GEORISK AND CLIMATE CHANGE
A proposal to establish a Collaborative Research Group and a
permanent distributed educational and research center on
environmetrics.
Sep 25, 2006
Submitted to the Pacific Institute for the Mathematical Sciences by
Charmaine Dean
Sylvia Esterby
Peter Guttorp
Jim Zidek
Simon Fraser University
University of British Columbia, Okanagan
University of Washington
University of British Columbia, Vancouver
PIMS Environmetrics CRG
The eventual goal of this project, whose specific theme is georisk and climate change, is
to develop a multi-site, distributed environmetrics research center. Activities of such a
center would include conferences, workshops, summer schools, joint courses, a
diploma/certificate program, and collaborative research. In order to develop this idea, we
propose to hold an initial meeting in January of 2007 with participants from a number of
institutions, principally Simon Fraser University (SFU), University of British Columbia
at Okanagan (UBC-O) and Vancouver (UBC-V), University of Victoria (UV) and
University of Washington (UW).
In addition to the Center’s Pacific Northwest aspect, we are working on extending links
with international collaborators.
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We will be taking advantage of collaboration between the Universities of Lund
and Washington, partly funded by a Swedish STINT grant (see the workshop on
trends in extreme climate events below).
In addition, the Principal Investigators (PIs) are building contacts with Pacific
Rim universities, in particular the Institute of Mathematical Sciences (IMS) and
the Tropical Marine Science Institute at the National University of Singapore.
Meetings in June 2006 with the Director of the IMS, Louis Chen, have led to an
agreement in principle to explore joint ventures, funded in part by a newly
announced Singaporean research grants program on environment and water
resources. Specifically Louis proposes that mathematicians and statisticians with
the relevant expertise meet with engineers to identify common areas of interest for
joint research at a workshop described below.
During meetings at the University of Sheffield in July, Jim Zidek and Tony
O’Hagan explored possible links between O’Hagan’s newly established research
program, about “managing uncertainty in complex models (MUCM)” and the
distributed center to be established with the requested PIMS support. Over the
next 4 years, the MUCM project is to establish a technology for quantifying and
reducing uncertainty in the predictions of complex models across a wide range of
application areas, including basic science, environmental science, engineering,
technology, biosciences, and economics. The PIMS project would test and
thereby possibly assist in the development of the new technology. As well, there
might well be opportunities to exchange personnel, information and ideas.
Moreover, some of the MUCM group might well benefit from or even make
contributions to the courses, workshops and conferences being organized as part
of the PIMS project.
Additional linkages will also be explored between this group and a German
research group with a focus on sustainable forest management
(http://www.sustman.de/seite1_e.htm). With partners at the University of Ulm,
Volker Schmidt and Marian Kazda, a workshop will be held at Reisensburg
Castle, a facility of the University of Ulm, for the week April 21-25, 2008. The
research topics will lie at the interface of mathematics, statistics and forest
ecology. Other international linkages with a focus on forestry are expected with
the project leader, Paulo Justiniano Ribeiro Jr, and his team at the Laboratório de
Estatística e Geoinformação at the Universidade Federal do Paraná in Brazil
where geostatistical methods are developed for mapping and studying ecological
aspects of forest and agricultural regions in Brazil.
We are collaborating with two main US institutes:
• the Institute for Mathematics Applied to Geophysics (IMAGe) at the National
Center for Atmospheric Research (NCAR) in Boulder, Colorado (where we have
plans for a summer school in 2008).
• the Statistical and Applied Mathematical Sciences Institute (SAMSI) at Research
Triangle Park, North Carolina. Derek Bingham (SFU) will be participating in this
year’s program on “Program on Development, Assessment and Utilization of
Complex Computer Models” and related workshops at NCAR beginning with the
organizational meeting in Sep 2006. Jim Zidek (UBC) has also been invited to
participate in that program as well as one on random matrices . The former is
closer to the research in this proposal and that invitation has provisionally been
accepted. The proposal budget includes funds for a visit to the Research Triangle
Park in North Carolina early in 2007.
2. Opening meeting:
Organizers: Peter Guttorp, U Washington, Jim Zidek, U British Columbia
Location: Semiahmoo conference center, Blaine, January 23-24, 2007.
The introductory meeting will open with a presentation of the old NRCSE (by Guttorp)_
and a presentation of the current PIMS plan (by Zidek). The remainder of the afternoon
will be spent with presentations of a variety of current projects (individuals currently
involved are mentioned below).
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Policy and decisions regarding climate change (Alison Cullen, Martina Morris,
Mark Handcock, Peter Guttorp)
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Agroclimate risk management (Jim Ramsey, Sam Shen, Jim Zidek)
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Impacts of climate change: moth prevalence (with impact on the BC apple
industry); fisheries (especially salmon production); animal populations; forest
fires, fire regimes and fire management; forest ecology; human health.
(Charmaine Dean, Sylvia Esterby, Rick Routledge, Carl Schwarz, Mike Brauer,
John Petkau, Sverre Vedal, Thomas Lumley, Lianne Shepard, Tim Larsen)
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Numerical vs. statistical modeling methods: quantifying uncertainty; combining;
multi-resolution issues (William Hseih, Peter Guttorp, Paul Sampson, Tillman
Gneiting, Nhu Le, Zhong, Adrian Raftery, Douw Steyn, Jim Zidek, Francis
Zwiers)
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Design (Will Welch, Steve Thompson, Derek Bingham, Jason Leoppky, Nhu Le,
Paul Sampson, Jim Zidek)
During dinner we may discuss a statistical report card for the International Panel for
Climate Change. The second day will be spent discussing individual activities in small
groups, followed by a summary meeting and overall discussion of the plans for the CRG.
2. Summer Schools:
2007: Summer school: Space-time modeling of environmental processes
Location: University of Washington
Target audience: Senior graduate students and young researchers
Instructors: Peter Guttorp and Paul Sampson (University of Washington),
Jim Zidek and Nhu Le (University of British Columbia Vancouver)
Dates: TBA.
Content: Transform tools, such as power spectra, wavelets, and empirical orthogonal
functions, are useful tools for analyzing temporal, spatial and space-time processes. We
will develop some theory and illustrate its use in a variety of applications in ecology and
air quality.
Harmonic (or frequency) analysis has long been the one of the main tools in time series
analysis. Application of Fourier techniques work best when the underlying process is
stationary, and we develop and illustrate it here for stationary spatial and space-time
processes. However, spatial stationarity is rather a severe assumption for environmental
models, and we show how the theory can be generalized beyond that assumption. In some
circumstances, we can develop formal tests for stationarity.
In geophysics and meteorology, variants of principal components called empirical
orthogonal functions (EOFs) are used to describe leading modes of variability in spacetime processes. Smoothed EOFs can be used to model the spatio-temporal mean field of a
random field, while another type of spatially nonstationary model will be introduced to
describe the random part of the field.
Finally, we describe an approach to a fully Bayesian modeling of space-time processes,
using several of the tools discussed earlier in the course. This will enable analysis of
space-time processes for which the covariance structure is non-separable, an assumption,
which has frequently (but incorrectly) been made in the literature.
Funding synergies: Some funding for this summer school will come from a UW VIGRE
NSF grant.
2008: Summer school: Computation in environmental statistics.
Location: The National Center for Atmospheric Research, Bolder, Colorado
Target audience: Senior graduate students and young researchers in atmospheric and
statistical science.
Instructors: TBA
Dates: TBA.
Content: This course is given as a “field trip” to the National Center for Atmospheric
Research. The course will cover topics for which NCAR is uniquely equipped: managing
and handling large datasets; fast computing algorithms such as the ensemble Kalman
filter; current research topics; distributed computing.
3. Workshops:
2007: Maintaining and assessing water quality
Organizer: TBA (joint with National University of Singapore)
Dates: Possibly late in 2007.
Content: Mathematicians and statisticians with the relevant expertise will meet with
engineers to identify common areas of interest for joint research to enable interaction
and exchange ideas on environmental research. That workshop would involve PIMS
and CRG participants. Topics would include climatic changes, air pollution and water
resources, with the aim of encouraging research collaboration.
Funding: The
IMS would fund the program/workshop up to S$75,000 (= US$46,000) for
the expenses [accommodation, per diem for all and airfare (with cap) for some] of the
invited speakers.
Possible participants: Abdel El-Shaarawi, Sylvia Esterby, Hans Künsch, Noel Cressie,
Mark Kaiser, Yingcun Xia.
2008: Extreme climate event
Organizers: Peter Guttorp (Statistics), University of Washington, Gabi Hegerl (Earth
and Ocean Sciences), Duke University, Georg Lindgren (Mathematical Statistics), Lund
University
Location: Lund, Sweden
Dates: Winter 2008
Content: There is a lot of current interest in judging whether we are observing changes
in the Earth’s climate due to global warming. A special issue of the Bulletin of the
American Meteorological Society (no. 3, 2000) contains five articles about trends in
extreme weather and climate events, covering observations (Easterling et al., 2000),
socioeconomic impacts, terrestrial ecological impacts, and model predictions (Meehl et
al., 2000). The tools used in these articles are those developed for single variable
extremes in independent and identically distributed data, and lack firm estimates of
variability. There is a rapidly growing amount of data on extremes, both from
observations and particularly from climate models that are now being used in ensemble
predictions of future climate (e.g. Stainforth et al. 2005). However, the statistical methods
used to interpret this information, especially the assessment of trends in extreme events,
requires some attention. Several gaps in the knowledge were identified and future
research needs pointed to in IPCC (2002). The use of spatial data can help to improve
estimation of extreme value models that are regionally similar (Casson and Coles, 1999).
In this workshop we will be discussing tools for the identification of significant
parametric and nonparametric trends in spatiotemporal extremes.
Preliminary list of speakers: Georg Lindgren (U of Lund, Sweden), Francis Zwiers
(Canadian Climate Centre and U of Victoria), Gabi Hegerl (Earth and Ocean Sciences),
Duke University, Rick Katz (NCAR), Jan Heffernan (Lancaster U), Richard Smith (U of
NC).
Funding synergies: Some funding for this workshop will come from a Swedish STINT
grant, and from an EU project called SEAMOCS.
4. Conferences
2007: TIES North American Regional Meeting 2007
Organizer: Peter Guttorp (U of Washington)
Location: Seattle
Dates: June 19–21, 2007
Content: This meeting, the first of its kind in North America, has as its theme “Climate
change and its environmental effects: monitoring, measuring, and predicting”. Keynote
speakers include David Brillinger, UC Berkeley, and Paul Switzer, Stanford University.
There will be invited sessions on
• Agroclimate risk assessment
• Forests, fires and stochastic modelling
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The role of statistics in environmental policy
Using large spatial datasets in ecology
The hockey stick controversy
Monitoring the environment and biota on landscape to continental scales
Assessing trends in extreme climate events
Inference for mechanistic model
2008: Environmetrics CRG: Satellite Meeting to TIES 2008
Organizer: Charmaine Dean, Simon Fraser University
Location: BIRS
Dates: June 2008
Content: A proposal for hosting a workshop on "Climate Change Impacts on Ecology
and the Environment" at the Banff International Research Station, June 2 - 6, 2008 will
be submitted jointly with this application. This meeting will consider agroclimate risk
management; impacts on the structure and biodiversity of forests including those
resulting from the greater frequency, severity and scope of fire events in combination
with landscape change; the implications of emissions for global and regional climate
change; and space-time modeling of environmental processes. The primary aim of the
workshop will be to compile and assess models and methods for modeling climate events
and assessing sensitivity of environmental outcomes to changes, and to assess the
evidence for existing impacts. Gaps in methodological developments will be identified,
for example, methods for isolating the species and ecosystems most vulnerable to climate
change, and detection of changes when observations are available at several spatial and
temporal scales. This workshop will also play the important role of providing
opportunity for discussion of timelines and progress toward the goals identified in the
collaborative research group application and interim reporting on research objectives.
2008: TIES 2008: Quantitative Methods for Environmental Sustainability
Organizers: Sylvia Esterby, UBC-Okanagan and David Brillinger, UC Berkeley
Location: Kelowna. BC
Dates: June 8–13, 2008
Content: TIES 2008, the 19th annual conference of The International Environmetrics
Society (TIES) will be held at The University of British Columbia Okanagan. Conference
technical topics are expected to include: monitoring, modeling and managing
environmental systems, network design and efficient data collection, design and analysis
of computer experiments, analysis of extremes, space-time modeling, environmental risk
assessment, assessing status and trends, environmental reporting and indicators, and
environmental standards. Areas of application will be biodiversity, climate change,
sustainable agriculture, air quality, water quality, soil contamination, energy,
environmental economics, ecosystem and human health. TIES conferences draw an
international and interdisciplinary group of participants, feature special lectures relevant
to the theme and are organized to provide ample opportunity for informal discussions and
the facilitation of collaborations. As such, linking the conference with the BIRS
workshop and the CRG should further facilitate the promotion of Environmetrics in the
region and beyond.
2008: Pacific Northwest Environmetrics Meeting
Location: TBA
Dates: Autumn 2008
Content: This will be the closing session for the CRG, aimed at making permanent the
multi-site environmetric research center.
