The Effects of Livestock Grazing and Habitat Type on Plant-Pollinator Communities of British Columbia’s Endangered Shrubsteppe by Sherri L. Elwell B.Sc. (Hons., Biology), University of Victoria, 2007 Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in the Department of Biological Sciences Faculty of Science Sherri L. Elwell 2012 SIMON FRASER UNIVERSITY Spring 2012 All rights reserved. However, in accordance with the Copyright Act of Canada, this work may be reproduced, without authorization, under the conditions for “Fair Dealing.” Therefore, limited reproduction of this work for the purposes of private study, research, criticism, review and news reporting is likely to be in accordance with the law, particularly if cited appropriately.
Transcript
The Effects of Livestock Grazing and Habitat Type on
Plant-Pollinator Communities of
British Columbia’s Endangered Shrubsteppe
by
Sherri L. Elwell
B.Sc. (Hons., Biology), University of Victoria, 2007
Thesis Submitted in Partial Fulfillment
of the Requirements for the Degree of
Master of Science
in the
Department of Biological Sciences
Faculty of Science
Sherri L. Elwell 2012
SIMON FRASER UNIVERSITY
Spring 2012
All rights reserved. However, in accordance with the Copyright Act of Canada, this work may be
reproduced, without authorization, under the conditions for “Fair Dealing.” Therefore, limited reproduction of this work for the purposes of private study, research, criticism, review and news reporting is likely to be in
accordance with the law, particularly if cited appropriately.
ii
Approval
Name: Sherri L. Elwell
Degree: Master of Science (Biological Sciences)
Title of Thesis: The effects of livestock grazing and habitat type on plant-pollinator communities of British Columbia’s endangered shrubsteppe
Examining Committee:
Chair: Bernard D. Roitberg, Professor
Elizabeth Elle Senior Supervisor Associate Professor
David J. Green Supervisor Associate Professor
Jonathan W. Moore Internal Examiner Assistant Professor
Date Defended/Approved: April 16, 2012
iii
Partial Copyright Licence
iv
Abstract
Understanding how anthropogenic disturbances affect plant-pollinator
communities is important for their conservation. I investigated how plant-pollinator
communities of British Columbia’s endangered shrubsteppe are affected by spring
livestock grazing. I surveyed vegetation structure and abundance and diversity of
flowering plants and pollinators in four paired grazed/ungrazed sites. Grazing increased
percent cover of shrubs and bare soil and decreased grass and forb height. However,
flowering plant and pollinator abundance, richness and community composition were
unaffected by grazing. Instead, floral and pollinator community composition differed
between antelope-brush and big sagebrush habitats. I also compared plant-pollinator
interaction network structure between habitats, and found that generalization was
greater in big sagebrush than the more endangered antelope-brush habitat. Late-
flowering-season networks were more asymmetric and had greater plant generalization.
These results suggest differences in network resilience to disturbance between habitats
and across the flowering season, and so could be used to inform conservation planning
in the region.
Keywords: Biodiversity; pollinator; livestock grazing; community composition; interaction network; shrubsteppe
v
Acknowledgements
I owe my deepest gratitude to my supervisor, Elizabeth Elle, for her mentorship, support,
and encouragement throughout all aspects of my degree. I am also thankful to her for
igniting in me what I know will be a lifelong love of bees. I extend a special thank you to
David Green for his advice and insight into my research and to Jonathan Moore for his
role as public examiner.
This research would not have been possible without the assistance of many wonderful
people, to whom I am grateful. I thank Jane Pendray and Taylor Holland for their
friendship and wonderful assistance in the field. I also extend my sincere thank you to
those who helped me with pollinator identification: Elizabeth Elle, Lisa Neame, Terry
Griswold and associates at the USDA Bee Biology and Systematics Lab, Jason Gibbs
from Cornell University, and Cory Sheffield from York University. Additionally, I thank
The Nature Trust of B.C., B.C. Parks, B.C. Ministry of Forest and Range, Canadian
Wildlife Service, and Wade Clifton of the Clifton Ranch for allowing me to conduct my
research on their properties. I am also thankful to Anne Skinner, from the B.C. Ministry
of Forest and Range, for her help with grazing regime information.
I was truly fortunate to have shared my time in the Elle lab with some amazing labmates.
I thank Grahame Gielens, Lisa Neame, Lindsey Button and Julie Wray for being
wonderful colleagues and friends and for providing me with plenty of laughs, support and
encouragement.
Finally, I wish to extend a heartfelt thank you to my family and Jordy Thomson for their
loving support throughout this degree. In particular, I thank my parents, Kathy and Tom
Elwell, for showing me the meaning of dedication to both family and profession, and for
their friendship, love and unwavering support of my educational goals.
vi
Table of Contents
Approval .......................................................................................................................... ii Partial Copyright Licence ............................................................................................... iii Abstract .......................................................................................................................... iv Acknowledgements ......................................................................................................... v Table of Contents ........................................................................................................... vi List of Tables ................................................................................................................. viii List of Figures................................................................................................................. ix
Chapter 1 General introduction .............................................................................. 1 References ...................................................................................................................... 5
Chapter 2 Shrubsteppe plant and pollinator communities influenced more by habitat type than by livestock grazing ................................... 8
Study area ............................................................................................................ 11 Study sites ............................................................................................................ 11 Vegetation ............................................................................................................ 12
Discussion ..................................................................................................................... 21 The effects of livestock grazing ............................................................................ 21
Habitat and temporal influences on network structure .......................................... 58 Network size and generalization .................................................................. 58 Asymmetry ................................................................................................... 60 Nestedness .................................................................................................. 61
Caveats to the current network approach ............................................................. 62 Practical implications ............................................................................................ 63 Conclusions and future directions ......................................................................... 64
Chapter 4 General conclusions ............................................................................ 78 The effects of livestock grazing and habitat type on flowering plants and
pollinators ............................................................................................................. 78 The plant-pollinator network structure of British Columbia’s endangered
Appendices .................................................................................................................. 88 Appendix A Floral unit designations ........................................................................ 89 Appendix B Species degree and asymmetry ........................................................... 92 Appendix C Most abundant pollinators and floral resources .................................. 104 Appendix D Formulas for network structural properties ......................................... 105 Appendix E Network structural property values ..................................................... 109
viii
List of Tables
Table 2.1. Site characteristics of focal shrubsteppe sites in the Southern Okanagan Valley, British Columbia. The first two letters of the site abbreviation designate a grazed and ungrazed pair. AUM refers to Animal Unit Month, where 1 AUM is equivalent to the forage removed by one 454 kg cow grazing for one month (Gayton 2003), and 1 AUM/ha is considered sufficient to maintain dry bunchgrass habitat in good range condition (McLean and Marchland 1968). ................................. 34
Table 2.2. Summary of the total abundance, richness and diversity of pollinator-attractive flowering plants and flower visitors (hereafter pollinators) for eight shrubsteppe study sites in the southern Okanagan, British Columbia. .................................................................................................... 35
Table 2.3. The effects of livestock grazing and sample episode on the abundance, richness and diversity of all pollinators, and on pollinator functional groups defined by nesting location or taxonomic (and so resource-based) affiliations. GLMMs were used to investigate grazing impacts on pollinator abundance and actual species richness, while mixed models were used to investigate impacts on pollinator diversity. Simpson’s index of diversity was arcsine square-root transformed for analysis. ...................................................................................................... 36
Table 3.1. Plant-pollinator interaction network property definitions with brief explanations of their influence on network resilience. .................................. 72
Table 3.2. Characteristics of focal shrubsteppe sites in the southern Okanagan Valley, British Columbia. “U” in the site abbreviation denotes ungrazed and “G” denotes grazed. For more information see Table 2.1. .............................................................................................................. 73
Table 3.3. The effects of habitat type and period of the flowering season (early, mid, late) on plant-pollinator interaction network structural properties. The effects of habitat on network structure were also generated using full season networks. Bolded values = P < 0.10, * = P < 0.05. .................... 74
Table 3.4. The identity if the top-10 most functionally important plants and pollinators in antelope-brush and big sagebrush shrubsteppe. Species presented have the highest combined degree and asymmetry. .................................................................................................. 75
ix
List of Figures
Figure 2.1. Map of study area in the Southern Okanagan Valley, B.C. The four paired sample sites (grazed and ungrazed) are denoted by different coloured symbols. The WL and SO pairs are located in big sagebrush shrubsteppe, while the OK and HL pairs are in antelope-brush shrubsteppe. ...................................................................................... 37
Figure 2.2. Sample-based rarefaction curves, rescaled to individuals, for pollinator species richness in all eight sample sites, paired on the basis of similar environmental characteristics except for the presence of grazing livestock. ..................................................................................... 38
Figure 2.3. The number of individuals caught in pan-trap surveys for all grazed and ungrazed sites. The number above each bar represents the taxonomically distinguished groups: species for bees [mining bees (Andrenidae); honeybee (Apis mellifera); bumblebees, digger bees, small carpenter bees (Apidae); plasterer bees (Colletidae); sweat bees (Halictidae); mason bees and leaf cutter bees (Megachilidae)], Syrphid flies and Bombyliid flies; morphospecies for beetles, butterflies, moths and wasps. ...................................................................... 39
Figure 2.4. The effects of livestock grazing on the percent cover of vegetation and ground layers and maximum height of grasses and forbs. Note the different scale for percent cover and height variables. Significant effects are indicated by an asterisk: P < 0.01. .............................................. 40
Figure 2.5. Least square means of the natural logarithm of flowering plant abundance and richness between grazed and ungrazed sites, over eight sampling episodes. Floral richness is based on Chao2 richness estimates. Flowering plants were surveyed every two weeks from late March until late July. .................................................................................... 41
Figure 2.6. Least square means of the natural logarithm of flowering plant abundance and richness between antelope-brush and big sagebrush sites, over eight sampling episodes. Floral richness is based on Chao2 richness estimates. Flowering plants were surveyed every two weeks from late March until late July. .......................................................... 42
Figure 2.7. Least square means of the natural logarithm of total pollinator abundance and richness between grazed and ungrazed sites, over eight sampling episodes. Pollinators were sampled every two weeks from late March until late July. ..................................................................... 43
Figure 2.8. Least square means of the natural logarithm of total pollinator abundance and richness between antelope-brush and big sagebrush sites, over eight sampling episodes. Pollinators were surveyed every two weeks from late March until late July. .................................................... 44
x
Figure 2.9. NMDS of sites in flowering plant species space, over eight sampling episodes. The site management regime (grazed vs. ungrazed) is coded with open and filled symbols, shrubsteppe type is coded by symbol shape and sampling date is coded by colour. The axes are labelled with the traits of floral species that are significantly correlated with the NMDS output. ................................................................................. 45
Figure 2.10. NMDS of sites in pollinator species space, over eight sampling episodes. The site management regime (grazed vs. ungrazed) is coded with open and filled symbols, shrubsteppe type is coded by symbol shape and the sampling date is coded by colour. Pollinators associated with axes were significantly correlated with the NMDS output. ......................................................................................................... 46
Figure 3.1. Quantitative plant-pollinator interaction networks from antelope-brush and big sagebrush habitats: a/e) Full season networks; b/f) Early season networks; c/g) Middle season networks; and d/h) Late season networks. In each network, rectangles represent pollinator (top row) or plant (bottom row) species, and the lines connecting them represent interactions. The width of each plant rectangle represents how frequently the plant was visited by pollinators, and the width of each pollinator rectangle indicates how frequently a pollinator was collected off of flowering plants. The width of the interaction represents how frequently that interaction was recorded. Pollinators are colour-coded as follows: red = bees (Hymenoptera); green = wasps (Hymenoptera); blue = flies (Diptera); purple = beetles (Coleoptera); yellow = butterflies (Lepidoptera); orange = hummingbird (Trochilidae). Plants in the seasonal sub-networks are colour-coded as follows: light grey = blooming in early and mid season; dark grey = blooming in mid and late season; black = blooming during a single season. Species blooming through two seasons are arranged in the same order to allow comparison. Networks are meant to give an impression of how network interaction change through time, and are not all drawn to the same scale. ................... 76
Figure 3.2. Changes in plant-pollinator network structural properties across early, mid. and late flowering seasons, including full season values, in antelope-brush and big sagebrush shrubsteppe: a) network size, b) number of plant and pollinator species, c) H2’ specialization index, d) plant and pollinator generality, e) interaction strength asymmetry, f) NODF nestedness. The solid lines connect the least square mean values of each metric across the flowering season for both shrubsteppe types. ...................................................................................... 77
1
Chapter 1 General introduction
Pollinators are an important component of global biodiversity, playing a vital role
in maintaining natural ecosystems and agricultural productivity (Kearns et al. 1998; Potts
et al. 2010). It is estimated that 87.5% of the world’s flowering plant species, require
animal pollinators, primarily insects, for sexual reproduction (Ollerton et al. 2011). Thus
in natural ecosystems, pollinator declines could lead to a decrease in pollination service
to pollinator-dependent plants which in turn could result in plant population declines
(Kearns and Inouye 1997). Such parallel declines, between pollinators and pollinator-
dependent plants, have already been reported in the Netherlands and United Kingdom
(Biesmeijer et al. 2006). The pollinator declines now reported in many regions of the
world are thus raising concern over the health of pollinator populations and the
preservation of their functional roles (Kearns et al. 1998; Potts et al. 2010). These
reports have emphasized the need to understand how anthropogenic disturbances affect
pollinator populations and highlight the importance of their consideration in conservation
planning and protection efforts.
Anthropogenic disturbances play a major role in influencing biodiversity patterns
worldwide (Dornelas et al. 2011). At present, habitat loss, which is the most commonly
studied anthropogenic threat to pollinators, appears to be the most important factor
influencing pollinator populations (Winfree et al. 2009; Potts et al. 2010). Habitat altering
disturbances, such as fire, logging and livestock grazing, on the other hand, were found
not to have an overall significant effect on pollinator communities in a meta-analysis by
Winfree et al. (2009), but studies assessing the effects of these disturbances on
pollinators are still few. It is apparent in the current literature that the response of
pollinator communities to anthropogenic disturbance is quite variable (e.g., Erhardt 1985;
Cane et al. 2006; Vulliamy et al. 2006; Winfree et al. 2007), emphasizing that additional
2
studies are needed to gain a better understanding of how various disturbances affect
pollinator communities (Potts et al. 2010; Winfree 2010).
Livestock grazing is one of the most prevalent grassland and shrubsteppe
disturbances (Fleischner 1994). Grazing has been shown to directly influence
vegetation structure and community composition, soil compactness and nutrient cycling,
while indirectly affecting populations of mammals, birds and amphibians (Fleischner
1994; Jones 2000). Although pollinators make a substantial contribution to grassland
biodiversity and are important for grassland functioning (Wilson 1987; Gilgert and
Vaughan 2011), they have been given less attention in grazing impact studies (Debano
2006; Yoshihara et al. 2008). Furthermore, the studies that have been conducted report
a range of pollinator responses to grazing, both positive (Carvell 2002; Vulliamy et al.
2006) and negative (Soderstrom et al. 2001; Debano 2006; Hatfield and LeBuhn 2007;
Xie et al. 2008). One commonality found among previous studies is that pollinator
communities tend to respond in concert with plant communities, because of their need
for floral resources for food and nest provision. The majority of studies assessing the
impacts of grazing on pollinator populations come from Europe, with only a few studies
previously conducted in North American grasslands, most of which focus exclusively on
bees (Sugden 1985; Debano 2006; Hatfield and LeBuhn 2007; Kearns and Oliveras
2009; Kimoto 2010). Continuing to develop an understanding of how all pollinating
insects and the flowering plants they interact with respond to grazing pressure will be
important for their conservation, particularly as grasslands are among North America’s
most threatened ecosystems (Curtin and Western 2008; Peart 2008).
Long term data sets on pollinator populations, particularly solitary native bees
and pollinating flies, are fragmentary at best (Potts et al. 2010; Winfree 2010). Most
studies to date have relied on making inferences about pollinator communities by
comparing pollinator richness, abundance and diversity along gradients of disturbance
as a surrogate for change over time (e.g., Kruess and Tscharntke 2002; Cane et al.
2006; Vulliamy et al. 2006; Winfree et al. 2007). Furthermore, it has been argued that
quantifying species composition, in addition to diversity, is important for understanding
disturbance impacts on pollinators. Studies have shown that even when overall bee
abundance and species richness are not negatively affected by disturbance; there can
be significant changes in species composition (Cane et al. 2006; Winfree et al. 2007;
3
Brosi et al. 2008). Thus, multivariate analyses are important statistical tools for
determining community-level disturbances, such as livestock grazing. Additionally, over
the last decade the study of plant-pollinator interaction networks, a community-based
analytical approach, has provided another means of quantifying the structural and
functional dynamics of communities (Bascompte and Jordano 2007; Bascompte 2009;
Vazquez et al. 2009). Plant-pollinator network analysis can identify which species
interact within a community and how those interactions collectively influence community
structure (Bascompte and Jordano 2007). It has been found that plant-pollinator
networks have particular network-level structural properties that have consequences for
community stability and resilience (Memmott et al. 2004; Bascompte and Jordano 2007).
Combining multivariate and network approaches when and where possible is likely to
provide a more comprehensive view of pollinator communities, with more power to
inform conservation planning and management.
Within Canada, the shrubsteppe habitats of the south Okanagan basin, British
Columbia, are recognized as some of the most biologically diverse as well as
endangered ecosystems in the country. Antelope-brush shrubsteppe in particular,
supports a disproportionately high percentage of Canada’s endangered and threatened
species and is considered in the top four most endangered ecosystems in the country
(Schlute et al. 1995; Dyer and Lea 2003). Over the last century the Okanagan basin has
lost 68% of its antelope-brush shrubsteppe and 33% of its big sagebrush shrubsteppe to
agricultural and urban development. Much of what remains is grazed by livestock (Lea
2008). The pollinator communities of these habitats are predicted to be very diverse (L.
Packer, bee taxonomist, York University, pers. comm.), but have not been extensively
inventoried and studies assessing the impacts of anthropogenic disturbances on
pollinator communities are lacking. These pollinators and the flowering plants with which
they interact are a vital component of shrubsteppe biodiversity, together providing
vegetation structure and forage for many of the other species that inhabit these
ecosystems (Gilgert and Vaughan 2011). Thus, understanding how plant and pollinator
communities are structured and how they are affected by disturbance will be important
for effective management and conservation.
In this thesis, I examine the influence of livestock grazing on plant and pollinator
communities in British Columbia’s Okanagan Valley and use network analysis to assess
4
the structural properties of plant-pollinator communities in antelope-brush and big
sagebrush habitats. In Chapter 2, I investigate the effects of livestock grazing on floral
and pollinator abundance, richness and community composition. I also assess the
impacts of grazing on habitat structure, as habitat features other than floral resources,
such as vegetation structure and bare soil availability, can impact pollinator populations.
Additionally, as two shrubsteppe types, antelope-brush and big sagebrush, were
sampled, I investigate whether habitat type influenced the abundance, richness or
community composition of flowering plants and pollinators. In Chapter 3, I investigate
differences in plant-pollinator network structure between antelope-brush and big
sagebrush shrubsteppe that may have consequences for community resilience to
disturbance, and assess which plant and pollinator species are functionally important in
each habitat. I also examine temporal variability in network structure to investigate how
these plant-pollinator networks, and sensitivity to disturbance, change over the course of
the flowering season. This thesis contributes to our understanding of the plant-pollinator
communities of B.C’s endangered shrubsteppe. Additionally, in a broader context, it
contributes to a growing body of research examining how habitat alteration influences
pollinator communities, and illustrates how plant-pollinator networks could be useful in
elucidating practical implications for conservation planning.
5
References
Bascompte, J. (2009). Mutualistic networks. Frontiers in Ecology and the Environment 7(8): 429-436.
Bascompte, J. and P. Jordano (2007). Plant-animal mutualistic networks: The architecture of biodiversity. Annual Review of Ecology Evolution and Systematics. Palo Alto, Annual Reviews. 38: 567-593.
Biesmeijer, J. C., S. P. M. Roberts, M. Reemer, R. Ohlemuller, M. Edwards, T. Peeters, A. P. Schaffers, S. G. Potts, R. Kleukers, C. D. Thomas, J. Settele and W. E. Kunin (2006). Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands. Science 313(5785): 351-354.
Brosi, B. J., G. C. Daily, T. M. Shih, F. Oviedo and G. Duran (2008). The effects of forest fragmentation on bee communities in tropical countryside. Journal of Applied Ecology 45(3): 773-783.
Cane, J. H., R. L. Minckley, L. J. Kervin, T. H. Roulston and N. M. Williams (2006). Complex responses within a desert bee guild (Hymenoptera : Apiformes) to urban habitat fragmentation. Ecological Applications 16(2): 632-644.
Carvell, C. (2002). Habitat use and conservation of bumblebees (Bombus spp.) under different grassland management regimes. Biological Conservation 103(1): 33-49.
Curtin, C. and D. Western (2008). Grasslands, people, and conservation: Over-the-horizon learning exchanges between African and American pastoralists. Conservation Biology 22(4): 8.
Debano, S. J. (2006). Effects of livestock grazing on aboveground insect communities in semi-arid grasslands of southeastern Arizona. Biodiversity and Conservation 15(8): 2547-2564.
Dornelas, M., C. U. Soykan and K. I. Ugland (2011). Biodiversity and disturbance. Biological Diversity: frontiers in measurment and assessment. A. E. Magurran and B. J. McGill. New York, Oxford University Press: 237-251.
Dyer, O. and E. C. Lea (2003). Status and importance of the Antelope-brush - Needle-and-thread grass plant community in the South Okanagan Valley, British Columbia. Ecosystems at Risk - Antelope Brush Restoration Conference. R. Seaton. Osoyoos, B.C.
Erhardt, A. (1985). Diurnal Lepidoptera - senstive indicators of cultivated and abandoned grassland. Journal of Applied Ecology 22(3): 849-861.
Fleischner, T. L. (1994). Ecological costs of livestock grazing in western North America. Conservation Biology 8(3): 629-644.
6
Gilgert, W. and M. Vaughan (2011). The value of pollinators and pollinator habitat to rangelands: Connections among pollinators, insects, plant communities, fish, and wildlife. Rangelands 33(3): 6.
Hatfield, R. G. and G. LeBuhn (2007). Patch and landscape factors shape community assemblage of bumble bees, Bombus spp. (Hymenoptera : Apidae), in montane meadows. Biological Conservation 139(1-2): 150-158.
Jones, A. (2000). Effects of cattle grazing on North American arid ecosystems: A quantitative review. Western North American Naturalist 60(2): 155-164.
Kearns, C. A. and D. S. Inouye (1997). Pollinators, flowering plants, and conservation biology - Much remains to be learned about pollinators and plants. Bioscience 47(5): 297-307.
Kearns, C. A., D. W. Inouye and N. M. Waser (1998). Endangered mutualisms: The conservation of plant-pollinator interactions. Annual Review of Ecology and Systematics 29: 83-112.
