TEMPORAL BEE DIVERSITY AND ABUNDANCE WITHIN THE
CALIFORNIA SAGE SCRUB OF THE SAN JOSE HILLS AND CHINO HILLS
A Thesis
Presented to the
Faculty of
California State Polytechnic University, Pomona
In Partial Fulfillment
Of the Requirements for the Degree
Master of Science
In
Biological Sciences
By
Carmel P. Tabush
2019
SIGNATURE PAGE
THESIS: TEMPORAL BEE DIVERSITY AND ABUNDANCE WITHIN THE CALIFORNIA SAGE SCRUB OF THE SAN JOSE HILLS AND CHINO HILLS
AUTHOR: Carmel P. Tabush
DATE SUBMITTED: Fall 2019
Department of Biological Sciences
Dr. Joan M. Leong Thesis Committee Chair Biological Sciences
Dr. Erin Questad Biological Sciences
Dr. Aaron Fox Plant Sciences
ii
ACKNOWLEDGMENTS
There are so many people that I am grateful for. I owe thanks to my advisor, Dr.
Joan Leong, for her patience and guidance these past few years and for the many hours she spent reviewing my work; to Dr. Erin Questad, Dr. Aaron Fox, Dr. Jeremy Claisse and Jake Cecala for their help on my thesis and data analyses; to Dr. Doug Yanega for my bee taxonomic identifications; and to my helpers and friends, including Carina
Glaccum, Stephanie Martinez, Ben Soto, Seth Kapp, Andy Tung, Drew Pearson, Ben
Holdridge, Keith Smith, Corina Jimenez, Doel Lee, Jon Sacro, Jesus Cepeda, Manuela
Edwards and John Glaccum III, for all their help out in the field and in the lab to collect and identify the 3,436 bees. This thesis surely would not have been possible without all of your contributions!
The success of this thesis is also due to the generous funding I received through scholarships and grants from the Cal Poly Pomona Biological Sciences Department, the
BioTiER (Biological Training in Education and Research) Scholars Program, the Sea and
Sage Audubon Society, and the MENTORES (Mentoring, Educating, Networking, and
Thematic Opportunities for Research in Engineering and Science) scholars program.
Lastly, I gratefully acknowledge David Moronez of Frank G. Bonelli Park, Nikole
Bresciani of Galster Park, and Ken Kietzer and Alissa Ing of Chino Hills State Park in providing me with sites at which to conduct this research.
Finally, I thank my parents (Gary and Sherri Pearson) for assisting and supporting me during this project by babysitting Orion day and night, helping me make my project materials, and assisting me out in the field on numerous occasions; my husband (Mike
Tabush) for his encouragement and humor during this venture and his assistance in the
iii field; and my son (Orion) for lovingly sharing his mommy’s time with her thesis work.
Each of you generously gave everything you had to ensure my success on this journey, and because of that, I dedicate this thesis to you four. I love you, guys!
iv
ABSTRACT
California sage scrub (CSS), an endangered ecosystem consisting of deciduous shrubs like California sagebrush (Artemisia californica), black sage (Salvia mellifera), white sage (Salvia apiana), and California buckwheat (Eriogonum fasciculatum), occupies coastal, as well as inland regions in Southern California. Unlike coastal CSS regions, little is known about the seasonal diversity and abundance of native bee pollinators of inland CSS habitats. The purpose of this study was to determine how bee diversity and abundance differ seasonally in two inland CSS hill regions, San Jose Hills
(SJH) and Chino Hills (CH). I hypothesized that the greatest bee diversity and abundance occurs in spring, and that CH will have greater bee diversity and abundance due to its larger natural area. I sampled bees using pan traps at six different CSS localities, three per hill region. A total of 3,436 bees, representing at least 80 species/morphospecies, were collected from June 2017 to June 2018. The most abundant species, present in all sampling periods, were Lasioglossum (Dialictus) spp., Ceratina arizonensis, and Halictus tripartitus. Bee abundance varied significantly across sampling periods and sites within hills, but not between hill regions. Bee diversity (i.e. genus and species richness, genus and species community composition) varied between hills, sites within hills, and sampling periods. Most of the variation in bee community composition was due to temporal effects. My results partially support my prediction, as CH harbored a higher bee richness than SJH, and late spring/early summer had a higher bee richness and diversity; however, contrary to my expectations, summer yielded a greater abundance of bees. In addition, geographical variation in bee richness was observed within CH sites.
Documentation of strong temporal patterns of native bee assemblages is important basic
v knowledge that can inform conservation efforts for inland CSS ecosystems in Southern
California.
vi
TABLE OF CONTENTS
SIGNATURE PAGE ...... ii
ACKNOWLEDGMENTS ...... iii
ABSTRACT...... v
LIST OF TABLES ...... ix
LIST OF FIGURES ...... x
INTRODUCTION ...... 1
METHODS ...... 5
Study sites...... 5
Pan trap sampling...... 7
Experimental design: temporal bee diversity and abundance...... 7
Experimental design: flora diversity and abundance ...... 9
Statistical analysis: temporal bee diversity and abundance...... 10
Statistical analysis: flora diversity and abundance ...... 12
RESULTS ...... 13
Bee taxa collected ...... 13
Temporal Variation in Bee Assemblages...... 13
Geographical Variation in Bee Assemblages ...... 17
Plant Species Assemblage and Floral...... 20
DISCUSSION...... 50
vii
Green River Post-Fire Observations ...... 61
Limitations and criticisms of experimental design ...... 63
Contribution to future CSS conservation efforts...... 64
CONCLUSION...... 66
REFERENCES ...... 68
APPENDIX A ...... 73
APPENDIX B ...... 74
APPENDIX C ...... 76
APPENDIX D ...... 77
APPENDIX E ...... 78
APPENDIX F...... 79
APPENDIX G ...... 80
APPENDIX H ...... 81
APPENDIX I ...... 82
APPENDIX J ...... 83
viii
LIST OF TABLES
Table 1. Details of each sampling site with dates sampled...... 41
Table 2. Three-Factor nested ANOVA for bee abundance ...... 41
Table 3. Average number of bees per trap for hill region and sampling period ...... 42
Table 4. Three-Factor nested ANOVA for bee genus richness...... 42
Table 5. Average number of bee genera per trap for hill region and sampling period . 42
Table 6. Three-factor nested ANOVA for bee species richness ...... 43
Table 7. Three-factor nested ANOVA for bee species diversity ...... 43
Table 8. Three-factor nested ANOVA for bee species evenness ...... 43
Table 9. Three-Factor PERMANOVA for bee species community composition ...... 44
Table 10. Three-Factor PERMANOVA for bee genus community composition ...... 44
Table 11. Tukey HSD pairwise comparisons of species community composition
between sampling periods...... 45
Table 12. Tukey’s HSD pairwise comparisons for genus community composition
between all sampling periods...... 46
Table 13. Sorenson’s similarity of species community composition between hills per
sampling period...... 47
Table 14. Tukey’s HSD pairwise comparisons for genus community composition
between sites within hills...... 47
Table 15. Total number of species collected for each site...... 48
Table 16. Tukey HSD pairwise comparisons of species community composition
between sites within hills...... 48
Table 17. Sorenson’s similarity of species community composition between sites...... 49
ix
LIST OF FIGURES
Figure 1. Map of the 6 sites used in the study...... 22
Figure 2. Diagram of the site perimeter and transect layout...... 23
Figure 3. Average bee abundance per trap per sampling period...... 24
Figure 4. Average bee genus richness per trap per sampling period...... 25
Figure 5. Average bee species richness per trap per sampling period ...... 26
Figure 6. Evenness and Diversity Indices per sampling period across sites...... 27
Figure 7. Ordination (nMDS) plot for bee species community composition ...... 28
Figure 8. Bee genus abundance by percentage per site for Jun-17 and Jun-18...... 29
Figure 9. Bee abundance by genus per hill region and sampling period...... 30
Figure 10. Average bee abundance per trap per site and sampling period...... 31
Figure 11. Average bee abundance per trap for sites...... 32
Figure 12. Average bee genus richness per trap for sites...... 33
Figure 13. Average bee species richness per trap for sites...... 34
Figure 14. Bonelli Park plant species percent cover by date...... 35
Figure 15. Galster Park plant species percent cover by date...... 36
Figure 16. Voorhis Reserve plant species percent cover by date...... 37
Figure 17. Campsite plant species percent cover by date...... 38
Figure 18. Green River plant species percent cover by date...... 39
Figure 19. Quarter Horse plant species percent cover by date...... 40
x
INTRODUCTION
Although honey bees (Apis mellifera) are the most well-known for crop pollination, native bees also contribute greatly to pollination (Ballmer, 1995). The act of pollination by honey bees and native bees, which leads to fruit and seed production, is considered an ecosystem service (Hanley et al., 2015). In 2010, the pollination services provided by bees was estimated to be worth around $20 billion annually in the United
States alone (Johnson, 2010). Unfortunately, the recent declines in honey bee and native bee populations worldwide could mean a decrease in the pollinator ecosystem services
(Fortel et al., 2014; Cameron et al., 2011; Klein et al., 2006). The recent decline in bee populations have initiated studies and conservation efforts to preserve bee populations and pollinator ecosystem services (Leong et al., 2015; Fortel et al., 2014; Kimoto et al.,
2012).
To better understand the dynamics of bee pollinators, many studies have documented strong patterns of temporal variation in native bee assemblages. In
California, as seasons change, native bee diversity and abundance fluctuates throughout the year (Wojcik et al., 2008). When sampling bees each season, Wojcik et al. (2008) and
Leong et al. (2015) found that bee activity, diversity and abundance, was highest in the spring and/or summer. The patterns and fluctuations of each bee species, however, were not completely identical between these two studies in CA (Wojcik et al., 2008; Leong et al, 2015). In the spring and summer of 2004, Wojcik et al. (2008) found that Megachile perihirta, Halictus tripartitus, Melissodes robustior and Megachile rotundata were extremely common. For both spring and summer of 2011, however, Leong et al. (2015) found that Lasioglossum species, Halictus tripartitus, Eucera actuosa, Osmia nemoris,
1
Agapostemon texanus, Melissodes lupina, Apis mellifera, Ceratina nanula, and
Melissodes stearnsi were very common. Although both studies were conducted in an urban setting in the San Francisco Bay area, Leong et al. (2015) sampled a different assemblage of bee species.
While bee diversity and abundance may differ and fluctuate with season, bee fauna may also differ drastically amongst regions or land types (Leong et al, 2015).
Leong et al (2015) found that bee species from natural areas peaked in abundance during the spring, those from urban areas peaked during the late spring/early summer, and those from agricultural areas peaked later in the summer. It was also found that natural areas displayed a greater abundance and richness of bee species than urban and agricultural areas. Studies have shown that natural habitats help support many of the bee species that pollinate agricultural crops (Klein et al., 2006; Leong et al, unpublished). Natural areas near agricultural landscapes provide resources for bees that are responsible for crop pollination. Leong et al. (unpublished) sampled bees in agricultural landscapes and in natural surrounding areas and found that the bee species that were collected in agricultural settings were also collected in natural landscapes. Results suggest that many of the same bee species that pollinate our crops are also pollinating native plants in natural habitats.
Many natural habitats are becoming increasingly fragmented into smaller-sized habitats due to agricultural and suburban development. A natural ecosystem in California that has become fragmented is the California sage scrub (CSS). CSS consists of deciduous shrubs, which include the California sagebrush (Artemisia californica), Salvia mellifera (Salvia mellifera), white sage (Salvia apiana), and California buckwheat
2
(Eriogonum fasciculatum). CSS is considered to be endangered due to an 85% decline in size over the past century (Rubinoff, 2001). Although CSS is shrinking, it is still home to many native organisms that include endangered species, such as the California gnatcatcher and the cactus wren, and other endemic species, like the El Segundo blue butterfly and the Palos Verdes blue butterfly.
CSS habitat fragments can vary in diversity and abundance of plant species (Soule et al. 1992; Raghubanshi and Tripathi, 2009). Soule et al. (1992) studied scrub fragments and found that the plant species assemblages in natural habitats changed over time. For example, many CSS habitats are being invaded by non-native grasses, which can cause a change in the plant species assemblage (Staubus et al, 2015). In addition to changes in plant species assemblages, fragments may differ in their faunal assemblages, such as arthropod communities. Staubus et al. (2015) found that CSS fragments in southern
California differed in their ant assemblages. While some studies (Suarez et al, 1998;
Wolkovich et al, 2009) suggest that non-native vegetation decreases CSS species diversity, Staubus et al. (2015) determined that some inland fragments of CSS harbor a greater diversity of ant species when containing some proportion of non-native grasses.
This suggests that a mosaic of native shrubs and non-native plant assemblages may play a factor in arthropod richness by providing resources from two habitat types. In studying the effect of CSS fragments on bee assemblages, Hung et al (2015) suggest that habitat/fragment size could influence bee diversity. When sampling bee pollinators from a large coastal reserve of CSS and from coastal fragments of CSS near San Diego during the spring season, the fragments of CSS experienced a 14% decrease in bee species richness when compared to the larger reserves.
3
Despite increasing interest in CSS arthropods, not much is currently known about the seasonal or temporal fluctuations and patterns in bee diversity and abundance in CSS regions in southern California. There have been no studies that systematically document or inventory bees within inland CSS regions. In this study, I compile an inventory of inland CSS native bees across multiple seasons by systematically collecting and identifying bees from two inland CSS regions. I examine temporal and geographical variation between two inland CSS fragments; and I examine which variables (i.e. hill region, sites within hills, sampling period (also known as time of year)) are most responsible for the temporal patterns in bee assemblages. Finally, I determine how the temporal patterns in plant species assemblages and floral resources vary between sites of two inland CSS hill regions. I predict that there will be significant geographic and temporal differences in bee diversity and abundance between two inland CSS hill regions, with a greater diversity and abundance of bees occurring in the spring, and in the
CSS hill region with the largest natural area. In addition, I predict that there will be similar plant species assemblages in each site throughout the year, with more flowering species in the spring and summer than in the fall, due to flowering phenology.
