.
2009), and often called “Spear’s PE”:
PE = (Pi -Z)/ (U- Z)
Pi= mean number of seeds set / flower by a plant population receiving a single visit from species i
Z= mean number of seeds set / flower by a population receiving no visitation.
U= mean number of seeds set / flower by a population receiving unrestrained visitation
In a standard experiment to determine the effectiveness of all pollinators on a given plant,
a researcher hand pollinates some of a plant’s flowers to ensure complete pollination and
allows other flowers to be freely pollinated by the usual animals (Kearns and Inouye
1993; Cane 2005; Fazzino et al. 2011). By counting and comparing the viable seeds
produced by each experimental set of flowers, pollinator efficiency can be directly
inferred (Kearns and Inouye 1993; Cane 2005; Fazzino et al. 2011). When conducting
any experiment involving seed measurements, researchers must keep in mind that seed
viability can be affected by other variables aside from pollinator efficiency such as soil
nutrients and moisture content (Engel and Irwin 2003, Fimbel and McKinley 2010).
This direct method of measuring effectiveness has already been applied to one
species of plant in the Puget lowland prairies, B. deltoidea (Puget balsamroot), in a study
by Fazzino et al. (2011). Seed set was compared between naturally-pollinated
inflorescences and hand-pollinated inflorescences. Pollinators were not effective and B.
deltoidea was found to be pollinator-limited as hand-pollinated inflorescences produced
more potential germinants than naturally-pollinated inflorescences. In 2012, I adapted
methods from Fazzino et al. (2011) to also test B. deltoidea for pollinator limitation (see
Chapter 2). Seed-set from hand-pollinated inflorescences were again compared to
13
naturally-pollinated inflorescences, but seed viability was measured using a tetrazolium
assay. Seeds were soaked in a 1% solution of 2,3,5-triphenyltetrazolium; a dye that
indicates living tissue if the seed embryo stains red. Surprisingly, no evidence of
pollinator limitation was found (see chapter 2).
Computer modeling performed by Perfectti et al. (2009) illustrates the
importance of understanding the effectiveness and efficiency of the animal species in
addition to whether the pollinators are generalists or specialists. One theory about why
plants evolved to become specialists speculates they did so to attract only the most
efficient pollinator. A generalist plant may have the advantage of being able to survive if
one of its pollinators becomes extinct, but may be at a disadvantage if many of its visitors
do not effectively pollinate. Perfectti et al. (2009) put several plants and their respective
pollinators of various efficiencies into this model and simulated scenarios where the
diversity of the pollinator assemblage differed. They discovered that low diversity in
pollinators resulted in most successful plant reproduction when the most abundant
pollinators were the most effective. Higher pollinator diversity may be better though,
according to optimal plant fecundity, when the most effective pollinators are not the most
abundant (Perfectti et al. 2009).
Along with viable seeds produced, an additional variable must be monitored to
study pollinator efficiency. Keys et al. (1995) determined the efficiency of specific
pollinators by monitoring the length of time a pollinator spent on a spike and the distance
the pollinator traveled along the inflorescence per number of pods developed in addition
to PE. Engel and Irwin (2003) recorded the rate of visitation by hummingbirds per
number of pollen grains found on the stigmas of scarlet gilia (Ipomopsis aggregata
14
(Pursh) V.E. Grant) flowers. Jauker et al. (2012) measured the effect of density of visiting
insects by putting a known number of insects in a cage with a known volume containing
flowering plants. Both red mason bees (Osmia rufa) and hoverflies (Eristalis tenax and
Bpisyrphus balteatus) will pollinate oilseed rape (Brassica napus L.), but it takes about
five times the density of hoverflies to pollinate an oilseed rape plant as red mason bees
for the plant to produce the same number of seeds (Jauker et al. 2012). Calculating an
efficiency rate allows scientists to determine the necessary abundance of a pollinator
species to be effective at pollinating the plants in a region.
Pollinator efficiency and effectiveness can vary year to year or within a single
flowering season. Native pollinator assemblages can vary significantly from one year to
the next resulting in fluctuations in plant fecundity (Rader et al. 2012). Kudo et al. (2011)
found that queen bees were more efficient pollinators of rhododendron (Rhododendron
aureum Georgi) than worker bees. Because queen bees forage earlier in the season than
worker bees, pollinator effectiveness changed during the season (Kudo et al. 2011).
For many plants, rate of insect visitation is a critical factor for reproductive
success. Engel and Irwin (2003) found a positive relationship between insect visitation
rates and pollen receipt. Vazquez et al. (2005) compiled pollination data from the
literature and used a mathematical model to determine that frequency of visitation is a
factor usually contributing more to seed production than the effectiveness of the visitor.
Arroyo et al. (1982) counted visits to a known number of flowers during 10-minute
intervals to calculate visitation rates for an experiment that determined the effects of
altitude on pollination. In 1985, the same method was used in a second part of the study
to find the effects of temperature on visitation rates (Arroyo et al. 1985). Several more
15
researchers (Inouye and Pyke 1988; Berry and Calvo 1989; Kearns 1990; Mcall and
Primack 1992; Boyd 2004; Grindeland et al. 2005) followed suite in the next years, using
similar visitation rate methods for comparison of their studies (Kearns and Inouye 1993).
In the next chapter, I use research methods explored in this literature review to
investigate the current state of pollination at the Puget lowland prairies and at a nursery
that supplies native seeds for restoration projects at the prairies. At each study site, I
observed and recorded rates of insect visitation to selected plant species using methods
adapted from Arroyo et al. (1982). I also related visitation rate to the effectiveness of the
pollinators and explored pollinator limitation by collecting seeds from inflorescences that
had been hand-pollinated or naturally-pollinated and tested their viability. To do this, I
adapted methods from Fazzino et al. (2011) and tetrazolium testing procedures outlined
in the International Rules for Seed Testing manual (International Seed Testing
Association 2012).
16
Chapter 2: Manuscript formatted for Journal of Pollination Ecology.
Pollinators May Not Limit Native Seed Viability
for Puget Lowland Prairie Restoration
ABSTRACT
Reproductive success of plants can be influenced by the rate of visitation by insects to
flowers. Land managers often rely on large-scale production of native seeds in nurseries
for replanting into natural environments as part of restoration strategies. This study
investigated pollination of deltoid balsamroot (Balsamorhiza deltoidea Nutt.) and
sicklekeel lupine (Lupinus albicaulis Douglas) at a restoration nursery compared to a
Puget lowland prairie to determine if inadequate insect visitation restricts viable seed
production. In 2011 and 2012, insect visitation rates and community composition were
recorded for each plant species at each site. In 2012, seeds were collected from handpollinated and naturally-pollinated inflorescences and tested for viability. Overall
visitation rates were significantly higher at the nursery than the prairie for both plant
species and visiting insect communities differed between sites and years. However,
pollinator limitation was not evident for either plant species at either site and visitation
rate was not found to significantly influence the number of viable seeds produced. It is
possible that factors other than pollinator visitation are influencing seed viability and
further studies will address other factors, such as soil nutrients and seed handling
practices. This study is important for land managers because it shows that although
pollinator communities are different at a restoration nursery compared to a natural prairie
site, overall pollination processes were not different. In fact, natural pollination by both
assemblages of pollinators did not differ from forced pollination by hand. Increasing
insect visitation may not significantly increase seed viability at this restoration nursery. In
terms of monitoring the insect communities at both locations, weather conditions can
influence visiting insect community composition so long-term data collection will be
necessary to make broader generalizations about pollinator visitation at either site.
INTRODUCTION
Pollinators play a key role in the reproduction of wild plants as they are linked to viable
seed production and ecosystem restoration. Pollinators and their activities thus provide an
ecosystem-wide service (Kremen et al. 2007). The ability to produce viable seeds is
critical for plants to be able to maintain their populations naturally. In addition, the role
of pollinators needs to be better understood to improve conservation strategies, especially
in threatened habitats (Fontaine et al. 2006; Mayer et al. 2011). Often land managers
17
must understand plant-insect interactions to be able to grow successful yields of
supplemental native seed in nursery settings.
Native seed from nurseries plays an important role in ecosystem restoration.
Ecosystems in need of conservation attention may be stressed by factors such as invading
species, fragmentation, and climate change; all of which can suppress a plant species’
population size and limit its reproduction ability (McCarty 2001; Vila & Weiner 2004;
Fazzino et al. 2011; Tscheulin & Petanidou 2011). Many restoration practitioners depend
on native seed grown in nurseries for repopulating plant species in natural areas. Native
plant nursery managers strive to produce large quantities of high quality seed to keep up
with the demand.
The Center for Natural Lands Management (CNLM) relies on large scale
production of native seeds for replanting into the Puget lowland prairies as part of their
restoration strategy. Some years the CNLM has struggled to produce large quantities of
viable seeds at Webster Nursery for certain plant species (Cheryl Fimbel, CNLM, pers.
comm. 2010). The cause of this problem may be due to issues with proper seed handling
or storage, inadequate environmental conditions where the plants are grown (such as soil
nutrients, weather, etc.), or pollinator limitation. This study will address the latter by
investigating the current state of pollination at Webster Nursery and comparing it to a
Puget lowland prairie to determine if inadequate pollination is restricting viable seed
production at the nursery.
When plants produce fewer viable seeds because of insufficient pollination, they
are pollinator limited (Dieringer 1992; Price et al. 2008; Fazzino et al. 2011). Several
aspects of pollination can influence seed viability. Rate of insect visitation can be a
18
critical factor for the reproductive success of many plant species. Researchers found a
positive relationship between insect visitation rates and pollen receipt (Engel & Irwin
2003). Differences in pollinator community structure can also affect overall pollination
effectiveness (Perfectti et al. 2009).
The Puget lowland prairie ecosystem has been fragmented by coniferous forest
encroachment and urban and agricultural development so that now only 3% of the
original habitat remains (South Sound Prairies Working Group 2012). Re-establishing
native flora has been a priority of Puget lowland prairie land managers (Stanley et al.
2008). The deltoid balsamroot (Balsamorhiza deltoidea Nutt.) is a species of potential
concern in Washington State (Washington Natural Heritage Program 2012) and is one of
the many plant species replanted into the prairies. The federally endangered Fender’s
blue butterfly (Icaricia icarioides fenderi (Macy)) occasionally feeds on another species
of concern, the sickle-keel lupine (Lupinus albicaulis Douglas) (Wilson et al. 1997).
Both plant species grow along the west coast of the United States and into Canada
(USDA Natural Resources Conservation Service 2012).
In this study, I address the following research hypotheses: 1) Insect visitation rates
will be higher at the prairie site than the nursery because natural environments provide
more resources and habitat for insects than environments constructed by humans. 2)
There will be differences in visiting insect community composition between the nursery
and prairie and between years because of differing resources and weather conditions. 3)
There will be pollinator limitation at the nursery due to lower insect visitation rates and
4) Insect visitation rate will affect seed viability.
19
MATERIAL AND METHODS
Study Plants
To address my research questions, I focused this study on two native prairie plants, B.
deltoidea (deltoid balsamroot) and L. albicaulis (sicklekeel lupine). These plants are both
found at natural prairie sites and are being produced from seed by CNLM at the Webster
Nursery, Tumwater, WA, USA.