Kearns, C. A. and D. M. Oliveras (2009). Environmental factors affecting bee diversity in urban and remote grassland plots in Boulder, Colorado. Journal of Insect Conservation 13(6): 655-665.
Kimoto, C. (2010). Effect of livestock grazing on native bees in a pacific northwest bunchgrass prairie. Corvallis Oregon State University. Master of Science in Wildlife Science: 135.
Kruess, A. and T. Tscharntke (2002). Grazing intensity and the diversity of grasshoppers, butterflies, and trap-nesting bees and wasps. Conservation Biology 16(6): 1570-1580.
Lea, T. (2008). Historial (pre-settlement) ecosystems of the Okanagan Valley and Lower Similkameen Valley of British Columbia - pre-European contact to the present. Davidsonia 19(1): 34.
Memmott, J., N. M. Waser and M. V. Price (2004). Tolerance of pollination networks to species extinctions. Proceedings of the Royal Society of London Series B-Biological Sciences 271(1557): 2605-2611.
Ollerton, J., R. Winfree and S. Tarrant (2011). How many flowering plants are pollinated by animals? Oikos 120(3): 321-326.
Peart, B. (2008). A record of The World Temperate Grasslands Conservation Initiative Workshop Hohhot, China - June 28 & 29, 2008. Vancouver, BC, Temperate Grasslands Conservation Initiative.
Potts, S. G., J. C. Biesmeijer, C. Kremen, P. Neumann, O. Schweiger and W. E. Kunin (2010). Global pollinator declines: trends, impacts and drivers. Trends in Ecology & Evolution 25(6): 345-353.
7
Schlute, A., T. Lea, S. Cannings and P. G. Krannitz (1995). Antelope-brush ecosystems. L. a. P. B.C. Ministry of Environment, Wildlife Branch. Victoria, B.C.: 6.
Soderstrom, B., B. Svensson, K. Vessby and A. Glimskar (2001). Plants, insects and birds in semi-natural pastures in relation to local habitat and landscape factors. Biodiversity and Conservation 10(11): 1839-1863.
Sugden, E. A. (1985). Pollinators of Astragalus monoensis Barneby (Fabaceae) - New host records - Potential impact of sheep grazing. Great Basin Naturalist 45(2): 299-312.
Vazquez, D. P., N. Bluethgen, L. Cagnolo and N. P. Chacoff (2009). Uniting pattern and process in plant-animal mutualistic networks: a review. Annals of Botany 103(9): 1445-1457.
Vulliamy, B., S. G. Potts and P. G. Willmer (2006). The effects of cattle grazing on plant-pollinator communities in a fragmented Mediterranean landscape. Oikos 114(3): 529-543.
Wilson, E. O. (1987). The little things that run the world (the importance and conservation of invertebrates). Conservation Biology 1: 2.
Winfree, R. (2010). The conservation and restoration of wild bees. Year in Ecology and Conservation Biology 2010. R. S. Ostfeld and W. H. Schlesinger. Malden, Wiley-Blackwell. 1195: 169-197.
Winfree, R., R. Aguilar, D. P. Vazquez, G. LeBuhn and M. A. Aizen (2009). A meta-analysis of bees' responses to anthropogenic disturbance. Ecology 90(8): 2068-2076.
Winfree, R., T. Griswold and C. Kremen (2007). Effect of human disturbance on bee communities in a forested ecosystem. Conservation Biology 21(1): 213-223.
Xie, Z. H., P. H. Williams and Y. Tang (2008). The effect of grazing on bumblebees in the high rangelands of the Eastern Tibetan Plateau of Sichuan. Journal of Insect Conservation 12(6): 695-703.
Yoshihara, Y., B. Chimeddorj, B. Buuveibaatar, B. Lhaquasuren and S. Takatsuki (2008). Effects of livestock grazing on pollination on a steppe in eastern Mongolia. Biological Conservation 141(9): 2376-2386.
8
Chapter 2 Shrubsteppe plant and pollinator communities influenced more by habitat type than by livestock grazing
Introduction
In North America, grasslands and shrubsteppe are among the continent’s most
species-rich and threatened ecosystems. Thus, the continued fragmentation and
degradation of grassland ecosystems due to agricultural and urban development is an
increasing cause for concern (Curtin and Western 2008; Peart 2008). One of the
continent’s most prevalent grassland disturbances is livestock grazing (Fleischner 1994).
Consequently, the ecological impacts of livestock grazing in grassland and shrubsteppe
ecosystems, particularly the impacts on the vegetative community, have been
extensively studied. It is well known that livestock grazing can alter various habitat
features including vegetation community structure and composition, soil compactness,
bare soil abundance, nutrient cycling and microhabitat temperature and humidity (see
Fleischner 1994; Jones 2000 for reviews). Many studies have also indicated that
grazers indirectly impact other grassland organisms, such as birds, mammals and
amphibians, through structural changes in habitat caused by herbivory and trampling
(Fleischner 1994). However, although they constitute a large portion of the animal
biomass and have important roles in grassland ecosystem functioning (Wilson 1987;
Gilgert and Vaughan 2011), invertebrates, particularly pollinators, have been given less
attention in grazing impact studies (Debano 2006; Yoshihara et al. 2008).
Pollination is a vital ecosystem service (Kearns et al. 1998) and deserves
thorough consideration in terrestrial ecosystem disturbance studies. Pollinators, of
which bees are the primary group, are required for the successful reproduction of an
9
estimated 87.5% of the world’s flowering plant species (Ollerton et al. 2011). Thus,
aside from their immense importance in crop pollination (Klein et al. 2007), pollinator
communities are also critically important for the maintenance of natural ecosystems
(Kearns et al. 1998). The decline of pollinators and consequent disruption of pollination
systems now being reported in many regions of the world (Kearns et al. 1998; Biesmeijer
et al. 2006; Potts et al. 2010) emphasize the need to understand how anthropogenic
disturbances affect pollinator populations.
Collectively, a range of pollinator responses to grazing have been documented,
both positive (Carvell 2002; Vulliamy et al. 2006) and negative (Soderstrom et al. 2001;
Kruess and Tscharntke 2002; Debano 2006; Hatfield and LeBuhn 2007; Xie et al. 2008).
One commonality found among previous studies is that pollinator communities tend to
respond in concert with plant communities, because of their need for floral resources for
food and nest provision. Thus, studies of grasslands that depend on a frequent
disturbance regime to maintain floral diversity indicate grazing can be beneficial to
pollinator communities (e.g. Carvell 2002; Vulliamy et al. 2006), whereas studies of
grasslands without an abundance of disturbance-adapted plants, or those under heavy
grazing, suggest grazing can negatively impact pollinator communities (e.g. Kruess and
Tscharntke 2002; Debano 2006; Xie et al. 2008). Additionally, the response of
pollinators to grazing can be affected by impacts on nest sites, with increased availability
and compaction of bare soil in areas with historically high grazing tending to increase
ground nesting bees (Vulliamy et al. 2006). Collectively, these studies indicate that the
impacts of grazing on floral and pollinator communities are not universal and depend on
a host of factors, including the type of grazers (e.g. cattle, sheep) and the historical
disturbance and current grazing regimes.
The majority of studies assessing the impacts of livestock grazing on pollinator
populations have been conducted in Europe, with only a few studies previously
completed in North America, all of which were situated in the United States (Sugden
1985; Debano 2006; Hatfield and LeBuhn 2007; Kearns and Oliveras 2009; Kimoto
2010). All but one of these studies focused exclusively on bees. Although bees may be
the most important group of pollinators, grasslands and shrubsteppe also support
diverse beetle, fly, butterfly and wasp communities that contribute to the pollination of
native plants (Kearns et al. 1998; Harmon et al. 2011). Thus, information on how
10
grazing impacts whole communities of insect pollinators in North America, particularly in
more northern grasslands, is lacking.
In the Okanagan Valley, south-central British Columbia, shrubsteppe ecosystems
support numerous rare and endangered species, encompass Canada’s only temperate
desert (Schluter et al. 1995; Seaton 2003; Wikeem and Wikeem 2004), and due to the
hot and dry climate are likely to have a high diversity of bees (O'Toole and Raw 1999;
Michener 2000). The pollinator community has not been extensively inventoried and
studies assessing the impacts of anthropogenic effects on pollinator communities are
lacking. Over the last century the Okanagan basin has lost 68% of its antelope-brush
shrubsteppe and 33% of its big sagebrush shrubsteppe to agricultural and urban
development. Much of what remains is in semi-natural condition, largely due to livestock
grazing (Lea 2008). Grazing in shrubsteppe ecosystems can alter shrub cover, the
composition and distribution of herbaceous species and bare soil abundance (Jones
2000; Krannitz 2008). Therefore, I predicted that grazing would indirectly impact
pollinator communities by altering the plant community and ground-nesting site
availability. Understanding how livestock grazing affects the floral and pollinator
communities of these ecosystems will be important for biodiversity preservation and
management.
I surveyed flowering plants and pollinators in grazed and ungrazed shrubsteppe
sites over the course of an entire flowering season, March-July. I tested my expectation
that flowering plant and pollinator abundance, richness, diversity and community
composition would be negatively affected by livestock grazing. I also assessed whether
different pollinator functional groups were affected similarly by grazing disturbance.
Also, as habitat features other than floral resources, such as vegetation height and bare
soil availability, can also affect pollinator populations, I assessed the influence of grazing
on shrubsteppe vegetation structure. Finally, because the dominant shrubs species, as
well as other plant species, vary with elevation in this ecosystem, I also investigated
whether shrubsteppe type influenced the abundance, richness, diversity or community
composition of flowering plants or pollinators.
11
Methods
Study area
The shrubsteppe ecosystems of western North America range from the Great
Basin in eastern California and Nevada northward through the Columbia Basin and into
south central British Columbia (Mack 1981; Gayton 2003). In B.C., shrubsteppe
ecosystems occur primarily in the southern Okanagan and Similkameen Valleys, and in
the Thompson River Valley around Kamloops (Mack 1981; Krannitz 2008).
Within the Okanagan Valley, shrubsteppe ecosystems occupy the valley floor,
benches and lower slopes, ranging from approximately 250 m to 700 m (Wikeem and
Wikeem 2004). At slightly higher elevations, a sparse Ponderosa Pine (Pinus
ponderosa) over-story accompanies the shrubsteppe vegetation (Nicholson et al. 1991).
Antelope-brush (Purshia tridentata), along with rabbit-brush (Chrysothamnus
nauseosus), dominate dry sites with sandy soils, and are replaced by big sagebrush
(Artemisia tridentata) as elevation and moisture increase. The understory vegetation is
characterized by widely spaced bunchgrasses mixed with a variety of wildflowers and a
well-developed cryptogamic crust. This region has been subject to increasing
anthropogenic disturbance, with a combination of cattle ranching, commercial orchards,
vineyards, and urban development (Lea 2008).
Study sites
I chose eight sites, four grazed and four ungrazed, in the southern Okanagan
Valley (Figure 2.1, Table 2.1). Gazed and ungrazed sites were paired for similarity in
elevation, slope, aspect, and vegetation to improve the strength of comparison of
grazing regime. All sites were a minimum of 20 hectares and were connected to
contiguous shrubsteppe, grassland or ponderosa pine forest on at least one side. The
average distance between sites within a pair was 4.3 km, with an average between-pair
distance of 11 km. As the entire Okanagan Valley was historically grazed (Rick Tucker,
BC Ministry of Forests and Range, pers. comm.), even ‘ungrazed’ sites have had cattle
grazing at some point in the past; grazing regimes as reported by site managers are in
Table 2.1. All grazed sites are spring grazed by cattle for roughly one month between
the beginning of April and end of June (Table 2.1), and with the exception of SOG, were
12
grazed by livestock during the sampling season. At the start of research we were
informed that SOG was regularly grazed but subsequently it became clear that accurate
records since 2004 were lacking.
Within each site I chose an area that would be suitable for pairing, e.g. with
similar environmental variables to the paired site. Within these areas, a point was
randomly selected on an aerial photo and used as the starting point for a 100 m
permanent transect. A single random orientation was used for all transects. Around
each permanent transect a 1-ha sampling plot was delineated, within which I conducted
all pollinator and vegetation sampling.
Vegetation
Vegetation structure
Pollinator communities can be influenced by vegetation (floral resources and
habitat structure) and bare soil availability (nesting sites), both of which are expected to
be impacted by livestock grazing (Vulliamy et al. 2006). Therefore, I measured the
maximum height and percent cover of vegetation by layer (shrub, grass and forb), as
well as the percent cover of ground layers (bare soil, cryptogamic crust and litter).
Sampling was conducted in 60 0.5x1 m quadrats, spaced five meters apart, along four
90 m transects spread evenly across each 1-ha plot. Within quadrats, the percent cover
of vegetation and ground layers was estimated to the nearest half percentage. I
conducted vegetation structure sampling within the same week for sites within a pair,
between June 21st and July 7th, 2010.
Flowering plant diversity
I surveyed flowering plants at each site eight times. The first survey at each site
coincided with the beginning of the spring bloom (March 2010), after which surveys were
continued approximately every two weeks until the end of the flowering season (July
2010). In each hectare, I sampled 30 0.5x1 m quadrats evenly spaced along 90 m of the
central permanent transect. In each quadrat, I counted the number of “floral units”,
generally an inflorescence, of each wildflower species present (see Appendix A for floral
unit designations by species). I assessed forbs only, as grasses do not normally provide
13
forage for pollinators, and deleted from analysis any forb species apparently unattractive
to most pollinators (pers. obs.; mostly small-flowered species like Draba verna).
Pollinator diversity
I used pan-traps (blue, yellow, and white) to collect flying insects (putative
pollinators) eight times over the flowering season, concurrent with flowering plant
diversity surveys. Thirty 12 oz pan-traps (10 per color in a regular order) were laid out at
3-m intervals along the central transect. On each sampling date, pan-traps were
deployed by 8:30 am and collected starting at 5:00 pm, to keep the sampling time
between sites consistent (~8.5hr/date). Paired sites were always sampled on the same
day to eliminate potential differences between grazing treatments that were due to other
factors such as weather or Julian date. Pan-traps were only deployed on warm, sunny
days with low to moderate wind. I stored pan-trap samples in 75% ethanol until the
specimens could be dried and pinned for identification.
All species were identified to the lowest taxonomic level possible, with a focus on
insects observed to be floral visitors (data from netting surveys where insects were
collected directly from flowers; Chapter 3). Bees (Hymenoptera) comprised the majority
of specimens and were identified to species except for some genera without revised
keys (Evylaeus, Nomada, Sphecodes) which were identified to morphospecies.
Hoverflies (Syrphidae) and bee flies (Bombyliidae) were also identified to species, as
were thick-headed flies (Conopidae). Tachinids, Sarcophagids, and Calliphorid flies
were identified to morphospecies and included in the analysis if they were collected off
of flowers in other research (Chapter 3), but other Dipterans were not common flower
visitors and so were not included. Finally, beetles (Coleoptera), butterflies and moths
(Lepidoptera), and wasps (Hymenoptera) were often identified to genus or
morphospecies, and were included in the current analysis if also collected in netting
surveys. I considered flower visitors to be putative pollinators, as frequent flower visitors
often contribute to plant reproduction (Vazquez et al. 2005; Sahli and Conner 2006).
Hereafter, all morphospecies will be referred to as species for the purposes of simplicity
(specific morphospecies designations are presented in Appendix B, Table B.2).
14
Statistical analysis
Vegetation structure
The influence of livestock grazing on vegetation structure, measured as the
percent cover of vegetation and ground layers (shrub, forb, grass, bare soil, crust, litter)
and maximum height of vegetation layers (forb, grass), was analysed with a multivariate
analysis of variance (MANOVA) using the GLM procedure of SAS version 9.2 (SAS
institute, 2008). The maximum height of shrubs was excluded from the analysis as over
half of the quadrats sampled were without shrubs, and I wanted to retain the information
on other measured variables. The model included management (grazed vs. ungrazed)
as a fixed effect, transect as a random effect, and pair as random blocking effect.
Transect nested within block and management was used as the error term when testing
for a main effect of management. Because the overall MANOVA was significant (see
results) I subsequently performed univariate analyses of variance (ANOVAs) on each
variable using the same model. All percent cover variables were arcsine square-root
transformed, which is appropriate for proportion data (Sokal and Rohlf 1995), and height
measurements were log transformed to reduce heteroscedasticity.
Abundance, richness and diversity
I computed sample-based rarefaction for the pollinator communities of each site
to assess approximately how well sampling captured pollinator species richness. I also
calculated Simpson’s index of diversity (1-D) and Chao2 richness estimates for the
flowering plant and pollinator communities at all sites, using EstimateS (Colwell 2005).
Chao2 derives estimates of the true species richness of a community using the
occurrence of rare species within samples, specifically the number of species that occur
in just one (uniques) or two (duplicates) samples (Colwell and Coddington 1994). Chao2
is robust to small sample sizes (Colwell and Coddington 1994) and is considered
appropriate for invertebrate communities as singletons and doubletons are commonly
sampled.
I evaluated the effect of grazing on the species richness and abundance of
flowering plants and pollinators using generalized linear mixed models (GLMMs) in SAS
(PROC GLIMMIX), that included management and sample episode as fixed effects and
pair as a random blocking effect. Since abundance and richness are count data, a
15
Poisson distribution with log link function was used for all models (Zuur et al. 2007).
Raw count data was used for floral unit abundance, pollinator abundance and pollinator
richness, while Chao2 richness estimates were used for flowering plant richness.
Although pollinator sampling as some sites wasn’t sufficient to produces a clear
asymptote on the rarefaction curve (Figure 2.2), pollinator Chao2 richness estimates
could not be used in the GLMM as each sample episode had only three sub-samples
which was not sufficient for richness estimation. The residuals of initial models indicated
overdispersion, therefore the data was re-fitted with quasi-Poisson models (Zuur et al.
2007). Flowering plant and pollinator diversity (1-D) was compared between grazed and
ungrazed sites using mixed models in SAS (PROC MIXED). All mixed models included
management and sample episode as fixed effects and pair as a random blocking effect,
with an autoregressive covariance structure.
I also analyzed the effects of grazing on the abundance, richness and diversity of
pollinator functional groups using the same models. Differences in nesting substrate
and foraging strategies can be used to define functional groups (e.g., Neame et al.
2012), because they influence how pollinators are affected by anthropogenic
disturbances (e.g., Cane et al. 2006; Sjodin et al. 2008; Williams et al. 2010). I
categorized specimens into five functional groups based on taxonomy and nesting
behaviour: above-ground nesting bees (including the introduced honeybee, Apis
mellifera); below-ground nesting bees; beetles; wasps; and other pollinators (flies,
butterflies and moths). Cleptoparasitic bees, whose nesting biology is dictated by their
hosts, were excluded from the analysis because their response to disturbance is not
independent of the response of their host species (Williams et al. 2010). Five species of
the bee genus Megachile were also excluded as they are known to nest both above and
below ground and could not conclusively be placed in either category.
I also used GLMMs and mixed models in SAS to assess whether shrubsteppe
type (antelope-brush vs. big sagebrush) influenced flowering plant and total pollinator
abundance, richness and diversity over time. In all GLMMs investigating effects on
abundance and richness I specified a quasi-Poisson distribution and log link function.
Mixed models investigating effects on diversity included an autoregressive covariance
structure. All GLMMs and mixed models included shrubsteppe type and sample episode
as fixed effects and site nested within habitat as a random effect.
16
For all models the degrees of freedom were calculated using the Kenwood Roger
method and least square (LS) means were computed for all fixed effects. Flowering
plant and pollinator diversity values were arcsine square-root transformed to eliminate
heteroscedasticity prior to analyses.
Community composition
To explore whether livestock grazing impacts flowering plant or pollinator
community composition over time, I performed non-metric multidimensional scaling
(NMDS) of sites in species space using PC-ORD 5 (McCune and Mefford 2006). Prior
to running the ordinations, I square-root transformed floral unit and pollinator
abundances. The square-root transform is appropriate for community data, as it down-
weights the effect of single species and allows species of intermediate abundance to
contribute more to the overall assemblage pattern (McCune and Grace 2002).
Additionally, I removed all species represented by a single individual prior to the
pollinator community ordination to reduce noise (McCune and Grace 2002). All
flowering plant species were retained in the floral community ordination, as singletons
were few and did not influence the stress of the ordination. Sorensen distance was used
to generate the dissimilarity matrix of both ordinations. I determined the appropriate
number of dimensions for the ordinations using a step-down procedure from six
dimensions, using a maximum of 150 random starting configurations. The scree plot of
stress values generated from both ordinations suggested that a final three dimensional
solution was best. To facilitate interpretation of the ordinations I calculated correlations
between the abundance of floral units and pollinator species and the NMDS solutions
using SAS (PROC CORR).
To test for the effects of grazing and shrubsteppe type on pollinator and flowering
plant community composition, I used permutation-based multivariate analyses of
variance (PerMANOVA). PerMANOVA allows the effects of one or more factors on a
whole assemblage of species to be tested simultaneously on the basis of any distance
measure, using permutation methods (Anderson 2001). PerMANOVAs were performed
in R using the adonis function in the vegan package (R Development Core Team, 2011;
Oksanen et al. 2011). Models testing the impact of livestock grazing on plant and
pollinator communities incorporated management and sample episode as fixed effects,
17
blocked by pair. Models testing the impact of habitat type included sample episode and
shrubsteppe type as fixed effects. For all tests, Sorensen’s distance measure and 4999
random permutations were used. I also tested for the multivariate homogeneity of group
dispersions using the betadisper function, as PerMANOVA is sensitive to differences in
the dispersion of points within groups (Anderson 2001).
Finally, to assess whether the pollinator and flowering plant communities of the
sites sampled were correlated I ran a Mantel test, based on Mantel’s asymptotic
approximation, in PC-ORD (McCune and Grace 2002), using Sorensen’s distance and
square-root transformed overall abundance data as before. I retained all species
sampled for this analysis.
Results
I collected a total of 6317 putative pollinators, comprising 185 bee species, 25 fly
species, 11 beetle species, 17 wasp species, and 18 butterfly and moth species (Figure
2.3; Appendix B, Table B.2). The number of pollinators collected varied between sites,
from 514 individuals at SOG to 1227 individuals at OKG (Table 2.2). Pollinator species
richness varied considerably less, from 139 species at OKG to 198 species at OKU
(Chao2). Bees made up 81% of the total individuals caught, followed by wasps and
beetles with 8% and 7%, respectively. Ground nesting bees from the families Halictidae
and Andrenidae comprised the majority of bees collected (83%), however, the
Megachilidae were the most speciose family represented, with 59 species (Figure 2.3).
Many of the species collected were uncommon, with 27% of bee species being
represented by only one or two individuals.
I surveyed 54 pollinator-attractive wildflower species across the eight sites.