4
METHODS
Study sites
Six California sage scrub (CSS) habitat sites in Los Angeles, San Bernardino, and
Orange Counties of California were studied from June 2017 to June 2018 (Figure 1,
Table 1). Three of the sites (Voorhis Ecological Reserve (VER), Frank G. Bonelli Park
(BP) and Galster Park (GP)) were located in the San Jose Hills (SJH) and three (referred to as “Quarter Horse”, “Green River” and “Campsite”) were located in Chino Hills State
Park in the Chino Hills (CH) mountain range. SJH covers approximately 34 square kilometers of land with VER, BP and GP accounting for 0.31, 7.28, and 0.17 square kilometers, respectively. VER is located within the southeastern portion, BP in the northeastern portion and GP in the southwestern portion of the hills. Situated roughly 2 kilometers southeast from SJH, CH is estimated to be almost 7 times larger than SJH with approximately 221 square kilometers. Chino Hills State Park constitutes roughly 26% of
CH (57.4 square kilometers) and occupies the south-southeastern portion of the hills.
Each sampling site area measured 1200 square meters in size (30 meters x 40 meters) and varied in the proportion of native CSS shrubs and flora (e.g. Artemisia californica,
Eriogonum fasciculatum, Salvia mellifera) (Figure 2). The distance between any two
CSS sites were estimated to range from 3.72 to 27.5 kilometers (mean= 15.8 kilometers) with the shortest distance between a SJH site and CH site being 17.1 kilometers. The sites were chosen to be geographically distant from one another as to minimize the chances of overlap of bee flight ranges (Greenleaf et al. 2007). Although the sites were situated within a natural habitat, the distances from each site to the nearest impervious surface or building structure ranged from 13 to 260 meters and 48 to 820 meters, respectively.
5
Google Earth Pro 7.3.2.5491 was used to achieve all estimations, as well as site coordinates and elevation. On 25 September 2017, a wildfire, deemed the West Corona fire, burned through the Green River site, in Chino Hills, destroying all vegetation and leaving nothing but ash and charred plant remains. In spite of this natural disaster, the study continued on as planned and future sampling dates were unaffected.
Data were collected from each of the six SJH and CH sites seven times between
13 June in 2017 and 24 June in 2018. I sampled each site for 24 hours, every 6 to 8 weeks, for a total of 168 hours, or 7 sampling days, at each of the six sites (Leong et al,
2015; Gezon et al., 2015). Such frequent sampling methods over a long period have not been found to negatively impact bee populations (Gezon et al., 2015). All three SJH sites were sampled on the same days with no more than a 4-hour difference in starting time between the first and last site. The three CH sites were studied either on the same days, or on consecutive days, and occurred no more than 14 days following the SJH sites. The time frame in which all 6 sites were sampled within 14 days of each other is referred to as a sampling period, with a total of 7 sampling periods in this study. Sampling periods were categorized by month and year as follows: Jun-17, Jul/Aug-17, Sep-17, Nov-17, Mar-18,
Apr/May-18, Jun-18. I conducted field sampling on days that were sunny or partly sunny, as most bee species require exposure to solar radiation, as well as a certain light level and ambient temperature, to initiate flight activity (Heard and Hendrikz 1993, Burrill and
Dietz 1981, Stone et al. 1995). On sampling days, the ambient temperature ranged from
11.7 to 36.1°C (mean = 21.3°C) for the SJH sites and 6.1 to 37.7°C (mean = 19.9°C) for the CH sites. In addition to ambient temperature, humidity was recorded with a range
6 from 25 to 82% (mean = 61.5%) for the SJH sites, and 13 to 88% (mean = 53.1%) for the
CH sites.
Pan trap sampling
To allow minimal disturbance to habitats like the CSS, bees and other insects can be collected passively by using pan traps (Campbell and Hanula, 2007). Although some bee species are poorly sampled using the pan trap method, pan traps were found to efficiently trap a greater diversity and abundance of anthophiles when compared to other trapping methods (Campbell and Hanula, 2007; Bates et al. 2011; Vrdoljak and
Samways, 2012). Pan traps consist of colored plastic bowls filled with water and an environmentally safe, biodegradable detergent to reduce surface tension of the water.
Although each pan trap color may differ in the types of bees trapped, via color preferences of individual bee taxa, blue bowls have been found to trap a greater diversity and abundance of bee species in the CSS (Vrdoljak and Samways, 2012; Pearson, unpublished).
Experimental design: temporal bee diversity and abundance
On each sampling day, between 8:00 AM and 5:30 PM, I placed a total of 16 blue pan traps in each sampling site in the open sunlight amongst the CSS flora, with a minimum of 5 meters between each trap. Each trap was situated by hammering a 45 cm tall wooden post, with a 10 cm² wooden base top, into the ground until the top of the post was approximately 30 cm above the ground. After ensuring the post was sturdy and level,
I secured a pan trap bowl to the top of each post via a ~12 cm strip of inverted duct tape.
The pan trap bowls were of a royal blue color and measured 3.5 cm deep and 15 cm wide in diameter. Once all of the 16 bowls were securely attached to their posts, I added a
7 mixture of ~150 mL of tap water and ~2 mL of Seventh Generation - Natural Dish Liquid
(Hypoallergenic, Free and Clear) to each bowl. Traps were placed in approximately the same locations within a site, on each sampling date, as determined by GPS and mapping.
The traps were allowed to remain active 24 hours from the time the first bowl was filled with the soapy water.
Upon the completion of sampling, I placed each trap’s contents into its own
Ziploc bag along with a paper label of the appropriate trap ID, date and locality. Any bees observed within the site for 30 minutes to 1 hour, depending on presence or absence of bee activity following trap removal, were caught by aerial net. Any plant that the bees were associated with at the time of netting was also recorded. Aerial netting allowed for the collection of any bee species that may have been missed by the pan traps.
Insects in field samples were analyzed under a dissecting scope for positive identification of bee specimens. Non-bee specimens were not identified or counted. I placed all Apidae specimens, per trap or netting, into a mason jar and secured it with a modified screen lid. A hair dryer was used to dry the specimens within the mason jar in a short amount of time: 30 seconds to 2 minutes, depending on specimen size. The vorticular motion of the bee specimens in the jar, combined with warm air, enabled individual cuticular hairs on the specimens to dry, which facilitated taxonomic identification. Once dry, I pinned each bee specimen and appropriately labeled it with the site locality, date and trap number. In addition, I identified each specimen to species or morphospecies by using taxonomic keys from a text (Michener et al., 1994) or website
(discoverlife.org). Professional taxonomic identification services, provided by Dr. Doug
Yanega from University California Riverside, California, enabled identification of more
8 difficult species or morphospecies. Most species in genus Lasioglossum could not be discerned from one another and were only identified to subgenus level (Lasioglossum
(Dialictus), L. (Evylaeus), and L. (Lasioglossum). Species level identifications were primarily based on females, except in the case of Anthophorula, Chelostoma, Hoplitis, and Stelis, where male bees were used.
Experimental design: flora diversity and abundance
To determine the plant species abundances in each sampling site, I utilized transect sampling. Previous studies have used sampling transects to successfully examine the increase in plant species diversity of a habitat (Carson et al. 2016, Martin et al. 2015)
For this study, the percentage of area in each site covered by each plant species that was greater than 0.3 meters high was determined via transects with pole intercepts (Martin et al. 2015). Following netting of bees on each sampling day, three, 30-meter-long parallel transects were set up, 10 meters from one another in the site, with the outer transects being 10 meters from the edge of the sampling site. I recorded data for plant species every 1 meter along each transect by using a 1.6-meter-long wooden pole (2.5 cm diameter). Any plant species that measured greater than 0.3 meters in height that touched the pole at each 1-meter mark along the transect was recorded once, for a maximum total of 30 per transect, or 90 per site, for each plant species. The identification of plants to genus, and species when possible, was assisted by the use of an identification key
(Schwartzman, 2011) and colleagues.
In addition to transects, I determined the flowering plant species at each site for each sampling period. Any flowering species observed within 1 meter from either side of each transect was identified by the use of identification keys or assistance from
9 colleagues, and then recorded for species abundance (Kimoto et al. 2012). The number of open, active inflorescences on each flowering individual were counted, or estimated when necessary, and recorded. Typically, inflorescences exceeding 40 per individual were estimated to expedite the process.
Statistical analysis: temporal bee diversity and abundance
By pooling all of the trapped bees across the 16 traps, I was able to calculate the mean number of bee individuals per trap for each site and sampling period. An analysis of variance model (three-factor nested ANOVA (factors: hills, sites nested in hills, sampling periods), with 95% confidence) was used to determine the significance in difference of the bee abundances per trap between the hills, sites within hills and sampling periods. With Tukey’s HSD post-hoc, I determined which sites and sampling periods differed in bee abundance.
Like bee abundance, I analyzed genus richness by calculating the mean number of bee genera per trap for each hill, site and sampling period. Furthermore, I conducted a three-factor nested ANOVA (factors: hills, sites within hills, and sampling periods) and
Tukey’s HSD post-hoc to determine if and where significant differences occurred between sites within hills and sampling periods. A three-factor nested ANOVA and
Tukey’s HSD were also used to compare bee genus community composition between hills, sites within hills and sampling periods.
For bee species analyses, I excluded males from the analyses because they could not be definitively matched to their female counterparts, with the exception of males in 4 genera (Anthophorula, Chelostoma, Hoplitis, and Stelis) lacking female specimens. After calculating the mean species richness per trap for sites and sampling periods, I assessed
10 bee species richness via the use of a three-factor nested ANOVA. Tukey’s HSD post-hoc was then used to determine which sites and sampling periods differed in species richness.
In addition, I used Shannon’s diversity index (H) and Pielou’s evenness index (J’) to analyze differences in bee species diversity and evenness between the sites and sampling periods. ANOVAs (three-factor nested) and a Tukey’s HSD post-hoc were further used to determine which sites and/or sampling periods differed in their species diversity and evenness. To compare bee species composition between the sites and sampling periods, I conducted a three-factor nested permutational multivariate analysis of variance
(PERMANOVA, with 999 permutations, factors: hills, sites nested in hills, sampling periods) (Leong et al, 2015; Hung et al, 2015) and Tukey’s HSD post-hoc pairwise comparisons. Each site was compared throughout the year to determine if there was any significant difference in bee assemblages or patterns based on region or sampling period.
To explore the similarities of bee community composition between the sites by sampling periods via pair-wise comparisons, I used Sorenson’s Similarity Coefficient (Ss).
Furthermore, a non-metric multidimensional scaling plot (nMDS), with minimum convex polygons and centroids arranged by sampling period and hill, provided a visual representation of the differences in bee species composition between hills, sites within hills and sampling periods. I conducted all data analyses, except the bee genera pie charts, in RStudio V.3.5.2 using the VEGAN, DPLYR, and TIDYVERSE packages
(Hung et al, 2015; Oksanen et al, 2013). Bee abundance was fourth-root transformed to normalize the data distribution before any analyses in RStudio.
Netted bees were not included in the species analyses, and were only used for observational purposes. All bee species that were netted were also collected in pan traps,
11 except one male Osmia (Appendix A). The predominate bee netted was Apis mellifera
(82.4% of total).
Statistical analysis: flora diversity and abundance
The percent coverage for each plant species (greater than 0.3 meters in height) at each site per date was determined by calculating the average of each recorded plant species occurrence between the three transects, or 90 total meters. The mean for each flowering species per transect was also calculated by dividing the total number of observances per flowering species in the site per date by the number of transects.
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RESULTS
Bee taxa collected
A total of 3,436 bees (males and females) were collected during this study, with 2,237 in 2017 and 1,199 in 2018. Each pan trap collected between 0 and 92 bees
(mean±SEM = 5.11±0.27). At least 80 species and morphospecies, belonging to 32 genera (including Apis), were collected (morphospecies will hereafter be referred to as
“species” for simplicity) (Appendix B). Regardless of sex, the four most abundant native bee genera were Lasioglossum, Ceratina, Halictus, and Melissodes, making up 75.9% of the entire bee collection. Lasioglossum alone accounted for 29.1% of all the bees collected, with Ceratina accounting for 26.7%. The majority of Lasioglossum bees were of the subgenus Dialictus (88.5%). Of the bees collected, only 4.22% (145) were found to be non-native honey bees (Apis mellifera). The most numerically dominant bee species
(>100 individuals), in order of abundance, were Lasioglossum (Dialictus) species,
Ceratina arizonensis, Halictus tripartitus. Apis mellifera, Agapostemon texanus,
Melissodes sp. 5, and Lasioglossum (Evylaeus) species. Each of the other 73 species consisted of less than 50 individuals. Nearly one third of the bee species were represented by singletons (32.5%) and 7.5% were doubletons, with more singletons and doubletons collected at Campsite than any other site.
Temporal Variation in Bee Assemblages
Depending upon the sampling period, CSS bees were quite different in abundance, and measures of richness, diversity, evenness and community composition.
Bee abundances varied significantly between sampling periods (Nested ANOVA: F6,654 =
33.59, P << 0.0001) (Table 2). In addition, sampling periods were found to have a
13 significant interaction with hill regions (Nested ANOVA: F6,654 = 18.87, P << 0.0001)
(Table 2). In 2018, a strong increase in early spring (Mar-18) bee abundance was followed by a drop in mid-spring and late spring/early summer (Apr/May-18 and Jun-18)
(Figure 3). Whereas in 2017, bee abundance tended to be greater in mid-summer samples
(Jul/Aug-17), and gradually declined until mid-fall (Nov-17) (Figure 3). Temporal differences were due to significantly greater bee abundance during Jun-17 and Jul/Aug-
17 (Figure 3). Jun-17 had 2 to 7.2 times more bees per trap than Sep-17, Nov-17,
Apr/May-18, and Jun-18. In the hill x sampling period interaction, I found that the temporal pattern in bee abundance was different between the two hill regions (Table 2,
3). SJH, for example, had a lower bee abundance in Nov-17 and a greater bee abundance in Jul/Aug-17, while CH had a lower bee abundance in Apr/May-18 and greater bee abundance in Jun-17 (Table 3).
