DECOUPLING OF NEOTROPICAL SEASONALLY DRY TROPICAL FOREST
PLANT-POLLINATOR INTERACTIONS IN THE MIDST OF CLIMATE CHANGE
A thesis submitted
to Kent State University in partial fulfillment
of the requirements for the
degree of Master of Science
by
Theresa N. Wolanin
August 2021
Copyright
All rights reserved
Except for previously published materials Thesis written by
Theresa Wolanin
B.S., Kent State University, 2014
M.S., Kent State University, 2021
Approved by
Oscar J. Rocha, Ph.D. , Advisor
Laura G. Leff, Ph.D. , Chair, Department of Biological Sciences
Mandy Munro-Stasiuk, Ph.D. , Interim Dean, College of Arts and Sciences TABLE OF CONTENTS
TABLE OF CONTENTS ...... iii
LIST OF FIGURES ...... v
LIST OF TABLES ...... vi
ACKNOWLEDGMENTS ...... …..... vii
I. INTRODUCTION ...... 1
II. CHANGES IN ABUNDANCE AND COMPOSITION IN THE SEASONALLY
DRY TROPICAL FOREST POLLINATOR BEE COMMUNITY: A
COMPARISON BETWEEN HISTORICAL AND CURRENT
COMMUNITIES...... …...... 7
ABSTRACT...... 7
INTRODUCTION...... 8
MATERIALS AND METHODS...... 12
RESULTS...... 16
DISCUSSION...... 19
III. LONG-TERM VARIATION IN PRECIPITATION PATTERNS AFFECT PLANT-
POLLINATOR RELATIONSHIPS OF SEASONALLY DRY TROPICAL
FORESTS TREES ...... 35
ABSTRACT...... 35
INTRODUCTION ...... 36
MATERIALS AND METHODS ...... 39
RESULTS ...... 45
iii DISCUSSION ...... 48
IV. CONCLUSION ...... 57
REFERENCES...... 63
APPENDICES
A. Rarefied observations of genera in each dry season collection...... 79
B. Wet season precipitation data compiled from IMN and PVNP meteorological stations . 80
iv LIST OF FIGURES
Figure 1. Dissecting differences in bee community structure across sample seasons…………28
Figure 2. Population dynamics in three common SDTF solitary bee genera…………………..29
Figure 3. Non-Metric Dimensional Scaling model for bee communities from thirteen dry seasons………………………………………………………………………………....………..30
Figure 4. Boxplots mapping the variance in bee community structure during the dry season between decades……………………………………………………………………………..…...30
Figure 5. Comparison between historical bee community structure of 1971-1972 and 2016-2018 in the SDTF of Guanacaste, Costa Rica………….……………………...... …………..…….31
Figure 6. Taxa turnover of the dominant SDTF pollinator genera……………………………..32
Figure 7. Decomposed additive time series analysis of wet season precipitation patterns in regions of SDTF in Guanacaste, Costa Rica……………………………………………………54
Figure 8. A bimodal plant-pollinator network comparing the pollinator networks for five SDTF plants……………………………………………………………………………………………55
v LIST OF TABLES
Table 1. Presence/absence table of genera found in thirteen sampled dry seasons in Guanacaste,
Costa Rica………………………………………………………………………………………33
Table 2. Measures of diversity calculated on rarefied dataset (s = 96) of thirteen dry seasons that were representative in terms of sample duration and size……………………………………...34
Table 3. Results from seven Mantel Peason’s product-moment correlation tests…………..….56
vi ACKNOWLEDGMENTS
I dedicate this thesis to my fellow women in science, who inspired and supported me with their expertise, tenacity, and passion for their work, especially: Davinia Beneyto Garrigós, Claire
Bennett, Colleen Cosgrove, Anna Droz, EmmaLeigh Given, Lilliam Morales Gutiérrez, AE
Nash, and Carlyn Rocazella. Carlyn and Claire were instrumental in assisting me in the field studies for this research, and continue to make the world a better place through their work.
A special thanks to Mahmood Sasa, the staff of the Palo Verde National Park Biological
Research Station, and the park rangers of the Palo Verde National Park. Without their help, my field research would not have been possible. I also thank the gracious curators and collectors who allowed me to access and collect samples from museum specimens of bees. These include the staff at the Instituto Nacional de Biodiversidad, Paul Hanson at the Universidad de Costa
Rica, Terry Griswold at the Bee Biology and Systematics Laboratory at Utah State University, and Noelle Jordan and Paul Heithaus at the Brown Family Education Center at Kenyon College.
Additional thanks to Chris Blackwood, Andrea Case, Rollin Coville, Dan Janzen, Monika
Springer, and Brad Vinson for entertaining my many questions.
Lastly, I would like to thank my advisor and mentor, Oscar Rocha, for his guidance over the years. Without this opportunity, I would not be the person or the scientist I am today.
This research was partially funded through the Graduate Student Research Award, provided by the KSU Graduate Student Senate; and the ECTS Graduate Fellowship Award, provided by the Organization for Tropical Studies via the Emily Foster Memorial Fellowship
(fund 512) and the Henry Leigh Fellowship (fund 517).
vii CHAPTER I.
INTRODUCTION
Plants are the foundation of tropical ecosystems, 94% of which are dependent on animal pollinators (Ollerton et al. 2011). My research focuses on how the plant-pollinator relationships in a water-limited tropical forest system are being disrupted by climate change. Which pollinator species are going to win or lose in the process is uncertain, so this project seeks to establish the changing status of bees in the ecosystem, and to investigate the mechanisms that are disrupting the pollinator community.
Costa Rican seasonally dry tropical forests (SDTF) are characterized by trees and vines that are adapted to severely arid dry seasons (Opler et al. 1976, Borchert 1983). During the wet season, many of these trees will begin the development of flowers, which remain dormant until dry season. The timing of anthesis, or flower emergence, in these trees is signaled by the last rain of the wet season, or in some cases, a rain event following a period of dormancy during or after the dry season. During the dry season, many trees will drop their leaves and synchronously bloom in spectacular mass-flowering events. Such events have been argued to be a key visual cue and evolutionary advantage in attracting pollinators and in increasing the efficacy of pollination (Frankie and Coville 1979, Thorp 1979, Michener 2000).
1 The pollinator community of SDTFs is characteristically dominated by solitary bees
(Kalacska et al. 2004). Most non-parasitic solitary bees individually gather all provisions for their offspring. As such, solitary bees capitalize on the wide availability of resources during dry season mass-flowering events to maximize reproductive capacity (Michener 2000). This characterizes them as seasonal specialists, and reflects a strong evolutionary relationship between flowering trees and these pollinators (Thorp 1979). Peak solitary bee activity and diversity observed during February and March (Heithaus 1974, 1979) coincides with peaks in the mass- flowering events of several species of trees (Frankie et al. 1974, 1976, Opler et al. 1976, 1980).
This strong seasonal specialization has been linked to the abundance and diversity of floral resources required for nest-building and offspring provisions (Frankie et al. 1988, 2013,
Michener 2000).
Little formal investigation was conducted to establish the bee pollinator community prior to many of the effects of climate change. In 1979, Ray Heithaus published a comprehensive survey of three dry, lowland habitats within Guanacaste, Costa Rica, which included SDTF.
According to this study, bee diversity in the SDTF from 1971 – 1972 was historically higher than any temperate forest bee community surveyed to that point. This is largely driven by the diversity of the flowering plant community (Heithaus 1974), and by the relationship between the solitary seasonal specialists and mass-flowering events during the dry season (Heithaus 1979).
Consequently, solitary bees accounted for 88% of the diversity for the sampled SDTF bee communities, even though eusocial bees made up 50% of the sample abundance. In terms of phenology, the highest abundance and diversity of solitary bees was found during the dry season
2 (from November to May), with peaks in abundance and diversity during the months of February and March. In contrast, eusocial bees were relatively consistent in presence and abundance year- round, showing little to no seasonality. It should be noted here that halictids display varying degrees of social behavior, and were excluded from analyses of seasonality in the study.
Other studies that defined historical (pre-1980) SDTF bee pollinator communities were not comprehensive, but now provide key insights into the plant-pollinator relationships of certain plant species during the dry season. For instance, studies like that of Jones and Buchman (1974) confirmed the presence of several solitary and eusocial genera on Parkinsonia aculeata and
Caesalpinia eriostachys in February of 1972, despite only seeking to experiment with visual floral cues for pollinators. Other bee lists of similar quality have been published for Ipomoea carnea (Keeler 1975, 1977) and Senna pallida, formerly Cassia biflora (Wille 1963).
Later studies have focused on certain solitary bee pollinators of individual species, describing the plant-pollinator relationships and behavior of these bees and dry-season flowering plants. Particular attention has been paid to large-bodied, solitary bee pollinators of Andira inermis and Byrsonima crassifolia, as these trees have been determined to be broadly attractive
(Frankie et al. 1976, 2005, 2009). The majority of this research mainly focused on life history traits and reproductive habit for the genus, Centris, and paid relatively little attention to the pollinator community as a whole. Most recent study of the pollinator community in this area has focused on the effects of urbanization and deforestation as the key factor in how pollinator communities are being affected in SDTF habitats, and focuses on pollinator relationships with
3 the introduced and native plants of nearby developed areas (Frankie et al. 2013). A species list was published with this study, but this list did not include frequency data needed to describe pollinator community structure as a whole.
Precipitation patterns and changes in photoperiod have been well-established as seasonal cues for SDTF flowering plants. Unfortunately, the environmental cues that control solitary bee phenology and diapause are poorly understood. One study compared the difference between precipitation and potential evaporation to bee activity, and found a strong negative correlation between this rate and solitary bee abundance on a seasonal basis (Heithaus 1979). However, it is unclear as to whether this provides insight into bee phenology, or simply reinforces the relationship between the co-occurrence of seasonal specialists and their host plants.
Historically, the bimodal wet season of Costa Rica lasts from May – November, with peak precipitation occurring in June and September. In recent decades, this pattern has changed in two ways. First, there has been a 25.5% reduction in the average amount of precipitation in the Guanacaste province between 1928-1973 and 1997-2016 (paired, one-sample t-test, p =
0.015). From 1961-1990, regions home to SDTFs lost more than 20mm of precipitation on average (Vargas and Trejos 1994), and regional climate change projections predict a further 9-
16% reduction in annual precipitation and more severe dry seasons (Dokken 2014). Second, there has been a shift in the timing of precipitation during the wet season. In Costa Rica, the wet season typically occurs from May to November, with peak precipitation occurring in June and
September. However, within the last ten years, the first peak in rainfall has diminished, and the
4 second peak in precipitation has been shifting from September to October. This is exacerbated by erratic trends in the onset of the wet season (Giorgi 2006), and higher incidence of storms
(Aguilar et al. 2005).