Balsamorhiza deltoidea (Fig. 1 A; Asteraceae) bloomed from the last week of
May to mid-June in 2011 and from May 7 to June 1 in 2012. This perennial has yellow,
compact head inflorescences containing many fertile female ray flowers and bisexual
disk flowers. The fruits are achenes, each with a single ovule.
Lupinus albicaulis (Fig. 1 B; Fabaceae), is a perennial and bloomed from late
June to mid-July in 2011 and from May 29 to June 29 in 2012. The blue, papilionaceous
flowers develop basally first in racemes. Each flower contains 10 monodelphous stamens
and a one-celled pistil with an average of five ovules (indicated by the number of cells
found in collected pods).
A.
B.
Figure 1. A= Balsamorhiza deltoidea, B= Lupinus albicaulis. The study plants found on
Puget lowland prairies, Thurston Co., 2011.
20
Study Sites
Washington Department of Natural Resources (DNR) owns Webster Nursery (Fig. 2),
which is managed by the CNLM to produce seed from native plants at a large scale for
restoring Puget lowland prairies. The plants are grown outdoors in dense rows. The rows
planted with B. deltoidea and L. albicaulis were last fertilized in 2008, are watered only
by rain, and were not sprayed with pesticides or herbicides in 2012 (Angela Winter,
CNLM nursery manager, pers. comm. 2012). Farmland, a highway, and forested areas
surround the nursery.
Figure 2. Webster Nursery, Tumwater, WA, 2011
The US Department of Defense manages Johnson Prairie (Fig. 3), a natural prairie
site on Joint Base Lewis-McChord. Johnson is one of the few remaining natural Puget
lowland prairie sites, and is located near Rainier, WA. This prairie receives frequent
horseback riding, hunting, and off-road driving activity, though less military training
21
activity than other prairie sites located on the base (Stinson 2005). This site was burned in
August, 2011 for restoration purposes. Coniferous forest borders this prairie site.
Figure 3. Johnson Prairie, Thurston Co., 2012
Visitation Rates
The methods used for this study were adapted from procedures used to calculate
visitation rates in many other studies. Arroyo et al. (1982) first recorded the number of
visits to a know number of flowers for a set time interval. Others (Arroyo et al. 1985,
Inouye & Pyke 1988, Berry & Calvo 1989, McCall & Primack 1992) replicated this
method to allow comparisons among studies (Kearns & Inouye 1993). Boyd (2004) used
this method to calculate visitation rates and combined those with pollen deposition values
as a measurement of pollinator effectiveness.
22
For this study, plots were selected to collect visitation rate data for both study
plant species in 2011 and 2012. Plot locations were selected randomly at Webster
Nursery, and plot locations at Johnson Prairie were selected randomly from patches of
plants with similar floral densities as found at the nursery. Floral density was calculated
for each plot by counting the number of inflorescences of the focal species in bloom and
dividing that number by the area of the plot (3 m2).The selected patches contained few
other flowering species to reduce the chance that floral competition would be a
confounding factor. In 2011, six plots were selected for B. deltoidea and 16 plots were
selected for L. albicaulis at each location and observed once (B. deltoidea n=6, L.
albicaulis n=16). Differences in number of observations made were due to sampling time
constraints. In 2012, 30 plots were selected at each site for B. deltoidea, and each
observed once (n=30). After sampling B. deltoidea it was noted that visitation rates can
vary throughout the bloom period, so the experimental design was changed for L.
albicaulis in 2012. Recorded visits to flower patches for three rounds of timed intervals
can be used to calculate a mean number of visits per flower per hour (Tscheulin &
Petanidou 2011). Ten plots were selected at each site and each sampled three times for L.
albicaulis in 2012 (n=10).
Observations took place during peak flowering times on three days for each plant
species between May 20 and July 6 in 2011. In 2012, observations took place between
May 8 and June 21 on six days for B. deltoidea and five days for L. albicaulis. Each
observation period lasted 10-minutes. All observations were made between 1000 and
1530 hours. Sampling dates were chosen to be as close together as possible on days with
similar temperature, cloud cover, and wind conditions within an optimal range for insect
23
activity (temperatures ranging from 9 to 27 0C, clear to cloudy skies with shadows
present, and still air to light breeze). I assumed all flowers in bloom were receptive to
pollen.
Visiting insects were grouped into morphotypes: small dark bees (Halictidae,
Colletidae: Hylaeinae, Apidae: Xylocopinae, and Andrenidae), large dark bees (Andrena
sp. and Colletidae), green metallic bees (Agapostemon sp.), cuckoo bees (Apidae:
Nomadinae), honey bees (Apis mellifera), bumblebees (Bombus sp.), flies (Diptera), ants
(Formicidae), wasps (Hymenoptera: Apocrita), and beetles (Coleoptera). The only
category that was further identifies into species categories was the bumblebee category as
they were easily identified to species in the field. The number of visits made by each
insect type was recorded during each ten-minute period. A visit was recorded only if the
insect landed on the reproductive parts of a flower in an inflorescence. If an insect
appeared to be “nectar robbing,” where there was no potential for pollen transfer, the visit
was discounted. Nectar robbing was rarely observed in this study.
Two-sample Wilcoxon tests were used to compare the overall mean visitation rate
and visitation rate of each insect group at the nursery to the prairie for each plant species
because the data were not normally distributed. The data were first logarithmically
transformed. Analyses were conducted using R statistical package (www.r-project.org )
and an alpha = 0.05.
Visiting Insect Communities
Community analysis was performed to examine characteristics of the visiting insect
communities. R statistical package was used to perform two-sample Wilcoxon tests to
find differences in visiting insect morphotype richness, evenness, and diversity between
24
the study sites and years for both plant species (alpha = 0.05). PC-ORD statistical
software (http://home.centurytel.net/~mjm/pcordwin.htm) was used to run all other
community analyses. Shannon’s diversity index (H’) and Simpson’s diversity index (D)
were used to calculate visiting insect morphotype diversity for each plant species. The
total number of visits made by each morphotype was summed from all observations to
compare community composition and total number of visits made to each plant species
each year. Permutative multivariate ANOVAs and non-metric multidimensional scaling
(NMDS) ordinations were used to determine if insect communities differed between sites
for each plant species in each year (alpha = 0.05). Indicator Species Analysis was
performed to find evidence for preferences of insects for certain environmental
conditions (alpha = 0.05). Multiresponse permutation procedures (MRPP) were used to
determine if temperature, wind speed, or cloud cover (as ranked categorical variables)
influenced the community structure of visiting insects (alpha = 0.05).
Pollinator Limitation
Procedures for this pollinator limitation experiment were adapted from methods used by
Fazzino et al. (2011) who compared seed set from naturally-pollinated B. deltoidea
inflorescences to hand-cross-pollinated inflorescences to investigate pollinator limitation.
In 2012, a subset of 10 plots for B. deltoidea at each site was selected randomly from the
visitation rate plots, and all plots from the L. albicaulis visitation rate observations were
used for the seed set experiment. Two similarly sized plants were chosen within each plot
for L. albicaulis. On the first plant, four inflorescences of similar size were marked with
thread before the styles matured. A bag made out of tulle was placed over one
inflorescence to exclude all insect visitations to test for autogamy (unassisted self-
25
pollination). A second inflorescence was also bagged and then hand-pollinated using
pollen from flowers on the same plant to mimic geitonogamy (pollinator-assisted selfpollination). A third inflorescence was left uncovered and hand cross-pollinated and a
fourth inflorescence was left uncovered to be naturally pollinated. On the second plant,
one inflorescence of a similar size to the others was marked and left to be naturally
pollinated as a control comparison to rule out differences in resource allocation in the
treated plant. Only hand-cross-pollination and natural pollination treatments were applied
to one plant per plot for B. deltoidea, as Fazzino et al. (2011) documented that this
species is self-incompatible and does not reallocate resources in this kind of experiment.
After setting up the plots, hand-pollination treatments were applied every other
day until the stigmas shriveled. I then covered all the inflorescences with a coarser mesh
bag to prevent seed predation. When the fruits matured, I collected the inflorescences and
extracted and counted the seeds. For L. albicaulis, I also counted flowers (indicated by
pedicel scars), ovules, and pods (fruits).
A tetrazolium assay was used to test the seeds for viability using procedures
adapted from the International Seed Testing Association (2012). Ten seeds were
randomly selected from each inflorescence for B. deltoidea, and all seeds from the L.
albicaulis inflorescences were tested. Balsamorhiza deltoidea seeds were soaked in warm
water for four hours, and L. albicaulis seeds were soaked for 24 hours. A 1% aqueous
solution of 2,3,5-triphenyltetrazolium chloride was prepared and the pH was adjusted to
6.8. All seed coats were pierced before soaking the seeds in the tetrazolium solution.
After four hours, I examined the embryos for the red staining that indicates viability.
26
Because these data were not normally distributed, I used two-sample Wilcoxon
tests to compare the number and percent of viable seeds produced by the inflorescences
of each treatment group for each plant species at each site. These analyses were done
using R statistical software (alpha=0.05). The seed number data were first logarithmically
transformed, and the percent viable seed data were first arcsine square root transformed.
To determine if there was pollinator limitation for either plant species at Webster Nursery
or Johnson Prairie, I compared the number and percentages of viable seed produced by
the hand-pollinated inflorescences to the naturally pollinated inflorescences. For L.
albicaulis, I also compared number of seeds per flower, seeds per ovule, seeds per pod,
and pods per flower for each treatment.
Visitation Rate vs. Viable Seed Production
Finally, using R statistical package (alpha=0.05), I investigated whether or not different
variables affected viable seed production. I used simple linear regression to determine if
insect visitation rate affected number or percent viable seed of the naturally pollinated
inflorescences for B. deltoidea, and number, percent viable, seeds per flower, seeds per
ovule, seeds per pod, and pods per flower for L. albicaulis. I also used simple linear
regression to determine if inflorescence diameter or plant volume affected the percentage
or number of viable seeds produced by B. deltoidea.
RESULTS
Visitation Rates
Insect visitation rates differed between Webster Nursery and Johnson Prairie, both overall
and for many of the insect groups in both years. In 2011, overall visitation rates were
27
significantly higher at Webster nursery than at Johnson prairie for L. albicaulis (W=57,
n1=n2=16, P=0.0078), but not for B. deltoidea (W=8, n1=n2= 6, P=0.1255). In contrast, in
2012 overall visitation rates were significantly higher at Webster nursery than at Johnson
prairie for both B. deltoidea (W=169, n1=n2=30, P<0.0001) and L. albicaulis (W=11,
n1=n2=10, P=0.0036). Webster nursery also had significantly higher visitation rates than
Johnson prairie for specific insect morphotypes visiting each of the plant species in both
years (Tables 1 & 2).
Table 1. Results of two-sample Wilcoxon tests comparing insect visitation rates at
Webster nursery and Johnson prairie for B. deltoidea
2011 (n1=n2=6)
2012 (n1=n2=30)
Insect Morphotype/Species
W
P
W
P
Small Dark Bees
----- ----348.5 0.0326
Large Dark Bees
2.0 0.0124
435.0 0.3337
Green Metallic Bees
15.0 0.4047
420.0 0.1608
Cuckoo Bees
----- ----420.0 0.1608
Honey Bees
15.0 0.4047
----- ----Bumblebees (total)
21.0 0.4047
244.0 0.0008
Bombus sitkensis
----- ----335.5 0.0266
Bombus mixtus
21.0 0.4047
465.0 0.3337
Bombus vosnesenskii
----- ----343.0 0.0289
Bombus melanopygus
----- ----405.0 0.0815
Bombus flavifrons
----- ----465.0 0.3337
Flies
27.0 0.0740
449.5 1.000
Ants
21.0 0.4047
----- ----Beetles
----- ----435.0 0.5703
Significant results are in bold. All significant results indicate higher visitation rates at
Webster nursery than at Johnson prairie.
