4.30.26

Live fast, die young?

Fast living snake (grey checked) Slow living snake (dark with yellow stripe)
The two garter snake ecotypes – Fast living snake with grey checked pattern, and slow living snake with dark with yellow stripe.

Garter snakes are a common sight across North America, but one small species in Northern California has helped scientists learn a lot about how animals adapt to their environment. Since 1972, a long lineage of scientists has studied these snakes and passed their data down through generations. This long-term dataset allows scientists to ask questions about how replicate populations change over time.

These garter snakes live in two very different types of habitats. Some populations live along lakeshores at low elevations. These areas have rocky shorelines, warmer temperatures, and steady access to water and food like small fish and frogs. However, these snakes also face more predators. Other populations live in high-elevation mountain meadows. These habitats are cooler and covered in grass. Water and food are not always available and can change each year depending on snow and rain. Because these habitats are so different, the snakes in each place experience different challenges.

Over time, these differences have led to the evolution of two distinct ecotypes. Ecotypes are groups within a species that have adapted to their local environment. The lakeshore and meadow snakes differ in both their physical traits and their genetics. They also differ in how they grow, reproduce, and survive—traits known as life history strategies.

Life history strategies are often described along a spectrum from “fast” to “slow.” Lakeshore snakes have a “fast” life history. They grow quickly, reach adulthood sooner, are larger at adulthood, and produce larger and more frequent litters of offspring. In contrast, meadow snakes have a “slow” life history. They grow more slowly, reach adulthood later, have a smaller body size, and have fewer, less frequent litters.

Kaitlyn became interested in these snakes after a surprising start to her career. Interested in reptiles since childhood, she originally moved to Texas to join a lab that was studying turtles. Unfortunately, only a few weeks in, the grant money supporting her position fell through – right after she moved from Wisconsin to Texas! Luckily, another researcher invited her to join a lab studying snakes. After earning her Master’s degree, Kaitlyn continued this work during her PhD with her collaborator, Anne.

Kaitlyn and Anne wanted to understand how these snake populations are surviving today, especially after years of severe drought in California. They wondered if survival rates had changed over time and whether snakes in lakeshore and meadow habitats survived differently.

Scientists standing on a rocky lakeshore looking for snakes.
Flipping rocks and reaching into stinging nettle at Lakeshore sites.

To answer these questions, Anne and Kaitlyn wanted to take a fresh look at snake survival rates. They went out into the field to collect their own data, and compared their estimates to over 50 years of prior data collection. Both the historic and current data were collected using the method called capture-mark-recapture. In this method, researchers catch snakes, measure traits like size and weight, and give each snake a unique mark before releasing it back into the wild. If a snake is caught again later, scientists can track how it has grown. Not all snakes are recaptured. These data can be used to estimate survival rates, though some snakes may have moved away or avoided being caught.

Because it is hard to know the exact age of each snake, Kaitlyn grouped them into four age classes based on size: neonates (newborns), juveniles, young adults, and old adults. She then used statistical models to use her capture-mark-recapture dataset to estimate the probability of survival for each group. Kaitlyn predicted that meadow snakes, with their “slow” life history strategy, would have higher survival rates than lakeshore snakes. She also expected this difference to be greatest in young snakes.

Featured scientists: Kaitlyn Holden (she/her) and Anne Bronikowski (she/her) from Michigan State University

Flesch–Kincaid Reading Grade Level = 9.4

Additional Teacher Resources:

  • Scientist profile: Anne Bronikowski has a scientist profile to supplement this activity. Have students read more about her research, personal life, and career advice as a way to share contemporary scientist role models with students!
  • You can learn more about the IISAGE (Integration Initiative: Sex, Aging, Genomics, and Evolution) project here. This initiative is a collaborative effort to learn more about the mechanisms of sex-specific differences in aging and features research with a variety of organisms.
  • Visit this page for additional scientist profiles and Data Nuggets featuring IISAGE research.
6.7.21

Blinking out?

A researcher collects data from a yellow sticky card at the MSU KBS LTER site. Photo Credit: K. Stepnitz, Michigan State University.

The activities are as follows:

The longest surveys of fireflies known to science was actually started by accident!

At the Kellogg Biological Station Long-Term Ecological Research Site, scientists work together to answer questions that can only be studied with long-term data. Their focus is to collect data in the same way over many consecutive years to look for patterns through time. One of these long-term studies, looking at lady beetle populations, was developed to keep watch on these important species. To count lady beetles, scientists placed yellow sticky card traps out in the same plots year after year. These data are used to figure out if lady beetle numbers are changing over time.

Because sticky traps catch everything small that flies by, other insect species get stuck as well. One day, a research technician noticed this and decided to add a few new columns to the data sheet. That way they could start recording data on the other insect species found on the sticky traps. Each year the technician kept adding to the record and over time, more and more data were collected. One of those new columns happened to record the number of fireflies caught. Though the exact reason for this data collection is lost to history, scientists quickly realized the value of this dataset! 

Several years later, Julia became the lab technician. She took over the responsibility of the sticky trap count, adding to the dataset. Christie joined this same lab as a scientist and stumbled upon the data on fireflies that Julia and the previous technician had collected. She wanted to take advantage of the long-term data and analyze whether firefly populations had been increasing or decreasing. 

Many people have fond memories of watching fireflies blink across open fields and collecting them in jars as children. This is one of the reasons why fireflies are a beloved insect species. Julia grew up in southwest Michigan and fondly recalls spending summers watching them blink over yards and open fields, catching them in jars to watch them for a little while. Christie did the same in her parent’s yard in rural Ontario! That fondness never really went away and both enjoy watching the fireflies around Northeast Ohio where they currently live. Fireflies are also an important part of the ecosystems where they live. Larvae spend most of their time in the soil and are predators of insects and other small animals, such as snails. 

All the insects collected on a yellow sticky card trap over the course of one week. Photo credit: Elizabeth D’Auria, Michigan State University.

Many scientists and citizens alike have noticed that they aren’t seeing as many fireflies as they used to. Habitat loss and light pollution could be causing problems for fireflies. This is where the importance of long-term data really comes into play. Long-term data are critical to identifying and understanding natural population cycles over long periods of time that we wouldn’t be able to see with just a few years of data. It also gives scientists opportunities to answer unanticipated research questions. In this situation, even though the data were collected without a specific purpose in mind, having the dataset available offered new opportunities! Christie and Julia were able to look at the long-term changes in southwest Michigan firefly populations, something they would not have been able to do before the research technician added those extra columns. In order to start answering this question, they compiled all of the years of firefly data and began to compare the average counts from year to year. Although data were collected in multiple different habitat types, they focused on data from open fields because fireflies use these areas to find mates.

Featured scientists: Christie Bahlai and Julia Perrone from Kent State University. Data from the Kellogg Biological Station Long Term Ecological Research Program – KBS LTER

Flesch–Kincaid Reading Grade Level = 10.7

Additional teacher resources related to this Data Nugget include: