NRES 105 Lab 4 Instructions

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University of Illinois, Urbana Champaign *

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105

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Geography

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Apr 30, 2024

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pdf

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14

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Module 6 Lab Exercise: Climate Change and Phenology Introduction Climate change as a result of anthropogenic greenhouse gas (GHG) emissions is evident in both climatological and biological data. While global temperatures have increased by 0.74°C ± 0.18°C over the past 100 years (1906-2005), some regions experience locally greater warming (IPCC 2007). Along with this average increase in temperature, extreme weather events including extreme heat have become more common. The 10 warmest years on record have all occurred since 2005, and 2020 tied 2016 as the warmest year on record. Scientists use long-term climate (for example, see Figure 1) and biological datasets to assess past and current rates of warming and the impacts of warming on key ecosystem functions. These analyses provide crucial information for the prediction of future impacts of warming as we continue to release massive quantities of GHGs into the atmosphere. One clear biological indicator of climate change is phenology, or the timing of key life events in plants and animals. Phenological events are diverse and include the timing of flowering, mating, hibernation, and migration among many others. Generally, phenological events are strongly driven by temperature, with warmer temperatures typically resulting in earlier occurrence of leaf out, springtime migration, insect emergence from dormancy, and reproductive events. Shifts in phenology in the direction predicted by climate change have been observed worldwide, suggesting that climate change is already having profound, geographically extensive impacts on ecology (Parmesan & Yohe 2003, Menzel et al. 2006, Rosenzweig et al. 2008). In this lab, you will be analyzing long-term temperature data collected in Ohio by the U.S. Historical Climatology Network ( http://cdiac.ess-dive.lbl.gov/epubs/ndp/ushcn/ushcn.html ) to establish temperature trends in Ohio over the past 115 years. You will then investigate temperature effects on the flowering of six plant species and the arrival and emergence times of two pollinator species to determine biological signals of climate change in Ohio. There are four parts to this lab exercise: • Part 1: Regional Long-term Temperature Trends • Part 2: Statewide Long-term Temperature Trends • Part 3: Biological Indicators of Climate Change: Flowering Time • Part 4: Biological Indicators of Climate Change – Butterfly Emergence and Hummingbird Arrival Time Make sure to complete all of the questions on the lab answer sheet.
NRES 105 Phenology Lab 2 DIVISION 1 – DIVISION 10 TABS Part 1: Regional Long-term Temperature Trends An important component of climate change studies is the analysis of temperature change over long timescales in the region of interest. For our analysis of Ohio, you will assess temperature change across the entire state as well as at smaller, regional scales. The U.S. Historical Climatology Network (USHCN) has collected temperature and precipitation data at 26 weather stations throughout Ohio since 1895 (Figure 2). The number of USHCN weather stations is limited as USHCN stations are required to have a consistent, non-urban location since 1895; this eliminates urban heat island effects (urbanized areas that are hotter than surrounding rural areas, U.S. EPA) and latitudinal/altitudinal effects. Changes in the location of weather stations can cause apparent increases or decreases in temperature as a result of moving to a generally warmer or cooler location. These possible altitudinal or latitudinal effects are eliminated in the USHCN climate record by requiring consistent station locations since the start of data collection. Using the mean of temperatures recorded at all 26 weather stations in Ohio, we can evaluate statewide trends in temperature since 1895. To assess regional trends in temperature, we can use the ten climate divisions in Ohio established by the National Oceanic and Atmospheric Administration (NOAA, see Figure 2). Examine the data file in Excel that you downloaded. The temperature record for each climate division is given in separate worksheets . Each climate division worksheet includes two columns: [Year] provides the year in which the temperature data were collected, and [Temp (deg C)] provides the springtime temperature for that year in degrees Celsius. The temperatures for a division were calculated by averaging the temperature records for every USHCN weather station in that division for the year of interest from February to May (spring temperatures). For example, Division 1 temperatures are the mean Feb - May temperatures of USHCN weather stations A, B, and C (Figure 2). Below, we provide step-by-step instructions for plotting temperature by year and quantifying the annual rate of change in temperature using the Division 1 data. You will repeat these steps for Divisions 3 and 9. First, record your answer to the following question on the Lab 4 answer sheet: 1. Explain how you would determine temperature change from 1895-2009 for a climate division. In your answer, address the following questions: What type of graph would be useful and why? What statistical procedure could you use to quantify the rate of temperature change?
NRES 105 Phenology Lab 3 CREATE LINE GRAPH OR SCATTER PLOT CLICK SELECT DATA To plot temperature by year, select the [Temp (deg C)] column and create a line graph (or a scatter plot if you prefer) as shown below . To change the x-axis to represent years, right click on the plotted data in the graph and left click on Select Data…
NRES 105 Phenology Lab 4 Now, click on Edit in the Horizontal (Category) Axis Labels Box, then select the data in rows 2 to 116 from the [Year] column as shown below on the right and click OK: Make sure that your plot includes the temperature data from 1895 - 2009. To calculate the annual rate of change, add a trend line to the graph by right clicking the data again and left clicking Add Trendline… and make sure to display the equation and R-squared value.
NRES 105 Phenology Lab 5 Make your graph look presentable by adding a title and labeling the axes appropriately. Our final graph for the Division 1 dataset looks like this after cleaning it up: Now, plot temperature by year for Divisions 3 and 9 and determine the annual rate of change ( o C/year) for each dataset. The annual rate of change is the same as the slope of the line and is equivalent to the coefficient for the ‘x’ variable, which is ‘year’ in this case. In the example above, you will notice that the arrow is pointing to the slope in the linear equation. This value indicates that temperature changes by 0.0113°C every year. This is a positive number, which means temperature is increasing at this rate on average. A negative number would indicate that the temperature was decreasing by this rate on average. Copy and paste your graphs for each climate division, and record your answers to the following questions on the lab answer sheet: 2. What is the rate of temperature change for Divisions 3 and 9? 3. Compare and contrast the results for Division 1 to the results for Divisions 3 and 9: Is temperature increasing, decreasing, or remaining stable in the climate divisions? Do the divisions show similar trends or are they different? What are some possible explanations for this?
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