28
Table 2. Results of two-sample Wilcoxon tests comparing insect visitation rates at
Webster nursery and Johnson prairie for L. albicaulis
2011 (n1=n2=16)
2012 (n1=n2=10)
Insect Morphotype/Species
W
P
W
P
Small Dark Bees
164.5 0.0988
72.0 0.0666
Large Dark Bees
126.0 0.9216
46.0 0.7280
Bumblebees (total)
54.0 0.0054
2.0 0.0002
Bombus sitkensis
147.5 0.4102
45.0 0.5842
Bombus mixtus
29.5 0.0001
0
1.0000
Bombus vosnesenskii
76.0 0.0353
25.0 0.0149
Bombus melanopygus
136.0 0.3485
45.0 0.3681
Flies
152.0 0.0800
55.0 0.3681
Wasps
120.0 0.3485
----- ----Beetles
120.0 0.3485
65.0 0.0779
Significant results are in bold. All significant results indicate higher visitation rates at
Webster nursery than at Johnson prairie.
Visiting Insect Communities
Characteristics of visiting insect community composition varied between sites and years.
There was no significant difference in morphotype richness for visiting insects on either
plant species between Webster nursery and Johnson prairie in 2011 (B. deltoidea:
W=22.5, n1=n2=6, P=0.4760; L. albicaulis: W=109.5, n1=n2=16, P=0.4790), but there
was increased insect richness at Webster Nursery for both plant species in 2012 (Figure
4A: B. deltoidea: W=189, n1=n2=30, P=<0.0001; 4B: L. albicaulis: W=24, n1=n2=10,
P=0.0491).
29
A.
B.
Figure 4. Visiting insect morphotype richness for A) Balsamorhiza deltoidea and B)
Lupinus albicaulis at Webster nursery and Johnson prairie in 2011 and 2012. Different
letters above bars indicate a significant difference between sites and years.
30
Balsamorhiza deltoidea had a significantly more even distribution of visiting insect
morphotypes at Webster nursery in 2012 (W=299, n1=n2=30, P=0.0060), however no
significant difference was found in morphotype evenness between Webster nursery and
Johnson prairie in 2011(W=21, n1=n2=6, P=0.4047) (Table 3). There was no significant
difference found in visiting insect morphotype diversity between Webster nursery and
Johnson prairie in 2011 for B. deltoidea (H’: W=21, n1=n2=6, P=0.4047; D: W=21,
n1=n2=6, P=0.4047), but diversity was significantly higher at Webster nursery in 2012
(H’: W=301, n1=n2=30, P=0.0067; D: W=302, n1=n2=30, P=0.0071) (Table 3). Lupinus
albicaulis had a significantly more even distribution of visiting insect morphotypes at
Johnson prairie in 2012 (W=362.5, n1=n2=30, P=0.0475), and no siginifcant difference
was found in morphotype evenness between Webster nursery and Johnon prairie in
2011(W=135, n1=n2= 16, P=0.8025) (Table 3). There was no significant difference found
in visiting insect morphotype diversity between Webster nursery and Johnson prairie in
either year for L. albicaulis (2011- H’: W=127.5, n1=n2=16, P=1.0000 D: W=122,
n1=n2=16, P=0.8324; 2012- H’: W=364.5, n1=n2=30, P=0.0529 D: W=364.5, n1=n2=30,
P=0.0529), but interestingly, diversity was higher in 2011 than in 2012 at both sites
(Webster- H’: W=338, n1=16, n2=30, P=0.0130 D: W=340, n1=16, n2=30, P=0.0113;
Johnson- H’: W=355.5, n1=16, n2=30, P=0.0004 D: W=356.5, n1=16, n2=30, P=0.0003)
(Table 3).
31
Table 3. Results of Evenness, Shannon’s Diversity (H’) and Simpson’s Diversity (D)
indices for visiting insect morphotypes at Webster nursery and Johnson prairie.
Plant Species
Year Site
E
H’
D
Balsamorhiza deltoidea
2011 Nursery
0.000a 0.000a 0.0000a
Balsamorhiza deltoidea
2011 Prairie
0.167a 0.116a 0.0833a
Balsamorhiza deltoidea
2012 Nursery
0.399b 0.285b 0.1933b
Balsamorhiza deltoidea
2012 Prairie
0.107a 0.087a 0.0555a
Lupinus albicaulis
2011 Nursery
0.363a 0.352a 0.1980a
Lupinus albicaulis
2011 Prairie
0.427a 0.369a 0.2315a
Lupinus albicaulis
2012 Nursery
0.218a 0.161b 0.1062b
Lupinus albicaulis
2012 Prairie
0.058b 0.051 b 0.0325b
Different letters after S, E, H’, and D values indicate a significant difference between
sites and years based on two-sample Wilcoxon test results.
Insect community composition and total number of visits by each group varied between
sites and years (Figures 5 & 6). In 2011 at Webster nursery, the greatest number of visits
to B. deltoidea was made by honeybees and green metallic bees and bumblebees were
absent. In 2012, bumblebees made the greatest number of visits and honeybees and green
metallic bees were absent. Bumblebees visited B. deltoidea more frequently than any
other morphotype at both sites in 2012, but not in 2011. In 2011, bumblebees made the
greatest number of visits to L. albicaulis at Johnson prairie, but almost no visits were
made by bumblebees to L. albicaulis at Johnson prairie in 2012.
32
100
90
80
Bumblebees
70
Ants
60
Beetles
50
Flies
40
Honey Bees
30
Cuckoo Bees
20
Green Metallic Bees
10
Large Dark Bees
0
Small Dark Bees
Nursery
Prairie
Nursery
2011
Prairie
2012
Figure 5. Total number of visits (from all observations summed) made to Balsamorhiza
deltoidea by each insect morphotype.
700
600
500
Bumblebees
400
Beetles
300
Wasps
Flies
200
Large Dark Bees
100
Small Dark Bees
0
Nursery
Prairie
2011
Nursery
Prairie
2012
Figure 6. Total number of visits (from all observations summed) made to Lupinus
albicaulis by each insect morphotype.
33
In 2011 and 2012 significantly different insect communities visited plants
between Webster nursery and Johnson prairie. Specifically, in 2011 differences in
community structure existed only for insects visiting L. albicaulis (Table 4); however, in
2012 differences in community structure existed for insects visiting both B. deltoidea and
L. albicaulis (Figure 7; Table 4).
Table 4. perMANOVA Results for Influence of Location (Webstery nursery and Johnson
prairie) on Community Structure of Visiting Insects
Plant Species
Year
F
d.f.
P
Balsamorhiza deltoidea
2011
1.3607
11
0.3538
Balsamorhiza deltoidea
2012
9.7535
59
0.0002
Lupinus albicaulis
2011
4.4255
31
0.0006
Lupinus albicaulis
2012
4.6195
59
0.0006
Significant results are in bold.
Figure 7. A representative NMDS ordination plot of influence of site differences on
visiting insect community structure for Lupinus albicaulis in 2012. Location 1= Webster
nursery. Location 2= Johnson prairie.
Indicator species analysis provides evidence for the preferences of certain insects
for certain environmental conditions. Data were pooled across the nursery and prairie for
34
these analyses. Bombus mixtus and B. vosnesenskii were significant indicator species for
L. albicaulis at Webster nursery in both years (Table 5).
Table 5. Indicator Species and Morphotype P Values for Location (Webster nursery or
Johnson prairie)
Visiting Insect
Balsamorhiza deltoidea
Lupinus albicaulis
Species/Morphotype
2011
2012
2011
2012
Small Dark Bees
----0.0562
0.1826
0.1166
Large Dark Bees
1.0000
1.0000
1.0000
0.4433
Green Metallic Bees
1.0000
0.4881
--------Honey Bees
1.0000
------------Cuckoo Bees
----0.4819
--------Bombus mixtus
1.0000
1.0000
0.0002*
0.0002*
Bombus vosnesenkii
----0.0904
0.0196*
0.0044*
Bombus sitkensis
----0.0788
0.2703
0.7491
Bombus melanopygus
----0.2466
1.0000
1.0000
Bombus flavifrons
----1.0000
--------Bombus californicus
------------1.0000
Wasps
--------1.0000
----Beetles
----0.7441
1.0000
0.2334
Flies
0.1840
1.0000
0.2270
1.0000
Ants
1.0000
------------Significant results are in bold. *Significant indicator for Webster nursery **Significant
indicator for Johnson prairie
Bombus mixtus and B. vosnesenskii were also significant indicator species for a light
breeze and clear skies for L. albicaulis in 2011 (Tables 6 & 7). When conditions were
partly cloudy, more often than not, no insect visitors were present (Table 7). In 2012, B.
melanopygus was a significant indicator of temperatures around 13 0C and an absence of
visiting insect species was a significant indicator of high wind speeds for B. deltoidea
(Tables 7 & 8). For insects visiting L. albicaulis in 2012, B. mixtus was a significant
indicator species for temperatures around 16 0C; B. sitkensis and B. mixtus were
significant indicator species for calm wind speeds; small dark bees and large dark bees
were significant indicators of clear skies; and B. mixtus was a significant indicator species
for mostly cloudy skies (Tables 6, 7, & 8).
