Climate Change & Butterfly Phenology

A monarch butterfly (Danaus plexippus) feeding on the nectar of a bog sage plant (Salvia uliginosa) at the Brooklyn Botanic Garden. Wikimedia Commons, CC BY-SA 4.0 [https://commons.wikimedia.org/wiki/File:Monarch_butterfly_(70387).jpg]

Overview

In this activity we'll explore connections between climatic and biological data sets to ask whether climate change is affecting butterfly phenology.

Background Material


Objectives 

Students should be able to


Introduction

Phenology is the study of the timing of cyclical events in an organism's life cycle, such as the flowering of plants, emergence of worker bees from the hive, or the migration of birds. The timing of critical life stages can be triggered by external environmental cues such as seasonal changes in temperature, precipitation, or photoperiod (day length).

As global weather patterns alter or fluctuate due to climate change, an organism's phenology may shift in response to a change in these cues. For example, spring temperatures are becoming warmer in recent decades due to climate change, resulting in many plants and animals starting their spring activities earlier than they used to. 

On one hand, it's encouraging that many organisms are responding to rapid changes in their environment. However, when species respond at different rates it can disrupt ecological relationships. Mutualistic relationships between plants and animals can be disrupted if they have different sensitivities to warming spring temperatures. For example, if a host plant is able to shift its phenology to track warmer springtime temperatures but its pollinating insect can't respond at the same rate, they may end up out of synch with each other. This is known as a phenological mismatch, and it can have dire consequences. The plant may lose pollination service and not be able to reproduce, and the pollinating insect may lose its food source (nectar from flowers). Phenological mismatches can occur between any interacting organisms such as predators and prey, diseases and hosts, or competitors exploiting a shared resource. 

To study the impacts of climate change on phenology we need to examine long-term historical patterns and trends in both the environmental conditions and phenologies of the species of interest. We need current and historical data on when and where species occur, the timing of phenological events (e.g. emergence, flowering dates, peak flight), and key environmental variables that can initiate phenological transitions (e.g. temperature, precipitation). This means we need long-term data for both the organisms we study and the ecosystems they occupy. Fortunately, we are in the data rich era of science! Environmental data and data from natural history collections, professional scientists, amateur naturalists, and long-term weather stations provide the information that is necessary to investigate phenological changes.

The role of natural history collections in studying climate change

Natural history collections data are based on a physical specimen that was collected by a scientist, carefully preserved, and stored in a museum, university, or research collection space, much like books in a library. These collections serve as warehouses for all kinds of biological data such as phenology, taxonomy, evolution, and ecology of the species. Each specimen has information beyond the physical object itself. A specimen contains valuable metadata (e.g., collection date, location, habitat, images) and is accessible for repeatable, iterative, and expanded observations when physical verification is needed, new questions arise, or new investigative techniques are developed. 

Recent technological advances allow researchers to use specimens to study past biological phenomena such as molecular variation, historical environmental conditions, presence of environmental toxins, and host-parasite assemblages. Many of these specimens were collected far before some of these technologies were created! This highlights the importance of systematically collecting and storing information for current and future uses. 

Natural history collections provide a source of biodiversity data that is unequaled in temporal, geographic, and taxonomic complexity and unique in its ability to allow researchers to verify and expand the data by returning to the physical specimens on which they are based. Further, these data can be combined with other data sources to inform research questions. For example, climate data can provide information on historic temperature and precipitation, citizen science observations can provide contemporary species occurrence information, and genetic data can provide information about evolutionary history.

Scientific classification 

In today's lab activity, you'll see several scientific names for different butterfly species. There are over 1 million organisms on the planet that have been named and described, with an estimated 10 million more species yet to be discovered. With all of this diversity, it's important to have a standardized way of classifying and naming organisms. An important aspect of ecological research, especially with natural history collections, is understanding how the Linnaean classification system works.

The scientific classification system used today was developed in the early 1700s by Carl Linnaeus. Taxonomy, the scientific field that classifies organisms, remains an active area of research as new genetic technologies allow scientists to continually improve the accuracy of their classifications. The basic hierarchy of groups (taxa) is shown here, ranging from kingdom (the most broad or inclusive taxon) to species (the most specific taxon). 