This shift in the timing and volume of precipitation has delayed the onset of flowering among STDF trees (Borchert et al. 2004) by as much as two months (G. Frankie, personal communication, 20 February 2016), as they are triggered by precipitation cues at the beginning and ends of the dry season (Janzen 1967). As such, Costa Rican SDTFs have been identified to be highly sensitive to these shifts in precipitation, putting this ecosystem at high risk for irreparable damage (Enquist, 2002). Already, the plant community has begun to change (Enquist
& Enquist, 2011), and this will only worsen as the pollinator community continues to disappear.
Changes in climate that have lead to a mismatch between plants and their pollinators has already been seen on a global scale, and is trending toward local extinction of key pollinator populations
(Brown & Paxton, 2009; Goulson, Nicholls, Botías, & Rotheray, 2015; Schenk, Krauss, &
Holzschuh, 2017).
The question this project seeks to answer is how the STDF solitary bee community has responded to a series of unpredictable seasons. In other water-limited systems, years of drought largely favor generalist pollinators over specialists (Minckley et al. 2013). Furthermore, with repeated years of unfavorable weather with insufficient time for populations to recover, this change in community structure may have shifted into permanence (Boggs 2016). Eusocial species (such as Apis mellifera or the stingless bees) are largely unaffected by such changes
5 (Heithaus 1979, Frankie et al. 2005). In contrast, the solitary pollinator community seems to be at great risk for local extinction, evidenced by a gradual decline in abundance and diversity in the region (Frankie et al. 2009), and by differences between historical and modern observations in
SDTFs (Jones and Buchmann 1974, Frankie et al. 2005).
The second chapter of this thesis investigates how the SDTF pollinator community structure has changed with respect to how each species functions as pollinators within the community, and examines turnovers in species dominance over time.
The third chapter analyzes possible environmental causes for why the solitary bee community has lost diversity, and seen turnovers in species dominance. For the most part, I consider each season’s community structure within the context of changes in precipitation patterns associated with climate change on strongly seasonal floral resources.
6 CHAPTER II
CHANGES IN ABUNDANCE AND COMPOSITION IN THE SEASONALLY DRY
TROPICAL FOREST POLLINATOR BEE COMMUNITY: A COMPARISON
BETWEEN HISTORICAL AND CURRENT COMMUNITIES
ABSTRACT
The loss of ecosystem function and services resulting from worldwide insect population declines and species loss has alarming ecological implications. The potential impacts of the decline of native and managed bees on plant reproduction are receiving considerable attention; however, there is insufficient information about the current conservation status of tropical bees. I compared pollinator bee communities in the seasonally dry tropical forest (SDTF) of Palo Verde
National Park (PVNP) and neighboring SDTF in Guanacaste, Costa Rica, from 1971-2018, using museum collections and field surveys. I also proposed that changes in bee communities result from changes associated with habitat, climate change, and the arrival of Africanized Apis mellifera in the mid to late 1980s. To establish the composition and abundance of historical pollinator communities, I examined the records of 6,475 specimens collected in the seasonally dry tropical forests of Guanacaste from four different institutions: Museo Nacional de Costa
Rica, Universidad de Costa Rica, the USDA Bee Biology and Systematics Laboratory at Utah
State University, and the Brown Family Education Center at Kenyon College. I compared the historical records with dry season surveys conducted at PVNP in 2016-2018. There was a
7 general decline of solitary bee diversity and abundance in PVNP, with a clear declining trend at the species level for bees in the genus Centris, and Xylocopa subvirescens. Historically common species in the Halictid family, three Xylocopa species and Gaesischia exul (Apiddae) have become more prominent, and there were changes in the abundance of native eusocial bees
(Cephalotrigona, Melipona, Plebeia, and Trigona). Melipona beecheii appears extirpated from
PVNP, while the abundance of A. mellifera increased. Overall, the abundance and diversity of solitary bees were lower in dry years, while eusocial bees thrive. The increase in the abundance of A. mellifera in the mid-1980s coincided with the decline of Meliponid bees.
INTRODUCTION
There is an increasing alarm about the ongoing decline of insect populations worldwide and how the current climate change scenario is exacerbating this process (Dirzo et al. 2014,
Salcido et al. 2020, Cardoso et al. 2020). One subject receiving particular attention is the global population decline and species loss of native and managed bees. These declines are linked to stress caused by parasites, pesticides, and changes in the flowering phenology of the plants they visit (Biesmeijer et al. 2006, Brown and Paxton 2009, Bartomeus et al. 2011, 2013, Lebuhn et al.
2013, Goulson et al. 2015). As this situation persists, declining bee populations are at increased risk of local extinction (Potts et al. 2010), and many species are likely to experience range shifts
(Kuhlmann et al. 2012, Kerr et al. 2015), potentially creating a global pollination crisis. In addition to the threats that damage bee populations, plant-pollinator relationships are also being disrupted by anthropogenic and environmental changes worldwide (Burkle et al. 2013, Solga et al. 2014, Polce et al. 2014, Xiao et al. 2016). However, more information is needed to determine
8 the impacts on the diversity and community composition of native bees in seasonally dry tropical forest areas, the most threatened tropical ecosystem (Janzen 1987, Miles et al. 2006).
Seasonally dry tropical forests (SDTF) are particularly vulnerable to disruptions of the ecological processes that determine plant-pollinator interactions (Miles et al. 2006, Quesada et al. 2011, Allen et al. 2017). SDTFs are the second-largest tropical forest type, comprising nearly
40% of all tropical forests. These forests have a significant concentration of endemic species and a high diversity of life forms and functional groups of plants (Murphy and Lugo 1986, 1995,
Dirzo and Raven 2003, Miles et al. 2006, Linares-Palomino et al. 2011). Historically, SDTFs have experienced large-scale deforestation and are considered highly threatened ecosystems throughout the world (Murphy and Lugo 1986, Janzen 1987). Currently, 95% of the remaining
SDTFs face two or more threats capable of disrupting ecosystem functions, including climate change, habitat fragmentation, fire, human population density, and cropland conversion (Miles et al. 2006). These anthropogenic threats can harm plant and pollinator communities, further affecting these already threatened ecosystems (Janzen 1987, Miles et al. 2006, Quesada et al.
2011, Allen et al. 2017, Razo-León et al. 2018, Galbraith et al. 2020).
The overall bee species richness peaks during the dry season in the SDTFs of Costa Rica in concurrence with the abundance and diversity of floral resources (Frankie et al. 1974, 2004,
Gentry 1974, Heithaus 1974). Some SDTF trees have adaptive traits to minimize water loss during the long dry season, shedding their leaves to minimize water losses while flowering profusely (Dirzo et al. 2012). The diversity and structure of the dry season bee community
9 depend on the availability of resources such as nectar, pollen, and resins, the foraging habits of the bees, and their reproductive behavior (Lobo et al. 2003, Palmer et al. 2003, Alvarenga et al.
2020, Escobedo-Kenefic et al. 2020, Galbraith et al. 2020). However, prolonged droughts may limit flower resources, intensifying interspecific competition among bees and causing enormous stress on the seasonal specialist bees (Minckley et al. 2013, Souza et al. 2018). Additional strains, such as the introduction of non-native species (Kearns and Inouye 1997, Cairns et al.
2005), and habitat destruction (Brosi et al. 2008, Frankie et al. 2009, Quesada et al. 2011,
Escobedo-Kenefic et al. 2020) are known to exacerbate the threats to native specialist bees.
Mass-blooming trees and vines provide a significant portion of floral resources utilized by bees during the long dry season (Janzen 1967, Frankie et al. 2004). Because solitary bees have a limited flight season and reproductive period, they are more likely to maximize foraging efficiency via specialization on floral resources. Consequently, most solitary bee species depend on the availability of mass-flowering SDTF trees during the dry season for resources (Gerling et al. 1989, Frankie et al. 2013). Herbaceous plants bloom to a lesser extent during the dry season and are primarily pollinated by eusocial bees, specialized small-bodied solitary bees, and the nectar-robbing solitary Xylocopa bees (Frankie et al. 1998, Michener 2000). Consequently, solitary bee species are most sensitive to reductions in the availability of mass-flowering SDTF trees during the dry season for resources.
There is insufficient information about the factors that directly induce and release solitary bee diapause. However, it has been noted that the emergence and foraging time of solitary bees
10 strongly coincides with the availability of food and nest-building materials (Denlinger 1986). In contrast, eusocial bees tend to be generalists in utilizing floral resources and can forage year- round (Heithaus 1979). Cleptoparasitic bee species, another group of dry season specialist bees that lay their eggs in finished but unsealed cells in nests of solitary bees, seem to track the activity of solitary bees and serve as an indicator of the health of solitary bee populations
(Sheffield et al. 2013). The timing of the production of pollen, nectar, and resins by SDTF trees seems to affect the abundance and composition of bee communities, particularly defining the diversity of solitary and cleptoparasitic bees (Heithaus 1974, 1979, Frankie et al. 2004).
SDTFs in Central America experienced significant anthropogenic change due to land practices (Edelman 1985, Calvo-Alvarado et al. 2009), changes in the frequency and severity of
El Niño Southern Oscillation, and the reduction in precipitation due to global climate change
(Castro et al. 2017, 2018, Stan and Sanchez-Azofeifa 2019, Stan et al. 2020). Such changes are likely to affect the abundance and diversity of the dry season specialist solitary bees. Moreover,
I also predict a decline of native eusocial Meliponines resulting from the arrival of Africanized
Apis mellifera to the region. I address two hypotheses on bee communities in Palo Verde
National Park: 1. The SDTF bee pollinator community structure has changed from 1971 –
2018. I predict changes in genera dominance and a general reduction in the abundance and diversity of sensitive solitary seasonal specialists. 2. The arrival of Africanized Apis mellifera in the mid to late 1980s should contribute to the declines in native eusocial stingless bee populations in the SDTF.
11 MATERIALS AND METHODS
Study site
This study was conducted in the SDTF of Palo Verde National Park (PVNP), Bagaces,
Guanacaste, Costa Rica. Located in the lowlands on the Nicoya peninsula, the 19,000-hectare park is surrounded by sugar cane fields and rice paddies and protects one of the last contiguous
SDTFs remaining in Costa Rica. Other significant systems within the park include a large marsh fed by the Tempisque River, and transitional SDTF areas in various stages of succession.
Annual rainfall in this part of Costa Rica ranges from 717 to 2600 mm per year (mean =
1536 mm). A well-defined dry season extends from late November to mid-May. The mean annual temperature is 28° C, and the mean relative humidity is 81% (Brenes-Prendas et al. 2006).
