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More than 1,000 Forest Service employees staff work out of greenhouses, laboratories and cabins in urban and in rural offices near the 193 million acres of national forest and grassland that the agency manages. The employees work on a range of projects, from restoring native trees in Hawaii after invasive species take over to learning how to prevent wildfires in Montana. Those projects often include local partners like Camp Small, Forest Service employees said, and theirs is the largest forestry research network in the world. But on March 31, the Forest Service announced a reorganization of the agency that would close facilities used for research, including the one in Baltimore. Three days later, President Donald Trump's 2027 budget proposed allocating $0 for Forest Service research, down from $309 million in 2026. More than 100 facilities are now being evaluated for potential closure, according to an NPR analysis. "The research being done is hyperlocal. It's unique to the landscapes that it's supporting and then also the data sets that are in each of these buildings," said a current Forest Service scientist. "Closing these offices is going to result in the loss of irreplaceable data sets, which contain just vital information that has been gathered." Some of the science the agency does is not optional. The agency's Forestry Inventory Analysis program is mandated by Congress to collect data to assess the condition of forests in the United States. This move will effect hundreds of local jobs. About one third of all Forestry Inventory Analysis staff work at facilities being evaluated for closure, according to Forest Service research scientists. Many of those scientists have said they will not remain with the agency if their projects are terminated. Most of these projects are extremely inexpensive to run, because staff are local and the government owns many of the properties and facilities. Many others are rented for as little as $1 per year. This move will cost government employees jobs and create a loss of critical scientific data, while also forcing the government to spend more money to produce the same data through other means. This is a massive waste of monetary resources, critical scientific data, and skilled scientists.