The most frequently used part of this naming system is the genus and species, also known as binomial classification. In writing, the binomial is always italicized with the genus capitalized and species in lowercase. For example, the binomial for the Monarch butterfly is Danaus plexippus, and the binomial for the Canadian tiger swallowtail is Papilio canadensis.

Image showing hierarchy of scientific classification
Climate Change & Butterfly Phenology (virtual)

Methods

Here, we’ll use the earliest collection date of butterfly museum specimens as a proxy for their phenology. That is, the date that the adult butterfly was collected signifies a date that the butterfly was in flight. The relatively short lifespan of butterflies allows us to use their collection date to study how their phenology may have changed over time and relative to abiotic variables such as temperature. Today we’ll use data from an online natural history collections database, iDigBio. This database provides us the opportunity to peek into the past, in this case as far back as the 1930s, to see the species, dates, and localities of butterflies that were collected. The inspiration for this activity comes from butterfly phenology research conducted by Kharouba and Vellend (2015) using specimens collected in British Columbia, Canada.

Part 1: Evaluate the published research

Use the article search tool on the Baruch library homepage to obtain the Kharouba & Vellend (2015) article on the phenology of butterflies and their host plants.  

Read the article and answer the questions below.

Part 2: Analyze the data & interpret the trends 

The data set shown below is a portion of Kharouba & Vellend's data from their 2015 article. It includes climate data and butterfly phenology data from British Columbia, Canada. 

Butterfly Phenology Climate Change data set for students

Download the data set and make a copy for yourself.  Explore the spreadsheet (note it contains multiple tabs).  Then complete the following activities and answer the related questions.

4.  Data from how many weather stations are compiled in the Temp Data?  Hint: Check out the Metadata tab!

5.  How many butterfly species are in the Butterfly Data?  Hint: try to use the UNIQUE function.

6.  Understanding the details of the data, where they come from, and what they represent is a critical part of data management. What is the term for these “data about data”?

7.  Create a scatterplot of average annual temperature vs. year for British Columbia. Add a trendline including its equation and R2 value (refer to the Summarizing Data lab activity to review these concepts). Based on the trendline, how has annual temperature changed over time in British Columbia?

8.  Natural history collections are rich repositories of biodiversity data. We can use information from specimen labels to compile data about phenology. Specifically, the date that a butterfly specimen was collected represents a day during which the butterfly was in flight. Create a scatterplot of butterfly flight date vs. year.. Add a trendline including its equation and R2 value. How has the phenology of these butterflies shifted over time? Use the trendline equation to provide a quantitative estimate.

9.  How does your estimate of phenological shift from Question 8 compare to the estimate from Kharouba and Vellend that is provided in Table 1 of their article? Why is this?

10.  You may be surprised by your anwser to questions 8 and 9.  Let's consider a different relationship.  Create a scatterplot of the day of year vs. mean spring temperature and add a trendline including its equation and R2  value. Repeat with mean summer temperature instead of spring. Based on your graphs, how does the phenology of butterflies relate to temperatures in each season? Use the trendline equations to provide quantitative estimates and the R2 to describe how well the data fit the trendline. 

11. Did your results from  questions 8-9 and 10 match?  Why or why not?  Remember, science isn't always easy, and results are not always clear!  We will return to some of these questions later in the class.

12.  Is the change in temperature the cause of the changes in phenology? Why or why not?

13.  Kharouba and Vellend found that the host plants are more sensitive to temperature than the butterflies. Using the figure and values you derived in Question 8 as a reference, describe how a plot of the phenology of temperature-sensitive plants vs. temperature would compare to your butterfly plot.

14.  How would you recognize if a phenological mismatch were possible between butterflies and their host plants? Describe how this would look when plotted.

15.  During which periods of time were there the greatest numbers of collected specimens? When were there the least? How might this impact the analysis?

16.  As a follow-up to the previous question, what other types of data could provide you with additional information on butterfly flight times, particularly in recent years?

References

This activity is adapted from: Debra Linton, Anna Monfils, Molly Phillips, and Elizabeth R. Ellwood. March 2018. The Effect of Climate Change on Butterfly Phenology. Teaching Issues and Experiments in Ecology, Vol. 13: Practice #7 [online]. http://tiee.esa.org/vol/v13/issues/data_sets/ellwood/abstract.html