Corey Chivers

PhD candidate in the Leung Lab

McGill University, Department of Biology

Invasion Biology Modeling

My PhD research focuses on the development of forecasting, risk, and impact assessment models of non-native species. By combining computational simulations with both biological and sociological data, this research aims to provide decision support to resource managers and policy makers.

With an emphasis on uncertainty quantification through the construction of Bayesian models, I analyze the implications of various human and biological factors on the spatial spread of fresh water invasive species, including: 1) environmental and demographic stochasticity, 2) dispersal network structure, and 3) human behavioural feedbacks to policy decisions. Together, this research provides novel insights into both ecological processes and environmental policy.

Research

  • Incorporating multiple levels of stochasticity and epistemic uncertainty using hierarchical Bayesian models to forcast invasions.
  • General state-space modeling of spatio-temporal processes.
  • Econometric models
  • Software (FOSS)

  • Corey Chivers (2013). rvmapp: Validation Metric Applied to Probabilistic Predictions. R package version 0.1-1.Pre-released.
  • Corey Chivers (2012). MHapaptive: General Markov Chain Monte Carlo for Bayesian Inference using adaptive Metropolis-Hastings sampling. R package version 1.1-8.
  • Collaborative Groups

  • NCEAS The National Center for Ecological Analysis and Synthesis (Non-Native Forest Pests and Pathogens Working Group)
  • CAISN Canadian Aquatic Invasive Species Network
  • Publications

  • Chivers, C., & Leung, B. (2014) Modelling responses to management intervention for controlling the spread of freshwater invasives. in prep.
  • Chivers, C., & Leung, B. (2014) The probability of establishment and spread of biological organisms: Issues of uncertainty, detection and presence-only data. in review.
  • Chivers, C., Leung, B., & Yan (2013) Probabilistic predictions in ecology and their validation. in review.
  • Low-Decarie, E., Chivers, C. & Granados, M. (2013) Rising complexity and falling predictive power in ecology. in review.
  • Bradie, J., Chivers, C. & Leung, B. (2013) Importing risk: quantifying the propagule-pressure establishment relationship at the pathway level. Diversity and Distributions. doi:10.1111/ddi.12081
  • Chivers, C & Leung, B. (2012) Predicting invasions: Alternative models of human-mediated dispersal and interactions between dispersal network structure and Allee effects. Journal of Applied Ecology, 49: 1113-1123. doi:10.1111/j.1365-2664.2012.02183.x
  • Aukema JE, Leung B, Kovacs K, Chivers C, Britton KO, et al. (2011) Economic Impacts of Non-Native Forest Insects in the Continental United States. PLoS One 6(9): e24587. doi:10.1371/journal.pone.0024587
  • Selected Presentations

  • Chivers, C. (2013) From Whale Calls to Dark Matter: Competitive Data Science with R and Python. Montreal Python. (Montreal, QC. June, 2013)
  • Chivers, C. & Leung, B. (2013) Implications of uncertainty: Bayesian modelling of aquatic invasive species spread. International Conference on Aquatic Invasive Species. (Niagara Falls, ON. April, 2013)
  • Chivers, C. (2013) Future Avenues for Open Data. Open Data Exchange. (Montreal, QC. April, 2013)
  • Chivers, C. (2013) Predictive Ecology and Management Decisions Under Uncertainty. McGill BGSA Organismal Seminar Award. (Montreal, QC. January, 2013)
  • Chivers, C. & Leung, B. (2011) Interactions between dispersal network structure and Allee Effects. Quebec Centre For Biodiversity Science. (Montreal, QC. September, 2011) (french)
  • Posters

  • Chivers, C., Guillemette, J., Ragan, K. (2012) Predictive Modelling of Student Grades and Comparisons with Conceptual Gains. The Society for Teaching and Learning in Higher Education. (Montreal, QC. June, 2012)
  • Chivers, C. (2009) Why Aren't We All Bayesians? Paris Interdisciplinary PhD Symposium. (Paris, France. December, 2009)
  • Teaching

  • T-PULSE Teaching Fellowship
  • BIOL645 Biodiversity Field Course (Lecturer & Section Designer)
  • BIOL202 Introduction to Genetic Analysis (TA)
  • BIOL373 Biometry (Guest Lecturer & TA)
  • BIOL200 Molecular and Cell Biology (TA)
  • Facilitated Workshops
  • Hackathons

  • Hacktaville Prize for most interesting data mashup. Project: Velobstacle.
  • HackReduce Montreal First place team for Bixi data visualization
  • MOOCs

  • Stanford CS184 Startup Engineering
  • Intro to Hadoop MapReduce Coursera
  • Media Coverage

  • New York Times In This Battle Arena, Warriors Are Armed With Algorithms
  • Wall Street Journal Do the Numbers Behind Prism Add Up? (pdf).
  • LA Times More global trade means more forest pests
  • Washington Post Invasive insects are growing threat to trees, forests
  • New York Times The Toll From Tree-Boring Pests
  • Montreal Gazette McGill grad student visualizes Bixi station activity and Bike accidents visualized over time
  • Wall Street Journal Taxpayers Feel Bite From Invasive Species
  • Science Daily Local Government, Homeowners Paying Price for Non-Native Forest Insects, U.S. Study Finds
  • Scientific American Invasive Insects Take Big Cash Bite
  • BBC P-value fallacy on More or Less
  • Quartz Simple math shows why the NSA's Facebook spying is a fool's errand
  • Popular Science A Concise History Of The NSA's Online Spying Program PRISM
  • Editorial and Review Service

  • The Performance of Open Source Applications - Technical review.
  • Reproducible Research with R & RStudio. CRC Taylor & Francis Press - Peer review (book).
  • Ecological Applications - Peer review
  • Trend in Ecology and Evolution - Peer review
  • Biological Invasions - Peer review
  • Journal of Applied Ecology - Peer review
  • Technical Experience

  • Highly proficient in Linux OS and associated data manipulation tools (sed, grep, awk)
  • Expert level R programming for predictive modelling and data visualization
  • Skilled in both low level programming (c++) and scripting languages (Bash, python)
  • Proficient with open source Geographic Infomation Systems (GIS) QGIS and GRASS.
  • Experience with SQL and No-SQL (couchdb) databases
  • Experience using scalable High Performance Computing (HPC) resources including CLUMEQ and AWS
  • Experience using Big Data technologies including MapReduce using Appache Hadoop
  • Experience with version control (Git)

  • hacker emblem