35
Table 6. Indicator Species and Morphotype P Values for Wind Speed
Visiting Insect
Balsamorhiza deltoidea
Lupinus albicaulis
Species/Morphotype
2011
2012
2011
2012
Small Dark Bees
----0.3891
0.2747
0.6469
Large Dark Bees
1.0000
0.4293
0.6293
0.6263
Green Metallic Bees
1.0000
0.3415
--------Honey Bees
1.0000
------------Cuckoo Bees
----0.9196
--------Bombus mixtus
1.0000
0.8026
0.0148**
0.0034*
Bombus vosnesenkii
----0.4015
0.0004**
0.1104
Bombus sitkensis
----0.7027
0.6519
0.0122*
Bombus melanopygus
----0.3935
1.0000
0.8006
Bombus flavifrons
----0.6707
--------Bombus californicus
------------0.2118
Wasps
--------0.3851
----Beetles
----0.7898
0.3695
0.2547
Flies
0.1810
0.1814
0.4485
0.6133
Ants
1.0000
------------No Species
1.0000
0.03708*** 0.6283
0.2659
Significant results are in bold. * Significant indicator for calm wind conditions
**Significant indicator for light breeze ***Significant indicator for windy conditions
Table 7. Indicator Species and Morphotype P Values for Cloud Cover
Visiting Insect
Balsamorhiza deltoidea
Lupinus albicaulis
Species/Morphotype
2011
2012
2011
2012
Small Dark Bees
----0.4649
0.3873
0.0014*
Large Dark Bees
0.1676
1.0000
0.5083
0.0006*
Green Metallic Bees
0.4915
0.3243
--------Honey Bees
0.4959
------------Cuckoo Bees
----0.2983
--------Bombus mixtus
1.0000
1.0000
0.0154*
0.0252***
Bombus vosnesenkii
----0.3563
0.0250*
0.0856
Bombus sitkensis
----0.6415
0.1252
0.0676
Bombus melanopygus
----1.0000
0.2585
1.0000
Bombus flavifrons
----0.4937
--------Bombus californicus
------------1.0000
Wasps
--------1.0000
----Beetles
----0.5631
1.0000
0.2507
Flies
0.1532
1.0000
0.0568
0.4237
Ants
1.0000
------------No Species
1.0000
0.1658
0.0070**
0.2943
Significant results are in bold. *Significant indicator of clear skies **Significant indicator
of partly cloudy skies *Significant indicator of mostly cloudy skies
36
Table 8. Indicator Species and Morphotype P Values for Temperature
Visiting Insect
Balsamorhiza deltoidea
Lupinus albicaulis
Species/Morphotype
2011
2012
2012
Small Dark Bees
----0.4265
0.9860
Large Dark Bees
0.1716
0.5827
0.2076
Green Metallic Bees
1.0000
0.3003
----Honey Bees
1.0000
--------Cuckoo Bees
----0.1356
----Bombus mixtus
1.0000
1.0000
0.0330**
Bombus vosnesenkii
----0.2711
0.9362
Bombus sitkensis
----0.8544
0.5093
Bombus melanopygus
----0.0428*
0.4191
Bombus flavifrons
----0.5811
----Bombus californicus
--------0.7123
Beetles
----0.2216
0.9526
Flies
0.8620
0.1198
1.0000
Ants
1.0000
--------No Species
1.0000
0.3071
0.5105
Significant results are in bold. *Significant indicator of temperatures around 13 0C
**Significant indicator of temperatures around 16 0C
Environmental conditions influenced visiting insect community structure. Wind
speed and cloud cover significantly influenced visiting insect community structure for L.
albicaulis in 2011 (Table 9); and temperature, wind speed, and cloud cover significantly
influenced community structure of insects visiting L. albicaulis in 2012 (Table 9).
Table 9. MRPP Results for Influence of Temperature, Wind Speed, and Cloud Cover on
Community Structure of Visiting Insects
Temperature Wind Speed Cloud Cover
Plant Species
Year
A
P
A
P
A
P
Balsamorhiza deltoidea
2011 -0.042 0.732 0.016 0.261 -0.038 0.642
Balsamorhiza deltoidea
2012 0.052 0.126 0.012 0.328
0.068 0.352
Lupinus albicaulis
2011 ----- -----*
0.042 0.008 0.068 0.001
Lupinus albicaulis
2012 0.071 0.033 0.085 0.006 0.027 0.018
Significant results are in bold. *In 2011, temperatures were all in the same range for all
observations taken for L. albicaulis.
37
Pollinator Limitation
Pollinator limitation was not evident for either plant species at either site. No significant
difference was found between number or percentage of viable seeds produced by
naturally-pollinated inflorescences and hand-cross-pollinated inflorescences for B.
deltoidea at either site in 2012 (Figure 8).
A.
B.
Figure 8. A) Percent and B) number of viable seeds produced by naturally pollinated and
hand-cross pollinated Balsamorhiza deltoidea inflorescences at Webster nursery and
Johnson prairie in 2012.
38
Although no pollinator limitation was observed for either plant species, some of
the L. albicaulis treatments did produce different numbers of viable seed. Naturallypollinated inflorescences produced a significantly greater number of viable seeds than the
hand-self-pollinated inflorescences (W=102.5, n1=n2=20, P=0.0016) and the unassisted
self-pollinated inflorescences (W=293.5, n1=n2=20, P=0.0025) (Figure 9). Hand-crosspollinated inflorescences produced a significantly greater number of viable seeds than the
hand-self-pollinated inflorescences (W=288, n1=n2=20, P=0.0035) and the unassisted
self-pollinated inflorescences (W=284.5, n1=n2=20, P=0.0051) (Figure 0). No significant
difference was found between numbers of viable seeds produced by naturally-pollinated
and control inflorescences (Figure 9).
39
Figure 9. A) Number and B) percentage of viable seeds, C) number of seeds per flower,
D) seeds per ovule, E) seeds per pod, and F) pods per flower produced by Lupinus
albicaulis for each treatment. n1=n2=20 for all treatments.
40
Visitation Rate vs. Viable Seed Production
Visitation rate was not found to significantly influence the number or percentage of
viable seeds produced by either plant species (Table 10). Seeds per flower, seeds per
ovule, seeds per pod, and pods per flower of L. albicaulis were not found to be
significantly related to insect visitation rates (Table 10).
Table 10. Results of Linear Regressions Comparing Insect Visitation Rates (# Visits per
Inflorescence per Hour) to Various Measures of Reproduction
Plant Species
Reproductive Measures
F
d.f.
P
Balsamorhiza deltoidea
% Viable Seeds Produced
1.12 1,25 0.3000
Balsamorhiza deltoidea
# Viable Seeds Produced
1.12 1.25 0.3000
Lupinus albicaulis
% Viable Seeds Produced
1.74 1,18 0.2038
Lupinus albicaulis
# Viable Seeds Produced
0.17 1,18 0.6860
Lupinus albicaulis
Seeds per Flower
0.01 1,18 0.9100
Lupinus albicaulis
Seeds per Ovule
0.02 1,18 0.8959
Lupinus albicaulis
Seeds per Pod
0.00 1,18 0.9445
Lupinus albicaulis
Pods per Flowers
0.59 1,18 0.4515
Balsamorhiza deltoidea plant size was compared to seed production to determine the
influence of overall productivity on fecundity. Diameter of the inflorescence was not
found to significantly affect the percentage or number of seeds produced by B. deltoidea
(Table 11) although there was a non-significant positive trend (Figure 10). Plant volume
was also not found to significantly affect seed production (Table 11), but results showed
a non-significant negative trend (Figure 11).
Table 11. Results of Linear Regressions Comparing Inflorescence Diameter or Plant
Volume to Seed Production for Balsamorhiza deltoidea
Comparison
F
d.f.
P
Inflorescence Diameter to % Viable Seeds Produced
1.84 1,24 0.1877
Inflorescence Diameter to # Viable Seeds Produced
1.84 1,24 0.1877
Plant Volume (cm3) to % Viable Seeds Produced
0.42 1,24 0.5253
3
Plant Volume (cm ) to # Viable Seeds Produced
0.42 1,24 0.5253
41
Number Viable Seeds
10
9
8
7
6
5
4
3
2
1
0
y = 1.2539x - 0.349
R² = 0.0712
0.0
1.0
2.0
3.0
4.0
5.0
6.0
Inflorescence Diameter (cm)
.
Number Viable Seeds
Figure 10. Inflorescence diameter vs. number of viable seeds produced by Balsamorhiza
deltoidea
10
9
8
7
6
5
4
3
2
1
0
y = -3E-06x + 4.3428
R² = 0.017
0
100000 200000 300000 400000 500000 600000 700000 800000
Plant Volume (cm3)
.
Figure 11. Plant volume vs. number of viable seeds produced by Balsamorhiza deltoidea
DISCUSSION
Characteristics of Webster nursery appear to be attracting higher insect visitation than at
Johnson prairie. Insect visitation rates at the nursery exceeded rates at the prairie
unexpectedly given that the nursery is located in an area with assumed fewer resources
42
for pollinators. Sample size may have been too low to detect a difference in visitation
rates between sites for B. deltoidea in 2011. Plants for native seed production have been
grown at Webster nursery only in the last three years, so there has not been much time for
these resources to attract pollinator populations. Matteson et al. (2012) found it
inappropriate to generalize about landscapes created by humans as land-use types can
vary greatly in suitability for pollinators. Some researchers found that bee abundance
increases in human-constructed landscapes developed with a superabundance of floral
resources, and that a combination of natural and developed landscapes can provide a
greater diversity of habitat resources (Frankie et al. 2009). Also, some bees can rapidly
increase offspring production in response to an increase in floral resources because less
foraging time means less time they are exposed to predators and parasites (Goodell
2003). I recommend considering characteristics at Webster that may be attracting more
insects, and then investigating ways to enhance these at Johnson. Since some insect group
visitation rates differed between the sites, this creates an opportunity to design restoration
strategies geared toward specific insect types to increase visitation at Johnson prairie. For
example, nesting habitat and floral resources that attract B. mixtus could be enhanced at
Johnson to encourage more activity from this particular species that is known to visit L.
albicaulis frequently, given the evidence from Webster nursery.
Environmental conditions can influence visiting insect community composition at
both nursery and prairie sites. Insect types can have different levels of effectiveness at
pollinating flowers so a change in the visiting insect community can affect plant
reproduction differently. Visiting insect community composition, proportion of visits
made by each insect morphotype, and insect morphotype richness, diversity, and
43
evenness varied between years. Certain insect morphotypes preferred certain weather
conditions. Weather conditions during sampling times may have affected the visitation
rate results and community composition data for comparisons between sites for L.
albicaulis. There was no evidence that temperature, wind speed, or cloud cover
influenced observations for B. deltoidea as they were the same during observation times
at Webster nursery and Johnson prairie, but other factors such as time of year or weather
conditions earlier in the year may have been influential. Sampling dates and bloom times
were several weeks earlier in 2012 than 2011, and this could have affected the insect
community present between years.
The variation in visiting insect community composition seen in this study is not
surprising given that other researchers have found weather conditions and seasonal
fluctuations to be significant factors influencing community composition and insect
visitation rates. Different insect species have been found to have different preferential
weather conditions for foraging (Arroyo et al. 1982). Temperature and cloud cover have
been found to influence insect visitation rates more than humidity, wind speed, season,
and time of day in another study, although all factors had some influence depending on
the study site (McCall & Primack 1992). Lower temperatures have been found to
coincide with lower levels of insect activity in general (Arroyo et al. 1985). Weather
conditions and bloom times can vary from year to year and site to site, so visiting insect
communities and rates of visitation can vary as well. oth study years occurred during La
Ni a weather conditions characteri ed by lower temperatures and more cloud cover than
most years (National Weather Service 2012). My results highlight that long term data
collection is needed to make more accurate generalizations of visitation to a site.
44
Increasing insect visitation at Webster nursery may not be a conservation priority
given a lack of evidence for pollinator limitation for either study plant species at either
site. In addition, no evidence was found that supplemental pollen increases viable seed
production for the plants in this study. Fazzino et al. (2011) found that hand-pollinated
inflorescences produced more sprouting seeds than naturally-pollinated inflorescences for
B. deltoidea in the Puget lowland prairies. In contrast, the B. deltoidea plants in this study
were either not pollinator-limited or the hand-pollinated inflorescences did not receive
enough supplemental pollen by hand to show a difference. Increasing the number of
replicates in a repeated study may yield different results for both plant species. Although
cross-pollination is necessary for maintaining genetic diversity, autogamous plants may
still produce viable seeds in the absence of pollinators (Arathi et al. 2002). Lupinus
albicaulis did not show evidence for autogamy, although the self-pollinated
inflorescences may have produced fewer viable seeds than the cross-pollinated
inflorescences if the pollinator exclusion bags covering them caused a treatment effect.
In this experiment, I assumed more pollen would increase viable seed production.
