Population size, or the abundance of organisms in a study site, is the most fundamental of the primary demographic statistics. In this lab you will apply a simple mark-recapture technique to estimate population size in a population of frogs and use statistics to quantify your confidence in the estimate.
Chapter 7.1 Lockwood and Schneider.
Students should be able to
Explain the mathematical methodology for estimating population size in nature by means of mark-recapture techniques
Perform a simulation to estimate the number of frogs in a population and evaluate the reliability of estimates.
Estimating the abundance of organisms, especially in naturally occurring populations, is a fundamentally important activity in ecological research. An accurate census informs us of changes in population size due to recruitment (births), mortality (deaths), and migration. Reliable estimates of population abundance are also at the core of managing natural resources, protecting endangered species, and mitigating environmental impacts of habitat loss to residential, commercial, or industrial uses.
There are many ways to perform a population census, each method having benefits for particular scenarios as well as underlying assumptions about the study organism. Smaller areas can be carefully sampled using the quadrat method, which works well for sessile or slowly moving organisms. Surveys or transects, meanwhile, can be employed to measure larger organisms and larger areas. In this study, we will use a third type of census method known as “mark-recapture” that’s used to study highly mobile organisms like fish, birds, and mammals.
Mark-recapture techniques allow ecologists to track movement of individuals in space and in time. In its simplest form, this type of study requires a pair of surveys. On the first survey, ecologists capture, mark, and release individuals back into the population. On the second survey, which could be the next day or the next year(s) depending on the study, ecologists capture another set of individuals from the population to determine the proportion that are marked. The proportion of recaptured marked individuals is then used to estimate population size. Ecologists can also use statistics to measure their confidence in the estimated population size.
The type of “mark” in these studies can vary depending on the species. It might a bracelet (bird banding), a collar (wolves), an ear clip (antelope, deer), a fin clip (fish), a paint dot (insects), or a biodegradable dermal injection (salamanders). For some species, a radio tag can be used to continuously track location (white sharks, mountain lions). Still for other species, digital photographs and automated image analysis of fin scars (whales) or pigment patterns (cheetahs) can be used like fingerprints to identify and track individuals. The most important aspect of any mark is that it doesn’t affect the organism’s chances of growth, survival, or reproduction. For example, a large bright tag might make an individual more conspicuous to its predators, less likely to attract a mate, or more likely to be recaptured by scientists.
Data from mark-recapture experiments are so important that researchers continue refining analytical techniques to maximize the information yield from mark-recapture data (Lebreton et al., 1992; Schwarz and Seber, 1999; Schtickzelle et al., 2003). The Petersen method, also known as the Lincoln index (Haag & Tonn, 1998), is what we’ll use in this activity. It’s the easiest of the mark-recapture census methods to perform because it is based on a single episode of marking and recapturing individuals. The important assumptions of the Petersen method are:
The population being sampled is closed (no births/deaths/migration) so that population size remains constant throughout the sampling period.
Every individual has the same chance of being caught; in other words, sampling is random.
Marks are not lost in the interval between mark and recapture.
Population estimation with the Petersen method is focused on solving for N in the following equation:
M/N = R/S
where
M = number collected and marked in first sample
N = total population size
S = size of second sample
R = number of marked organisms in second sample (recaptured)
For example, let’s say 50 juvenile frogs are captured, marked (M), and released back into a pond. Several days later, 30 are captured (S for second capture), 10 of which are marked (R for recaptured). To estimate total population size (N),
M/N = R/S
N = (M x S) / R
N = (50 x 30)/10 = 150
In this example, the estimate of frog population size is 150. How reliable is this estimate though? An estimate, by definition, carries with it a level of uncertainty. Ecologists use statistics to construct a range of estimates known as a “confidence interval”. We covered this topic in the population statistics lab and will use it again today.
Remember that a confidence interval of our estimated population size (NEST ) is a numerical range within which the actual, or true, population size (NTRUE ) will fall with a certain level of probability (Sokal and Rohlf, 1981). For example, in our frog example, we understand that if we did this experiment multiple times that 95% of the time the confidence interval would contain the true mean.
