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Performing a population viability analysis from data students collect on a local plant

During two lab periods, students collect demographic data on perennial plants and then use these data in a matrix model to perform population viability analyses. During the first lab, students tag and record data on individual plants in the field. During the second lab, students compile these data to build transition matrices and then use R to run simulations. In the first year that instructors run this experiment, simulated field data of subsequent years is used to complete the classroom exercises. In subsequent years, students use real data from previous years. No prior experience with R is necessary.
Cumulative Rating: This resource has a 4 star rating (based on 1 response)
Primary or BEN resource type
Secondary resource type
General Biology Core Concepts
Discipline Specific Core Concepts
Life science discipline (subject)
Keywords Conservation biology, demography, extinction, life history, plant ecology, population ecology
Intended End User Role
Educational Language
Pedagogical Use Description This exercise could be performed by majors or non-majors in intro or upper division college courses or in pre-college environments, although the skills taught might be most relevant to college majors. This exercise is easily transferable across geographies and different plant species. Students with physical disabilities may encounter challenges in the field work portion of the lab depending on access to the chosen field site.
Primary Author Controlled Name
Primary Author Affiliation Hampshire College
Primary Author email
Secondary Author Name(s) Sydne Record
Secondary Author Affiliation(s) Harvard University, Harvard Forest
Secondary Author Email(s)
Submitter Name Teresa Mourad
Submitter Email
Rights Copyright is held by author.
Date Of Record Submission 2014-06-02

Resource Comments

Subject: Comment On: Performing a population viability analysis from data students collect on a local plant
Posted By: Kevingeedey
Date Posted: 2016-05-24 18:50:10
Institution/institution type: Augustana College, Rock Island Illinois (residential liberal arts college)

Course/Course format: General Ecology (Junior and senior biology and environmental studies majors, does not count towards general education requirements).

What I hoped to accomplish with this module was to give students an opportunity to apply demographic models in a more real world setting, and see how those models can inform management decisions. As a secondary objective, I wanted to give students a chance to work with a stochastic model, rather than the deterministic models I have traditionally used in this class.

I had not used matrix-based models in this class before, so I also spent about a half hour at the beginning of lab working through the example on page 6 of the Charney and Record module.

Unfortunately, I experienced some difficulty fully implementing this module. My lack of experience with R proved to be a barrier.

The students loved the fieldwork aspects of the lab, and collecting the data and getting students to enter the data on google docs was straightforward. Further, the students noticed lots of variation in petal number in the population, and this got them thinking about the possible fitness impact of petal number as well as asking good ecological questions about this trait, for example, do large plants also have more petals? Any time students are provoked to ask good questions I feel it is a great day. The module was very successful on that level.

However, I was not able to get the R script I was supposed to run to simulate next year’s data to run (PVA_instructor_script-singleyear.R). The sample data the module authors provided ran just fine, but I could not get my file to work. More familiarity with R would have helped here, as it is likely that some small format issue was the barrier.

The students were still excited about the project, though, so I came up with some simulated data for next year based on crude back-of-the–envelope calculations assuming that the current data represented a stable stage distribution. I practiced using the student R scripts in my office, and the simulations ran perfectly.

Unfortunately, of the twenty-one computers in the classroom, only two or three were able to run the scripts successfully. Error messages popped up, and without R experience, I was not able to troubleshoot the simulation or diagnose what went wrong. Sometimes if students just exited R and started over, the script worked, which suggested user error on our part, but mostly we would just hit the same errors repeatedly. After 40 minutes, I decided we needed to move on.

Wanting to salvage more from the experience, I used excel to create a deterministic matrix model (Chapter 14 in Donovan and Welden Spreadsheet exercises in Ecology and Evolution, 2002 Sinauer and associates press), and I asked students to prepare a lab report using our data and entering different parameter values in this excel based model. This worked reasonably well, but lacked the more realistic element of the stochastic model in the R based module.

On the plus side, the variation in petal numbers became the basis for a good, engaging, student project. Further, the lab reports based on the excel-based model showed that students successfully got the connection between stage based survival, fecundity, and the viability of the population. While students were initially surprised that changing the fecundity of different stages by the same amount had different population impacts, most reasoned out the connection with survivorship and the potential conservation applications of this connection. This all felt like a success to me.

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