Welcome back!
The topic for this week is the effect climate change has on phenology.
You might be asking yourself, “What is phenology?”.
Well it`s your lucky day because I have the answer for you! According to USGS.gov, phenology is defined as “the study of the influence of climate on the timing of biological events, such as annual plant flowering and seasonal bird migration”. Phenology is often referred to as natures calendar as it studies reoccurring plant and animal life stages.
First, I`m going to discuss some graphs that depict long-term temperature trends before leading to the discussion of temperatures effect on bee and orchid pollination. The values from my scatter plots come from the United Kingdom Meteorological Office which recorded mean monthly temperature data from three cities: London, Bristol, and Preston. The monthly temperature data from 1659-2016 was downloaded by researchers from the UK Meteorological Office to determine how average temperature has changed over the span of 350 years.
For those of you that don`t live for the rush of reading scientific graphs I will explain what the graphs mean and why they are important. As you will notice from my scatter plots, the year is on the x-axis and the average temperature is on the y axis. Is it important which variable goes where? You betcha! I can hear my high school teacher lecturing in my ear that the “independent” variable goes on the x-axis while the “dependent” variable goes on the y-axis. Therefore, the year is the independent variable whereas the average temperature is the dependent variable. Now that we have that sorted, let`s move on to interpreting the trend line.
The trend line indicates that the annual temperature has increased over time. The trend line shows that the average temperature rose from roughly 8.75°C in 1659 to 9.75°C in 2009. A rise in average annual temperature by 1°C in a span of 350 years isn`t that bad, right? Wrong! If the Earths age (4.5 billion years) was compressed into a 12-month period, 350 years would be equivalent to 2.4 seconds. Therefore, a rise in temperature by 1 °C in the span of 2.4 seconds is very dramatic. The trend line indicates that the average temperature has increased from February- April in a similar pattern. The average temperature being roughly 5.1°C in 1659 and rose to 6.4°C by 2009. Again, a rise is seen in average temperature from March-May. Average temperature being 7.8°C in 1659 and rises to 8.8°C by 2009.
What does this mean?
According to NASA, this increase in temperature is due to “a change driven largely by increased carbon dioxide and other human-made emissions into the atmosphere”. Most of the warming in this 350-year span occurred in the past 35 years.
Next, let`s look at the correlations in the average temperature (Feb – April) vs. year and average temperature (March – May) vs. year scatter plots. The coefficient of determination (R²) is defined by StatTrek as the proportion of the variance in the dependent variable (average temperature) that is predictable from the independent variable (year). The scatterplot depicting average temperature from February-April has a coefficient of determination that equals 0.087 while the scatterplot depicting average temperature from March-May has a coefficient of determination that equals 0.101. Now what does this mean? The graph that depicts the strongest relationship between temperature and year is the latter. The higher the coefficient of determination is, the stronger the relationship between the independent and dependent variable is. The R2 value of 0.087 for average temperature from February-April means that 8.7% of the variance in average temperature is predictable by the year. While the R2 value of 0.101 for average temperature from March-May means that 10.1% of the variance in average temperature is predictable by the year.
Scatter plots are a great way to study climate change. Next up is another scatter plot exemplifying a great topic of phenology; bees and their duty to pollinate flowers.
The Early Spider Orchid (Ophrys sphegodes) is pollinated by the Solitary Bee (Andrena nigroaenea). These orchids use sexual deception to attract pollinators. They accomplish this by producing the female bees sex pheromones as well as by looking and feeling like a female bee. This orchid basically catfishes the male bee to become pollinated. I`ll just leave this meme right here….

The peak flowering dates, periods with the highest number of flower observation, were determined for each year. Researchers examined records of the flight dates for the Solitary Bee to understand how the timing of the bee reproduction aligns with peak flowering dates. I used this data to create this scatter plot of bee arrival time vs orchid flowering time to understand the impact climate change has. Glancing at the graph it can be determined that there is a mismatch in the two events which is caused by the increasing temperatures mentioned previously.

Looking more in depth at the scatter plot it can be seen that at 7°C the timing of the arrival of bees has basically ended while the peak flowering time has barely begun. This means that the bees are arriving earlier than the orchids peak flowering time. Therefore, less orchids will be pollinated. At 10°C the timing of the arrival of bees ended 2°C ago while the peak flowering time has just ended. This means there is a period of time where the flowers are not being pollinated by the bees. The scatter plot helps to visualize the offsetting of this bee arrival time and peak orchid flowering time. These bar graphs are another way to visually see the orchid/bee issue. These bar graphs, with error bars, look at comparing peak orchid flowering times and the years as well as bees first flight and the years.
The bar graphs show that orchid flowering time decreases drastically from the beginning of the century (1848-1900) to the end of the century (1954 – 2006) while bee activity decreases less drastically from the beginning of the century to the end. Using the data from the graph, it can be extrapolated that continued increases in global temperature might affect the reproductive success of the orchid in a negative way. The peak flowering time decreased dramatically from the beginning of the century to the end therefore, a negative trend will likely continue.
These practical examples show how phenology is all around us and why it is such an important field of study. Phenology is important because it affects whether plants and animals will survive in their environments which can affect the ecosystem around them.
![Cicada_Molting[1]](https://ecology.home.blog/wp-content/uploads/2018/09/cicada_molting1.jpg?w=1100)
What could cause this?
The answer is climate change. According to Keith Clay, a biologist and cicada expert at Indiana University Bloomington, in the article Brood Awakening: 17-year Cicadas Emerge 4 Years Early, “cicada nymphs may be growing to a threshold size so quickly that their internal biological clock is miscalculating when it is time to emerge”. The rising temperatures cause the soil to be warmer which miscalculates the biological clocks of the cicadas, causing them to emerge early.
This pattern could be explained best using a scatter plot showing how the temperature has affected the early emergence of the periodical cicadas. Although climate change should not be ruled out, alternatives to this hypothesis need to be considered such as destruction/disruption of habitat, change in soil, or evolution of cicada social structure.
Although there is so much evidence for the existence of climate change, especially the part humans have played in it, the majority of Americans are skeptical about the entirety of climate change or certain aspects of it. According to a peer reviewed journal by Alexis Hannart called Probabilities of Causation of Climate Changes stated that ‘‘It is extremely likely that human influence has been the dominant cause of the observed warming since the mid-20th century”. As I stated in my previous blog, science is about ignorance and curiosity. We would not have science with neither ignorance nor curiosity therefore we must ignite curiosity in those ignorant on certain topics so there can be effective communication between scientists and non-scientists. Although there are challenges involved with communicating to the general public about a climate change. Some people are not receptive to science as they`d rather believe in a certain religion or deity, while others may chose not to accept the theory of climate change as it would be accepting the fault of humanity in contributing to it. A way to address some of these concerns would be to communicate effectively with the audience and ensure them that believing in climate change neither negates their religion nor blames them as an individual for the change in climate. Also mentioning certain climate change impact examples that the general public has probably experienced such as droughts, early emergence of cicadas, or rising water levels would be a great way to get a dialogue started and ignite curiosity.
To conclude I`d like to restate the importance of understanding phenology and the impact climate change has on it. While some people may hope they can just close their eyes and will climate change to disappear, that simply won`t happen. We need to think consciously about our actions and their ecological consequences. A better tomorrow starts with us today!
![giphy[1]](https://ecology.home.blog/wp-content/uploads/2018/09/giphy1.gif?w=1100)
“Read, Learn, Inspire”
Until next time!
~Courtney Hattaway-Burchett

