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Overview
Overview
Demography is the study of populations. In a sociological context, demography focuses mainly on human populations, but the same concepts can be readily used in ecology. Many aspects of a population, such as growth, survivorship, and longevity, can be mapped and predicted using demographic data with a diverse range of applications. This can range from tracking the stability of a species facing conservation concerns to assessing social disparities in survivorship between groups of people. In this lab, you will use online public cemetery records to compare the survivorship of two different groups of people of your choice (such as between genders, geographic locations, cultural backgrounds, socioeconomic groups, or historic periods).
Objectives
Objectives
Students will be able to conduct their own research using existing data sources to address a demographic question of their choosing.
Once data is obtained, students should be able to create and interpret survivorship curves to answer that question.
Background
Background
Introduction
Introduction
In demographic studies, various population characteristics such as lifespan, reproductive output, and rates of mortality may be considered. There are a number of ways that the data related to these factors can be synthesized, analyzed, and graphed. Two of these, called life tables and survivorship curves, are useful in helping us understand the dynamics of populations and interactions with the environment. Species vary in schedules, or timing, of mortality and reproduction. This may impact which strategies related to offspring production are favored through evolution. For example, oysters experience high mortality early in life but produce huge numbers of offspring annually, whereas elephants have a high probability of survival after birth but females produce only one calf at a time.
Life tables are ways to compile information related to mortality and reproduction for each stage, or age, an organism encounters. They contain many different columns of information about a population, including information related to mortality (e.g., number of individuals dying at a given age, lx; expected remaining years of life, ex) and reproduction (e.g., number of female offspring produced at each age, mx).
Survivorship curves are graphical representations of the numbers or fractions of individuals that survive to a given age. There are species that have (I) low mortality at a young age, (II) constant mortality throughout life, or (III) high mortality at a young age (Types I, II, and III, respectively). These curves can help us determine possible causes of population limitation; periods of heaviest mortality may have the greatest impact on population growth. These graphs may be plotted on a log-scale to help consider relative survivorship for each age or stage. For example, birds generally display a Type II survivorship curve. This means the chance of surviving to the next stage is constant throughout their life. Plotting survival on a log scale allows this to be displayed as a straight-line, since a log-scale shows proportional (not absolute) changes.
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Knowing patterns of death and reproduction can be important in managing plant and animal populations. For example, fisheries managers might adjust the allowed catch after good and poor years of reproduction; managers trying to eliminate invasive plants might be able to target specific ages of plants for removal; and managers seeking to protect rare species might know what ages of individuals most need protection.
There are a variety of ways to construct life tables and survivorship curves. The best way, as represented by the studies of Darwin’s finches by Peter and Rosemary Grant and their colleagues, is to follow a number of cohorts over time. In this way, Gibbs & Grant (1987) showed that survival of Geospiza fortis varies among years. For example, the 1978 cohort had a higher overall survival rate than did the 1981 cohort, which the authors attribute to the different environmental conditions (e.g. rainfall, food availability) encounterd by each cohort. Although cohort-derived life tables (also called dynamic life tables) and survivorship curves provide the best quality data, they are difficult and time consuming to construct.
Sometimes scientists develop static life tables and use those to estimate survival rates. Two major ways to develop a static life table and survivorship curve are to (1) discover the age at death of members of a population or (2) count the number of individuals in each age class alive at one time. Deevey (1947) constructed a life table from Adolph Murie’s data on Dall sheep. Murie had collected and aged horns that he found lying on the ground, thus providing an estimate of the age at death of each sheep (static method 1). Alternatively, ecologists often collect and age samples of animal or plant populations and use these data to construct a static life table and related survivorship curve (static method 2). A classic data set that was used in this way is the number of red deer in different age classes (Lowe, 1969).
There are assumptions involved in both of the static methods. Both methods assume a stable age distribution—a situation in which the percentage of individuals in each age class does not change from one time period to the next. They also assume the population size is constant (no change in birth rates and no net emigration/immigration). Using age of death averages any changes in survivorship rate over many cohorts. Using the age structure of a population gives less reliable information because it simply provides a snapshot of the population at one instant in time. However, the snapshot may be better than nothing.
In this exercise, you can use either static method to construct a life table and survivorship curve for humans. You can either
collect data from two groups (using the methods outline below) and compare their survivorship
collect data from one group using both methods outlined below to assess if both methods give you the same results
Methods
Methods
In this exercise, you will use a static method to construct a life table.
First, make sure you understand how to develop a life table and survivorship curve using each approach. To use the age at death of members of a population, explore the "Dall Sheep Example” tab in the attached file “StudentLifeTableTemplate” to be sure you understand how to fill out a life table and graph a survivorship curve.