Flowering plant richness varied from 5 to 26 species across sites, while floral units
varied over almost an order of magnitude (Table 2.2).
Vegetation structure
The overall structure of shrubsteppe vegetation was affected by livestock grazing
(MANOVA, F8,20=13.73, P<0.0001). Univariate tests indicated that grazing increases the
18
percent cover of shrubs and bare soil, while decreasing the cover of cryptogamic crust
and the maximum height of forbs and grasses (Figure 2.4). The percent cover of the
grass, forb, and litter layers were unaffected by grazing.
Abundance, richness and diversity
Flowering plants
Although a trend of decreased flowering plant abundance was observed in
grazed sites over the last four sampling episodes (Figure 2.5), models revealed no
overall influence of grazing on floral abundance, richness or diversity (GLMMs,
The Mantel test indicated that there was a positive correlation (t= 3.128) between
pollinator and flowering plant communities; sites with similar plant community
composition are also more likely to have similar pollinator community composition
(Mantel statistic r=0.612, P= 0.002).
Discussion
In this study, I found that livestock grazing affected shrubsteppe vegetation
structure, but did not significantly influence flowering plant or pollinator abundance,
richness, diversity or community composition, although a trend towards differing
pollinator community composition was identified. Instead, the composition of both the
flowering plant and pollinator community differed significantly between the two
shrubsteppe habitats sampled, antelope-brush and big sagebrush. This difference was
likely driven by environmental characteristics associated with elevation change.
Flowering plant and pollinator community compositions were positively correlated across
sites, and along with floral and pollinator abundance, richness and diversity, changed
over the course of the flowering season, as was expected. Overall, these findings
suggest that flowering plant and pollinator diversity can be maintained under short-
duration, low-intensity livestock grazing in the southern Okanagan.
The effects of livestock grazing
Vegetation structure
In agreement with other studies investigating the impacts of livestock grazing on
vegetation structure (Jones 2000; Kruess and Tscharntke 2002; Krannitz 2008), my
results show that grazing can influence the percent cover and height of vegetation.
Shrub cover was greater on grazed sites, complementing findings by Krannitz (2008)
which showed that big sagebrush increases with grazing intensity and that although
heavy grazing can be detrimental, antelope-brush cover is highest under light grazing
pressure. Similarly, Ganskopp et al. (2004) found that the growth of young antelope-
brush shrubs can be stimulated by light, spring cattle grazing. In B.C., range managers
consider both antelope-brush and big sagebrush as “increasers” and two other common
shrub species, rabbit-brush and pasture sage (Artemisia frigida), as “invaders” in
22
response to livestock grazing (Gayton 2003), also supporting my findings. In contrast,
the percent cover of grasses and forbs were unaffected by grazing, but both vegetation
layers were shorter at grazed sites. Grasses and forbs could be shorter under grazing
disturbance for a variety of reasons, including herbivory, reductions in plant vigor due to
herbivory stress (Pond 1960; Krannitz 2008) and changes in species composition
(Fleischner 1994). However, the consistency in the percent cover of grasses and forbs
between grazed and ungrazed sites suggests that the current intensity of grazing does
not negatively affect plant basal diameter or recruitment. Many other grazing impact
studies have reported similar responses of the grass and forb layers (e.g. Kruess and
Tscharntke 2002; Krannitz 2008; Sjodin et al. 2008).
Trampling by livestock increased the cover of bare soil, while decreasing the
cover of cryptogamic crust, a finding previously shown in these (Krannitz 2008) and
other semi-arid ecosystems (Anderson et al. 1982; Fleischner 1994; Jones 2000;
Vulliamy et al. 2006). Cryptogamic crust, which is important for soil stability (Kleiner and
Harper 1972) and moisture retention (Loope and Gifford 1972), is most susceptible to
disturbance in the growing season (Memmott et al. 1998; Krannitz 2008) which is likely
why spring grazing can be so damaging. The litter layer however, which commonly
decreases in cover under grazing (Jones 2000; Sjodin et al. 2008) was unchanged at my
sites, likely because of the relatively low grazing pressure.
Flowering plants
Contrary to expectations, changes in vegetation structure under livestock grazing
did not extend to changes in pollinator-attractive flowering plant abundance, richness,
diversity or community composition. Although other studies have reported similar
findings (Sjodin et al. 2008; Vazquez et al. 2008; Batary et al. 2010), the response of
floral communities to grazing appears complex, as reports that grazing is positive
(Carvell 2002; Vulliamy et al. 2006) and that it is negative (Xie et al. 2008; Yoshihara et
al. 2008; Kimoto 2010) have also been made. A number of factors appear to be
important in determining how livestock grazing will impact floral communities.
Ecosystems with long grazing histories and disturbance-adapted flowering plants often
respond positively to grazing, as long as the grazing intensity is at an intermediate level
(Carvell 2002; Vulliamy et al. 2006). In contrast, ecosystems without long grazing
23
histories, such as western North America and South America, are thought to be more
likely to respond negatively to livestock grazing (Mack and Thompson 1982; McIntyre et
al. 1996; Debano 2006; Vulliamy et al. 2006). This study, and that of Vazquez et al.
(2008) from Argentina, indicate that floral communities of grasslands without long
grazing histories do not necessarily respond negatively, and emphasize the importance
of the current grazing regime in determining vegetation responses.
Although non-significant, there was a trend (P= 0.076) of decreased floral
abundance in grazed sites during the later-half of the flowering season (June – July),
roughly corresponding with the cessation of grazing. It may be that forbs subject to
herbivory by livestock tend to produce fewer flowers, or that grazing decreases the
abundance of some species. Yarrow (Achillea millefolium), slender hawksbeard (Crepis
atrabarba), triple-nerved daisy (Erigeron subtrinervis), and silky lupine (Lupinus
sericeus), all mid-to-late season flowering plants, had at least four times more floral units
at ungrazed sites. Therefore, livestock may have had some influence on particular
members of the floral community, but the short duration and low-intensity of grazing
precluded any significant negative effects on the community as a whole.
Pollinators
The abundance, richness and diversity of pollinators were also unaffected by
livestock grazing. As with floral communities, the reported responses of pollinators to
grazing disturbance varies widely (e.g., Kruess and Tscharntke 2002; Vulliamy et al.
2006; Sjodin et al. 2008; Xie et al. 2008; Sarospataki et al. 2009). A common thread
throughout this and previous studies is that regardless of whether grazing proved
positive, negative or neutral, the response of the pollinator community closely mirrored
that of the floral community. For bees this is an expected result, as pollen and nectar
are food sources for both adults and their offspring (Kearns and Inouye 1997). However,
flowering plant abundance and richness have also been shown to influence community
structure of butterflies (Erhardt 1985), flies (Hegland and Boeke 2006; Frund et al.
2010), beetles (Volkl et al. 1993; Hegland and Boeke 2006) and wasps (Karem et al.
2010) even though only the adults feed on floral resources. The flowering plant and
pollinator communities at my sites were significantly correlated, suggesting that food
resources (i.e., floral community composition) are an important determinant of pollinator
24
community composition. Therefore, it is not surprising that the neutral effects of grazing
on flowering plant abundance, richness and diversity were carried through to the
pollinator community.
Although floral resources are important in shaping pollinator communities,
nesting resources (Kearns and Inouye 1997; Potts et al. 2005) can also be a critical
factor. Several studies have found that pollinators of differing functional groups, such as
those differing in nesting habit, can respond differently to anthropogenic disturbance
(e.g., Cane et al. 2006; Sjodin et al. 2008; Williams et al. 2010; Neame et al. 2012). The
abundance and richness of ground nesting bees, for example, can be positively
influenced by livestock grazing through the increased availability of compacted bare soil
(nesting substrate) caused by livestock trampling (Vulliamy et al. 2006). However, other
researchers have suggested that cattle trampling may actually disturb underground
nests, leading to detrimental effects on ground nesters (Gess and Gess 1983; Sugden
1985). My results show that bare soil cover can increase under grazing pressure, but
that this does not necessarily lead to an increase or decrease in ground nesting bees.
Additionally, decreased vegetation height due to grazing has been shown to negatively
influence the abundance and richness of butterflies (Kruess and Tscharntke 2002),
hoverflies and beetles (Sjodin et al. 2008), presumably because habitat requirements for
their young were altered. Although grasses and forbs were shorter at grazed sites, this
did not have a significant effect on abundance, richness or diversity of butterflies, flies or
beetles in my study.
Although there were no differences in pollinator abundance, richness or diversity
between grazed and ungrazed sites, there was a trend towards differing pollinator
community composition. Examination of pollinator species abundances indicated that,
although the majority of pollinator species did not differ in abundance between grazed
and ungrazed sites, those that did were among the most abundant species collected.
For example, Buprestidae sp.2 and Lasioglossum pruinosum were roughly three times
more abundant in ungrazed sites, whereas Halictus farinosus and H. tripartitus were
twice as abundant in grazed sites. All four species were within the top-10 most
abundant species sampled (175-830 individuals collected). Due to their high abundance
these species are likely to carry a large weight in multivariate analyses (McCune and
Grace 2002) and are likely to be driving the trend seen. Therefore, livestock grazing
25
may influence the relative abundance of some pollinator species, but the duration and
intensity of grazing has precluded any changes in overall pollinator abundance, richness
and diversity.
The effects of shrubsteppe type
Antelope-brush shrubsteppe is a lower-slope to valley-bottom ecosystem, and as
a result is drier, sandier and often more nutrient-poor than the higher elevation big
sagebrush shrubsteppe (Nicholson et al. 1991). These environmental differences
appear to have significantly influenced the flowering plant community composition at my
sites. Although many flowering plant species are present in both ecosystems, many
others were sampled primarily or exclusively at low or high elevations. For instance,
silky lupine (Lupinus sericeus), Thompson’s paintbrush (Castilleja thompsonii), and
lemonweed (Lithospermum ruderale) were found exclusively at higher elevation big
sagebrush sites, whereas golden aster (Heterotheca villosa), pale evening-primrose
(Oenothera pallida) and brittle prickly-pear cactus (Opuntia fragilis) were found primarily
at low elevation antelope-brush sites.
The composition of the pollinator community also differed between shrubsteppe
types, perhaps as a response to available floral resources (see Appendix C for the top
10 most abundant flowering plants and pollinators of each shrubsteppe type). The bee
genera Eucera, Andrena, Nomada and Cerambycid beetles were all more prevalent in
big sagebrush shrubsteppe. Eucera spp. are long-tongued bees that often visit
lemonweed, silky lupine, and thread-leaved phacelia (Phacelia linearis), all species more
common or exclusively in big sagebrush shrubsteppe. The most common Andrena spp.
collected also favoured plants more abundant in big sagebrush sites: desert-parsleys
(Lomatium macrocarpum and L. triternatum), and long-flowered mertensia (Mertensia
longiflora). Nomada spp. are cleptoparasites, primarily of Andrena, and their habitat
choices are likely based on the location of their hosts (T. Griswold, USDA bee lab, Utah
State University, pers. comm.). Cerambycid beetles favoured species from the
Asteraceae family which were common everywhere, suggesting factors other than floral
resources are important in determining their distribution.
26
Several other pollinator species were collected more frequently at antelope-brush
sites than at big sagebrush sites, including honeybees. Honeybee prevalence, like
Cerambycid beetles, was likely unrelated to diet. Honeybee abundance is largely
determined by the location of managed hives, and in the southern Okanagan Valley
most orchards and other crops are on the valley bottoms, adjacent to the remaining
antelope-brush shrubsteppe. Dianthidium spp. were collected almost exclusively in
antelope-brush habitats but insufficient floral records exist to assess whether diet may
drive this pattern. Melissodes spp. were also collected primarily in antelope-brush
habitats and visited only a few plant species including golden aster (Heterotheca villosa)
which is only found at low elevations. Perdita fallax is a golden aster specialist, and
along with Megachile umatillensis which specializes on the provincially Red-listed pale
evening-primrose (Oenothera pallida), is found only in low elevation antelope-brush
shrubsteppe where these plants occur.
Management implications
Much of the remaining shrubsteppe in the Okanagan is grazed by livestock under
regimes that vary widely depending on the productivity of the land as well as the goals of
local land managers. Although this variability in grazing regimes could have contributed
to a lack of a grazing effect in this study, the long recovery time after disturbance of dry
bunchgrass ecosystems (20-40 years; McLean and Tisdale 1972) I expected any
grazing to be detrimental. Although much of the Okanagan Valley was severely
overgrazed by the early 1900’s, changes in range management, such as the
implementation of single-season and rotational grazing, have resulted in considerable
improvements to ecosystem health (Bawtree 2005). The grazed areas included in this
study, at least in the recent past, were managed with the preservation of biological
diversity in mind (Wade Clifton, Clifton Ranch; Anne Skinner, B.C. Ministry of Forest and
Range, pers. comm.).
My results indicate that short-term spring cattle grazing with <1 AUM/ha (1 AUM
is equivalent to the forage removed by one 454 kg cow grazing for one month) does not
negatively impact flowering plant or pollinator abundance, richness or diversity. Given
the trends towards differing pollinator community composition and decreased floral
abundance identified, I recommend that these grazing regimes be maintained, and not
27
increased, if the preservation of flowering plants and pollinators is of conservation
concern. As the trend of decreased floral resources occurred during the mid-to-late
portion of the flowering season, monitoring of grazing impacts may be most valuable
within this time frame. Additionally, because antelope-brush and big sagebrush
shrubsteppe both support high flowering plant and pollinator diversity, but their
community compositions differ, attention to maintaining the health of both habitats under
sustainable grazing practice is of great importance.
My research was performed at the community level, therefore provincially-listed
rare species such as pale evening-primrose, Lyall’s mariposa lily (Calochortus lyallii),
and grand coulee owl-clover (Orthocarpus barbatus) were not my focus. If rare plant
species or specialist pollinators are of conservation interest, further work will be needed
that aims specifically to assess such species. An encouraging observation is that aside
from pale evening-primrose, other plants supporting specialist pollinators [meadow death
camas (Zigadenus venenosus) with Andrena astragali; golden aster with Perdita fallax,
large-fruited and narrow-leaved desert-parsleys with Andrena microchlora; Phacelia spp.
with Dufourea trochantera, Colletes consors and Chelostoma phaceliae] were common
and appeared unaffected by low levels of livestock grazing, suggesting grazing may not
be detrimental to these specialist pollinators.
Conclusions
Short-term, low-intensity livestock grazing in the southern Okanagan
shrubsteppe does negatively influence some aspects of vegetation structure, but does
not significantly impact flowering plant or pollinator communities. These results suggest
that semi-natural habitats, when managed responsibly, can remain reservoirs of
flowering plant and pollinator diversity. This is especially encouraging for habitats, like
shrubsteppe, which are biologically diverse but have few remaining undisturbed areas.
As anthropogenic pressures continue to increase, the continued effort of land managers
to find a balance between biological integrity and economic viability will be vital for the
conservation of native plants and pollinators.
28
References
Anderson, D. C., K. T. Harper and S. R. Rushforth (1982). Recovery of cryptogramic soil crusts from grazing on Utah winter ranges. Journal of Range Management 35(3): 355-359.
Anderson, M. J. (2001). A new method for non-parametric multivariate analysis of variance. Austral Ecology 26(1): 32-46.
Batary, P., A. Baldi, M. Saropataki, F. Kohler, J. Verhulst, E. Knop, F. Herzog and D. Kleijn (2010). Effect of conservation management on bees and insect-pollinated grassland plant communities in three European countries. Agriculture Ecosystems & Environment 136(1-2): 35-39.
Bawtree, A. H. (2005). A History of Range Use in British Columbia. Rangelands 27(6): 4.
Biesmeijer, J. C., S. P. M. Roberts, M. Reemer, R. Ohlemuller, M. Edwards, T. Peeters, A. P. Schaffers, S. G. Potts, R. Kleukers, C. D. Thomas, J. Settele and W. E. Kunin (2006). Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands. Science 313(5785): 351-354.
Cane, J. H., R. L. Minckley, L. J. Kervin, T. H. Roulston and N. M. Williams (2006). Complex responses within a desert bee guild (Hymenoptera : Apiformes) to urban habitat fragmentation. Ecological Applications 16(2): 632-644.
Carvell, C. (2002). Habitat use and conservation of bumblebees (Bombus spp.) under different grassland management regimes. Biological Conservation 103(1): 33-49.
Colwell, R. K. (2005). EstimateS: Statistical estimation of species richness and shared species from samples. Version 7.5, User's guide and application published at: http://purl.oclc.org/estimates.
Colwell, R. K. and J. A. Coddington (1994). Estimating terrestrial biodiversity through extrapolation. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences 345(1311): 101-118.
Curtin, C. and D. Western (2008). Grasslands, people, and conservation: Over-the-horizon learning exchanges between African and American pastoralists. Conservation Biology 22(4): 8.
Debano, S. J. (2006). Effects of livestock grazing on aboveground insect communities in semi-arid grasslands of southeastern Arizona. Biodiversity and Conservation 15(8): 2547-2564.
Erhardt, A. (1985). Diurnal Lepidoptera - senstive indicators of cultivated and abandoned grassland. Journal of Applied Ecology 22(3): 849-861.
Fleischner, T. L. (1994). Ecological costs of livestock grazing in western North America. Conservation Biology 8(3): 629-644.
29
Frund, J., K. E. Linsenmair and N. Bluthgen (2010). Pollinator diversity and specialization in relation to flower diversity. Oikos 119(10): 1581-1590.
Ganskopp, D., T. Svejcar, F. Taylor and J. Farstvedt (2004). Can spring cattle grazing among young bitterbrush stimulate shrub growth? Journal of Range Management 57(2): 161-168.
Gayton, D. (2003). British Columbia Grasslands Monitoring Vegetation Change, FORREX - Forest Research Extension Partnership. 7.
Gess, F. W. and S. K. Gess (1983). Effects of increasing land utilization on species representation and diversity of aculeate wasps and bees in semi-arid areas of southern Africa. Hymenoptera and biodiversity. J. LaSalle and I. D. Gauld, CAB International: 83-114.
Gilgert, W. and M. Vaughan (2011). The value of pollinators and pollinator habitat to rangelands: Connections among pollinators, insects, plant communities, fish, and wildlife. Rangelands 33(3): 6.
Harmon, J. P., A. C. Ganguli and M. J. Solga (2011). An overview of pollination in rangelands: Who, why, and how. Rangelands 33(3): 5.
Hatfield, R. G. and G. LeBuhn (2007). Patch and landscape factors shape community assemblage of bumble bees, Bombus spp. (Hymenoptera : Apidae), in montane meadows. Biological Conservation 139(1-2): 150-158.
Hegland, S. J. and L. Boeke (2006). Relationships between the density and diversity of floral resources and flower visitor activity in a temperate grassland community. Ecological Entomology 31(5): 532-538.
Jones, A. (2000). Effects of cattle grazing on North American arid ecosystems: A quantitative review. Western North American Naturalist 60(2): 155-164.
Karem, J., S. A. Woods, F. Drummond and C. Stubbs (2010). The relationships between Apocrita wasp populations and flowering plants in Maine's wild lowbush blueberry agroecosystems. Biocontrol Science and Technology 20(3): 257-274.
Kearns, C. A. and D. S. Inouye (1997). Pollinators, flowering plants, and conservation biology - Much remains to be learned about pollinators and plants. Bioscience 47(5): 297-307.
Kearns, C. A., D. W. Inouye and N. M. Waser (1998). Endangered mutualisms: The conservation of plant-pollinator interactions. Annual Review of Ecology and Systematics 29: 83-112.
Kearns, C. A. and D. M. Oliveras (2009). Environmental factors affecting bee diversity in urban and remote grassland plots in Boulder, Colorado. Journal of Insect Conservation 13(6): 655-665.
30
Kimoto, C. (2010). Effect of livestock grazing on native bees in a pacific northwest bunchgrass prairie. Corvallis Oregon State University. Master of Science in Wildlife Science: 135.
Klein, A. M., B. E. Vaissiere, J. H. Cane, I. Steffan-Dewenter, S. A. Cunningham, C. Kremen and T. Tscharntke (2007). Importance of pollinators in changing landscapes for world crops. Proceedings of the Royal Society B-Biological Sciences 274(1608): 303-313.
Kleiner, E. F. and K. T. Harper (1972). Environment and community organization in grasslands of Canyonlands National Park. Ecology 53(2): 299-&.
Krannitz, P. G. (2008). Response of antelope bitterbrush shrubsteppe to variation in livestock grazing. Western North American Naturalist 68(2): 138-152.
Kruess, A. and T. Tscharntke (2002). Contrasting responses of plant and insect diversity to variation in grazing intensity. Biological Conservation 106(3): 293-302.
Kruess, A. and T. Tscharntke (2002). Grazing intensity and the diversity of grasshoppers, butterflies, and trap-nesting bees and wasps. Conservation Biology 16(6): 1570-1580.
Lea, T. (2008). Historial (pre-settlement) ecosystems of the Okanagan Valley and Lower Similkameen Valley of British Columbia - pre-European contact to the present. Davidsonia 19(1): 34.
Loope, W. L. and G. F. Gifford (1972). Influence of a soil microfloral crust on select properties of soils under pinyon-juniper in southeastern Utah. Journal of Soil and Water Conservation 27(4): 164-&.
Mack, R. N. (1981). Invasion of Bromus tectorum L into western North America - An ecological chronicle. Agro-Ecosystems 7(2): 145-165.
Mack, R. N. and J. N. Thompson (1982). Evolution in steppe with few large, hoofed mammals. American Naturalist 119(6): 757-773.
McCune, B. and J. B. Grace (2002). Analysis of Ecological Communities. Gleneden Beach, Oregon, U.S.A., MjM Software Design.
McCune, B. and M. J. Mefford (2006). PC-ORD. Multivariate Analysis of Ecological Data. Gleneden Beach, Oregon, U.S.A., MjM Software.
McIntyre, S., G. W. Barrett and H. A. Ford (1996). Communities and Ecosystems. Conservation Biology. I. F. Spellerberg. England, Longman Group Limited: 154-170.
McLean, A. and L. Marchand (1968). Grassland ranges in the southern interior of British Columbia. Ottawa, Canada , Publication 1319. Canadian Department of Agriculture.
31
McLean, A. and E. W. Tisdale (1972). Recovery rate of depleted range sites under protection from grazing. Journal of Range Management 25(3): 178-&.
Memmott, K. L., V. J. Anderson and S. B. Monsen (1998). Seasonal grazing impact on cryptogamic crusts in a cold desert ecosystem. Journal of Range Management 51(5): 547-550.
Michener (2000). The Bees of the World. Baltimore, The Johns Hopkins University Press.
Neame, A. L., T. Griswold and E. Elle (2012). Pollinator nesting guilds respond differently to urban habitat fragmentation in an oak-savannah ecosystem. Insect Conservation and Diversity doi:10.1111/j.1752-4598.2012.00187.x.
