Abstract

The mathematical modeling of populations utilizing field-collected demographic data is an important component of lab curricula in a variety of undergraduate biology lab courses. During the global pandemic brought about by the SARS-CoV-2 virus in 2020, we successfully converted an in-person lab on demographic population modeling to a lab that could be run remotely. We used a Google Earth Web Project to simulate a population study of the Northern Spotted Owl. In the simulation, students collected both demographic and mark-recapture data, based on surveying images of Northern Spotted Owls as they navigated four different wildlife transects. After conducting the survey, students used the data to determine population size using the mark-recapture method, derived a life table, calculated the net reproductive rate, and used the information to assess the current management plan for the population studied. Here we outline the lesson and provide materials required to duplicate the lab or to use Google Earth to create a similar simulation centered around a different species in any location around the globe.

Primary Image: Population Ecology with Google Earth. This population ecology lesson utilizes the Google Earth Project to provide students a simulated mark-recapture study. This lesson framework can be applied to any species or location; we chose to focus our lesson on the Northern Spotted Owl.

Citation

Lesson Learning Goals

• use methods by field biologists to research populations of species that are endangered, threatened, or of specific interest.
• learn how GPS data and GIS systems are used in field research associated with population biology.
• use quantitative skills to investigate a research question in population biology.
• use of demographic analyses to evaluate the status of populations and derive inferences about the effectiveness of management plans on threatened, endangered, or other species.
• be introduced to the Northern Spotted Owl and their dependence on the old-growth-forest ecosystem. The disruption of habitat, such as the logging of old-growth forests, can have far reaching impacts on population dynamics of numerous interacting species, both positive and negative.

Lesson Learning Objectives

• use transects to gather virtual field data by assessing age classes, sex, fecundity, and mortality of Northern Spotted Owls seen in the field.
• use virtual field data to estimate the size of a population through mark-recapture and to create a life table.
• evaluate the outcome of a conservation management program based on the results of field data and the associated demographic analyses.

Introduction

Classroom laboratory exercises that can be conducted remotely can be advantages for many situations. In the fields of wildlife biology and field ecology, providing practical outdoor and hands on lessons can provide excellent opportunities for students to simulate research situations. However, providing outdoor laboratory lessons is not always feasible (1, 2). Here we introduce a virtual lab in population ecology of Northern Spotted Owls. The lesson utilized Google Earth Web to allow students to interact and engage with simulated data. Importantly, the lesson framework we developed can be adapted for other species and locations depending on the interests of instructors and students living in different ecosystems.

The challenge for any transition to a virtual platform is to effectively incorporate the goals of an in-person class into the virtual classroom. For undergraduate biology labs, important goals are to facilitate manipulative skills, quantitative skills, and reasoning skills associated with research and potential careers in biology (3). Population ecology is a subdiscipline of biology that investigates demographic and mathematical modeling of populations including growth, dynamics, control, and sustainability. Quantitative skills are used to investigate endangered and threatened species (4, 5), invasive species (6), human population growth (7), and to model the growth and spread of diseases (8). Overall, quantitative literacy is an essential component of science literacy (9).

Intended Audience

This lesson was originally designed as a single class lab experience within an introductory undergraduate General Biology course (a one-credit-hour lab, a three-credit-hour lecture). The original audience was a lab class enrolled by approximately nine hundred students divided into 60 sections and taught by 20 graduate student teaching assistants (GTAs). The lesson can be adapted for other labs or lectures in courses related to biology, ecology and environmental science.

Required Learning Time

The lesson plan is designed for a two-hour time period (see Table 1). No prior preparation before class is needed. Data collection, analysis, and assessment is expected to be completed by most students within two hours, although the ability for this to be a self-guided lesson would allow students to work at their own pace.

Table 1. Lesson plan timeline table. Designed for a single 2-hour lesson. Students are expected to go through the introductory material and complete the lab within 2 hours. Some of the assessment questions may require additional time outside of the two-hour expectations.

Prerequisite Student Knowledge

This lesson is designed to function on its own and students do not need any prerequisites to successfully complete this lab. The lab incorporates mathematical functions with algebraic expressions so a background in algebra is helpful but is not required. Likewise, students should be familiar with the scientific method, analyzing data, and making evidence-based claims. Introductory material on population biology is provided at the beginning of the lab. If desired, this lesson can be integrated into a class meeting session.