5. Certificate/diploma program
We will develop a joint program wherein graduate students at any of the participating
universities may get a certificate or diploma, signifying that, in addition to their graduate
degree, they have successfully completed an approved program in the quantitative
analysis of environmental problems. While the details of this program remain to be
worked out, we anticipate that students will be able to take courses that count towards
this program at any of the campuses. We also hope that we will be able to offer some of
these courses over the web or using other remote technologies. The development of these
courses will enhance the quality of the graduate education at all the campuses. In order to
work out the details of these courses we will have interested faculty from all the sites
meet during two half-day meetings, one each year.
6. Research narratives:
Statistical & deterministic models in georisk analysis
(UBC-V: Phil Austin, Nancy Heckman, Nhu Le, Douw Steyn, Will Welch, Jim Zidek;
UBC-O: Jason Loeppky; SFU; Derek Bingham; San Diego: Sam Shen; McGill: Jim
Ramsey)
Neither statistical nor physical models like those in climate modeling suffice for
modeling large-scale processes like those involved in climate change. That is spawning a
new modeling paradigm that seeks to combine the best elements of both. One promising
approach due to Adrian Raftery and his co-authors uses Bayesian melding to integrate
them. Central to this approach is the “truth” represented by a latent random Gaussian
process. Deterministic models are assumed to be affine transformations of integrals of the
truth over the grid cells that derived from the difference equation methods used to solve
these deterministic models; monitoring site measurements, such as those involved in
climate modeling, are similarly biased point measurements of the truth. A Bayesian
hierarchical framework enables the integration of these two very different outputs. This
framework enables uncertainty estimates to be added to deterministic outputs and those
outputs to be dynamically tuned over time as data flows in. At the same time, the
deterministic models may well provide statistical models with the “backbones” they lack
when confronting large - scale climatic processes.
However, a number of research questions arise in connection with the use of
deterministic models in a statistical domain. These would be addressed in the PIMS
study.
1. How should environmental processes best be monitored taking account of the
need to protect human populations from the deleterious societal impacts of such
change? (Obviously more emphasis would need to be placed on impacts on
populated areas whereas most classical design approaches focus only on physical
aspects of the environmental.)
2. How can deterministic models constructed at different scales of resolution be
statistically integrated by the use of wavelets, for example. (Those at the coarsest
resolution run quickly on a computer so the goal would be to use statistical
methods for predicting the hypothetical outputs of the deterministic models at
finer scales to gain speed and practicality.)
3. How can deterministic models be turned into practical forecasting tools, say to
predict drought or exceptionally hot weather?
4. Most environmental fields are not Gaussian processes but rather (after suitable
transformation) multivariate-t processes. How can melding be adapted for use
with such processes?
5. How can the spatial melding approach best be turned into a space-time melding
approach? (The plan: use dynamic linear modeling on the coefficients generated
by an orthogonal decomposition. Purpose built software has been developed at
UBC that might be used for that purpose.)
Funding: For #1-5 above, funding is requested below for a full time UBC-V Statistics
PhD student, Zhong Liu (Jan 1 – Aug 30, 2008) who is co-supervised by Le and Zidek.
Modeling space-time fields.
(UBC-V: Nancy Heckman, Nhu Le, Jim Zidek; UW: Peter Guttorp, Paul Sampson)
Modeling environmental space-time processes has become an area of intense research
activity (see Le and Zidek 2006. Statistical analysis of environmental space – time
processes. New York: Springer) in recent years. Yiping Dou, a Statistics PHD GRA at
UBC – V, has made substantial progress in the development of dynamic linear models
(DLMs) for such fields using the approach of West and Harrison, in particular. However
a number of topics remain to be addressed:
1. The use of physical models and the DLM in conjunction with the Le – Zidek
prefiltering approach to modeling multivariate processes with non-stationary spatial
covariances modeled by the Sampson – Guttorp approach. As well, covariates will
need to be included.
2. Models and their MCMC implementation for multivariate response vectors (where
multiple responses are obtain at each site)
3. Log matroid-normal random response fields (eg species x time x space) and their
implementation in a hierarchical Bayesian framework for environmental processes.
Funding: One year of partial postdoctoral funding is requested below for Yiping Dou, a
current UBC-V doctoral student who is expected to complete her PhD in the summer of
2007. The remainder will be provided by grants held by her current thesis co-supervisors,
Nhu Le and Jim Zidek.
Agroclimate risk analysis
(UBC-V: Nhu Le, Jim Zidek; McGill: Jim Ramsay; U San Diego: Sam Shen)
Climate change has led to the need for agricultural risk management where amongst other
things drought has assumed increasing importance. That has prompted Agriculture
Canada to allocate funding for managing risk. Such management entails the development
of appropriate models for precipitation and methods for finding optimal management
strategies. The National Program for Complex Data Structures (NPCDS) has approved
and committed funding for a startup workshop to develop a detailed research proposal
and subject to the approval of funding and the requisite matching funding, work should
begin on this project early in 2007. However, such a workshop may not now be needed
since Jim Ramsey attended one in June 2006 that reviewed, compared and discussed
techniques for gridding precipitation on 10 km and daily scales. Discussion of those
techniques with Agriculture Canada and other subject area scientists, notably Aston
Chipanshi, Denise Neilson, Harvey Hill and Allan Howard, suggested some important
statistical research directions for risk management.
In particular, new methods are needed for spatial precipitation analysis that admit
covariates such as elevation, wind direction and velocity, along with other climate
covariates to improve the accuracy of precipitation. Moreover recent advances in
statistical theory make it possible to estimate aspects of the entire distribution of rainfall
at any given location and time point.
Such advances include work on quantile regression pioneered by Roger Koenker and his
colleagues, and described in Koenker, R. (2005) Quantile Regression, Cambridge
University Press. This work estimates any quantile or percentage point in the distribution
of the outcome variable defined by a linear model, in addition to the mean of that
distribution. The methodology has been already been applied to very large scale
problems, including spatially distributed data, with the collaboration of Ivan Mizera
(Dept. of Mathematics, U. of Alberta). Moreover, Jim Ramsay and a Postdoctoral
Fellow, Giles Hooker, are developing a method for estimating the distribution of a
response variable at any point over the continua over which the data are distributed. In
this context, we would have the capacity to provide an estimate of the probability density
function at any location and any time.
Alternatively, advances in hierarchical Bayesian modeling enable continuous covariate
fields (like temperature) to be input as latent variables into discrete (or mixed) process
models such as the binary process of precipitation occurrence using the clipped Gaussian
(or multivariate t) approach. This leads to a Bayesian version of disjunctive kriging
appropriate for use in climate change impact modeling of precipitation fields. A large
number of unanswered questions arise in this connection. The process of answered these
question began at UBC-V this summer with the work of Reza Hosseini, a Statistics PhD
student. He downloaded Alberta precipitation data and wrote the software needed to
manage it. Finally, he began to look into the feasibility of building a hierarchical
Bayesian model using ideas of De Oliveira (2000 Computational and Statistical & Data
Analysis, 299-314.)
Funding: Funding has been tentatively approved by the National Program for Complex
Data Systems (NPCDS) with Agriculture Canada as a funding partner. That will support
another full time Statistics PhD GRA, Reza Hosseini (Jan 1 2007 –Dec 30 2008). No
PIMS funding will be needed to cover this part of the proposed research program.
Environmental quality assessment, with emphasis on water and linkages to
agriculture and species at risk.
(UBC-O: Sylvia Esterby, Paramjit Gill, Jason Loeppky; National Water Research
Institute and McMaster: Abdel El-Shaarawi)
Assessment of status and trends and the prediction of future status provide important
information for the processes of environmental planning and management. Attribution of
changes in environmental status to natural or anthropogenic origin is also critical. The
Okanagan region faces pressures on water resources, forests, rare species and air quality
from rapid population growth and changing climate. Agricultural practices are adapting
to climate change and to the need for sustainable modes of operation. As such, the region
provides an ideal setting for studying environmental change as a prototype for expected
changes due to a warming climate and in relation to agriculture and impacted species.
The PIMS study will concentrate on improved methods for the analysis of environmental,
ecological and agricultural data and on data collection designs, clear needs if predictive
models and climate-change/resource-sector-impact scenarios are to provide reliable
information for planning and management. The study will also address an imbalance
between the expenditure of effort and resources, high for data collection and low for the
extraction of information from data. Some research topics which have been identified are
briefly described:
1) Regardless of the environmental question being considered, invariably the question
asked is whether or not environmental quality is changing. Methods that incorporate the
complexities of the system, including covariates if appropriate, will be developed and
applied to existing climatological and water-resource data sets to permit quantitative
statements about status and change in status, be it linear change or change of a more
complex nature. Currently nonparametric methods that are amenable to testing for
monotonic change are often all that is used. Modern smoothing and regression methods
will be adapted and/or extended to the particular designs of the data collections.
2) Climate scenarios and hydrological scenarios are being developed from models,
where the models are calibrated with observational data. An open question is how to
determine if the model is adequate for the region of interest. One method is the
calculation of a coefficient that measures how well the model-generated hydrograph
compares with the observed hydrograph. Methods for testing the fit will be developed
where several features of the record are important. Model calibration is important in a
number of other areas where models are being used to develop scenarios after a
qualitative judgment of the adequacy of the calibration. Quantitative methods for
evaluating the calibration would increase our confidence in the credibility of the
scenarios being generated.
3) Locations where fruit crops can be grown depend on microclimates in mountainous
areas. Analyses of fruit-crop pests will be extended to include new data on microclimates
in situations where pest counts are low. This is a case of spatial-temporal modeling of
counts with covariates and in the presence of many zeros. The data sets are part of a
project to control pests with reduced usage of pesticides. Statistical methods used for this
data set will be relevant to another area of interest, methods for species at risk where
counts are low. Sample collection designs are also being considered. These topics
coincide with the research interests of Zuzana Hrdličková who is expected to spend a post
doctoral year at UBC O, with some time at collaborating universities. Collaborations with
Howard Thistlewood, entomologist, at Pacific Agri-Food Research Centre in
Summerland will continue.
4) Environmental quality is always measured in terms of an indicator. The indicator may
be simple such as the concentration of a specific form of phosphorous in a stream
collected under standard conditions, complex where a suite of measurements are used, or
derived as an index from a suite of measurements. Remote sensing provides the
opportunity for the development of indicators that may cost less than ground
measurements or provide more spatially extensive data. Statistical methods play a role
since a relationship between the remote measurement and the environmental property
must be established in the use of such quality indicators. A project has been proposed for
the application of GIS and remote sensing on watershed hydrology and other watershed
processes.
Aquatic Habitat Indicators and Forest Harvesting in BC Interior: Using suitable
indicators as an important approach to support sustainable forest management has been
widely recognized in scientific and resource management communities. This approach is
particularly relevant in BC because of the recent introduction of the results-based Forest
and Range Practices Act (FRPA). In spite of significant efforts devoted to selection of
forest sustainability indicators, many identified watershed indicators have not been well
tested and applied in supporting design of forest management strategies for protection of
both terrestrial and aquatic values in BC. Lack of well-tested, sensitive, measurable
indicators as well as a system for their broad application will greatly constrain our ability
to evaluate the environmental implications of the results-based FRPA. Therefore, we
propose to use GIS and remote sensing, together with multivariate statistical analysis
based on field measurements to assess aquatic habitat indicators at both the stream reach
and watershed scale. The aquatic habitat indicators to be tested would mainly be focused
on channel morphological features (e.g. residual pool depth, channel unit sequences,
substrate, sinuosity etc.), riparian conditions and characteristics of in-stream large woody
debris (LWD).
The rationale for this proposed research includes the following. First, there are many
watershed indicators including hydrology, water quality, biology and channel
morphology. It has been suggested that those stream morphology-related aquatic habitat
indicators are likely more sensitive to forest management and land use changes, and they
can also be easily measured and monitored. Second, large spatial variability generally
exists in many aquatic habitat indicators and their interactions with watershed properties,
forest disturbance and land use changes. The spatial variability could best be assessed
through GIS and remote sensing technologies.
5) Mapping water quality in southern British Columbia streams/creeks: There are about
300 watersheds in the southern British Columbia. A short term goal of the project is to
map the (seasonal) water quality indicators for these watersheds and relate the quality to
bio-geoclimatic zones and to the level of land use for upstream reaches.
The long term goals are : (i) To create a province-wide coordination with other agencies
and groups, (ii) To create a standardized database for the region and (iii) Long term
predictions taking climate change and human intervention into account.
6) Linkages with the “Statistical vs Deterministic Models” project of UBC V are
expected in terms of hydrological modeling. An additional aspect, regional downscaling
of climate predictions is particularly relevant in developing climate-driven hydrological
scenarios in mountainous regions.
Funding: One year of partial postdoctoral funding is requested for Zuzana Hrdličková,
PhD student at Masaryk University Brno Czech Republic, who is about to complete her
degree and is expected to come to UBC O early January 2007. Partial funding is
requested to support a PhD level GRA in year two of the CRG. . The remainder will be
provided by research grants, funding of partners at Environment Canada and teaching one
course (post doc).
Impact of climate change: Modeling changes in the diversity and structure of
forests and in animal and insect populations, and assessing impact on human
health (SFU: Charmaine Dean, Rick Routledge, Carl Schwarz; UBC-V: Mike Brauer, John
Petkau, Kirstin Campbell; UBC-O: Sylvia Esterby; U Victoria: Bill Reed, Farouk Nathoo;
UNBC: Chris Hawkins; U Alberta: Fangliang He; U Toronto: Dave Martell; U Western
Ontario: John Braun; U Calgary: Ed Johnson)
Forest fires are a natural component of many of Canada’s forested ecosystems, yet they
pose a threat to public safety, property and forest resources. Forest fires cause millions of
dollars worth of damage and sometimes force the evacuation of affected communities.