Nicholson, A., E. Hamilton, W. L. Harper and B. M. Wikeem (1991). Bunchgrass Zone. Ecosystesm of British Columbia. D. Meidinger, Pojar, J. Victoria, B.C, Province of British Columbia.
O'Toole, C. and A. Raw (1999). Bees of the World. London, England, Blandford.
Oksanen, J., F. G. Blanchet, R. Kindt, P. Legendre, R. B. O'ttara, G. L. Simpson, P. Solymos, M. H. H. Stevens and H. Wagner (2011). vegan: Community Ecology Package. R package.
Ollerton, J., R. Winfree and S. Tarrant (2011). How many flowering plants are pollinated by animals? Oikos 120(3): 321-326.
Peart, B. (2008). A record of The World Temperate Grasslands Conservation Initiative Workshop Hohhot, China - June 28 & 29, 2008. Vancouver, BC, Temperate Grasslands Conservation Initiative.
Pond, F. W. (1960). Vigor of idaho fescue in relation to different grazing intensities. Journal of Range Management 13(1): 3.
Potts, S. G., J. C. Biesmeijer, C. Kremen, P. Neumann, O. Schweiger and W. E. Kunin (2010). Global pollinator declines: trends, impacts and drivers. Trends in Ecology & Evolution 25(6): 345-353.
Potts, S. G., B. Vulliamy, S. Roberts, C. O'Toole, A. Dafni, G. Ne'Eman and P. Willmer (2005). Role of nesting resources in organising diverse bee communities in a Mediterranean landscape. Ecological Entomology 30(1): 78-85.
Sahli, H. F. and J. K. Conner (2006). Characterizing ecological generalization in plant-pollination systems. Oecologia 148(3): 365-372.
Sarospataki, M., A. Baldi, P. Batary, Z. Jozan, S. Erdos and T. Redei (2009). Factors affecting the structure of bee assemblages in extensively and intensively grazed grasslands in Hungary. Community Ecology 10(2): 182-188.
32
Schluter, A., T. Lea, S. Cannings and P. G. Krannitz (1995). Antelope-Brush Ecosystems. L. a. P. B.C. Ministry of Environment, Wildlife Branch. Victoria, B.C.: 6.
Seaton, R., Ed. (2003). Ecosystem at risk: Antelope-brush restoration - proceedings. BC, Canada, Brinkman and Associates Reforestation Ltd.
Sjodin, N. E., J. Bengtsson and B. Ekbom (2008). The influence of grazing intensity and landscape composition on the diversity and abundance of flower-visiting insects. Journal of Applied Ecology 45(3): 763-772.
Soderstrom, B., B. Svensson, K. Vessby and A. Glimskar (2001). Plants, insects and birds in semi-natural pastures in relation to local habitat and landscape factors. Biodiversity and Conservation 10(11): 1839-1863.
Sokal, R. R. and F. J. Rohlf (1995). Biometry: the principles and practice of statistics in biological reseach. New York, W.H. Freeman and Company.
Sugden, E. A. (1985). Pollinators of Astragalus monoensis Barneby (Fabaceae) - New host records - Potential impact of sheep grazing. Great Basin Naturalist 45(2): 299-312.
Vazquez, D. P., V. Aschero and E. L. Stevani (2008). Livestock grazing, habitat protection and diversity of bees and wasps in the Central Monte desert. Rev. Soc. Entomol. Argent. 67(3-4): 10.
Vazquez, D. P., W. F. Morris and P. Jordano (2005). Interaction frequency as a surrogate for the total effect of animal mutualists on plants. Ecology Letters 8(10): 1088-1094.
Volkl, W., H. Zwolfer, M. Romstockvolki and C. Schmelzer (1993). Habitat management in calcareous grasslands - Effects on the insect community developing in flower heads of Cynarea. Journal of Applied Ecology 30(2): 307-315.
Vulliamy, B., S. G. Potts and P. G. Willmer (2006). The effects of cattle grazing on plant-pollinator communities in a fragmented Mediterranean landscape. Oikos 114(3): 529-543.
Wikeem, B. and S. Wikeem (2004). The Grasslands of British Columbia. Kamloops, B.C., Grasslands Conservation Council of British Columbia.
Williams, N. M., E. E. Crone, T. H. Roulston, R. L. Minckley, L. Packer and S. G. Potts (2010). Ecological and life-history traits predict bee species responses to environmental disturbances. Biological Conservation 143(10): 2280-2291.
Wilson, E. O. (1987). The little things that run the world (the importance and conservation of invertebrates). Conservation Biology 1: 2.
33
Xie, Z. H., P. H. Williams and Y. Tang (2008). The effect of grazing on bumblebees in the high rangelands of the Eastern Tibetan Plateau of Sichuan. Journal of Insect Conservation 12(6): 695-703.
Yoshihara, Y., B. Chimeddorj, B. Buuveibaatar, B. Lhaquasuren and S. Takatsuki (2008). Effects of livestock grazing on pollination on a steppe in eastern Mongolia. Biological Conservation 141(9): 2376-2386.
Zuur, A. F., E. N. Ieno and G. M. Smith (2007). Analysing ecological data. USA, Springer.
34
Tables
Table 2.1. Site characteristics of focal shrubsteppe sites in the Southern Okanagan Valley, British Columbia. The first two letters of the site abbreviation designate a grazed and ungrazed pair. AUM refers to Animal Unit Month, where 1 AUM is equivalent to the forage removed by one 454 kg cow grazing for one month (Gayton 2003), and 1 AUM/ha is considered sufficient to maintain dry bunchgrass habitat in good range condition (McLean and Marchland 1968).
Site abbr.
Site Name Area (ha)
Elevation (m)
Slope (%)
Grazing regime Description
HLU Haynes Lease Ecological Reserve
50 337 9 Ungrazed 30 yrs + Antelope-brush; valley bottom
HLG Haynes Lease -Calf pasture
43 314 7 Grazed yearly from April 1-30th; 14 AUMs
Antelope-brush; valley bottom
OKU Kennedy Bench Antelope-brush Conservation Area
40 448 3 Ungrazed 40 yrs + Antelope-brush; valley side bench
OKG Mt. Oliver Protected Area
260.5 503 5 Grazed yearly from April 15- May 15; 72 AUMs
Table 2.2. Summary of the total abundance, richness and diversity of pollinator-attractive flowering plants and flower visitors (hereafter pollinators) for eight shrubsteppe study sites in the southern Okanagan, British Columbia.
Site abbr.
Flowering plants Pollinators
Total floral unit abundance
Diversity (1-D)
Richness (Chao2)
Richness (Actual)
Total pollinator Abundance
Diversity (1-D)
Richness (Chao2)
Richness (Actual)
HLU 361 0.3310 13.75 12 745 0.8865 170.11 95
HLG 143 0.2305 5.00 5 598 0.8720 142.10 87
OKU 873 0.5978 20.12 20 725 0.8578 198.17 94
OKG 474 0.4537 23.08 19 1227 0.9040 139.53 98
WLU 729 0.6805 21.63 19 629 0.9671 152.08 108
WLG 645 0.5578 27.15 24 895 0.9462 172.88 130
SOU 1382 0.6805 27.09 26 984 0.9710 171.48 120
SOG 1118 0.5578 21.88 20 514 0.9533 144.21 96
36
Table 2.3. The effects of livestock grazing and sample episode on the abundance, richness and diversity of all pollinators, and on pollinator functional groups defined by nesting location or taxonomic (and so resource-based) affiliations. GLMMs were used to investigate grazing impacts on pollinator abundance and actual species richness, while mixed models were used to investigate impacts on pollinator diversity. Simpson’s index of diversity was arcsine square-root transformed for analysis.
37
Figures
Figure 2.1. Map of study area in the Southern Okanagan Valley, B.C. The four paired sample sites (grazed and ungrazed) are denoted by different coloured symbols. The WL and SO pairs are located in big sagebrush shrubsteppe, while the OK and HL pairs are in antelope-brush shrubsteppe.
38
0
20
40
60
80
100
120
140
0
20
40
60
80
100
120
140
Number of Individuals
Nu
mb
er
of S
pe
cie
s
0 200 400 600 800 1000 1200
Haynes Lease (HL)
Mt. Oliver/Kennedy bench (OK)
S. Okanagan Grasslands (SO)
White Lake (WL)
Grazed
Grazed
Ungrazed
Ungrazed
Ungrazed
Ungrazed
0
20
40
60
80
100
120
140
Grazed
0 200 400 600 800 1000 1200
0
20
40
60
80
100
120
140
Grazed
Figure 2.2. Sample-based rarefaction curves, rescaled to individuals, for pollinator species richness in all eight sample sites, paired on the basis of similar environmental characteristics except for the presence of grazing livestock.
39
Pollinator type
And
reni
dae
Api
s m
ellif
era
Api
dae
Col
letid
aeH
alic
tidae
Meg
achi
lidae
Syr
phid
aeBom
bylid
aeO
ther
Dip
tera
Bee
tles
But
terflie
s/M
oths
Was
ps
Num
ber
of in
div
iduals
caught
0
500
1000
1500
2000
2500
3000
3500
Grazed
Ungrazed
47
35 11
33 517
41
5917
181
Figure 2.3. The number of individuals caught in pan-trap surveys for all grazed and ungrazed sites. The number above each bar represents the taxonomically distinguished groups: species for bees [mining bees (Andrenidae); honeybee (Apis mellifera); bumblebees, digger bees, small carpenter bees (Apidae); plasterer bees (Colletidae); sweat bees (Halictidae); mason bees and leaf cutter bees (Megachilidae)], Syrphid flies and Bombyliid flies; morphospecies for beetles, butterflies, moths and wasps.
40
Shrub
Grass
Forb
Bare so
il
Crust
Litter
Grass
Forb
Me
an
pe
rce
nt co
ve
r ±
1 S
E
0
10
20
30
40
Grazed
Ungrazed
Me
an
ma
xim
um
he
igh
t (c
m)
± 1
SE
0
20
40
60
80
100
Vegetation and ground layers
**
*
*
*
Figure 2.4. The effects of livestock grazing on the percent cover of vegetation and ground layers and maximum height of grasses and forbs. Note the different scale for percent cover and height variables. Significant effects are indicated by an asterisk: P < 0.01.
41
0 2 4 6 8
e-1
e0
e1
e2
Sample episode
1 2 3 4 5 6 7 8
LS
me
an
s o
f flo
ral u
nit
abundance a
nd r
ichness ±
1S
E
e-1
e0
e1
e2
Richness
Abundance
Grazed
Ungrazed
Figure 2.5. Least square means of the natural logarithm of flowering plant abundance and richness between grazed and ungrazed sites, over eight sampling episodes. Floral richness is based on Chao2 richness estimates. Flowering plants were surveyed every two weeks from late March until late July.
42
1 2 3 4 5 6 7 8
e-1
e0
e1
e2
Sample episode
1 2 3 4 5 6 7 8
LS
me
an
s o
f flo
ral u
nit
ab
un
da
nce
an
d r
ich
ne
ss ±
1S
E
e-1
e0
e1
e2
Richness
Abundance
Antelope-brush
Big sagebrush
Figure 2.6. Least square means of the natural logarithm of flowering plant abundance and richness between antelope-brush and big sagebrush sites, over eight sampling episodes. Floral richness is based on Chao2 richness estimates. Flowering plants were surveyed every two weeks from late March until late July.
43
Sample episode
0 2 4 6 8
LS
me
an
s o
f to
tal p
olli
na
tor
abundance a
nd r
ichness ±
1S
E
e0
e1
e2
1 2 3 4 5 6 7 8
e0
e1
e2
Richness
Abundance
Grazed
Ungrazed
Figure 2.7. Least square means of the natural logarithm of total pollinator abundance and richness between grazed and ungrazed sites, over eight sampling episodes. Pollinators were sampled every two weeks from late March until late July.
44
1 2 3 4 5 6 7 8
LS
me
an
s o
f to
tal p
olli
na
tor
ab
un
da
nce
an
d r
ich
ne
ss ±
1S
E
e0
e1
e2
Sample episode
1 2 3 4 5 6 7 8
e0
e1
e2
Richness
Abundance
Antelope-brush
Big sagebrush
Figure 2.8. Least square means of the natural logarithm of total pollinator abundance and richness between antelope-brush and big sagebrush sites, over eight sampling episodes. Pollinators were surveyed every two weeks from late March until late July.
45
Axis1
-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5
Axis
2
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5Early-flowering
spp.
Late-floweringspp.
Early/late-flowering spp. Mid-flowering spp.
Infrequent across sitesCommon across sites
Grazed
Ungrazed
Management:
Antelope-brush
Big sagebrush
Shrubsteppe type:
1
2
3
4
5
6
7
8
Sample episode:
Figure 2.9. NMDS of sites in flowering plant species space, over eight sampling episodes. The site management regime (grazed vs. ungrazed) is coded with open and filled symbols, shrubsteppe type is coded by symbol shape and sampling date is coded by colour. The axes are labelled with the traits of floral species that are significantly correlated with the NMDS output.
46
Axis 1
-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0
Axis
2
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
AndrenaWasps
Lasioglossum
Agapostemon
Nomada
Eucera
Andrena
Apis mellifera
Sample episode:
Cerambycidae
Grazed
Ungrazed
Management:
Antelope-brush
Shrubsteppe type:
Big sagebrush
1
2
3
4
5
6
7
8
Figure 2.10. NMDS of sites in pollinator species space, over eight sampling episodes. The site management regime (grazed vs. ungrazed) is coded with open and filled symbols, shrubsteppe type is coded by symbol shape and the sampling date is coded by colour. Pollinators associated with axes were significantly correlated with the NMDS output.
47
Chapter 3 A comparison of plant-pollinator network structure between British Columbia’s endangered shrubsteppe habitats
Introduction
The vast majority of flowering plants are dependent on animals, primarily insects,
for pollination (Ollerton et al. 2011). Thus, through the facilitation of plant reproduction,
pollinators play a vital role in maintaining natural ecosystems and agricultural
productivity. Concern over the fate of pollinator communities is rising, however, as
reports of pollinator declines have surfaced in numerous places around the world
(Kearns et al. 1998; Potts et al. 2010), with some areas also reporting parallel declines in
pollinator-dependent plants (Biesmeijer et al. 2006). These reports have highlighted the
importance of considering pollinator communities in future conservation and
management efforts (Potts et al. 2010).
Over the last decade, the study of pollinators has benefited from taking a
community-based analytical approach, made possible by examining plant-pollinator
interaction networks (Bascompte 2007; 2009; Vazquez et al. 2009). In contrast to
traditional analyses, which focus on quantifying species abundances, plant-pollinator
networks provide a more functional perspective by identifying which species interact
within a community, how frequently species interact, and how these interactions are
structured (Bascompte and Jordano 2007). Recently, studies have shown that network
structure can be influenced by anthropogenic disturbances (e.g., Lopezaraiza-Mikel et
al. 2007; Aizen et al. 2008; Yoshihara et al. 2008), even when species richness within a
community is unaffected (Tylianakis et al. 2007). These results emphasize the
importance of an analytical approach that addresses species interactions in ecological
48
communities, in addition to traditional abundance and richness indices. Although there
is still much to be learned about plant-pollinator network structure, its potential use in
conservation and management is beginning to be realized (e.g., Gibson et al. 2006;
Carvalheiro et al. 2008; Forup et al. 2008).
Plant-pollinator networks have been found to have conserved network-level
structural properties that have implications for community resilience (Table 3.1;
Memmott et al. 2004; Bascompte and Jordano 2007). In the context of plant-pollinator
networks, resilience generally concerns a network’s capacity to resist secondary
extinctions following species loss (Memmott et al. 2004; Tylianakis et al. 2010), thus
increasing the ability of the community to absorb disturbance and retain essentially the
same structure and function. Although many network structural properities can be
measured, connectance, generalization, asymmetry and nestedness may be the most
useful properties for understanding resilience (Elle et al. in press).
One of the most commonly measured network properties is connectance, a
measure of interaction richness, which is calculated as the proportion of realized
interactions out of all possible interactions within a network (Jordano et al. 2006). When
compared between networks of similar size (i.e. similar species richness), increased
connectance indicates increased generalization of the species involved (Tylianakis et al.
2010) and confers higher network resilience through redundancy in interaction partners
(Thebault and Fontaine 2010). That is, the more interaction partners each species has,
i.e. the more pollinators each plant has and the more plants each pollinator visits, the
less likely the loss of an interaction partner will result in secondary population declines or
extinctions. However, it is well-established that connectance decreases with increasing
network size and is thus inappropriate to compare across networks of different size
(Vazquez et al. 2009). Furthermore, connectance is based on binary data and thus does
not incorporate the frequency of interactions between species in a network, which is an
important component in assessing species generalization and in determining how
detrimental the loss of an interaction partner may be. Quantitative metrics of
generalization (generality and H2’ specialization index) which evaluate the average
number of species each species in the network interacts with, account for heterogeneity
in interaction frequency and are thus an appropriate way to compare interaction diversity
49
among networks of different sizes (Bluthgen et al. 2006; Albrecht et al. 2010; Tylianakis
et al. 2010).
Asymmetry and nestedness are two other commonly measured network
properties that have implications for network resilience. Plant-pollinator networks are
usually asymmetric in terms of degree and interaction strength (Vazquez and Aizen
2004; Bascompte et al. 2006). Asymmetry in degree refers to the tendency of
specialized species to interact with more generalized species (Vazquez and Aizen
2004), while asymmetry in interaction strength refers to the tendency of species with
strong effects to usually experience weak reciprocal effects from their interaction
partners (Bascompte et al. 2006). A generalist plant, for example, may be the dominant
pollen source for a number of pollinator species, but does not rely strongly on any one of
these species for pollen transfer. Increased asymmetry is thought to confer greater
network resilience by contributing to the persistence of more specialized species, since
the abundance of their generalist interaction partners tend to be higher and less prone to
fluctuation (Bascompte et al. 2006; Bascompte 2009). When calculated separately for
each species in a network, interaction strength asymmetry also provides a method to
identify which plants and pollinators are strongly relied upon within the network (Hegland
et al. 2010) and thus may be good candidates for monitoring programs (Elle et al. in
press). Plant-pollinator networks are also usually nested, such that they are organized
around a core of interacting generalists, some of which also interact with specialists
(Bascompte et al. 2003). Increased nestedness is thought to confer network resilience
by increasing the persistence of more specialized species, similar to asymmetry, and by
creating an interacting core of generalists that remains intact if more specialized species
are lost from the network (Memmott et al. 2004; Fortuna and Bascompte 2006).
The aforementioned structural properties, among others, can be compared
between different networks to indicate which may be more sensitive to disturbance or
investigate how disturbances influence community structure. For example, many studies
have investigated how introduced species, particularly plants, influence network
structure (e.g., Lopezaraiza-Mikel et al. 2007; Aizen et al. 2008; Bartomeus et al. 2008;
Vila et al. 2009; Kaiser-Bunbury et al. 2010). Other studies have compared the
robustness of different networks to species loss, for example those in restored vs.
50
reference heathland sites (Forup et al. 2008) and lightly grazed vs. heavily grazed
rangeland (Yoshihara et al. 2008).
Thus far, studies taking a network approach to plant-pollinator conservation have
rarely incorporated the effects of temporal dynamics (e.g., seasonality) on network
structure (but see Valdovinos et al. 2009; Hagen and Kraemer 2010). The few studies
that have explored the temporal dynamics of plant-pollinator networks (e.g., Basilio et al.
2006; Medan et al. 2006; Olesen et al. 2008) have shown that some network properties
have strong temporal dynamics, such as connectance and nestedness. Taking a
temporal approach to network analysis could therefore aid in the development of
conservation strategies by indicating how network structure changes over time and
suggesting when networks may be more sensitive to disturbance.
In North America, grasslands and shrubsteppe are among the continent’s most
species-rich and threatened ecosystems. Conservation concerns in these ecosystems
include extensive fragmentation and degradation due to agricultural and urban
development (Curtin and Western 2008; Peart 2008). Within Canada, the shrubsteppe
habitats of the south Okanagan Valley, British Columbia, are recognized as some of the
most biologically diverse and threatened habitats. Antelope-brush shrubsteppe in
particular, supports a disproportionately high percentage of Canada’s endangered and
threatened species and is considered one of the top four most endangered ecosystems
in the country (Schlute et al. 1995; Dyer and Lea 2003). Due to its position on valley
bottoms and low elevation valley side benches, 68% of antelope-brush habitat has been
lost to agriculture and urban development and was still being lost at a rate of 2% per
year within the last decade (CDC 2003; Dyer and Lea 2003). Big sagebrush
shrubsteppe, which also supports numerous endangered and threatened species,
occurs at higher elevations than antelope-brush shrubsteppe and has suffered less from
habitat loss and fragmentation (Lea 2008). Fairly little is known about the pollinator
communities of this region, though they are hypothesized to be very diverse due to the
sub-desert climate. Pollinators and the flowering plants with which they interact are a
vital component of shrubsteppe biodiversity, together providing vegetation structure and
forage that is vitally important for many species of herbivores, insectivores, granivores
and frugivores that also inhabit these ecosystems (Gilgert and Vaughan 2011). Thus,
51
understanding the structure of the plant-pollinator communities in shrubsteppe habitats
is important for their effective management and conservation.
In this study, I describe plant-pollinator interaction networks from antelope-brush
and big sagebrush shrubsteppe generated from plant-pollinator interaction sampling
completed over an entire flowering season. I investigate differences in network structure
between antelope-brush and big sagebrush shrubsteppe that may have consequences
for community resilience to disturbance and explore which plant and pollinator species
are functionally important in each habitat. I also examine temporal variability in network
structure to investigate how these plant-pollinator networks, and sensitivity to
disturbance, change over the course of the flowering season. I conclude by
summarizing the practical implications of my findings for the conservation of shrubsteppe
plant-pollinator communities of the southern Okanagan.
Methods
Study sites
The shrubsteppe ecosystems of western North America range from the Great
Basin in eastern California and Nevada northward through the Columbia Basin and into
south central British Columbia (Mack 1981; Gayton 2003). In B.C., shrubsteppe
ecosystems occur primarily in the southern Okanagan and Similkameen Valleys, and in
the Thompson River Valley around Kamloops (Mack 1981; Krannitz 2008).
Within the Okanagan Valley, shrubsteppe ecosystems occupy the valley floor,
benches and lower slopes, ranging from approximately 250 m to 700 m (Wikeem and
Wikeem 2004). At slightly higher elevations, a sparse Ponderosa Pine (Pinus
ponderosa) over-story accompanies the shrubsteppe vegetation (Nicholson et al. 1991).
The shrubsteppe habitat is dominated by either antelope-brush or big sagebrush with an
understory of widely spaced bunchgrasses mixed with a variety of wildflowers and a
well-developed cryptogamic crust (Wikeem and Wikeem 2004).