Ashman et al. (2004) state that when maximum seed production is reached there are no
longer unfertilized ovules for additional pollen to be of benefit. Cane & Schiffhauer
(2003) discovered a point of pollen saturation on stigmas. Supplemental pollen negatively
affected seed weight in Hegland &Totland’s (2008) study on pollinator limitation at the
community level. I did not find evidence that insect visitation influenced viable seed
production for the study plants; however, visitation rate is only one of many factors that
may influence the number of viable seeds a plant produces. Availability of resources such
as soil nutrients, water, and light can also affect plant reproduction (Stephenson 1981;
45
Corbet 1998; Bos et al. 2007), and seed handling and storage practices can affect seed
viability. In addition, changes in light and temperature during germination can affect L.
albicaulis seed viability (Morey & Bakker 2011). I recommend that land managers turn
efforts towards investigating the influence of the above factors on native seed production
in future studies.
ACKNOWLEDEMENTS
I thank H. Elizabeth Kirkpatrick, University of Puget Sound, for her suggestions on
designing this pollinator experiment. I thank the Center for Natural Lands Management
for their support and Joint Base Lewis-McChord for permission to conduct research on
their lands. I thank Greg Dasso, The Evergreen State College, for helping me get set-up
in the lab. I also thank The Evergreen State College Foundation and the Evergreen
Sustainability Fellowship committee for their financial support. Finally, a special thank
you to my grandma, Polly Robinson, for her help with sewing pollinator exclusion bags.
LITERATURE CITED
Arathi HS, Rasch A, Cox C, Kelly JK (2002) Autogamy and floral longevity in Mimulus
guttatus. International Journal of Plant Sciences 163:567-573.
Arroyo MTK, Armesto JJ, Primack RB (1985) Community studies in pollination ecology
in the high temperate Andes of central Chile II. Effect of temperature on visitation
rates and pollination possibilities. Plant Systematics and Evolution 149:187-203.
46
Arroyo MT, Primack R, Armesto J (1982) Community studies in pollination ecology in
the high temperate Andies of central Chile I. Pollination Mechanisms and
Altitudinal Variation. American Journal of Botany 69:82-97.
Ashman T, Knight TM, Steets JA, Amarasekare P, Burd M, Campbell DR, Dudash MR,
Johnston MO, Mazer SJ, Mitchell RJ, Morgan MT, Wilson WG (2004) Pollen
limitation of plant reproduction: Ecological and evolutionary causes and
consequences. Ecology 85:2408-2421.
Berry PE, Calvo RN (1989) Wind pollination, self-incompatibility, and altitudinal shifts
in pollination systems in the high Andean genus Espeletia (Asteraceae). American
Journal of Botany 76:1602-1614.
Bos MM, Veddeler D, Bogdanski AK, Klein A, Tscharntke T, Steffan-Dewenter I,
Tylainakis JM (2007) Caveats to quantifying ecosystem services: Fruit abortion
blurs benefits from crop pollination. Ecological Applications 17:1841-1849.
Boyd AE (2004) Breeding system of Macromeria viridiflora (Boraginaceae) and
geographic variation in pollinator assemblages. American Journal of Botany
91:1809-1813.
Cane JH, Schiffhauer D (2003) Dose-response relationships between pollination and
fruiting refine pollinator comparisons for cranberry (Vaccinium macrocarpon
[Ericaceae]). American Journal of Botany 90:1425-1432.
Corbet SA (1998) Fruit and seed production in relation to pollination and resources in
Bluebell, Hyacinthoides non-scripta. Oecologia 114:349-360.
Dieringer G (1992) Pollinator limitation in populations of Agalinis strictifolia
(Scrophulariaceae). Bulletin of the Torrey Botanical Club 119:131-136.
47
Elliott CW, Fischer DG, LeRoy CJ (2011) Germination of three native Lupinus species in
response to temperature. Northwest Science 85:403-410.
Engel EC, Irwin RE (2003) Linking pollinator visitation rate and pollen receipt.
American Journal of Botany 90:1612-1618.
Fazzino L, Kirkpatrick HE, Fimbel C (2011) Comparison of hand-pollinated and
naturally-pollinated Puget balsamroot (Balsamorhiza deltoidea Nutt.) to
determine pollinator limitations on South Puget Sound lowland prairies.
Northwest Science 85: 352-360.
Fimbel C (2010) Center for Natural Lands Management. Personal Communication.
Fontaine C, Dajoz I, Meriguet J, Loreau M (2006) Functional diversity of plant-pollinator
interaction webs enhances the persistence of plant communities. PLoS Biology
4:0129-0135. [online] URL: www.plosbiology.org (accessed June 2011).
Frankie GW, Thorp RW, Hernandez J, Rizzardi M, Ertter B, Pawelek JC, Witt SL,
Schindler M, Coville R, Wojcik VA (2009) Native bees are a rich natural resource
in urban California gardens. University of California. California Agriculture
[online] URL: http://californiaagriculture.ucanr.edu (accessed Oct 2012).
Goodell K (2003) Food availability affects Osmia pumila (Hymenoptera: Megachilidae)
foraging, reproduction, and brood parasitism. Oecologia 134:518-527.
Hegland SJ, Totland O (2008) Is the magnitude of pollen limitation in a plant community
affected by pollinator visitation and plant species specialization levels? Oikos
117:883-891.
48
Inouye DW, Pyke GH (1988) Pollination in the snowy mountains of Australia:
Comparisons with montane Colorado, USA. Australian Journal of Ecology
13:191-210.
International Seed Testing Association (2012) International Rules for Seed Testing
(2012ed.). Bassersdorf: Switzerland.
Kearns CA, Inouye DW (1993) Techniques for Pollination Biologists. University Press of
Colorado, Niwot.
Kremen C, Williams NM, Aizen MA, Gemmill-Herren B, LeBuhn G, Minckley R,
Packer L, Potts SG, Roulston T, Steffan-Dewenter I, Vazquez DP, Winfree R,
Adams L, Crone EE, Greenleaf SS, Keitt TH, Klein A, Regetz J, Ricketts TH
(2007) Pollination and other ecosystem services produced by mobile organisms:
A conceptual framework for effects of land-use change. Ecology Letters 10:299314.
Matteson KC, Grace JB, Minor ES (2012) Direct and indirect effects of land use on floral
resources and flower-visiting insects across an urban landscape. Oikos doi:
10.1111/j.1600-0706.2012.20229.x [online] URL: onlinelibrary.wiley.com
(accessed Nov. 2012).
Mayer C, Adler L, Armbruster S, Dafni A, Eardley C, Huang S, Kevan PG, Ollerton J,
Packer L, Ssymank A, Stout JC, Potts SG (2011) Pollination ecology in the 21st
century: Key questions for future research. Journal of Pollination Ecology 3:8-23.
McCall C, Primack RB (1992) Influence of flower characteristics, weather, time of day,
and season on insect visitation rates in three plant communities. American Journal
of Botany 79:434-442.
49
McCarty JP (2001) Ecological consequences of recent climate change. Conservation
Biology 15:320-331.
Morey M and Bakker J (2011) Effects of light and temperature regimes on germination
and viability of native WA prairie species. Undergraduate senior project. School
of Forest Resources, University of Washington, Seattle, WA.
National Weather Service (2012) Climate Prediction Center. National Oceanic and
Atmospheric Administration [online] URL: www.nws.noaa.gov (accessed Oct
2012).
USDA Natural Resources Conservation Service (2012) Plants Database. [online] URL:
www.plants.usda.gov (accessed Oct 2012).
Perfectti F, Gomez JM, Bosch J (2009) The functional consequences of diversity in plantpollinator interactions. Oikos 118:1430-1440.
Price MV, Campbell DR, Waser NM, Brody AK (2008) Bridging the generation gap in
plants: Pollination, parental fecundity, and offspring demography. Ecology
89:1596-1604.
South Sound Prairies Working Group (2011) Historic prairie landscape. South Sound
Prairies [online] URL: http://www.southsoundprairies.org/historic-prairielandscapes/ (accessed Feb 2012).
Stanley AG, Kaye TN, Dunwiddie PW (2008) Regional strategies for restoring invaded
prairies: Observations from a multisite, collaborative research project. Native
Plants Journal 9:247-254.
Stephenson AG (1981) Flower and fruit abortion: Proximate causes and ultimate
functions. Annual Review of Ecology and Systematics 12:253-279.
50
Stinson DW (2005) Washington State Department of Fish and Wildlife. Washington
State status report for the Mazama pocket gopher, streaked horned lark, and
Taylor’s checker spot. Olympia.
Tscheulin T, Petanidou T (2011) Does spatial population structure affect seed set in
pollen-limited Thymus capitatus? Apidologie 42:67-77.
Vila M, Weiner J (2004) Are invasive plant species better competitors than native plant
species? – Evidence from pair-wise experiments. Oikos 105:229-238.
Washington Natural Heritage Program (2012) Washington Department of Natural
Resources [online] URL: http://www1.dnr.wa.gov/nhp/refdesk/lists/plantrnk.html
(accessed August 2012).
Wilson MV, Hammond PC, Schultz CB (1997) The interdependence of native plants and
Fender’s blue butterfly. In: Kaye TN, Liston A, Love RM, Luomo D, Meinke RJ,
Wilson MV (eds) Conservation management of native flora and fungi. Native
Plant Society of Oregon, Corvallis, pp 83-87.
51
Chapter 3: Interdisciplinary Connections
Pollination ecology is inherently interdisciplinary. Throughout the process of completing
this thesis, I crossed back-and-forth over lines of several disciplines within the realm of
natural science. My personal interest in this topic stemmed from a background in botany,
but this thesis required that I learn entomology, ecology, multivariate statistics, and even
a bit of chemistry.
Nevertheless, pollination ecology is not just about natural science. This thesis has
both political and economic connections. Through the process of selecting this topic, I
found that many different stakeholders are involved in Puget lowland prairie conservation
due to policies written for the protection of biodiversity. Investigating ways to improve
restoration practices and to prevent further losses to this ecosystem has potential benefits
for human society at large. Pollinators provide an essential ecosystem service that affects
the local economy, agriculture, and homeowners. A better understanding of the
pollination web could influence conservation policy at many levels.
PUGET LOWLAND PRAIRIE STAKEHOLDER VIEWS
Numerous stakeholders are invested in protecting the Puget lowland prairies for various
reasons and a better understanding of pollination could influence conservation policies.
Concerned stakeholders exist at all levels, including: federal, state, and county agencies,
private non-profit organizations, farmers, and private citizens.
Federal Agencies
Federal agencies have the duty to uphold the Endangered Species Act of 1973 mandating
that endangered species and their habitat be protected. This act, among other conservation
policies, gives a voice to many plants and animals that are a part of the threatened Puget
52
lowland prairie ecosystem. At the federal level, the Endangered Species Act involves the
U.S. Fish and Wildlife Service, the U.S. Department of Defense, the U.S. Natural
Resources Conservation Service, and the U.S. Environmental Protection Agency when it
comes to considering Puget lowland prairie protection.
The U.S. Fish and Wildlife Service is responsible for administering the
Endangered Species Act to recover listed species to levels at which their protection is no
longer necessary (U.S. Fish and Wildlife Service 2012). Three species found in the Puget
lowland prairies are considered for listing under this act —Taylor’s checkerspot butterfly
(Euphydryas editha taylori) has been proposed as endangered, Streaked Horn Lark
(Eremophila alpestris strigata) has been proposed as threatened, and the Mazama pocket
gopher (Thomomys mazama) is a candidate (U.S. Fish and Wildlife Service 2012). One
plant species, golden paintbrush (C. levisecta) is already listed as threatened (U.S. Fish
and Wildlife Service 2012). If pollinator species are found to be keystone species that are
critical for endangered plant survival or for survival of plants that are critical habitat for
endangered animals, they would need to be considered in habitat conservation plans for
species listed under the Endangered Species Act.