Bee genus richness varied significantly between most sampling periods, however, there was no significant difference between Jul/Aug-17 and Mar-18, Sep-17 and Jun-18, and Nov-17 and Apr/May-18 (F6,654 = 55.48, P << 0.0001) (Figure 4; Table 4). The number of bee genera per trap tended to be highest in late spring/early summer (Jun-17) and lowest in mid-fall (Nov-17) (Figure 4). Similar to the temporal pattern of bee abundances in 2017, the number of bee genera per trap declined each sampling period from Jun-17 to Nov-17 (mid-fall); this was followed by a spike in early spring (Mar-18)
(Figure 4). Each hill region had a different temporal pattern in bee genus richness given the significant hill x sampling period interaction (F6,654 = 10.22, P << 0.0001) (Tables 4,
5). Bee species richness also varied significantly between sampling periods (F6,654 =
48.02, P << 0.0001) (Figure 5; Table 6). For example, samples from Jun-17 had nearly
14
4.5 times more bee species than Nov-17 and 3.7 times more species than Apr/May-18
(Figure 5). Moreover, a significant interaction was found between sampling periods and hills (F6,654 = 12.23, P << 0.0001) (Table 6). Additionally, while only 5 bee species were exclusively trapped in Sep-17, 12 species were exclusive to Apr/May.
Bee assemblages from different sampling periods were significantly different in both species evenness (Nested ANOVA: F6,23 = 3.99, P = 0.007) and species diversity
(Nested ANOVA: F6,24 = 8.66, P < 0.001) (Table 7, 8). The only significant difference in species evenness occurred between Jul/Aug-17 and Apr/May-18 (Tukey’s HSD: P =
0.0242), due to Jul/Aug-17 having 3 dominant species (Ceratina arizonensis,
Lasioglossum (Dialictus) sp, Halictus tripartitus) that constituted for 89% (763) of the sample for that period (Figure 6). Apr/May-18 had a greater species evenness with all 25 species having no more than 40 individuals. For species diversity, Nov-17 was significantly lower than most sampling periods, while Jun-18 had a higher diversity than two other sampling periods (Sep-17 and Apr/May-18) (Figure 6). There was a significant hill x sampling period interaction for species evenness (Nested ANOVA: F6,24 = 3.06, P
= 0.024) (Table 8). Each hill region had different temporal patterns in species evenness as exemplified by numerically dominant Lasioglossum (Dialictus) species in early-spring from CH, and Ceratina arizonensis in mid-summer from SJH (Appendix B). Despite no significant difference in species evenness or diversity between Sep-17 and Apr/May-18, there was two times the species richness per trap in Sep-17 than in Apr/May-18, (Tukey’s
HSD: P > 0.382) (Figures 5, 6).
Additionally, bee genus and species community composition significantly differed between sampling periods (Nested PERMANOVA: F6,24 = 7.79, P = 0.001; F6,24
15
= 5.24, P = 0.001, respectively), with sampling periods significantly interacting with hills
(hill x sampling period) (F6,24 = 1.50, P = 0.04; F6,24 = 1.85, P = 0.001, respectively)
(Table 9, 10). Sampling periods accounted for the majority of the variation in bee genus
(47.7%) and species community composition (39.3%), more than both the hills and sites within hills combined (Table 9, 10). Sep-17, for example, significantly differed from Jun-
17, Mar-18, Apr/May-18 and Jun-18 in species community composition, while Nov-17 significantly differed from Jun-17, Jul/Aug-17 and Sep-17 in genus community composition (Table 11, 12). Ordination (nMDS) plot of bee species community composition had a relatively high stress value (~0.21), indicating that there was not an ideal representation of data in reduced dimensions, probably due to the dominant species
(Figure 7). The community composition of the spring 2018 and mid-fall (Nov. 17) sampling periods appear somewhat distinct from the other seasonal periods along the x axis.
Additionally, I found consistent temporal patterns in the presence of bee genera across sampling periods for all sites. Lasioglossum, Ceratina, Apis, and Agapostemon were the only genera that were present in every sampling period (Appendix C, D).
Thirteen genera were found exclusively in one season: 12 genera in spring (Stelis,
Hoplitis, Osmia, Nomada, Chelostoma and Conanthalictus in Mar-18; Townsendiella and
Dufourea in Apr/May-18; and Andrena, Anthidium, Eucera, Panurginus in both Mar-18 and Apr/May-18) and 1 genus in summer (Ashmaediella in Jul/Aug-17). Furthermore, genus assemblages tended to be similar between like months over the two years (Figure
8). In SJH, for example, Diadasia, Melissodes, Halictus and Lasioglossum were common both sampling periods (Jun-17 and Jun-18) in Bonelli Park, Ceratina in Galster Park, and
16
Melissodes and Ceratina in Voorhis Reserve. In CH, Lasioglossum and Agapostemon were common both sampling periods in Campsite, and Melissodes, Diadasia, Ceratina and Lasioglossum in Quarter Horse.
There were also consistent temporal patterns in the presence of individual bee species across sampling periods. All sampling periods had the following native species in common: Agapostemon texanus, Ceratina arizonensis, and Lasioglossum (Dialictus) species – all of which are small, green or black bees that tend to be solitary generalists
(Appendix B). Apis mellifera was the only non-native species that was present in all sampling periods. Peaks in abundance occurred at different times for different species; for example, Augochlorella pomoniella in late summer/early fall (Sep-17), Halictus tripartitus and Diadasia ochracea in late spring/early summer (Jun-17). The spring sampling periods had the most species that were exclusive to that season (31 species)
(Appendix B). Three bee species were present only in the summer (Jul/Aug-17), including Diadasia enavata, Ceratina tejonensis, and Ashmeadiella cockerelli; no species were exclusively caught during the fall periods (Appendix B). Of the 31 species present only during spring periods, 25 belonged to 12 genera that were trapped only in the spring
(i.e. Andrena, Osmia, Panurginus, Eucera, Nomada, Dufourea, Townsendiella,
Conanthalictus, Anthidium, Chelostoma, Hoplitis and Stelis), many of which were singletons (10) and doubletons (4) (Appendix B-D).
Geographical Variation in Bee Assemblages
Hill regions differed in measures of bee richness and community composition.
There was no significant difference in bee abundance between hills (Nested ANOVA:
F1,654 = 0.54, P = 0.4625) (Table 2). Nearly 48% (1,661) of the total bees were collected
17 from SJH and 52% (1,775) from CH. Bee genus and species richness varied significantly between hills: SJH had 28 genera (mean genera per trap±SEM = 1.99±0.07) and 55 species (mean species per trap±SEM = 1.88±0.08), CH had 27 genera (mean genera per trap±SEM = 2.42±0.10) and 63 species (mean species per trap±SEM = 2.43±0.12) (F1,654
= 19.13, P << 0.001; F1,654 = 23.74, P << 0.0001, respectively) (Tables 4, 6). Hill regions also differed in genus and species community composition (PERMANOVA: F1,24 = 4.63,
P = 0.002; F1,24 = 3.87, P = 0.001), but only accounted for 4.72% of the variation in genus community composition and 4.84% in species community composition (Table 9,
10). Sorenson’s similarity index indicated that the two hills shared the greatest similarity in bee species community composition in Nov-17 (Ss = 71.4%), and were most different in Apr/May-18 (Ss = 38.7%) (Table 13). No significant difference in species diversity occurred between hills (F1,24 = 1.71, P = 0.204), but numerous bee taxa were collected from a single hill region: 17 species and 5 genera (Anthidium, Atoposmia, Chelostoma,
Dufourea, and Townsendialla) were exclusive to SJH, whereas 25 species and 4 genera
(Anthophorula, Ashmeadiella, Nomada, and Stelis) were exclusive to CH (Table 7,
Appendix B-D). Specific bee taxa tended to be more abundant in one hill region, such as
Ceratina arizonensis, which was more abundant in SJH, and Diadasia ochracea,
Agapostemon texanus and Lasioglossum (Dialictus) species, which were more abundant in CH (Figure 9, Appendix B).
Sites within hills varied in CSS bee abundance and measures of richness and community composition. There was a significant difference in bee abundance between sites within a hill region (Nested ANOVA: F4,654 = 19.04, P << 0.0001), although bee abundances did not vary between hill regions (Table 2). Within SJH, Galster Park had
18 nearly double the average bees per trap than Voorhis Reserve and Bonelli Park, across all sampling periods (Tukey’s HSD: P = 0.001; P = 0.001, respectively) (Figures 10, 11).
For CH, both Quarter Horse and Campsite had greater bee abundances than Green River, with Green River having three times less as many bees per trap (P = 0.001; P = 0.001, respectively) (Figure 10, 11). When comparing all six sites, Galster Park had three times as many bees as Green River (P = 0.001) (Figure 11). Similarly, samples from Quarter
Horse had approximately 2.6 times as many bees as Green River.
Bee genus richness varied significantly between sites within hills (F4,654 = 20.65,
P << 0.001) (Table 4). Across all sampling periods, 28 genera were collected at SJH and
27 were collected at CH, 16 of which were found at Bonelli Park, 20 at Galster Park, 19 at Voorhis Reserve, 21 at Campsite, 13 at Green River and 23 at Quarter Horse. Due to their high bee genus richness, Campsite and Quarter Horse were the only sites that had significantly greater genus richness than the other four sites (Figure 12). Bee genus community composition also varied significantly between sites within hills
(PERMANOVA F4,24 = 3.41, P = 0.001) (Table 10). Sites within hills accounted for
13.9% of the variation in genus community composition (Table 10). Despite reporting a significant difference, there was no significant pairwise comparisons in bee genus community composition (Tukey’s HSD: P > 0.44) (Table 14).
Species richness varied significantly between sites within hills (F4,654 = 15.61, P
<< 0.0001), (Table 6). Traps at each site, collectively, caught between 26 and 48 species total, with 48 species at Campsite and 26 species each at Bonelli Park and Green River
(Table 15). Samples from Campsite and Quarter Horse had a greater species richness than the other sites (Figure 13). Campsite and Quarter Horse samples had nearly double the
19 species richness of Green River samples (Tukey’s HSD: P = 0.001) (Figure 13). In addition, bee species community composition significantly varied between sites within hills (PERMANOVA F4,24 = 2.39, P = 0.001) (Table 9). Sites within hills accounted for slightly more of the variation (11.9%) than did hills (4.84%) (Table 9). Yet, there were no significant pairwise comparisons (Tukey’s HSD) between sites (Table 16). Sites within
CH were more similar with each other in community composition (Sorenson’s similarity
(Ss)) = 55%) than the SJH sites (Ss = 50.9%). Within each hill region, Bonelli Park was the least similar from the other SJH sites, Voorhis Reserve and Galster Park (Ss = 55.2%;
Ss = 41.4%, respectively), and Green River was the least similar from the other CH sites,
Campsite and Quarter Horse (Ss = 51.4%; Ss = 55.7%, respectively) (Table 17). In an ordination plot, sites within hills, for both hills, seemed to differ less in Jul/Aug-17 and
Sep-17, along both axes, than they did during the other sampling periods (Figure 7).
Plant Species Assemblage and Floral Presence
Across all sampling periods, 21 plant species were recorded from transects as being present in one or more of the 6 sites, with 13 species being present in SJH and 13 being present in CH. Each site had different plant species assemblages, with Artemisia californica (California sagebrush) being dominant at Voorhis Reserve, Quarter Horse, and Green River (before the wildfire), Eriogonum fasciculatum (California buckwheat) being dominant at Bonelli Park and Campsite, and Salvia mellifera (black sage) being dominant at Galster Park (Figures 14-19). Of the 21 recorded species, 8 were exclusive to
SJH and 8 were exclusive to CH. While each site had between 4 and 8 plant species observed across all sampling periods, each sampling period had between 12 and 20 plant species across all sites. Brassica nigra (black mustard), an invasive weed, was common
20 in the spring and late spring/early summer, and was observed covering a larger percentage of Galster Park than the other sites, especially in Jun-17 (47%) (Figures 14-
19). Brassica nigra was not observed at Campsite and was not very common at Quarter
Horse in CH.
I documented 24 flowering plant species across all sites, with 14 being found in SJH, and 14 in CH (Appendix E-J). Similarly, between both hill regions, 8 flowering species were exclusive to CH and 8 were exclusive to SJH (Appendix E-J).
Between 3 and 14 flowering species were observed each sampling period (mean per sampling period±SEM = 8.86±1.47), with Apr/May-18 having the most flowering species
(14 species) (mean±SEM = 3.33±0.56). Nov-17 had the least species (mean±SEM =
0.83±0.54). The number of flowering species ranged from 4 to 8 species for each site across all sampling periods, with 8 species at Green River and 4 species at Campsite.
Despite Green River being burned in a wildfire, 7 of its 8 species appeared after the fire from March to June 2018 (mean±SEM = 2.57±0.65). Each flowering plant, across all sites and sampling periods, had anywhere between 1 and 10,000 (estimated) inflorescences, depending on the species. Eriogonum fasciculatum, for example, had many inflorescences, on average, per individual (mean±SEM = 1,136.61±87.24), and was observed flowering in spring and summer in Bonelli Park, Campsite and Quarter Horse and only in the summer in Voorhis Reserve and Green River; Eriogonum fasciculatum was not present at Galster Park (Appendix E-J).
21
N San Jose Hills Frank G. Bonelli Park
Voorhis Ecological Reserve
Galster Park
Chino Hills
CHSP: Campsite
CHSP: Quarter Horse
CHSP: Green River 2 km
Figure 1. Map of the 6 sites used in the study. Three sites were located within the San Jose Hills hill region and three were located within the Chino Hills hill region (CHSP=Chino Hills State Park).
