If you have a garden, there’s a good chance it is filled with signs of climate change, though they might not always be what you would expect.
It seems obvious that as global temperatures increase, flowers might be inclined to bloom earlier. But Will Pearse, an assistant professor in Utah State University’s Department of Biology, had a hunch that the effects of a changing climate could be more profound.
So Pearse, who has a background in evolutionary ecology, used unconventional statistical techniques to show that flowering plants may indeed be struggling to adapt — not just blossoming earlier in some cases but becoming less consistent overall in when they bloom. Those findings were published Monday in the journal Nature Ecology & Evolution.
“Our work provides new insights into how human activities have altered today’s climate by contrasting the time a flower bloomed in the past to observation in the present-day,” Pearse said in a statement.
The USU scholar doesn’t typically study flowers. But for years he had heard his mother, an avid gardener, and other friends talk about how their tulips came up early one year, but not the next. The connection between early tulip blooms and warming temperatures might be obvious, but Pearse theorized that climate change could also be causing the late bloomers, as well.
Thanks to the efforts of gardeners and citizen scientists across the globe, there is a plethora of data available about flowering plants, Pearse said. The U.S. National Phenology Network, for example, maintains a database of bloom data from all over the nation, dating back to its founder, Henry David Thoreau.
And through standard analysis of that data, scientists could tell that plants around the world were, on average, blooming earlier than they used to. Flowers opened about 2.5 days earlier in 2015 than in 2009, according to their study.
But a standard statistical analysis alone could not discern whether plants are becoming more variable in when they bloom, partly because those statistical techniques are not that good at dealing with the kind of variability scientists were trying to measure.
Likening the analysis to a study of school test scores, a basis statistical model might plot students’ scores to form a bell-shaped curve, with the average score somewhere in the middle and most students’ grades forming a bulge within that range.
Some scores will deviate from the norm, but there will be fewer students on either extreme — known as “outliers” — as scores grow larger or smaller than the average.
Pearse and other scientists studying climate change theorized that the number of plant outliers — plants that bloom much earlier or much later than other plants — was increasing. Essentially, they worried that the bell curve on plant blooming was flattening out.
Why does this concern scientists? Human-caused climate change is causing the earth to warm at a much faster rate than it has in the past. Plants and animals are able to adapt to changes in their environments, but only if those changes come about slowly. A sudden increase in temperature might outstrip a species’ ability to adjust, causing it to die off in large numbers.
Pearse tested the data on plant blooming using a technique typically used to analyze fossils to determine when a species went extinct. By doing this, he said, he and his colleagues found that plants’ life cycles have indeed become more variable — a finding that held true across multiple datasets.
That suggests, Pearse said, that climate change is pushing plants to the limits in terms of how early they can bloom and produce fruit.
Contributing authors on the study included Charles Davis, Harvard University; David Inouye, University of Maryland and Colorado’s Rocky Mountain Biological Laboratory; Richard Primack, Boston University; and T. Jonathan Davies of Canada’s McGill University. The research was backed by the National Science Foundation and the USA National Phenology Network.
The USU scholar stressed that more research is needed to verify those findings. He said he felt compelled to publish his results to “flag this so more people would look at it.” His methodology could apply to more than just flowers, Pearse added. Other researchers have already begun to use it to analyze bird migration data, and insect hatching.
Pearse said his next research project involves using analysis of plant data to develop a model for predicting when plants will bloom should the climate continue to warm — an important tool to help humans adapt to climate change, given that most people food starts out as a flower.