Two thirds of the remaining 20,000 acres of Puget lowland prairies are located on
Joint-Base Lewis McChord (JBLM), owned by the U.S. Department of Defense (USAEC
2012). Some of the healthiest examples of Puget lowland prairie habitat exist on these
lands (Cheryl Fimbel, CNLM, pers. comm. 2010). Historically, the Puget lowland
prairies had been maintained by Native American burning (South Sound Prairies 2012).
Fire is an important part of the ecosystem that prevents conifer encroachment (South
Sound Prairies 2012). Often training activity on Joint-Base Lewis McChord has had the
53
unintended consequence of setting fire to the Puget lowland prairies on base and has
unexpectedly benefited the ecosystem. Not all training activity is beneficial to this
ecosystem and training restrictions could still be imposed on this large area of land
because it is critical habitat for all three Puget lowland prairie candidate species. To avoid
these restrictions, the Army Compatible Use Buffer program was formed to create land
conservation partnerships with JBLM and other organizations to restore prairies on and
around training lands (USAEC 2012).
USDA Natural Resources Conservation Services (NRCS) goal is to maintain a
sustainable food supply as well as healthy ecosystems (U.S. NRCS 2012).Under the
Food, Conservation, and Energy Act of 2008, otherwise known as the Farm Bill, the
NRCS is authorized to create conservation programs for agricultural lands (U.S. NRCS
2012). One of the NRCS programs, the Wildlife Habitat Incentive Program, has been
used in Thurston County to restore Puget lowland prairies by providing financial
incentives to develop habitat for fish and wildlife on private lands (U.S. NRCS 2012).
The Farm Bill has already established conserving wild pollinator habitat as a priority goal
(U.S. Natural Resources Conservation Service 2008).
Tasked with regulating any activity that may harm the environment, the U.S.
Environmental Protection Agency (EPA) has provided funding for conservation and
restoration projects for a unique subset of Puget lowland wet prairies (U.S.
Environmental Protection Agency 2012). The EPA partners with other agencies and nonprofit organizations to protect the Puget lowland prairies. Under the Federal
Environmental Pesticide Control Act of 1972, the EPA regulates pesticides that can harm
54
pollinators and they may make adjustments to this policy as new information on the
effects of chemicals on insects becomes available (Burlew 2010).
State Agencies
State agencies have the responsibility of maintaining natural resources sustainably while
promoting economic use of those resources to enhance the state’s economy. Washington
State Department of Natural Resources, Department of Transportation, Department of
Fish and Wildlife, and even Department of Corrections all participate in Puget lowland
prairie restoration.
Washington Department of Natural Resources manages two Puget lowland prairie
sites, Mima Mounds and Rocky Prairie, as Natural Area Preserves. The Natural Areas
Preserve Act of 1972 designates these areas to be protected as high quality examples of
Washington State’s native ecosystems to be used for education, scientific research, and to
maintain biological diversity (Washington State Department of Natural Resources 2012).
Native Puget lowland prairie pollinators are necessary components of this rare
Washington State ecosystem, and if they are threatened, these insects may fall under the
Natural Areas Preserve Act as a component in need of protection.
In 1981, the Washington Natural Heritage Program (WNHP) was established
within DNR by the Washington legislature to identify, manage, and share information on
priority species and ecosystems for environmental assessments and conservation planning
(Washington State Department of Natural Resources 2012). Several plant species found
in the Puget lowland prairies are on WNHP’s rare plant species list including B. deltoidea
(Washington Natural Heritage Program 2012).
55
Washington Department of Transportation’s Environmental Services Office is
dedicated to protecting critical habitat for the prairie species listed under the Endangered
Species Act (Washington State Department of Transportation 2012). Considerations of
these habitats are a part of the Agency’s environmental impact assessments for all
building projects (Washington State Department of Transportation 2012). Roadside rightof-ways have been considered valuable pollinator corridors (Wojcik & Buchmann 2012)
which may change WSDOT best management practices for how they maintain their land
along state highways.
Washington State Department of Fish and Wildlife owns another piece of the
remaining Puget lowland prairies, Scatter Creek Wildlife Area. This site is managed for
conservation as well as recreation such as hunting, bird-watching, and horseback riding
(Washington State Department of Fish and Wildlife 2012).
Prisoners are also involved in Puget lowland prairie conservation. The
Sustainability in Prisons Project (SPP) provides inmates with job experience while
raising Taylor’s checkerspot butterflies for release into the Puget lowland prairies, and
propagating over 50 species of native prairie plants (TESC and WSDOC 2012). The
project was created through a partnership between The Evergreen State College and
Washington State Department of Corrections.
Regional Agencies
County agencies hold responsibility for sustainable land-use planning for residential and
business communities around the Puget lowland prairies. The remaining Puget lowland
prairie fragments are located in both Thurston and Pierce counties. Thurston Parks and
Recreation manages Glacial Heritage Preserve which is only open for Thurston County
56
sponsored environmental and educational activities (Thurston County Parks and
Recreation 2012). Streaked-horned larks nest at the Olympia airport and because they are
a sensitive Puget lowland prairie species, the Port of Olympia has partnered with WDFW
to create best management practices to protect Puget lowland prairie species as required
by the State Environmental Policy Act (Port of Olympia 2012). Prairies in Pierce County
are located on and managed by Joint-Base Lewis McChord. Local agencies may be
mandated under the State Environmental Policy Act to create best management practices
to protect Puget lowland prairie pollinators if they become limited.
Non-profit organizations aim to protect wildlife and habitat. In 2011, the Nature
Conservancy passed on its 17 year legacy of being a primary land manager for the Puget
lowland prairies to the CNLM. The CNLM partners with other organizations, including
Joint Base Lewis-McChord, to assist with restoration on their lands (South Puget Sound
Prairies Working Group 2012). CNLM staff, SPP staff, and prison crews are joined by a
dedicated group of volunteers from the community who do everything from pulling
invasive weeds to collecting native seed at both the prairies and the native seed nurseries.
School groups also participate in Puget lowland prairie restoration with the CNLM and
join in educational events hosted by the organization such as Prairie Appreciation Day.
Other non-profit conservation organizations are also active in Puget lowland
prairie restoration and education. Wolf Haven International is a Puget lowland prairie
landowner. The focus of Wolf Haven is on wolf conservation, though the prairies on their
land also attract visitors (Wolf Haven International 2012). The Audubon Society is not
only interested in protecting birds, but the ecosystems on which they depend and they
have formed partnerships with other organizations to conserve Puget lowland prairie
57
ecosystems as well (National Audubon Society 2012). Capitol Land Trust is a local,
community-based organization that buys or accepts donations of land or conservation
easements to protect natural areas including several Puget lowland prairies (Capitol Land
Trust 2012).
Private citizens are also invested in Puget lowland prairie conservation. The
diverse farming sector of this region wants productive crops and native insects often
substantially contribute to crop pollination along with introduced honey bees (U.S.
Natural Resources Conservation Service 2008). Local, private, land-owning citizens
value the aesthetic quality of prairie landscapes, recreational opportunities, and would
like to develop their land as they see fit. Federal and private grants are available to landowners with Puget lowland prairie habitat to provide incentives to conserve this
ecosystem (South Puget Sound Prairies Working Group 2012).
WHY CONSERVE BIODIVERSITY?
Today we live in a world of human-dominated ecosystems facing faster anthropogenic
extinction rates than ever before (Primack 2010). Biodiversity provides a variety of
ecological services that benefit humans. All species play an important role in providing
these services. This is why it is essential to understand the role pollinators play in
protecting plant biodiversity.
Losing a diversity of species means more than the loss of fun discoveries on a
weekend hike, it also means the loss of the ecological functions each individual species
provides. Healthy ecosystems composed of complex networks of interactions provide
humans with food, shelter, oxygen, medicine, recreation, waste removal, etc. These
functions are considered ecosystem services, another is pollination. Sixty to ninety
58
percent of plant species require an animal pollinator (Kremen et al. 2007), and humans
would have to figure out how to replace them if they disappear, which would be both
costly and time-consuming.
Individual species all play a part in ecosystems. Keystone species have a
dominate role to play in structuring ecosystems, but keystone species cannot hold a
complex ecosystem and all of its functions together alone. Other species provide, at the
very least, redundancy and genetic variation within communities (Primack 2010). Genetic
diversity allows species to evolve and survive in a changing environment.
In the threatened Puget lowland prairie ecosystem, pollinators are a potential
limiting factor in maintaining floral diversity. Pollinators provide an essential ecosystem
service by facilitating sexual reproduction in plants, thereby mixing genes.
POLLINATION AS AN ECOSYSTEM SERVICE
Economically, there are incentives to better understand how pollination affects floral
diversity at the Puget lowland prairies. Estimates of the global annual value of pollinator
services range from $112 to 200 billion, and no studies have yet attempted to estimate the
value of ecosystem services provided by native plants that are due to animal pollination
(Kremen et al. 2007). Protecting pollination now, prevents having to figure out what to
do if this ecosystem service is lost, decreases the need for supplemental seed and
replanting, and supports local agriculture.
Land managers would be left with limited options if pollinators are lost.
Replacing the services of native insects with honey bees or hand-pollination may be the
only options left, and neither option is ideal. Honey bees are already disappearing from
the Northern hemisphere and have not been found to be significant pollinators of wild
59
plant populations in most regions (Ollerton et al. 2012). In fact, some studies have shown
that honey bees decrease biodiversity in ecosystems through competition with native
insects (Ollerton et al. 2012; Badano & Vergara 2011). Hand-pollination by humans can
be costly, time-consuming, and ineffective (Partap & Ya 2012).
If natural pollination can be enhanced, there may be less of a need for
supplemental seed and replanting. When pollinators are lost or limited, some plant
species cannot maintain their populations (Mayer et al. 2011). When plant species in the
Puget lowland prairies do not sustain themselves, the CNLM bolsters the populations by
growing plants and seed in nurseries and then replants them into the prairies (Cheryl
Fimbel, CNLM, pers. comm. 2010). No evidence for pollinator limitation was found for
B. deltoidea or L. albicaulis in this thesis, but pollinator limitation may be one reason
why other plant species struggle to maintain their populations. So, enhancing pollination
may be a solution for some land managers who wish to save time and money by
decreasing their reliance on native plant nurseries.
Native bees can substantially contribute to crop pollination (Stubbs & Drummond
2001; Greenleaf & Kremen 2006; U.S. Natural Resources Conservation Service 2008) of
farms and private gardens in the surrounding area. By using sustainable agriculture
practices that strategically use or eliminate pesticide use and promote plant diversity
around crop fields, farmers can benefit from this free ecosystem service (Nicholls &
Altieri 2012).
Pollination research and conservation may take time and resources, but the
benefits clearly outweigh the potential costs of doing nothing. Understanding Puget
60
lowland prairie pollinator systems enables land managers to be alert to changes and
declines in pollinator populations that provide this economically beneficial service.