I selected eight sites in the southern Okanagan Valley; four in antelope-brush
shrubsteppe and four in big sagebrush shrubsteppe (Table 3.2). Sites were initially
52
chosen to investigate the impacts of livestock grazing on plant and pollinator
communities, thus two sites in each shrubsteppe habitat type are lightly spring grazed
for a month’s time on a yearly or bi-yearly basis. Previous analysis has shown this
disturbance does not significantly impact flowering plant and pollinator diversity or
community composition, although vegetation structure does change with grazing (see
Chapter 2). All sites were a minimum of 20 hectares and were connected to contiguous
shrubsteppe, grassland or ponderosa pine forest on at least one side. Within each site I
selected areas that would be suitable for sampling, i.e. encompassing the most
prevalent shrubsteppe vegetation type of the site and excluding less common landscape
features such as drainage areas. Within these areas a point was randomly selected on
an aerial photo and used as the starting corner for a 1-ha sampling plot, within which I
conducted all plant-pollinator interaction sampling.
Sampling plant-pollinator interactions
I sampled plant-pollinator interactions at each site over the entire flowering
season (March-July 2010). Flower visitors were collected with a net directly off of
flowering plants so that species-level interactions could be identified and their frequency
assessed. Plant-species-specific netting is considered more appropriate than transect-
based netting in heterogeneous environments like shrubsteppe, as netting effort is
allocated more evenly among plant species and is more likely to detect uncommon
interactions (Gibson et al. 2011). I conducted netting surveys at roughly one-week
intervals, in fair weather conditions between 9:30 and 16:00 hours. During each netting
survey, two 10 minute netting bouts were conducted on each flowering plant species in
bloom. On occasion, a single netting bout was conducted if a plant species was just
beginning to bloom and there were few open flowers. During netting bouts, samplers
walked throughout the plot catching all observed flower visitors that came into contact
with the reproductive organs of the focal plant species. Sampling bout times (AM, mid-
day, PM) for each plant species were varied within and between netting surveys to
encompass the flight time of most pollinating insects. I attempted to allocate consistent
netting effort to each plant species across all sites, but differences in bloom length
precluded complete consistency. Thus, the overall netting effort of each site reflects the
flowering plant diversity and phenology of that site. Plant species with very small
flowers, such as spring draba (Draba verna), and species present at only a single site in
53
low abundance (< 10 flowering individuals) were not included in the study. All flower
visitors were identified to the lowest taxonomic level possible, primarily species or
morphospecies. Bees and wasps (Hymenoptera), beetles (Coleoptera), and flies
(Diptera) were collected for identification, whereas butterflies (Lepidoptera) and
hummingbirds (Trochilidae) were identified without being captured. The interaction
networks resulting from this sampling are most appropriately termed flower-visitor
networks, as I did not assess the role each visitor played in plant pollination, but
following convention I will call them plant-pollinator networks hereafter.
Each site was surveyed 13 or 14 times across the flowering season, but to
facilitate comparison of network structural properties across sites over time, each
network was reduced to 12 netting surveys for analysis. The first survey of the flowering
season was removed for all networks because of low floral availability and limited
pollinator activity. If a site was surveyed an extra time (14 rather than 13 samples), the
last netting survey was also removed. Each network was then divided into three
seasonal sub-networks (early, mid and late flowering season), each consisting of four
netting surveys spanning approximately 35 days.
Quantifying plant-pollinator network structure
I constructed quantitative plant-pollinator interaction matrices for all complete and
seasonal sub-networks. In these matrices, rows and columns represent flowering plant
and pollinator species, respectively, while cells record the frequency of interactions
between each plant and pollinator species. To investigate if plant-pollinator community
structure differs between habitat types over the course of the flowering season I
calculated the following properties for all networks: number of plant species, number of
pollinator species, network size, connectance, plant generality and pollinator generality,
H2’ specialization index, interaction strength asymmetry, and nestedness. All network
properties were calculated using the bipartite package of R v.0.95.263 (R Development
Core Team, 2011; see Appendix D for network property formulas).
I calculated network size as the sum of all plant and pollinator species in the
network, as defined by Dormann et al. (2009). Connectance was calculated as the
realized proportion of possible interactions (number of realized interactions/ total number
54
of possible interactions). Although connectance is ineffective for comparison across
networks of different size, as those in this study are, it does provide a rough gauge of
sampling effort through the comparison of connectance values with previously published
networks of similar size.
I calculated overall plant and pollinator generalization using the generality and
vulnerability indices originally derived by Bersier et al. (2002) for food web analysis,
which have recently been applied to mutualistic networks by Albrecht et al. (2010).
Pollinator generality (same as the generality index) is measured as the mean number of
plant species visited by a pollinator species weighted by interaction strength. Where
interaction strength is a measure of the dependence of one species on another and is
well estimated by interaction frequency (Vazquez et al. 2005). Plant generality (same as
the vulnerability index) is measured as the mean number of pollinator species visiting a
plant species weighted by interaction strength.
To characterize the degree of network-level generalization, including both plants
and pollinators, I used the H2’ specialization index developed by Bluthgen et al. (2006).
H2’ ranges between 0 and 1 for extreme generalization and specialization, respectively.
This index is useful for comparison across multiple networks as it is robust to differences
in network size and sampling intensity (Bluthgen et al. 2006). The H2’ index
characterizes the degree of specialization in a network based on the deviation of a
species’ realized number of interactions from that expected from the total number of
interactions for that species. The underlying equation is the same as Shannon’s
interaction diversity (H2), but the value computed for a given network is standardized
against the minimum and maximum possible for the same distribution of interaction
totals (Bluthgen et al. 2006; Dormann et al. 2009).
I calculated interaction strength asymmetry (hereafter asymmetry) as per
Vazquez et al. (2007), which ranges between -1 and 1. Using this method, independent
asymmetry values are calculated for each species in a network and then averaged to
obtain a network-level asymmetry value. At the species-level, an asymmetry value close
to 1 indicates that a species is strongly relied upon by its interaction partners but does
not experience strong reciprocal effects, i.e., it does not rely strongly on any one
interaction partner. Conversely, a species with an asymmetry value close to -1 relies
55
strongly on its interaction partners, but does not exert a strong reciprocal effect. At the
network level, a value closer to 1, either positive or negative, indicates high overall
asymmetry in the network (reliance between interaction partners is disproportionate),
whereas a value closer to 0 indicates that interactions within the network are more
symmetric (reliance between interaction partners is similar).
I also used species-level asymmetry values to identify functionally important
plants and pollinators. I consider a species to be of high functional importance if it has
many interaction partners and is relied strongly upon by those interaction partners.
Antelope-brush and big sagebrush habitat differ in plant and pollinator community
composition (see Chapter 2), therefore I aimed to identify and compare the top-10 plant
and pollinator species with high functional importance in each habitat type. For this
assessment I created a cumulative network for each habitat type, combining data across
all sites, and ranked species according to asymmetry and species degree (the number of
species which a species visits or is visited by). As a species may be able to interact with
more species than are available at a single site, combining data across sites provides a
more accurate estimate of each species degree and asymmetry and will identify species
that are, in general, the most functionally important in each habitat type. Plants and
pollinators were ranked separately and those species with a large species degree and
high positive asymmetry were identified.
I calculated nestedness using the NODF metric developed by Almeida-Neto et al.
(2008), which reduces the potential bias introduced by network size and asymmetry in
network dimensions (ratio of plants to pollinators) compared to the previously commonly
used nestedness metrics like matrix temperature and discrepancy (Almeida-Neto et al.
2008). The NODF metric is based on two properties of nestedness termed decreasing
fill and paired overlap. The metric measures whether the number of interaction partners
differs among plants and among pollinators in the matrix (decreasing fill), and whether
more specialized species interact with subsets of the species that more generalized
species interact with (paired overlap). The NODF metric ranges from 0 to 100 indicating
non-nestedness and perfect nestedness, respectively (Almeida-Neto et al. 2008).
Perfect nestedness implies that each species interacts only with proper subsets of those
species interacting with more generalized species (Bascompte et al. 2003).
56
Statistical analysis
To investigate whether antelope-brush and big sagebrush habitat differ in
network structural properties over the course of the flowering season I used mixed
models in SAS 9.2 (Proc MIXED; SAS Institute Inc. 2008). The models included habitat,
season and the corresponding two-way interaction as fixed effects and site nested within
habitat as a random effect. For comparison, I also used mixed models to assess the
impacts of habitat type on the structural properties of full season networks. These
models included habitat as a fixed effect and site nested within habitat as a random
effect. For all models, least square means were computed for all fixed effects.
Results
I surveyed 48 flowering plant species, 26 of which were present in both habitat
types, and collected 264 floral visitor species/morphospecies (hereafter pollinators), 112
of which were present in both habitats, across the eight sites. Overall, I recorded 2480
plant-pollinator interactions, 919 of which were unique. Full season networks ranged in
size between 43 and 170 species, while seasonal sub-networks varied between 16 and
79 species (see Appendix E for the properties of each network). Bees were the most
prevalent and species-rich pollinator group collected (66.8% of recorded interactions;
153 species), followed by flies (12.7%; 57 species), beetles (9.2%; 16 morphospecies),
wasps (7.1 %; 28 morphospecies), butterflies (4.0%; 8 morphospecies) and
hummingbirds (<1%; 1 species; Figure 3.1). The most prevalent plant families surveyed
were the aster (Asteraceae, 13 species), carrot (Apiaceae, 3 species), and lily (Liliaceae,
3 species) families.
A quantitative plant-pollinator network, including both full season and seasonal
sub-networks from both antelope-brush and big sagebrush habitat is shown in Figure
3.1. There was a trend, although non-significant, for networks to increase in size across
the flowering season (Table 3.3; Figure 3.2a), driven by a significant increase in the
number of pollinator species (Table 3.3; Figure 3.2b). Plant species richness, on the
other hand, decreased in richness late in the flowering season (Table 3.3; Figure 3.2b).
57
Additionally, networks in big sagebrush habitat tended to be larger than those in
antelope-brush habitat, but the difference was non-significant (Table 3.3; Figure 3.2a, b).
Network-level specialization, measured by the H2’ specialization index, was
unchanged throughout the flowering season, but was significantly higher in antelope-
brush networks than in big sagebrush networks (Table 3.3, Figure 3.2c). This was
reflected in the results for generality: plant generalization was significantly higher in big
sagebrush networks, and although non-significant, pollinators also tended to be more
generalized in big sagebrush habitats (Table 3.3; Figure 3.2d). Over time, pollinator
generalization remained the same, which is likely driving the consistency in overall
network-level specialization, as pollinators make up a large proportion of the species
present. Plant generalization increased over the course of the flowering season, but the
timing of this increase depended on shrubsteppe type (habitat x season interaction;
Table 3.3; Figure 3.2d). In antelope-brush networks plant generalization increased in
the mid flowering season and continued into the late season, whereas in big sagebrush
habitats the increase in plant generalization occurred late in the flowering season.
Network-level asymmetry was similar between antelope-brush and big sagebrush
shrubsteppe networks throughout the flowering season (Table 3.3; Figure 3.2e). At all
sites, there were more pollinators with negative asymmetry values (~96%) than plants
(~15%; see Appendix B for species-level asymmetry values), which indicates that
pollinators in these habitats relied more strongly on the plants they visit for floral
resources than the plants relied on them in turn for pollen transfer. As there was
approximately four times more pollinator than plant species in these habitats, network-
level asymmetry was consequently negative. Network asymmetry also became
significantly more negative late in the flowering season (Table 3.3; Figure 3.2e). This
difference was a result of a significantly more generalized plant community interacting
with a proportionally larger, but similarly generalized pollinator community during that
period of the flowering season.
Antelope-brush and big sagebrush shrubsteppe shared six of their top-10
functionally important plant species (Table 3.4). Yarrow (Achillea millefolium) had the
largest degree and was the most positively asymmetric plant in the study, interacting
with 47 and 51 species in antelope-brush and big sagebrush shrubsteppe, respectively.
58
Species from the Aster family were prominent in the top-10 lists of both habitats. Bee
species comprised 8 of the top-10 functionally important pollinators in both habitats,
three species of which were shared between shrubsteppe types. The only introduced
bee species collected (Apis mellifera; European honeybee) was included in the top-10
lists for both habitats, while the most functionally important plant species were all native.
The nestedness of networks in antelope-brush and big sagebrush differed
significantly with the period of the flowering season (habitat x season interaction; Table
3.3; Figure 3.2f). Nestedness of big sagebrush networks tended to increase across the
flowering season, while the nestedness of antelope-brush networks tended to decrease.
There was no significant main effect of either habitat type or season (Table 3.3).
Overall, nestedness values for networks in both habitats were low, suggesting
nestedness may not be a strong structural component of these plant-pollinator
communities.
Discussion
Habitat and temporal influences on network structure
Network size and generalization
There were trends in network size, although non-significant, between habitat
types and across the flowering season. Big sagebrush networks tended to be larger
than antelope-brush networks, and late-season networks tended to be larger than those
earlier in the season. It has frequently been proposed that more diverse communities
are more stable and resilient to disturbance (Macarthur 1955; Elton 1958; Tilman et al.
1996; McCann 2000). One hypothesis is that increased species richness increases
functional redundancy; in other words, it increases the number of species contributing to
the same function so that if one species is lost, ecological function (e.g. pollination) may
persist because of compensation from other species (Lawton and Brown 1993; Naeem
1998). Additionally, it is thought that the more species present in a community the
higher the odds that at least some species contributing to the same function will respond
differently to perturbations and thus be able to compensate for the loss of affected
species (Elmqvist et al. 2003). Winfree and Kremen (2009), for example, have shown
59
that diverse pollinator assemblages comprised of species that respond differently to
agricultural development are responsible for the maintenance of pollination rates in
watermelon. Also, in the network literature, increased species richness and increased
connectance (interaction richness) have been shown to increase plant-pollinator
community resilience to simulated species loss (Memmott et al. 2004; Thebault and
Fontaine 2010). In the context of my study, these results suggests plant-pollinator
communities in big sagebrush habitat may be more resilient to species loss than those in
antelope-brush habitat, and that all shrubsteppe communities are more resilient late in
the flowering season. However, a more concrete comparison of interaction redundancy
can be provided by network-level generalization measures.
For more diverse plant-pollinator communities to be more resilient to disturbance
through interaction redundancy there should be an increase in the average
generalization of the species involved, which I found. Plant-pollinator networks in big
sagebrush had more generalized species on average than those in antelope-brush
habitat. For example, 71% of plant species in big sagebrush habitats interacted with
more than 10 pollinator species, compared to only 48% in antelope-brush habitats.
Similarly, 37% of pollinators in big sagebrush habitat interacted with three or more
plants, compared to 29% in antelope-brush habitats. Specialized plants and pollinators
have long been hypothesized to be more vulnerable to disturbances, such as habitat
alteration or fragmentation, than more generalized species because the loss or decline
in even one interaction partner could lead to reproductive failure for plants or population
declines due to reduced forage for pollinators (Bond 1994; Waser et al. 1996; Aizen et
al. 2002). Thus if higher generalization levels can increase network resilience through
interaction redundancy then plant-pollinator communities in big sagebrush habitat may
be less vulnerable to disturbance. Additionally, I found that late-season communities of
both habitats contained plant species that had a wider suite of pollinators (more
generalized) on average than those blooming early in the season. Therefore, plants
blooming late in the season should be less sensitive to anthropogenic disturbances that
influence the abundance of some pollinator species (Waser et al. 1996).
60
Asymmetry
The asymmetry of antelope-brush and big sagebrush networks was similar
through time, and was significantly higher late in the flowering season. Simulation
studies suggest that network asymmetry contributes to the resilience of plant-pollinator
communities, by contributing to the persistence of more specialized species (Fortuna
and Bascompte 2006; Kaiser-Bunbury et al. 2010). Since specialists are more likely to
persist under disturbance when they interact with more generalized species, which are
often more abundant and less prone to population fluctuation, than when they interact
with other specialists. This increase in resilience rests on the assumption that rare and
more specialized species are most likely to be lost first from a community, since losing a
well-connected generalist can be very detrimental to community structure (Memmott et
al. 2004; Kaiser-Bunbury et al. 2010). Although anthropogenic disturbances or other
ecological processes can result in the selective decline of abundant and generalized
species in a network, such as bumblebee declines in Europe (Goulson et al. 2008),
theory and empirical evidence indicate that it is more likely that rare and/or specialized
species will be lost before the most functionally important mutualists (Tscharntke et al.
2002; Henle et al. 2004; Biesmeijer et al. 2006; Kaiser-Bunbury et al. 2010). In Britain,
for example, pollinators that rely on few plants for their floral resources have
experienced the largest declines over the past 30 years (Biesmeijer et al. 2006). If
asymmtery in mutualistic networks can promote network resilience, then networks of
both shrubsteppe habitats may be more resilient to disturbance late in the flowering
season. Specifically, higher network asymmetry paired with higher plant generalization
during this time period may contribute to the persistence of more specialized pollinators.
As with most plant-pollinator networks studied, network-level asymmetry values
were negative in this study. Pollinators tend to have more negative asymmetry than
plants (Vazquez et al. 2007) and are often far more abundant within networks. In the
shrubsteppe habitats I studied, most plants were generalists and many were very
generalized (> 20 interaction partners), supporting a much more diverse pollinator
community that on average interacted with only a few plants. Thus, pollinator species
tended to have a stronger reliance on the plants they visited than the plants did on them,
suggesting plant-centered conservation and monitoring is likely a good strategy in this
region.
61
Comparing asymmetry and degree between species provides a way to identify
which plants and pollinators are most functionally important within each habitat.
Although antelope-brush and big sagebrush habitat have different plant and pollinator
community composition (see Chapter 2), they do share roughly half of their top-10 most
functionally important species. Bees were the most prevalent and generally most
functionally important pollinators in both habitats. Sweat bees (Lasioglossum spp.,
Halictus spp.) and mining bees (Andrena spp.) were the most common functionally
important native bees, followed by bumblebees (Bombus spp.), small carpenter bees
(Ceratina spp.), and mason bees (Osmia spp.). Even when extended to include the top-
20 pollinators, bees dominated functionally in big sagebrush habitats, along with
Cerambycid beetles, while in antelope-brush habitats wasps (Vespids, Chrysidids and
Sawflies) and flies (Syrphids and Tachinids) also became quite important.
Introduced plants did not rank highly in terms of functional importance in either
habitat. This suggests that although introduced plants are integrated into the pollination
networks of these sites, at their current abundance they are unlikely to be attracting a
considerable number of pollinator visits away from native species. The one introduced
pollinator collected in the study, the European honeybee, was ranked within the top-10
functionally important pollinators in both habitats. Although present in both, honeybees
were far more prevalent in antelope-brush habitat, comprising 12.5% of all interactions
compared to only 1.5% in big sagebrush habitat, likely because antelope-brush habitat is
closer in proximity to the valley bottom orchards that use managed honeybees for
pollination services.
Nestedness
Although overall nestedness between the two habitats was similar, there was a
trend for nestedness to be larger in big sagebrush networks late in the flowering season.
Nestedness in big sagebrush networks increased over time while it decreased in
antelope-brush networks. Higher nestedness, like asymmetry, indicates increased
tendency of specialist species to interact with generalists, but also indicates an
increased tendency for generalists to interact amongst themselves, which together buffer
against secondary extinctions (Memmott et al. 2004; Tylianakis et al. 2010). Because
networks in both habitats are similarly asymmetric, it is likely an increase in the number
62
of generalized interactions in big sagebrush habitat that is the cause for the observed
differences. That said, networks in both habitats had low nestedness values overall
(between 4-11), with all network values falling well below the range of NODF nestedness
values commonly reported in the literature (commonly published NODF range: 20-60;
e.g., Bosch et al. 2009; Hegland et al. 2010; Sugiura 2010; Chacoff et al. 2012; Vilhena
et al. 2012). This suggests nestedness is not a large structural attribute of these
communities. Although it was previously suggested that nestedness was a universal
property of plant-pollinator networks, recent studies indicate that some plant-pollinator
networks are not in fact nested (Ulrich et al. 2009; Joppa et al. 2010; Gibson et al. 2011).
NODF nestedness is sensitive to matrix fill (the number of realized interactions between
species in a network; Almeida-Neto et al. 2008), as all nestedness metrics are, thus it is
possible that higher sampling effort could have produced a more nested structure.
However, connectance values of all full and seasonal sub-networks were comparable to
networks of similar size in the published literature (Memmott 1999; Olesen et al. 2002;
Vazquez and Simberloff 2003; Bezerra et al. 2009; Albrecht et al. 2010), thus I feel
confident that my sampling effort was adequate and that nestedness is not a large
structural component of these plant-pollinator communities.
Caveats to the current network approach
Several caveats to this study are worth noting. Firstly, I quantified pollinator
visitation to flowering plants and not pollination. However, Vazquez et al. (2005) has
showed that the most frequent pollinators to a flowering plant species are likely to be the
most important pollinators. Secondly, sampling effort was not only related to flowering
plant phenology but also species richness. This resulted in equal netting effort among
species of similar bloom length, but different netting effort across sites. Therefore big
sagebrush sites, which tended to have higher plant richness, had increased overall
sampling effort which may have influenced recorded pollinator richness. However, more
species-rich floras commonly support higher pollinator diversity (Kevan 1999). Thirdly,
these networks exclude flowering plant species that were infrequent and in low
abundance, thus do not capture the entire plant-pollinator networks of these sites.
Although I feel confident the networks are a good representation of these plant-pollinator
communities, further work would be needed to address the pollinator assemblages of
rare plant species. Lastly, although taking a sub-network approach can provide
63
additional valuable information about network structure, it also requires analyzing
smaller networks. Extensive simulations recently completed by Dormann et al. (2009)
suggest certain network properties, such as H2’ specialization index, are sensitive to
asymmetry in network dimensions (ratio of plants to pollinators) when networks are
small. The authors suggest networks have a minimum of 50 species, which is the
average size of my sub-networks, before such indices are used with confidence. As
there was good overall concordance between the influence of habitat on network
structure generated through the seasonal and full season approach, I have confidence
the sub-network properties generated were representative of each network and were not
an artefact of their size.
Practical implications
Both of the shrubsteppe habitats of the Okanagan Valley support diverse plant
and pollinator communities. My network analysis suggests that the plant-pollinator
communities of the more critically endangered antelope-brush shrubsteppe may be more
sensitive to disturbances than those in big sagebrush, such as increased habitat
alteration or fragmentation, as they have a tendency to be less diverse and are less
generalized on the whole. These may be natural differences characteristic of each
plant-pollinator community, or could be a result of the differences in anthropogenic
disturbance experienced regionally by these shrubsteppe habitats. If so, my results
suggest that further fragmentation and alteration of antelope-brush habitats is likely to
have negative effects on plant-pollinator communities. Although their community
composition differs, these shrubsteppe habitats support a number of the same plant
species and share more than half of their pollinator species when singletons are not
considered. Additionally, the habitats share roughly half of their top-10 functionally
important plants and pollinators. Thus, the management and protection of one habitat is
likely to be very beneficial to the plant-pollinator communities of the other. Protection or
restoration of big sagebrush habitat near remaining antelope-brush fragments will likely
promote plant and pollinator diversity by reducing habitat isolation. Also, due to the
many species present in only one of the shrubsteppe habitat types, an effort towards
management and conservation of both habitats will be important for maintaining regional
diversity. The networks of both habitats appear to be better buffered against the loss of
64
pollinators than that of plants, suggesting that monitoring and management of the floral
communities may be most important.