Note the data you collect tells you how many organisms died during each interval. You then can find the number of deaths per 1000 (dx, just a way to standardize among populations of different sizes!) by dividing the number of deaths in each stage by the total number of deaths (organisms) you observed and multiplying that by 1000 (look at the formulas!). Next, calculate the number of individuals per 1000 that survived to the next stage (nx). The first stage always get a 1000 here (since all had to be born to be counted in death records!). If you subtract the number of deaths per 1000 in each stage from the number per 1000 that survived to each stage, you get the number surviving to the next stage! You can turn this into a proportion (lx) by dividing nx by 1000. Look at the Dall sheep example, then complete the table. Finally, graph a survivorship curve by plotting the age at the beginning of each interval against lx. The example shows how you can also plot survivorship on a log-scale (see Data Summaries in Google Sheets for more help).
After you feel confident about how to construct and interpret survivorship curves, brainstorm about the kinds of questions that interest you and choose what groups you will compare (or what group you will use to compare methods).
What populations? That’s up to you. You can compare males vs. females, people living at different times, people living in different places, or, perhaps, people of different ethnicities or socio-economic backgrounds. You may even think of other interesting comparisons. As you plan your project, make sure you identify a specific, interesting question, and hypothesize an answer to your question.
Supplement this brainstorming with an examination of cemeteries records available from https://www.findagrave.com
Protocols
Protocols
Choose two groups whose survivorship curves you'll construct with cemetery data (see other note below for ideas). Record the birth & death years for 50 individuals in each group. The age at death should automatically fill in for you in the spreadsheet.
Summarize your age data into the next worksheet (count the number of individuals that died in ages 0-4, 5-9, 10-14, etc).
Construct the survivorship curves as scatterplots: age at death vs proportion surviving. Do not include a trendline or R-squared value. Make sure axes are labeled, series is visible, and chart title is updated to interpret the trend. Also make sure your y-axis does not have negative values on it (set y-axis minimum value to 0), and make sure your x-axis shows your final data point where y=0 (should have a dot on the x-axis at your oldest age interval).
Interpret your graphs: compare the shape of the survivorship curves between the groups and answer the three review questions below.
Review Questions
Review Questions
How did your two groups compare in terms of survivorship?
What factors do you think might have contributed to the trends you observed (e.g., social, historic, environmental)?
Why do you think it might be difficult to disentangle some of these factors from one another, such as socioeconomic/environmental?
Additional tips & instructions
Additional tips & instructions
Selecting groups to compare
Selecting groups to compare
You're tasked with choosing two groups of humans whose survivorship you want to compare. Here are some possibilities to consider to get you started, but you are encouraged to come up with your own ideas; you just need two groups that are interesting for you to compare.
Effect of sex on survivorship: Choose one cemetery and one time period (e.g., Bronx born 1900-1910 but died at any point). Using traditional naming conventions, assign individuals to group 1 (females) or group 2 (males) based on your best estimate of their sex.
Effect of time on survivorship: Choose one cemetery, find 50 individuals born in the same decade a long time ago (e.g. 1850s), and 50 individuals born in the same decade more recently (e.g. 1950s). We might expect more recent groups to live longer, though remember to consider effects like war, economic depression, social issues, medicine, environmental degradation, and other factors that might influence survivorship curves.
Effect of geography and/or socioeconomic conditions on survivorship: Choose two cemeteries from different locations (e.g., Bronx vs. Long Island; urban vs. rural; northeast vs. south; area of high median income vs. area of low median income; area of high racial diversity vs. area of low racial diversity; there lots of different ways you could do this!). Find 50 individuals per cemetery to construct your survivorship curves.
Step-by-step spreadsheet instructions
Step-by-step spreadsheet instructions
Record the birth and death years of at least 50 people from each of the two groups in your “Template for grave data collection” sheet in the Life tables and survivorship template spreadsheet. You do not need the same number of people in each group, but the minimum is 50. ENTER YOUR DATA INTO THE WHITE CELLS ONLY. Green cells contain formulas that will calculate the age at death for you.
Using the data from the "Age at Death" column, tally the number of people who died in each age range on the “Life table for grave data” sheet. Column A will have the age groups and Column B will have the number of people dying in each age group. Only enter data into the white columns for each group.
The number of deaths per 1000 individuals in Column 3 will be calculated for you (this is done by dividing the number of deaths during that age interval by the total number of deaths and multiplying that number by 1000).
Similarly, the number of survivors per 1000 individuals in column 4 will be calculated for you (by subtracting the number of deaths per 1000 during that age interval from the number of survivors at the beginning of that age interval).
Construct a survivorship curve and log version of the curve for each group. You will use the columns titled "nx: Number survivors per 1000 at beginning of age interval" and age interval at death. Then answer the review questions based on what you found. Make sure to submit a link to your spreadsheet and a screenshot of all four graphs with your submission.
References
References
Adapted from:
Larson, E. (2020). Demography from "virtual cemeteries". ESA Data Access - Inclusive Pedagogy, (Version 1.1). QUBES Educational Resources. doi:10.25334/65XT-CM66
Janet Lanza. 2 March 2012. Demography from physical cemeteries, "virtual cemeteries," and census data. Teaching Issues and Experiments in Ecology, Vol. 8: Experiment #1 [online]. http://tiee.esa.org/vol/v8/experiments/lanza/abstract.html
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