Meghan Blumstein studied red oak genotypes across New England, concentrating on trees that were within reach in Cambridge, Massachusetts. She then collaborated with people doing research at the Harvard Forest, a research forest in rural central Massachusetts. Credits: Courtesy of the researchers Leafing in temperate trees is crucial for climate models, as small shifts can significantly impact warming predictions. Researchers often study urban heat islands, which are warmer than rural areas, to understand plant responses to higher temperatures. However, an MIT study suggests that urban heat islands are unreliable for predicting the effects of global warming. This is partly due to the limited genetic diversity of urban tree species, leading to misunderstandings of warming impacts. Des Marais’ group primarily conducts research in tightly controlled lab settings, regulating temperature, humidity, and carbon dioxide levels. While a few field experiments use heaters to modify conditions around individual trees, these setups are minimal in scale. Des Marais said, “When you’re looking at these longer-term trends that are occurring over space that’s quite a bit larger than you could reasonably manipulate, an important question is, how do you control the variables?” Des Marais and his students have explored temperature gradients to study tree responses to warming. However, they’ve also turned their attention to genetics, comparing urban tree species to the same species found in nearby natural forests. Interestingly, they discovered genetic differences even among trees that looked alike. While the model assumes only the temperature difference between urban and rural areas is changing, an overlooked factor is the genetic diversity of the trees. This unaccounted genotypic variation adds complexity to the findings, revealing that temperature alone doesn’t fully explain the differences observed. Genetic differences showed that the urban trees studied were not representative of natural ones, masking the true impact of warming. Urban […]
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