2006 Summer Graduate Program
This year the program will focus on Ecology and Evolution. The program leaders are Kate Calder and Yuan Lou. The first week is spent in a tutorial, which combines morning lectures with active learning laboratories in the afternoon. The following two weeks are spent working on guided team projects and participating in a mini-conference to share project results. The program is meant primarily for graduate students; college instructors and qualified undergraduates will also be considered.
The 2006 Summer Program dates are July 17 - August 4.
Topics:
- Effects of spatial heterogeneity on invasions of rare species
- Patterns of multiallelic polymorphism maintained by migration and selection
- Evolution of ranges of species
- Spatial modeling of trends in species abundance
- Modeling wild bird population dynamics from citizen surveys
- Constructing the progression pathway from normal tissue to carcinoma
Week 1 |
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| Monday, July 17 | |||
| 9:00-11:00am | Yuan Lou: Math tutorial - PDF | ||
| 1:30-3:00pm | Paul Tian: Computer simulation | ||
| 3:30-4:30pm | Greg Singer: General biology/molecular biology - PDF | ||
| 5:00-6:30pm | Happy Hour: Wendell's Alumni Grille | ||
| Tuesday, July 18 | |||
| 9:00-10:00am | Yuan Lou: Math tutorial - PDF | ||
| 10:30-11:30am | Kate Calder: Statistics tutorial - PDF | ||
| 1:30-3:00pm | Hong Fei Li: Statistical computing | ||
| 4:00pm | Wetlands Tour | Wednesday, July 19 | |
| 9:00-10:00am | Yuan Lou: Math tutorial - PDF | ||
| 10:30-11:30am | Kate Calder: Statistics tutorial - PDF | ||
| 1:30-3:00pm | Andrew Nevai: Computer simulation | ||
| 3:15-4:15pm | Dennis Pearl: Statistical phylogenetics | ||
| 4:30-5:30pm | Tao Shi: Remote sensing data | Thursday, July 20 | |
| 9:00-10:00am | Yuan Lou: Math tutorial - PDF | ||
| 10:30-11:30am | Kate Calder: Statistics tutorial - PDF | ||
| 1:30-3:00pm | Hong Fei Li: Statistical computing | ||
| 3:30-5:30pm | Alfred Cheng: Epigenetic alterations in gene regulation and chromatin landscaping using ChIP-chip or ChIP-PCR techniques - PPT Michael Chan: Cancer biology and laboratory techniques - PPT Pearlly Yan: DNA methylation and data types and heritability of this mark in cancer progression - PPT |
Friday, July 21 | |
| 9:00-10:00am | Yuan Lou: Math tutorial - PDF | ||
| 10:30-11:30am | Kate Calder: Statistics tutorial - PDF | ||
| 1:30-2:30pm | Partha Srinivasan: Computer simulation | ||
| 3:00-4:30pm | Presentation of projects by group leaders | ||
| 4:30-4:40pm | Students will rank their top four projects | Monday, July 24 | |
| 9:00am | Project assignments | ||
Team projects: Friday, August 4
Project 1: Effects of spatial heterogeneity on invasions of rare species
Project Leader: Andrew Nevai
Presentation: PPT1 PPT2
Partcipants: Tucker Gilman, Katy Greenwald, Vishu Guttal, Rich Hambrock, and Will Newton
The evolution of disperal has been one of the central topics in recent theoretical studies of population dynamics. The source-sink model assumes that individuals disperse at fixed constant rates, and it predicts that the selection is for slow dispersal. Part of the project will involve studies of this prediction for two or more competing species. The rest of this project will investigate in a logistic model the effects of migration and spatial heterogeneity of the environment on the total population size at equilibrium of a single species, and its applications to ecological invasions in the context of a two-species Lotka-Volterra competition model with migration. Evolution of conditional dispersal will also be addressed.
Project 2: Patterns of multiallelic polymorphism maintained by migration and selection
Project Leader: Partha Srinivasan
Presentation: PPT
Partcipants: Anthony D'Orazio, Andre De Laire, Richard Gejji, Namyong Lee, and Ellen Peterson
The goal of this project is to investigate the spatial patterns in gene frenquencies due to the joint action of migration and selection. We'll first study the conditions for the maintenance of polymorphism at a single diallelic locus under a wide variety of migration schemes in discrete-space, discrete-time models. The rest of the project is concerned with a continuous-space, continuous-time model which is sometimes biologically more appropriate and generally yields more transparent and explicit results for the evolution of the gene frequencies. Discrete-time, continuous-time models will also be discussed.