22 -r
I w ■ • I
I l 0 0 0 8 II l -
Figure 2. Diagram of the site perimeter and transect layout for each study location. Numbers 1,2 and 3 denote the transects.
23
12 a
10 a
8 ad
6 bdef 4 b Average # bees per trap # trap bees per Average
bce 2 bc
0 I y '\ '\
Figure 3. Average bee abundance per trap per sampling period. Letters denote the Tukey’s HSD pairwise comparison results. (Q-critical=4.182)
24
Tukey’s HSD pairwise comparison results.(Q comparison Tukey’s HSDpairwise denote the sampling period.Letters per richnesspertrap genus bee Figure 4.Average
Average Bee Genera Per Trap 3.5 4.5 0.5 1.5 2.5 4 0 1 2 3 a
b
c
25
-critical=4.182) -critical=4.182) I d
b
d
c
4.5 a 4
3.5 be 3 b
2.5 bc
2 c Average Species Per Trap Species Per Average 1.5 d 1 d
0.5 0 I
Figure 5. Average bee species richness per trap per sampling period. Letters denote the Tukey’s HSD pairwise comparison results. (Q-critical=4.182)
26
3
a 2.5 bcdef
abce abcef 2
bc ■ ■ 1.5 ab cd Pielou’s
Index Value Index Evenness (J’)
1 ■ Shannon’s Diversity (H)
0.5
0 Jun-17 Jul/Aug-17 Sep-17 Nov-17 Mar-18 Apr/May-18 Jun-18
Figure 6. Evenness and Diversity Indices per sampling period across sites. Letters denote the Tukey’s HSD pairwise comparison results for Shannon’s Diversity, arrows denote the only significant difference between sampling periods for Pielou’s Evenness. (Q-critical=4.182 for both evenness and diversity)
27
C
B
A A 0.5 · B B C F F Season A F C i.J Jun-17 E i.J JuUAug-17 D ■ Sep-17 D B F A Nov-17 D Mar-18 F D C I F • Apr/May-18 A A E D Jun-1 8 E B B Hill E E C E t CHINO HILLS SAN JOSE HILLS C A E
-0.5 · C D B
F
D
-0.5 0.0 0.5 1.0 nmds1 Figure 7. Ordination (nMDS) plot for bee species community composition grouped by sites within hills and sampling periods. Bee species rank orders were used, instead of absolute abundances. Minimum convex polygons grouped by sampling periods and hills. Letters denote sites: A=Bonelli Park, B=Galster Park, C=Voorhis Reserve, D=Campsite, E=Green River, F=Quarter Horse. (Stress value: 0.2153571)
28
Jun-17 Jun-18
2.3% 4.7% 16.1% 9.7% 20.9% 3.2% 3.2% 25.6% 32.3% 18.6% 19.4% 27.9% Bonelli Park • Agapostemon 16.1% 1.0% 11.2% 10.2% 8.7% 0.9% • Anthophorula 4.1% 7.8% 2.6% 1.0% 0.9% Apis 2.0% 0.9% • 6.1% 5.1% 2.6% • Atoposmia 59.2% 75.7% Augochlorella
Galster Park Park Galster • Bombus 8.6% 3.8% 0.8% 3.9% • 4.8% 3.9% 0.8% 2.9% 4.7% 10.5% • Calliopsis
6.7% 17.8% Ceratina 5.4% • 0.8% Voorhis Voorhis 11.4% 61.2% • Diadasia 51.4% 0.8% • Exomalopsis 9.4% 0.5% 5.6% 0.5% • Halictus 1.4% 22.9% 43.7% 1.4% 40.0% • Hylaeus 11.3% 11.4% Lasioglossum Campsite 19.7% • 5.7% 5.7% 0.5% 8.6% 0.5% 5.6% 5.7% • Megachile
12.2% • Melissodes 6.8% Peponapis 33.3% • 36.5% 8.1% 57.6% Xenoglossa 3.0% • 27.0% Green River Green 1.4% 3.0% 2.7% 1.4% 4.1% 3.0% 2.1% 0.7% 7.5% 6.2% 3.1% 4.9% 9.8% 1.0% 0.7% 1.7% 19.5% 1.6% 23.0% 16.4% 30.1% 1.6% 0.7% 14.7% 6.6% Horse Quarter 12.0% 34.4% 1.6%
Figure 8. Bee genus abundance by percentage per site for Jun-17 and Jun-18. A
similar pattern in bee genus diversity and abundance can be seen between the 2
sampling periods for most of sites.
29
CHINO HILLS
15 600 -
18
400 -
15 Genus 11 ■ Agapostemon ■ Eucera 200 - Andrena ■ Exomalopsis 11 ■ 5 ■ Anthidium ■ Halictus 9 ■ Anthophora ■ Hoplitis Anthophorula ■ Hylaeus Apis ■ Lasioglossum o- g ■ Ashmeadiella ■ Megachile ~"' SAN JOSE HILLS ■ Atoposmia ■ Melissodes :, .0 Augochlorella Nomada <( 11 ■ ■ Bombus ■ Osmia 600 - ■ Calliopsis Pa nurginus ■ Ceratina ■ Peponapis ■ Chelostoma ■ Stelis ■ Conanthalictus ■ Townsendiella Diadasia ■ Xenoglossa 400 - ■ Dufourea ■ Xy1ocopa 11 12 16 200 - 8 12 6 o-
Jul/Aug~17 Sep--17 Nov-17 Sampling Period -
Figure 9. Bee abundance by genus per hill region and sampling period. Graphs are arranged by hill region. Dominant bee genera include Lasioglossum, Ceratina, Halictus, and Melissodes. Numbers on top of each column denote the total number of genera collected during that sampling period per hill region.
30
38 36 34 32 30 ■ Jun-17 28 ■ Jul/Aug-17 26 24 ■ Sep-17
22 ■ Nov-17 20 Mar-18 18 ■
16 ■ Apr/May-18 14 ■ Jun-18 12
Average Bee Number Per Trap Trap Per Number Bee Average 10 8 6 4 2 0 Bonelli Galster Voorhis Campsite Green River Quarter Horse San Jose Hills Chino Hills
Figure 10. Average bee abundance per trap per site and sampling period.
31
10
9 a
8 a a 7
6
5 b 4
Average # bees per trap # trap bees per Average b 3 b
2
1
0 Bonelli Galster Voorhis Campsite Green Quarter Park Park River Horse San Jose Hills Chino Hills
Figure 11. Average bee abundance per trap for sites. Letters denote the Tukey’s HSD pairwise comparison results. (Q-critical=4.042)
32
3.5 b 3 b
2.5 a a 2 a a
1.5
1 Average Bee Genera Per Trap
0.5
0 Bonelli Park Galster Park Voorhis Campsite Green River Quarter Reserve Horse San Jose Hills Chino Hills
Figure 12. Average bee genus richness per trap for sites. Letters denote the Tukey’s HSD pairwise comparison results. (Q-critical=4.042)
33
3.5 b b 3
2.5 a a 2 a a 1.5
Average Species Per Trap Trap Species Per Average 1
0.5
0 Bonelli Galster Voorhis Campsite Green Quarter Park Park Reserve River Horse San Jose Hills Chino Hills
Figure 13. Average bee species richness per trap for sites. Letters denote the Tukey’s HSD pairwise comparison results. (Q-critical=4.042)
34
35
30
■ Eriogonum fasciculatum 25 ■ Artemisia californica 20 ■ Brassica nigra
Percent Cover (%) 15 ■ Bromus spp.
10 ■ Avena spp.
5
0 Jun-17 Jul/Aug-17 Jul-17 Sep-17 Sep-17 Nov-17Nov-17 Mar-18Mar-18 Apr/May-18 Apr-18 Jun-18 Jun-18
Figure 14. Bonelli Park plant species percent cover by date. Eriogonum fasciculatum was most dominant at this site.
35
50
45 ■ Artemisia californica 40 ■ Brassica nigra 35
■ Salvia mellifera 30
Marrubium vulgare 25 ■
20 Juglans nigra Percent Cover (%) ■
15 ■ Toxicodendron diversilobum 10 ■ Cucumis anguria 5
0 Jun-17 Jul/Aug-17 Sep-17 Nov-17 Mar-18 Apr/May-18 Jun-18
Figure 15. Galster Park plant species percent cover by date. Salvia mellifera was most dominant at this site.
36
30
■ Eriogonum fasciculatum 25 ■ Artemisia californica
20 ■ Brassica nigra
■ Nicotiana glauca 15
Percent Cover (%) ■ Carduus pycnocephalus 10 ■ Pseudognaphalium californicum
5 ■ Bromus spp.
0 Jun-17 Jul/Aug-17 Sep-17 Nov-17 Mar-18 Apr/May-18 Jun-18 Jun-17 Jul- 17 Sep-17 Nov- 17 Mar-18 Apr-18 Jun-18 Figure 16. Voorhis Reserve plant species percent cover by date. Artemisia californica was most dominant at this site.
37
40
35
■ Eriogonum fasciculatum 30
25 ■ Encelia californica
20 Percent Cover (%) ■ Salvia leucophylla 15
Ericameria 10 ■ pinifolia
5
0 Jun-17Jun-17 Jul/Aug-17 Aug-17 Sep-17 Sep-17 Nov Nov-17- 17 Mar-18 Mar-18 Apr/May-18 May-18 Jun-18 Jun-18
Figure 17. Campsite plant species percent cover by date. Eriogonum fasciculatum was most dominant at this site.
38
55
50
45
Artemisia 40 ■ californica
35 ■ Eriogonum fasciculatum 30 ■ Brassica nigra Percent Cover (%) 25
■ Carduus 20 pycnocephalus
15 ■ Eriodictyon californicum 10
5
0 Jun-17 Jun-17 Jul/Aug-17 Aug-17 Sep-17 Sep-17 NovNov-17- 17 Mar-18 Mar-18 Apr/May-18 May-18 Jun-18 Jun-18
Figure 18. Green River plant species percent cover by date. Due to a wildfire, all vegetation was burned in Nov. 2017, with slow regrowth following shortly after. Before the fire, Artemisia californica was most dominant.
39
45
■ Artemisia californica 40 ■ Salvia mellifera 35 ■ Isocoma menziesii 30 ■ Eriogonum fasciculatum 25 ■ Encelia californica Percent Cover (%) 20 ■ Baccharis pilularis 15 ■ Sambucus cerulea 10 ■ Astragalus trichopodus 5
0 Jun-17Jun-17 Jul/Aug-17 Aug-17 Sep-17 Sep-17 Nov Nov-17- 17 Mar-18 Mar-18 Apr/May-18 May-18 Jun-18 Jun-18
Figure 19. Quarter Horse plant species percent cover by date. Artemisia californica was most dominant at this site.
40
Table 1. Details of each sampling site with dates sampled.
County, City Coordinates Elevation Hill Site Dates Sampled (California) (N, W) (m) Bonelli Los Angeles, 34.078180, 321 Park 13-14 Jun. 2017 San Dimas -117.797969
lls 29-30 Jul. 2017 Galster 16-17 Sep. 2017 Los Angeles, 34.043232, 222 Park 11-12 Nov. 2017 West Covina -117.900230 Jose Hi 11-12 Mar. 2018 Voorhis San 28-29 Apr. 2018 Los Angeles, 34.058769, Ecol. 286 15-16 Jun. 2018 Pomona -117.830842 Reserve 27-28 Jun. 2017 San Bernardino, 33.924075, Campsite 12-13 Aug. 2017 253 23-24 Sep. 2017 Chino Hills -117.708045 18-19 Nov. 2017 25-26 Mar. 2018 Green Orange, 33.870841, 152 River 13-14 May 2018 West Corona -117.686988 23-24 Jun. 2018 27-28 Jun. 2017
Chino Hills 12-13 Aug. 2017 23-24 Sep. 2017 Quarter Orange, 33.908693, 18-19 Nov. 2017 312 Horse Yorba Linda -117.791854 25-26 Mar. 2018 12-13 May 2018 23-24 Jun. 2018
Table 2. Three-Factor nested ANOVA for bee abundance per trap between hill regions, sites within hills and sampling periods, with interaction between hills and sampling periods. Interaction between sites and sampling periods unobtainable due to one sampling per site per sampling period.
Three-factor nested ANOVA Source of Variation SS df MS F P-value Hills 19.3393 1 19.3393 0.540431 0.46252 Sites within Hills 2455.65 4 613.914 19.03672 8.019E-15 *** Sampling Period 6498.82 6 1083.14 33.58676 2.185E-35 *** Hill x Sampling Period 3650.74 6 608.457 18.86752 2.589E-20 *** Within 21090.80 654 32.2489
Total 33715.40 671
41
Table 3. Average number of bees per trap per hill region and sampling period.
Jul/Aug- Apr/May- Jun-17 17 Sep-17 Nov-17 Mar-18 18 Jun-18
Mean 5.125 14.04167 3.20833 0.5625 4.25 1.6875 5.72917 SD 3.37466 16.02785 2.24043 0.71179 2.96433 1.57313 4.05672 SJH SEM 0.48709 2.31342 0.32338 0.10274 0.42786 0.22706 0.58554
Mean 12.0625 5.6875 4.10417 1.8125 9.08333 1.54167 2.6875 SD 8.82310 5.25582 2.42539 1.96411 8.80965 1.18426 2.28926 CH SEM 1.27351 0.75861 0.35008 0.28349 1.27156 0.17093 0.33043
Table 4. Three-Factor nested ANOVA for bee genus richness per trap between hill regions, sites within hills and sampling periods, sites within hills and sampling periods, with interaction between hills and sampling periods.
