Land use reduces carbon in plants, soils
FILE PHOTO: An aerial photo of a palm oil plantation in Batanghari, Jambi province, Sumatra island, Indonesia November 28, 2018. Antara Foto/Wahdi Septiawan/via REUTERS
Ludwig-Maximilians-Universität München – Human activities, such as deforestation and the expansion of agricultural areas, have a massive impact on the natural state of ecosystems. As a result, large amounts of carbon are released into the atmosphere, contributing substantially to anthropogenic climate change.
A team led by geographer Raphael Ganzenmüller from Ludwig-Maximilians-Universität München in Munich, Germany has calculated that human influence has reduced natural land carbon stocks by a total of 24 per cent – which corresponds to 344 billion tonnes of carbon.
By combining high-resolution Earth observation data with historical and current land use data and machine learning, the team created a detailed global estimate. The researchers were also able to show that most of the loss is caused by the expansion of pasture and croplands, as well as forest management.
“Our study reveals the far-reaching human impact on the global carbon cycle,” Ganzenmüller explained. “The deficit of 344 billion tonnes of carbon is comparable in size to global carbon dioxide emissions from coal, oil and natural gas over the past 50 years. Our approach provides a clear picture of where and how vegetation and soils have been degraded and can be used as a general indicator of the state of ecosystems.”
Julia Pongratz, Professor of Physical Geography and Land Use Systems at LMU, added, “Our study provides important insights for climate policy. For example, the findings can be used to evaluate carbon removal measures. Moreover, they underscore the great potential of restoring carbon stocks on land to achieve global climate goals.”
The findings are relevant for both policymakers and scientists: They provide an important basis for prioritizing the conservation and restoration of carbon sinks and offer opportunities to improve existing climate models and their projections.