Methods in Experimental Ecology II (PCB 6468)

Course Information

Time: Mondays and Wednesdays (11:30-12:20) & Thursdays (9:00-11:50)
Room: Bio 305
Instructor: Pedro Quintana-Ascencio
TA: Federico Lopez Borghesi

Description

This course will assist graduate students to design, analyze and interpret their own experiments and observations and establish a research program in ecology and other biological fields. This course reviews basic analytical tools needed to collect, organize and interpret ecological data in a critical way. It is based on the revision of case studies illustrating frequent research problems and the discussion of potential solutions. As much as possible, several alternative approaches are evaluated and compared. This class complements courses on basic statistics and is directed to beginning graduate and senior undergraduate researchers. The course confronts concepts in experimental design, execution and analysis as a tool to improve ecological research.

Syllabus 2018

Materials

Extra Material (from Old Methods 1)

Session	Topic	PDFs	Scripts and Data	Excercises
I	Class Presentation			Exercise 0 Ex0 Chart
				Extra Credit
II	Assumptions	Assumptions Demo	Assumptions Script Hypericum Data	Exercise 1 EX1 data
III	Analysis Frameworks	Frameworks Demo	Frameworks Script Frameworks Data ants_jags.R	Exercise 2 EX2 data
IV	Analysis of Averages	Averages Demo	Averages Script (jags) mean model Inform mean model diffused Hypericum Data pop mean data	Exercise 3
V	Logistic Regressions	Regression Demo Low-Decarie et al.	Logistic Regression Script Logmodel_1 Logmodel_2 Hypericum Survival Data	Exercise 4 Ex4_data
VI	Non-Linear Relationships	Non-Linear Relationships Demo Ellison 2004 Gordon et al. 1998 Morris et al. 2015	wg_priors (script) ** wire_grass_in_Jags grasses_inf_int grasses_dif_int wg_priors (data) wg_data	Exercise 5
VII	Count Data	Count Data Demo OHanlon et al. 2014	Mantis R (script) Mantis Jags – Poisson (script) Mantis jags -Neg Binom (script) Mantis (data)	Exercise 6 Exercise 6 Data
VIII	Linear Mixed Models	Linear Mixed Models Demo	LMM (script) LMM intercept (script) LMM intercept and slope (script) Hypericum Data	Exercise 7 Exercise 7 Data
IX	Model Selection of Mixed Models	Mixed Model Selection Demo	Mixed Model Selection (script) Model_w_year (script) Comparison Bayesian/Frequentist Hypericum Data	Exercise 8 Nuzzo 2014 Wasserstein & Lazar 2016
X	Model Selection of Mixed Models Binary	Mixed Model Selection Binary Demo	Mixed GLM vR (script) Mixed GLM vR Bayes (script) Model_w_year binary (script) Model_w_year binary intercept (script) Hypericum Data Chaos(EXTRA)	Exercise 9 Exercise 9 Data
XI	Zero Inflated Models	Zero Inflated Models Demo	Zero Inflated (script) Data for Demo Martin et al. —————— Zero Inflated (with Bayesian) bayesian zero inflated poisson bayesian zero inflated neg binom	Exercise 10 Data for Exercise 10
XII	General Additive Models	GAMs Demo	GAMs (script) Data for Demo	Exercise 11 Data for EX11 ISIT file Gillibrand et al. 2007
XIII	Non-linear Count Data	Non Linear Counts Demo	Non Linear Counts (script) Data for Demo	Exercise 12

** File is in .doc format and has to be copied into an R script