Three-factor nested ANOVA Source of Variation SS df MS F P-value Hills 30.43006 1 30.43006 19.12792 1.42E-05 *** Sites within Hills 131.423 4 32.85575 20.65267 4.82E-16 *** Sampling Periods 529.5923 6 88.26538 55.4824 2.30E-55 *** Hill x Sampling Period 97.53869 6 16.25645 10.21858 7.95E-11 *** Within 1040.43 654 1.590872
Total 1829.415 671
Table 5. Average number of bee genera per trap, for hill regions and sampling periods.
Jul/Aug- Apr/May- Jun-17 17 Sep-17 Nov-17 Mar-18 18 Jun-18
Mean 2.75 2.66667 2 0.52083 2.39583 1.22917 2.41667 SD 1.36054 1.29374 0.82514 0.65199 1.14371 1.01561 1.28548 SJH SEM 0.19638 0.18674 0.11910 0.09411 0.16508 0.14659 0.18554
Mean 4.52083 2.85417 2.3125 1.25 3.27083 1.20833 1.54167 SD 2.16343 1.16673 1.22312 1.15777 2.26668 0.89819 1.21967 CH SEM 0.31226 0.16840 0.17654 0.16711 0.32717 0.12964 0.17604
42
Table 6. Three-factor nested ANOVA for species richness between hills, sites within hills, and sampling periods, with interaction between periods and hills.
ANOVA Source of Variation SS df MS F P-value Hills 51.482143 1 51.48214286 23.76438 1.37E-06 *** Sites within hills 135.2857 4 33.821425 15.61212 3.30E-12 *** Sampling Periods 624.12202 6 104.0203373 48.01624 7.47E-49 *** Hill x Sampling Period 158.95536 6 26.49255952 12.22908 4.59E-13 *** Within 1416.7976 654 2.166357187
Total 2386.6429 671
Table 7. Three-factor nested ANOVA for species diversity between hills, sites within hills, and sampling periods, with interaction between periods and hills.
ANOVA Source of Variation SS df MS F P-value Hills 0.2501 1 0.2501 1.706682 0.20381 Sites within hills 1.0624 4 0.2656 1.812454 0.15934 Sampling Periods 7.6177 6 1.269617 8.663861 4.50E-05 *** Hill x Sampling Period 1.9212 6 0.3202 2.185044 0.08016 Within 3.517 24 0.146542
Total 14.3684 41
Table 8. Three-factor nested ANOVA for species evenness between hills, sites within hills, and sampling periods, with interaction between periods and hills.
ANOVA Source of Variation SS df MS F P-value Hills 0.0000166 1 1.66E-05 0.254096 0.61938 Sites within hills 0.0005603 4 0.00014 2.144282 0.10774 Sampling Periods 0.0015628 6 0.00026 3.986914 0.00702 ** Hill x Sampling Period 0.0011984 6 0.0002 3.057243 0.02386 * Within 0.0015026 23 6.53E-05
Total 0.004841 40
43
Table 9. Three-Factor PERMANOVA for bee species community composition between hill regions, sites within hills, and sampling periods, with interaction between hills and sampling periods.
Three-Factor nested PERMANOVA Source of Variation SS df MS F R2 P-value Hills 0.3888 1 0.38876 3.8675 0.04835 0.001 ** Sites Within Hills 0.9610 4 0.24026 2.3901 0.11951 0.001 ** Sampling Period 3.1610 6 0.52683 5.2409 0.39309 0.001 ** Hill x Sampling Period 1.1180 6 0.18634 1.8537 0.13904 0.001 ** Residuals 2.4125 24 0.10052 0.30001
Total 8.0413 41 1.00000
Table 10. Three-Factor PERMANOVA for bee genus community composition between hill regions, sites within hills, and sampling periods, with interaction between hills and sampling periods.
Three-Factor nested PERMANOVA Source of Variation SS df MS F R2 P-value Hills 0.2714 1 0.27136 4.6303 0.04723 0.002 ** Sites Within Hills 0.7991 4 0.19977 3.4087 0.13909 0.001 ** Sampling Period 2.7401 6 0.45668 7.7924 0.47694 0.001 ** Hill x Sampling Period 0.5280 6 0.08800 1.5016 0.09191 0.040 * Residuals 1.4066 24 0.05861 0.24483
Total 5.7451 41 1.00000
44
Table 11. Tukey HSD pairwise comparisons of species community composition between sampling periods. (Q-critical=4.182)
Treatments p-value
Jun-17 vs Jul/Aug-17 0.0790277
Jun-17 vs Sep-17 0.0012270 **
Jun-17 vs Nov-17 0.2323062
Jun-17 vs Mar-18 0.9997416
Jun-17 vs Apr/May-18 0.9838010
Jun-17 vs Jun-18 0.8826441
Jul/Aug-17 vs Sep-17 0.6889920
Jul/Aug-17 vs Nov-17 0.9981021
Jul/Aug-17 vs Mar-18 0.0326619 *
Jul/Aug-17 vs Apr/May-18 0.0111539 *
Jul/Aug-17 vs Jun-18 0.6149875
Sep-17 vs Nov-17 0.3610565
Sep-17 vs Mar-18 0.0004093 ***
Sep-17 vs Apr/May-18 0.0001179 ***
Sep-17 vs Jun-18 0.0329574 *
Nov-17 vs Mar-18 0.1112756
Nov-17 vs Apr/May-18 0.0431385 *
Nov-17 vs Jun-18 0.8990714
Mar-18 vs Apr/May-18 0.9995175
Mar-18 vs Jun-18 0.6867456
Apr/May-18 vs Jun-18 0.4243859
45
Table 12. Tukey’s HSD pairwise comparisons for genus community composition between all sampling periods. (Q-critical=4.182)
Treatments p-value
Jun-17 vs Jul/Aug-17 0.9939607
Jun-17 vs Sep-17 0.3734341
Jun-17 vs Nov-17 0.0000571 ***
Jun-17 vs Mar-18 0.9999999
Jun-17 vs Apr/May-18 0.2652471
Jun-17 vs Jun-18 0.9305645
Jul/Aug-17 vs Sep-17 0.7752948
Jul/Aug-17 vs Nov-17 0.0004062 ***
Jul/Aug-17 vs Mar-18 0.9974527
Jul/Aug-17 vs Apr/May-18 0.6484889
Jul/Aug-17 vs Jun-18 0.9995333
Sep-17 vs Nov-17 0.0224291 *
Sep-17 vs Mar-18 0.4290364
Sep-17 vs Apr/May-18 0.9999909
Sep-17 vs Jun-18 0.9446112
Nov-17 vs Mar-18 0.0000762 ***
Nov-17 vs Apr/May-18 0.0380549 *
Nov-17 vs Jun-18 0.0013690 **
Mar-18 vs Apr/May-18 0.3114737
Mar-18 vs Jun-18 0.9548620
Apr/May-18 vs Jun-18 0.8741687
46
Table 13. Sorenson’s similarity of species community composition between hills per sampling period.
Sampling Period Ss
Jun-17 0.5964912
Jul/Aug-17 0.6060606
Sep-17 0.6363636
Nov-17 0.7142857
Mar-18 0.4
Apr/May-18 0.3870968
Jun-18 0.6060606
Table 14. Tukey’s HSD pairwise comparisons for genus community composition between sites within hills. (Q-critical=4.042)
Treatments p-value
Bonelli vs Galster 0.9410525
Bonelli vs Voorhis 0.9925379
Galster vs Voorhis 0.9993090
Campsite vs Green River 0.4616623
Campsite vs Quarter Horse 1.0000000
Green River vs Quarter Horse 0.4404063
47
Table 15. Total number of species collected across all sampling periods for each site.
Site Number of species Bonelli Park 26 Galster Park 32 Voorhis Reserve 32 Campsite 48 Green River 26 Quarter Horse 35
Table 16. Tukey HSD pairwise comparisons of species community composition between sites within hills. (Q-critical= 4.042)
Treatments p-value
Bonelli vs Galster 0.9992929
Bonelli vs Voorhis 0.9997449
Galster vs Voorhis 0.9999998
Campsite vs Green River 0.9962024
Campsite vs Quarter Horse 0.9999978
Green River vs Quarter Horse 0.9988350
48
Table 17. Sorenson’s similarity of species community composition between sites.
Site Comparisons Ss
Bonelli vs Galster 0.4137931
Bonelli vs Voorhis 0.5517241
Bonelli vs Campsite 0.4594595
Bonelli vs Green River 0.4230769
Bonelli vs Quarter Horse 0.4590164
Galster vs Voorhis 0.5625
Galster vs Campsite 0.525
Galster vs Green River 0.5862069
Galster vs Quarter Horse 0.5074627
Voorhis vs Campsite 0.5
Voorhis vs Green River 0.6896552
Voorhis vs Quarter Horse 0.5373134
Campsite vs Green River 0.5135135
Campsite vs Quarter Horse 0.5783133
Green River vs Quarter Horse 0.557377
49
DISCUSSION
My study provides strong evidence of significant seasonal differences in bee abundance and diversity in southern California inland CSS regions. Although studies on coastal CSS bee fauna currently exist (Hung et al., 2015; 2017; and 2019), this is the first study to document temporal differences and patterns in the bee fauna of inland CSS hill regions (SJH and CH) over multiple seasons (summer, fall, and spring). At least 80 bee species (32 genera) were collected across all sampling periods, with late spring/early summer having the highest genus/species richness and species diversity and mid-fall having the lowest genus/species richness and diversity (Figures 4-6). In addition, there was greater bee abundance in mid-summer and lower bee abundance in mid-fall (Figure
3). Significant variation in species evenness between sampling periods was due to mid- summer (Jul/Aug-17) having the lowest species evenness, with 3 dominant species
(Ceratina arizonensis, Lasioglossum (Dialictus) sp, Halictus tripartitus), and mid-spring
(Apr/May-18) having the highest species evenness, with all species consisting of no more than 40 individuals (Figure 6; Appendix B). These findings somewhat support my initial hypothesis that there would be higher bee abundance and diversity in the spring, in that higher diversity was observed in late spring/early summer.
Bee abundance, peaked in mid-summer (Jul/Aug-17), and genus/species richness, peaked in late spring/early summer. Both displayed similar temporal trends of decreasing into mid-fall, and spiking again in early spring. Numerous genera were present in only one season, such as 12 genera in spring (Andrena, Anthidium, Conanthalictus, Eucera,
Panurginus, Dufourea, Stelis, Hoplitis, Osmia, Nomada, Chelostoma and Townsendiella) and 1 genus in summer (Ashmaediella). High genus/species richness in spring reflected
50
the presence of numerous spring-only bee taxa (31 species) which include species in
genera Andrena, Osmia, Panurginus, Eucera, Nomada, Dufourea, Townsendiella,
Conanthalictus, Anthidium, Chelostoma, Hoplitis and Stelis (Appendix B-D), many of
which were singletons (10) and doubletons (4). A few bee species (3) were present only
in the summer which include Diadasia enavata, Ceratina tejonensis, and Ashmeadiella
cockerelli (Appendix B). No bee taxa were exclusively trapped in fall. Some bee taxa
displayed temporal patterns in abundance, such as Apis mellifera, Diadasia ochracea and
Halictus tripartitus peaking in late spring/early summer of 2017 (Jun-17), Ceratina
arizonensis peaking in mid-summer (Jul/Aug-17), Augochlorella pomoniella peaking in
late summer/early fall (Sep-17), and Lasioglossum (Dialictus) peaking in early spring
(Mar-18). For the spring-exclusive species that were identifiable to their adaptations, 11
species are known generalists (Anthidium utahense and A. clypeodentatum; 1 Anthophora
sp.; 2 Panurginus sp.; Ceratina neomexicana; 4 Eucera sp.; Lasioglossum
(Lasioglossum) sisymbrii.) and 5 are specialists (1 Conanthalictus sp.; 1 Dufourea sp.;
Diadasia lutzi; 2 Chelostoma sp.). The only cleptoparasitic species in the collection were
three species (1 Nomada sp.; 1 Stelis sp.; 1 Townsendiella sp.) trapped during the spring
sampling periods.
Findings from previous studies (Leong et al., 2015; Kimoto et al., 2012; Wojcik et
al., 2008) contrast with my results of temporal variation in bee abundance and
genus/species richness. Leong et al. (2015), in particular, found that bee abundance and
richness, in natural landscapes consisting of grasslands and oak woodlands in Brentwood,
California, peak in the spring, versus human-altered landscapes that peak later in the year.
Overall, Leong et al. (2015) collected 84 species (out of a total 91 species collected) from
51 the natural landscape from spring and summer over the course of three years. Wojcik et al. (2008), after sampling 32 species of bees from an urban garden in Berkeley,
California, consisting of various flowering species, found that bee abundance peaked in late spring/early summer (June) (89 bees) and late summer/early fall (September) (92 bees), with no significant seasonal peak in species richness (23 species from April to
June, and 25 species from July to October). Another study, conducted from early-summer to late-summer in a natural setting of bunchgrass prairie in Oregon (Kimoto et al., 2012)., observed a peak in bee abundance and richness in mid-summer (July), supporting my findings for bee abundance but contrasting those for richness.
The most commonly trapped bee taxa in my study have also been reported from previous studies (Wojcik et al., 2008; Leong et al., 2015; Hung et al., 2015; Kimoto et al.,
2012). These numerically dominant bees include Lasioglossum (Dialictus) species,
Ceratina arizonensis, Halictus tripartitus, Apis mellifera, Agapostemon texanus,
Melissodes sp. 5, and Lasioglossum (Evylaeus) species, all of which are ground-nesters, except Ceratina arizonensis and Apis mellifera (cavity-nesters) (Appendix B). All other species (73) consisted of less than 50 individuals (Appendix B). Similar to my findings, in an urban setting of the San Francisco Bay Area, Wojcik et al. (2008) found that
Melissodes species and Halictus tripartitus were some of the most numerically dominant species from spring through fall, and Leong et al. (2015) found that Lasioglossum species, Agapostemon texanus, Apis mellifera, Halictus tripartitus and Melissodes species were some of the most common species in spring and summer. In contrast to my study,
Megachile perihirta was most abundant in Wojcik et al. (2008), while Ceratina nanula and Osmia nemoris were among the most abundant species in Leong et al. (2015), all of
52
which are cavity nesters. Out of the 70 bee species and morphospecies collected from
coastal CSS fragments in April through June, Hung et al. (2015) reported Lasioglossum
(Dialictus) species (Lasioglossum incompletum), Halictus tripartitus and Ceratina
arizonensis as being some of the most abundant species, as well as Anthophorula
torticornis and Anthidium jocosum – two genera that were rarely trapped in my study.