The more confident we become in our estimate, the narrower this range becomes. Still looking at the frog example where N=150, let's say we improved our sampling methods and ended up calculating a narrower 95% confidence interval of 145-155. In this case, the 95% confidence interval (145-155) is narrower than the previous example (125-175), therefore we have stronger confidence in our estimate of population size in this second example. Make sure you understand this relationship: the more confident we are in our estimate, the narrower the 95% confidence interval.
Similarly, if decrease our confidence and create a 90% confidence interval, we end up with smaller interval. Think about it this way - you are 100% sure the size of the frog population is between 0 and infinity, but that's not a very useful guess. We have less confidence the population size is between any two numbers, and as those numbers get closer our confidence level continues to decrease.
In ecology, the de facto standard level for confidence intervals is 95 per cent, i.e. a 95% confidence interval fitted around our point estimate of population size. Calculating these requires large sample sizes and intensive calculations on proportions, so in this lab activity we will employ a simplified method to calculate 95% confidence intervals using a binomial approximation (we’ll look up values in a table).
In this study, you will apply the Petersen method to obtain point estimates of population size in a population of juvenile frogs (tadpoles). This type of simulation is useful in exploring and validating the ideas behind mark-recapture studies. You will consider how marking different numbers of individuals impacts population size estimates. You will then evaluate the reliability of your estimates by fitting 95% confidence intervals around those point estimates and interpreting your results.
Overview
In this experiment you’ll estimate frog population size using a mark-recapture study. Initial set-up involves sampling the frogs, marking individuals with a red tag, and releasing them back into the pond. You’ll then collect 3 samples where you count how many marked and unmarked tadpoles you capture, from which you estimate population size. You’ll repeat this process in three separate rounds where you vary the number of marked individuals:
Round 1: Initial set up with 20 marked individuals x 3 samples
Round 2: Initial set up with 50 marked individuals x 3 samples
Round 3: Initial set up with 100 marked individuals x 3 samples
Initial set-up
1. Open the Virtual Biology Lab animated frog sampling tool (note: may not work in Chrome, so try other browsers as needed) and orient yourself to the controls. If the website doesn't function properly, try using your browser's incognito mode (if it has one), and/or clear your browser cache, and/or try using a different browser. On the sampling tool, in the green boxes on the left, select these settings:
Pond size: medium
Population size: large
Net size: medium
2. Click on “Setup” to complete the setup process. Then click “Go” and you’ll see tadpoles begin to swim. Allow them to mix for a few seconds. Note that there’s no time limit for the simulation, so there’s no need to rush through steps.
3. Click “Dip Net” (bottom right corner). You should see tadpoles appear in the Sample Bucket. Note you should catch approximately 20-30 tadpoles in your first dip. We will only mark 20 of these to standardize results, though in a true mark-recapture experiment you could mark all tadpoles in your first sample.
4. With that collection of tadpoles, click “Mark” 20 times. Note the count appear below in the yellow boxes. Then click “Release” to see the red-marked tadpoles go back into the pond with the others.
5. You’re now ready to begin data collection. Make a copy of the spreadsheet below and use it to record data from your samples.
In this spreadsheet, you're ultimately interested in the Population Estimate and the 95% Confidence Intervals. To use this data sheet for the mark-recapture simulation, enter data only in green cells (blue cells have equations in them and should update automatically). In the above example, look at Round 1 where 20 frogs were marked. Sample 1 then yielded 2 recaptured (marked) individuals and 18 unmarked; using the statistical table below, this results in a Lower R of 0.355 and an Upper R of 6.686. Notice that the blue cells in the Total row auto-fill as you enter your samples. Using this information, a 95% confidence interval for the true populations size of frogs is created. In our example, the interval is 59.8 - 1126.8. Once you complete Round 1 with samples 1, 2, and 3, use the Total row to look up the Lower R and Upper R values in the statistical table so that you can calculate a Total 95% confidence interval around your population estimate.