Vegetation in this area is classified as Tropical Dry Forest according to the Holdridge life zone system (Holdridge 1967, Holdridge and Grenke 1971, Hartshorn and MacHargue 1983)
Project Methods
Current communities
To determine the current abundance and composition of the SDTF bee pollinator community, I captured and identified all bees visiting flowers of thirteen tree species and three vines species during the dry seasons of 2016 and 2018 in PVNP. Sample methods mimicked those used in historical sampling efforts (Frankie et al. 1976, Heithaus 1979), but I increased the frequency of sample efforts to improve detection rate. I sampled each flowering plant species using aerial sweep nets during mass-flowering events from 5:45 am-10:45 am, and then again
12 from 2:00 pm-4:00 pm. For flowering trees, the net was fitted onto a pole extendable to 5m in length, enabling technicians to reach the mid-upper canopy on targeted trees. Flowering vines
(Ipomoea spp. & Cydista diversifolia) had deep-throated flowers, enabling a mixed-methods approach of both sweep-netting and hand-trapping bees as they exited flowers. Sampling periods were structured to permit 40 minutes of sweeping the target plant species, followed by a 20- minute break to record observations and label collected bees. I retained two to three voucher specimens of each bee species each day of sampling and recorded and released all other captured bees at the end of the morning and the afternoon sampling periods. Live vouchers were frozen and later pinned and identified to genus. Efforts were made to relocate to different locations in the park after each subsequent collection day to minimize risk of recapture, but it is possible that observation frequencies were slightly inflated.
Historical pollinators
To establish the composition and abundance of historical pollinator communities, I pooled 6,475 records of voucher specimens collected in SDTFs of Guanacaste, Costa Rica, from four different institutions. These included Instituto de Biodiversidad (1,749 bees), Universidad de Costa Rica (110 bees), the USDA collection at the Bee Biology and Systematics Laboratory at
Utah State University (3,858 bees), and the collection of Ray Heithaus held at the Brown Family
Education Center at Kenyon College (612 bees). Collection dates for these specimens were restricted to dry season months (November – May) and spanned from 1971-2004. Specimens considered were sampled in SDTF located in PVNP, Santa Rosa National Park, Barra Honda
National Park, Lomas Barbudal Biological Reserve, and SDTF surrounding the cities of Cañas
13 and Bagaces. Because of concerns with the reliability of species identification in some genera, I only keyed those individuals to the genus level.
Data analyses
Establishing patterns in bee pollinator community structure over time. Because the dry season does not follow the calendar year, I grouped museum records into seasons that spanned from late November to mid-May of the following year. For analyses of changes to the community over time, all data were standardized using rarefaction to ensure quality representation of each season and to avoid statistical problems with different sample sizes. I excluded those dry seasons with small collection sizes from analysis, and I rarefied all seasons using the lowest sample size (set by the 1993-1994 season with 96 bees). This selection criteria limited the analysis to thirteen seasons for comparisons of community structure over time. I calculated the Shannon’s Diversity Indices and Pielou’s Evenness for the bee communities using the rarefied community assemblage data for each of the thirteen seasons. I further analyzed for shifts in species diversity, evenness, ranked abundance, and species turnover using the package codyn in R.
I compared community composition for each season in a multi-dimensional space utilizing a Bray-Curtis based Nonmetric Multi-dimensional Scaling (NMDS, R package vegan) ordination model using the rarefied dataset. I used single-factor permutational multivariate analysis of variance (PERMANOVA) and analysis of similarity (ANOSIM) as post-hoc tests to
14 examine differences in the Bray-Curtis dissimilarity matrix of species assemblages between seasons by decade.
Characterizing change in structure with species turnover and reproductive habit. The best historical description of the SDTF pollinator community structure came from a comprehensive survey conducted by Heithaus from 1971-1972 (Heithaus 1979). To compare Heithaus’ 1979 description of community structure against my 2016-2018 observations, I conducted a chi-square test of heterogeneity on the proportion of bees sampled in each family. I also grouped all species according to the modal reproductive behavior of each genus into one of the following functional groups: native eusocial, introduced eusocial, solitary, and cleptoparasitic bees. Following, I also made comparisons between proportions of bees sampled in each of four “functional groups” to determine changes in the community assemblage of seasonal specialists and temporally- generalized eusocial bees. Cleptoparasitic genera were separated to help track populational differences in solitary host species (Sheffield et al. 2013). The solitary genera included a few
Halictid genera known to have weak social tendencies. A further distinction was also made between the native and non-native eusocial bees to track the effect of the hybridized Apis mellifera population surge in the mid to late 1980s and into the early 1990s. I conducted a
SIMilarity PERcentages analysis using the rarefied dataset to determine which genera contributed most to between-group differences between dry seasons (R package, vegan). The genera identified in this analysis were used to characterize turnover in dominance in the bee communities sampled between 1971–2016
15 RESULTS
Establishing patterns in bee pollinator community structure over time
In the dry seasons of 2016 and 2018, total of 1,257 pollinating bees were sampled on thirteen species of flowering trees and three vines found in PNVP. Adding these observations to the historical data, a total of 68 genera were identified in the 7,067 bees sampled in the thirteen dry seasons included in this study. The number of genera sampled ranged from 14 in 1993-1994 to 46 in 1989-1990 (Table 1) with an average of 30 taxa sampled over the thirteen seasons.
Variation in the number of taxa can be grouped into three periods (Figure 1A): 1. A period of fluctuations around the mean in the 1970s and early 1980s, 2. A period of higher diversity in the late 1980s and early 1990s, and 3. An ongoing period of lower diversity starting in the mid-
1990s. In general, rare genera added most of the diversity in each sample year, while the community is dominated by a few genera in each season (Figure 1B), and showed a high amount of variance between sample years (Figure 1A). The number of genera observed in all families was significantly reduced after the 1900’s (Figure 1C), including the corbiculate and non- corbiculate Apidae. This impacted the proportion of the functional groups found in each season across the board, but the most noticeable impact was in the richness observed for the solitary and cleptoparasitic genera (Figure 1D). Observations made in 2016-2018 (n = 1,257) were a quarter of those made in 1971-1972 (n = 4,505), even with the potential effects of inflation with the risk of recapturing released individuals over time.
Although most specimens could only be reliably identified to genus, two genera of solitary bees, Centris and Xylocopa, could be reliably identified to species. I compared the
16 species richness and abundances of these two genera for all seasons with enough samples of these species, along with solitary long-horned bee, Gaesischia exul, to further capture the change in composition and abundance of characteristic solitary bee species at the species level (Figure
2). Overall, there are changes in species richness and abundance in Centris and Xylocopa, where current diversity is the lowest (Figure 2A and 2C). For Gaesischia exul, there is a marked change in their abundance in the samples obtained in 2016-2018. However, the relative abundance of Centris, Xylocopa, and Gaesischia exul remained similar over time (Figure 2D).
Overall, my results showed no trend in Shannon’s diversity and Pielou’s evenness scores calculated for the rarefied community samples (Table 2). However, NMDS analysis using rarefied bee community assemblage of sampled seasons suggests that communities were clustered by decade, except for the sample from 1977-1978 (Figure 3). Community samples obtained in 2016, 2018, and 1977-1978 had lower Shannon’s diversity scores and are more similar to each other in species composition than to those of other seasons. Furthermore, my analysis also revealed differences in abundance and composition of bee communities between and within decades (ANOSIM R2 = 0.34, p = 0.035 and PERMANOVA R2 = 0.44, df= 4, p =
0.006) (Figure 4). As a whole, the genera dominating the pollinator community appears to be very similar until the 1990s, demonstrated by a broad dispersal over the NMDS plot area (Figure
3) and the high within-decade variance in community structure (Figure 4).
17 Characterizing change in structure with species turnover and reproductive habit
A comparison between the raw data of the 1971-1972 Heithaus collection and 2016-2018 collections revealed significant heterogeneity in abundance by both functional group (χ2=782.7, df =3, p <0.001) and by family (χ2=141.85, df =5, p <0.001) (Figure 5B, D). My analysis showed that the proportions of species richness according to categories of functional group or family were not significantly different. However, it is important to note a significant difference in Shannon’s diversity indices of these two sample seasons (Hutcheson’s t: 4.88, df = 2015, p
<0.001), and an increase Pielou’s evenness (J1971-1972=0.727; J2016-2018=0.783) (Figure 5A, C). It is also important to note the larger presence of the Africanized bees, labeled as the “Introduced
Eusocial” functional group, as their proportion of the pollinator community increases.
The SIMilarity PERcentages analysis showed significant differences in the abundances of eleven common genera among the thirteen seasons. This analysis reveals changes in the abundance of native eusocial bees (Cephalotrigona, Melipona, Plebeia, & Trigona), the introduced eusocial (Apis mellifera), and native solitary bees (Centris, Exomalopsis, Gaesischia,
Megachile, Ptiloglossa, & Xylocopa) (Figure 6). For the eusocial bees, the formerly common native stingless bee, Melipona, appears to be extirpated from PVNP. Meanwhile, the surviving native stingless bees responded strongly to population fluxes of the introduced Apis mellifera.
Among the common solitary bees not found in recent years were the genus, Ptiloglossa, and previously dominant genera such as Centris, Exomalopsis, and Megachile gave way to
Gaesischia and Xylocopa. Lastly, the relationship between the relative abundance of common eusocial and solitary genera appears to have equalized in the current system relative to the historical dry season community structure.
18 DISCUSSION
This study showed that the abundance and composition of bee pollinator communities in the SDTF of PVNP and neighboring areas have changed since the first extensive sampling conducted by Heithaus (1979). The emergent trend indicates a significant shift in the early
1990s that culminated in the loss of diversity from rare genera, a change in the proportional abundances of bee families and functional groups, and the replacement or loss of previously dominant common genera.
Establishing patterns in bee pollinator community structure over time
A comparison between the Heithaus (1979) results and my 2016-2018 observations revealed a clear difference in diversity scores, reflecting the general decline of bee diversity consistent with other studies in the region (Frankie et al. 1998, 2005, 2009, 2013). Relatively rare species contributed a significant portion of taxa diversity in the historical samples; however, these taxa became less frequent after 1993 (Table 1 and Figure 1B). Overall, bee abundance has diminished, even in spite of slight recapture risks inherent in the catch and release collection method used in 2016 – 2018. Most taxa have natural fluctuations of abundance, but in PVNP, several previously dominant species and entire genera have entirely disappeared. In contrast, one new species, the eusocial Apis mellifera, is now a dominant pollinator, booming in the late
1980s to the early 1990s, then dropping to an apparent stable state (Figure 6).
