Combining High-performance Computing and Ecological Field Experiments to Understand Insect Outbreaks /

Saved in:
Bibliographic Details
Author / Creator:Gallagher, Molly E., author.
Imprint:2017.
Ann Arbor : ProQuest Dissertations & Theses, 2017
Description:1 electronic resource (77 pages)
Language:English
Format: E-Resource Dissertations
Local Note:School code: 0330
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11715069
Hidden Bibliographic Details
Other authors / contributors:University of Chicago. degree granting institution.
ISBN:9780355078107
Notes:Advisors: Greg Dwyer Committee members: Stefano Allesina; Sarah Cobey; Marcus Kronforst; J. Timothy Wootton.
Dissertation Abstracts International, Volume: 78-12(E), Section: B.
English
Summary:Effectively managing outbreaks of defoliating insects requires an understanding of the factors regulating outbreaks, which in turn requires mechanistic models. Classical models of insect defoliators include only density-dependent attacks by natural insect enemies, but variation in host plant quality can also strongly affect defoliator survival. I have combined model fitting with field experiments and observational data collection to identify the mechanisms driving the complex dynamics of the forest defoliator jack pine budworm (Choristoneura pinus). I collected data in outbreaking budworm populations from 2012-2015, recording budworm density, rates of parasitism, tree quality, and climate measurements, as well as conducting parasitoid exclusion experiments. I fit mechanistic models to my observational and experimental data on jack pine budworm outbreaks, using non-linear differential equations. The results show that drivers of budworm population dynamics include direct density-dependence, density-dependent parasitoid attacks, and the effects of plant quality. I then embedded my model of larval mortality into an annual model of insect population dynamics and their interactions with jack pine trees and forest fires. This model shows that the influence of plant quality directly affects the period of insect outbreaks, which in turn changes the interval between forest fire events. My results indicate that before we can make predictions about the effects of climate change on fire frequency and forest health, we must understand effects of defoliating insects.

MARC

LEADER 00000ntm a22000003i 4500
001 11715069
005 20170926110229.5
007 cr un|---|||||
008 170926s2017 miu|||||om |||||||eng d
003 ICU
020 |a 9780355078107 
035 |a (MiAaPQD)AAI10274000 
035 |a (OCoLC)1078446956 
040 |a MiAaPQD  |b eng  |c MiAaPQD  |e rda 
100 1 |a Gallagher, Molly E.,  |e author.  |0 (orcid)0000-0001-5285-5930 
245 1 0 |a Combining High-performance Computing and Ecological Field Experiments to Understand Insect Outbreaks /  |c Molly E Gallagher. 
260 |c 2017. 
264 1 |a Ann Arbor :   |b ProQuest Dissertations & Theses,   |c 2017 
300 |a 1 electronic resource (77 pages) 
336 |a text  |b txt  |2 rdacontent  |0 http://id.loc.gov/vocabulary/contentTypes/txt 
337 |a computer  |b c  |2 rdamedia  |0 http://id.loc.gov/vocabulary/mediaTypes/c 
338 |a online resource  |b cr  |2 rdacarrier  |0 http://id.loc.gov/vocabulary/carriers/cr 
500 |a Advisors: Greg Dwyer Committee members: Stefano Allesina; Sarah Cobey; Marcus Kronforst; J. Timothy Wootton. 
502 |b Ph.D.  |c University of Chicago, Division of the Biological Sciences, Department of Ecology and Evolution  |d 2017. 
510 4 |a Dissertation Abstracts International,   |c Volume: 78-12(E), Section: B. 
520 |a Effectively managing outbreaks of defoliating insects requires an understanding of the factors regulating outbreaks, which in turn requires mechanistic models. Classical models of insect defoliators include only density-dependent attacks by natural insect enemies, but variation in host plant quality can also strongly affect defoliator survival. I have combined model fitting with field experiments and observational data collection to identify the mechanisms driving the complex dynamics of the forest defoliator jack pine budworm (Choristoneura pinus). I collected data in outbreaking budworm populations from 2012-2015, recording budworm density, rates of parasitism, tree quality, and climate measurements, as well as conducting parasitoid exclusion experiments. I fit mechanistic models to my observational and experimental data on jack pine budworm outbreaks, using non-linear differential equations. The results show that drivers of budworm population dynamics include direct density-dependence, density-dependent parasitoid attacks, and the effects of plant quality. I then embedded my model of larval mortality into an annual model of insect population dynamics and their interactions with jack pine trees and forest fires. This model shows that the influence of plant quality directly affects the period of insect outbreaks, which in turn changes the interval between forest fire events. My results indicate that before we can make predictions about the effects of climate change on fire frequency and forest health, we must understand effects of defoliating insects. 
546 |a English 
590 |a School code: 0330 
690 |a Ecology. 
690 |a Biostatistics. 
690 |a Biology. 
710 2 |a University of Chicago.  |e degree granting institution.  |0 http://id.loc.gov/authorities/names/n79058404  |1 http://viaf.org/viaf/143657677 
720 1 |a Greg Dwyer  |e degree supervisor. 
856 4 0 |u http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10274000  |y ProQuest 
856 4 0 |u https://dx.doi.org10.6082/M14M92N1  |y Knowledge@UChicago 
035 |a AAI10274000 
903 |a HeVa 
929 |a eresource 
999 f f |i 4666b05b-84ea-53bf-8285-6690409f1311  |s 9b97d40e-ec9e-52db-ba50-ca43e3cbabdd 
928 |t Library of Congress classification  |l Online  |c UC-FullText  |u http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10274000  |z ProQuest  |g ebooks  |i 11159192 
928 |t Library of Congress classification  |l Online  |c UC-FullText  |u https://dx.doi.org10.6082/M14M92N1  |z Knowledge@UChicago  |g ebooks  |i 11159193