Estimation and Analysis of Insect Populations: Proceedings of a Conference held in Laramie, Wyoming, January 25–29, 1988

499 Pages·1989·11.671 MB·English

by  Bryan F. J. Manly (auth.), Lyman L. McDonald, Bryan F. J. Manly, Jeffrey A. Lockwood, Jesse A. Logan (eds.)

Lecture Notes in
Statistics
Edited by J. Berger, S. Fienberg, J. Gani,
K. Krickeberg, and B. Singer
55
L. McDonald B. Manly
J. Lockwood J. Logan (Eds.)
Estimation and Analysis
of Insect Populations
Proceedings of a Conference held in Laramie,
Wyoming, January 25-29, 1988
Spri nger-Verlag
Berlin Heidelberg New York London Paris Tokyo Honq Konq
Editors
Lyman L. McDonald
Departments of Statistics and Zoology
University of Wyoming
Laramie, WY 82071, USA
Bryan F. J. Manly
Department of Mathematics and Statistics
University of Otago
Dunedin, New Zealand
Jeffrey A. Lockwood
Department of Plant, Soil and Insect Sciences
University of Wyoming
Laramie, WY 82071, USA
Jesse A. Logan
Departments of Entomology and Forestry
Virginia Polytechnic Institute
Blacksburg, VA 24061, USA
Mathematical Subject Classification Codes: 62P 10
ISBN-13: 978-0-387-96998-5 e-ISBN-13: 978-1-4612-3664-1
001: 10.1007/978-1-4612-3664-1
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© Springer-Verlag Berlin Heidelberg 1989
2847/3140-543210
Preface
The papers in this volume were presented at a symposium/workshop on "The
Estimation and Analysis of Insect Populations" that was held at the University of
Wyoming, Laramie, in January, 1988. The meeting was organized with financial support
from the United States - New Zealand Cooperative Science Program and the University of
Wyoming. The purpose was to bring together approximately equal numbers of
quantitative biologists and biometricians in order to (1) provide a synthesis and evaluation
of currently available methods for modeling and estimating parameters of insect
population, and to (2) stimulate research into new methods where this is appropriate.
The symposium/workshop attracted 46 participants. There were 35 papers presented
in four subject areas: analysis of stage-frequency data, modeling of population dynamiCS,
analysis of spatial data, and general sampling and estimation methods. New results were
presented in all these areas. All except one of the papers is included in the present volume.
There were ten papers concerned with the analysis of stage-frequency data. Manly
began the workshop with his review of past work in this area. His paper also discusses a
new model for the estimation of the parameters of a single generation of a population based
on the concept of a development variable. New single generation models were also
described by Braner and Hairston, Faddy, Kemp et al., Munholland et al., and Pontius et
al. Bellows et al. address the difficult problem of estimating losses from parasitism using
stage-frequency and other data in a host-parasite system. Caswell and Twombly consider
the estimation of stage transition matrices for cases where generations cannot be separated.
Here estimates are naturally ill-eonditioned and there is interest in techniques such as
ridge regression as possible ways to improve their properties. Morton and Vogt consider
the problem of estimating relative recapture rates for blowflies of different ages and
development stages. Again ill-conditioning problems are apparent. Schneider proposes a
computer-intensive approach for estimating parameters for a nematode population.
There were 12 papers on various aspects of modeling of population dynamics. Manly
reviews development in key factor analysis and proposed a test for delayed
density-dependent mortality with data consisting of stage-based life tables from a series of
successive generations. Allen shows that natural enemy populations can easily display
chaotic behavior. Carey presents a demographic framework for the analysis of cohort life
IV
histories, and discusses the modeling of harvesting and two sexes. Dennis reviews the use
of stochastic differential equations for population modeling. Dianmo and Chang review a
number of approaches for modeling single species populations. Fargo and Woodson note
the potential use of the computer language SLAM for simulating insect populations. Lih
and Stephen describe SPBMODEL, a computer simulation model that predicts infestation
rates of the southern pine beetle. Lockwood and Lockwood show that some aspects of
grasshopper population dynamics can be described by a cusp catastrophe. Logan discusses
the composite modeling approach to population analysis which involves first developing a
complex realistic model which is then simplified until it is amenable to a mathematical
analysis. Nordheim et al., consider stochastic Leslie matrix models for population
development, noting that their behavior may be somewhat different from that of the
equivalent deterministic models. Schaalje and van der Vaart, and Smerage address the
relationship between alternative models for the development of populations with a stage
structure.
There were five papers concerned with various aspects of the analysis of spatial data.
Hutcheson and Lyons discuss the analysis of quadrat counts in two papers. Johnson
describes two modeling methods for testing hypotheses concerning the relationship between
grasshopper densities and soil type in southern Alberta. Liebhold and Elkinton show how
classical key factor analysis can be extended for studying life tables determined for different
