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For the people who live in the thousands of subsistence communities around the world, climate change is already affecting how they hunt, farm, and even where they can live. Yet their experiences—their on-the-ground observations of how the environment is changing—are not generally considered by mainstream climate science. But now, a new, unprecedented data set suggests that those experiences are well worth listening to.
Valentina Savo, an ecologist and ethnobotanist at Simon Fraser University, spent more than a year compiling peoples’ accounts of air and water temperatures, rainfall, wind patterns, floods, and animal movements into one massive data set. The observations, 10,660 in all, were drawn from previous research on subsistence communities in 137 countries.
(Savo’s research is supported by a grant from the Tula Foundation, which also funds Hakai Magazine and the Hakai Institute. The magazine is editorially independent of the institute and foundation.)
Savo and her colleagues compared those observations against data gathered in the same regions by more conventional methods, such as weather stations, and against the historical simulations of climate models. The researchers found that the peoples’ accounts often track closely with the sensors’ readings.
“With temperature, for example, we had an almost 100 percent match,” Savo says, meaning that when people said they observed temperature changes, the models also showed a change in that location. For rainfall data, there were more regional mismatches. But here, Savo sees opportunity: perhaps the peoples’ accounts are showing small-scale changes in precipitation patterns that are too fine-grained to show up in large-scale climate models.
Savo suggests that scientists could use the new data set to supplement their information in sparsely monitored places like the Himalayas. It could also flag problems that instruments may not have picked up.
“Look at the places where there are some problems, where people are starting to see changes, and [climate modelers] are not seeing changes,” Savo says. “This would be a stimulus to do more research in those areas.”
Faron Anslow, a climatologist at the University of Victoria who was not involved in the new research, says he can see these observations informing climate models similar to the way in which other indirect measurements, such as the ratios of oxygen isotopes in ice cores, have been used to reconstruct conditions thousands of years ago, before weather stations or temperature gauges existed.
Anslow also agrees that rainfall patterns are spatially complex even at small scales. “Those patterns are very difficult for models to simulate,” he says.
The data set is a testament to the observational skills of those who live closely with the land. But actually integrating the collected observations into mainstream climate science—which is largely quantitative and based on complex numerical climate models—is thorny.
Part of the problem, of course, is that it’s difficult to compare numbers to experiences in a meaningful way. For example, interviewers recording a subsistence farmer’s account of a drought can ask what approximate decade he recalls it happening in, yielding data that can pinpoint the event within about 10 years. Savo says that while such strategies are useful, they are also limited: not all communities mark time the same way. For instance, the farmer may refer to an event, such as a local tribal war, as a marker of time rather than to specific years. It’s theoretically possible to use that kind of technique to turn memory into quantitative data, Savo says, but not always.
John Fyfe, a senior research scientist with Environment and Climate Change Canada, says that Savo and her colleagues make a very convincing case for using non-traditional sources of information to augment temperature and precipitation records.
“I can see a lot of scope for climate scientists using these alternative sources of information to fill in the blanks where direct observations do not exist,” Fyfe says, adding that these observations might also give information on variables that are socially relevant, but may not be measured with conventional instruments.
For the moment, Savo and her team are hoping that this data set can ultimately lead to a deeper understanding of climate change and its impacts.
“In the future, in a perfect world, I would like to see this qualitative data have the same value as data from gauging stations,” Savo says. “These people are well aware of what’s happening.”