Affiliated industries can also be heavily affected; for example, construction labour costs
have risen dramatically in Kelowna, BC, because of the need to replace the many houses
that were destroyed by fire in August of 2003. Such problems will be exacerbated as
more homes and cottages are established in and near forested areas and as climate change
alters forest vegetation. Currently, there is a very limited understanding of the changes
in diversity and structure of forests as a consequence of fire regime and landscape
change. Studies that address these issues are critical, however, in view of future changes
in fire regimes because of climate shifts. Forest ecology studies are also important with
increasing outbreaks of mountain pine beetle and other insects and also more broadly in
evolutionary studies which aim to understand how the conversion of old-growth forests
to managed forests affects the structure, function, and species diversity of ecosystems and
whether converted forests will eventually recover to a state that mimics many of the traits
of old-growth stands. Research topics include:
1) The forest fire research community has made steady progress over the past four
decades in increasing our understanding of the nature of forest fires. Deterministic spread
models are used for planning purposes and have been incorporated in computer
simulations to aid in the prediction of the future behaviour of existing and potential fires.
Such models are used in conjunction with queueing, simulation and mathematical
programming models for the strategic and tactical management of fire-fighting resources
such as aircraft and fire-fighters. Although much has been learned about the interactions
of weather and fuel-types and their effects on fire spread and intensity, a large number of
questions remain. For example, how can the fire hazard in particular areas be estimated
reliably, given sparse networks of weather stations, precipitation radar and lightning
stroke detectors? Importantly, what are the potential impacts of climate change on fire
regimes and fire management systems? How should uncertain weather forecasts influence
the management of large project fires? What is the impact of pine beetle on fire regime?
We will develop stochastic models of these processes, including adaptations of point
process intensity models have been used successfully to model earthquakes and
volcanoes. For example, the times and locations of lightning strikes and fire ignitions can
be viewed as a bivariate point process. A mutually exciting process is a possible model,
where the lightning process drives the ignition process, but where the ignition process
itself may also have a self-exciting component, such as jump-fires. Interacting particle
system models offer a way to model, stochastically, the spatio-temporal dynamics of a
forest fire. Stochastic cellular automata may provide a way to simulate fire spread more
effectively than current deterministic models. In particular, jump-fires might be modelled
more effectively.
2) Scientists have recently begun using charcoal abundances in lake sediments to
generate insight on the local fire history. A layer of sediment in which charcoal is
unusually abundant suggests a local fire around the time that the layer was deposited.
Statistical techniques will be developed for distinguishing such layers from an often noisy
background and estimating the deposition dates for the sediment. There are frequently
several sources of incomplete information from sources such as 14C estimates from
older, deeper deposits, 210Pb estimates from younger deposits closer to the sediment
surface and fire scars on trees. There is typically a gap of around 200 years between the
two types of isotope dates where, in the absence of fire-scarred trees, there is no direct
information on deposition dates. In addition, a researcher may have observations from
sediments in several lakes which need to be analyzed spatially in tandem. Recent
developments in computational Bayesian statistics will be of particular value, along with
ideas from state-space modeling, statistical process control, and metaanalysis. In addition,
evidence is emerging of substantial changes in fire history associated with European
suppression of aboriginal broadcast burning in the 19th century and subsequent
suppression of wildfires in the latter half of the 20th century. Other specific needs for
improved statistical methodology include incorporating information from multiple
sources for dating a lake sediment core, and a variety of unsolved statistical challenges
associated with combining charcoal records in lake sediments, fire scars on nearby trees,
and written and oral history for inferring fire history.
3) In the forest ecology arena, an important focus will be to develop and test new
methods for predicting pine beetle outbreaks and the outbreak severity based on forest
data and climate data. The lack of stability caused by pine beetle and fire is a threat to
economic sustainability, but that variability supports the biodiversity that is so essential
for the maintenance of natural ecosystem processes. We will therefore also develop new
statistical models that can be incorporated in stochastic timber supply models that will be
used to explore the extent to which tradeoffs between these apparently conflicting
management and environmental objectives affect economic returns, harvest levels, and
harvest flow stability, reconciling those with the integrity of the natural ecosystem
processes.
For modeling annual beetle infestations in British Columbia forests state space models
will be employed including “mixture models” where the population consists of two or
more subsets behaving differently and where spatial clustering is evident both in the
placement of the population mixtures and their evolution over time. With pine beetle
attacks on trees, it is hypothesized that there are present trees that never succumb to
attack, while other trees experience transitions from the attacked to non-attacked states,
for example, depending on spatially-correlated, random effects. The primary goal of this
aspect of the work is the development of methodology for analysis of such spatiallycorrelated mixture Markov models. This is important for identifying trees from the two
sub-populations and their characteristics, and how susceptibility to attack depends on the
spatial environment and temporal effects. Advancements in the development of
methodology in this field have been recently made by Nathoo (U Vic) and Dean (SFU).
Extensions to include effects of a weevil parasite which is predominant in the Pacific
region are underway. Complex models for multiple insect attacks are important in a
variety of areas and methodology developed will be framed in a broad context.
4) The development of methods for mapping species abundance and diversity is required
for forest management and conservation. It is important to understand how the
conversion of old-growth forests to managed forests affects the structure, function, and
species diversity of ecosystems and whether converted forests will eventually recover to
a state that mimics many of the traits of old-growth stands. Methods for the development
and dynamics of the ecosystems from a newly disturbed to an old-growth stand and the
development of tools for predicting vegetation succession are fundamental. Of
importance in the short term is the reliable projection of some specific, important stand
features. However, evolution to a substantial spatio-temporal scale which will investigate
stand dynamics for exploring environmental, and particularly climatic, changes for forest
management is of essence. This research is part of a multidisciplinary coastal forest
chronosequences study, starting from 1991, led by the Canadian Forest Service.
For modeling succession dynamics, stem mapping techniques, statistical point process
modeling and computer simulation will be jointly utilized. A specific goal is to
understand how the three dominant species, Douglas-fir, western hemlock, and western
redcedar, coexist and partition space along a chronosequence comprised of immature,
mature, and old-growth stands.
5) The development of methods for assessing the impacts of climate change on animal
populations and on human health is another important facet of this component. In order
to assess the impacts of change, it is necessary to know basic biological parameters about
animal populations such as survival rates, population numbers, population movement
rates etc. These are often obtained using methods such a capture-capture, point-count, or
distance-sampling. The design of long-term studies using these methods needs to be
planned carefully in order to detect change with some reliability. To give an idea of the
order of magnitude of some of these studies, the Northern Spotted Owl is an endangered
species in the Pacific North West. There has been a 20+ year monitoring study where
approximately 32,000 captures have been made on 11,000 banded birds costing about
(cumulative) $25,000,000 in field and analysis costs! The analysis of such studies
requires sophisticated analysis tools not usually available, nor accessible to most
biological researchers. The development of suitable methodologies in capture-recapture,
distance-sampling, and point-count methodologies for these large scale problems will be
another focus of this CRG. In addition, tools for both modeling and analysis of current
ecosystems and inferring past conditions from natural recorders will be investigated.
Current applications include (i) ecological interactions between salmon farms, sea lice,
and wild Pacific salmon, and (ii) the role of spring river discharge on the marine survival
of outmigrating juvenile sockeye salmon in Rivers Inlet, British Columbia. Identified
needs for improved statistical methodology include relating deterministic, fluid-dynamic
modelling to observations containing considerable stochastic components. In the area of
human health, methods for quantifying risk for certain diseases (asthma, cardiovascular
disease) associated with climate change and specific strategies to assess health impacts
will be considered. A specific and important application is the development of methods
for forest fire smoke modeling and linkages with adverse events related to asthma.
Funding: Partial funding to support graduate students working in the areas of topics 2,
3 and 5 is requested. Support for research in the other topics will be provided by NPCDS
funding with partners from the Canadian Forest Service, the GEOIDE NCE, the BC
Ministry of Forests and the German Center for Environmental Research.
7. Budget:
2007
GRAs
UBC-V
SFU
UBC-O
12320
22000
Total RAs
Postdocs
Travel
Meeting costs
Total cost
2008 Total
22880
19240
12320
44880
19240
34320
42120
76440
25167
3000
49500
13333
50000
38500
3000
99500
111987
105453
217440
Opening meeting
TIES NA 2007
PNWEM
Workshop 1
19500
5000
Summer school 1
Workshop 2
Summer school 2
BIRS
TIES 2008
Total
10000
Semiahmoo
Seattle
3000
15000
49500
SingaporeVancouver
Seattle
20000 Lund
10000 NCAR
10000 Banff
7000 Kelowna
50000
Investing in people, discovery and innovation
Investir dans les gens, la découverte et l'innovation
FORM 100
Personal Data Form
PART I
Family name
Given name
Date
2006/09/24
Initial(s) of all given names Personal identification no. (PIN)
Dean
Charmaine
CB
48748
I hold a faculty position at an eligible Canadian college
(complete Appendices B1 and C)
I do not or will not hold an academic appointment at a
Canadian postsecondary institution
Place of employment other than a Canadian postsecondary
Institution (give address in Appendix A)
APPOINTMENT AT A POSTSECONDARY INSTITUTION
Title of position
Tenured or tenure-track
academic appointment
Burnaby Mountain Research Professorship
Yes
No
Department
Statistics & Actuarial Science
Part-time appointment
Campus
•
Burnaby, B.C. V5A 1S6
Canadian postsecondary institution
•
Simon Fraser
Full-time appointment
X
For all non-tenured or non tenure-track academic appointment and
Emeritus Professors, complete Appendices B & C
For life-time Emeritus Professor and part-time positions, complete
Appendix C
ACADEMIC BACKGROUND
Degree
Name of discipline
Institution
Country
Date
yyyy/mm
Mathematics Hons.
University of Saskatchewan
CANADA
1980 / 10
Master's
Statistics
University of Waterloo
CANADA
1984 / 06
Doctorate
Statistics
University of Waterloo
CANADA
1988 / 06
Bachelor's
TRAINING OF HIGHLY QUALIFIED PERSONNEL
Indicate the number of students, fellows and other research personnel that you:
Over the past six years
(excluding the current year)
Currently
Supervised
Co-supervised
Supervised
Co-supervised
Total
3
2
10
Undergraduate
Master's
5
Doctoral
4
1
Postdoctoral
2
7
2
2
Others
Total
Form 100 (2006 W)
9
1
7
Personal information collected on this form and appendices will be
stored in the Personal Information Bank for the appropriate program.
PROTECTED WHEN COMPLETED
2
19
Version française disponible
Not Completed
Personal identification no. (PIN)
Family name
48748
Dean
ACADEMIC, RESEARCH AND INDUSTRIAL EXPERIENCE (use one additional page if necessary)
Position held (begin with current)
Organization
Period (yyyy/mm
to yyyy/mm)
Department
2006 /09
Burnaby Mountain Research
Professorship
Simon Fraser
Statistics & Actuarial
Science
Affiliate Scientist
BC Cancer Agency
Cancer Control
Research
2004/09
Associate Dean
Simon Fraser University
Faculty of Health
Sciences
2004/09
2005/08
to
Associate Director
Simon Fraser University
Inst. for Health
Research & Education
2004/04
Visiting Fellow
University of Queensland
School of Public Health
2003/01
2003/09
to
Professor
Simon Fraser University
Statistics & Actuarial
Science
2002/09
Chair (prev. Director)
Simon Fraser University
Statistics & Actuarial
Science
to
1998/09
2001/08
to
1996/01
1996/12
to
1995/09
2002/08
Visiting Associate Professor
Associate Professor
Form 100 (2006 W), page 2.1 of 4
University of Washington
Simon Fraser University
PROTECTED WHEN COMPLETED
Biostatistics
Math & Stat/Statistics
& Actuarial Sc
Version française disponible
Personal identification no. (PIN)
Family name
48748
Dean
ACADEMIC, RESEARCH AND INDUSTRIAL EXPERIENCE (use one additional page if necessary)
Position held (begin with current)
Assistant Professor
Assistant Professor
Form 100 (2006 W), page 2.2 of 4
Organization
Simon Fraser University
University of Calgary
PROTECTED WHEN COMPLETED
Department
Period (yyyy/mm
to yyyy/mm)
Mathematics &
Statistics
to
1989/06
1995/08
Mathematics &
Statistics
to
1988/06
1989/05
Version française disponible
Personal identification no. (PIN)
Family name
48748
Dean
RESEARCH SUPPORT
Family name and initial(s)
of applicant
Title of proposal, funding source and program,
and time commitment (hours/month)
Amount
per year
Years of
tenure
(yyyy)
List all sources of support (including NSERC grants and university start-up funds) held as an applicant or a co-applicant: a) support held in the
past four (4) years but now completed; b) support currently held, and c) support applied for. For group grants, indicate the percentage of the
funding directly applicable to your research. Use additional pages as required.
a) Support held in the past 4 years
Dean, C.B.
New methodology for handling overdispersion as
arises in recurrent event data and disease mapping
NSERC
Research Grant
60 hours/month
21,000
21,000
21,000
21,000
21,000
1999
2000
2001
2002
2003
Ugarte, M.D.