locations in space as well as different generations. Willson and Young present a model for
arthropod movement that accounts for the negative binomial distributions often observed
for counts.
The final section consists of eight papers on various types of statistical analysis and
sampling problems. Blough discusses the analysis of the time series of trapping records of
the pink bollworm moth from a cotton field in southern Arizona, in terms of the
relationship of this series with amounts of irrigation water and the times when insecticide
was applied. Buonaccorsi and Liebhold review statistical methodologies appropriate for
estimating gypsy moth numbers from the ratio of mean frass drop from a forest canopy to
the mean frass production from caged larvae. Burnham reviews recent developments in the
analysis of population parameters from capture-recapture data. Cooper, Ellington et al.,
and Morrison et al., address various aspects of sampling designs. Gates describes a
computer program DISCRETE that can be used to fit a variety of discrete distributions to
v
data. McDonald and Manly discuss ways in which biased sampling procedures can be
calibrated, as in cases where the sampling fraction differs for the various development
stages in a population.
Lyman L. McDonald
Bryan F. J. Manly
Jeffrey A. Lockwood
Jesse A. Logan
ACKNOWLEDGEMENTS
In addition to the authors of the papers in this volume, a number of other people
have made valuable contributions, and we would like to express our gratitude for their
assistance. Our thanks are due to referees, to the Department of Statistics, University of
Wyoming for both financial and moral support, to Charles Cooper and Ester Fouts,
Conferences and Institutes, University of Wyoming, for hosting the conference, to Brenda
Shriner and Julie Williams for clerical assistance, and especially to Lisa Eckles, Secretary
for the symposium and publication of the proceedings.
CONTENTS
Preface ..... iii
Acknowledgements . vii
Contents ..... ix
SECTION I
ANALYSIS OF STAGE-FREQUENCY DATA. 1
A Review of Methods for the Analysis of Stage-frequency Data 3
Bryan F. J. Manly
Life Tables and Parasitism: Estimating Parameters in Joint
Host-Parasitoid Systems ............. . 70
T. S. Bellows, Jr., R. G. Van Driesche and J. Elkinton
From Cohort Data to Life Table Parameters via Stochastic Modeling 81
Moshe Braner and Nelson G. Hairston, Jr.
Estimation of Stage-Specific Demographic Parameters for Zooplankton
Populations: Methods Based on Stage-Classified Matrix Projection
Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Hal Caswell and Saran Twombly
Compartmental Models in the Analysis of Populations ......... 108
Malcolm J. Faddy
x
Modeling Grasshopper Phenology with Diffusion Processes ....... 118
William P. Kemp, Brian Dennis, Patricia L. Munholland
Estimation of Relative Trappabilities by Age and Development
Delays of Released Blowflies .................... 128
Richard Morton and W. G. Vogt
A Stochastic Model for Insect Life History Data ........... 136
P. L. Munholland, J. D. Kalbfleisch and B. Dennis
Nonparametric Estimation of Insect Stage Transition Times ...... 145
Jeffrey S. Pontius, John E. Boyer, Jr., and Michael L. Deaton
Problems Associated with Life Cycle Studies of a Soil-Inhabiting
Organism. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
S. M. Schneider
SECTION II
MODELING OF POPULATION DYNAMICS ...... 167
A Review of Methods for Key Factor AnalY3is ............. 169
Bryan F. J. Manly
Are Natural Enemy Populations Chaotic? . . . . . . . . . . . . . . . . 190
J. C. Allen
XI
Demographic Framework for Analysis of Insect Life Histories ..... 206
James R. Carey
Stochastic Differential Equations as Insect Population
Models ................................ 219
Brian Dennis
Intensive Study and Comparison of Single Species Population
Simulation Models . . . . . . . . . . . . . . . . . . . . . . . 239
Li Dianmo and Liu Chang
Potential Use of an Engineering-Based Computer Simulation
Language (SLAM) for Modeling Insect Systems ..... ....... 247
W. Scott Fargo and W. David Woodson
Modeling Southern Pine Beetle (Coleoptera: Scolytidae) Population
Dynamics: Methods, Results and Impending Challenges ......... 256
M. P. Lih and F. M. Stephen
Application of Catastrophe Theory to Population Dynamics
of Rangeland Grasshoppers ...................... 268
Dale R. Lockwood and Jeffrey A. Lockwood
Derivation and Analysis of Composite Models for Insect
Populations ............................ 278
Jesse A. Logan
XII
Leslie Matrix Models for Insect Populations with Overlapping
Generations ................... . . . . . . . 289
Erik V. Nordheim, David B. Hogg, and Shun-Yi Chen
Relationships Among Recent Models for Insect Population
Dynamics with Variable Rates of Development ............. 299
G. Bruce Schaalje and H. R. van der Vaart
Models of Development in Insect Populations ............. 313
Glen H. Smerage
SECTION III
ANALYSIS OF SPATIAL DATA ......... 333
A Significance Test for Morisita's Index of Dispersion and the
Moments when the Population is Negative Binomial and Poisson ..... 335
K. Hutcheson and N. 1. Lyons
Spatial Analysis of the Relationship of Grasshopper Outbreaks to
Soil Classification ......................... 347
Daniel L. Johnson
Use of Multi-Dimensional Life Tables for Studying Insect
Population Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . 360
Andrew M. Liebhold and Joseph S. Elkinton