Life Table Lab Background Spring 19 PDF

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POPULATION SURVIVORSHIP LAB: HUMAN LIFE TABLES Objectives: Discover how patterns of survivorship relate to the three types of survivorship curves Learn how patterns of survivorship relate to life expectancy Learn how to use excel and analyze population data

Assignments: Moodle Quiz (5pts) Life Table Worksheet (10 pts)

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BACKGROUND LIFE TABLES AND SURVIVORSHIP CURVES A life table is an age-specific record of survival and reproduction rates in a population. Included in a life table is information based on age of the individuals. Some life tables also take into account other important variables that affect population growth like size or life stage (e.g., egg, hatchling, juvenile, adult) of the organism. Wildlife population ecologists use lifetables to understand and predict changes in populations and manage populations.

TYPES OF LIFE TABLES Life types fall into two main types: cohort and static. Cohort life tables follow the survival and reproductions of all members of a cohort, which is the set of all focal individuals in a population, from birth to death (e.g., all deer born in Ruston, LA in 2018). Static life tables records the number of living individuals of each age in a population and their reproductive output. We will be focused on age-based static life tables. These tables count how many individuals in a population are currently at each age class, rather than following a group of individuals from birth to death as in cohort life tables. It is rarely possible to study all individuals in a population from birth to death, so static life tables are frequently used. However, the assumption in static life tables is that age-specific survivorship and fertility rates are constant and unchanging. This assumption is rarely met, however these tables are still useful for predicting population changes.

HUMAN DEMOGRAPHY Demography is the statistical study of the size and structure (with regard to age and sex) of populations. The word is derived from the Greek demos, meaning ‘people’ and graphe, meaning ‘writing’. Detailed records of human births and deaths were kept at least as far back as the Roman Empire (27 B.C. – 476 A.D.). Life tables were developed by human demographers working for life insurance companies, who have a vested interest in knowing how long people can be expected to live. Life tables allow us to compare mortality and survivorship among different segments of populations and to generate and test hypotheses about these populations. Objectives In this lab, we will construct static life tables for human populations from two different time periods and for two different major cities. You will work individually in class to collect data from online public records databases, and then we will combine everyone’s data to construct life tables and survivorship curves. We will use these to generate testable hypotheses about factors contributing to differences in survivorship between sexes, cities, and time periods. Exercise Each person will be responsible for collecting data from online public records databases for one of two cities: Ruston or New Orleans, LA. Each person is responsible for collecting 40 data points (i.e., 40 deaths): 10 females and 10 males from each of two time periods: 1910–1930 and 1970–1990.

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Part 1: Collecting Static Age-based Data Half the class (designated by TA) will use public records for Ruston, LA. https://www.findagrave.com/cemetery/67672/greenwood-cemetery Each student will get a different letter of the alphabet. Type your letter into the ‘Last Name’ box on the website. Leave ‘First Name’ blank. This will return hundreds of records spread across many pages. You can move among pages by scrolling to the bottom of the page or by selecting a Page number. Record data for names that have a last name that actually start with that letter, which may require scrolling to other pages. You will need 40 data points (i.e., 40 deaths): 10 females and 10 males from each of two time periods: 1910–1930 and 1970–1990. The second half of the class (designated by TA) will use public records for New Orleans, LA. https://www.findagrave.com/cemetery/67668/greenwood-cemetery Each student will get a different letter of the alphabet. Type your letter into the ‘Last Name’ box on the website. Leave ‘First Name’ blank. This will return hundreds to thousands of records spread across many pages. If you get this error message below:

Then type a second letter of your choosing after the first assigned letter. You can move among pages by scrolling to the bottom of the page or by selecting a Page number. Record data for names that have a last name that actually end in that letter, which may require scrolling to other pages. You will need 40 data points (i.e., 40 deaths): 10 females and 10 males from each of two time periods: 1910–1930 and 1970–1990. 3

Data Sheet

Name: ___________________

Record the Age at Death below for 10 females and 10 males that died in one of the years between 1910–1930 and years between 1970–1990. Be sure to write down your city and the year you chose within each time period. Use the birth date and date of death to calculate the Age at Death. City: ___________________ Death Year (1910–1930): ________ Gender Female Female Female Female Female Female Female Female Female Female Male Male Male Male Male Male Male Male Male Male

Age at Death

Death Year (1970–1990): ________ Gender Female Female Female Female Female Female Female Female Female Female Male Male Male Male Male Male Male Male Male Male

Age at Death

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Part 2. Compiling the data and creating a static life table We will divide into four groups and construct static life tables for males and females in two different major cities during two different time periods: Ruston 1910–1930 Ruston 1970–1990 New Orleans 1910–1930 New Orleans 1970–1990 Each group will do the following: 1) Compile the data for your city and time period from all students who collected data for your city. 2) For females and males separately, count the number of deaths that occurred within each age increment: 0–0.99, 1–9.99, 10–19.99, and so on for each 10-year increment. 3) Record your count data in the Table below. 4) Enter your data into the provided excel spreadsheet to construct a life table and survivorship curve for each sex. Each life table includes the following variables: x = age increments at death ax = number of individuals that died in age interval x dx = number of individuals that died during age intervals x to x + 1 (scaled to 100). lx = percentage of individuals surviving to start of age interval x. 5) Save your life table and survivorship curve figure (the excel file) showing the curves for both sexes and email it to your instructor so he/she can combine the results for all four groups into a single document. 6) Use the results from all four groups to answer the questions on the next page. City & Time Period: _____________________________ Females 0–0.9x 1–9.x 10–19.x 20–29.x 30–39.x 40–49.x 50–59.x 60–69.x 70–79.x 80–89.x 90–99.x 100–109.x 110–119.x

# Deaths

Males 0–0.9x 1–9.x 10–19.x 20–29.x 30–39.x 40–49.x 50–59.x 60–69.x 70–79.x 80–89.x 90–99.x 100–109.x 110–119.x

# Deaths

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Questions

Name: ___________________

1) In general, how does survivorship differ between males and females?

2) In general, how does survivorship differ between the cities of Ruston and New Orleans?

3) In general, how does survivorship differ between the time periods 1910–1930 and 1970– 1990?

4) How does survivorship of each sex compare between the time periods 1910–1930 and 1970–1990? Are the patterns similar for both cities? For each time period and sex, at what ages are increases in mortality most evident?

5) Considering what you know about differential sources of mortality for females and males and what you know about differences between time periods and cities, formulate a hypothesis about the factors that might explain variation in survivorship between sexes, time periods, and cities.

6) What would you predict the survivorship curves for females and males living in Monroe, Louisiana, will look like 100 years from now? Draw the survivorship curves you would predict and explain your reasoning.

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