- A study using detailed 3D imagery found that the carbon released by roads, selective logging, fires and natural disturbances in the southern Brazilian Amazon are not fully reflected in the country’s carbon emissions reporting.
- The high-resolution findings are thought to be unprecedented, offering precision insights into major land use changes that ultimately impact climate change.
- Indigenous and protected areas in the Amazon show significantly less degradation, highlighting their effectiveness in preserving carbon storage.
- Authors and experts say the new data could help policymakers rethink rainforest emission targets and plan conservation efforts.
Forest degradation — access roads, selective logging, fires, natural disturbances — is having a far greater impact on reducing carbon storage in the southern Brazilian Amazon than deforestation, according to a new study that has produced some of the most precise findings of changes in carbon stocks in a critically important region of the tropics.
In real terms, forest degradation reduced carbon storage in the study area five times more than deforestation, a finding not currently reflected in Brazil’s carbon emissions accounting.
“When countries report their forest and carbon changes, they mostly rely on deforestation because it’s much easier to see and quantify,” Ovidiu Csillik, lead author who is formerly of the NASA Jet Propulsion Laboratory at the California Institute of Technology, told Mongabay. “But we’ve found that forest degradation is actually more important in terms of carbon loss.”
Analyzing and comparing data from 2016 and 2018 in Brazil’s so-called Arc of Deforestation and covering 48,280 hectares (119,300 acres), a team of international experts divided the region into 99 transects. They used repeated flyovers of airborne lidar, a remote laser sensor technology that registers objects in three dimensions and obtains detailed data, to produce two vast data sets, according to the study published in the National Academy of Sciences’ journal, PNAS.
The high-resolution findings are thought to be unprecedented, offering precision insights into major land use changes that ultimately impact climate change. Lidar data also enable carbon storage estimates in biomass and soils.
“While the effects of deforestation on carbon loss have been thoroughly researched,” the study notes, “the carbon impact of forest degradation is not well understood and is difficult to quantify accurately at large scale. Degradation is more spatially dispersed than deforestation, expanding the frontiers of forest loss.”
The researchers note that degradation usually leads to deforestation with almost half of tropical forests cleared in subsequent years, according to the study. While degraded land has the potential to be restored over time, deforestation typically heralds a permanent land-use change like farming and ranching.
The findings are significant at multiple levels, according to experts. The Amazon, 64% of which lies in Brazil, is a major carbon storage source and a frontline defense against the increasing rate of global warming. But dramatic rates of deforestation in the past five decades are diminishing the Amazon’s ability to sequester and store carbon. Understanding more precisely what’s driving such changes can lead to new or improved strategies to reduce both forest degradation and deforestation, according to the authors.
It can also lead tropical countries to report forest-based carbon sequestration and emissions more accurately, which is essential for effective climate mitigation strategies and policies.
“The vulnerability of tropical forests to climate change, including more frequent and severe droughts, as well as increased susceptibility to fires, further intensifies the degradation of these forests, resulting in accelerated carbon losses and ecosystem disruptions,” the authors write.
A detailed understanding
Csillik, a remote-sensing expert, said the data used in the study had gone unanalyzed since their completion in 2016 and 2018. Joining the Jet Propulsion Laboratory in 2022, he was tasked with comparing two of the largest data sets of intensive airborne lidar over a tropical forest ever compiled.
“Besides quantifying the carbon dynamics, or losses and gains, at a very high resolution with repeated airborne lidar, we also took the study a bit further and presented a detailed understanding of what the drivers are behind these carbon losses,” he said.
In degraded land, for example, natural and human-driven occurrences such as landslides, flooding, wind-related tree toppling, isolated logging and forest fragmentation all stood out clearly in the lidar data as carbon-loss sources that had previously gone largely unnoticed or unaccounted for.
“Forest degradation is often difficult to quantify and monitor because it occurs in subtle ways that are not easily detectable through conventional remote sensing methods and in places where access on the ground may be controlled by landowners conducting illegal or irregular activities,” the study notes.
Marcos Longo, a co-author and climate and ecosystem scientist at the Lawrence Berkeley National Laboratory in California, told Mongabay the study “is an important snapshot of what has happened in the recent past” in Brazil. But he said an even deeper understanding of tropical land changes will require new and longer-term remote-sensing research.
“I think that with the development of technology we now have, like lidar on the International Space Station, we can start building this long-term understanding of forest degradation in tropical ecosystems,” Longo said. NASA’s Global Ecosystem Dynamics Investigation, or GEDI, is now onboard the space station.
Prioritizing Indigenous and protected areas
The research also found that Indigenous territories and conservation units were effective in protecting the forest against anthropogenic degradation, echoing past studies. “While combined they occupied 47.5% of the area [studied], they only contained 9.1% of clearing, 2.6% of logging and 9.6% of fires,” the authors note.
Ecology and evolutionary biology professor Scott Saleska said the new study reveals unique data on forest degradation drivers in the southern Brazilian Amazon. In 2000, Saleska, a University of Arizona professor, was involved in some of the first small-scale lidar surveys in the Amazon. While Brazil is part of his study field, he was not involved in the PNAS study.
And while his own focus is on basic research, he said he can imagine practical or policy outcomes stemming from the findings, such as greater enforcement of existing forest-protection regulations.
“The other thing that stands out is the prioritization of conservation and preservation,” Saleska told Mongabay. “This study gives an impressive look at the effectiveness of conservation areas and Indigenous regions for saving forests because those areas are clearly shown to have the least impact. They appear effective at actually preventing logging and fire at an impressive scale.”
Given his interest in the issues and the Brazilian Amazon, Saleska added that the new study “provides a template, a model for taking this kind of research to a larger scale. We have so many more tools at our disposal to measure the CO2 in the atmosphere to figure out which places in the Amazon, over broad regions, are losing carbon or gaining carbon.”
Banner image: Fire in an area newly deforested in Brazil. Fire also contributes to forest degradation throughout the tropics, especially in the study area of the southern Brazilian Amazon. Image © Christian Braga / Greenpeace.
Justin Catanoso is a regular contributor to Mongabay and a professor of journalism at Wake Forest University in North Carolina in the United States. Disclosure: the study’s lead author, Ovidiu Csillik, joined the Wake Forest environmental sciences faculty in July.
Citation:
Csillik, O., Keller, M., Longo, M., Ferraz, A., Pinage, E., Gorgens, E., Ometto, J., Silgueiro, V., Brown, D., Duffy, P., Cushman, K., Saatchi, S. (2024) A large net carbon loss attributed to anthropogenic and natural disturbances in the Amazon Arc of Deforestation. PNAS, Vol. 121, No. 33. doi:10.1073/pnas.2310157121
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