Kimoto et al. (2012) reported that Lasioglossum, Melissodes, Halictus, Bombus and
Osmia were the most abundant genera collected in their study – Bombus and Osmia were
not common in my study.
Some of the seasonal patterns in bee diversity that have been reported in previous
literature are similar to the ones observed in my study (Kimoto et al., 2012 and Wojcik et
al., 2008). While Kimoto et al. (2012) did not report beyond genus level, Halictus,
Osmia, Lasioglossum, Bombus and Melissodes were observed peaking in abundance in
July; and although I similarly observed Halictus peaking in July, it is difficult to compare on the genus level, as there are many species within each genus. In terms of species,
Wojcik et al. (2008), for example, similar to my study, collected Andrena species and
Osmia species only in the spring and Apis mellifera, Agapostemon texanus, and Halictus tripartitus most of the year. Like my study, Wojcik et al. (2008) observed Halictus tripartitus peaking in June, and while no clear peak in abundance was found in my study for Megachile brevis, Wojcik et al. (2008) observed a peak in abundance in September.
Given that Kimoto et al. (2012) and Wojcik et al. (2008) were conducted in Oregon and
Northern California, respectively, climatic weather patterns may be contributing to these differences in bee diversity (Karunaratne and Edirisinghe, 2008).
53
In addition, significant sampling period x hill interactions indicate differences in temporal patterns in bee abundance and diversity (i.e. richness, evenness, community composition) between SJH and CH. For example, SJH had a lower bee abundance in mid-fall (Nov-17) and a greater bee abundance in mid-summer (Jul/Aug-17), while CH had a lower bee abundance in mid-spring (Apr/May-18) and greater bee abundance in late spring/early summer (Jun-17) (Table 3). Despite both hills having greater genus richness in late spring/early summer (Jun-17), SJH had a lower genus richness in mid-fall
(Nov-17) (mean per trap±SEM = 0.52±0.094) and CH had a lower genus richness in mid- spring (Apr/May-18) (mean per trap±SEM = 1.21±0.13) (Table 5). Each hill region had different temporal patterns in species evenness as exemplified by numerically dominant bee species from each hill, such as Ceratina arizonensis in mid-summer from SJH, and
Lasioglossum (Dialictus) species in early-spring from CH (Figure 9; Appendix B). These findings of significant spatio-temporal interactions in bee abundance and diversity are similar to those found by Hung et al. (2017) and Tylianakis et al., (2005). Hung et al
(2017) observed some CSS fragments in San Diego having higher bee abundance in the spring and other CSS fragments having higher bee abundance in the summer. Tylianakis et al. (2005) found that season and habitat significantly interacted on bee and wasp abundance and species richness, as well as species diversity, in multiple agricultural and natural habitat types (i.e. rice, pasture, coffee, forest) of coastal Ecuador, due to each habitat type having different seasonal effects.
My findings refute my hypothesis that both bee abundance and diversity would vary geographically between inland CSS hill regions. My results show that bee genus/species richness and community composition vary between CSS hill regions, and
54 that bee abundance, species evenness and species diversity did not (Tables 2, 4, 6-9, 12).
Although SJH had one more genus (28) than CH (27), CH had 63 species and SJH had 55 species. Although hill regions did not significantly vary in bee species diversity, some bee taxa exhibited spatial patterns by being geographically specific to each hill region: 17 species (e.g. Ceratina micheneri, C. neomexicana, C. tejonensis, Lasioglossum
(Dialictus) sisymbrii) and 5 genera (Anthidium, Atoposmia, Chelostoma, Dufourea, and
Townsendialla) were exclusive to SJH, and 25 species (e.g. Bombus crotchii, B. vosnesenskii, Diadasia enavata, D. lutzi, D. nitidifrons, Halictus ligatus) and four genera
(Anthophorula, Ashmeadiella, Nomada, and Stelis) were exclusive to CH (Appendix B-
D). For bee species common to both hill regions, spatial patterns in abundance were observed for some species, such as Ceratina arizonensis, which was more abundant in
SJH, and Diadasia ochracea, Agapostemon texanus and Lasioglossum (Dialictus) species, which were more abundant in CH (Appendix B). Due in part to these observed patterns, hill region (geographical location) accounted for nearly 5% of the variation in both genus and species community composition between the two hill regions (Table 9,
10).
Additionally, my study provides evidence that bee abundance, genus/species richness, and genus/species community composition vary between sites within the CSS hill regions (Table 2, 4, 6, 9, 10). Species evenness and diversity were found to not vary within hills (Table 7, 8). With each site separated by 3.72 to 27.5 kilometers, it is safe to assume that the distances between sites are greater than the flight range of most bees, meaning it is unlikely that two sites shared the same bee community (Greenleaf et al.
2007). Between sites within hills, CH was the only hill region to display geographic
55 variation in genus and species richness, as Campsite and Quarter Horse significantly harbored a higher genus richness (mean genera per trap±SEM = 2.68±0.19 and
2.99±0.20, respectively) and species richness (mean species per trap±SEM = 2.89±0.24 and 2.85±0.23, respectively) than Green River across all sampling periods (Figures 12,
13). Campsite and Quarter Horse also had a significantly greater bee abundance (mean per trap±SEM = 6.80±0.68 and 6.41±0.72, respectively) than Green River (mean per trap±SEM = 2.63±0.22) (Figure 11). Despite no variation in genus or species richness between SJH sites, there was a greater bee abundance documented for Galster Park (mean per trap±SEM = 7.66±1.12) than the other two sites (Bonelli Park and Voorhis Reserve)
(Figure 11). Sites within hills accounted for more of the variation in genus and species community composition than did hill regions with ~14% and ~12%, respectively (Table
9, 10). The CH sites were found to be more similar in species community composition
(Sorenson’s similarity (Ss)) = 55%) than the SJH sites (Ss = 50.9%), with Bonelli Park being the least similar from the other two SJH sites, and Green River being the least similar from the other two CH sites (Table 17).
Varying levels of spatial variation in bee abundance and genus/species richness and community composition have been found in previous studies (Hung et al., 2015;
Hung et al., 2019; Antonini et al., 2017). Hung et al. (2015) found 70 bee species within large and small San Diego coastal CSS fragments – very similar to my study. Large fragments, also referred to as “reserves” and defined as more than 5 square kilometers of natural land, were more similar in size and geographic composition to the areas studied in the CH hill region in my study, while small fragments, defined as being less than 0.8 square kilometers, were more similar in size and composition to the areas studied in the
56
SJH hill region. Similar to my study, at least 2 kilometers separated each large and small
CSS fragment site, with the exception of one small CSS site being slightly less than 1 kilometer from a large CSS site (Hung et al., 2015). A total of 58 species were collectively trapped in large fragments and 53 in small fragments (Hung et al., 2015).
Likewise, I trapped more species in CH (63) than I did in SJH (55). Similar to Hung et al.
(2015), I also found no significant difference in bee abundance between CSS regions.
The findings of Hung et al. (2015), however, contrast specifically with my own on community composition varying, to some degree, between hills, as Hung et al. (2015) found no significant geographic difference in species community composition between coastal CSS fragments. It was suggested and further supported by Hung et al. (2019), which was also conducted in large and small coastal CSS fragments, that ecological filters, like available food resources, could be altering the species richness in small fragments versus large fragments. Antonini et al. (2017), after sampling the orchid bee fauna from multiple plateaus of Amazon rainforest in Brazil (each being 8 to 30 kilometers apart), discovered that large plateaus harbored a higher bee species richness than small plateaus; however, bee abundance varied by plateau size. Comparable to my study, Meiners et al. (2019) observed multiple species, including Halictus tripartitus,
Agapostemon texanus, Diadasia ochracea and Ceratina arizonensis, as being present in all alluvial, oak, and grassland study plots (each being roughly between 0.25 km to 14 km apart for each year) in Pinnacles National Park in central California across all years.
Similarly, Agapostemon texanus and Diadasia ochracea were more abundant in certain plots, however, Halictus tripartitus and Ceratina arizonensis were common in all plots.
57
Meiners et al. (2019) additionally documented certain species, such as Bombus crotchii, as being exclusive to select plots of the same habitats.
Finally, my data for plant species assemblages and floral resources in each site support my predictions in that similar plant species assemblages were found in each site and there were more floral resources in the spring. Excluding Green River, the plant species assemblages in each site remained consistent across all sampling periods, except for the annual flowering species. More flowering species were observed in mid-spring
(Apr/May-18) (14 species) (mean±SEM = 3.33±0.56) than any other sampling period
(Appendix E-J). My results showed that, although the sites shared many of the same plant species, certain sites had different dominant species (Figures 14-19). Certain plant species were present only at select sites, such as Salvia mellifera, being present only at
Galster Park, and Encelia californica, being present only at Campsite and Quarter Horse.
Certain plant species could explain the high abundance of Lasioglossum
(Dialictus) species, Ceratina arizonensis, Halictus tripartitus, Apis mellifera,
Agapostemon texanus, Melissodes sp. 5, and Lasioglossum (Evylaeus) in this study. The six dominant species (Lasioglossum (Dialictus) species, Ceratina arizonensis, Halictus tripartitus, Apis mellifera, Agapostemon texanus, and Lasioglossum (Evylaeus)) are mainly generalists, in that they collect resources from a wide variety of plant species
(LeBuhn and Pugh, 2013). During sampling days, I observed a large activity of bees at
Eriogonum fasciculatum inflorescences during the entire duration of its flowering season
(spring to late summer/early fall) in all sites with E. fasciculatum, except Galster Park
(Figure 15). Most of the bees observed were Apis mellifera, however, other smaller, dark bees were observed visiting the flowers, which were unable to be netted and identified. E.
58 fasciculatum has been reported to attract many bees, including Apis mellifera, Halictus species and Lasioglossum (Dialictus) species (Montalvo and Beyers, 2010). Due to the observed high bee activity at E. fasciculatum during each sampling period, it is likely that this species could be contributing to the high abundances of Apis mellifera, Halictus tripartitus, and Lasioglossum (Dialictus) species, and possibly Ceratina arizonensis,
Agapostemon texanus, and Lasioglossum (Evylaeus). Apis mellifera, and species of
Lasioglossum, Halictus, Ceratina, Agapostemon have been reported by previous literature to visit buckwheat (Eriogonum pelinophilum) (Tepedino et al, 2011).
Of these seven dominant species, only one is considered a specialist, Melissodes sp. 5 (Parker et al., 1981). Melissodes is known to collect floral resources from only select plant species, such as Helianthus species (i.e. sunflower and thistle species) (Parker et al., 1981). As reported in a study (Parker et al., 1981), the abundance of one
Melissodes species (M. agilis) was found to be positively correlated with the abundance of sunflower species in Utah. M. agilis was also observed being abundant during all summer months (Parker et al., 1981). In this study, Melissodes was observed being most prevalent in Voorhis Reserve in SJH and Quarter Horse in CH in late spring/early summer. Although no Helianthus species were observed in these sites, Helianthus could be near the proximity of Voorhis Reserve and Quarter Horse, or another plant species could be responsible for the high abundances of Melissodes sp. 5 in each site, such as
Trichostema lanceolatum (vinegar weed). In Campsite, while netting in August 2017,
Melissodes sp. 13 was collected from T. lanceolatum. This species, while it was reported being visited by a different species of Melissodes, could also be responsible for the abundances of Melissodes sp. 5.
59
While no E. fasciculatum was present at Galster Park, I did observe Brassica nigra as being more abundant at Galster Park than any of the other sites during the spring and late spring/early summer. At Galster Park, Brassica nigra covered as much as nearly half of the site (47% in Jun-17) (Figures 14-19), which could explain the large amount of
Ceratina collected at Galster Park in Jul/Aug-17. It has been found in a previous study that Brassica nigra can be utilized by Ceratina species as a nesting substrate, as Ceratina excavate a burrow in the pith of the dead stems (McIntosh, 1996). It is possible that the
Ceratina species used the dead Brassica nigra (most likely those from the previous year) at Galster Park for nesting purposes; and it is possible that, upon them emerging from their nests or finding new nesting locations in Brassica nigra, I trapped a large abundance of the Ceratina species. As Ceratina are also generalists, they could have been using the
Brassica nigra or Salvia mellifera for floral resources. The presence of Encelia californica in Campsite and Quarter Horse could explain their high bee genus and species richness, and the variation within CH. Encelia californica, which is an evergreen species to commonly flower in the winter and spring, could be providing early resources to bees in those sites.
While most of the seven dominant species were present in multiple sampling periods, it is the other less abundant bee species that are responsible for the temporal variation observed in this study. Despite spring having the most exclusive species (31), late spring/early summer (Jun-17) had the highest species richness (Figure 5). Some of the less common bees exclusive to late spring/early summer include Bombus crotchii, B. vosnesenskii, Diadasia nitidifrons, and Anthophorula species (Appendix B).
Interestingly, of the species exclusive to late spring/early summer, I observed that the
60 majority of them appeared to be smaller or medium in size, unlike the Bombus species, which are larger. The bees exclusive to Jun-17 also varied in biology (i.e. nesting traits or being social/solitary). Some species, like Bombus crotchii and B. vosnesenskii, are social, cavity-nesting bees, while others, like Diadasia nitidifrons, and Anthophorula species, are solitary, ground-nesting bees (Rozen, 2011; LeBuhn and Pugh, 2013). In spring (Mar-
18 and Apr/May-18), most of the bees appear to be solitary, ground-nesters, with the exception of Megachile species, Osmia species, and Hoplitis, which are solitary, cavity- nesters, and Halictus and some Lasioglossum species that are social/semi-social, ground- nesters (LeBuhn and Pugh, 2013). With more cavity-nesting bees exclusive to late spring/early summer, spring season plants could be dying out and giving cavity-nesting bees a potential nesting substrate, similar to that of Brassica nigra for Ceratina
(McIntosh, 1996).