Network structural properties also indicated that early-season communities may
be more sensitive to disturbance than late-season communities. The majority of
remaining antelope-brush and big sagebrush habitat is grazed by livestock at some point
on a yearly or bi-yearly basis (Lea 2008). Although low-intensity spring grazing has
been found not to negatively affect shrubsteppe plant and pollinator communities (see
Chapter 2), grazing at higher intensities may have less impact on plant-pollinator
communities if it can be shifted away from early spring to later in the flowering season
(June-July). Comparing network structural properties temporally, although rarely
pursued in a conservation context, may be a promising additional component of using
plant-pollinator networks to address applied ecological questions.
Often conservation aims to preserve endemic or endangered species, but taking
a network approach highlights that monitoring and preserving some of the more
common, generalist taxa may be more beneficial for preserving overall community
diversity and functioning (Dupont et al. 2003; Hegland et al. 2010). Networks allow
functionally important species to be identified which not only provide good candidates for
monitoring programs but also suggest plants species that are likely to be most beneficial
in restoration programs (Hegland et al. 2010; Elle et al. in press). That said, networks
also allow specialist species to be identified. There were 12 oligolectic bee species
collected in these habits: Andrena astagali, A. microchlora, Colletes consors, Duforea
trochantera, Heriades cressoni, Megachile perihirta, M. umatillensis, Osmia californica,
O. coloradensis, O. marginipennis, O. montana and Perdita fallax. Only antelope-brush
habitat supports all 12 specialist species, as H. cressoni was collected exclusively in
antelope-brush habitats and the floral hosts of M. umatillensis and P. fallax only grow in
dry, low-elevation shrubsteppe. If preservation of specialist bees is a conservation goal,
protection of antelope-brush habitat should be a priority.
Conclusions and future directions
I found that plant-pollinator networks in big sagebrush habitat may be more
resilient to disturbance than those in the more critically endangered antelope-brush
65
shrubsteppe habitat, through a trend towards larger network size and significantly
greater network-level generalization. Additionally, late-season communities may also be
more resilient than those early in the season as they tended to be larger, were more
asymmetric and had more generalized plant species. Comparing plant-pollinator
network structure to investigate differences in resilience between threatened and
endangered communities has the potential to contribute valuable information to
conservation priority decision-making. Additionally, the species-level information that
can be deduced from network analysis, such as assessing the functional importance of
species, can provide useful information for habitat monitoring and restoration. It is,
however, still early in the study of plant-pollinator interaction networks and much still
needs to be learned about how strongly structural differences detected through network
analysis translate into differences in network resilience in natural communities. Future
research should focus on challenging network theory with empirical data to gain a better
understanding of how network structural parameters respond to different natural and
anthropogenic disturbances and what these responses mean functionally for real
communities. The development of networks as research and conservation tools, which
are capable of understanding both species- and community-level interactions, will be
important for the conservation and sustainability of pollinations systems in the Okanagan
and around the world.
66
References
Aizen, M. A., L. Ashworth and L. Galetto (2002). Reproductive success in fragmented habitats: do compatibility systems and pollination specialization matter? Journal of Vegetation Science 13(6): 885-892.
Aizen, M. A., C. L. Morales and J. M. Morales (2008). Invasive mutualists erode native pollination webs. Plos Biology 6(2): 396-403.
Albrecht, M., M. Riesen and B. Schmid (2010). Plant-pollinator network assembly along the chronosequence of a glacier foreland. Oikos 119(10): 1610-1624.
Almeida-Neto, M., P. Guimaraes, P. R. Guimaraes, R. D. Loyola and W. Ulrich (2008). A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement. Oikos 117(8): 1227-1239.
Bartomeus, I., M. Vila and L. Santamaria (2008). Contrasting effects of invasive plants in plant-pollinator networks. Oecologia 155(4): 761-770.
Bascompte, J. (2007). Networks in ecology. Basic and Applied Ecology 8(6): 485-490.
Bascompte, J. (2009). Mutualistic networks. Frontiers in Ecology and the Environment 7(8): 429-436.
Bascompte, J. and P. Jordano (2007). Plant-animal mutualistic networks: The architecture of biodiversity. Annual Review of Ecology Evolution and Systematics. Palo Alto, Annual Reviews. 38: 567-593.
Bascompte, J., P. Jordano, C. J. Melian and J. M. Olesen (2003). The nested assembly of plant-animal mutualistic networks. Proceedings of the National Academy of Sciences of the United States of America 100(16): 9383-9387.
Bascompte, J., P. Jordano and J. M. Olesen (2006). Asymmetric coevolutionary networks facilitate biodiversity maintenance. Science 312(5772): 431-433.
Basilio, A. M., D. Medan, J. P. Torretta and N. J. Bartoloni (2006). A year-long plant-pollinator network. Austral Ecology 31(8): 975-983.
Bersier, L. F., C. Banasek-Richter and M. F. Cattin (2002). Quantitative descriptors of food-web matrices. Ecology 83(9): 2394-2407.
Bezerra, E. L. S., I. C. S. Machado and M. A. R. Mello (2009). Pollination networks of oil-flowers: a tiny world within the smallest of all worlds. Journal of Animal Ecology 78: 1096-1101.
Biesmeijer, J. C., S. P. M. Roberts, M. Reemer, R. Ohlemuller, M. Edwards, T. Peeters, A. P. Schaffers, S. G. Potts, R. Kleukers, C. D. Thomas, J. Settele and W. E. Kunin (2006). Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands. Science 313(5785): 351-354.
67
Bluthgen, N., F. Menzel and N. Bluthgen (2006). Measuring specialization in species interaction networks. BMC Ecology 6(9).
Bond, W. J. (1994). Do mutualisms matter? Assessing the impact of pollinator and disperser disruption on plant extinction. Philosophical Transactions of the Royal Society of London B Biological Sciences 344(1307): 83-90.
Bosch, J., A. M. M. Gonzalez, A. Rodrigo and D. Navarro (2009). Plant-pollinator networks: adding the pollinator's perspective. Ecology Letters 12(5): 409-419.
Carvalheiro, L. G., E. R. M. Barbosa and J. Memmott (2008). Pollinator networks, alien species and the conservation of rare plants: Trinia glauca as a case study. Journal of Applied Ecology 45(5): 1419-1427.
CDC, B. C. (2003). [Purshia tridentata / Hesperostipa comata Antelope brush / needle-and-thread grass]. Plant Community Account Summary [C3B4APTSC1]. B. C. M. o. S. R. Management. Victoria.
Chacoff, N. P., D. P. Vazquez, S. B. Lomascolo, E. L. Stevani, J. Dorado and B. Padron (2012). Evaluating sampling completeness in a desert plant-pollinator network. Journal of Animal Ecology 81(1): 190-200.
Curtin, C. and D. Western (2008). Grasslands, people, and conservation: Over-the-horizon learning exchanges between African and American pastoralists. Conservation Biology 22(4): 8.
Dormann, C. F., J. Frund, N. Bluthgen and B. Gruber (2009). Indices, graphs and null models: Analyzing bipartite ecological networks. The Open Ecology Journal 2: 7-24.
Dupont, Y. L., D. M. Hansen and J. M. Olesen (2003). Structure of a plant-flower-visitor network in the high-altitude sub-alpine desert of Tenerife, Canary Islands. Ecography 26(3): 301-310.
Dyer, O. and E. C. Lea (2003). Status and importance of the Antelope-brush - Needle-and-thread grass plant community in the South Okanagan Valley, British Columbia. Ecosystems at Risk - Antelope Brush Restoration Conference. R. Seaton. Osoyoos, B.C.
Elle, E., S. Elwell and G. Gielens (in press). The use of pollination networks in conservation. Botany.
Elmqvist, T., C. Folke, M. Nystrom, G. Peterson, J. Bengtsson, B. Walker and J. Norberg (2003). Response diversity, ecosystem change, and resilience. Frontiers in Ecology and the Environment 1(9): 488-494.
Elton, C. S. (1958). Ecology of invasions by animals and plants. London, Chapmen & Hall.
68
Fortuna, M. A. and J. Bascompte (2006). Habitat loss and the structure of plant-animal mutualistic networks. Ecology Letters 9(3): 278-283.
Forup, M. L., K. S. E. Henson, P. G. Craze and J. Memmott (2008). The restoration of ecological interactions: plant-pollinator networks on ancient and restored heathlands. Journal of Applied Ecology 45(3): 742-752.
Gayton, D. (2003). British Columbia Grasslands Monitoring Vegetation Change, FORREX - Forest Research Extension Partnership. 7.
Gibson, R. H., B. Knott, T. Eberlein and J. Memmott (2011). Sampling method influences the structure of plant-pollinator networks. Oikos 120(6): 822-831.
Gibson, R. H., I. L. Nelson, G. W. Hopkins, B. J. Hamlett and J. Memmott (2006). Pollinator webs, plant communities and the conservation of rare plants: arable weeds as a case study. Journal of Applied Ecology 43(2): 246-257.
Gilgert, W. and M. Vaughan (2011). The value of pollinators and pollinator habitat to rangelands: Connections among pollinators, insects, plant communities, fish, and wildlife. Rangelands 33(3): 6.
Goulson, D., G. C. Lye and B. Darvill (2008). Decline and conservation of bumble bees. Annual Review of Entomology. Palo Alto, Annual Reviews. 53: 191-208.
Hagen, M. and M. Kraemer (2010). Agricultural surroundings support flower-visitor networks in an Afrotropical rain forest. Biological Conservation 143(7): 1654-1663.
Hegland, S. J., J. Dunne, A. Nielsen and J. Memmott (2010). How to monitor ecological communities cost-efficiently: The example of plant-pollinator networks. Biological Conservation 143(9): 2092-2101.
Henle, K., K. F. Davies, M. Kleyer, C. Margules and J. Settele (2004). Predictors of species sensitivity to fragmentation. Biodiversity and Conservation 13(1): 207-251.
Joppa, L. N., J. M. Montoya, R. Sole, J. Sanderson and S. L. Pimm (2010). On nestedness in ecological networks. Evolutionary Ecology Research 12(1): 35-46.
Jordano, P., J. Bascompte and J. M. Olesen (2006). The ecological consequences of complex topology and nested structure in pollination webs. Plant-Pollinator Interactions: From Specialization to Generalization. N. M. Waser and J. Ollerton. Chicago, The University of Chicago Press: 173-199.
Kaiser-Bunbury, C. N., S. Muff, J. Memmott, C. B. Mueller and A. Caflisch (2010). The robustness of pollination networks to the loss of species and interactions: a quantitative approach incorporating pollinator behaviour. Ecology Letters 13(4): 442-452.
69
Kearns, C. A., D. W. Inouye and N. M. Waser (1998). Endangered mutualisms: The conservation of plant-pollinator interactions. Annual Review of Ecology and Systematics 29: 83-112.
Kevan, P. G. (1999). Pollinators as bioindicators of the state of the environment: species, activity and diversity. Agriculture Ecosystems & Environment 74(1-3): 373-393.
Krannitz, P. G. (2008). Response of antelope bitterbrush shrubsteppe to variation in livestock grazing. Western North American Naturalist 68(2): 138-152.
Lawton, J. H. and V. K. Brown (1993). Redundancy in ecosystems. Biodiversity and ecosystem function. E. D. Schulze and H. A. Mooney. 99: 255-270.
Lea, T. (2008). Historial (pre-settlement) ecosystems of the Okanagan Valley and Lower Similkameen Valley of British Columbia - pre-European contact to the present. Davidsonia 19(1): 34.
Lopezaraiza-Mikel, M. E., R. B. Hayes, M. R. Whalley and J. Memmott (2007). The impact of an alien plant on a native plant-pollinator network: an experimental approach. Ecology Letters 10(7): 539-550.
Macarthur, R. (1955). Fluctuations of animal populations, and a measure of community stability. Ecology 36(3): 533-536.
Mack, R. N. (1981). Invasion of Bromus tectorum L into western North America - An ecological chronicle. Agro-Ecosystems 7(2): 145-165.
McCann, K. S. (2000). The diversity-stability debate. Nature 405(6783): 228-233.
Medan, D., A. M. Basilio, M. Devoto, N. H. Bartoloni, J. P. Torretta and T. Petanidou (2006). Measuring generalization and connectance in temperate, year-long active systems. Plant-pollinator interactions: From specialization to generalization. N. M. Waser and J. Ollerton. Chicago, The University of Chicago Press: 245-259.
Memmott, J. (1999). The structure of a plant-pollinator food web. Ecology Letters 2(5): 276-280.
Memmott, J., N. M. Waser and M. V. Price (2004). Tolerance of pollination networks to species extinctions. Proceedings of the Royal Society of London Series B-Biological Sciences 271(1557): 2605-2611.
Naeem, S. (1998). Species redundancy and ecosystem reliability. Conservation Biology 12(1): 39-45.
Nicholson, A., E. Hamilton, W. L. Harper and B. M. Wikeem (1991). Bunchgrass Zone. Ecosystesm of British Columbia. D. Meidinger, Pojar, J. Victoria, B.C, Province of British Columbia.
70
Olesen, J. M., J. Bascompte, H. Elberling and P. Jordano (2008). Temporal dynamics in a pollination network. Ecology 89(6): 1573-1582.
Olesen, J. M., L. I. Eskildsen and S. Venkatasamy (2002). Invasion of pollination networks on oceanic islands: importance of invader complexes and endemic super generalists. Diversity and Distributions 8(3): 181-192.
Ollerton, J., R. Winfree and S. Tarrant (2011). How many flowering plants are pollinated by animals? Oikos 120(3): 321-326.
Peart, B. (2008). A record of The World Temperate Grasslands Conservation Initiative Workshop Hohhot, China - June 28 & 29, 2008. Vancouver, BC, Temperate Grasslands Conservation Initiative.
Potts, S. G., J. C. Biesmeijer, C. Kremen, P. Neumann, O. Schweiger and W. E. Kunin (2010). Global pollinator declines: trends, impacts and drivers. Trends in Ecology & Evolution 25(6): 345-353.
Schlute, A., T. Lea, S. Cannings and P. G. Krannitz (1995). Antelope-brush ecosystems. L. a. P. B.C. Ministry of Environment, Wildlife Branch. Victoria, B.C.: 6.
Sugiura, S. (2010). Species interactions-area relationships: biological invasions and network structure in relation to island area. Proceedings of the Royal Society B-Biological Sciences 277(1689): 1807-1815.
Thebault, E. and C. Fontaine (2010). Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329(5993): 853-856.
Tilman, D., D. Wedin and J. Knops (1996). Productivity and sustainability influenced by biodiversity in grassland ecosystems. Nature (London) 379(6567): 718-720.
Tscharntke, T., I. Steffan-Dewenter, A. Kruess and C. Thies (2002). Characteristics of insect populations on habitat fragments: A mini review. Ecological Research 17(2): 229-239.
Tylianakis, J. M., E. Laliberte, A. Nielsen and J. Bascompte (2010). Conservation of species interaction networks. Biological Conservation 143(10): 2270-2279.
Tylianakis, J. M., T. Tscharntke and O. T. Lewis (2007). Habitat modification alters the structure of tropical host-parasitoid food webs. Nature 445(7124): 202-205.
Ulrich, W., M. Almeida and N. J. Gotelli (2009). A consumer's guide to nestedness analysis. Oikos 118(1): 3-17.
Valdovinos, F. S., R. Ramos-Jiliberto, J. D. Flores, C. Espinoza and G. Lopez (2009). Structure and dynamics of pollination networks: the role of alien plants. Oikos 118(8): 1190-1200.
Vazquez, D. P. and M. A. Aizen (2004). Asymmetric specialization: A pervasive feature of plant-pollinator interactions. Ecology 85(5): 1251-1257.
71
Vazquez, D. P., N. Bluethgen, L. Cagnolo and N. P. Chacoff (2009). Uniting pattern and process in plant-animal mutualistic networks: a review. Annals of Botany 103(9): 1445-1457.
Vazquez, D. P., C. J. Melian, N. M. Williams, N. Bluthgen, B. R. Krasnov and R. Poulin (2007). Species abundance and asymmetric interaction strength in ecological networks. Oikos 116(7): 1120-1127.
Vazquez, D. P., W. F. Morris and P. Jordano (2005). Interaction frequency as a surrogate for the total effect of animal mutualists on plants. Ecology Letters 8(10): 1088-1094.
Vazquez, D. P. and D. Simberloff (2003). Changes in interaction biodiversity induced by an introduced ungulate. Ecology Letters 6(12): 1077-1083.
Vila, M., I. Bartomeus, A. C. Dietzsch, T. Petanidou, I. Steffan-Dewenter, J. C. Stout and T. Tscheulin (2009). Invasive plant integration into native plant-pollinator networks across Europe. Proceedings of the Royal Society B-Biological Sciences 276(1674): 3887-3893.
Vilhena, A., L. Rabelo, E. Bastos and S. Augusto (2012). Acerola pollinators in the savanna of Central Brazil: temporal variations in oil-collecting bee richness and a mutualistic network. Apidologie 43(1): 51-62.
Waser, N. M., L. Chittka, M. V. Price, N. M. Williams and J. Ollerton (1996). Generalization in pollination systems, and why it matters. Ecology 77(4): 1043-1060.
Wikeem, B. and S. Wikeem (2004). The Grasslands of British Columbia. Kamloops, B.C., Grasslands Conservation Council of British Columbia.
Winfree, R. and C. Kremen (2009). Are ecosystem services stabilized by differences among species? A test using crop pollination. Proceedings of the Royal Society B-Biological Sciences 276(1655): 229-237.
Yoshihara, Y., B. Chimeddorj, B. Buuveibaatar, B. Lhaquasuren and S. Takatsuki (2008). Effects of livestock grazing on pollination on a steppe in eastern Mongolia. Biological Conservation 141(9): 2376-2386.
72
Tables
Table 3.1. Plant-pollinator interaction network property definitions with brief explanations of their influence on network resilience.
73
Table 3.2. Characteristics of focal shrubsteppe sites in the southern Okanagan Valley, British Columbia. “U” in the site abbreviation denotes ungrazed and “G” denotes grazed. For more information see Table 2.1.
OKU Kennedy Bench Antelope-brush Conservation Area
Antelope-brush 40 448 3
OKG Mt. Oliver Protected Area Antelope-brush 260.5 503 5
SOU White Lake Biodiversity Ranch Big sagebrush 55 713 7
SOG White Lake Biodiversity Ranch Big sagebrush 170 563 15
WLG Southern Okanagan Grasslands Protected Area
Big sagebrush 20 883 22
WLU Southern Okanagan Grasslands Protected Area
Big sagebrush 1850 884 18
74
Table 3.3. The effects of habitat type and period of the flowering season (early, mid, late) on plant-pollinator interaction network structural properties. The effects of habitat on network structure were also generated using full season networks. Bolded values = P < 0.10, * = P < 0.05.
Table 3.4. The identity if the top-10 most functionally important plants and pollinators in antelope-brush and big sagebrush shrubsteppe. Species presented have the highest combined degree and asymmetry.
76
Figures
Figure 3.1. Quantitative plant-pollinator interaction networks from antelope-brush and big sagebrush habitats: a/e) Full season networks; b/f) Early season networks; c/g) Middle season networks; and d/h) Late season networks. In each network, rectangles represent pollinator (top row) or plant (bottom row) species, and the lines connecting them represent interactions. The width of each plant rectangle represents how frequently the plant was visited by pollinators, and the width of each pollinator rectangle indicates how frequently a pollinator was collected off of flowering plants. The width of the interaction represents how frequently that interaction was recorded. Pollinators are colour-coded as follows: red = bees (Hymenoptera); green = wasps (Hymenoptera); blue = flies (Diptera); purple = beetles (Coleoptera); yellow = butterflies (Lepidoptera); orange = hummingbird (Trochilidae). Plants in the seasonal sub-networks are colour-coded as follows: light grey = blooming in early and mid season; dark grey = blooming in mid and late season; black = blooming during a single season. Species blooming through two seasons are arranged in the same order to allow comparison. Networks are meant to give an impression of how network interactions change through time, and are not all drawn to the same scale.
77
Early Mid Late Full
Asym
metr
y
-0.60
-0.55
-0.50
-0.45
-0.40
-0.35
-0.30
-0.25
Early Mid Late Full
Neste
dness
2
4
6
8
10
12
14
H2' s
pecia
lization index
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
Genera
lity
2
4
6
8
10
Num
ber
of
specie
s
0
20
40
60
80
100
120
Netw
ork
siz
e
20
40
60
80
100
120
140Antelope-brush Big sagebrush
b)a)
c) d)
Network Network
e) f)
Plant
Pollinator
Plant
Pollinator
Figure 3.2. Changes in plant-pollinator network structural properties across early, mid. and late flowering seasons, including full season values, in antelope-brush and big sagebrush shrubsteppe: a) network size, b) number of plant and pollinator species, c) H2’ specialization index, d) plant and pollinator generality, e) interaction strength asymmetry, f) NODF nestedness. The solid lines connect the least square mean values of each metric across the flowering season for both shrubsteppe types.
78
Chapter 4 General conclusions
The reports of pollinator population declines that have surfaced in many places
around the world have raised concern over the health of pollinator communities and the
preservation of their functional roles (Kearns et al. 1998; Potts et al. 2010). Although still
rarely considered in the conservation planning process, pollinators are a vitally important
component of most terrestrial ecosystems (Winfree 2010). As anthropogenic pressures
on natural ecosystems continue to increase, understanding how habitat-altering
disturbances influence pollinator communities will be important for their future
conservation and preservation. In this thesis, I assessed the effects of livestock grazing
on shrubsteppe flowering plant and pollinator communities (Chapter 2), and used plant-
pollinator interaction networks to compare network structure between British Columbia’s
endangered shrubsteppe ecosystems (Chapter 3), to investigate network resilience and
generate information useful for conservation planning.