Prerequisite Teacher Knowledge

Instructors should know the concepts associated with population biology such as demography (births, deaths, age structure), telemetry, life tables, mark-recapture methods, use of transects, and population growth rates. Additionally, instructors will need familiarity with the online platform—Google Earth Web—and have the ability to accurately sex and age Spotted Owls in provided photos. Instructors may spend 1–2 hours reviewing the lab prior to teaching the module (see Table 1). If phones or tablets are the only electronic devices available, it is recommended that students are provided with a paper copy of Supporting File S1 and a printout of the Owl Identification Sheet (link provided in Supporting File S1), as it will be difficult to record information on a phone that is being used to view the Google Earth Web Project.

Scientific Teaching Themes

Active Learning

Students will engage in active learning by interacting with a Google Earth Web Project to collect data. Students will make “observations” by examining photos of owls that were taken along simulated transects and record their observations on a data sheet. The students will use the results of these observations to calculate demographic measures. The results of these measures will be used to address if the management program is succeeding based on student calculations.

Assessment

Observation

Students will be required to fill out Table 1 in Supporting File S1 (notation will be formatted such as—Table S1.1—for remaining tables in Supporting Files). Table S1.1 is used to record the observations made by students from each of the Northern Spotted Owl photographs in the Google Earth presentation. This includes the age, sex, whether it was banded, and the number of fledglings (Table S1.1).

Data Analysis

Students will use the observations from Table S1.1 to summarize the number of alive and dead owls that were found in each sex and age class (Table S1.2). With the age class data, students will complete the life table (Table S1.3). The information from the life table is used to estimate the number of owls in each age class that are in the population. Finally, students will calculate the net replacement rate using the results from the life table.

Evaluation of Results

Students will be asked to use the results of their analysis to provide evidence and reasoning to support their claim on whether the management program is working or not.

Inclusive Teaching

This lesson connects concepts of population biology, conservation, field methods, GIS methods, and demographic analysis within a single learning module. This learning module as able to be completed by any student with a computer, phone, or tablet and access to an internet connection. This provides students who may have a physical disability that prevents them from conducting a field-based population biology lab with a way to also go through the data collection process of the lab. While not a replacement for having students preform fieldwork outside, Google Earth provides an easy way to model the world and observe how it changes. Students can visit and interpret data from field sites from anywhere in the world on their computer. This Google Earth Project can provide an introduction for students to visualize the world from a unique perspective and promote self-exploration of the various other projects and time lapses existing on the service.

The Northern Spotted Owl is an iconic species associated with old growth forests and conservation. Iconic species such as the Northern Spotted Owl may increase engagement from students, birders, and those interested in preserving nature. The plight of the Northern Spotted Owl connects the need for preserving habitat and interspecies relationships. While we use the Northern Spotted Owl as the focus of this lesson, the focal species can be adjusted to any species around the world, while using the same demographic framework. It is possible for Instructors to design a new Google Earth Web Project with a species that is of local importance to students or a species from a completely different ecosystem (e.g., polar bears).

Lesson Plan

Our Population Ecology module was used in the 2020 and 2021 spring semesters. The lesson duration was 110 minutes, was remote, and was completed by students without direct intervention by the teacher. If desired, this lesson can be conducted in class or in groups without any modifications. Most of the variation in time required for completing the lesson was due to differences among students in their time on the end-of-lesson assessment questions; thus, students who require additional time are best served if the lesson time can be up to three hours or are expected to complete questions as homework. Since we provided this lesson remotely and asynchronously, the lesson was available for a full week and without time constraints to allow students to work at their own pace. The results and answers to the assessment questions were submitted online at the end of the week.

Before Class Meeting

Instructor Preparation

The materials provided within the lesson are expected to provide the necessary preparation for instructors. Instructors should make sure they complete the lesson on their own and understand how to use the Google Earth Web interface. It is necessary to understand the basic concepts of population biology, demographics, and the calculations to complete life tables. Additionally, instructors need to correctly identify the owls from photos. If teachers complete the lab and the results from the life tables are accurate, this will demonstrate sufficient training to help students if problems arise. Teachers can provide additional introductory materials if they choose to do so.

Student Preparation

Our approach did not require students to have completed any pre-lab work. If desired, additional introductory materials, readings, or pre-assessment questions could be assigned to students prior to the lesson.

The Lesson

Introduction

Human perturbation of habitats has led to a potentially prominent threat to ecosystems. Sometimes, once rare or absent species can invade an altered habitat as the new ecosystem conditions facilitate species invasions. When a new species is introduced, if conditions are right, the species has an enormous potential to proliferate within the new ecosystem. But what about native invasions due to habitat alterations, such as those caused by climate change or local human activities? Can alterations in habitat caused by people favor one native species over another? This is a question that can be addressed by population biologists and will be the topic of this lesson.

