Determining factors that reflect aphid presence eco informatics summer institute 2007
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Determining Factors that Reflect Aphid Presence Eco-Informatics Summer Institute 2007. Genevieve Layman Sean Moore Elizabeth Borer. Barley Yellow Dwarf Virus (BYDV) is extensive and economically important Includes Virus, vector, and host

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Determining Factors that Reflect Aphid Presence Eco-Informatics Summer Institute 2007

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Determining factors that reflect aphid presence eco informatics summer institute 2007

DeterminingFactors that Reflect Aphid PresenceEco-Informatics Summer Institute 2007

Genevieve Layman

Sean Moore

Elizabeth Borer


Background

Barley Yellow Dwarf Virus (BYDV) is extensive and economically important

Includes Virus, vector, and host

Disease epidemics affect ecosystems and biodiversity

California’s perennial

grasslands serves as

an example

Background


Introduction

This project focuses on vector behavior as indication of disease movement and structure

BYDV cannot be transmitted directly

or intergenerationally

Determined largely by aphids!

Objective: To study characteristic factors that

reflect aphid presence to

gain a better idea of BYDV’s

spatial epidemiology in the

HJ Andrews Experimental

Forest

Introduction

www.ipm.ucdavis.edu/.../englishgrainaphid.html

www.dewarcropprotection.co.uk/images/sitobion...


Methods

Methods

  • Study design created by Sean Moore

  • 15 study sites

    • 5 Meadow, 5 Forest, and 5 Road Habitat Sites

      Selection Requirements

      -20 Elymus Glaucus

      -20 Bromus of Carinatus or

      Vulgaris species

      Meadow and Forest from Carpenter Mtn.

      Road from Lookout Mtn.


Methods continued

Methods Continued

  • 6 Vegetation Quadrats per Site

  • 1 Pan trap per Site

  • Area sq meters

  • Elevation by GPS

  • Soil Samples, % canopy cover, and biomass samples taken as well although not used in analysis


Statistical analysis

Statistical Analysis

  • Log-linear Poisson regression

  • Appropriate for this model because of the distinct dependent variable being count based and non-continuous

  • Tests for significance

  • Aphid Count = %BV + %BC + %EG + %Total Grasses + Site Area + FMR + Elevation

  • Aphid Count = %BC + FMR + Elevation


Results

Results

  • 4 explanitory variables were found to be significant- Road, Meadow, Elevation, and Bromus carinatus


Results for elevation

Overall slight downward trend in Elevation for Aphid Count

Increase in elevation with road habitat has a distinct correlation with the increase in aphid count

Results for Elevation


Results for bromus vulgaris

Results for Bromus vulgaris

  • Bromus vulgaris significant with outlier

  • When the outlier is removed, P-Value drops and becomes no longer significant

  • This gives more weight to %Total Grasses and it then becomes

    significance


Discussion

Discussion

  • Roadsite habitat variable confounded

  • Mean number of aphids found in the Meadows was 3.8 compared to the 1.4 mean of aphids in the forested sites

  • Site size had no correlation

  • Elevation results may be influenced by temperature

  • Outputs suggest more local interactions

    are influencing aphid feeding preference

  • The presence of Bromus vulgaris

    does not necessarily reflect aphid

    presence


Assumptions and limitations

Assumptions and Limitations

  • Small sample size

  • Subjectivity in defining Site area

  • Seasonality of aphids and grasses

  • All aphids grass feeders

  • Site selection requirements hard to find


Conclusions

Conclusions

  • Road and meadow habitat as well as grass populace all are good indication of aphid presence

  • Elevation is indirectly reflective of aphid population

  • Broad, large-scale factors that provide insight for general trends in aphid populations

  • This research will be used in Sean Moore’s dissertation testing the role of local community interactions and the effects of landscape structure and regional processes on the dynamics of plant pathogens

  • Can also be used in consideration with the effects of land management


Future studies

Future Studies

  • Lab analysis

  • Aphid collection

  • Multiple Mountain

    Comparison

  • Road habitat and

    exotic species

  • Temperature

  • Aspect

  • Explanatory variable

    interactions


Acknowledgments

Acknowledgments

  • A big thank you to Desiree Tullos who created the Eco-Informatic Summer Institute program and made this research possible. Thank you to Sean Moore for mentoring this project, helping with field data collection, and for aiding with brainstorm ideas for statistical analysis. Also a great thanks to Elizabeth Borer and Eric Seabloom who suggested the topic of review and aided in the statistical analysis process.


Eco informatics

Eco-Informatics

  • Eco-Informatics is combining ecology and mathematical interpretation of research based problems to provide a more holistic view of an environmental system.

  • It is also a technique to visualize some of these problems and communicate them in a clear manner

  • I approached this research from a largely ecological angle but used the data I collected in statistical analysis to view it from a different perspective

  • I would not have been able to recognize these findings from exclusively observational field work.


The end

The End


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