Green River Post-Fire Observations
On 25 September 2017, the West Corona fire, burned through the Green River site. The intensity and duration of the fire within the site is unknown, but all that remained within the perimeters of the site post-fire was ash and charred plant remains.
When comparing Green River to Campsite, a CH site with a similar elevation, I documented a noticeably lower bee diversity and abundance at Green River only in early spring (Mar-18) in relation to Campsite following the fire (Figure 10; Table 1; Appendix
C, D). The bee genera, Melissodes, Ceratina and Megachile, were collected at Green
River every sampling period up until the fire, and while those genera were present at
Campsite, as well as Quarter Horse, following the fire, they were no longer present at
Green River (Appendix C, D) in subsequent samples. In addition, Andrena and Hylaeus
61
bees were sampled from the other CH sites post-fire, but not at Green River. The only bee
species that were present pre-fire and post-fire included Lasioglossum (Dialictus) species,
Halictus species, Agapostemon texanus, Peponapis pruinosa, and Apis mellifera, all of
which (excluding Apis mellifera) are primarily ground-nesting bees. Some genera collected in Jun-17 in Green River were not collected in Jun-18, such as Ceratina,
Diadasia, Megachile and Melissodes (Figure 8). Although it may be too early to tell from the data collected at Green River, some studies have found that native bee diversity and abundance increase in the 1-5 years following wildfires (Potts et al., 2003), as it was suggested that wildfires may create an environment that supports native bees, like ground-nesting and cavity-nesting bees (Burkle et al., 2019). This could explain why the majority of the bees collected post-fire at Green River were ground-nesters, as the fire created more exposed ground space for nesting. It is also possible that the ground-nesting bees in Green River were able to survive the high temperatures of the fire by being underground.
The first observed plant species to reappear in the site post-fire were Brassica nigra (black mustard), Eriodictyon californicum (Yerba Santa) and invasive grasses in
Mar-18, however, the species were just starting to regenerate and were not nearly 0.3 meters in height (Figure 18). It took an additional month (April-18), nearly seven months after the fire, for any of the plant species to reach a height of 0.3 meters, with four species being recorded (Artemisia californica, Brassica nigra, Cardus pycnocephalus, and
Eriodictyon californicum). By Jun-18, only Brassica nigra and Eriodictyon californicum were recorded in the site.
62
Limitations and criticisms of experimental design
Understandably, there are certain variables related to sites that I could not account for in the field, such as elevation, wind, wildfires, surrounding habitats, wildlife, trespassers, etc. In May-18, there were gloomy morning skies that would last until noon, which could explain why there were low bee richness and abundance per trap for the CH sites (Heard and Hendrikz, 1993; Burrill and Dietz, 1981; Stone et al., 1995). As mentioned earlier, the wildfire at Green River may have caused the decrease in bee abundance, and possibly, the diversity in sampling periods following the fire (Figure 10;
Appendix D).
In this study, one possible criticism is that not enough sampling effort was applied per site. In collecting data for only seven sampling periods one day of actual trapping per period- snapshot in a one-year span, for each site, my data only displays the temporal differences between sites for that particular time period. Due to an unexpected wildfire in late summer/early fall (Sep-17) and gloomy morning skies in mid-spring (Apr/May-18) during the one year of data collection, it is unlikely that the temporal patterns in bee assemblages for a particular site will be identical to the patterns in following years.
Continued research may allow us to furthermore understand the temporal patterns in bee assemblages in inland CSS fragments in relation to plant assemblages and wildfires.
Another possible criticism would be the inefficiency of sampling the bee community via pan traps. Although pan traps are one of the most efficient, passive bee traps, it is unlikely that all bee species were collected for each sampling period and site, as pan traps may be species selective (Campbell and Hanula, 2007; Bates et al. 2011;
Sircom et al., 2018; Vrdoljak and Samways, 2012) or inefficiently sample bee richness
63 when there are abundant floral resources (Cane et al., 2000; Mayer, 2005; Roulston et al.,
2007; Wilson et al., 2008). One study found that the number of pan traps influences the adequacy of bee community sampling. Shapiro et al. (2014) found that 30-bowl (pan trap) transects would be the optimal trap number (out of 75% sampling events) for sampling bee fauna in a site; 45-bowl transects, however, would have adequately sampled the bee fauna in 100% of sampling events. It is possible, that by using 16 pan traps for each site, that I may have under sampled each site. By increasing the number of pan traps to 30, or even 45, inland CSS bee fauna may be more adequately sampled in future samplings. To help alleviate the possibility of species selectivity by pan traps, I netted bees in each site after every sampling period. All bee species netted were also collected in traps, except for one Osmia morphospecies (Appendix A).
Contribution to future CSS conservation efforts
Conservation of CSS ecosystems is imperative, as CSS has declined over 85% since 1977 (Kuchler, 1977; Westman, 1981; Rubinoff, 2001). Many native species depend on the CSS, including endangered species, like the California gnatcatcher, the cactus wren, the El Segundo blue butterfly and the Palos Verdes blue butterfly. This study is the first to systematically document bee assemblage patterns in the Pomona-
Chino inland CSS, and the first to document strong temporal effects on bee abundance and diversity. Data from this study could assist in CSS post-fire recovery efforts by providing data of bee fauna and plant species regeneration immediately following a wildfire. My data documenting the seasonal patterns in bee fauna and plant species assemblages (pre and post-fire) could also benefit research regarding the response of CSS to climate change, as it has been determined that climate change accentuates fire
64 intensities and adversely affects CSS through plant species loss (Malanson and Westman,
1991). Not only will CSS benefit from these conservation efforts, but agricultural landscapes near the CSS may benefit as well. While it has recently been suggested that natural habitats support many bee species that pollinate our crops (Klein et al., 2006;
Leong et al, unpublished), by conserving the CSS habitat, agricultural landscapes near the
CSS may benefit from the CSS bee fauna. Peponapis pruinosa (squash bee), for example, is an important pollinator of cucurbits in agricultural landscapes. It is more than probable, that bees, like Peponapis pruinosa, may be utilizing CSS habitat resources while also contributing to our crop productions.
Since habitat loss threatens bee diversity (Brown and Paxton, 2009), conservation measures of CSS bee fauna should start with the conservation of CSS habitat. This could be done via planting and seeding CSS shrubs to existing CSS habitat regions and continuing the protection of CSS reserves. While abiotic factors, such as climate change and wildfires, are out of our control, conservation and regeneration of CSS could also be promoted by the active removal of invasive plant species from CSS regions, like Brassica nigra (black sage), as it is suggested that invasive plant species could be outcompeting and limiting the success of native plant species (Dangremond et al., 2010). Furthermore, to conserve the native CSS bee assemblages, the use of pesticides should be prohibited within CSS regions because of their negative impact on bee population numbers
(Goulson et al., 2015).
65
CONCLUSION
In this study, I examined and compared the temporal bee diversity and abundance between two inland CSS hill regions, SJH and CH, in southern California. I hypothesized there would be greater bee diversity and abundance in CH, due to its large natural area, and spring would have greater bee diversity and abundance due to climatic temperatures and flowering phenology. In the two inland CSS hill regions, my results indicate: (1) seasons account for more of the variation in inland CSS bee communities than sites within hills and hill regions, that (2) bee abundance varies temporally and geographically within CSS hill regions, and that (3) bee diversity (richness, community composition) varies temporally and geographically within and between CSS hill regions. The most abundant bee species collected, exceeding 100 in individuals, included Lasioglossum
(Dialictus) species, Ceratina arizonensis, Halictus tripartitus, Apis mellifera,
Agapostemon texanus, Melissodes sp. 5, and Lasioglossum (Evylaeus) species (Appendix
B). My results support my hypotheses in that CH harbored a higher bee richness than
SJH, and late spring/early summer had a higher bee richness and diversity; however, summer yielded a greater abundance of bees.
My results demonstrate that inland CSS hill regions, even those within several kilometers of each other, differ in their bee communities, and that seasonal change is the driving factor that structures the inland CSS bee fauna. Due to the strong effect of seasons on the CSS bee community, the conditions associated with seasons, such as seasonal changes in temperature and phenology of flowering plant species, could potentially be driving the seasonal patterns in the bee assemblages within the CSS hill regions. These results, coming from the first study to document bee assemblages in
66 inland CSS, will help promote and initiate CSS conservation measures by making an electronic database of the presence and abundance of bee species in inland CSS available to the public or allowing researchers access to the data for future comparisons. CSS conservation could potentially benefit agricultural production by providing additional resources for many bee species that pollinate our crops. In addition, results from this study could assist in CSS post-fire recovery efforts by providing immediate post-fire documentation of bee fauna and plant species regeneration. My data documenting the seasonal patterns in bee fauna and plant species assemblages could also benefit research regarding the response of CSS to climate change.
67
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APPENDIX A
Bees netted per site and date. For dates not listed in the table, no bees were netted due to low bee flight activity or lack of bee presence. Host plants denote the plant species that the bees were netted on.
Bees Genus Species Sex Site Date Host Plant Netted Apis mellifera F Voorhis 6/14/2017 9 Eriogonum fasciculatum Apis mellifera F Galster 6/14/2017 1 Salvia mellifera Apis mellifera F Galster 6/14/2017 7 Brassica nigra Apis mellifera F Bonelli 6/14/2017 27 Eriogonum fasciculatum Apis mellifera F Green River 6/28/2017 1 Eriogonum fasciculatum Apis mellifera F Quarter 6/28/2017 42 Eriogonum fasciculatum Apis mellifera F Campsite 6/28/2017 54 Eriogonum fasciculatum Apis mellifera F Bonelli 7/30/2017 3 Eriogonum fasciculatum Ceratina acantha F Galster 7/30/2017 1 N/A: IN AIR Apis mellifera F Quarter 8/13/2017 2 Eriogonum fasciculatum Apis mellifera F Campsite 8/13/2017 1 Eriogonum fasciculatum Melissodes #13F F Campsite 8/13/2017 1 Trichostema lanceolatum Anthophora urbana F Campsite 8/13/2017 1 Trichostema lanceolatum Apis mellifera F Green River 8/13/2017 5 Eriogonum fasciculatum Apis mellifera F Voorhis 9/17/2017 4 Eriogonum fasciculatum Lasioglossum (Dialictus) sp. F Green River 9/24/2017 1 Eriogonum fasciculatum Apis mellifera F Quarter 9/24/2017 1 Eriogonum fasciculatum Apis mellifera F Voorhis 11/12/2017 1 Stephanomeria virgata Apis mellifera F Galster 11/12/2017 2 N/A: IN AIR Apis mellifera F Galster 3/12/2018 1 Ribes aureum Apis mellifera F Voorhis 3/12/2018 3 Brassica nigra Apis mellifera F Galster 4/29/2018 1 Salvia mellifera Apis mellifera F Voorhis 4/29/2018 1 Eriogonum fasciculatum Apis mellifera F Bonelli 4/29/2018 1 Brassica nigra Bombus californicus F Bonelli 4/29/2018 1 Raphanus raphanistrum Apis mellifera F Quarter 5/13/2018 1 Eriogonum fasciculatum Osmia #6M M Quarter 5/13/2018 1 N/A: IN AIR Apis mellifera F Green River 5/14/2018 2 Carduus pycnocephalus Apis mellifera F Bonelli 6/16/2018 2 Eriogonum fasciculatum Apis mellifera F Bonelli 6/16/2018 1 Brassica nigra Apis mellifera F Voorhis 6/16/2018 5 Eriogonum fasciculatum Apis mellifera F Galster 6/16/2018 1 Marrubium vulgare Apis mellifera F Quarter 6/24/2018 3 Eriogonum fasciculatum Apis mellifera F Campsite 6/24/2018 3 Eriogonum fasciculatum
73
APPENDIX B
Bee species (female specimens, including males from Anthophorula, Chelostoma, Hoplitis and Stelis) collected during this study, with abundances per hill region. Sampling sites are denoted by numbers: 1=Jun-17, 2=Jul/Aug-17, 3=Sep-17, 4=Nov-17, 5=Mar-18, 6=Apr/May-18, 7=Jun-18
# in # in Sampling Family Genus Species SJH CH Periods Andrenidae Andrena sp. 1 1 0 5 sp. 2 1 6 5,6 sp. 3 0 1 5 sp. 4 0 31 5 sp. 5 0 2 5 Calliopsis rhodophila 2 6 1,2 Panurginus sp. 1 1 0 6 sp. 2 0 3 5 Apidae Anthophora urbana 2 1 2,3 sp. 1 0 4 5 Anthophorula sp. 1 0 1 1 sp. 2 0 1 1 sp. 3 0 1 1 Apis mellifera 63 82 ALL Bombus californicus 1 3 1,4, crotchii 0 1 1 vosnesenskii 0 1 1 Ceratina acantha 17 10 1,2,3,4,5,6 arizonensis 602 203 ALL micheneri 2 0 7 nanula 3 1 1,3,5 neomexicana 1 0 6 tejonensis 1 0 2 Diadasia australus 6 3 1,6,7 bituberculata 9 1 1,6,7 diminuta 1 4 1 enavata 0 1 2 laticauda 4 9 1,2,6,7 lutzi 0 1 5 nitidifrons 0 5 1 ochracea 2 47 1,6,7 rinconis 3 2 1,7 Eucera sp. 1 2 1 5 sp. 2 12 11 5,6 sp. 3 2 9 5,6 sp. 4 3 0 6
74
Exomalopsis sp. 1 1 7 1 Melissodes sp. 1 5 9 1,2 sp. 2 12 11 1,7 sp. 3 1 8 1,2 sp. 4 6 27 1,2,3,7 sp. 5 84 37 1,6,7 sp. 6 9 4 1,2 sp. 7 2 0 1,7 sp. 8 0 8 1,2,3 sp. 9 0 1 6 Nomada sp. 1 0 6 5 Peponapis pruinosa 6 3 1,2,7 Townsendiella sp. 1 1 0 6 Xenoglossa strenua 1 2 1,3,7 Xylocopa californica 3 1 2,5 Colletidae Hylaeus mesillae 1 2 5,7 rudbeckiae 5 4 1,2,3,4,5,7 sp. 1 1 0 1 Halictidae Agapostemon texanus 15 108 ALL Augochlorella pomoniella 19 17 1,2,3,4,5,7 Conanthalictus sp. 1 2 1 5 Dufourea sp. 1 4 0 6 Halictus farinosus 1 3 1,5 ligatus 0 4 1,2,3 tripartitus 179 175 1,2,3,5,6,7 Lasioglossum (Dialictus) species 288 585 ALL (Evylaeus) species 20 82 1,4,5,6,7 (Lasioglossum) species 7 3 1,6,7 (Lasioglossum) sisymbrii 1 0 5 Megachilidae Anthidium clypeodentatum 1 0 6 utahense 1 0 5 Ashmeadiella cockerelli 0 1 2 Atoposmia sp. 1 1 0 7 Chelostoma sp. 1 1 0 5 sp. 2 1 0 5 Hoplitis sp. 1 2 0 5 sp. 2 0 7 5 sp. 3 0 1 5 Megachile brevis 2 4 2,3,6 sp. 1 0 3 1 sp. 2 0 1 5 Osmia sp. 1 0 2 5 sp. 2 0 2 5 Stelis sp. 1 0 1 5
75
APPENDIX C
Bonelli Park Galster Park Voorhis Reserve 2.3% 4.7% 1 0% 11.2% 4.1% . 20.9
25.6% 2.0%- 6.1% ...... ,.....,,,) 18.6% Jun-17 5.1%/
3.5%
Jul/Aug-17
31.3% 33.3% Sep-17 Sep-17
Nov-17
11.8 % 55.9% .5%
Mar-18 9% 1.5% 2.9% 2.9% %
14.3% 4.2% !:2% 4.2% 16.7 4.2% ·..- 4.8% 16.7 7.8% 8.3% ,,,,. % % 2.8% 14.3% 4.8% 16.7~ 58.3 -...... Apr/May-18 % \_5.6% %
0 9.7% 3.9% _ _ --::::,--\ii---- 0.9% 7.8% 3.2% 4. 7% 17.8 3.2% 0.9% % 19.4% 32.3% 2.6% Jun-18 61.2 % ■ Agapostemon ■ Anthidium Anthophora ■ Ap i s ■ Augochlorella ■ Bombus ■ Calliopsis ■ Ceratina Conanthalictus Diadasia ■ Halictus Hylaeus ■ Megachile ■ Melissodes ■ Peponapis ■ Xenoglossa ■ Exomalopsis ■ Lasioglossum ■ Dufourea ■ Panurginus ■ Townsendiella ■ Xylocopa ■ Eucera Hoplitis Osmia Andrena ■ Chelostoma ■ Atoposmia
Bee genera (%) trapped per site and sampling period for SJH.