The effects of livestock grazing and habitat type on flowering plants and pollinators
Previous studies have shown that the abundance and richness of pollinator
populations can be influenced by changes in vegetation structure induced by grazing,
such as vegetation height (Kruess and Tscharntke 2002) and bare soil availability
(Vulliamy et al. 2006), thus I assessed whether shrubsteppe vegetation structure was
influenced by grazing. I found that livestock grazing did affect vegetation structure, by
increasing the cover of shrubs and bare soil and decreasing the height of the grass and
forb layers. Similar responses to livestock grazing have been reported by many other
studies (Anderson et al. 1982; Fleischner 1994; Jones 2000; Kruess and Tscharntke
2002; Vulliamy et al. 2006; Krannitz 2008). Cattle often cause decreases in grass and
79
forb height through direct herbivory and/or reductions in plant vigor due to herbivory
often increases bare soil availability (Fleischner 1994). In these shrubsteppe
ecosystems increases in bare soil come at the expense of cryptogamic crust cover, a
layer important for soil moisture retention. Spring grazing is reputed to be the most
destructive time of year to graze dry shrubsteppe habitat as it is the primary growing
season for many grass, forb and cryptogamic crust species (Gayton 2003; Krannitz
2008).
Contrary to my expectations, the changes in vegetation structure imposed by
livestock grazing did not extend to significant changes in flowering plant or pollinator
abundance, richness or community composition. There was a trend of decreased floral
abundance in grazed sites during the later-half of the flowering season (June-July),
roughly corresponding with the cessation of grazing. It may be that forbs subject to
cattle herbivory tend to produce fewer flowers, or that grazing decreases the abundance
of some species. There was also a trend towards differing pollinator community
composition between grazed and ungrazed sites. Thus, livestock may have had some
influence on some members of the plant-pollinator community, but the duration and
intensity of grazing precluded any significant negative effects on the community as a
whole. It is predicted that livestock grazing in ecosystems without long grazing histories,
such as those west of the Rocky Mountains in North America (including my study sites),
will be harmful to plants and pollinators. But my work, as well as that of Vazquez et al.
(2008) from Argentina, shows that floral and pollinator communities of habitats without
long grazing histories do not necessarily respond negatively to grazing pressure. My
results therefore contribute to the growing body of literature indicating that the current
grazing regime is an important determinant of plant and pollinator responses (e.g., Pond
1960; Carvell 2002; Vulliamy et al. 2006; Krannitz 2008; Sjodin et al. 2008; Xie et al.
2008).
Floral and pollinator communities were significantly correlated at my sites,
suggesting that pollen and nectar resources (i.e. floral community composition) were a
major determinant of pollinator community composition. Thus, it is perhaps not
surprising that the non-significant effects of grazing on the flowering plant community
were carried through to the pollinator community. My results suggest that semi-natural
80
habitats, like rangeland, when managed responsibly, can remain reservoirs of flowering
plant and pollinator diversity.
Both antelope-brush and big sagebrush shrubsteppe were found to have diverse
plant and pollinator communities, though they differed in their community composition.
Differences in flowering plant community composition between habitats is likely driven by
environmental differences associated with elevation change, as antelope-brush habitats
are drier and lower in elevation than big sagebrush habitats. Although many flowering
plant species were present in both ecosystems, many others were sampled primarily or
exclusively at low or high elevations. A similar pattern was found with pollinators. Bee
genera that were found to be more prevalent in one shrubsteppe type were found to
frequently visit flowering plant species with a similar distribution. For example, the bee
genera Andrena and Eucera which were more prevalent in big sagebrush habitat,
primarily visited flowering plants found only (or more prevalently) in big sagebrush
habitat. As both antelope-brush and big sagebrush shrubsteppe support high pollinator
diversity, but the composition of their floral and pollinator communities differ, attention to
maintaining the health of both habitats under sustainable grazing practices is of high
conservation importance.
The plant-pollinator network structure of British Columbia’s endangered shrubsteppe
Given the endangered status of both shrubsteppe habitats and the differences in
their plant and pollinator community composition, I also investigated differences in plant-
pollinator network structure between habitats. I found that plant-pollinator networks of
the two shrubsteppe habitats were different in the average generalization of their
constituent species. Big sagebrush networks were significantly more generalized
overall, with more generalized plants and a trend towards more generalized pollinators.
Additionally, big sagebrush networks tended to be larger (more species-rich). Networks
with more interacting species that are, on the whole, more generalized are thought to be
more stable and resilient to disturbances, such as habitat alteration, through increased
interaction redundancy (Memmott et al. 2004; Thebault and Fontaine 2010). For
example, plants that are visited by many pollinator species should be less likely to
81
experience population decline or local extinction from the loss of a pollinator than those
species that interact with few. Network analysis also indicated that big sagebrush and
antelope-brush habitats shared roughly half of their top-ten most functionally important
flowering plants and pollinators. Thus, protection of one habitat is likely to be beneficial
to the plant-pollinator communities of the other; protecting and restoring big sagebrush
habitat near remaining antelope-brush fragments could reduce the negative effects
associated with this habitats excessive fragmentation. As was found in Chapter 2,
network analysis also indicated that many species are more prevalent or only found in
one shrubsteppe type, thus preservation of both habitats will be important in maintaining
regional diversity.
I also used plant-pollinator networks to investigate how community interactions
changed across the flowering season. Plant-pollinator networks late in the flowering
season tended to be larger, were more asymmetric, and had greater plant generalization
than those in the spring. Thus, plants flowering late in the season should be less
susceptible to fluctuations in population sizes of their pollinators than those flowering
early in the season, because they have more pollinators to rely on for pollen receipt
(Waser et al. 1996). Although I found that low-intensity spring grazing did not negatively
affect these plant and pollinator communities, my network analysis suggests that the
potential impact of higher-intensity grazing in this region could be minimized if it can be
shifted away from early spring to later in the flowering season. Comparing network
structural properties temporally, although rarely pursued in a conservation context, may
be a promising additional component of using plant-pollinator networks to address
applied ecological questions.
Plant-pollinator interaction networks can provide a more functional perspective of
communities than traditional biodiversity sampling, by identifying which species interact
within a community, how those interactions are structured and what that structure may
mean for community stability (Bascompte and Jordano 2007). However, there is still
much to be learned about plant-pollinator community structure and network analysis,
particularly in relation to their use as a tool for management and conservation (Tylianakis
et al. 2010; Elle et al. in press). Future research should work towards gaining a deeper
understanding of the functional consequences of network structure in real communities
and should focus on identifying what network structural properties are influenced by
82
different anthropogenic disturbances. Although a push towards this aim can be seen in
the current literature (e.g., Forup and Memmott 2005; Aizen et al. 2008; Bartomeus et al.
2008; Yoshihara et al. 2008; Hagen and Kraemer 2010), there is still much to be
understood about practically applying the information gained from networks in
conservation planning (Tylianakis et al. 2010; Elle et al. in press). Additionally,
identifying how plant-pollinator networks can be sampled effectively, but also cost
efficiently, is necessary if they are to be widely adopted as a management tool (Hegland
et al. 2010; Tylianakis et al. 2010). These are laudable aims because the development
of networks, which improve understanding of both species- and community-level
interactions, as research and conservation tools will be important for the conservation
and sustainability of pollinations systems.
Summary and future directions
Low-intensity, spring livestock grazing does not negatively affect plant and
pollinator abundance, richness or community composition, although trends towards
decreased floral abundance and differing pollinator community composition were found
in grazed sites. My results suggest that rangelands can maintain grassland flowering
plant and pollinator diversity when responsibly managed. This is heartening news for
pollinator conservation given the ever-increasing threat of human-induced disturbance.
However, given the trends observed, I recommend that the current grazing regimes of
these areas be maintained and not increased. Although some aspects of vegetation
structure are influenced by low-intensity spring grazing, the disturbance is minor from the
flowering plant and pollinator perspective, suggesting the grazing regimes implemented
at these sites could act as a model for private land owners in the region. Additionally,
since network analysis indicated early-season plant-pollinator communities may be less
resilient to disturbance than late season communities, the potential impacts of higher-
intensity grazing could be minimized if it can be shifted away from early spring to later in
the flowering season.
Grasslands are among the ecosystems predicted to experience the largest
losses in biodiversity over the next century, particularly due to their sensitivity to land-
use change (Sala et al. 2000), thus community-based monitoring and analyses of plants
83
and pollinators in the southern Okanagan is likely to be important for their conservation.
Although the monitoring of both taxa would be preferable, under monetary constraints
monitoring flowering plant diversity and community composition may be a decent
surrogate for monitoring pollinator communities. Flowering plant and pollinator
community compositions were correlated across my sites and network analysis indicated
that pollinator species tended to rely more strongly on the plant species they visited for
pollen and nectar than the plants relied on them, on an individual species basis, for
pollination. Thus, if shrubsteppe flowering plant communities are doing well, it is likely
that the pollinator communities are also doing well. That said, long-term data sets on
pollinator populations are few (Potts et al. 2010) and need to be initiated now to better
assess the changes in pollinator populations over the next few decades due to increased
habitat loss, alteration and climate change. I believe the southern Okanagan is an
appropriate region to begin a pollinator monitoring program within B.C. because of the
region’s high pollinator diversity, endangered ecosystems and increasing urban and
agricultural development. Due to the overlap of early and late season pollinators, data
collection during mid flowering season (late May - early June) would likely be sufficient
for such a monitoring program.
Both antelope-brush and big sagebrush shrubsteppe of the southern Okanagan
Valley are not only Red-listed in British Columbia, but are considered globally imperilled
(B.C. Ministry of Environment) thus effective conservation of these habitats and their
flowering plant and pollinator communities should be a Canadian conservation priority.
The conservation of flowering plants and pollinators will be critical to the successful
preservation of both shrubsteppe habitats, as so many other species depend on
flowering plants and insects for food resources and vegetative habitat structure (Gilgert
and Vaughan 2011). Given that the plant-pollinator communities of antelope-brush
habitat may be more sensitive to disturbance than those in big sagebrush habitat and
given the highly fragmented state of remaining antelope-brush shrubsteppe, prioritizing
the monitoring, restoration and conservation of remaining antelope-brush habitat will be
highly important in preserving biodiversity in the southern Okanagan region. Big
sagebrush shrubsteppe, although also Red-listed, is approximately twice as abundant as
antelope-brush shrubsteppe (Lea 2008) and is also far less fragmented. The plant-
pollinator communities of big sagebrush shrubsteppe tend to be more diverse and may
84
be more resilient to disturbance through increased network-level generalization than
those in antelope-brush shrubsteppe. Large contiguous tracts of big sagebrush habitat
still exist in the Okanagan and, although much of this habitat is grazed by livestock
attention towards responsible grazing practices, such as those studied here, will be one
of the most important factors in maintaining the integrity of this ecosystem. The proposal
to create a national park in the south Okanagan – lower Similkameen Valleys, which
would have enforced adaptive management of livestock grazing within park boundaries
and connected many present day protected areas (Parks Canada 2010), is not currently
supported by the government of British Columbia (Parks Canada 2012). Thus, the
continued effort of land managers and conservation practitioners to use community-
based monitoring and analyses to find a balance between biological integrity and
economic viability in this region will be vital for the conservation of shrubsteppe
pollination systems.
85
References
Aizen, M. A., C. L. Morales and J. M. Morales (2008). Invasive mutualists erode native pollination webs. Plos Biology 6(2): 396-403.
Anderson, D. C., K. T. Harper and S. R. Rushforth (1982). Recovery of cryptogramic soil crusts from grazing on Utah winter ranges. Journal of Range Management 35(3): 355-359.
Bartomeus, I., M. Vila and L. Santamaria (2008). Contrasting effects of invasive plants in plant-pollinator networks. Oecologia 155(4): 761-770.
Bascompte, J. and P. Jordano (2007). Plant-animal mutualistic networks: The architecture of biodiversity. Annual Review of Ecology Evolution and Systematics. Palo Alto, Annual Reviews. 38: 567-593.
B.C. Ministry of Environment. B.C. Species and Ecosystem Explorer. Retrieved Februrary 23, 2012 from http://www.env.gov.bc.ca/atrisk/red-blue.htm.
Carvell, C. (2002). Habitat use and conservation of bumblebees (Bombus spp.) under different grassland management regimes. Biological Conservation 103(1): 33-49.
Elle, E., S. Elwell and G. Gielens (in press). The use of pollination networks in conservation. Botany.
Fleischner, T. L. (1994). Ecological costs of livestock grazing in western North America. Conservation Biology 8(3): 629-644.
Forup, M. L. and J. Memmott (2005). The restoration of plant-pollinator interactions in hay meadows. Restoration Ecology 13(2): 265-274.
Gayton, D. (2003). British Columbia Grasslands Monitoring Vegetation Change, FORREX - Forest Research Extension Partnership. 7.
Gilgert, W. and M. Vaughan (2011). The value of pollinators and pollinator habitat to rangelands: Connections among pollinators, insects, plant communities, fish, and wildlife. Rangelands 33(3): 6.
Hagen, M. and M. Kraemer (2010). Agricultural surroundings support flower-visitor networks in an Afrotropical rain forest. Biological Conservation 143(7): 1654-1663.
Hegland, S. J., J. Dunne, A. Nielsen and J. Memmott (2010). How to monitor ecological communities cost-efficiently: The example of plant-pollinator networks. Biological Conservation 143(9): 2092-2101.
Jones, A. (2000). Effects of cattle grazing on North American arid ecosystems: A quantitative review. Western North American Naturalist 60(2): 155-164.
86
Kearns, C. A., D. W. Inouye and N. M. Waser (1998). Endangered mutualisms: The conservation of plant-pollinator interactions. Annual Review of Ecology and Systematics 29: 83-112.
Krannitz, P. G. (2008). Response of antelope bitterbrush shrubsteppe to variation in livestock grazing. Western North American Naturalist 68(2): 138-152.
Kruess, A. and T. Tscharntke (2002). Grazing intensity and the diversity of grasshoppers, butterflies, and trap-nesting bees and wasps. Conservation Biology 16(6): 1570-1580.
Lea, T. (2008). Historial (pre-settlement) ecosystems of the Okanagan Valley and Lower Similkameen Valley of British Columbia - pre-European contact to the present. Davidsonia 19(1): 34.
Memmott, J., N. M. Waser and M. V. Price (2004). Tolerance of pollination networks to species extinctions. Proceedings of the Royal Society of London Series B-Biological Sciences 271(1557): 2605-2611.
Parks Canada (2010). National Park Reserve Feasibility Assessment Update – South Okanagan – Lower Similkameen. Pentiction, B.C.
Parks Canada (2012). Retrieved March 18, 2012 from http://www.pc.gc.ca/eng/prgs/np-pn/cnpn-cnnp/index.aspx.
Pond, F. W. (1960). Vigor of idaho fescue in relation to different grazing intensities. Journal of Range Management 13(1): 3.
Potts, S. G., J. C. Biesmeijer, C. Kremen, P. Neumann, O. Schweiger and W. E. Kunin (2010). Global pollinator declines: trends, impacts and drivers. Trends in Ecology & Evolution 25(6): 345-353.
Sala, O. E., F. S. Chapin, J. J. Armesto, E. Berlow, J. Bloomfield, R. Dirzo, E. Huber-Sanwald, L. F. Huenneke, R. B. Jackson, A. Kinzig, R. Leemans, D. M. Lodge, H. A. Mooney, M. Oesterheld, N. L. Poff, M. T. Sykes, B. H. Walker, M. Walker and D. H. Wall (2000). Biodiversity - Global biodiversity scenarios for the year 2100. Science 287(5459): 1770-1774.
Sjodin, N. E., J. Bengtsson and B. Ekbom (2008). The influence of grazing intensity and landscape composition on the diversity and abundance of flower-visiting insects. Journal of Applied Ecology 45(3): 763-772.
Thebault, E. and C. Fontaine (2010). Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329(5993): 853-856.
Tylianakis, J. M., E. Laliberte, A. Nielsen and J. Bascompte (2010). Conservation of species interaction networks. Biological Conservation 143(10): 2270-2279.
87
Vazquez, D. P., V. Aschero and E. L. Stevani (2008). Livestock grazing, habitat protection and diversity of bees and wasps in the Central Monte desert. Rev. Soc. Entomol. Argent. 67(3-4): 10.
Vulliamy, B., S. G. Potts and P. G. Willmer (2006). The effects of cattle grazing on plant-pollinator communities in a fragmented Mediterranean landscape. Oikos 114(3): 529-543.
Waser, N. M., L. Chittka, M. V. Price, N. M. Williams and J. Ollerton (1996). Generalization in pollination systems, and why it matters. Ecology (Washington D C) 77(4): 1043-1060.
Winfree, R. (2010). The conservation and restoration of wild bees. Year in Ecology and Conservation Biology 2010. R. S. Ostfeld and W. H. Schlesinger. Malden, Wiley-Blackwell. 1195: 169-197.
Xie, Z. H., P. H. Williams and Y. Tang (2008). The effect of grazing on bumblebees in the high rangelands of the Eastern Tibetan Plateau of Sichuan. Journal of Insect Conservation 12(6): 695-703.
Yoshihara, Y., B. Chimeddorj, B. Buuveibaatar, B. Lhaquasuren and S. Takatsuki (2008). Effects of livestock grazing on pollination on a steppe in eastern Mongolia. Biological Conservation 141(9): 2376-2386.
88
Appendices
89
Appendix A Floral unit designations
Table A.1. Inflorescence descriptions and floral unit designations for all sampled pollinator-attractive forb species.
Scientific name Common name Inflorescence description
Floral unit designation
Achillea millefolium Yarrow Many heads in flat-topped cluster
1 inflorescence
Agoseris glauca Pale agoseris Solitary composite head 1 plant
Antennaria dimorpha Low pussytoes Solitary composite head all flowering stems traced back to single root, mat-forming sp.
Antennaria microphylla Rosy pussytoes Several- to- many composite heads
1 inflorescence
Antennaria umbrinella Umber pussytoes Several- to- many composite heads
1 inflorescence
Arabis holboellii Holboell’s rockcress Raceme, loose elongate cluster with many to several flowers
1 inflorescence
Arnica fulgens Orange Arnica Solitary composite head 1 inflorescence
Table B.2. Putative pollinators collected through netting and pan-trap surveys in antelope-brush and big sagebrush shrubsteppe. Netted specimens have species-level degree and interaction strength asymmetry values, while those species/morphospecies collected in pan-traps are marked by an x in the pan column.