Prior to recent human activities, the Pacific Northwest (Northern California, Oregon, and Washington) was dominated by what is known as late successional or old growth forests. Old growth forests are characterized by trees greater than two hundred years of age, which have a high number of snags or broken tops, which shed needles and create a relatively sparse understory. Many animals have been adapted to thrive in old growth forests such as the Northern Spotted Owl, which has many adaptations for living in old growth forests. One such adaptation is related to nest building; they prefer to nest high up in the snags of large old-growth trees and they build their nests accordingly. Periodically in the past, fires and other natural disturbances would wipe out vast areas of old growth forest and create early-successional patches within the old growth forest that would favor animals with different adaptations such as Barred Owls. Over the last 200 years, human disturbance through logging has changed much of the vast expanses of old growth forest habitat in the Pacific Northwest to new growth forests (< 200 years). In the 1980’s population biologists noticed populations of Northern Spotted Owls were declining rapidly and in 1990, the Northern Spotted Owl was designated as threatened under the endangered species act. Since 1990 a recovery plan has been enacted and an attempt to preserve critical Northern Spotted Owl habitat was carried out. In this lesson, your role as a population biologist is to gather information on a representative current Northern Spotted Owl population. Before you begin your study, here is background information you may use.

Population Growth and Demography

The rate of growth of a population is determined by four factors: births, deaths, immigrations (animals entering the population from another population), and emigrations (animals leaving the population). In many cases, and for cases in this exercise, immigration and emigration account for little change compared with that of births and deaths. Therefore, we will concentrate on influences of births and deaths on the size and growth of populations.

Birth rates and death rates may depend upon the age structure within the population. For instance, grizzly bears can live more than 20 years, they typically do not start reproducing until age five, and their mortality rate is high for the first 4 years of life, decreases in middle-aged bears, and increases after an age of 15 (10). Therefore, the rate of growth of a population of grizzly bears would depend on the relative frequencies of young individuals, middle-aged individuals, and old individuals in the population. The study of age-specific and other statistical factors influencing the size of a population is called demography. Population demographics are determined through research and organized into life tables. Two types of life tables are cohort life tables and static life tables. A cohort is a group of individuals born at the same time or during the same season. A cohort life table is developed by marking a cohort at birth, following them throughout their lives and estimating age-specific fecundity (reproduction) and survival rates. A cohort life table is developed through a longitudinal study and may take many years. For instance, to develop a cohort life table for grizzly bears it may take longer than 20 years of research. In contrast, a static life table is developed by aging and marking a randomized sample from the entire population all at the same time, then following them for a short period of time to determine age-specific fecundity and survival rates. Age-specific fecundity of male animals is often difficult to determine especially when the mating system is not monogamous. Therefore, in the life table, you will examine age-specific fecundity and mortality of females only. The following symbols are important to know for evaluating life tables (11).

x = age class. An age class is a group of individuals in the population that are a certain age (0, 1, 2, 3 ... years old), or group of ages (0–4, 4–8, 8–12 ... years old). Age classes are usually determined by the ability of a researcher to distinguish the age of the organism, the size of the population, and the generation time of the organism.

s_x = survival in age class. The probability an individual survives from the beginning of an age class to the end of the age class and is calculated by the equation:

# Alive in age class / (# alive in age class + # dead in age class)

l_x = survival to age class x. The probability an individual survives from the beginning of its life to age class x. The survival to age class x can be determined by multiplying values of s_x for all age classes ≤ x. For example, if you wanted to determine l_3, you would multiply s₁, s₂, and s₃.

b_x = age-specific fecundity. The number of female offspring produced by a female during age class x. Under situations where you cannot determine the sex of the offspring you can assume that the sex ratio of males to females is equal. You can determine the age-specific fecundity rates from the equation:

b_x = 0.5(# of offspring in age class / # of females in age class)

R_o = net reproductive rate. The number of female progeny produced by a female during its lifetime. The net reproductive rate can be determined by summing the products of l_x and b_x in each age class (l₁b₁ + l₂b₂ + l₃b₃ ...). This value indicates whether each individual can replace itself in its lifetime. If R_o = 1 the individual replaces itself exactly. If R_o < 1 then the individual does not replace itself, and thus, the population is decreasing. If R_o > 1 then the individual over-replaces itself, and thus, the population is increasing. If R_o is 0.5 then the individual is only replacing one-half of itself over its life. Note that R_o is an average value for all individuals in the population.