76
APPENDIX D
Campsite Green River Quarter Horse
12.2% 2 1% 7.5%6.2%0.7% 3 1 6.8% 1.0% . - ~ - % 0.7% 1.4% 36.5% 19.5% 1.7% 0.7% 30.1%
Jun-17 2.7~ ~
1.;~ 2HJ'/o '---14.7%
18.7 8.7% 3.3% 0.7% 17.2% 1.6% 1.3% / 2.7%
1.36%0% 0.7% 51.6% 0.7%
Jul/Aug-17 Jul/Aug-17 5.3% 50.7%
14.3%
Sep-17 Sep-17 62.4%
16.7%
Nov-17 Nov-17
1.6% ---..;;2;,.:;:.2%...:..- 0.3% 0.3% 10.7% 3.6% 1.1% __--:: 1;..:;:·1....:.%11;~1.1%8.0% 0.6% 17.4% 31.0% ,.-=-=--4.6% 0.9% 0.6% r,.- \ 3.4% 0.3% Mar-18 19.5% 23.0% 2.3%------\..3.4%
11.1%
51.9% 5.6%
Apr/May-18 3.4%
4.9% 9.8%
40.0% 1.6% 16.4% 57.6% Jun-18 Jun-18 5.7%
■ Agapostemon Anthophora ■ Anthophorula ■ Apis ■ Ashmeadiella ■ Augochlorella ■ Bombus ■ Calliopsis ■ Ceratina Conanthalictus Diadasia ■ Halictus Hylaeus ■ Megachile ■ Melissodes ■ Panurginus ■ Peponapis ■ Xenoglossa ■ Xylocopa Exomalopsis ■ Eucera ■ Stelis Hoplitis Osmia Andrena Nomada ■ Lasioglossum
Bee genera (%) trapped per site and sampling period for CH.
77
APPENDIX E
Bonelli Park mean flowering species per transect by date. Standard deviation and standard error of the mean included. Inflorescences per flowering individual varied by date and plant species. On dates not listed in the Table, the site lacked presence of flowering individuals (i.e. Nov-17).
Mean Per Inflorescences Date Species SD SEM Transect Per Individual Brassica nigra 4 4.04145 2.33333 3-100 Eriogonum 7.33333 3.60555 2.08166 50-3000 6/13/2017 fasciculatum Raphanus 1.33333 2.30940 1.33333 2-17 raphanistrum Brassica nigra 1.66667 0.57735 0.33333 9-70 7/29/2017 Eriogonum 0.66666 1.15470 0.66667 50-200 fasciculatum 9/16/2017 Brassica nigra 1.33333 1.52753 0.88192 4-19 Dichelostemma 3/11/2018 0.33333 0.57735 0.33333 10 capitatum Brassica nigra 5.66667 8.73689 5.04425 7-20 Eriogonum 1 1.15470 0.66667 20-200 fasciculatum 4/28/2018 Bloomeria crocea 0.66667 1.15470 0.66667 2-5 Raphanus 0.66667 1.73205 1 10-40 raphanistrum Brassica nigra 0.66667 1.73205 1 20-50 Eriogonum 7.33333 4.72581 2.72845 100-5000 6/15/2018 fasciculatum Pseudognaphalium 0.33333 0.57735 0.33333 20 californicum
78
APPENDIX F
Galster Park mean flowering species per transect by date with range of inflorescences per individual. Standard deviation and standard error of the mean included. On dates not listed in the Table, the site lacked presence of flowering individuals (i.e. Nov-17).
Mean Per Inflorescences Date Species SD SEM Transect Per Individual Brassica nigra 3.66667 0.57735 0.33333 50-500 6/13/2017 Salvia mellifera 5.33333 5.50757 3.17979 3-70 Brassica nigra 3.33333 0.57735 0.33333 20-200 7/29/2017 Salvia mellifera 6.66667 4.16333 2.40370 3-70 Marrubium vulgare 0.33333 0.57735 0.33333 18 9/16/2017 Brassica nigra 0.33333 0.57735 0.33333 30 Salvia mellifera 0.33333 0.57735 0.33333 12 Pseudognaphalium 0.33333 0.57735 0.33333 1 californicum 3/11/2018 Ribes aureum 0.33333 0.57735 0.33333 10 Solanum douglasii 0.33333 0.57735 0.33333 50 Marah macrocarpa 0.66667 0.57735 0.33333 10-60 Brassica nigra 1.33333 0.57735 0.33333 20-50 4/28/2018 Salvia mellifera 1 0 0 100 Marrubium vulgare 1 1 0.57735 30-200 Brassica nigra 0.33333 0.57735 0.33333 30 Salvia mellifera 1.66667 0.57735 0.33333 3-25 6/15/2018 Pseudognaphalium 0.33333 0.57735 0.33333 20 californicum Marrubium vulgare 2 0 0 10-100
79
APPENDIX G
Voorhis Ecological Reserve mean flowering species per transect by date with range of inflorescences per individual. Standard deviation and standard error of the mean included. On dates not listed in the Table, the site lacked presence of flowering individuals (i.e. Nov-17).
Mean Per Inflorescences Date Species SD SEM Transect Per Individual Brassica nigra 2.66667 1.52753 0.88192 8-50 Eriogonum 1.33333 1.15470 0.66667 300-500 fasciculatum 6/13/2017 Carduus 3.66667 0.57735 0.33333 1-10 pycnocephalus Nicotiana glauca 0.33333 0.57735 0.33333 50 Brassica nigra 2.66667 1.15470 0.66667 8-20 7/29/2017 Nicotiana glauca 0.33333 0.57735 0.33333 50 Brassica nigra 2 2.64575 1.52753 1 9/16/2017 Nicotiana glauca 0.33333 0.57735 0.33333 50 Brassica nigra 1.66667 1.52753 0.88191 4-40 Dichelostemma 3/11/2018 0.33333 0.57735 0.33333 8 capitatum Nicotiana glauca 0.33333 0.57735 0.33333 150 Brassica nigra 5.33333 2.51661 1.45297 10-100 Pseudognaphalium 4.33333 5.13160 2.96273 17-33 californicum 4/28/2018 Eriophyllum 0.33333 0.57735 0.33333 100 confertiflorum Nicotiana glauca 0.33333 0.57735 0.33333 50 Brassica nigra 4 1.73205 1 5-100 Eriogonum 1.33333 0.57735 0.33333 1000-2000 fasciculatum Pseudognaphalium 6/15/2018 1.66667 0.57735 0.33333 8-150 californicum Carduus 2.66667 0.57735 0.33333 3-8 pycnocephalus Nicotiana glauca 0.33333 0.57735 0.33333 50
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APPENDIX H
Campsite mean flowering species per transect by date with range of inflorescences per individual. Standard deviation and standard error of the mean included. On dates not listed in the Table, the site lacked presence of flowering individuals (i.e. Nov. 2017).
Mean Per Inflorescences Date Species SD SEM Transect Per Individual Eriogonum fasciculatum 8.66667 1.52753 0.88192 20-3000 6/27/2017 Encelia californica 0.33333 0.57735 0.33333 1 Trichostema lanceolatum 0.66667 1.15470 0.66667 15-50 Eriogonum fasciculatum 6.33333 1.52753 0.88192 20-1000 8/12/2017 Ericameria pinifolia 0.66667 0.57735 0.33333 20-100 Trichostema lanceolatum 0.66667 1.15470 0.66667 10-30 9/23/2017 Ericameria pinifolia 1.33333 1.15470 0.66667 10-200 Eriogonum fasciculatum 1 1 0.57735 10-50 3/25/2018 Encelia californica 1.33333 1.52753 0.88192 1-4 5/13/2018 Eriogonum fasciculatum 1 0 0 200 6/23/2018 Eriogonum fasciculatum 2.33333 0.57735 0.33333 20-1000
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APPENDIX I
Green River mean flowering species per transect by date with range of inflorescences per individual. Standard deviation and standard error of the mean included. On dates not listed in the Table, the site lacked presence of flowering individuals (i.e. Nov. 2017).
Mean Per Inflorescences Date Species SD SEM Transect Per Individual Brassica nigra 1.33333 1.52753 0.88192 30-80 6/27/2017 Eriogonum fasciculatum 4 2.64575 1.52753 200-10000 8/12/2017 Eriogonum fasciculatum 3.33333 2.08167 1.20185 150-3000 9/23/2017 Brassica nigra 0.33333 1 0.57735 3 3/25/2018 Brassica nigra 0.33333 1 0.57735 15 Brassica nigra 1.33333 1.15470 0.66667 5-50 5/13/2018 Erodium cicutarium 0.33333 1 0.57735 1 Carduus pycnocephalus 2.33333 0.57735 0.33333 1-9 Acmispon glaber 1 1.73205 1 7-40 Brassica nigra 1 0 0 4-10 6/23/2018 Carduus pycnocephalus 0.33333 1 0.57735 5 Malacothamnus 0.33333 1 0.57735 2 fasciculatus Calystegia macrostegia 0.33333 1 0.57735 1
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APPENDIX J
Quarter Horse mean flowering species per transect by date with range of inflorescences per individual. Standard deviation and standard error of the mean included.
Mean Per Inflorescences Date Species SD SEM Transect Per Individual Eriogonum fasciculatum 4.66667 1.15470 0.66667 20-10000 6/27/2017 Encelia californica 0.66667 0.57735 0.33333 1-2 Isocoma menziesii 0.33333 1 0.57735 10 Eriogonum fasciculatum 5.33333 1.15470 0.66667 40-3000 8/12/2017 Isocoma menziesii 2 1 0.57735 2-20 Eriogonum fasciculatum 0.33333 1 0.57735 2000 9/23/2017 Isocoma menziesii 1.66667 1.15470 0.66667 3-100 Brassica nigra 0.66667 1.15470 0.66667 4-10 11/18/2017 Baccharis pilularis 0.33333 1 0.57735 2000 Isocoma menziesii 0.66667 1.15470 0.66667 2-5 Eriogonum fasciculatum 0.33333 1 0.57735 50 3/25/2018 Isocoma menziesii 0.33333 1 0.57735 10 Salvia mellifera 0.66667 0.57735 0.33333 2-5 Eriogonum fasciculatum 1.33333 0.57735 0.33333 50-1000 5/12/2018 Encelia californica 1 0 0 1 Brassica nigra 0.33333 0.57735 0.33333 5 Isocoma menziesii 0.66667 1.15470 0.66667 4-10 Salvia mellifera 0.33333 1 0.57735 1 6/23/2018 Eriogonum fasciculatum 5 1 0.57735 20-5000 Isocoma menziesii 1.66667 1.15470 0.66667 2-13
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