Analysis of cancer mortality in Navarra, Spain
Spanish and Navarran Government
5 hours/month
25,000
25,000
25,000
2000
2001
2002
MacNab, Y.C.
Neonatal health services in Canada
MRC
Research Operating
10 hours/month
74,610
74,610
2001
2002
Hayes, M.
Urban structure, population health and public
policy
CPHI
5 hours/month
521,538
521,538
521,538
521,538
2002
2003
2004
2005
Form 100 (2006 W), page 3 of 4
PROTECTED WHEN COMPLETED
Version française disponible
Personal identification no. (PIN)
Family name
48748
Dean
RESEARCH SUPPORT
Family name and initial(s)
of applicant
Title of proposal, funding source and program,
and time commitment (hours/month)
Amount
per year
Years of
tenure
(yyyy)
List all sources of support (including NSERC grants and university start-up funds) held as an applicant or a co-applicant: a) support held in the
past four (4) years but now completed; b) support currently held, and c) support applied for. For group grants, indicate the percentage of the
funding directly applicable to your research. Use additional pages as required.
a) Support held in the past 4 years
Borwein, P.
4,700,000
IRMACS: Interdisciplinary research in the
mathematical and computational sciences
CFI
2 hours/month
2002
Vanasse, A.
SIST-IM: Systeme d'information spatio-temporel
sur l'infarctus du mycarde
GEOIDE
10 hours/month
126,900
126,900
126,900
2002
2003
2004
Dean, C.B.
Modeling and simulating the dynamics of coastal
forests
Canadian Forestry Service
Student Support
5 hours/month
22,000
2005
Braun J., Dean, C.B., and
Martell, D.
Forests, Fires and Stochastic Modeling
NPCDS
Workshop
2 hours/month
20,000
2005
Form 100 (2006 W), page 3.1 of 4
PROTECTED WHEN COMPLETED
Version française disponible
Personal identification no. (PIN)
Family name
48748
Dean
RESEARCH SUPPORT
Family name and initial(s)
of applicant
Title of proposal, funding source and program,
and time commitment (hours/month)
Amount
per year
Years of
tenure
(yyyy)
List all sources of support (including NSERC grants and university start-up funds) held as an applicant or a co-applicant: a) support held in the
past four (4) years but now completed; b) support currently held, and c) support applied for. For group grants, indicate the percentage of the
funding directly applicable to your research. Use additional pages as required.
b) Support currently held
Carleton, B.
Modelling trends and regional variations in
asthma medication and health service utilization
to improve care
CIHR
5 hours/month
124,037
124,037
124,037
2004
2005
2006
Dean, C.B.
New methodology for the design and analysis of
longitudinal count studies
NSERC
Discovery Grant
60 hours/month
36,000
36,000
36,000
36,000
36,000
2004
2005
2006
2007
2008
Vanasse, A. and Dean, C.B.
Spatio-temporal Information System: Chronic
diseases and primary care
GEOIDE
10 hours/month
124,729
124,729
124,729
124,729
2005
2006
2007
2008
Dean, C.B.
Stochastic Modeling in Forestry and
Epidemiology
BIRS
Workshop
2 hours/month
40,000
2006
Form 100 (2006 W), page 3.2 of 4
PROTECTED WHEN COMPLETED
Version française disponible
Personal identification no. (PIN)
Family name
48748
Dean
RESEARCH SUPPORT
Family name and initial(s)
of applicant
Title of proposal, funding source and program,
and time commitment (hours/month)
Amount
per year
Years of
tenure
(yyyy)
List all sources of support (including NSERC grants and university start-up funds) held as an applicant or a co-applicant: a) support held in the
past four (4) years but now completed; b) support currently held, and c) support applied for. For group grants, indicate the percentage of the
funding directly applicable to your research. Use additional pages as required.
b) Support currently held
Braun, J., Dean, C.B., and
Martell, D.
Forests, Fires and Stochastic Modeling
GEOIDE&NPCDS
GEOIDE SII
25 hours/month
130,000
130,000
2006
2007
Dean, C.B.
Modeling the impact of stand dynamics on the
wood characteristics of lodgepole pine
Ministry of Forests
3 hours/month
10,000
2006
Form 100 (2006 W), page 3.3 of 4
PROTECTED WHEN COMPLETED
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Highly Qualified Personnel (HQP)
Provide personal data about the HQP that you currently, or over the past six years, have supervised or co-supervised.
Personal identification no. (PIN)
Family name
48748
Name
Type of HQP
Training and Status
Years
Supervised or
Co-supervised
Title of Project or Thesis
(Name
withheld)
Master's
(In Progress)
Supervised
2006 -
To Be Determined
(Name
withheld)
Master's
(In Progress)
Supervised
2006 -
To Be Determined
E. Juarez
Doctoral
(In Progress)
Supervised
2005 -
To Be Determined
K. Jivani
Master's
(In Progress)
Supervised
2005 -
Evaluation of an Oral Health Care
Initiative
K. Riyazi
Master's
(In Progress)
Supervised
2005 -
Health Literacy in Immigrant BC
Parents
L. Xing
Master's
(In Progress)
Supervised
2005 -
Mixed Effects Modeling for Wood
Density Analysis
S. Getzin
Doctoral
(In Progress)
Co-supervised Spatial patterns and competition of
2005 tree species
Dean
Present Position
D. Thompson Doctoral
(In Progress)
Supervised
2004 -
Mixture Models for Survival
Analysis
J. Nielsen
Doctoral
(In Progress)
Supervised
2001 -
Semi-Parametric Adaptive Spline
Analysis of Recurrent Events
L. Ainsworth Doctoral
(In Progress)
Supervised
1999 -
Mapping Zero-Heavy Disease
Rates
L. Zeng
Postdoctoral
(Completed)
Incomplete Longitudinal Data
Supervised
2005 - 2006 Analysis
Assistant Professor, SFU
G. Silva
Postdoctoral
(In Progress)
Spatial Survival Analysis
Supervised
2004 - 2005
Assistant Professor, Instituto
Superior Técnico, Portugal
S. Jiwani
Master's
(Completed)
Changepoint Survival Analysis
Supervised
2003 - 2005
Statistical Analyst, Office of
Student Affairs, SFU
F. Nathoo
Doctoral
(Completed)
Spatial Markov Mixture Models
Supervised
2001 - 2005 and Analysis
Assistant Professor, UVic
M. Chui
Master's
(Completed)
Multistate Survival Analysis
Supervised
2000 - 2002 Model for Two Endpoints
Research Statistician, Workers'
Compensation Board
J. Nielsen
Master's
(Completed)
Semi-Parametric Analysis of
Supervised
1999 - 2001 Recurrent Event Data
PhD student under my supervision
M. Ugarte
Postdoctoral
(Completed)
Mapping Disease Rates
Supervised
1997 - 1999
Assistant Professor, Univ Publica
de Navarra, Spain
Y. MacNab
Doctoral
(Completed)
Spatio-Temporal Modeling of
Supervised
1995 - 1999 Rates
Assistant Professor, UBC Health
Care & Epidemiology
Form 100 (2006 W), page 4 of 4
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stored in the Personal Information Bank for the appropriate program.
PROTECTED WHEN COMPLETED
Note: 1 Yr Maternity Leave Ended
Sept 2003
Version française disponible
5
Dean 48748 FORM 100 PART II
1. Most Significant Contributions to Research and/or to Practical Applications
See end of Section for listing of these publications.
Derivation of Methods for Mapping Disease/Mortality Rates
This is work done with my PhD students Y. MacNab, F. Nathoo and my PDFs M. Ugarte and
G. Silva. MacNab and Dean (2001) develops methods for describing the geographic and temporal distribution of mortality/incidence rates using generalized additive mixed models. The
models use autoregressive local smoothing across the spatial dimension and spline smoothing
over the temporal dimension. MacNab and Dean (2002) discusses spatio-temporal modeling of
rates and disease mapping broadly. This paper has had high impact in the biostatistical usercommunity. Dean, Ugarte and Militino (2001) develops tests for interaction between random
spatially correlated region and fixed age-group effects in disease mapping. It is not uncommon
for mapping studies to proceed on the assumption that this interaction is absent. This paper
discusses that the effect of a failure of the assumption can be substantial and derives a simple test for interaction, and the computation of its power function. Note that new work with
Nathoo makes substantial strides in the advancement of methods for spatio-temporal analyses
by developing methods for the analysis of both discrete time and continuous time longitudinal
spatial data permitting spatial variability in the rates of transition. Recent new work with Silva
focuses on specialized techniques in spatial analyses for non-rare events.
Count Processes and Longitudinal Data Analysis
This is work done with my PhD student R. Balshaw. Dean and Balshaw (1997; JASA) considers
the loss in efficiency in the analysis of counts generated from a non-homogeneous Poisson process versus the analysis of the full counting process which records the actual times of occurrence
of events. Data for an individual are stochastically ordered, correlated, subject to censoring,
and the times of followup need not be coincident. The paper derives conditions under which
the analysis of the counts is fully efficient both for models with and without random effects.
The paper also considers the loss in efficiency when the conditions are not satisfied, explores
how different experimental designs affect efficiency, and how far away from the ideal design one
must be before severe losses are incurred. The practical relevance is cost-effective design of
clinical studies. Balshaw and Dean (2002) develop methods for the semiparametric analysis of
recurrent event data arising in a panel structure.
Student co-authors are indicated in bold.
Dean, C.B. and Balshaw, R. (1997), Efficiency lost by analyzing counts rather than event
times in random effects Poisson processes, J. Amer. Statist. Assoc., 92, 1387-1398.
1. Balshaw, R. and Dean, C.B. (2002), A Semi-Parametric Model for Recurrent Event
Panel Data, Biometrics, 58, 324-331.
2. MacNab, Y. and Dean, C.B. (2001), Autoregressive Spatial Smoothing and Temporal
Spline Smoothing for Mapping Rates, Biometrics, 57, 949-956.
3. MacNab, Y. and Dean, C.B. (2002), Spatio-Temporal Modeling of Rates, Statistics in
Medicine, 21, 347-358.
Dean 48748 FORM 100 PART II
6
4. Dean, C.B., Ugarte, M.D. and Militino, A.F. (2001), Detecting Interaction between
Random Region and Fixed Age Effects in Disease Mapping, Biometrics, 57, 197-202.
2. Other Research Contributions
Refereed Publications
5. Nathoo, F. and Dean, C.B. (2006), Spatial Multi-State Transitional Models for Longitudinal Event Data. To appear in Biometrics – under revision.
6. Getzin, S., Dean, C.B., He, F., Trofymow, T., Wiegand, K., Wiegand, T. (2006), Spatial
Patterns and Competition of Tree Species in a Chronosequence of Douglas Fir Forest on
Vancouver Island. To appear in Ecography.
7. Synnes, A.R., MacNab, Y.C., Qiu, Z., Ohlsson, A., Gustafson, P., Dean, C.B., Lee, S.K.,
and the Canadian Neonatal Network (2006), Neonatal Care Unit Characteristics Affect
the Incidence of Severe Intraventricular Hemorrhage, To appear in Medical Care.
8. Nathoo, F. and Dean, C.B.(2006), A Mixed Mover-Stayer Model for Spatio-Temporal
Two-State Processes. To appear in Biometrics – under revision.
9. Ainsworth, L.M., and Dean, C.B. (2006), Approximate Inference for Disease Mapping.
To appear, Computational Statistics and Data Analysis.
10. Nathoo, F., Ainsworth, L., Gill, P., and Dean, C.B., (2006) Spatial Analysis of Codling
Moth Incidence in Okanagan Orchards. To appear, Canadian Journal of Statistics.
11. Nathoo, F. and Dean, C.B. (2005), Spatial Multi-State Models with Application to
Revascularization Intervention in Quebec, Geomatica, 59, 335-343.
12. MacNab, Y.C. and Dean, C.B., (2005) Spatio-Temporal Modeling, Encyclopedia of Biopharmaceutical Statistics, Wiley, Shein-Chung Chow (ed.).
13. Nielsen, J. and Dean, C.B. (2005), Regression Splines in the Quasi-Likelihood Analysis
of Recurrent Event Data, Journal of Statistical Planning and Inference, 134, 521-535.
14. Silva, G.L., Dean, C.B., Courteau, J., Niyonsenga, T. and Vanasse, A. (2005). “Anlise
espacial de admisso de pacientes com enfarte do miocrdio em Quebeque”. In Carlos A.
Braumann, C.A., Infante, P., Oliveira, M.M., Alpzar-Jara, R. and Rosado, F. (Editors),
“Estatstica Jubilar”, Proceedings of the XII SPE Annual Congress, SPE Edition, pg.
717-722, Lisbon.
15. MacNab, Y.C., Qui, Z., Gustafson, P., Dean, C.B., Ohlsson, A., and Lee, S.K.(2004),
Hierarchical Bayes Analysis of Multilevel Health Services Data: A Canadian Neonatal
Mortality Study, Health Services and Outcomes Research Methodology, 5, 5-26.
16. Niyonsenga T., Courteau J., Dean C., Hemiari A., Bénié G., Vanasse A. (2004), Geomatics, Epidemiology and Biostatistics : an Application to Acute Coronary Syndrome. In
J. Pilz (Ed.): Interfacing Geostatistics, GIS and Spatial Data Bases. Proceedings of the
International Workshop StatGIS2003. Springer, Berlin-Heidelberg.
