If a tree falls in a forest and no one is around to hear it, does it make a sound? This question has engaged philosophers through the ages in discussions regarding observation and the knowledge of reality. Scientists in the PhenoCam Network are also interested in what goes on in forests when no one is around to observe them but are less interested in the presence or absence of noise as trees fall but in knowing the timing of when trees flower, leaf, or fruit. They have found a relatively simple and clever way to record what is going on with plants via a network of digital cameras, called PhenoCams, mounted on platforms at various locations around the world. PhenoCams take photos every 30 minutes, thus capturing the different stages, or phenophases, of the plant life cycle. These data are then made available to scientists to better understand how climate change might impact the timing of these stages. But, the PhenoCam network is about more than just taking pictures. It also provides learning opportunities. Katie Bennett, a 5th grade teacher, has been engaged with the PhenoCam network for several years through teacher programs offered at Harvard University. With a PhenoCam now located at her school in Massachusetts, she uses the study of phenology to help introduce students to more complex, but related, environmental issues such as climate change. “My students had been tracking the growing season for years by watching individual trees in our schoolyard through Project Budburst. As part of the PhenoCam network, we can compare our trees to the whole canopy and to other regions as well.”
The PhenoCam network now consists of 290 cameras globally and produces over 6,000 images a day! This is how YOU, as a citizen scientist, can help! To date, approximately 7,000 participants have made over 105,000 image classifications. And, although the project has come a long way, there are still many more images to be classified. For this reason, the project will be launching its first ever Spring Challenge on March 7 to assist researchers in classifying over 9,000 images of spring. With the images classified, researchers will be able to determine the exact start and end dates of spring at various locations and how variation in weather and climate are affecting those dates now and into the future. They can also compare the results from Season Spotter with satellite imagery so that the start and end of spring can be better detected around the world. Interested in contributing? Visit Season Spotter to get started!