CONCLUSION
If stakeholders decide that action must be taken to protect pollinators, then both the
ecology and the social aspects must be considered as an integrated system. An
interdisciplinary viewpoint is essential for addressing environmental problems of this
nature. Ideologies of many people have shaped this landscape. Land-managers may
someday unmask an imbalance in the Puget lowland prairie pollination web using
scientific research, but because more power exists in the voices of the human
stakeholders, policy may need to be created to serve justice to and balance out the voices
of the varied human players with the collective need to preserve biodiversity.
Compromises will need to be made when finding a solution for protecting
pollinators. Managers of the preserves can work with agencies and local landowners to
encourage pollination conservation. Much of the Puget lowland prairie ecosystem lies on
private and agricultural land and though it may be costly in the short term to save patches
of native vegetation instead of converting them to crops, farmers could save money in the
long run by being active in conservation. Opportunity lies in creating public awareness of
the benefits of maintaining pollination systems to rally volunteers to help out with
restoration and monitoring. Pollinator protection in the Puget Lowland Prairies is a
potential issue where solutions can be found cooperatively by looking at the bigger
picture.
61
References
Abramson, G., C.A. Trejo Soto, and L. Ona. 2011. The role of asymmetric interactions
on the effect of habitat destruction in mutualistic networks. PLoS ONE. 6:e21028.
[online] URL: www.plosbiology.org (accessed Nov. 2012).
Anderson, S. H., D. Kelly, J.J. Ladley, S. Molloy, and J. Terry. 2011. Cascading effects
of bird functional extinction reduce pollination and plant density. Science.
331:1068-1071.
Arathi, H.S., A. Rasch, C. Cox, and J.K. Kelly. 2002. Autogamy and floral longevity in
Mimulus guttatus. International Journal of Plant Sciences. 163:567-573.
Arroyo, M. T. K., J. J. Armesto, and R. B. Primack. 1985. Community studies in
pollination ecology in the high temperate Andes of central Chile II. Effect of
temperature on visitation rates and pollination possibilities. Plant Systematics and
Evolution. 149:187-203.
Arroyo, M.T., R. Primack, and J. Armesto. 1982. Community studies in pollination
ecology in the high temperate Andies of central Chile I. Pollination mechanisms
and altitudinal variation. American Journal of Botany. 69:82-97.
Ashman, T., T. M. Knight, J. A. Steets, P. Amarasekare, M. Burd, D.R. Campbell, M. R.
Dudash, M.O. Johnston, S. J. Mazer, R. J. Mitchell, M.T. Morgan, and W. G.
Wilson. 2004. Pollen limitation of plant reproduction: ecological and evolutionary
causes and consequences. Ecology. 85:2408-2421.
62
Bandano, E. I., and C. H. Vergara. 2011. Potential negative effects of honeybees on the
diversity of native pollinators and yield of highland coffee plantations.
Agricultural and Forest Entomology. 13:355-372.
Berry, P. E. and R. N. Calvo. 1989. Wind pollination, self-incompatibility, and altitudinal
shifts in pollination systems in the high Andean genus Espeletia (Asteraceae).
American Journal of Botany. 76:1602-1614.
Bos, M. M., D. Veddeler, A. K. Bogdanski, A. Klein, T. Tscharntke, I. Steffan-Dewenter,
and J. M. Tylainakis. 2007. Caveats to quantifying ecosystem services: fruit
abortion blurs benefits from crop pollination. Ecological Applications. 17:18411849.
Boyd, A. E. 2004. Breeding system of Macromeria viridiflora (Boraginaceae) and
geographic variation in pollinator assemblages. American Journal of Botany.
91:1809-1813.
Buchmann, S. L., and G. P. Nabhan. 1996. The forgotten pollinators.
Washington D.C.: Island Press.
Capitol Land Trust. 2012. [online] URL:http://www.capitollandtrust.org/index.htm
(accessed Nov. 2012).
Cane, J. H. 2005. Pollination needs of arrowleaf balsamroot, Balsamorhiza sagittata
(Heliantheae: Asteraceae). Western North American Naturalist. 65:359-364.
Cane, J. H., and D. Schiffhauer. 2003. Dose-response relationships between pollination
and fruiting refine pollinator comparisons for cranberry (Vaccinium macrocarpon
[Ericaceae]). American Journal of Botany. 90:1425-1432.
63
Chappell, C. B., and R. C. Crawford. 1997. Native vegetation of the South Puget sound
prairie landscape. Ecology and conservation of the South Puget sound prairie
landscape. Ed. P. Dunn and K. Ewing. The Nature Conservancy. 107-124.
Chramiec, M. 2004. Field report for mardon skipper surveys in range and training land
assessment 2004 report. Department of Defense. Engineering and Environment,
Inc. Fort Lewis, WA.
Corbet, SA. 1998. Fruit and seed production in relation to pollination and resources in
Bluebell, Hyacinthoides non-scripta. Oecologia. 114:349-360.
Davis, J. D., S. D. Hendrix, D. M. Debinski, and C. J. Hemsley. 2008. Butterfly, bee and
forb community composition and cross-taxon incongruence in tallgrass prairie
fragments. Journal of Insect Conservation. 12:69-79.
Dieringer, G.1992. Pollinator limitation in populations of Agalinis strictifolia
(Scrophulariaceae). Bulletin of the Torrey Botanical Club 119:131-136.
Douglas, G. W., and M. Ryan. 2001. Status of the deltoid balsamroot, Balsamorhiza
deltoidea (Asteraceae) in Canada. The Canadian Field-Naturalist. 115:451-454.
Dunwiddie, P., E. Alverson, A. Stanley, R. Gilbert, S. Pearson, D. Hays, J. Arnett,
E. Delvin, D. Grosboll, and C. Marschner. 2006. The vascular plant flora of the
South Puget Sound prairies, Washington, USA. Davidsonia. 14:51-69.
Elliott, C. W., D. G. Fischer, and C. J. LeRoy. 2011. Germination of three native
Lupinus species in response to temperature. Northwest Science. 85:403-410.
Engel, E. C., and R. E. Irwin. 2003. Linking pollinator visitation rate and pollen receipt.
American Journal of Botany. 90:1612-1618.
64
Fang, Q., and S. Huang. 2012. Relative stability of core groups in pollination networks in
a biodiversity hotspot over four years. PLoS ONE. 7:e32663. [online] URL:
www.plosone.org (accessed Nov. 2012).
Fazzino, L., H. E. Kirkpatrick, and C. Fimbel. 2011. Comparison of hand-pollinated and
naturally-pollinated Puget balsamroot (Balsamorhiza deltoidea Nutt.) to
determine pollinator limitations on South Puget Sound lowland prairies.
Northwest Science. 85: 352-360.
Fimbel, C., and M. McKinley. June 2010.The Nature Conservancy. JBLM/Fort Lewis
Faunal (Pollinator) Survey Task Order: Final Report. TNC#147029-4921.
Fontaine, C., I. Dajoz, J. Meriguet, and M. Loreau. 2006. Functional diversity of plantpollinator interaction webs enhances the persistence of plant communities. PLoS
Biology 4:0129-0135. [online] URL: www.plosbiology.org (accessed June 2011).
Frankie, G.W., R. W. Thorp, J. Hernandez, M. Rizzardi, B. Ertter, J. C. Pawelek, S. L.
Witt, M. Schindler, R. Coville, and V. A. Wojcik. 2009. Native bees are a rich
natural resource in urban California gardens. University of California. California
Agriculture [online] URL: http://californiaagriculture.ucanr.edu (accessed Oct
2012).
Garcia-Meneses, P. M. and P. M. Ramsay. 2012. Pollinator response to within-patch
spatial context determines reproductive output of a giant rosette plant. Basic and
Applied Ecology. 13:516-523.
Goodell, K. 2003. Food availability affects Osmia pumila (Hymenoptera: Megachilidae)
foraging, reproduction, and brood parasitism. Oecologia 134:518-527.
65
Greenleaf, S. S., and C. Kremen. 2006. Wild bee species increase tomato production and
respond differently to surrounding land use in northern California. Biological
Conservation. 133:81-87.
Grindeland, J. M., N. Sletvold , and R. A. Ims. 2005. Effects of floral display size and
plant density on pollinator visitation rate in a natural population of Digitalis
purpurea. Functional Ecology. 19:383-390.
Hanson, T., Potter, A., and Vernon, S. 2010. Surveys for island marble butterfly
(Eucholoe ausonides insulanus) in San Juan County, Washington, 2009.
Washington Department of Fish and Wildlife. Olympia.
Hays, D. W., A. E. Potter, C. W. Thompson, and P. V. Dunn. 2000. Critical habitat
components for four rare South Puget Sound grassland butterflies. Report.
Washington Department of Fish and Wildlife, Olympia, WA.
Hegland, S. J., and O. Totland. 2008. Is the magnitude of pollen limitation in a plant
community affected by pollinator visitation and plant species specialization
levels? Oikos. 117:883-891.
Hines, H. M., and S. D. Hendrix. 2005. Bumble bee (Hymenoptera: Apidae) diversity
and abundance in tallgrass prairie patches: Effects of local and landscape floral
resources. Environmental Entomology. 34:1477-1484.
Inouye, D. W., and G. H. Pyke. 1988. Pollination in the snowy mountains of Australia:
Comparisons with montane Colorado, USA. Australian Journal of Ecology.
13:191-210.
International Seed Testing Association. 2012. International rules for seed testing. 2012
edition. Bassersdorf: Switzerland.
66
Jauker, F., B. Bondarenko, H. C. Beckert, and I. Steffan-Dewenter. 2012. Pollination
efficiency of wild bees and hoverflies provided to oilseed rape. Agricultural and
Forest Entomology. 14:81-87.
James, A., J. W. Pitchford, and M. J. Plank. 2012. Disentangling nestedness from models
of ecological complexity. Nature. 487:227-230.
Jordano, P., J. Bascompte, and J.M. Olesen. 2006. The ecological consequences of
complex topology and nested structure in pollination webs. Plant-pollinator
interactions: from specialization to generalization. Ed. N. M. Waser and J.
Ollerton. Chicago: University of Chigaco Press.
Kaiser-Bunbury, C. N., S. Muff, J. Memmott, C. B. Muller, and A. Caflisch. 2010. The
robustness of pollination networks to the loss of species and interactions: A
quantitative approach incorporating pollinator behaviour. Ecology Letters.
13:442-452.
Kearns, C. A. 1990. The role of fly pollination in montane habitats. Ph.D. dissertation.
University of Maryland. College Park, Maryland, USA.
Kearns, C. A., and D. W. Inouye. 1997. Pollinators, flowering plants, and conservation
biology. BioScience. 47:297-307.
Kearns, C. A., and D. W. Inouye. 1993. Techniques for pollination biologists. Niwot:
University Press of Colorado.
Keys, R. N., S. L. Buchmann, and S. E. Smith. 1995. Pollination effectiveness and
pollination efficiency of insects foraging Prosopis velutina in south-eastern
Arizona. Journal of Applied Ecology. 32:519-527.
67
Kremen C., N. M. Williams, M. A. Aizen, B. Gemmill-Herren, G. LeBuhn, R. Minckley,
L. Packer, S. G. Potts, T. Roulston, I. Steffan-Dewenter, D. P. Vazquez, R.
Winfree, L. Adams, E. E. Crone, S. S. Greenleaf, T. H. Keitt, A. Klein, J. Regetz,
and T.H. Ricketts. 2007. Pollination and other ecosystem services produced by
mobile organisms: A conceptual framework for effects of land-use change.