ANTELOPE-BRUSH BIG SAGEBRUSH
Pollinator species/morphospecies Degree Asymmetry Pan Degree Asymmetry Pan
Agapostemon texanus 8 -0.0521 x 6 -0.1246 x
Agapostemon virescens 2 -0.4641 x - - x
Ammophila sp. 4 -0.2115 x 1 -0.9767 x
Anastrangalia laetifica 2 -0.4864
- -
Andrena amphibola 5 -0.1148 x 7 -0.1009 x
Andrena angustitarsata 1 -0.6667 x 1 -0.9890 x
Andrena astragali 1 -0.6667 x - - x
Andrena buckelli - -
9 -0.0679 x
Andrena caerulea - - x 3 -0.1428 x
Andrena candida - - x - -
Andrena chapmanae - -
1 -0.9714 x
Andrena chlorogaster - -
2 -0.4530 x
Andrena cuneilabris - -
- - x
Andrena cupreotincta 1 -0.9875 x 1 -0.9818 x
Andrena evoluta - - x - - x
Andrena figida - -
1 -0.9917
Andrena forbesii - -
- - x
Andrena lawrencei - - x 3 -0.2780 x
Andrena lupinorum - - x 4 -0.0556 x
Andrena merriami 2 -0.3821 x 9 0.0777 x
Andrena microchlora 2 -0.2644 x 2 -0.3541 x
Andrena nigrihirta 3 -0.2708
5 0.0399 x
Andrena nigrocaerulea - - x 5 -0.1220 x
Andrena nivalis - -
1 -0.9273
Andrena nothocalaidis - - x 1 -0.9890 x
Andrena pallidifovea - - x 8 -0.0805 x
Andrena piperi - -
- - x
Andrena porterae - -
1 -0.9818 x
Andrena prunorum 12 -0.0224 x 7 -0.1033 x
Andrena saccata 1 -0.9615
1 -0.9615 x
Andrena salicifloris 1 -0.9796
3 -0.2820 x
Andrena schuhi 2 -0.4027 x 3 -0.2508 x
Andrena scurra 1 -0.9091 x 7 -0.0041 x
95
ANTELOPE-BRUSH BIG SAGEBRUSH
Pollinator species/morphospecies Degree Asymmetry Pan Degree Asymmetry Pan
Andrena sigmundi - -
- - x
Andrena sladeni 1 -0.7429 x 4 -0.0924 x
Andrena sola - - x 4 -0.1798 x
Andrena sp. 6 1 -0.8750
- - x
Andrena sp. 7 - - x - - x
Andrena sp. 8 - - x - - x
Andrena striatifrons - - x - -
Andrena subaustralis - - x - -
Andrena subtilis 1 -0.9808 x - -
Andrena subtrita - -
- - x
Andrena transnigra - -
5 -0.1310 x
Andrena trizonata 1 -0.9750 x - -
Andrena vicina - - x - -
Andrena vierecki - - x 5 -0.1663 x
Andrena w scripta - -
1 -0.9917
Andrena walleyi - - x - - x
Anthidium clypeodentatum 1 -0.9194 x - - x
Anthidium utahense - - x - -
Anthomyiidae sp. - -
2 -0.3854
Anthophora pacifica - - x 2 -0.4182
Anthophora porterae 1 -0.9000
- -
Anthophora ursina - -
2 -0.2378
Anthrax sp. - - x - - x
Apis mellifera 10 0.2101
10 -0.0400
Artogeia sp. - - x - -
Bembix sp. - - x - -
Bembix sp. 1 - -
2 -0.4885
Bembix sp.2 1 -0.9804
- -
Bibio sp. - -
- - x
Bibio sp. 2 1 -0.9783
3 -0.2986
Bombus appositus 1 -0.8636
2 -0.2357
Bombus bifarius - - x 11 -0.0431 x
Bombus californicus 1 -0.8636 x 6 -0.1317 x
Bombus centralis 9 -0.0008 x 13 0.0527 x
Bombus fervidus 3 -0.2138 x 3 -0.2512 x
Bombus flavifrons 1 -0.9767 x - - x
96
ANTELOPE-BRUSH BIG SAGEBRUSH
Pollinator species/morphospecies Degree Asymmetry Pan Degree Asymmetry Pan
Bombus griseocollis 2 -0.3934 x 1 -0.9714 x
Bombus huntii 2 -0.4786 x 2 -0.4518
Bombus mixtus - -
1 -0.9474
Bombus nevadensis 4 -0.1623
3 -0.1567
Bombus occidentalis - -
1 -0.9714
Bombus suckleyi - - y 1 -0.9804 y
Bombylius major - -
2 -0.4076
Bombylius pendens - -
1 -0.9744
Buprestidae sp. 2 6 0.0046 x 1 -0.9804 x
Buprestidae sp. 3 - -
1 -0.9804
Calliphora livida - - x - -
Calliphora vicina - - x - - x
Cerambycidae sp.1 2 -0.4781 x 18 0.1036 x
Cerambycidae sp. 2 3 -0.2980
5 -0.1734 x
Cerambycidae sp. 3 - -
1 -0.9756 x
Cerambycidae sp. 4 1 -0.9767
- -
Ceratina acantha - - x 2 -0.4664 x
Ceratina nanula 1 -0.9839 x 10 -0.0211 x
Ceratina pacifica 8 -0.0046 x 3 -0.2820 x
Cercyonis sp. - -
2 -0.4806 x
Chalceria spp. - -
- - x
Cheilosia rita - -
1 -0.9890
Chrysididae 5 -0.1292 x 4 -0.2202 x
Chrysotoxum flavifrons 1 -0.9833
- -
Cleridae sp. 3 -0.3039 x 1 -0.9762 x
Coelioxys octodentata/novomexican
x - -
Coelioxys rufitarsis 2 -0.4661
- -
Coelioxys serricaudata - - x - -
Coleothorpa sp. - -
1 -0.9752
Colias spp. - - x - - x
Colletes consors 2 -0.4487 x 1 -0.9588 x
Colletes fulgidus 2 -0.4598
2 -0.4707 x
Colletes kincaidii 2 -0.4259
- - x
Conophorus sp. 2 1 -0.9434 x 5 -0.1208 x
Copestylum sp. 1 1 -0.9597
- -
Copestylum sp. 2 1 -0.9919 x - -
Crabronidae sp. 2 -0.4864 x - - x
97
ANTELOPE-BRUSH BIG SAGEBRUSH
Pollinator species/morphospecies Degree Asymmetry Pan Degree Asymmetry Pan
Cyanus elongata - - x - - x
Cythereinae sp. 1 - -
3 -0.3085
Dianthidium curvatum - - x - -
Dianthidiun pudicum - - x 1 -0.9535
Dufourea holocyanea - - x - - x
Dufourea trochantera 1 -0.9667
1 -0.9588 x
Elateridae spp. - - x - - x
Elateridae sp. 1 - -
1 -0.9500
Elateridae sp. 2 1 -0.9919
1 -0.9667
Elateridae sp. 3 - -
4 -0.2159
Epalpus signifer 1 -0.9333
- -
Epeolus sp. 1 -0.9839
- -
Epistrophe emarginata - -
2 -0.4916
Eristalis dimidiatus 1 -0.9839
3 -0.3173
Eucera douglasiana - - x 3 -0.3070 x
Eucera edwardsii - - x 5 -0.1169 x
Eucera fulvitarsis 2 -0.3906 x 6 -0.0558 x
Eucera virgata - -
4 -0.1900 x
Eumeninae spp. - - x - - x
Eumeninae sp. 1 5 -0.0963
2 -0.4893
Eumeninae sp. 2 - -
4 -0.2254
Eumeninae sp. 4 1 -0.9667
1 -0.9897
Eupeodes latifasciatus 1 -0.9231
- -
Eupeodes luniger - -
1 -0.9500
Eupeodes sp. 2 - -
1 -0.9917
Eupeodes volucris 3 -0.1892
8 -0.0854
Exoprosopa sp. 1 1 -0.9839
- -
Exoprosopa sp. 2 - -
1 -0.9851
Gaeides sp. - - x - -
Geometridae spp. - - x - -
Gorytes sp. 1 1 -0.9091 x - - x
Gorytes sp. 2 4 -0.2035
2 -0.4778
Gymnosoma fulginosa 3 -0.2866 x 2 -0.4775
Habropoda cineraria 3 0.0178
5 -0.0094 x
Halictus confusus - - x 12 -0.0123 x
Halictus farinosus 4 -0.2003 x 1 -0.9524 x
Halictus ligatus 2 -0.4862 x 3 -0.3006 x
98
ANTELOPE-BRUSH BIG SAGEBRUSH
Pollinator species/morphospecies Degree Asymmetry Pan Degree Asymmetry Pan
Halictus rubicundus 10 -0.0308 x 8 -0.0825 x
Halictus tripartitus - - x 8 -0.0737 x
Heliothodes spp. - -
- - x
Hemipenthes edwardsii - -
1 -0.9804
Hemipenthes seminigra - -
1 -0.9935
Heriades carinatus 3 -0.1849 x - -
Heriades cressoni 3 -0.1348
- -
Heringia sp. 3 2 -0.4710
- -
Heringia sp. 4 1 -0.9783
- -
Hesperia spp. - -
- - x
Hesperiidae sp. 2 -0.4419
7 -0.1172
Heterosarus didirupa - - x 2 -0.4821 x
Hoplitis albifrons - - x
Hoplitis grinnelli 3 -0.2932 x 4 -0.1968 x
Hoplitis hypocrita 2 -0.4318 x 1 -0.9714 x
Hoplitis producta - - x - - x
Hoplitis sambuci 5 -0.0935
- - x
Hoplitis sp. 1 metallic - -
- - x
Hoplitis sp. 2 metallic 1 -0.9833
- -
Hylaeus coloradensis nevadensis 2 -0.4743
- -
Hylaeus mesillae - -
1 -0.9917
Hylaeus rubeckiae - -
3 -0.3180
Icaricia sp. - -
- - x
Ichneumonidae spp. - - x - - x
Ichneumonidae sp. 1 1 -0.9375
1 -0.9935
Ichneumonidae sp. 2 - -
2 -0.4667
Ichneumonidae sp. 3 1 -0.9796
3 -0.2990
Ichneumonidae sp. 5 2 -0.4835
1 -0.9767
Ichneumonidae sp. 6 - -
1 -0.9935
Lasioglossum abundipunctum - - x 2 -0.4887
Lasioglossum albipenne - -
5 -0.1486 x
Lasioglossum albohirtum 4 -0.1948 x - - x
Lasioglossum anhypops - - x 1 -0.9897 x
Lasioglossum brunneiventre - - x - - x
Lasioglossum dashwoodi - - x 5 -0.1851 x
Lasioglossum egregium 1 -0.9545
1 -0.9762 x
99
ANTELOPE-BRUSH BIG SAGEBRUSH
Pollinator species/morphospecies Degree Asymmetry Pan Degree Asymmetry Pan
Lasioglossum imbrex 4 -0.1967 x - -
Lasioglossum incompletum - - x - - x
Lasioglossum knereri 3 -0.2623 x 5 -0.1712 x
Lasioglossum macroprosopum - - x - - x
Lasioglossum mellipes 1 -0.9839 x 1 -0.9935 x
Lasioglossum nevadense 6 -0.0403 x 1 -0.9545 x
Lasioglossum ovaliceps - - x 1 -0.9500
Lasioglossum prasinogaster 1 -0.9429 x 8 -0.0927 x
Lasioglossum pruinosum 13 0.0106 x 12 -0.0418 x
Lasioglossum punctatoventre - - x 4 -0.2264 x
Lasioglossum ruidosense - -
8 -0.0771 x
Lasioglossum sedi 3 -0.2805 x 2 -0.4752 x
Lasioglossum sisymbrii 2 -0.4505 x 7 -0.1195 x
Lasioglossum sp. 1 2 -0.3973 x 13 0.0048 x
Lasioglossum sp. 2 - - x 2 -0.2409 x
Lasioglossum sp. 3 8 -0.0819 x 10 -0.0714 x
Lasioglossum sp. 4 - -
- - x
Lasioglossum sp. 6 - -
1 -0.9767 x
Lasioglossum trizonatum 2 -0.4585 x 2 -0.4797 x
Lucilia illustris 1 -0.9796 x 1 -0.9500
Lycaenidae sp. 5 -0.1219 x 8 -0.0632 x
Lycaenidae sp. 2 1 -0.9839 x - -
Megachile angelarum - - x - -
Megachile brevis 4 -0.1998 x 2 -0.4868
Megachile frigida - - x - -
Megachile inermis 1 -0.6667 x - -
Megachile lippiae 1 -0.9608 x - -
Megachile melanophaea - - x 1 -0.9429 x
Megachile montivaga 2 -0.4575 x 2 -0.4803
Megachile onobrychidis 2 -0.3990 x - - x
Megachile parallela - -
- - x
Megachile perihirta 5 -0.1335 x 4 -0.1971
Megachile subnigra - - x 2 -0.4722 x
Melecta separata - - x - - x
Melecta thoracica 2 -0.4775 x 2 -0.4574 x
Melissodes communis 1 -0.9737 x - - x
100
ANTELOPE-BRUSH BIG SAGEBRUSH
Pollinator species/morphospecies Degree Asymmetry Pan Degree Asymmetry Pan
Melissodes microstricta 1 -0.9714 x 1 -0.9535
Melissodes rivalis - - x - -
Mischocyttarus flavitarsis 3 -0.2941 x 2 -0.4686 x
Mordellidae sp. 3 -0.2062 x 3 -0.2711 x
Muscidae metallic sp. 1 4 -0.2061
3 -0.3130
Myopa sp. - - x 1 -0.9818 x
Myopa sp. 2 - - x 1 -0.9615 x
Neopasities aff fulviventris 1 -0.9839 x - -
Neorhyocephalus sackenii - -
3 -0.2928
Noctuidae spp. - -
- - x
Nomada sp. OK1 - - x 1 -0.9545 x
Nomada sp. OK10 - - x - -
Nomada sp. OK11 2 -0.4821
1 -0.9767
Nomada sp. OK12 1 -0.9767
1 -0.9917
Nomada sp. OK13 - -
1 -0.9655 x
Nomada sp. OK14 1 -0.9808
- -
Nomada sp. OK16 - -
- - x
Nomada sp. OK17 - -
- - x
Nomada sp. OK18 - -
1 -0.9091
Nomada sp. OK19 - -
- - x
Nomada sp. OK2 1 -0.9286
1 -0.9839 x
Nomada sp. OK3 2 -0.4580
3 -0.3192
Nomada sp. OK4 1 -0.9714 x 9 -0.0394 x
Nomada sp. OK5 - -
4 -0.2313 x
Nomada sp. OK6 - -
- - x
Nomada sp. OK7 - -
- - x
Nomada sp. OK8 - -
- - x
Nomada sp. OK9 - -
1 -0.9780
Nymphalidae sp. 1 -0.9836
1 -0.9673
Oestridae sp. 1 -0.9783
- -
Osmia albolateralis 1 -0.9545 x - - x
Osmia atrocyanea - - x 1 -0.9800 x
Osmia bakeri - - x 2 -0.4719
Osmia bella - - x 1 -0.9897 x
Osmia bruneri 1 -0.9667 x 1 -0.9737
Osmia californica 5 0.0400 x 1 -0.9767 x
Osmia calla 2 -0.4836 x 7 -0.0067
101
ANTELOPE-BRUSH BIG SAGEBRUSH
Pollinator species/morphospecies Degree Asymmetry Pan Degree Asymmetry Pan
Osmia claremontensis - - x - - x
Osmia coloradensis 3 -0.2780 x 1 -0.9691 x
Osmia cyanella 1 -0.9833
1 -0.9935 x
Osmia cyaneonitens - - x - - x
Osmia densa - - x 1 -0.9897
Osmia dolerosa - - x 1 -0.9897 x
Osmia ednae - -
2 -0.4672 x
Osmia exiguua - - x - -
Osmia juxta - - x - -
Osmia kincaidii 2 -0.4143 x 1 -0.9381 x
Osmia ligaria 2 -0.4714 x 1 -0.9714 x
Osmia marginipennis 1 -0.9672 x 4 -0.1915 x
Osmia montana 4 -0.1683 x 2 -0.4729 x
Osmia odontogaster - -
1 -0.9714 x
Osmia pusilla 2 -0.4615 x 3 -0.3043 x
Osmia regulina - - x 1 -0.9897 x
Osmia sedula - -
1 -0.9897 x
Osmia subaustralis - -
- - x
Osmia texana - - x 3 -0.3146 x
Osmia trevoris 2 -0.4819 x 8 -0.0947 x
Osmia tristella - -
1 -0.9897
Paragus sp. 1 5 -0.1167
1 -0.9804 x
Paragus sp. 2 2 -0.4718 x 1 -0.9935 x
Paravilla sp. - -
1 -0.9839
Peleteria spp. - - x - -
Peleteria iterans - -
1 -0.9744 x
Peleteria sp. 2 6 0.0643
10 -0.0241
Perdita fallax 1 -0.8857 x - -
Perdita nevadensis 1 -0.9737
- - x
Phalacridae sp - -
1 -0.9615 x
Philanthus sp. 1 -0.9919
1 -0.9935
Physocephala sp. 1 2 -0.4823
- -
Pieridae - -
2 -0.4818
Platycheirus sp. 3 - -
4 -0.1807
Podalonia sp. 1 -0.9737 x - - x
Polistes sp. 1 4 -0.2109 x 1 -0.9714 x
Polistes sp. 2 7 -0.0934 x 1 -0.9835 x
102
ANTELOPE-BRUSH BIG SAGEBRUSH
Pollinator species/morphospecies Degree Asymmetry Pan Degree Asymmetry Pan
Pompilida sp. 6 -0.1393
3 -0.3117
Pompilidiae spp. - - x - - x
Scaeva pyrastri - -
3 -0.3100 x
Scarabaeidae sp. 2 -0.4817 x 2 -0.4525 x
Sesiidae sp. 1 -0.9919
2 -0.4926 x
Sphaerophoria bifurcata - -
1 -0.9545
Sphaerophoria contigua - -
2 -0.4916
Sphaerophoria philanthus 6 -0.0204 x 3 -0.3016 x
Sphaerophoria sulphuripes 1 -0.9836
1 -0.9935
Sphecidae sp. 1 -0.9000 x 2 -0.4885 x
Sphecidae sp. 1 1 -0.9811 x 1 -0.9615 x
Sphecodes sp. OK1 - - x - - x
Sphecodes sp. OK2 - - x - - x
Sphecodes sp. OK3 1 -0.9245 x 2 -0.4885 x
Sphecodes sp. OK4 - - x 1 -0.9890 x
Stelis callura - -
- - x
Stelis carnifex 1 -0.9804
- -
Stelis montana - - x - -
Stelis monticola - -
- - x
Stelis sp. B - -
- - x
Stellula calliope 2 -0.3975
- -
Stratiomyidae sp. 1 2 -0.4293 x - - x
Stratiomyidae sp. 2 - - x - -
Symphyta spp. - - x - - x
Symphyta sp. 1 7 -0.0725
2 -0.4545
Symphyta sp. 2 1 -0.9388
1 -0.8421
Symphyta sp. 3 - -
2 -0.4646
Syrphus opinator 1 -0.9231
1 -0.9636
Systoechus oreas - -
1 -0.9767
Systoechus vulgarius - -
- - x
Tachinidae spp. - - x - - x
Tachinidae large 1 -0.9839
1 -0.9487
Tachinidae medium 2 -0.4817
1 -0.9744
Tachinidae small 2 -0.4552
- -
Tachinidae sp. 5 - -
2 -0.4786 x
Tachinidae sp. 6 - -
1 -0.7368
Tachysphex sp. 1 -0.9919 x 1 -0.9869 x
103
ANTELOPE-BRUSH BIG SAGEBRUSH
Pollinator species/morphospecies Degree Asymmetry Pan Degree Asymmetry Pan
Thecophora sp. 1 1 -0.9737 x 1 -0.9677 x
Thymelicus spp. - -
- - x
Trichiotinus assimilis 1 -0.9808
- - x
Trichopoda sp. 1 2 -0.4839
- -
Trichopoda sp. 2 1 -0.9758
- -
Typrocerus sp. - -
1 -0.9935 x
Vespula sp. 1 - - x 1 -0.9835
Villa sp. 2 1 -0.9714
- -
Villa sp. 5 1 -0.9677
- -
Villa sp. 6 3 -0.1382
2 -0.4821
Zodion sp. 1 -0.9714 x 4 -0.2313 x
104
Appendix C Most abundant pollinators and floral resources
Table C.1 The top-10 most abundant pan-trapped pollinators and floral resources of each shrubsteppe habitat type
FLOWERING PLANTS
Antelope-brush shrubsteppe Big sagebrush shrubsteppe
Scientific name # floral units
Scientific name
# floral units
Lithophragma parviflorum 278
Phacelia linearis 1035
Polygonum douglasii 231
Ranunculus glaberrimus 469
Phlox longifolia 209
Lupinus sericeus 424
Ranunculus glaberrimus 206
Phlox longifolia 403
Phacelia linearis 177
Erigeron subtrinervis 157
Lithophragma glabrum 167
Lithophragma glabrum 122
Achillea millefolium 122
Sisymbrium altissimum 116
Eriogonum heracleoides 97
Castilleja thompsonii 116
Saxifraga integrifolia 78
Lomatium triternatum 107
Lomatium geyeri 52
Polygonum douglasii 98
POLLINATORS
Antelope-brush shrubsteppe Big sagebrush shrubsteppe
Scientific name #
specimens
Scientific name #
specimens
Halictus tripartitus 590
Halictus tripartitus 244
Lasioglossum pruinosum 568
Buprestidae sp. 2 145
Lasioglossum nevadense 487
Lasioglossum pruinosum 133
Lasioglossum brunneiventre 132
Andrena microchlora 123
Pompilidae spp. 111
Lasioglossum nevadense 115
Halictus farinosus 105
Andrena caerulea 111
Osmia californica 69
Cerambycidae sp. 1 97
Lasioglossum imbrex 54
Lasioglossum sp. 1 86
Buprestidae sp. 2 52
Halictus farinosus 69
Lasioglossum sp. 1 51 Andrena scurra 69
105
Appendix D Formulas for network structural properties
Pollinator and plant generality
The equations for plant and pollinator generality are the same as those originally proposed by Bersier et al. (2002) for food web analysis, to identify the mean number of prey per predator weighted by interaction strength (Generality index) and the mean number of predator per prey weighted by interaction strength (Vulnerability index). Albrecht et al. (2010) first used these indices in the context of pollinator systems to identify the mean number of plants visited per pollinator and the mean number of pollinators each plant is visited by.
Pollinator generality (same as Generality index)
Where, J = the number of pollinator species in the network, Aj = the total number of interactions of pollinator species i, m = the total number of interaction for all species, and Hj is the Shannon diversity of interactions for pollinator species j, and is represented by the following equation:
Where, I = the number of plant species in the network, aij = the number of interaction between plant species i and pollinator species j.
Plant generality (same as Vulnerability index)
The formula for plant generality (Gplant) is analogous to pollinator generality (Gpoll), but the j’s are replaced by i’s and the J’s are replaced by I’s in the pollinator generality equation.
H2’ specialization index
The H2’ specialization index proposed by Bluthgen et al. (2006) characterizes the degree of specialization for an entire bipartite network based on the deviation of a species realized number of interactions and that expected from each species total number of interactions. The underlying equation is the same as Shannon’s interaction diversity (H2), but the value computed for a given network is standardized against the minimum and maximum possible for the same distributions of matrix interaction totals (Bluthgen et al. 2006, 2007; Dormann et al. 2009). Shannon’s diversity of interactions (H2) is given by:
106
Where, i represents one plant species and I is the total number of plant species in the network; j represents one pollinator species and J is the total number of all pollinator species in the network. The number of interactions between plant i and pollinator j (which is termed aij) is divided by the total number of interaction frequencies recorded for the entire network to find pij,
The H2’ specialization index normalizes the H2 of a network between the minimum and maximum H2 for interactions leading to the same matrix row and column totals. Thus,
Maximum and minimum values for H2 are computed algorithmically by using the fixed total number of interactions of each species as a constant. The resulting H2’ ranges between 0 and 1 for extreme generalization and specialization, respectively.
Interaction strength asymmetry
I used the method of interaction strength asymmetry developed by Vazquez et al. (2007), in which authors define interaction asymmetry as the average mis-match between a focal species effect on its interaction partners and the reciprocal effect of the interaction partners on the focal species. This method involves calculating the interaction strength asymmetry for each species in the network and then taking an overall average of these values to obtain the network level asymmetry value.
The strength of the interaction between two species in a bipartite network can be defined by two coefficients: sij = the strength of the effect of plant species i on pollinator species j, and sji = the strength of the reciprocal effect of pollinator species j on plant species i. Given that Vazquez et al. (2005) has shown that interaction frequency is a good surrogate for interaction strength, it is assumed that sij and sji can be derived from matrices describing the frequency of interaction between pairs of species in a network (fij and fji). In particular, the index assumes that the effect of a plant species i on pollinator species j is proportional to the frequency of interaction between the two species relative to all other interactions of j. Thus,
Where, I = the total number of plant species.
A measure of the symmetry of the strength of each pairwise interaction is as follows:
107
A dij value close to zero indicate that both species contribute equally to the interaction, otherwise stated as highly symmetric interaction strength, whereas a value of 1 or -1 indicates high asymmetry in interaction strength. A positive dij value indicates that plant species i exerts a stronger effect of pollinator species j than the pollinator species exerts on it. A negative dij value indicates the opposite.
The interaction strength asymmetry of plant species i (termed Ai) is defined as the average dij values corresponding to all realized interactions of i:
Where, ki = the degree (number of pollinator species i interacts with) of species i. Species with an A value close to 1 are strongly relied upon by their interaction partners by do not rely strongly on any one interaction partner in return, whereas an A value close to -1 would indicate that a species relies strongly on its interaction partners, but they in turn not are not relied strongly upon. An A value close to 0 indicates that the focal species and their interaction partners rely on each other similarly.
NODF Nestedness
The NODF nestedness metric, proposed by Almedia-Neto et al. (2008), is based on two network properties, decreasing fill and paired overlap. This metric reduced the potential bias introduced by network size and shape (ratio of plants to pollinator species) compared with alternative measures.
Assume that the figure below is a plant-pollinator matrix with five plant and six pollinator species. 1’s represent an interaction between species, while 0’s indicate the absence of an interaction. MT (marginal total) represent the number of interaction partners of any plant or pollinator species, for example MTk = 4, as pollinator k interacts with four plant species.
Decreasing fill (DF):
For any pair of rows, for example i and j, Dij will be equal to 100 if MTj < MTi, whereas DFij will be equal to zero if MTj ≥ MTi.
Similarly, for any pair of columns, for example k and l, DFkl will be equal to 100 if MTl < MTk, whereas DFkl will be equal to 0 if MTl ≥ MTk.
Paired overlap (PO):
For any pair of rows, POij is the percentage of 1’s in a given row j that are located at identical column positions to the 1’s observed in a row i.
108
While, for any pair of columns, POkl is the percentage of 1’s in a given column l that are located at identical row positions to those in column k.
Thus, for any left-to-right pair of columns and right-to-left pair of rows there is a degree of paired nestedness (Npaired) such that,
if DFpaired = 0, then Npaired = 0; and if DFpaired = 100, then Npaired = PO;
From the n(n-1)/2 and m(m-1/)2 paired degrees of nestedness for n columns and m rows, a measure of nestedness can be calculated among all columns and among all rows by averaging all paired values of columns and rows:
109
Appendix E Network structural property values
Table E.1 Network structural properties of all seasonal sub-networks (early, mid, late) and full season networks in antelope-brush (AB) and big sagebrush (SB) shrubsteppe habitat. “G” in the site abbreviation denotes grazed and “U” denotes ungrazed.