Dean 48748 FORM 100 PART II
7
17. Dean, C.B., Ugarte, M.D. and Militino, A.F. (2003), Penalized Quasi-Likelihood with
Spatially Correlated Data, Computational Statistics and Data Analysis, 45, 235-248.
18. Dean, C.B. and MacNab, Y. (2001), Modeling of Rates over a Hierarchical Health Administrative Structure, Canadian Journal of Statistics, 29, 405-419.
19. Militino, A.F., Ugarte, M.D. and Dean, C.B. (2001), The Use of Mixture Models for
Identifying High Rates in Disease Mapping, Statistics in Medicine, 20, 2035-2049.
20. Ghahramani, M., Dean, C.B., and Spinelli, J. (2001), Simultaneous Modeling of Operative Mortality and Long-term Survival after Coronary Artery Bypass Surgery, Statistics
in Medicine, 20, 1931-1945.
21. Dean, C.B. and Balshaw, R. (2001), Methods for the Analysis of Recurrent Events,
Proceedings of the International Biometric Society Spanish Regional Meeting, Universidad
Pública de Navarra, 37-41.
22. MacNab, Y. and Dean, C.B. (2000), Parametric Bootstrap and Penalized Quasi-Likelihood
Inference in Conditional Autoregressive Models, Statistics in Medicine, 19, 2421-2435.
Articles Submitted to Refereed Journals
23. Chui, M., Dean, C.B., and Spinelli, J., (2005) A Multi-State Model for Joint Investigation
of Two Endpoints in Survival Analysis.
24. Silva, G., Dean, C.B., Hierarchical Bayesian spatio-temporal mapping of revascularization odds using smoothing splines.
25. Silva, G., Dean, C.B., Niyonsenga, T., and Vanasse, A., Geographical variation and
temporal trends in revascularization in Québec, 1993 - 2000.
26. Silva, G., Dean, C.B., Niyonsenga, T., and Vanasse, A., Spatio-temporal variation in
coronary-artery bypass procedures in Québec with emphasis in estimation of an intervention effect.
27. Ainsworth, L. and Dean, C.B., Spatial Analysis of Zero-Heavy Count Data.
28. Lee, S.K., MacNab, Y.C., Qui, Z., Ohlsson, A., Dean, C.B., Gustafson, P., Lynn, Y.C.,
and the Canadian Neonatal Network, Risks of Mortality among Neonates Admitted to
Canadian Neonatal Intensive Care Units: Beyond Reporting on Rates.
29. Ding, Y. and Dean, C.B., Single Factor Analysis of Overdispersed Counts.
30. Prior, J.C., Nielsen, J.D., Hitchcock, C.A., Williams, L.A., and Dean, C.B., Medroxyprogesterone compared with Conjugated Equine Estrogen for Vasomotor Symptoms after
Premenopausal Ovariectomy, Submitted for Publication.
Dean 48748 FORM 100 PART II
8
3. Other Evidence of Impact and Contributions
Relevance of Work
Overdispersion: Dean, C.B. (1992), Testing for overdispersion in Poisson and binomial regression models, J. Amer. Statist. Assoc. 87, 451-457. My previous work on overdispersion
generated substantial interest in the community with many application papers and several
methodological papers considering related problems. This paper has been used as a building
block for much other work and hence I mention it – based on citations of publications in 1992
of this high impact journal, this article ranks in the top 5%. I continue to review several papers
a year which are quite closely related to this work (special cases; truncated count data models; zero-heavy count data models popular in econometric studies, for example) and primarily
because of this work I was invited to serve as a statistical appraiser for the American Public
Health Association.
Spatio-temporal methods for disease mapping: My interest in mapping rates was initiated by
the Division of Vital Statistics at the BC Ministry of Health and this work is directly related
to their mandate. It has also led to my participation in a GEOIDE NCE grant for the study
of heart disease in Quebec with the emphasis being the estimation of the effect of an intervention in the recent change in management of the disease in Quebec and in the spatial analysis
of survival data related to the disease. With Michael Hayes and others I am involved in a
study to understand spatial distribution of health inequities and localized policy impact within
Vancouver’s census metropolitan area. This will also analyze the distribution of health status
indicators, and make linkages with disease incidence and mortality at the intra-regional level;
the project will use health status indicators from BC’s Health Goals: the Roadmap Initiative,
including quality of life indicators, social capital and other variables.
Awards: 2003 CRM-SSC Award. The SSC website explains this award as follows: “The
award, jointly sponsored by the Statistical Society of Canada and the Centre de recherches
mathématiques de Montréal, is given each year to a Canadian statistician in recognition of
outstanding contributions to the discipline during the recipient’s first 15 years after earning a
doctorate.”
Prestigious Invited Lectures in the last 6 Years
2006 Workshop on Spatio-Temporal Modelling of Environmental Processes, Pamplona; 2006
Meeting of the Brazilian Statistical Society, Brazil; 2005 WNAR Meeting, Alaska; 2005 Inaugural UBC-SFU Harbour Centre Seminar Series, Vancouver; Keynote Speaker, 2003 Queensland Branch of the Australian Stat. Soc., Brisbane; 2002 Workshop, Caribbean Epidemiology
Centre, Port-of-Spain, Trinidad; 2002 Joint Statistical Meetings, New York; Keynote Speaker,
2001 Spanish Meeting of the International Biometrics Society, Pamplona; 2001 Latin-American
Congress of Probability & Mathematical Statistics, Cuba; 2001 SSC/WNAR/IMS Joint meeting, Burnaby, B.C.; 2000 Statistics and Health Conference, Edmonton, Alberta; 1999 Workshop
on Smoothing and its Applications, UBC; 1999 Spanish Biometrics Conference, Mallorca; 1999
IMS/WNAR Meeting, San Diego, CA.
Presidential Terms: Committee of Presidents of Statistical Societies, 2001-03 & 05-08; President, Statistical Society of Canada, 06-07, President-Elect 05-06, Past-President, 07-08; President, International Biometric Society, Western North-American Region, 2002; President-Elect,
Dean 48748 FORM 100 PART II
9
01; Past-President, 03; President, Biostatistics Section, Statistical Society of Canada, 1999-00;
President-Elect, 1998-99; Past-President, 2000-01.
Journals/Bulletins: Senior Editor, Advances in Disease Surveillance, 2005 - Present; Statistical Appraiser for the American Public Health Association, 1995-Present; Associate Editor,
Liaison, 1996-00, Associate Editor, Canadian Journal of Statistics, 03-2008; Associate Editor,
Biometrics, 05-08.
Granting Agencies: College of Reviewers, UK Engineering and Physical Sciences Research
Council, 2006-09; Review Panel, NIH Biostatistical Methods and Research Design, 2006-07;
Health Effects Institute, U.S. Environmental Protection Agency, 2005-06; College of Reviewers
of the Canada Research Chairs Program, 04-Present; Michael Smith Foundation for Health
Research Council Member, 2004-07; Chair of the NSERC Statistical Sciences Grant Selection
Committee, 2001-03; NSERC Statistical Sciences Grant Selection Committee, 2000-03; Michael
Smith Foundation for Health Research Population Health Grant Selection Committee, 2001-02;
Chair, Search Committee for SFU Site Director for the Pacific Institute for the Mathematical
Sciences, Fall 2000; SFU PIMS Steering Committee, 99-01; PIMS Postdoctoral Fellow Selection
Committee, 1998-00; PIMS Research Panel, 1996-98.
NISS: Board Member, National Institute of Statistical Sciences (NISS) Corporation, 2002;
AAAS: American Association for the Advancement of Science Section on Geology and Geography Cmtee, 2003-05; ASA: Snedecor Award Cmtee, 2001-2003; SSC: SSC Research Cmtte
(97-03); Publications Cmtee (00-01); Elections Cmtee (00-01); Search Cmtee for Editor of
CJS (99-00); Chair, Cmtee on Women in Statistics (97-98); Chair, Education Cmtee (96-97);
WNAR Program Chair, 1999 Seattle Meeting; CRM: Chair, CRM-SSC Award Committee,
2004-05.
4. Delays in Research Activity
Department Chair at SFU: In 1998, I became Director of Statistics and developed a proposal for the establishment of a Department of Statistics and Actuarial Science at SFU. My
main administrative priority at SFU between 1998 and 2001 was the establishment of this
department. In 2004, I became the Associate Dean in SFU’s new Faculty of Health
Sciences in charge of the hiring of twelve faculty and the development of programs. A major
implication for my research was a reduction of time for work with collaborators. However, a
strong focus on high quality training of students was maintained. I intend to increase research
activity with students and with collaborators as detailed in the proposal.
5. Contributions to the Training of Highly Qualified Personnel
Thesis Supervision detailed on Part I of Form.
Thesis Co-Supervision and External Examination:
Over the last 6 years I served as External Examiner for 4 PhD students (2000 Curtin U Australia; 2001 U of Windsor; 2002 U of Alberta; 2004 Memorial U of Newfoundland), 6 MSc
students at SFU; as a committee member for 6 MSc and 2 PhD students at SFU.
SEND ONE
ORIGINAL ONLY
DO NOT
PHOTOCOPY
Investing in people, discovery and innovation
Investir dans les gens, la découverte et l'innovation
APPENDIX A
Personal Data
(Form 100)
Complete this appendix (i) if you are an applicant or co-applicant applying for the first time; (ii) if you need
to update information submitted with a previous application; or (iii) if you do not hold an appointment at a
Canadian postsecondary institution. For updates, include only the revised information in addition to the
date, your name and your PIN.
This information will be used by NSERC primarily to contact applicants and award holders. It may also be
used to identify prospective reviewers and committee members, and to generate statistics. It will not be
seen or used in the adjudication process.
Family name
Given name
Dean
Charmaine
Date
2006/09/24
Initial(s) of all given names Personal identification no. (PIN)
CB
48748
If address is temporary,
indicate:
Position and complete mailing address if your primary place of employment is not a Canadian
postsecondary institution or if your current mailing address is temporary
Starting date
Leaving date
Telephone number
Facsimile number
(604) 291-4919
E-mail address
(604) 291-4368
dean@stat.sfu.ca
Telephone number (alternate)
Gender (completion optional)
Give an alternate telephone number only if you can
be reached at that number during business hours.
(604) 291-3331
Male
X
Female
LANGUAGE CAPABILITY
English
Read
X
Write
French
Read
X
Write
I wish to receive my correspondence:
in English
X
Speak
X
Speak
X
in French
AREA(S) OF EXPERTISE
Provide a maximum of 10 key words that describe your area(s) of expertise. Use commas
to separate them. If you have expertise with particular instruments and techniques, specify
which one(s).
overdispersion, quasi-likelihood, spatial statistics, point process, random
effect models, spline smoothing, disease mapping, longitudinal data
analysis, markov models, mixture models
Research subject code(s)
Primary
3005
Secondary
3007
Form 100, Appendix A (2006 W)
PROTECTED WHEN COMPLETED
Version française disponible
Investing in people, discovery and innovation
Investir dans les gens, la découverte et l'innovation
Appendix D (Form 100)
Consent to Provide Limited Personal Information About
Highly Qualified Personnel (HQP) to NSERC
NSERC applicants are required to describe their contributions to the training or supervision of highly qualified personnel
(HQP) by providing certain details about the individuals they have trained or supervised during the six years prior to their
current application. HQP information must be entered on the Personal Data Form (Form 100). This information includes
the trainee’s name, type of HQP training (e.g., undergraduate, master’s, technical etc.) and status (completed, in-progress,
incomplete), years supervised or co-supervised, title of the project or thesis, and the individual’s present position.
Based on the federal Privacy Act rules governing the collection of personal information, applicants are asked to obtain
consent from the individuals they have supervised before providing personal data about them to NSERC. In seeking this
consent, the NSERC applicant must inform these individuals what data will be supplied, and assure them that it will only
be used by NSERC for the purpose of assessing the applicant’s contribution to HQP training. To reduce seeking consent
for multiple applications, applicants will only need to seek consent one time for a six-year period. If the trainee provides
consent by e-mail, the response must include confirmation that they have read and agree to the text of the consent form.
When consent cannot be obtained, applicants are asked to not provide names, or other combinations of data, that would
identify those supervised. However, they may still provide the type of HQP training and status, years supervised or
co-supervised, a general description of the project or thesis, and a general indication of the individual’s present position if
known.
An example of entering HQP information on Form 100 (with and without consent):
Name
Type of HQP
Training and Status
Years
Supervised or
Co-supervised
Title of Project or Thesis
Present Position
Supervised
1994 - 1997
Isotope geochemistry in
petroleum engineering
V-P (Research), Earth Analytics
Inc., Calgary, Alberta
Isotope geochemistry
research executive in petroleum
industry - western Canada
Consent Received from Marie Roy
Roy, Marie
Undergraduate
(Completed)
Consent Not Obtained from Marie Roy
(name
withheld)
Undergraduate
(Completed)
Supervised
1994 - 1997
Consent Form
Name of Trainee
Applicant Information
Name
Dean, Charmaine CB
Department
Postsecondary Institution
Statistics & Actuarial Science
Simon Fraser
I hereby allow the above-named applicant to include limited personal data about me in grant applications submitted for
consideration to NSERC for the next six years. This limited data will only include my name, type of HQP training and
status, years supervised or co-supervised, title of the project or thesis and, to the best of the applicant's knowledge, my
position title and company or organization at the time the application is submitted. I understand that NSERC will protect
this data in accordance with the Privacy Act , and that it will only be used in processes that assess the applicant's
contributions to the training of highly qualified personnel (HQP), including confidential peer review.
