Modeling the Spread and Geographic Distribution of Invasive Termites in Florida

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Material Information

Title:
Modeling the Spread and Geographic Distribution of Invasive Termites in Florida
Physical Description:
1 online resource (13 p.)
Language:
english
Creator:
Tonini, Francesco
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Forest Resources and Conservation
Committee Chair:
HOCHMAIR,HARTWIG H
Committee Co-Chair:
CROPPER,WENDELL P,JR
Committee Members:
SCHEFFRAHN,RUDOLF H
ABD-ELRAHMAN,AMR H
SOUTHWORTH,JANE

Subjects

Subjects / Keywords:
gis -- invasive -- modeling -- simulation -- spatiotemporal -- statistics -- stochastic -- termites
Forest Resources and Conservation -- Dissertations, Academic -- UF
Genre:
Forest Resources and Conservation thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
Invasive termites are destructive insect pests that cause billions of dollars in property damage every year. To be able to mitigate the damaging effects of termite infestation, this research investigates the spread and geographic distribution of invasive termites in Florida. In order to assess their spatiotemporal spread over a landscape, two spatially-explicit stochastic simulation models were developed: an individual-based model (IBM) and a cell-based model. The setting of a case-study of an invasive termite, Nasutitermes corniger (Motschulsky), was used to simulate the spread of the species in Dania Beach, FL. The Monte Carlo simulation technique was used in both models to assess outcome uncertainty. A sensitivity analysis was carried out for the IBM using a set of model realizations describing potential areas of infestation in order to assess the importance of each ecological parameter included in the model. Results showed that the areas with the highest predicted likelihood of infestation in both simulation models matched well the empirical locations discovered over the years within the chosen time window. Frequently, the only data available on a species is the location of its occurrence (presence-only data). In order to predict the potential habitat of invasive termite species under both current and future climate change scenarios, several statistical models were considered using two approaches for presence-only data: a recently developed Bayesian linear logistic regression approach adjusted for presence-only data and the widely used maximum entropy approach (Maxent). A case study of two destructive invasive termite species in Florida, Coptotermes gestroi (Wasmann) and Coptotermes formosanus Shiraki, is presented to predict their current and future biotic distributions by using their occurrence records. Results showed that the predicted distributions of both C. gestroi and C. formosanus are strongly linked to urban development and that future climate warming seems to affect their projected probability of presence to a lesser extent than population growth. All models presented in this study can help state and local regulatory agencies to understand the response of invasive termites to different environmental conditions and anticipate their spread by developing successful early detection, quarantine, or eradication plans based on the predicted areas of infestation.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Francesco Tonini.
Thesis:
Thesis (Ph.D.)--University of Florida, 2014.
Local:
Adviser: HOCHMAIR,HARTWIG H.
Local:
Co-adviser: CROPPER,WENDELL P,JR.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2015-05-31

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2014
System ID:
UFE0046461:00001