19 Eusocial bees
The changes in taxa composition among eusocial generalist bees suggests that habitat disturbance and modification, and competition with Africanized Apis mellifera might play an essential role in driving those changes (Roubik 1978, 1980, Wilms et al. 1996). Following their introduction in Brazil, swarms of Africanized Apis mellifera hybrids were first established in
Costa Rica in 1984. Up to 75% of their genome was integrated and stabilized relatively quickly in the existing A. mellifera population throughout the country (Taylor 1985, Del Lama et al.
1990). Because of the tremendous success of the Africanized bees in lowland areas, European genomes were almost washed out in A. mellifera populations in the SDTFs of Costa Rica (Spivak
1992), and the resultant hybrid populations were projected to bring about local extinctions in stingless bee populations (Ramalho et al. 1990).
By the wet season of 1992, the hybrids were determined to have established in PVNP at intermediate levels of hybridization (Lobo 1995). Hybridization during the 1990s coincides with a dramatic increase in abundance of A. mellifera in museum records in 1994, and the disappearance of the genus Melipona and the small number of other stingless bee genera (Figure
6). Because the eusocial genera occupy a similar niche in SDTF (Wille 1963, Frankie et al.
2013), it would follow that native eusocial genera would have experienced intense competition for resources. A meta-analysis conducted by Ramalho et al. (1990) in the neotropics found that other stingless genera were more generalized foragers than Melipona and Africanized A. mellifera in host plants preference. Of the 288 observed host species, 25% were shared between
20 the hybrids A. mellifera and the native bees, placing the genus Melipona in a potential competitive disadvantage over limited resources (Ramalho et al. 1990).
Other studies in neotropical areas observe similar patterns of native bee species decline in the presence of Africanized hybrids (Roubik 1978, 1980, Wilms et al. 1996). These studies revealed that Africanized A. mellifera is in direct competition with the native stingless bees for food sources. However, Roubik and Villanueva-Gutiérrez (2009) noted that native stingless populations could remain stable in the presence of these hybrids, and Wilms et al. (1996) suggested that coexistence is possible so long as resources are stable. Frankie et al.(2002) proposed eight mechanisms for the partitioning of flower resources that may limit the effects of
Africanized A. mellifera on native bees in SDTFs in Costa Rica and thus allowed for their coexistence. However, the combination of anthropogenic disturbances limiting floral resources and intense competition with Africanized bees was responsible for the decrease in the diversity of native stingless bees and the local extinction of Melipona beecheii in the STDFs of Quintana
Roo, Mexico (Cairns et al. 2005). In PVNP, the common stingless bee genera, Trigona and
Melipona, appear to have been displaced during the proliferation of A. mellifera. While the reduction in the abundance of Trigona was temporary, Melipona is now absent from the PVNP.
Solitary bees
Another significant trend in this study was the decline in species diversity of solitary bees. The previously dominant genera Centris and Megachile appear to have exchanged positions with now-dominant genera Gaesischia and Xylocopa in the early 1990s (Figure 6). It is also
21 noteworthy that Xylocopa subvirescens have disappeared from the pollinator community of
PVNP (Figure 2A, C), while the three remaining Xylocopa species have become more prominent
(Figure 2B, C). Furthermore, specialized solitary genera such as Ptiloglossa are now absent, along with other less-common genera, such as Epicharis, Mesoplia, and other genera in
Andrenidae and Colletidae.
While the loss of diversity is apparent over time, there were high amounts of variation among surveys (Figure 1A). This finding is foreseeable, as most studies taken at small scales
(especially in the tropics) tend to have high variability in species richness, primarily owed to fluctuations in the presence and detection of rare species (Williams et al. 2001). Instead, the broader trend supported by my NDMS analysis and subsequent post-hoc tests is the similarity among communities sampled within the same decade (Figure 3). There are a few exceptions, such as the 1977-1978 season and the increase in within-group variation between 1987-1994
(Figure 4). The latter period (1987-1994) represented the best sampling coverage and effort in the historical dataset (Table 1). Moreover, this period also happens to coincide with a time of significant declines in precipitation (Williams et al. 2001) and the arrival of Africanized bee populations to PVNP (Lobo 1995). During this time, the community was most variable in the
1990s (Figure 4), suggesting a turning point for the dominance status of many common species.
The fact that samples taken in 2016 and 2018 are similar to each other despite the broad variation observed since 1971 could hint at a new equilibrium of species composition and warrants further study (Figure 3). Most disturbing in the comparisons between my observations and the historical
22 samples is the disparity in abundance and taxa richness despite an extreme difference in the intensity of effort dedicated to the collection.
Characterizing change in structure with species turnover and reproductive habit
My findings echo a world-wide phenomenon of high replacement rates and change in community composition in response to anthropogenic disturbance (Supp and Ernest 2014).
While diversity often correlates with stability, the fundamental essence lies in the composition of this community, as variations in the presence and dominance of common pollinator genera will have enormous implications for ecosystem function (Gaston and Fuller 2008). my results show a more even distribution among families in the 2016-2018 samples than in earlier surveys (Figure
5). Also notable is the absence of two families, Andrenidae and Colletidae. These families disappeared from the samples between mid-1992 and 2002 (Figure 1A). While both families contained rare species, I must also point out that they also are frequent visitors of the SDTF plants I sampled. Colletidae includes the genus Ptiloglossa, a once common pollinator now absent in PVNP. I also documented an unexpected departure from Heithaus’ observation of eusocial bee (corbiculate Apidae) abundance. This departure calls into question the relative stability of the eusocial populations suggested previously and set the stage for the possibility of competitive interactions between the Africanized A. mellifera hybrid and the native stingless bee genera.
The abundance and composition of the four functional groups, i.e., native eusocial, introduced eusocial, solitary seasonal specialist, and cleptoparasites, shifted from 1972 to 2018.
23 The proliferation he non-native eusocial species Apis mellifera, accompanied a decline in the abundance of native eusocial bees in PVNP relative to 1972 (Figure 5). Meanwhile, cleptoparasites and solitary species have maintained their overall presence in the community among most surveys. However, the overall diversity of solitary bees declined, and the bee community structure has shifted, as the ratio of diversity of abundance changed for all functional groups.
In contrast, the shift in species dominance in solitary specialist bees is likely to be attributable to changes in abiotic factors impacting food sources and habitat suitability (Galbraith et al. 2020). Genera such as Xylocopa and Gaesischia appear to be least affected in PVNP because, while they visit floral resources with strong seasonal responses, they are strongly associated with plants that are not sensitive to precipitation cues. In particular, Xylocopa is seen on most flowering plant species and can chew its way into flowers to obtain its rewards.
Gaesischia commonly visits Parkinsonia aculeata, a species living on the edge of the wetland in
PVNP, which has an extended blooming period throughout the dry season and appears to be a relatively more reliable food source. Meanwhile, Centris, Megachile, and Ptiloglossa are strongly associated with plants with mass flowering episodes cued by seasonal precipitation patterns, thus providing a possible link between resource limitation and declines in these genera.
There are descriptions of the relationship between solitary bee diversity and abundance and its potential mismatches with their floral resources within the contexts of anthropogenic habitat modification and climate change (Hoiss et al. 2015, Xiao et al. 2016, Schenk et al. 2017). Bee phenology decoupled from their plant hosts, and native populations decline due to climate
24 change is known in higher latitudes (Forrest and Thomson 2011, Burkle et al. 2013). However, there is insufficient information on the consequences of precipitation patterns on plant-pollinator synchronization in the tropics.
The history of land use in the province of Guanacaste challenges the notion that anthropogenic habitat degradation is driving bee community structure. Compilations of land-use practices in Guanacaste indicate that degradation of SDFTs in Guanacaste dates to the early
1500s (Edelman 1985, Calvo-Alvarado et al. 2009), and extensive Haciendas were well established in the 1800s (Edelman 1985). Widespread cattle raising started in the 1900s, but driven by the high beef prices in the international market, the fastest clearing of forest for pasture expansion occurred between 1950 and 1970, eliminating most SDFTs in Guanacaste. Changes in government policies and low beef prices halted the expansion of the cattle industry a decade later. In 1996, Costa Rica approved new legislation to restrict timber extraction and land used change of forest on private land and implemented a program of Payments for Environmental
Services. As a result of these changes, Guanacaste had a high rate of forest regrowth from 1986 to 2005; and only 20% of the total forest cover was in government-owned conservation units, meaning that most of the regrowth took place in private lands (Arroyo-Mora et al. 2005a,
2005b).
PVNP is part of the Hacienda COMELCO, a large cattle ranch expropriated by the Costa
Rican government in 1975 (Hartshorn, 1983). It became the Palo Verde National Wildlife
Refuge in 1977. In 1980, the Costa Rican government added an adjacent property to the Wildlife
25 Refuge and established the 18,410 ha Palo Verde National Park (Hartshorn and MacHargue
1983). The cessation of cattle raising and effective fire control in PVNP created a mosaic of patches of different time combinations since pasture abandonment and the last fire episode increasing forested areas. Counter-intuitively, multiple bee populations in PVNP declined during the same period.
The increase in the duration in the severity of El Niño-Southern Oscillation (ENSO) episodes also occurred at the time forest recovery (Castro et al. 2017, Stan and Sanchez-Azofeifa
2019). The eight of most severe ENSO episodes occurred between 1972 and 2018, including those of 1983, 1998, and 1973 that are considered the top three ENSO years
(https://psl.noaa.gov/enso/climaterisks/years/top24enso.html). my field seasons included a sample of the 2015-2016 ENSO year, while museum collections included the 1991-1992, 1987-
1988 ENSO episodes. Other authors reported the potential effects of ENSO episodes on freshwater macroinvertebrates (Gutiérrez-Fonseca et al. 2018), birds (Wolfe et al. 2015,
Barrantes and Sandoval 2019), frogs (Anchukaitis and Evans 2010), and the productivity of
SDTFs (Castro et al. 2018). my analysis shows some similarities in bee communities in ENSO years and the following years in the late 1980s and in the 1990s. The grouping those years on the right side of Figure 3, suggests that ongoing climate change and the increase in the frequency and severity of ENSO years may have contributed to the changes in the abundance and diversity of bee communities in PVNP .
26 In summary, the community of pollinating bees of SDTF has changed in Guanacaste,
Costa Rica. Many mechanisms could potentially drive observed patterns of change. For the eusocial bees, I argued that interspecific competition with Africanized Apis mellifera might have influenced the bee community structure in PVNP. However, more work should be conducted in
Costa Rican SDTF to test this hypothesis directly. Furthermore, the changes in the abundance and diversity of the solitary bees are more complex, suggesting that the mixed actions of the modifications of climate patterns and the ongoing anthropogenic modifications of the environment are affecting the abundance and composition of pollinator bee communities in the
SDTFs of PVNP. Due to the plant-pollinator relationship between flowering SDTF plants and the solitary bee community, it is possible that these factors could influence the availability of floral and nesting resources utilized by bees, which could potentially explain differences in solitary bee community structure.