Things to note include:
95% confidence intervals are automatically calculated here based on the values you report in the Lower R and Upper R cells.
Smaller recapture rates (marked and unmarked alike) lead to wider confidence intervals (notice how high the range is when only two marked frogs are recaptured); thus combining the three samples leads to a smaller confidence interval. In other words, having more samples improves your estimate of the population size.
Due to the type of data (counts) and approximation method we are using, the confidence interval may not be symmetric around your estimate of R (this is different than other confidence intervals we explored earlier in class).
Sampling & Data Collection
6. With 20 marked individuals in the pond, and with the medium net still selected, click on Dip Net but do not mark more individuals. On your spreadsheet, under Round 1 where Number Marked = 20, do the following:
For “Marked in Bucket(Recaptured, R) ”, record the number from the yellow box “Marked in Bucket”.
For “Total in Bucket (Second Sample, S) ", record the number from the yellow box “Total in Bucket”.
Notice both the “Proportion Marked (R/S) ” and the "Population Estimate (N = (S/R)*M) " column should auto-fill. Make sure you can explain how the Population estimate was made - it may help to write the equation out on a piece of paper.
7. To consider how multiple samples (or a larger sample) would impact our estimate, click on Hold. This moves the tadpoles from the Sample Bucket to the Holding Pen.
8. Repeat steps 6 - 7 two more times, then press Empty Pen to release all the tadpoles. The Total row should auto-fill as you enter data for your three samples.
Estimating population size using lower & upper 95% confidence intervals
9. Use the statistical table below to consider the uncertainty associated with your estimate by constructing 95% confidence intervals. Using your recaptured (R) value from sample 1, located its position in the table, find the associated Lower and Upper values. Record these Lower and Upper values in your spreadsheet (green cells titled “Lower R” and “Upper R”). The blue cells to the right should auto-fill with estimated population sizes. Complete this step for the “Total” row as well.
Complete steps 1-9 for each of your 3 rounds, where each round you adjust Number Marked (20, 50, 100). Note you may need to dip the net multiple times to catch the number of tadpoles you need to mark.. Once all 3 samples are complete for each of your 3 rounds (total of 9 samples), answer the review questions below.
Use this statistical table to determine "Lower R" and "Upper R" in your spreadsheet.
1. Observe the graph of hypothetical data at right where population size is consistently found to be 150 but there are varying levels of confidence around that estimate. In which sample number are you most confident that population size is 150? Why?
2. Observe the graph of hypothetical data at right where population size varies, as does the 95% CI. In which sample number are you most confident that population size is accurately estimated? Why?
3. How did marking more individuals impact the reliability of your estimate and width of your confidence interval?
4. Within each round (20 vs 50 vs 100), how did combining 3 samples impact the reliability of your estimate and width of your confidence interval?
5. Using your most reliable data in your spreadsheet, write one sentence interpreting the outcome of your study. For example, "I am 95% confident that...".
6. Of the three variables required to estimate population size (M, S, and R), which variable should you put the most energy and funding into? In other words, which one is the most important to getting an accurate estimate of population size?
7. Are there any specific factors in your sampling or counting method that may have compromised the validity of your estimate of population size?
Wildlife ecologists continuously evaluate the best methods for marking organisms, especially as new technologies come to market. Assume for a moment, however, that marked individuals were more likely to be captured by ecologists than unmarked individuals. How would this affect the estimate of population abundance? What if marked individuals were less likely to be captured than unmarked individuals?
This lab contains information from
Olvido, A. E., and L. S. Blumer. 2005. Introduction to mark-recapture census methods using the seed beetle, Callosobruchus maculatus. Pages 197-211, in Tested Studies for Laboratory Teaching, Volume 26 (M.A. O'Donnell, Editor). Proceedings of the 26th Workshop/Conference of the Association for Biology Laboratory Education (ABLE), 452 pages.