Project 3: Evolution of ranges of species
Project Leader: Paul (Jianjun) Tian
Presentation: PPT
Partcipants: Edgar Diaz, Xiaojie Hou, Etsuko Nonaka, Joaquin Rivera, and Jaffar Ali Shahul Hameed
Why do range boundaries sometimes lie at arbitrary points in the habitat? From an evolutionary perspective, the peripheral populations receive gene flow from the center of the species' range, which is adapted to the conditions at the periphery where the conditions are typically tougher. Peripheral populations are thus trapped by gene flow into acting as demographic sinks, preventing the range from expanding (Mayr 1963). The project will study recent models that describe both the evolution and demography of species distributed in space, and investigate whether the range limits can be determined by a balance between adaptation and gene flow.
Project 4: Spatial Modeling of Trends in Species Abundance
Project Leader: Hongfei Li
Presentation: PPT
Partcipants: Smriti Bhotika, Ben Chan, Esprit Heestand, Manish Madan, and Hongyan Zhang
Data collected from monitoring programs are an essential component of many applied ecological studies. These monitoring programs often have multiple objectives that include both monitoring trends and estimating abundance. In addition, exploring the effects of covariates on population dynamics is often an important component of a statistical analysis of such data.
The objective of this project is to assess the impact of the Exxon/Valdez oil spill that occurred in 1989 in Prince William Sound (PWS), Alaska, on the population of harbor seals in the region using a dataset of counts of harbor seals at 12 haulout sites in eastern and central PWS. For each site, the number of harbor seals was counted 7-10 times each year from 1990-2002. The counts were determined visually (with the aid of 7-power binoculars), from a single-engine fixed-wing aircraft (Cessna185) at altitudes of 100-300m. Typically, flights were conducted from two hours before low tide to two hours after low tide, and all sites were observed during each flight. Occasionally, poor weather or a rapidly rising tide prohibited data collection at certain sites.
Workshop participants will develop a statistical model to explore changes in the number of observed harbor seals in the region following the oil spill. Using a hierarchical Bayesian approach, the primary objective of the statistical analysis is to provide insight into the underlying mechanisms driving the temporal and spatial variation in population size. Specifically, the modeling objectives are: (1) to estimate trends at individual sites; (2) to estimate trends in the study area as a whole; and (3) to estimate the effects of covariates on seal counts.
Project 5: Modeling Wild Bird Population Dynamics from Citizen Surveys
Project Leader: Shannon LaDeau (presented by Kate Calder)
Presentation: PPT
Partcipants: Margaret Pelosa, Aparna Sathyanarayan, Nat Seavy, Hu Wei, and Richard Yamada
Understanding spatio-temporal population dynamics is fundamental to monitoring wildlife response to environmental challenges such as urbanization and invasive pathogens. Annual census data collected by "citizen scientists" provide the greatest temporal and spatial scope by which to evaluate populations and perturbations. However, these data present significant challenges to classical statistical analyses. The objective of this project is to explore population dynamics for species of wild birds and assess their response to an emergent pathogen. The North American Breeding Bird Survey (BBS) monitors over 400 species along more than 3500 designated routes (39.4 km) across the United States and Canada. Censuses are conducted during the breeding season, when birds are most visually and vocally distinctive. Changes in observer ability over time and among individuals, as well as incomplete coverage of all routes each year, introduce important uncertainty in these data.
West Nile virus is an invasive pathogen that spread rapidly through-out the contiguous United States following introduction into New York City in 1999. Although the virus has caused several severe epizootics and results in high mortality rates in lab challenges, little is known regarding its population-level implications for wild birds.
Workshop participants will develop a statistical model to explore historical count data for BBS bird species counted at routes in several Mid-Atlantic States. Using a hierarchical Bayesian approach, the primary objective of the statistical analysis is to provide insight into the underlying mechanisms driving the temporal and spatial variation in population size. Specifically, the modeling objectives are: (1) to estimate regional and local trends prior to West Nile virus introduction; (2) to identify effects of West Nile virus on individual species and, (3) to predict missing data and future population sizes.
Project 6: Constructing the progression pathway from normal tissue to carcinoma
Project Leaders: Dustin Potter and Pearlly Yan
Presentation: PPT
Partcipants: Flor Espinoza, Yu Liu, James Sharpnack, and Ying Wang
A new and rapidly evolving area of study in gene regulation in cancer development and progression is de novo DNA methylation. This form of epigenetic modification is particularly useful in mapping the landscape of different tumor types, stages, and aggressiveness because of its heritability and stability. In this study we will develop techniques for determining informative methylation signatures from high-throughput methylation microarrays of solid tumor samples. The signatures will subsequently be used in combination with tumor/patient phenotypic information to develop progression models for the studied tumors. The recently developed heritable clustering algorithms will be used to construct the progression models.