27 Figure 1. Dissecting differences in bee community structure across sample seasons. A. Anomalies in the number of taxa recorded in each sampled dry season relative to the mean (x=30) across all seasons. B. Number of taxa in each family in each sampled dry season. Corbiculate and non-corbiculate bees are distinguished to preserve original comparisons made by heithaus (1979) prior to taxonomic updates. C. The distribution of taxa in the community based on their relative abundance, where x is the percent composition contributed in terms of abundance. D. The distribution of taxa by functional group in each sampled dry season.
28 Figure 2. Population dynamics in three common SDTF solitary bee genera. A. Species abundances in the genus Centris, a solitary seasonal specialist that is declining in Costa Rican SDTF. B. Abundance for the solitary long-horned bee, Gaesischia exul. This common species has become dominant in SDTF in 2016-2018 samples. C. Species abundances for the solitary seasonal specialist genus, Xylocopa. This genus is a generalized forager and has become a dominant species in SDTF. D. A comparison of species richess for Centris, Xylocopa, and Gaesischia over time in SDTF. Xylocopa and Gaesischia have remained relatively stable, while Centris declines.
29 Figure 3. Non-Metric Dimensional Scaling model for bee communities from thirteen dry seasons. Constructed using Bray-Curtis distances (stress = 0.1421). Position of bee communities in multidimensional space for each sampling decade are shown with different colors.
Figure 4. Boxplots mapping the variance in bee community structure during the dry season between decades. Used program ANOSIM.
30 Figure 5. Comparison between historical bee community structure of 1971-1972 and 2016- 2018 in the SDTF of Guanacaste, Costa Rica. This approach evaluates the relative contribution of four functional groups (A, B) and the five families (C, D) to the abundance (B, D) and richness (A, C) of bees collected while visiting flowers. Contributions were calculated on the basis of the number of specimens observed in each functional group or family in relation to the total number of specimens or recorded in each sampling period, respectively. For 1971-1972, total number of specimens captured are 4,511 and 39 taxa were observed. In 2016-2018, 25 taxa were observed in the 1,257 bees sampled .
31 Figure 6. Taxa turnover of the dominant SDTF pollinator genera in eusocial (Apis, Cephalotrigona, Melipona, Plebeia, & Trigona) and solitary (Centris, Exomalopsis, Gaesischia, Megachile, Ptiloglossa, & Xylocopa) bees in the SDTF of Guanacaste, Costa Rica. Turnover is shown by the changes of the relative abundance of the eleven genera most abundant genera in the thirteen dry season considered in this study.
32 Table 1: Presence/absence table of genera found in thirteen sampled dry seasons in Guanacaste, Costa Rica. The relative abundance of each sampled genus is represented by asterisks to depict each genus’ proportional contribution to community structure during sampled years, where: * represents an abundance less than 1%, ** between 1% and 5%, *** between 5% and 10%, **** between 10% and 20%, and ***** an abundance greater than 20%. In total, 68 different genera were observed records of 7,067 bees sampled in these thirteen seasons.
Family Genus 1970 - 1971 1971 - 1972 1977 - 1978 1987 - 1988 1988 - 1989 1989 - 1990 1990 - 1991 1991 - 1992 1992 - 1993 1993 - 1994 2001 - 2002 2015 - 2016 2017 - 2018 Andrenidae Protandrena ** Pseudopanurgus ** * * * Apidae Ancyloscelis **** ** ** * * ** * Apis * * **** ** ** **** **** *** ***** ** *** **** Centris *** **** ***** *** **** ***** ** ***** *** ** * ** ** Cephalotrigona * ** *** * * ** *** ** *** ** ** *** Ceratina * ** * * * ** * * * ** ** Diadasia ** Epeolus * Epicharis *** ** * * Eufriesea * * Euglossa * * ** ** ** * ** ** * ** Eulaema ** * * * * ** * * **** ** * ** Exaerete * ** * * * * Exomalopsis ***** *** * * * ** ** ** * * Florilegus * ** * Frieseomelitta * * Gaesischia ** *** ** ** ** ** ** ***** ***** **** Geotrigona * Melipona ** ** **** ** * * ** * * Melissodes * * ** ** ** ** *** ** Melissoptila * * Melitoma * ** * ** ** Mesocheira * Mesoplia ** * ** ** ** * * Nannotrigona ** * * * ** ** **** ** ** ** ** Nogueirapis * Nomada ** * Odyneropsis * Osiris * Oxytrigona * *** Paratetrapedia ** ** * ** ** ** * * *** ** Paratrigona * Partamona * * * ** *** Peponapis * Plebeia ** ** * ** ** ** * ** **** * Scaptotrigona ** * ** * * * ** ** Tetragona ** ** * ** ** ** ** Tetragonisca ** * Tetraloniella * Thygater * Triepeolus * * * ** * Trigona *** ** ** ** ** ** ** *** * *** *** Xylocopa * ** *** ** ** ** ** **** *** *** ** ** **** Colletidae Calliopsis * * * ** * ** Colletes * * ** Hylaeus * * * * Ptiloglossa *** ** ** ** **** ** * ** **** Halictidae Agapostemon * * * ** * * Augochlora ** ** ** ***** *** ** ** ** *** ** * Augochlorella ** ** * ** ** ** ** *** ** Augochloropsis ** ** ** *** * * ** Caenaugochlora ** * * ** *** ** ** ** Halictus ** * ** * * ** ** Megalopta * * * * * * * ** Neocorynura * Pseudoaugochlora * Temnosoma * Megachilidae Anthidiellum * * ** * * ** ** Anthidium *** * Anthodioctes ** * ** **** * Coelioxys ** *** **** * ** ** * * *** * * Heriades ** * ** * ** * Hoplostelis * * * * Hypanthidium * * Lasioglossum *** * * *** * ** * ** ** * Megachile **** **** ***** ***** ** ** *** *** *** ***** *** ** Stelis ** SPECIES COUNT 27 36 18 29 40 46 42 40 23 14 29 20 24 SAMPLE SIZE 149 369 317 654 1342 845 811 715 201 92 313 394 865
33 Table 2: Measures of diversity calculated on rarefied dataset (s = 96) of thirteen dry seasons that were representative in terms of sample duration and size. Shannon’s Pielou’s Species Season Sample Size Index Evenness Richness 1970 - 1971 2.56 0.84 21 148 1971 – 1972 2.92 0.86 30 375 1977 – 1978 2.09 0.87 11 312 1987 – 1988 1.59 0.60 14 549 1988 – 1989 2.48 0.79 23 1417 1989 – 1990 2.89 0.88 27 751 1990 – 1991 2.94 0.90 26 1157 1991 – 1992 2.47 0.83 20 687 1992 – 1993 2.36 0.82 18 220 1993 – 1994 1.85 0.70 14 96 2001 – 2002 2.84 0.89 24 313 2015 – 2016 2.42 0.87 16 394 2017 – 2018 2.36 0.85 16 865
34 CHAPTER III
LONG-TERM VARIATION IN PRECIPITATION PATTERNS AFFECT PLANT-
POLLINATOR RELATIONSHIPS OF SEASONALLY DRY TROPICAL FORESTS TREES
ABSTRACT
There is concern about the decline in bee diversity and abundance in the seasonally dry tropical forest (SDTF) of Central America, and tropical ecologists are trying to uncover the factors driving this process. Because of the relationship between precipitation-cued flowering plants and the declining bee species, variation in precipitation cues could likely cause a mismatch between flowering time and bee activity. Meteorological data was gathered from several sources to create a dataset of precipitation information. To examine the relationship between precipitation patterns and the availability of floral resources, I used pollen samples taken from bee specimens from four museum collections and published data to create a historical dataset of flowering times of SDTF trees and bee communities. To isolate changes in precipitation patterns, I ran a time series analysis on the precipitation data. I then tested the correlation between precipitation cues, floral resource availability, and bee community structure to explain the loss of diversity and abundance in the SDTF pollinator community. The results of the time series analysis indicate a one-month delay in the timing of the last peak in precipitation before the onset of the dry season. I found a correlation between the timing of this precipitation peak and bee community structure. I did not find any correlation between pollen availability and
35 the descriptors of precipitation, or bee community structure. Lastly, I also conducted a comparative bipartite network analysis to compare the relationship between five SDTF plant species and their pollinators based on published literature and museum specimen collection tags and the current pollinators observed in 2016-2018. I found differences in the structure and composition between the historical and 2016-2018 plant-pollinator network, as indicated by the shifts in bee species visiting these species. These findings suggest that variation in precipitation patterns associated with the ongoing climate change has influenced floral resources and bee communities; however, additional research is necessary to verify this conclusion.
INTRODUCTION
There is increasing concern about changes in the amount and seasonality of precipitation in Central America during the last 30 years (Dokken 2014). Climate projections predict that the semi-arid lowlands within this region, particularly in the seasonally dry tropical forests (SDTF) of northwestern Costa Rica, are undergoing annual reductions in precipitation and changes in the onset and duration of the dry season (Chadwick et al. 2016, Allen et al. 2017). These changes in
SDTF precipitation patterns are projected to increase in severity, causing ecological droughts that might interrupt critical ecosystem processes (Dai 2013 p. 20, Allen et al. 2017, Stan et al. 2020).
Enquist (2002) and Enquist and Enquist (2011) suggested that rainfall reduction has increased tree mortality, decreased tree recruitment, and shifted forest community composition toward drought-resistant plants. Climate change can also cause a shift in the flowering time of SDTF plants (Haselhorst et al. 2017), potentially impairing plant-pollinator synchronization, further affecting SDTF communities (Janzen 1987, Janzen and Hallwachs 2021).
36 Seasonally dry tropical forests include nearly half of the tropical and subtropical forests worldwide. They are broadly defined as water-limited systems that undergo a dramatic change between wet and dry seasons. SDTFs have plant communities rich in endemic species, high beta-diversity between communities, and woody species adapted for prolonged droughts
(Pennington et al. 2009, Dirzo et al. 2012, Banda et al. 2016). For some species, prolonged absence of precipitation triggers leaf senescence, bud development, and flowering (Reich and
Borchert 1984, Borchert et al. 2004). Alternatively, sporadic showers throughout the dry season and the first heavy showers of the rainy season trigger blooming in some tree species whose flower buds developed during the previous wet season (Borchert et al. 2004, Calle et al. 2010).