Ecology Letters. 10:299-314.
Kudo, G., A. S. Hirao, and Y. Kawai. 2011. Pollination efficiency of bumblebee queens
and workers in the alpine shrub Rhododendron aureum. International Journal of
Plant Science. 172:70-77.
Matteson, K.C., J. B. Grace, and E. S. Minor. 2012. Direct and indirect effects of land use
on floral resources and flower-visiting insects across an urban landscape. Oikos
doi: 10.1111/j.1600-0706.2012.20229.x [online] URL: onlinelibrary.wiley.com
(accessed Nov. 2012).
Mayer, C., L. Adler, S. Armbruster, A. Dafni, C. Eardley, S. Huang, P.G. Kevan, J.
Ollerton, L. Packer, A. Ssymank, J.C. Stout, and S.G. Potts. 2011. Pollination
ecology in the 21st century: Key questions for future research. Journal of
Pollination Ecology. 3:8-23.
McCall, C., and R. B. Primack. 1992. Influence of flower characteristics, weather, time of
day, and season on insect visitation rates in three plant communities. American
Journal of Botany. 79:434-442.
McCarty, J. P. 2001. Ecological consequences of recent climate change. Conservation
Biology.15:320-331.
68
Memmott, J., N. M. Waser, and M. V. Price. 2004. Tolerance of pollination networks to
species extinctions. Proceedings: Biological Sciences. 271:2605-2611.
Michener, C. D. 2006. The Bees of the World. Johns Hopkins University Press.
Morey, M. and Bakker, J. 2011. Effects of light and temperature regimes on germination
and viability of native WA prairie species. Undergraduate senior project. School
of Forest Resources, University of Washington, Seattle, WA.
National Audubon Society. 2012. [online] URL:http://www.audubon.org/ (accessed
Nov. 2012).
National Weather Service. 2012. Climate Prediction Center. National Oceanic and
Atmospheric Administration [online] URL: www.nws.noaa.gov (accessed Oct.
2012).
Nicholls, C. I., and M. A. Altieri. 2012. Plant biodiversity enhances bees and other insect
pollinators in agroecosystems. A review. Agronomy for Sustainable
Development. [online] URL: http://www.agronomy-journal.org/ (accessed Nov.
2012).
Nielsen, A., J. Dauber, W. E. Kunin, E. Lamborn, B. Jauker, M. Moora, S. G. Potts, T.
Reitan, S. Roberts, V. Sober, J. Settele, I. Steffan-Dewenter, J. C. Stout, T.
Tscheulin, M. Vaitis, D. Vivarelli, J. C. Biesmeijer, and T. Petanidou. 2012.
Pollinator community responses to the spatial population structure of wild plants:
A pan-European approach. Basic and Applied Ecology. 13:489-499.
69
Ollerton, J., V. Price, W. S. Armbruster, J. Memmott, S. Watts, N. M. Waser, O. Totland,
D. Goulson, R. Alarcon, J. C. Stout, and S. Tarrant. 2012. Overplaying the role of
honey bees as pollinators: A comment on Aebi and Neumann (2011). Trends in
Ecology and Evolution. 27:141-142.
Pauw, A. 2007. Collapse of a pollination web in small conservation areas.
Ecology. 88:1759-1769.
Partap, U. and T. Ya. 2012. The human pollinators of fruit crops in Maoxian county,
Sichuan, China. Mountain Research and Development. 32:176-186.
Perfectti, F., J. M. Gomez, and J. Bosch. 2009. The functional consequences of diversity
in plant-pollinator interactions. Oikos. 118:1430-1440.
Port of Olympia. 2012. Sensitive species habitat management. [online]
URL:http://www.portolympia.com/index.aspx?nid=137 (accessed Nov. 2012).
Potts, S. G., . Vulliamy, A. Dafni, G. Ne’eman, and P. Willmer. 2003. Linking bees
and flowers: How do floral communities structure pollinator communities?
Ecology. 84:2628-2642.
Price, M.V., D. R. Campbell, N. M. Waser, and A. K. Brody. 2008 Bridging the
generation gap in plants: Pollination, parental fecundity, and offspring
demography. Ecology 89:1596-1604.
Primack, R. B. 2010. Essentials of Conservation Biology. 5th ed. Sunderland, MA:
Sinauer Associates, Inc.
70
Rader, R., B. G. Howlett, S. A. Cunningham, D. A. Westcott, and W. Edwards. 2012.
Spatial and temporal variation in pollinator effectiveness: Do unmanaged insects
provide consistent pollination services to mass flowering crops? Journal of
Applied Ecology. 49:126-134.
Roberts, S. P. M., S. G. Potts, K. Biesmeijer, M. Kuhlmann, B. Kunin, and R.
Ohlemuller. 2011. Assessing continental-scale risks for generalist and specialist
pollinating bee species under climate change. BioRisk. 6:1-18.
Schultz, C. B., J. D. Dzurisin, and C. Russell. 2009. Captive rearing of Puget blue
butterflies (Icaricia icarioides blackmorei) and implications for conservation.
Journal of Insect Conservation. 13:309-315.
Schultz, C. B., E. Henry, A. Carleton, T. Hicks, R. Thomas, A. Potter, M. Collins, M.
Linders, C. Fimbel, S. Black, H. E. Anderson, G. Diehl, S. Hamman, R. Gilbert,
J. Foster, D. Hays, D. Wilderman, R. Davenport, E. Steel, N. Page, P.L. Lilley, J.
Heron, N. Kroeker, C. Webb, and B. Reader. 2011. Conservation of prairie-oak
butterflies in Oregon, Washington, and British Columbia. Northwest Science.
85: 361-388.
Sih, A., and M. Baltus. 1987. Patch size, pollinator behavior, and pollinator
limitation in catnip. Ecology. 68:1679-1690.
South Sound Prairies Working Group. 2012. South Sound Prairies. [online]
URL:http://www.southsoundprairies.org (accessed Feb. 2012).
Spears Jr., E. E. 1983. A direct measure of pollinator effectiveness. Oecologia.
57:196-199.
71
Stanley, A.G., T. N. Kaye, and P. W. Dunwiddie. 2008. Regional strategies for restoring
invaded prairies: Observations from a multisite, collaborative research project.
Native Plants Journal 9:247-254.
Stephenson, A.G. 1981. Flower and fruit abortion: Proximate causes and ultimate
functions. Annual Review of Ecology and Systematics. 12:253-279.
Stinson, D.W. 2005. Washington State Department of Fish and Wildlife. Washington
State status report for the Mazama pocket gopher, streaked horned lark, and
Taylor’s checker spot. Olympia, WA.
Stubbs, C. S. and F. A. Drummond. 2001. Bombus impatiens (Hymenoptera: Apidae):
An alternative to Apis mellifera (Hymenoptera: Apidae) for lowbush blueberry
pollination. Journal of Economic Entomology. 94:609-616.
Tepedino, V. J., W. R. Bowlin, and T. L. Griswold. 2011. Diversity and pollination value
of insects visiting the flowers of a rare buckwheat (Eriogonum Pelinophilum:
Polygonaceae) in disturbed and “natural” areas. Journal of Pollination Ecology.
4:57-67.
The Evergreen State College and Washington State Department of Corrections. 2012.
Sustainability in Prisons Project. [online]
URL:http://blogs.evergreen.edu/sustainableprisons/what-we-do/science/ (accessed
Nov. 2012).
Thurston County Parks and Recreation. 2012. Black River – Mima prairie Glacial
heritage preserve. [online] URL:http://www.co.thurston.wa.us/parks/parksglacial-heritage.htm (accessed Nov. 2012).
72
Tscheulin, T., and T. Petanidou. 2011. Does spatial population structure affect seed set in
pollen-limited Thymus capitatus? Apidologie. 42:67-77.
USAEC. 2012. Army Compatible Use Buffers. [online]
URL:http://aec.army.mil/usaec/acub/docs_acub/ (accessed Nov. 2012).
U.S. Environmental Protection Agency. 2012. Our Mission and What We Do. [online]
URL:http://www.epa.gov/aboutepa/whatwedo.html (accessed Nov. 2012).
U.S. NRCS. 2012.Natural Resources Conservation Service. [online]
URL:http://www.nrcs.usda.gov/wps/portal/nrcs/main/national/about/ (accessed
Nov. 2012).
U.S. Natural Resources Conservation Service. August 2008. Using farm bill programs for
pollinator conservation. Report no.78.
U.S. Natural Resources Conservation Service. 2012. Plants Database. [online]
URL:www.plants.usda.gov (accessed Oct. 2012).
U.S. Department of Fish and WildlifeService. 2012. Endangered Species Program.
[online] URL:http://www.fws.gov/endangered/about/index.html (accessed Nov.
2012).
Vazquez, D. P., W. F. Morris, and P. Jordano. 2005. Interaction frequency as a surrogate
for the total effect of animal mutualists on plants. Ecology Letters.
8:1088-1094.
Vila, M., and J. Weiner. 2004. Are invasive plant species better competitors than native
plant species? – Evidence from pair-wise experiments. Oikos 105:229-238.
73
Washington Natural Heritage Program. 2012. Washington Department of Natural
Resources. [online] URL:http://www1.dnr.wa.gov/nhp/refdesk/lists/plantrnk.html
(accessed Aug. 2012).
Washington State Department of Fish and Wildlife. 2012. WDFW Lands. [online]
URL:http://wdfw.wa.gov/lands/wildlife_areas/index.html (accessed Nov. 2012).
Washington State Department of Natural Resources. 2012. Washington Natural Areas
Program. [online]
URL:http://www.dnr.wa.gov/ResearchScience/Topics/NaturalAreas/Pages/am
p_na.aspx (accessed Nov. 2012).
Washington State Department of Transportation. 2012. USFWS Threatened and
endangered species and habitat. [online]
URL:http://www.wsdot.wa.gov/Environment/Biology/bio_usfw.htm (accessed
Nov. 2012).
Wentworth, J. B. 1997. Castilleja levisecta, a threatened South Puget Sound prairie
species. Ecology and conservation of the South Puget Sound prairie landscape.
Ed. P. Dunn and K. Ewing. The Nature Conservancy. 101-105.
Wilson, M.V., P. C. Hammond, and C. B. Schultz. 1997. The interdependence of native
plants and Fender’s blue butterfly. In: Kaye, T.N., A. Liston, R. M. Love, D.
Luomo, R. J. Meinke, and M. V. Wilson (eds). Conservation management of
native flora and fungi. Native Plant Society of Oregon, Corvallis, pp 83-87.
Wirth, L. R., N. M. Waser, R. Graf, F. Gugerli, U. Landergott, A. Erhardt, H. P. Linder,
and R. Holderegger. 2011. Effects of floral neighborhood on seed set and degree
of outbreeding in a high-alpine cushion plant. Oecologia. 167:427-434.
74
Wojik, V. A., and S. Buchmann. 2012. Pollinator conservation and management on
electrical transmission and roadside rights-of-way: A review. Journal of
Pollination Ecology. 7:16-26.
Wolf Haven International. 2012. Wolf Haven’s prairie. [online]
URL:http://www.wolfhaven.org/prairie_overview.php (accessed Nov. 2012).
75