Mark-Recapture Method of Estimating Population Size

One method of estimating total population size from a sample is the mark-recapture method. The mark-recapture method involves capturing a certain subset of the total population, marking them in some way that they can be recognized in the future, releasing them back into the population, then capturing another subset of the population. For this lab you will use a modified mark-recapture method and use a sight-resight method. From knowing the total number of individuals marked, and the number of recaptures during the second capturing bout, an estimate of the total population size (N) can be made from the following equation.

N = ((total # in pop. with a band) (# of living owls seen)) / # of owls seen with a band

For this lab, suppose that the total # in the population with a band is thirty. In order for the mark-recapture method to be valid, the probability of capturing any individual in the population must equal the probability of capturing any other individual. When using traps, animals cannot become trap-shy or trap-happy. When using a mark-resight method, the re-sighting trips must be randomized rather than on the same pathways over and over.

Radio Telemetry

Radio telemetry is important in population biology. Radio telemetry utilizes a transmitter that emits a signal. The transmitter is usually in the form of a small battery-powered object that is placed on the animal. The transmitter may be in the form of a collar (for larger animals), a backpack for birds, it can be surgically implanted into the animal, or it can be glued on the outside of the animal such as on the shell of a turtle. The signal from the transmitter is then picked up by a portable receiver and an antenna carried by the researcher. Transmitters can vary in the frequency of their signal so that the receiver can be adjusted for the given transmitter. Radio Telemetry has many useful applications to population biologists.

• Visually Locating Animals. The antenna picks up a directional signal (i.e., the signal is loudest when the antenna is pointing directly at the transmitter). This allows the researcher to use the signal to walk in and visually sight the animal. This is helpful if you are doing a cohort population study, because you can locate the animal, then gather data such as the number of offspring and its mate. It also helps with behavioral studies because you can find the animal in the field for behavioral observations.

• Mapping Animal Locations. Telemetry can be used to locate animals from many miles away. To do this, researchers use triangulation. Telemetry produces a directional signal. A biologist can get a signal and determine its direction then move to a second location to get a second signal. By plotting each signal on a map, the biologist can get an approximate location of the organism. This is especially useful for estimating home-range sizes and tracking dispersing animals. Do males disperse farther than females? How far do animals disperse? At what age do animals disperse?

• Determine Survival Rates and Causes of Mortality. You can use telemetry to determine mortality. For a little more money, the transmitter can be equipped with mortality sensitivity. When the transmitter does not move for more than a day, the signal doubles in frequency. Then as a researcher you can locate the dead organism and determine the cause of death.

• If you even have more money, you can use transmitters that send their signal to a satellite, and you can use GPS to give you a periodic location of the organism without constantly going out in the field to track the organism. (A more time efficient method, but not as fun.) This application is especially useful for migrating animals such as whales. However, battery life and transmitter size is an issue especially for smaller animals.

Some problems with radio telemetry exist. The radio telemetry transmitter is typically very small, so it does not negatively impact the organism, thus battery life is limited. Capturing and recapturing the animals is time intensive and may have an impact on the animal as well, so banding birds or tagging mammals is still often preferable to radio telemetry for many population studies.

GIS and GPS

Global positioning system (GPS) data is important for recording positions in the world. These data can then be used in geographic information systems (GIS) and global visualization tools (such as Google Earth, ArcGIS Explorer, and QGIS). For biologists, GIS and GPS have become essential for most researchers and managers as a way to plan projects, track individuals, or analyze data from environmental systems. Incorporating GIS technologies, GPS data, and visualization platforms allows biologists to better understand the environment and make responsible environmental decisions (12, 13). Google Earth provides an easy-to-use interface that allows anyone to easily explore and visualize spatial data in a world model.

Summary of Student Procedures

In Supporting File S1, students are provided with an introduction into population ecology and background on the Northern Spotted Owl. The practical approach to the lesson begins by directing students to a Google Earth Web Project “Population Ecology.” Clicking on the “Present” button opens the Google Earth project presentation. A brief overview of wildlife tracking with radio telemetry and GPS tags provides background on how wildlife biologists can track wildlife. The use of GPS tags provides an opportunity to incorporate how GIS software, like Google Earth, is utilized as a tool for monitoring populations on the landscape. We provide two GPS-tagged owls as examples for how we can track wildlife with GPS data. The tracks from these GPS-tagged owls are drawn onto Google Earth, allowing students to visualize the paths owls take and identify locations where owls spend time. Points where owls commonly visit or occupy for extended periods are likely either nest sites or perches. Photos of each perch are shown, and one contains our tagged owl next to a fledgling.

Students will need to utilize the owl identification sheet (link provided in Procedure 1 of Supporting File S1) to help determine the sex and age of the owls they encounter. Students record the following information about each owl encountered in Table S1.1, the sex, the age, whether the owl is alive or dead, how many fledglings the owl has, and whether the owl is banded. Being banded means the owl has been captured previously and was marked with a color-coded band around the leg.

