hide
Free keywords:
-
Abstract:
Fire is widely used by farmers in Brazil during the winter, or the dry season, to remove accumulated dead pasture biomass. These practices have substantial impacts on vegetation, soil nutrients and carbon emissions. However, they are rarely represented within process-based fire models embedded within Dynamic Global Vegetation Models (DGVM). We developed an algorithm named Chalumeau to estimate the expected burning dates from daily precipitation or temperature depending on the seasonality type. By coupling with a fire module from a DGVM, Chalumeau enables the ignition of fire as an essential part of modelling fire practices. The burning dates are evaluated by comparing against observed fire dates on pasture. From these estimated dates, we extract the timing strategies of ranchers, which vary regionally within Brazil. This study confirms that climatic conditions are the main trigger for farmers decisions to set fire and shows the different burning strategies across Brazil.
