4.6 Article

Impacts of Land Use Change and Atmospheric CO2 on Gross Primary Productivity (GPP), Evaporation, and Climate in Southern Amazon

Journal

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2021JD034608

Keywords

dynamic global vegetation models (DGVMs); atmospheric CO2 elevated; climate changes; Amazon

Funding

  1. SAO PAULO STATE RESEARCH FOUNDATION (FAPESP) [2017/03048-5]
  2. National Council for Scientific and Technological Development (CNPq) [301084/2020-3, 317980/2021-1]
  3. ANPCyT, Argentina [PICTs 2017-1406, 2018-02511]
  4. CLIMAX-FAPESP-BELMONT [2015/50687-8]
  5. FAPESP [2017/22269-2]

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Recent publications suggest that the Amazon Rainforest may act as a carbon source rather than a carbon sink in certain regions, and deforestation may reduce its role as a moisture supplier to other areas. This study used dynamic global vegetation models to analyze the impacts of elevated CO2 and land use change on primary productivity and evaporation in the southern Amazon. The results indicate that increased CO2 levels may offset the effects of deforestation, leading to an increase in primary productivity, while land use change reduces evaporation.
Recent publications indicate that the Amazon may be acting more as a carbon source than a sink in some regions. Moreover, the Amazon is a source of moisture for other regions in the continent, and deforestation over the years may be reducing this function. In this work, we analyze the impacts of elevated CO2 (eCO(2)) and land use change (LUC) on gross primary productivity (GPP) and evaporation in the southern Amazon (7 degrees S 14 degrees S, 66 degrees W 51 degrees W), which suffered strong anthropogenic influence in the period of 1981-2010. We ran four dynamic global vegetation models (DGVMs), isolating historical CO2, constant CO2, LUC, and potential natural vegetation scenarios with three climate variable data sets: precipitation, temperature, and shortwave radiation. We compared the outputs to five observational data sets obtained through eddy covariance, remote sensing, meteorological measurements, and machine learning. The results indicate that eCO(2) may have offset deforestation, with GPP increasing by similar to 13.5% and 9.3% (dry and rainy seasons, respectively). After isolating the LUC effect, a reduction in evaporation of similar to 4% and similar to 1.2% (dry and rainy seasons, respectively) was observed. The analysis of forcings in subregions under strong anthropogenic impact revealed a reduction in precipitation of similar to 15 and 30 mm, and a temperature rise of 1 degrees C and 0.6 degrees C (dry and rainy seasons, respectively). Differences in the implementation of plant physiology and leaf area index in the DGVMs introduced some uncertainties in the interpretation of the results. Nevertheless, we consider that it was an important exercise given the relevance.

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