Project Title

Congruence and within-season variation in floral visitation and pollen transport networks in Southern Appalachia plant-pollinator communities

Authors' Affiliations

Daniel A. Barker, Department of Biological Sciences, College of Arts & Sciences, East Tennessee State University, Johnson City, TN.

Location

RIPSHIN MTN. ROOM 130

Start Date

4-12-2019 1:40 PM

End Date

4-12-2019 1:55 PM

Faculty Sponsor’s Department

Biological Sciences

Name of Project's Faculty Sponsor

Dr. Gerardo Arceo-Gomez

Type

Oral Presentation

Classification of First Author

Graduate Student-Master’s

Project's Category

Biological Diversity, Conservation Biology, Ecology

Abstract Text

Previous studies of plant-pollinator interactions have relied on the use of floral visitation data. Although, this may be insufficient to fully characterize the diversity and strength of plant-pollinator interactions. By using pollen transport data (i.e. pollen on pollinators), new insights can be gained on the structure and function of plant-pollinator communities. Yet studies that characterize and compare pollen-transport with floral-visitation networks are scarce. Furthermore, the strength and frequency of plant-pollinator interactions can vary across temporal scales. Although, monthly and within-day variation in network structure has been little studied. By evaluating variation in network structure across these biologically relevant time scales we will gain a better understanding of the factors that shape plant-pollinator communities. Here, we build plant-pollinator interactions networks based on floral visitation and pollen transport data by observing, collecting and sampling pollen from floral visitors in a southern Appalachian floral community. We aim to 1) compare the congruence of plant-pollinator networks built on floral visitation and pollen transport data and 2) evaluate within season and within-day variation in plant-pollinator network structure. To assess floral visitation and to quantify pollen transport, four 1x40m transects were set up at the study site. Morning collections were conducted between 8:00 AM and 3:00 PM twice per week while afternoon collections took place once per week between 3:01 PM and 5:00 PM over 20 non-consecutive days. All flower visitors observed interacting with a flower’s reproductive structures (i.e. searching for pollen and nectar) were collected.All collected pollinators were processed for surface pollen loads by dabbing the body with a 3x3mm fuschin jelly cube. Each area of the body was dabbed three times to standardize sampling. Identification and quantification of pollen was done using a compound light microscope. Data was then analyzed with the “bipartite” package of R to create bipartite plant-pollinator networks. Procrustes analysis was used to identify differences in network structure. Preliminary results show that the structure of floral visitation and pollen transport networks are significantly different from each other (P <0.01). Pollen-transport network size is almost four times larger (496 links) compared to the floral-visitation network (109 links). Species in the pollen transport network tend to be more connected (connectance = 2.3) and have five times more links per species on average (5.22 links) than floral visitation networks (connectance = 1.1, links = 1.8). Within-season and within-day differences in network structure are currently being evaluated. Our results so far show that pollen transport networks at our study site captured 78% more unique interactions and, thus, provide more accurate network structure. Interpretation of pollen transfer versus floral visitation networks can have important implications for our understanding of community-level functions such as their resilience and stability.

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Apr 12th, 1:40 PM Apr 12th, 1:55 PM

Congruence and within-season variation in floral visitation and pollen transport networks in Southern Appalachia plant-pollinator communities

RIPSHIN MTN. ROOM 130

Previous studies of plant-pollinator interactions have relied on the use of floral visitation data. Although, this may be insufficient to fully characterize the diversity and strength of plant-pollinator interactions. By using pollen transport data (i.e. pollen on pollinators), new insights can be gained on the structure and function of plant-pollinator communities. Yet studies that characterize and compare pollen-transport with floral-visitation networks are scarce. Furthermore, the strength and frequency of plant-pollinator interactions can vary across temporal scales. Although, monthly and within-day variation in network structure has been little studied. By evaluating variation in network structure across these biologically relevant time scales we will gain a better understanding of the factors that shape plant-pollinator communities. Here, we build plant-pollinator interactions networks based on floral visitation and pollen transport data by observing, collecting and sampling pollen from floral visitors in a southern Appalachian floral community. We aim to 1) compare the congruence of plant-pollinator networks built on floral visitation and pollen transport data and 2) evaluate within season and within-day variation in plant-pollinator network structure. To assess floral visitation and to quantify pollen transport, four 1x40m transects were set up at the study site. Morning collections were conducted between 8:00 AM and 3:00 PM twice per week while afternoon collections took place once per week between 3:01 PM and 5:00 PM over 20 non-consecutive days. All flower visitors observed interacting with a flower’s reproductive structures (i.e. searching for pollen and nectar) were collected.All collected pollinators were processed for surface pollen loads by dabbing the body with a 3x3mm fuschin jelly cube. Each area of the body was dabbed three times to standardize sampling. Identification and quantification of pollen was done using a compound light microscope. Data was then analyzed with the “bipartite” package of R to create bipartite plant-pollinator networks. Procrustes analysis was used to identify differences in network structure. Preliminary results show that the structure of floral visitation and pollen transport networks are significantly different from each other (P <0.01). Pollen-transport network size is almost four times larger (496 links) compared to the floral-visitation network (109 links). Species in the pollen transport network tend to be more connected (connectance = 2.3) and have five times more links per species on average (5.22 links) than floral visitation networks (connectance = 1.1, links = 1.8). Within-season and within-day differences in network structure are currently being evaluated. Our results so far show that pollen transport networks at our study site captured 78% more unique interactions and, thus, provide more accurate network structure. Interpretation of pollen transfer versus floral visitation networks can have important implications for our understanding of community-level functions such as their resilience and stability.