Trainee's signature
Date
Note: This form must be retained by the applicant and made available to NSERC upon request.
PROTECTED WHEN COMPLETED
Form 100, Appendix D (2006 W)
Version française disponible
CURRICULUM VITAE
Sylvia R. Esterby
Mathematics, Statistics and Physics
The University of British Columbia Okanagan
Email: sylvia.esterby@ubc.c
Education
Ph.D., Statistics, 1976
B.A., Chemistry, 1968
University of Waterloo
Queen's University, Kingston
Selected Professional Experience
2005-
Associate Professor, Statistics and Head, Mathematics, Statistics and Physics, UBC Okanagan
2000-2005 Associate Professor, Mathematics and Statistics, Okanagan University College
1998-
Adjunct Associate Professor (part-time teaching to 2000), Mathematics and Statistics, McMaster University
1996-98
Research Scientist, on assignment, Canadian Wildlife Science, ECS-Ontario Region, Environment Canada.
1978 -98 Research Scientist, National Water Research Institute, Environment Canada, Burlington.
1985 - 87 Section Head, Ecological Impact Section, Aquatic Ecology Division, National Water Research Institute.
International and National Activities, 1981 – 1996
1990 Workshop on Statistical Methods, eight-country International Development Research Centre (IDRC) Project
Viña Del Mar, Chile
1992 Five day course, "The Interpretation of Analytical Data", La Secretaria de Desarrollo Social of Mexico,
organized by the Instituto Nacional de Ecologia, Mexico and sponsored by the World Bank.
1995 Consultant for River Nile Protection and Development Project, Phase II, Central Laboratory for Environmental
Quality Monitoring component, Canadian International Development Agency(CIDA), Cairo, Egypt
1995 Workshop on Water Quality Trend Assessment, Centre for Applications of Statistics and Mathematics,
University of Otaga, Dunedin, New Zealand.
National/bi-national Committees: Climatic Fluctuations and Man, Environment Canada, 1980-84; ASTM Biometrics
Sub-Committee on Water, 1983; International Joint Commission Lake Superior Task Force, 1987; Design and
Assessment of Water Quality Data Collection Programs, Environment Canada, 1987,88; Statistics and the Environment,
American Statistical Association, 1987-1989; Ecological Resource Monitoring: Change and Trend Detection
Workshop,Ecological Society of America, American Statistical Association and US EPA, 1996.
National/bi-national Workshops:
Environment Canada sponsored - Water Quality Trend Assessment, Ottawa, June 1981; pH and the Diatom, Burlington,
Nov. 1981; Lake Erie Oxygen Depletion, Burlington, Dec. 1981; Water Quality Branch Monitoring Workshop, Apr.
1985; Soluble Reactive Phosphorous, Burlington, Jan. 1987.
International Joint Commission sponsored - Persistent Toxic Substances and the Health of Aquatic Communities,
Minneapolis 1985; Monitoring Areas of Concern, Burlington, 1985; Estimation of Atmospheric Loading of Toxic
Chemicals to the Great Lakes, Scarborough, 1986.
Prairie Provinces Water Board - Water Quality Trend Assessment, Winnipeg, Dec. 1991.
Selected Professional Service
NSERC: Member of NSERC, GSC Statistical Sciences, 1997-2000; Chair 1999-2000.
Associate Editor of Environmetrics, Wiley, 1990 to 1996, Editorial Advisory Board, 1997 to present; Associate Editor
(responsible for case studies), Canadian Journal of Statistics, 1996 to 2003.
Reviewer for Natural Sciences and Engineering Research Council strategic and operating grants, Hong Kong University
Research Grants Council, and for Great Lakes University Research Fund.
The International Environmetrics Society (TIES): member of Founding Board of Directors; Secretary-Treasurer, 19891994; Treasurer, 1994-1998; President-Elect,1998-2000; President, 2000-2002; Co-Editor TIES Newsletter 2002-.
Statistical Society of Canada: includes Ontario Regional Representative, Board of Directors, 1991-1995; President-Elect,
President, Past-President Biostatistics Section, 1994-1997; Accreditation Appeals Committee (IAAC), 2004 - .
Co-Chair of the International Conference on Environmetrics, Burlington, 1994, and Genoa Italy 2002.
2 CV S.R. Esterby
Honours, Accreditation:
Fellow of the Modelling and Simulation Society of Australia and New Zealand (MSSANZ), awarded August 1, 2000.
Elected member of the International Statistical Institute, February 2004.
Accreditation as Professional Statistician, P.Stat.,2004 (Statistical Society of Canada)
Research Funding
NATO Linkage Grant and Networking Supplement ($21,900), with, Institute of Limnology, Russian Academy of
Sciences, Statistical methods and software for lake water quality series, 1998and 1999
Internal: OUC Grant-in-Aid: Modelling temporal change in water quality indicators and wildlife abundance, $2750,
2000-2001. OUC Strategic Directions and Innovation Fund, Okanagan Centre for Mathematical Biology, Sylvie
Desjardins, Rebecca Tyson, Bob Lalonde and from PARC, Howard Thistlewood and Gary Judd, $10,000, 2003.
OUC Grant-in-Aid: Risk Assessment Issues in Wildland Fire Management, $4000, 2004-2006.
NSERC Research Grant, Individual: Statistical methods in the assessment of environmental status and change, 4 yrs,
$12,000 per year, GSC 014, first year of grant is 2002-2003
GEOIDE Strategic Investment Initiative, Forests, Fires and Stochastic Modeling. Funding as Co-applicant: $12,000
01/01/06-31/12/07. Principal Investigators: C.B. Dean, D. Martell, J. Braun.
NPCDS, Forests, Fires and Stochastic Modeling. Funding as Co-applicant: $12,000 01/01/06-31/12/07. Principal
Investigators: C.B. Dean, D. Martell, J. Braun.
Publications: papers published as 34 journal or refereed proceedings, 19 proceedings and 17 reports, and one edited
proceeding. Some selected articles are as follows:
Esterby, S.R. and A.H. El-Shaarawi. 1981. Inference about the point of change in a regression model. Applied
Statistics, 30(3), 227-285.
El-Shaarawi, A.H., S.R. Esterby and K. Kuntz. 1983. A statistical evaluation of trends in water quality of the Niagara
River. J. Great Lakes Res., 9(2), 234-240.
Esterby, S.R. and A.H. El-Shaarawi. 1984. Coliform concentrations in Lake Erie - 1966 to 1970. Hydrobiologia, 111,
133-146.
Anderson, J.E., A.H. El-Shaarawi, S.R. Esterby and T.E. Unny. 1984. Dissolved oxygen concentrations in Lake Erie)
1. Study of spatial and temporal variability using cluster and regression analysis. Journal of Hydrology, 72, 209-229.
El-Shaarawi, A.H., S.R. Esterby, N.D. Warry and K.W. Kuntz. 1985. Evidence of contaminant loading to Lake Ontario
from the Niagara River. Can. J. Fish. Aquat. Sci., 42(7), 1278-1289.
Esterby, S.R., L.D. Delorme, H. Duthie and N.S. Harper. 1986. Analysis of multiple depth profiles in sediment cores:
An application to pollen and diatom data from lakes sensitive to acidification. Hydrobiologia, 141(3), 207-235.
Esterby, S.R. 1988. Statistical methods for studying biotic responses to persistent toxic substances. In: Toxic
Contaminants and Ecosystem Health; A Great Lakes Focus, M.S. Evans (Ed.), Advances in Environmental Science and
Technology, Vol. 21, Wiley, pp. 447-475.
Esterby, S.R., A.H. El-Shaarawi, G.D. Howell and T.A. Clair. 1989. Spatial characterization of acidification related
parameters in sensitive regions of Atlantic Canada. Water, Air and Soil Pollution, 46, 289-303.
Kaiser, K.L.E. and S.R. Esterby. 1991. Regression and cluster analysis of the acute toxicity of 267 chemicals to six
species of biota and the octanol/water partition coefficient. Sci. Total Environ., 109/110, 499-514.
El-Shaarawi, A.H. and S.R. Esterby. 1992. Replacement of censored observations by arbitrary values: An evaluation.
Water Research, 26, 835-844.
Esterby, S.R. and P.E. Bertram. 1993. Compatibility of sampling and laboratory procedures evaluated for the 1985
three-ship intercomparison study on Lake Erie. J. Great Lakes Research, 19, 400-417.
Esterby, S.R. 1993. Trend analyses for environmental data. Environmetrics, 4,459-481
Esterby, S.R. 1996. A review of methods for the detection and estimation of trends with emphasis on water quality
applications. Hydrological Processes, 10, 127-149. (Invited paper)
Esterby, S.R., B. Vernon, H. Thistlewood & S. Smith. 2006. Case Studies in Data Analysis, . Discussion of the analysis
of codling moth data from the Okanagan Sterile Insect Release Program. Canadian Journal of Statistics. September
3 CV S.R. Esterby
issue.
CURRICULUM VITAE FOR PETER GUTTORP
Personal
Born March 10, 1949 in Lund, Sweden.
Citizen of Sweden.
Permanent resident of the United States of America.
Education
Journalist, College of Journalism, Stockholm, Sweden, 1969.
Fil. kand., University of Lund, Sweden, 1974 (with distinction in Mathematical Statistics and Musicology).
M.A. (Statistics), University of California at Berkeley, 1976.
Ph.D. (Statistics), University of California at Berkeley, 1980.
Professional And Cross-Disciplinary Activities
Dr. Guttorp has published two monographs, 78 papers, 25 book chapters, and numerous non-refereed
works. He has supervised 21 PhD students. Dr. Guttorp has initiated and directed a multidisciplinary
research center for statistics and the environment, with participation from 32 University of Washington scientists from 14 departments. As part of the outreach aspect of this center, he assisted in the development of
a middle school curriculum aimed at teaching the scientific method through a hands-on approach. He also
initiated the University of Washington VIGRE program, enabling vertical and horizontal integration of
teaching and research between the mathematical sciences departments at the University and affecting education at all levels, from students in kindergarten to postdoctoral researchers. He is the 2004-2005 Environmental Research Professor of the Swedish Organization of Graduate Engineers.
Selected Professional Experience
1980-
Assistant, Associate and Full Professor, Statistics, University of Washington.
1996-
Director, National Research Center for Statistics and the Environment.
2002-
Chair, Statistics, University of Washington
Selected Honors And Grants
1991-09
Co-investigator on National Institute of Health grant: Behavior of Hematopoietic Stem Cells.
1996-99
Principal investigator on National Science Foundation grant: Statistics in Atmospheric Science.
1996-02
Principal 9nvestigator on Environmental Protection Agency cooperative agreement: A National
Center for Environmental Statistics.
1999-09
Co-Principal investigator on National Science Foundation grant: Integration of Research and
Education in the Applied and Computational Mathematical Sciences.
2001
Fellow of the American Statistical Association
2002-05
Co-Principal Investigator on National Science Foundation grant: Wavelet-based statistical analysis of multiscale gephysical data.
Selected Professional Services
1989-91
Member, panel on Spatial Statistics, National Research Council.
1992-
Editorial Board member, Environmental and Ecological Statistics.
1995-97
Associate Editor, Annals of Statistics.
1995-98
Program chair, 7th International Meeting on Statistical Climatology, British Columbia.
1996-03
Associate Editor, Bernoulli.
1997-
Associate editor, Environmetrics.
1999-
Member, Advisory Panel for the Geophysical Statistics Project, National Center for Atmospheric Research (Chair 2003-).
2000-
Associate Editor, International Statistical Review.
2000-04
President-elect and President, the International Environmetric Society.
2001-02
Member, Scientific Advisory Panel, Banff International Research Station.
Selected Conference Lectures
1995 Detection of closely spaced periodicities in atmospheric oscillations on Mars. Joint Statistical Meetings, Orlando.
Statistics from Mars: some analysis of Viking pressure data, Pacific Northwest Statistics Meeting,
Vancouver, Canada.
1996
Nonhomogeneous hidden Markov models relating synoptic atmospheric patterns to local hydrologic
phenomena. 2nd International Symposium on Spatial Accuracy, Boulder, Colorado.
Space-time modelling of tropospheric ozone. Royal Statistical Society International Meeting, UK.
1997 Hidden Markov models in atmospheric science. AMS Short Course on Time Series, Long Beach,
California.
1999
Picture the Future—graphical innovation in environmental statistics. Hunter lecture, TIES/SSES
meeting (ISI satellite), Athens, Greece.
2001
Six lectures on Inference for stochastic processes in environmental science. Vth Brazilian School of
Probability,Ubatuba, SP, Brazil.
2002 Bayesian estimation of nonstationary spatial covariance. Statistical Society of Canada annual meeting, Hamilton, ON, Canada.
Estimating health effects of particulate matter air pollution (two lectures). III Curso/taller de Contaminacion Atmosferica y matematicas. UNAM, Mexico City, Mexico.
2003
Where is environmental statistics going? Opening lecture, SPRUCE VI, Lund, Sweden.
2004
Spatio-temporal data analysis using spectral tools (three lectures). SEMSTAT Summer School on
Statistics of Spatio-Temporal Systems, Munich, Germany.
