Predicted deforestation in Brazil could lead to local temperature increase up to 1.45°C
IMAGE: Scheme depicting presumed relationships between forest cover and climatic variables (albedo and evapotranspiration). view more
A new model quantifies how forest change affects local surface temperatures by altering sunlight-reflection and evapotranspiration properties, and predicts that Brazilian deforestation could result in a 1.45°C increase by 2050, in a study published March 20, 2019 in the open-access journal PLOS ONE by Jayme A. Prevedello from the Rio de Janeiro State University, Brazil, and colleagues.
Forests are known to reflect less sunlight and have higher evapotranspiration than open vegetation, meaning that deforestation and forestation could affect local land surface temperature. However, until recently there were limited high-resolution global data. The authors of the present study used a global dataset from 2000-2010 to quantify impacts of forest change on local temperatures. They used newly-released data on forest cover, evapotranspiration rates, sunlight-reflection and land surface temperature and built a model to quantify the relationship between these variables for tropical, temperate, and boreal regions.
The authors found that deforestation and forestation generally appeared to have opposite effects of similar magnitude on local temperature. However, the nature of the effect and the magnitude of the temperature change depended on latitude: in tropical and temperate regions, deforestation led to warming, while forestation had cooling effects. In boreal regions, deforestation led to slight cooling, though the magnitude of the effect was smaller. The magnitude of the forest change effects was greatest in tropical regions, with, for example, deforestation of approximately 50 percent leading to local warming of over 1°C.
The authors used their model to predict local temperature change in Brazil between 2010 and 2050. Assuming the current rate of illegal deforestation is maintained, this predicted an annual land surface temperature rise of up to 1.45°C in some areas by 2050. However, if no further illegal deforestation occurred, the temperature rise could be far more limited.
This new model quantifies the effect of forest change on local surface temperatures, through changes in sunlight-reflection and evapotranspiration. The authors note that their Brazil case study “illustrates that current land use policies can impact future local climate.”
The authors add: “Forestation has the potential to reverse deforestation impacts on local climate, especially in tropical and temperate regions.”
Peer-reviewed; Modelling study; People, Environment
Citation: Prevedello JA, Winck GR, Weber MM, Nichols E, Sinervo B (2019) Impacts of forestation and deforestation on local temperature across the globe. PLoS ONE 14(3): e0213368. https:/
Funding: JAP was supported by grants from Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (processes n. E-26/010.002334/2016 and E-26/010.000398/2016) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq; process n. 424061/2016-3); GRW received a post-doctoral fellowship and a technical grant (INCT/DTI-B) from CNPq (processes n. 151984/2016-6, 381247/2017-1), and currently receives a post-doctoral fellowship grant from CNPq (process n. 206876/2017-3); MMW received a post-doctoral fellowship grant from Programa Nacional de Pós-Doutorado from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (PNPD/CAPES, process number 1594913). BS was supported by an Emerging Frontiers grant from NSF (EF-1241848) and a Pesquisador Visitante Especial (PVE) scholarship from CNPq. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
In your coverage please use this URL to provide access to the freely available article in PLOS ONE: http://journals.
Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.