Differences in cues triggering flowering and bud and flower development rates among
SDTF tree species produce a somewhat staggered series of mass-flowering events during the dry season (Gentry 1974, Frankie et al. 1976, Borchert et al. 2005). Staggering flowering and increased flower visibility facilitated by the absence of foliage enhance pollinator services during the dry season (Janzen 1967, Frankie et al. 1976). Solitary bees are the main contributors to the pollination of SDTF trees. Peak solitary bee diversity and abundance historically coincides with seasonal availability of resources provided by mass flowering SDTF trees during the dry season
(Frankie et al. 1976, Frankie and Coville 1979, Heithaus 1979). As a result, the phenology of dry season flowering plants is likely a strong predictor of the solitary bee community in SDTF. The diversity of cleptoparasitic bee species peaks also with the diversity of potential hosts during the
37 dry season, making them strong indicators of solitary bee population dynamics (Heithaus 1979,
Frankie et al. 1993, Vinson et al. 2010, Sheffield et al. 2013).
In contrast, introduced and native eusocial bee species forage continuously throughout the wet and dry seasons, store resources for times of scarcity, and gather pollen from herbaceous and woody plants during the dry season (Heithaus 1979, Roubik 1992, Frankie et al. 2013).
Borchert et al. (2004) argue that introduced and native eusocial bees, active year-round, are sufficient to provide pollination services for SDTF trees (Borchert et al. 2004). However, pollen
“gleaning” or otherwise minimal anther contact performed by this generalized functional group provides a lower value service to precipitation-sensitive SDTF trees (Wille 1963). In comparison to eusocial bees, solitary bees perform a variety of pollen-collecting strategies and foraging patterns that result in higher genetic diversity, pollen-transfer efficacy (Eeraerts et al.
2020), and fruit sets (Blitzer et al. 2016). Consequently, the intricate relationship between dry season flowering plants and their pollinators depends on precipitation cues (Michener 2000).
This study aims to examine the impact of precipitation changes and pollen availability of
SDTF trees on the plant-pollinator relationships of woody plants flowering during the dry season. I propose that the production of floral resources by SDTF trees during the dry season is, at least in part, determined by the amount and timing of precipitation occurring during the prior rainy season and the onset of the next rainy season. I analyzed the flowering phenology of
Caesalpinia eriostachys, Tabebuia rosea, T. ochracea, Gliricidia sepium, and Senna pallida; five SDTF trees that respond to seasonal precipitation (Borchert et al. 2004). I also analyzed the
38 flowering phenology of Parkinsonia aculeata, a wetland tree species growing along the marsh of
PVNP; Cochlospermum vitifolium, a SDTF tree; and the vine Ipomoea carnea, which colonizes disturbed areas. Flowering in the last three species is largely thought to be triggered by photoperiod and not precipitation. I predict that changes in pollen availability coinciding with changes in precipitation cues determine the composition and abundance of bee communities visiting these eight plant species.
MATERIALS AND METHODS
Study site
I conducted this study in the Palo Verde National Park, Bagaces, Guanacaste
(10º20'38.36'' N, 85º29'18.54'' W). PVNP protects a seasonal marshland between the Tempisque river and limestone hills in the North of the wetland and one of the last relics of seasonally dry tropical forests in Central America (Holdridge 1967, Hartshorn and MacHargue 1983).
Historically, mean annual rainfall in this area ranged from 1000 – 1500 mm, and temperatures ranged from 22-26°C (Holdridge and Grenke 1971). More recent publications and meteorological data from the Organization for Tropical Studies (OTS) Research Station at PVNP showed average annual precipitations ranging from 800 to 1200 mm and average annual temperature ranging between 27°C and 29°C (Holdridge 1967, Vaughan et al. 1994). Moreover, there are two well-defined seasons: a rainy season extending from May to November and a dry one from December to April (Janzen, 2018, OTS Field Station at PVNP).
Inside the PVNP, the areas adjacent to the Tempisque River are flooded during most of the rainy season, establishing an extensive wetland (marshy area or lagoon) with water levels
39 reaching more than a meter above the ground. Flooding is widespread in October and
November. In contrast, parts of these wetlands are completely dry between March and April.
Because of its extensive wetlands and the seasonal concentration of migratory birds, PVNP was included in the Ramsar List of Wetlands of International Importance in 1991.
PVNP was also established to protect the existing remnants of SDTF. Surrounded by sugar cane fields and rice paddies, this park protects one of the most extensive remaining stands of contiguous SDTF in Costa Rica. PVNP is known for its relatively high diversity among
Neotropical SDTFs, and the park appeared to be relatively insulated from anthropogenic disturbances in the decades (Gillespie 1999). While deforestation rates have slowed in the park's buffer area, its connecting biological corridors have become corroded, further isolating this threatened habitat (Sánchez-Azofeifa et al. 2003).
Precipitation data
To characterize how precipitation patterns have changed over time, meteorological data was compiled from the US National Oceanic and Atmospheric Agency, the Instituto
Metereológico Nacional de Costa Rica, and the OTS Research Station in PVNP (Appendix B). I organized the monthly precipitation by decade and calculated the average monthly precipitation for each decade from 1960 to 2020, and used time series analysis to determine the trend and seasonality of the precipitation patterns in the SDTFs of PVNP and its vicinity. I used the package forecast in R to identify any anomalies in wet season precipitation patterns from 1960 to
40 2018 (Hyndman 2017). This analysis compares seasonal averages and the observed precipitation for each decade to extrapolate the variation in the “seasonal” trend over time.
Flowering phenology
I monitored the flowering phenology of five SDTF tree species Caesalpinia eriostachys,
Tabebuia rosea, T. ochracea, Gliricidia sepium, and Senna pallida weekly during the 2016 -
2018 dry seasons in PVNP. I also analyzed the flowering phenology of Parkinsonia aculeata,
Cochlospermum vitifolium, and the vine Ipomoea carnea. I determine the onset, duration, and magnitude of flowering for each species with this weekly sampling scheme. I scored the flowering phenology of each blooming tree by walking around the tree or using binoculars from access roads and trails to estimate the percentage of its crown-bearing flowers.
Pollinator visitation
The SDTF bee pollinator community was sampled in PVNP during the dry seasons from
2016-2018. I sampled bees visiting the flowers of twelve species of trees using a 5 m extendable aerial sweep net. For the vine I. carnea, I sampled the vines using aerial sweeps and hand- trapping bees in the deep-throated corollas. Two to three individuals of each species were preserved as voucher specimens and identified to the lowest possible taxon. When loads of pollen were present, I chilled the bees in a cooler to temporarily immobilize them for pollen removal (see description below). Live bees were gradually warmed and released after pollen collection.
41 To reconstruct historical pollinator communities, a total of 6,475 specimens were accessed from the Instituto Nacional de Biodiversidad (1,749 bees), Universidad de Costa Rica
(110 bees), the Bee Biology and Systematics Laboratory at Utah State University (3,858 bees), and the Brown Family Education Center at Kenyon College (612 bees). These same records were then compiled with the 2016-2018 field observations and used to reconstruct pollinating bee communities for the dry season of twelve years.
Pollen collection and flowering phenology
Pollen was lifted from the scopal hairs, thorax, abdomen, and glossa of dead or temporarily immobilized bees using a staining glycerol gel (Kearns and Inouye 1997). The gel was then placed on a microscope slide and melted to produce a preserved, stained pollen sample.
Slides were then photographed and identified using Pollen and Spores of Barro Colorado Island
(Roubik and Moreno 1991), and a reference collection from pollen samples taken from dry- season-blooming plants in PVNP in 2016-2018.
Historical flowering phenology was reconstructed using the presence of pollen grains removed from the museum specimens of bees from four collections examined for this study used to reconstruct pollinator communities. Pollen samples were restricted to bees collected in SDTF of Guanacaste, Costa Rica during the typical dry season, estimated to start 15 November and end
15 May. Tropical insects are notoriously underrepresented in museum collections (Beck and
Kitching 2007); therefore, multiple collections from similar lowland SDTF in Guanacaste were included to ensure a sufficient sample size. This included bees collected at PVNP, Santa Rosa
42 National Park, Lomas Barbudal Biological Reserve, and the cities of Cañas and Bagaces. A few bees of each species were chosen for each sample date at each sample site, yielding 490 successful pollen samples.
Relationship between precipitation data, flowering phenology, and bee community structure
The effects of the cycles of wet season precipitation and dry season flowering phenology at the time of bee monitoring efforts were analyzed for each collection year that had sufficient sample coverage over dry season months. I used the date of the first pollen detection of each species as an indicator of pollen availability for that flowering species. I obtained the collection date from the identification label for each museum specimen from which I collected pollen. I used information from the pollen collections to reconstruct the flowering phenology of the eight
SDTF plant species; namely, C. eriostachys, G. sepium, S. pallida, T. ochracea, and T. rosea
(precipitation-cued); and C. vitifolium, I. carnea, and P. aculeata (precipitation independent).
The date of first pollen detection each dry season (flowering initiation) was determined for each species for twelve seasons of bee community data, and used to estimate the number of days between recorded peak precipitation events and pollen availability for that species. I used the total wet season precipitation, the time (month) and highest monthly precipitation, and the time and total precipitation of the last rain event as predictors of the beginning of flowering for each species.
43 I examined the relationship between precipitation patterns and pollen availability on bee community structure using Mantel tests. I organized the bee genera observed during twelve dry seasons from 1971-2018 into a rarefied Bray-Curtis dissimilarity matrix. I then calculated the
Euclidean distances for the timing and volume of peak wet season precipitation and the timing and precipitation volume at the start of the dry season between each season. To test the influence of pollen availability, I compiled two separate datasets of the first date of pollen records for the three precipitation independent and five precipitation-cued flowering SDTF vines and trees. I then standardized each of the predictor datasets and generated Principal Components Analysis
(PCA) scores to summarize these variables. I constructed Euclidean distance matrices with the scores of the first three PCA vectors. Subsequently, I calculated six Mantel tests to estimate
Pearson’s product-moment correlation between the Bray-Curtis Dissimilarity matrix of rarefied bee genera and the Euclidean distances of precipitation variables and pollen availability of precipitation independent plants and precipitation-cued plants (Diniz-Filho and Bini 1996). I used the R package vegan for these statistical analyses (Oksanen et al. 2018).
To further compare STDF pollinator community function changes over time, I constructed a comparative bipartite network analysis of visiting bees on five plant species commonly found flowering during the dry season in PVNP. I reconstructed historical visitation using published species lists of pollinator visitation for I. carnea (Keeler 1977), P. aculeata, C. eriostachys (Jones and Buchmann 1974), and S. palida (Wille 1963). I also used insect tag records from Ray Heithaus’ specimens at the Brown Family Education Center to reconstruct the pollinator community for G. sepium. A second network was constructed using observations
44 from bees collected from 2016-2018. I used these two networks to compare divergences in visitation from historical and current patterns. Finally, I used the Pearson homogeneity test to compare the composition of pollinator visits and the structure of the visitation patterns among the networks of flowering plants induced by precipitation and those flowering plants independent of precipitation cues.