After students record the information from the first pair of owls, they are shown the four wildlife transects that were used in the Northern Spotted Owl population monitoring study, before moving onto identifying the remaining owls that were observed. The third location provides an example of a deceased owl. In this case, a Northern Spotted Owl has been observed in the talons of a great horned owl. Students record the information on the deceased owl in Table S1.1 as well. At this point, students have been guided through Google Earth and correctly identifying and recording information in Table S1.1 about each alive or dead owl that is observed.

When students finish the owl identification, they are finished with Google Earth Web. They can apply the information in Table S1.1 to the mark-recapture method and estimate the overall size of the population. In addition, in Table S1.2, students are asked to quantitatively distill the data in Table S1.1 by compiling totals of living and dead owls observed by sex and age class, and the associated fledglings for each female. Information in Table S1.2 is applied to completing life-table calculations (Table S1.3). In the life-table students calculate several parameters for each age class: survival probability within an age class (s_x); survival probability from the beginning of life to the end of an age class (l_x); the fecundity of individuals within a specific age class (b_x); and the net reproductive rate (R_o).

Once Table S1.3 is completed, the students are finally asked to assess the status of the population studied and relate the assessment to the implemented management plan (i.e., what is currently happening to the population; from the life table is there any demographic information indicating vulnerabilities in the success of the population that the management plan may need to address; and is it even possible to reverse any trends in the population?).

Teaching Discussion

This lab is based on a field-based simulation of a population ecology lab to be conducted through a GIS platform and designed for remote instruction. While field-based methods, such as using radio transmitters and conducting wildlife observations with binoculars are not used in this lab, we are able to introduce students to methods of using GIS and GPS data in a population ecology study and visualizing the data on Google Earth web platform. Also, with moderate effort by the instructor, this lab is adaptable for any species. Data can be simulated or obtained from real-world monitoring results. In addition, this lab can be conducted from any computer platform. All that is needed is an internet connection and a browser. Instructors can choose any biological system, edit the introductory material accordingly, ask different questions, or make the assignment group based.

Supporting File S2 provides information regarding the results of this lesson and will be helpful to instructors for understanding the lesson and evaluating students’ responses. Note that small mistakes in identifying owls or recording the results can lead to inaccurate results, a problem that occurs in real population monitoring studies. Small inaccuracies may influence the results significantly. These should not be harshly graded, but instead how students perform their calculations and interpret the results should be prioritized. For this reason, it is important to have students show their work and clearly explain their conclusions.

We were unable to complete IRB protocols prior to the implementation of the lab, but here we report overall student performance on assessments for the lesson. In the spring of 2020, the final five labs of the semester were converted to online experiences: plant diversity, human evolution, behavioral ecology, population ecology and stream ecology. For each lab, students completed an associated lab write-up, and we chose the three labs with similar write-ups: human evolution, behavioral ecology, and population biology. An ANOVA revealed no significant differences were present between student scores on the three write-ups (F = 0.87, d.f. = 1, 2236, p = 0.35). During spring 2021, all the labs were run in a hybrid format with over 95% of the students choosing the online format. An ANOVA comparing the seven labs with comparable write-ups in 2021 revealed no significant differences were present between student scores for the seven lab write ups (F = 1.66, d.f. = 1, 4499, p = 0.020). In 2022 the population ecology lab was run as an in-person field experience. An ANOVA comparing student performance on the population ecology write up in 2022 versus 2021 revealed no significant differences (F = 1.22, d.f. = 1, 1286, p = 0.27). These results indicate that the online version of the population ecology lab resulted in similar achievement by students compared to other online labs and compared to an in-person version of the same lab. In addition, student completion of the lab write-up in spring 2021 when it was online, was similar to that in spring 2022 when the lab was run as an in-person experience (2021 = 95.6 % completion, 2022 = 95.3 % completion). In general, our perception of student attitudes toward the online version of the lab was positive and similar to their attitudes toward other online versions of the labs.

Supporting Materials

• S1. Population Ecology – Student Handout

• S2. Population Ecology – Teacher Information and Rubric

Acknowledgments

We would like to thank Teachers and Students who were involved in adapting biology labs to an online environment at the start of the COVID-19 pandemic. We specifically acknowledge Erik Funk, Gabrielle Glime, Christa Torrens, and Noa Greenwald for their work on transitioning the field-based population ecology lab to a remote learning module during the start of the COVID-19 pandemic. We have no conflicts of interest to declare.

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