Recent Doctoral Students
1995
Dean Billheimer (Statistics): Statistical analysis of biological monitoring data: state-space models
for species composition.
Wendy Meiring (Statistics): Estimation of heterogeneous space-time covariance
1996
Ian Painter (Statistics): Inference in a discrete parameter space
1997
Sandra Catlin (Statistics): Statistical inference for partially observed Markov population models
1998
Brandon Whitcher (Statistics): Assessing nonstationary time series using wavelets
1999 Ashley Steel (Quantitative Ecology and Resource Management): In-stream factors affecting juvenile
salmon out-migration
2000 Enrica Bellone (Statistics): Nonhomogeneous hidden Markov models for downscaling synoptic
atmospheric patterns to precipitation amounts
Barnali Das (Statistics): Global covariance modeling: a deformation approach to anisotropy
Daniela Golinelli (Statistics): Bayesian inference in hidden stochastic population processes
Peter Craigmile (Statistics): Parameter estimation of trend contaminated long memory processes
2002
Doris Damian (Biostatistics): A Bayesian approach to estimating heterogeneous spatial covariances
2004 Tamre Cardoso (Quantitative Ecology and Resource Management): Modeling rainfall rate using a
hierarchical Bayes approach
Investing in people, discovery and innovation
Investir dans les gens, la découverte et l'innovation
FORM 100
Personal Data Form
PART I
Family name
Given name
Date
2006/5/2
Initial(s) of all given names Personal identification no. (PIN)
Zidek
V
James
I hold a full, an associate or
an assistant professor position
at a Canadian university
X
I do not or will not hold an academic
appointment at a Canadian
postsecondary institution
4599
I hold an academic appointment at a
Canadian university but am not a full, an
associate or an assistant professor
(complete Appendices B and C)
I hold a faculty position at an eligible
Canadian college (complete
Appendices B1 and C)
Place of employment other than a Canadian postsecondary institution (give address in Appendix A)
APPOINTMENT AT A POSTSECONDARY INSTITUTION
Title of position
Canadian postsecondary institution
Professor Emeritus
British Columbia
Department
Campus
Statistics
ACADEMIC BACKGROUND
Degree
Name of discipline
Institution
Country
Date
yyyy/mm
Mathematics
Alberta
CANADA
1961 / 05
Master's
Statistics
Alberta
CANADA
1963 / 05
Doctorate
Statistics
Stanford University
UNITED STATES
1967 / 09
Bachelor's
TRAINING OF HIGHLY QUALIFIED PERSONNEL
Indicate the number of students, fellows and other research personnel that you:
Over the past six years
(excluding the current year)
Currently
Supervised
Supervised
Co-supervised
Total
Undergraduate
2
2
4
Master's
2
2
4
1
4
1
2
6
14
Doctoral
1
Co-supervised
2
Postdoctoral
Others
1
Total
2
Form 100 (2005 W)
2
4
Personal information collected on this form and appendices will be
stored in the Personal Information Bank for the appropriate program.
PROTECTED WHEN COMPLETED
Version française disponible
Completed
Personal identification no. (PIN)
Family name
4599
Zidek
ACADEMIC, RESEARCH AND INDUSTRIAL EXPERIENCE (use one additional page if necessary)
Position held (begin with current)
Organization
Professor Emeritus
British Columbia
Visiting Research Scientist
Statistical & Applied Math
Sciences Institute, NC
EPSRC Fellow
Head
EPSRC Fellow
Visiting Professor
Visiting Research Scientist
Head
Visiting Professor
Form 100 (2005 W), page 2.1 of 4
University of Bath, UK
U British Columbia
University of Kent, UK
National University of Singapore
University of Bath, UK
U British Columbia
University of Washington
PROTECTED WHEN COMPLETED
Period (yyyy/mm
to yyyy/mm)
Department
2005 /01
Statistics
to
2003/01
2003/06
to
2002/07
2002/12
to
1997/07
2002/06
to
1996/01
1996/06
to
1995/07
1995/12
to
1989/07
1990/06
to
1984/07
1989/06
to
1983/07
1984/06
Mathematical Science
Statistics
Mathematics Institute
Mathematics
Mathematical Science
Statistics
Statistics
Version française disponible
Personal identification no. (PIN)
Family name
4599
Zidek
ACADEMIC, RESEARCH AND INDUSTRIAL EXPERIENCE (use one additional page if necessary)
Position held (begin with current)
Visiting Research Scientist
Visiting Research Scientist
Visiting Research Scientist
Professor
Visiting Research Scientist
Visiting Research Scientist
Associate Professor
Assistant Professor
Form 100 (2005 W), page 2.2 of 4
Organization
Imperial College London
CSIR, South Africa
Imperial College London
U British Columbia
CSIRO, Australia
University College London
U British Columbia
U British Columbia
PROTECTED WHEN COMPLETED
Period (yyyy/mm
to yyyy/mm)
Department
Mathematics
Statistics & Operations
Research
to
1982/11
1983/06
to
1982/07
1982/10
to
1977/01
1977/06
to
1976/07
2004/12
to
1975/07
1976/12
to
1971/07
1972/06
to
1971/07
1976/06
to
1967/07
1971/06
Mathematics
Statistics
Statistics & Applied
Math
Statistics
Statistics
Statistics
Version française disponible
Personal identification no. (PIN)
Family name
4599
Zidek
RESEARCH SUPPORT
Family name and initial(s)
of applicant
Title of proposal, funding source and program,
and time commitment (hours/month)
Amount
per year
Years of
tenure
(yyyy)
List all sources of support (including NSERC grants and university start-up funds) held as an applicant or a co-applicant: a) support held in the
past four (4) years but now completed; b) support currently held, and c) support applied for. For group grants, indicate the percentage of the
funding directly applicable to your research. Use additional pages as required.
a) Support held in the past 4 years
James V Zidek
Likelihood methods and spatial mapping
NSERC
Discovery Grants
106 hours/month
40,000
40,000
40,000
40,000
2002
2003
2004
2005
Environmetrics, likelihood & decision theory
NSERC
Discovery Grants
153 hours/month
86,300
66,299
38,300
36,300
36,300
2006
2007
2008
2009
2010
c) Support applied for
James V Zidek
Form 100 (2005 W), page 3 of 4
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Highly Qualified Personnel (HQP)
Provide personal data about the HQP that you currently, or over the past six years, have supervised or co-supervised.
Personal identification no. (PIN)
Family name
4599
Name
Type of HQP
Training and Status
Zidek
Years
Supervised or
Co-supervised
Title of Project or Thesis
Present Position
Jean-Francois Doctoral
(In Progress)
Plante
Supervised
2004 -
Extensions of the Weighted
likelihood
PhD Student, Statistics, UBC
Yiping Dou
Doctoral
(In Progress)
Co-supervised Dynamic linear modelling of
2004 space-time fields
Zhong Liu
Doctoral
(In Progress)
Co-supervised Combining physical and statistical PhD student, Statistics, UBC
2004 models
Carolyn
Taylor
Res. Associate
Analysis of BC data on lumber
Supervised
2005 - 2005 standards
Programmer Analysis, SCARL,
Statistics, UBC
Howard
Chang
Undergraduate
Co-supervised Environmental risk and Aircare
2002 - 2004 data analysis
PhD Student, Biostats, Johns
Hopkins U
Rick White
Res. Associate
Co-supervised Software development of
2001 - 2004 environmental risk analysis
Programmer analyst, SCARL,
Statistics, UBC
Audrey Fu
Master's
(Completed)
Co-supervised Inference for rainfall extremes
2001 - 2002
PhD student, Statistics, U
Washington
Eugenia Yu
Master's
Co-supervised Analysis of Vancouver airpollution Statistical analyst, St Pauls
2001 - 2002 fields
Hospital
Eugenia Yu
Master's
(Completed)
Co-supervised Analysis of a randomized clinical
2001 - 2002 trial in the presence ...
Statistical analyst, St Pauls
Hospital
Eugenia Yu
Undergraduate
Fairness and effectiveness of
Supervised
2000 - 2001 emission repair $ limits
Statistical analyst, St Paul's
Hospital
Liang Chou
Undergraduate
Co-supervised Survival distribution of vehicle
2000 - 2001 repairs for emission fails
Unclassified UBC student
Xaiogang
Wang
Doctoral
(Completed)
Co-supervised Weighted likelihood
1996 - 2001
Assistant Professor, York
University
Analysis of vehicle emission and
Supervised
2000 - 2000 repair data
Undergrad SFU Actuarial Program
Vivien Wong Undergraduate
Form 100 (2005 W), page 4 of 4
Personal information collected on this form and appendices will be
stored in the Personal Information Bank for the appropriate program.
PROTECTED WHEN COMPLETED
PhD student, Statistics, UBC
Version française disponible
1
James V Zidek
4599
1. Most Significant Research Contributions:
The emerging theory for the relevance weighted likelihood (created with my then PhD student,
Feifang Hu) holds promise. It: (1) provides a framework for development of that theory to
enable data from disparate sources to be combined, allowing prior knowledge to be
incorporated in complex problems where applying Bayesian methods may be difficult. (2)
generalizes nonparametric regression, providing new solutions to old problems there; (3)
provides smoothing approaches in statistical quality control and other areas where smoothing
had not been introduced; Significant recent publication:
Wang, X, and Zidek, JV (2005). Selecting likelihood weights by cross-validation. Ann
Statist. 33, 463-500. Refereed; Funding: NSF, NSERC; Alphabetic author order.
A new approach to bootstrapping, based on estimating equations seems promising because it
circumvents the issue of how re-sampling should be done. Moreover, Kalbfleisch and Hu
extended it in an deep and elegant paper that broadens its domain of application, in particular
to include dependent data. Significant recent publication:
Zidek, JV and Wang, X (2003). Discussion of Hu, F. and Kalbfleisch, J.D. "The estimating
function bootstrap. Can J Statist, 28, 449-499. Non-refereed. Funding: NSERC. Work
author order.
A Health Canada pNEM software development project led to a simulation model for setting air
quality criteria in Canada. It has been redeveloped as a WWW based platform (pCNEM) that
can be accessed and run online for any pollutant for which the internet client has the needed
data. PCNEM can be run to predict sub-population air pollution exposures under hypothetical
regulatory scenarios. Recently McBride, Zidek and Williams show the predictive exposure
distribution to be well calibrated for a group of seniors whose personal exposures were
monitored. Most importantly, Shaddick and Zidek show in a London study (unpublished as
yet) that pCNEM /PM10 forecasted exposures of senior males turns associations between
mortality (cardiovascular and also respiratory) from insignificant to (marginally) significant.
This model generally promises greater power in environmental epidemiological studies.
Significant recent
publication:
Zidek, JV, Meloche, J Shaddick, G, Chatfield, C and White, R (2003). A Computational Model
for Estimating Personal Exposure to Air Pollutants with Application to London's PM10
in 1997. TR 2003-3. Statistical & Applied Mathematical Sciences Instit. Nonrefereed.
Funding: NSF, EPSRC,NSERC. Part 1 has appeared: (2003) Environmetrics, 16, 481493. Work author order. Part 2 to be submitted.
Another important development: a Bayesian theory of optimal design and spatial prediction for
environmental processes. This work led directly to two Health Canada research contracts since
it yields a predictive distribution for a random fields (like air pollution). The contracts
supported a number of research students. As well, it led to a joint EPA cooperative agreement
with a Harvard group on personal exposure models. That agreement also provided substantial
graduate student and Post- doctoral support, as well as an opportunity for interdisciplinary
research. Finally the work led to: (1) a number of speaking invitations (see proceedings articles
below); (2) membership on a tribunal to resolve a dispute on the amount of cleanup needed at
the Rocky Mountain Arsenal, Colorado; (3) membership on a multi-year high-level EPA panel
concerned with ozone air quality standards in the USA; (4) a research monograph (with
associated software) that will appear in late 2005. Significant recent publication:
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James V Zidek
4599
Kibria, G, Sun, L, Zidek, JV and Le, ND (2002). A Bayesian approach to backcasting and
spatially predicting unmeasured multivariate random space-time fields with application to
PM2.5 . JASA, 97, 112-124. Refeered. Funding: Mantech-EPA. Work author order.
Kibria as a PostDoc.
When spatial fields such as those for particulate air pollution are measured as short-term time
aggregates (e.g. hourly), time and space become "inseparable", a problem that did not seem to
have been previously addressed. A method of dealing with it appears in the publication below.
Significant recent publication:
Zidek, JV, Sun, L, Le, ND and Özkaynak, H (2002). Contending with Space-time interaction in
the spatial prediction of pollution: Vancouver's hourly ambient PM2.5 field.
Environmetrics, 13, 595-613. Refereed. Funding: EPA, NSERC. Work author order.
2. Other Research Contributions over the last six years:
Refereed Publications:
Wang, X and Zidek, JV (2005). Derivation of mixture distributions and the weighted
likelihood estimator”. Ann Inst Statistic Math. To Appear. Accepted: Nov 22, 2004.
Refereed. Funding: NSERC. Alphabetical author order.
Zidek, JV, Shaddick, G, White, R, Meloche, J and Chatfield, C (2005). Using a probabilistic
model (pCNEM) to estimate personal exposure air pollution. Environmetrics. To
appear. Accepted: Sep 29, 2004. Funding: EPSRC, NSF, NSERC. Work author order.