RESULTS
Precipitation patterns
A time-series analysis of precipitation by decade allows comparing the observed precipitation data to the average seasonal pattern in precipitation from 1960 – 2018 (Figure 7.
Each segment of the time series analysis shows the average rainfall from January to December for each decade from 1970 to 2018; this allows comparing the average wet season precipitation pattern for each decade during the study period. My analysis generated three-time series trend lines. The “observed” precipitation trend line showed the average recorded for each decade
(Figure 7a). Next, the differential between seasonal averages and the observed precipitation generated the “trend” for each decade (Figure 7B). The last trend line was extrapolated from the aggregate seasonal average (“season”) from all data 1960 – 2018 (Figure 7C). The time series analysis reveals a delay in the highest precipitation peak from September to October during the rainy season and a slight reduction in May between the 1990s and 2018 (Figure 7A and 7B).
The timing of observed precipitation patterns first began to subtly diverge from the seasonal averages in the 1990s. First, there is a delay in the onset of the wet season and a shift in
45 peak wet season precipitation from September to October (Figure 7A). These shifts in both wet season initiation and observed peak rainfall have increased in frequency in the following two decades and represent a significant divergence from seasonal precipitation patterns for the region. Furthermore, the observed precipitation from 2010-2018 has lost intensity in May and
June and intensified in the latter months of the wet season, loading precipitation volume toward the latter half of the bimodal wet season.
The second indication of divergence from seasonal precipitation patterns is demonstrated by the “trend” line, which compares the average seasonal precipitation to observed data from
1990 - 2018 (Figure 7B). In the 1990s, the trend line began to show a negative relationship between observed rainfall and the seasonal averages in the latter half of the wet season. This trend continued into the 2000s, reporting a significant reduction in average rainfall for the entire season (Figure 7A-B).
Mantel tests
Mantel tests showed no correlation between the volume of the peak in precipitation during the wet season and the timing and precipitation at the start of the dry season between each season. There was a weak correlation between the timing of peak wet season precipitation with bee community structure (Mantel statistic r = 0.2520, p = 0.0374). Pollen availability of precipitation independent plants and precipitation-cued plants also showed no correlation with the twelve seasons of observed bee community structure (Table 3).
46 Plant-pollinator network analysis
In comparing the historical plant-pollinator network to what was observed in 2016-2018, the diversity of pollinating bees changed for two of the five focal plant species (Ipomea carnea,
Parkinsonia aculeata, Gliricidia sepium, Ceasalpinia eriostachys and Senna palida) (Figure 8).
Two SDTF tree species, G. sepium (referenced from Heithaus collection tags at the Brown
Family Education Center) and S. pallida (Wille 1963), lost several genera of visiting pollinators by 2016 and 2018. Historically, eleven taxa visited the flowers of G. sepium, but only four taxa visited this species in 2016-2018; moreover, A. mellifera is now the most frequent visitor.
Similar findings were found for S. pallida, that not only showed a reduction in the number of species visiting their flowers, but visitation is now dominated by Xylocopa spp. On the other hand, C. eriostachys, P. aculeata, (Jones and Buchmann 1974) and I. carnea (Keeler 1975) exhibited an increase in diversity of pollinators visiting their flowers in 2016 and 2018, relative to historical observations (Figure 8). Only four taxa were documented to visit flowers of I. carnea in the past; however, ten taxa currently visit these flowers. Likewise, P. aculeata and C. eriostachys currently exhibit higher diversity of visitors than in the past (2 vs. 9 taxa and 3 vs.
10 taxa, respectively). A significant portion of newly recorded taxa included eusocial species, such as the non-native Apis mellifera, and native stingless bees in the genera Trigona,
Cephalotrigona, Nannotrigona, and Plebia. Lastly, many solitary bee taxa historically recorded only on the precipitation-sensitive plant taxa switched to I. carnea and P. aculeata.
47 DISCUSSION
Shifts in seasonal cues that control ecological processes in the tropics are one of many potential effects of climate change (Chadwick et al. 2016, Stan et al. 2020, Janzen and Hallwachs
2021). The extent to which such shifts may impact plant-pollinator relationships is an imperative question on a global scale. This study documents the reduction in precipitation experienced in the last two decades in northwestern Costa Rica, the erosion of the historical norms in the bimodal wet season, delayed precipitation cues and decreased precipitation volume for SDTF flowering plants (Figure 7). While bee collections during the 2000s are unfortunately scarce, it is not unreasonable to associate the subsequent changes in pollinating bee community structure with the dramatic changes in environmental characteristics experienced during that decade. My results support that bee pollinator community structure in the SDTF of Costa Rica is affected by changes in precipitation patterns, flowering phenology of SDTF trees, and the subsequent shift in plant-pollinator networks.
The time-series analysis revealed critical shifts in the timing and total precipitation of the wet season, resulting in a delay in the initiation and shortening of the duration of the wet season
(Figure 7). Northwestern Costa Rica reported annual reductions of precipitation volume between
1960 – 1990 that are projected to continue into the coming decades (Vargas and Trejos 1994,
Mendez et al. 2020). Furthermore, year-to-year observations of precipitation patterns have become increasingly unpredictable (Aguilar et al. 2005), which weakens the strength of precipitation cues as a phenological signal (Singer and Parmesan 2010).
48 The relationship between the timing of peak precipitation during the wet season and the pursuant bee community structure explained 25% of the variation over twelve sampling seasons spanning four decades (Mantel statistic r = 0.2520, p = 0.0388). This finding provides additional context for the observations made during the 2016 – 2018 field seasons. The
Shannon’s diversity index for the 2016-2018 community is significantly less than that of the
1972 community observed by Ray Heithaus (Hutchenson’s t = 4.88, df = 2015, p <0.001) (see
Chapter 2). However, between 2016 and 2018, bee diversity and phenology changed relative to precipitation patterns, as the 2015-2016 dry season followed a severe El Niño drought event, and the 2017-2018 season was significantly wetter. As a result, while the 2018 community structure did not reflect the overall 1972 community structure, a few species associated with wetter years in the museum collections were present that year that were absent in 2016. This finding suggests that bees may experience range contraction and expansion in response to precipitation patterns.
This pattern of potential range contraction and expansion was observed both at the genus and species level during the two field seasons. For example, in 2016, I did not record bees in the genus Centris until the second blooming event of Tabebuia rosea in late April. The majority of bees captured were males and were active for the duration of the second T. rosea blooming event.
In 2018, one female Centris aethyctera was captured in January while visiting Caesalpinia eriostachys, and a few others while searching for nest sites in the forest floor. From February to
March, however, only males were captured, but only on Parkinsonia aculeata. The implications for the overall contribution of the remaining Centris species within the pollinator community are unknown, as the evidence suggests that Centris are not reproducing as readily as previously
49 recorded in PVNP. Male bees pursue floral resources on many of the same plant species as females, although most consider males to be less effective pollinators than females foraging for pollen to provision their nests (Michener, 2000). However, this may not always be the case, as another study found males to be effective pollinators in specialized relationships (Cane et al.,
2011).
I argue that change in the pollination services may have resulted from changes in flowering phenology and bee communities. A comparison of plant-pollinator networks interpreted from pollen collected from specimens of the historical collections, literature surveys, and my observations in 2016-2018 reveals a response in foraging patterns (Figure 8).
Comparing historical observations to recent observations taken at the same general locations and at the same time of season reveals a significant decline in pollinator diversity for two precipitation-sensitive plants, Gliricidia sepium and Senna pallida. Both of these species were previously visited by some genera that are now locally extinct. The inverse can be observed on
Ipomea carnea and Parkinsonia aculeata, non-precipitation sensitive plants, which now are visited by far more species than previously reported (Figure 8).
Furthermore, some previously dominant genera are still weakly present at PVNP, but do not appear to be nesting at volumes that would make them easily detectable (Wolanin, Pers.
Observations). For example, only three of nine species in Centris historically present in the park are currently present. However, observations of nesting females were limited to only one species in 2018 (Wolanin, Pers. Observations). The overwhelming majority of all Centris specimens
50 captured while visiting SDTF plants were male, suggesting that these populations are becoming endangered in this area.
Unlike G. sepium and S. pallida, the vine Ipomoea carnea colonizes disturbed areas along park access roads and is not dependent on wet season precipitation cues. Of the typical bee visiting genera recorded on I. carnea, two species are oligolectic. It would appear that this vine now supports a broader diversity of bees in the SDTF pollinator community (Figure 8).
This vine appears to remain a stable resource for its pollinators and may potentially function as an oasis in the absence of mistimed seasonal plants. An even better oasis candidate is the wetland riparian tree Parkinsonia aculeata, only visited by two genera in 1972. Although these observations were repeated for only one week for a short duration each morning, comparison of the same sample period taken in 2016-2018 revealed a much broader bee diversity. Parkinsonia aculeata trees were visited by genera missing from their typical host trees. As in other SDTF plants, a higher proportion of males were sampled on this species, suggesting that females were not replacing other nesting resources with Parkinsonia aculeata.
In the case of Caesalpinia eriostachys, a tree that flowers as a function of the last precipitation event of the rainy season, the change in the number of observed genera results from a higher diversity of stingless bees and the addition of Apis mellifera (Figure 8). In fact,
Africanized Apis mellifera hybrids were new observations for nearly all plants in 2016-2018, except for Senna pallida (Wille, 1963). According to Wille (1963), Apis mellifera “gleans” pollen released by large-bodied solitary bees and does not contact the reproductive parts of the
51 flower. This report suggests negative consequences for the efficacy of the remaining pollinator community, as generalists may not provide the same quality of pollen transfer with their visits.
While I could not directly link pollen availability to changes in bee community structure, it is evident SDTF plant-pollinator relationships have changed. There is some debate surrounding the phenological cues for SDTF anthesis, and Haselhorst et al. (2017) point to fluctuations in temperature as a likely alternative. However, precipitation shapes SDTF plant- pollinator relationships in other ways. SDTF trees produce pollen at a higher rate following wetter years (Haselhorst et al., 2017), and droughts like those associated with the 2015 El Niño increased SDTF tree mortality across all age classes (Powers et al., 2020).
Yet another explanation of the change in pollinator community dynamics could be linked to temporal climatological shifts that influence solitary bee diapause, voltinism, or inter-specific interactions (Forrest 2016). Although unexplored in Costa Rica SDTF, Denlinger (1986) suggested temporal changes in precipitation: temperature ratios could impact soil evapotranspiration rates, and therefore impact bee diapause. Other possible explanations include temporal shifts in thermal highs and lows associated with seasonal change, temperature spikes that result in insect fatality, and introduced chemicals and runoff associated with anthropogenic land-use (Boggs 2016) Because of the unique environmental conditions and strong seasonality of the tropics, many of the specialized species there are associated with more narrow thermal limits, and are therefore more sensitive to changes in climate (Antão et al. 2020).