Hu, F and Zidek, JV (2004) Forecasting NBA basketball scores using the weighted likelihood.
In Feitschrift for Herman Ruben (Ed Anirban Das Gupta). IMS Monograph Series, 385394. Funding: NSERC. Alphabetical author order.
Le, ND and Zidek, J.V (2005). Statistical Aspects of Environmental Space - Time Process
Analysis. Book to appear. Accepted: Mar 24, 2005. Funding: NSERC. Alphabetical
author order.
Le, ND, Sun, L and Zidek, JV (2002). Spatial Prediction and Temporal Backcasting for
Environmental Fields having monotone data patterns. Can J Statist, 29, 515-690.
Funding: EPA. Work author order.
Zidek, JV, Sun, W and Le, ND(2000). Designing and integrating composite networks for
monitoring multivariate Gaussian pollution fields. Applied Statist, 49, 63-79. Funding:
NSERC. Work author order.
Sun, L, Zidek, JV, Le, ND and Ozaynak, H (2000). Interpolating Vancouver's daily ambient
PM10 field. Environmetrics, 11, 651-663. Funding: EPA, NSERC. Work author order.
Ghosh, M, Zidek, JV, Maiti, T. and White, R. (2004). Weighted likelihoods for the NEF-QVF
family with application to small area estimation. Can J Statist, 32, 139-157. Funding:
NSF,NSERC. Work author order.
Wang, X, van Eeden, C and Zidek, JV (2004). Asymptotic properties of maximum weighted
likelihood estimators. Statist Planning Inference, 37-54. Funding: NSERC. Alphabetical
author order.
van Eeden, C and Zidek, JV (2004). Combining the data from two normal populations to
estimate the mean of one when their mean difference is bounded. J Mult Anal, 88, 19-46.
Funding: NSERC. Alphabetical author order.
Hu, F and Zidek, JV (2002). The weighted likelihood. Can. J Statist. 30, 347-371. SSC Gold
Medal address. Funding: NSERC. Alphabetical author order.
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James V Zidek
4599
van Eeden, C and Zidek, JV (2001). Combining sample information in estimating ordered
normal means. Sanhkya. 51, 277-284. Correction note: Statist Probab Lett 57, (2002).
Funding: NSERC. Alphabetical author order.
van Eeden, C and Zidek, JV (2001). Estimating one of two normal means when their mean
difference is bounded. Statist Probab Letters, 51, 277-284. Funding: NSERC.
Alphabetical author order.
Hu, F and Zidek, JV (2001). The relevance weighted likelihood with applications. Empirical
Bayes and Likelihood Inference. (Eds S.E. Ahmed and N. Reid.), New York: Springer
Verlag. Book chapter. Funding: NSERC. Alphabetical author order.
Hu, F., Rosenberger, W. and Zidek, J.V. (2000). The relevance weighted likelihood for
dependent data. Metrika, 51, 223-243. Funding: NSERC. Alphabetical author order.
Li, K, Le, ND, Sun, L and Zidek, JV (1999). Spatial-temporal models for ambient hourly
PM10 in Vancouver. Environmetrics, 10, 321-338.
van Eeden, C and Zidek, JV (1999). Minimax estimation of a bounded scale parameter for
scale-invariant squared-error loss. Statist. and Decisions, 17, 1-30
Non refereed publications:
Shaddick, G and Zidek, JV (2005). Results of using a probabilistic model to estimate personal
exposure to air pollution on a study of the short term effect of PM10 on mortality. Paper
no. ISEE/230. Accepted for presentation at the 17th Conference of the International
Society for Environmental Epidemiology. Non-refereed. Funding: NSERC. Alphabetical
author order.
McBride, S, Zidek, JV and Williams, R (2004). Assessing a Computer Model for Predicting
Human Exposure to PM_2.5. Poster accepted for and presented at the 2004 Annual
Meeting of the International Soc for Exposure Analysis.
Zidek, JV, Meloche, J, Le, ND and Sun, L. (2000). Combining statistical and computer models
for health risk assessment (exposure analysis). Statistical Modelling, Proceedings of the
15th International Workshop on Statistical Modelling: New Trends in Statistical
Modelling. (Eds. V. Núñez-Antón, E. Feffeirra). Bilbao:Universidad del Pais Vasco, 95106. Non-refeered. Funding: NSERC; Work author order.
Le, ND, White, R and Zidek, JV (1999). Using spatial data in assessing the association
between air pollution episodes and respiratory health. Statistics for the Environment 4:
Statistical Aspects of Health and the Environment. 117-136.
Zidek, JV (1999). Measuring and Modelling Pollution Exposure for Risk Analysis (with
discussion). Proceedings Novartis Foundation #220. 105-121.
Zidek, JV (1999). Discussion of Lavine, M.. Another look at conditionally Gaussian random
fields. Bayesian Statistics 6 (Eds. Berger, J.O, Bernardo, J.M, Dawid, A.P. and Smith,
A.F.M.). Oxford: Oxford University Press.
Le, ND, Sun, L and Zidek, JV (1999) Discussion ofGaudard, N., Karson, M, Linder, E. and
Sinha, D. "Bayesian spatial prediction." J Environmental Ecological Statist, 6, 147-171.
Submitted or under revision:
Zidek, J.V., Meloche, J. Shaddick, G., Chatfield, C. and White, R. “A Computational Model
for Estimating Personal Exposure to Air Pollutants with Application to London's PM10
in 1997.” 25pp. Under Revision, Jul 2005.
Chang, H., Fu, A.Q., Le, N.D. and Zidek, J.V. “Designing environmental monitoring networks
for measuring extremes.” 29pp. Environmetrics. Revised and Resubmitted Aug 2005.
4
James V Zidek
4599
Dawid, AP, Stone, M and Zidek, JV “Warring infinities: a critique based on Chapter 15 of ET
Jaynes’s “Probability Theory: The logic of Science.” 10pp. Under revision, Jul 2005.
Fu, A.Q., Le, N.D. and Zidek, J.V. “A statistical characterization of simulated Canadian annual
maximum rainfall field.” 28pp. Under revision Jul 2005.
Chang, J., Zidek, J.V. and Stewart, S.J. “Models for predicting full-duration carbon emissions
from fast-pass IM240 “ 25pp. Unpublished manuscript. To be submitted.
3. Other Evidence of Impact and Contributions
Awards
1976 Elected Fellow, Institute of Mathematics Statistics
1979 Elected Member, International Statistical Institute
1988 Elected Fellow, American Statistical Association
1987/88 President, Statistical Society of Canada, 1987- 88
1989/90 Izaak Walton Killam Senior Fellowship for
1999 9th Eugene Lukacs Symposium Distinguished Service Award,
2000 Invited Presidential Address, Statistical Society of Canada
2000 Gold Medal, Statistical Society of Canada
2000 Distinguished Achievement Medal, Environmental
Statistics Section of the American Statistical Association
2001 Izaak Walton Killam Research Prize
2003 Hunter Lecture, International Environmetrics Society
2003 Elected Fellow, Royal Society of Canada
2004 Plenary Lecture, South African Statistical Association
2005 Honorary Membership Statistical Society of Canada
Noteable Panels and Review Committees
2005 Review Committee, Department of Statistics, Oxford University
2005 - Scientific Advisory Committee, National Center for Atmospheric Research,
Boulder Colorado
2005 - Clean Air Scientific Advisory Committee for Ozone, Environmental Protection
Agency, USA
Editorships:
2005-:
Associate Editor, JASA
1998-2001:
Associate Editor, Canadian Journal of Statistics
1998Chapman&Hall/CRC: Advisory Editor in Statistics and Probability
1999Wiley: Editor for Encyclopedia of Environmental Statistics
Invited presentations since 1999:
1999 6 invited talks omitted to save space
2000 5 invited talks omitted to save space
“The weighted likelihood". Gold Medal address, Statistical Soc of Canada, SFU, Jun.
2001 3 invited talks omitted to save space
“Approaches the Monitoring Network Design." SPRUCE Workshop on Environmental
Design, Estoril, Portugal, Mar.
“The weighted likelihood". Gold Medal address, Statistical Soc of Canada, SFU, Jun.
“Space-time interaction issues in the spatial prediction of pollution fields", European Meeting
of Statisticians, Funchal, Madiera, Aug.
“Does air pollution cause ill-health?" Inaugural Mini-symposium for BIRS, Banff, Sep.
5
James V Zidek
4599
“Accounting for time-activity patterns in human exposures to air pollution: a computer
modeling approach.” Dept Mathematics & Statistics, U Lancaster, Oct
2002
“Uncertainty”. Symposium in Honor of Contance van Eeden’s 75th Birthday. Montreal, May.
“Designing for extremes”. Ann Meeting, Statist Soc of Canada. Hamilton, May.
2003
“Uncertainty.” Institute Statistics & Decision Sciences, Duke U, Jan
“A computer model for predicting human exposure to air pollutants in environmental risk
assessment.” Statistical & Applied Mathematical Sciences Instit, Jan
“Uncertainty” Dept Statistics, U of Florida, Apr
“Designs for Predicting the Extremes of Spatial Processes.” 2003 ENAR Spring Meeting.
Tampa, FL, Apr
"Modelling Environmental Space-Time Series." Hunter Lecture, The International
Environmetrics Soc 2003. Johannesberg, Nov
2004
“Uncertainty and Information.” Institute of Mathematics, Federal University of Rio de Janiero,
Feb
“Current directions in modelling environmental space time processes.” 7th Encontro
Brasileiro de Estatistica Bayesiana, Sao Carlos, Brazil, Feb
“Physical vs Statistical Modelling: Towards a Reconciliation." Joint SFU – UBC colloquium,
Oct
“A Statistical Characterization of a Simulated Canadian Annual Maximum Rainfall Field.”
Institute of Martime Technology, Simon’s Town & University of Orange Free State,
South Africa, Nov
“Uncertainty”, University of Cape Town, Nov
“Accounting for Time-Activity Patterns in Estimating Human Exposures to Air Pollution for
Health Risk Analysis”, Medical Research Council, Cape Town, Nov
"Physical vs Statistical Modelling: Towards a Reconciliation." Plenary Address, Statistical
Association of South Africa, Nov
2005
“Measuring and Modelling Space-Time Processes for Environment Risk Assessment.” One
Day Workshop, Biostatistics Section, Statistical Society Of Canada Annual Meeting,
Saskatoon. Jun
"Estimating exposure to and health impacts of PM10 in London, 1997 using a computational
model." WNAR Meeting. Fairbanks, Alaska, June
4. Delays in Research Activity
My second five year term as Head of Statistics cut into my research time during the 1997- 2002
as did the research monograph begun in 2002 and now to appear.
5. Contributions to the Training of Highly Qualified Personnel.
Following my Headship, I was granted a year’s administrative leave so I delayed taking on any
on new graduate students until I returned. Our graduate student population has grown
dramatically recently, so have opportunities for training especially PhDs.
Undergraduates (Chou, Yu and one unnamed) were involved with massive (BC
AirCare) SQL databases and learned how to handle. Valuable training for modern apps.
Investing in people, discovery and innovation
Investir dans es gens, la découverte et l'innovation
APPENDIX C
Description of Applicant's Activities
(Form 100)
Complete this appendix (i) if you hold an academic appointment at a Canadian university but are not a full,
associate or assistant professor, or (ii) if you hold a part-time academic appointment at a Canadian
postsecondary institution.This would include applicants or co-applicants holding an adjunct professor or a
professor emeritus position and all co-applicants from an eligible Canadian college. This information is
collected to provide peer reviewers with additional information on your activities at the postsecondary
institution and at your main place of employment (if applicable).
Family name
Given name
Zidek
James
Date
2006/5/2
Initial(s) of all given names Personal identification no. (PIN)
V
4599
DESCRIPTION OF ACTIVITIES AT CANADIAN POSTSECONDARY INSTITUTION
Outline the nature of your 1) research, 2) teaching, 3) training, 4) administrative and 5) other activities. Each of these aspects must be
addressed. Indicate the time typically spent on location at the postsecondary institution on each of these activities (e.g., 1 day every
week, 2 weeks every 4 months).
1) My research program has two components: (a) concerns the weighted likelihood estimator and the
properties of the estimators it produces; (b) concerns the environmental space-time proceses, their
measurement, modelling and mapping.
2) I have no teaching duties
3) I have three PhD students that are not expected to complete their theses for at least 3 years
4) I am am an Editor of the ChapmanHall/CRC textbook series and serve on the Advisory committee
for UWashington's PM Center. I spend 100% of my time at UBC, save for National and International
meetings.
DESCRIPTION OF ACTIVITIES AT PLACE OF EMPLOYMENT OTHER THAN CANADIAN POSTSECONDARY
INSTITUTION (if applicable)
Place of employment other than Canadian postsecondary institution, including self-employment
I do not hold a position
outside a Canadian
postsecondary institution
Outline the nature of your research program and other activities at your other place of employment. Also describe the relationship
between your research program at this organization and the proposed research. Refer to the institution's involvement in research
and development, if possible.
I am a Special Government Employee, serving on a panel for the US Environmental Protection Agency
for 2- 5 years, the goal being to recommend new US air quality criteria for ozone. The work requires
about 2 weeks per year of my time.
Form 100, Appendix C (2005 W)
PROTECTED WHEN COMPLETED
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