52 It is important to note here that the trends drawn from this data are not conclusive as to the sole explanation for the changes in bee community structure in the SDTF of PVNP. The changes to the community may be responding to additional variables that changed in the same timeline as the onset of changes in precipitation patterns. Furthermore, I found only twelve years in common with adequate information across my weather, bee, and pollen datasets. With such a small sample size, it was not possible to characterize the precise nature of the interplay between the other measures of precipitation, pollen availability, and bee community structure. The traditional approach to tracking floral phenology requires consistent and attentive study of target species throughout the season, which is not captured in the snapshot provided by pollen grains on bee specimens. Previous applications of this methodology utilized larger, temporally continuous collections from temperate systems (Burkle et al. 2013, Scheper et al. 2014), which highlights the urgent under-representation of the tropics. While I believe the correlation between pollen presence and bee community structure is a critical factor in understanding the dynamics leading to the local extinction of pollinator genera, precise temporal interaction requires further research.
More direct studies are necessary to link solitary bees to resource limitation, specifically how it affects female body size and sex ratio within populations. While the resources of museum collections provided a limited sample size, it is a worthwhile and necessary avenue of research as
SDTF plant-pollinator relationships continue to endure the effects of climate change and anthropogenic disturbances.
53 Figure 7. Decomposed additive time series analysis of wet season precipitation patterns in regions of SDTF in Guanacaste, Costa Rica. Meterological data was collected from the US National Oceanic and Atmospheric Agency, the Instituto Metereológico Nacional de Costa Rica, and Palo Verde Reserva Biologia, courtesy of the Organization for Tropical Studies. For each decade from 1960 to 2018, this decomposition displays the average observed rainfall Jan – Dec (A), the trend of change in average precipitation patterns (B), and the seasonal pattern of precipitation from 1960 - 2018 (C). Shifts in the timing second peak in precipitation volume from September to November are indicated by the dotted lines.
54 Figure 8. A bimodal plant-pollinator network comparing the pollinator networks for five SDTF plants. The connector thickness indicates the significance of the relative contribution of the bee genus to pollinating the corresponding plant species. Plants with precipitation-triggered flowering events are colored red, and those less dependent on precipitation cues are colored blue. Pollinator networks were constructed from publications from 1961 – 1972 (A), and the observed pollinator activity in PVNP in 2016 and 2018 (B). The roles of eusocial (green) and solitary (yellow) bee genera, and the communities of visiting bee genera differ greatly from observations made prior to repeated years of ecological disturbance.
55 Table 3: Results from seven Mantel Peason’s product-moment correlation tests.
Mantel Test 0.00000 p Community ~ Environmental -0.03104 0.5323 Variables (PC1) Community ~ Photoperiod- -0.18410 0.8928 cued Plants (PC1) Community ~ Precipitation- 0.20010 0.1599 cued Plants (PC1) Community ~ Peak Wet -0.03038 0.5735 Season Precipitation Volume Community ~ Peak Wet 0.25200 0.0374 Season Precipitation Month Community ~ Dry Season 0.04837 0.3429 Start Precipitation Volume Community ~ Dry Season -0.02038 0.5380 Start Month
56 CHAPTER IV
CONCLUSION
Overall, this study found strong supporting evidence of bee population and diversity declines, and corroborated shifts in pollinator community structure within the SDTF of Costa
Rica (Frankie et al. 2009). These declines are not limited to just insect pollinators within this system (Janzen and Hallwachs 2021), and these findings form a trend consistent with global insect pollinator declines (Potts et al. 2010, Lebuhn et al. 2013, Dirzo et al. 2014, Goulson et al.
2015, Didham et al. 2020, Wagner et al. 2021).
My findings also indicate a change in the plant-pollinator relationships over the course of the last fifty years of study. I was not able to firmly link the exact causes of this shift, but additional research could yield more definitive answers.
Chapter 2 Conclusions
Solitary seasonal specialists in bee pollinator genera experienced shifts in dominance and a general reduction in the abundance and diversity. There was a significant decline in diversity at the genus level, and species level declines in select genera between 1971 and 2018. Some of these genera were previously dominant in the pollinator community, and certain species within
Centris and Xylocopa appear to have been extirpated or are currently at risk of extirpation within
57 PVNP. Overall, abundance of solitary bees was a mere fraction of what was described in sample protocols from other studies (Frankie et al. 1974, 1998, Heithaus 1979).
As solitary bees have declined, eusocial species have taken on a larger role within the pollinator community. However, the dynamics between dominant species within this functional group have also changed. The previously dominant species, Melipona beecheii, appears to have been extirpated. Along with the loss of this species, the overall diversity and abundance of native eusocial bee genera initially declined with the arrival of Africanized Apis mellifera.
However, it appears that certain genera have managed to coexist with the A. mellifera hybrids.
The loss of M. beecheii in tandem with the invasion of A. mellifera hybrids corroborates other studies in SDTF and other habitat within the neotropics (Cairns et al. 2005). In conjunction with other environmental stressors, non-native honeybees should be considered as another stressor for
SDTF pollinator species.
Chapter 3 Conclusions
To explain the loss of diversity in solitary bee species, I tested the relationship between changing precipitation patterns, pollen availability, and bee community structure by analyzing publish data, museum records, and collection efforts conducted from 2016-2018. In my timeseries analysis, I found a shift in the timing of precipitation patterns, which had a weak correlation with bee community structure. I found a dramatic shift in the bee community that structured the pollinator network. Many dominant specialized solitary genera diminished in
58 contribution, or dropped out of the network altogether. In their place, generalist solitary genera and eusocial genera of bees make up a larger proportion of observed pollinators.
I were unable to directly link pollen availability to changes in bee community structure, but this network analysis clearly indicates a shift in the relative value of floral resources provided by plants not cued by precipitation. Ipomoea carnea and Parkinsonia aculeata provide consistent resources for an extended period of time, providing an oasis for bees during years with mistimed or reduced flowering events. Because the 2016 sampling season followed a very strong El Nino event, these resources were the often the only reliable foraging patches for bees in the park long stretches of time. Even contrasted with increased flower density across all precipitiation-cued species in 2018, I. carnea and P. actuleata still attracted a variety of bees not observed in the 1970’s. Seeing that C. eriostachys, G. sepium, and S. pallida are associated with a less diverse network of pollinators highlights the losses described in Chapter 2, and portends a change in the ecosystem services being provided to these plants.
Significance
As a whole, tropical areas are horrendously under-represented or poorly identified in museum collections, and in published community surveys (Beck and Kitching 2007, Cayuela et al. 2009). This deficit makes population modeling and meta-analysis of these areas difficult, and it isn’t uncommon to read studies that aren’t able to include the tropics in their analyses (Blowes et al. 2019, Antão et al. 2020).
59 Since data is so scarce, the submission of my work carries an added significance. In this thesis, I consolidated records of the SDTF bee community from publications, disparate museum collections, and through my own community surveys. I carefully followed the sampling techniques of previous studies (Frankie et al. 1976), and strove to match or exceed their collection efforts to better capture what has happened to this community. The low abundances I recorded fall in line with bee population declines noted near PVNP since the early 1990’s
(Frankie et al. 1998, 2009). The sobering implication of this trend is that I are running out of time to collect and to learn why these populations are declining.
Limitations
Insufficient data in the meterological dataset and the under-representation of tropical systems in museum collections greatly reduced my statistical power in this project. While I had a strong baseline for analysis, I lacked representative samples of bee populations from the mid-
1990’s to the late 2010. However, with the right approach, it is possible to overcome this deficit
(Didham et al. 2020). It is for this reason that careful, continued attention must be directed at the plant-pollinator community in this system in order to better understand why it is breaking down.
Applications
Besides factors related to climate change, parasites, pathogens, agricultural pesticides, commercial herbicides, loss of floral resources, and habitat loss have been cited as causes for bee population decline (Biesmeijer et al. 2006, Potts et al. 2010, Lebuhn et al. 2013, Burkle et al.
2013, Scheper et al. 2014, Goulson et al. 2015, Xiao et al. 2016). While the factors related to
60 climate change require an advanced implementation of policies, one more feasible route to slowing bee decline is to limit the amount of habitat loss. It is key to maintain protected areas to preserve SDTF habitat and to teach the value of leaving behind native plant species in developed areas when possible. National parks like Santa Rosa, Guanacaste, Barro Honda, and Palo Verde provide sanctuary to these important habitats. However, equally important are ecological corridors provided by right-of-ways, public green space, and the property of nature-loving landowners. Yet another potential area to provide habitat is by promoting native vegetation amongst shade-grown crop species, or along edges or in unused area otherwise set aside for agricultural practices. Regardless of what conservation method is employed, the key to its success is for it to be run, designed, and implemented at the community level by local residents.
As the economic incentives provided by the Costa Rican government cease to become outweighed by the value of developing land (Calvo-Alvarado et al. 2009), a more grassroots movement may be required to help stave off further damage to rare habitat in sensitive areas.
Time is a limiting resource in conservation. Action needs to be taken to ensure that these protected areas are safely buffered and monitored in order to maintain ecosystem health. The risk of local extinction identified in this study must be taken seriously, and a wide-scale analysis of the ranges of these pollinator populations is the next necessary step in their conservation. As a species, I cannot be complacent in the current trajectory of how I are changing my environment.
In order to preserve the pollinator community, I must continue to study and protect my bees before their losses can no longer be recovered.
61 Climate change is disrupting plant-pollinator relationships on a global scale, the consequences of which are far-reaching and not yet fully realized (Bertin 2008, Piao et al. 2019).
The time and nature of response to changes to phenological cues vary by species in a community, leading to multi-dimensional changes in community dynamics (Ovaskainen et al. 2013). Shifts in phenological cues in plant-pollinator relationships can push threatened insect pollinators to extinction (Singer and Parmesan 2010).
The loss of insect pollinators cannot be mitigated. As 94% of all tropical species depend on animal pollinators for reproduction (Ollerton et al. 2011), their decline precedes total ecosystem failure. The conclusions of this study has weighed heavily on me as a scientist, and as a human on this planet. My hope is that we are not too late to reverse or mitigate these effects, and that timely attention and effort will be enough to rescue these systems from further damage.
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78 APPENDIX A. Rarefied observations of genera in each dry season collection
79 APPENDIX B. Wet season precipitation data compiled from IMN and PVNP meteorological
stations
80