the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Effects of fire and grazing on biogeochemical cycles in Brazilian pastures using LPJmL5-Pasture-Burning
Abstract. Farmers across the world frequently use fire during the winter or dry season, to remove accumulated dead pasture biomass. These fire-management practices have profound effects on vegetation, soil nutrients, and biogeochemical cycles, yet they are rarely represented in process-based fire models embedded within Dynamic Global Vegetation Models (DGVMs). We couple the Chalumeau algorithm, which estimates expected burning dates, with the SPITFIRE module in the DGVM LPJmL and enable the modelling of fire as a grassland management method. Using this model development, we examine the short- and long-term impacts of varying burning strategies, frequencies, and livestock densities across distinct regions, using Brazil as a case study. Our results show that integrating grazing and fire management leads to a gradual decline in vegetation carbon, accompanied by a substantial reduction of the ecosystem and soil nitrogen. This study emphasises the importance of incorporating such practices into DGVMs to enhance the accuracy of impact assessments for pasture management. Furthermore, our findings call for improved data collection describing fire usage methods by farmers, as well as long-term measurements, particularly on vegetation, soil carbon and nitrogen development under burning practices.
Competing interests: Kirsten Thonicke is associate editor Biogeosciences
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RC1: 'Comment on egusphere-2025-922', Anonymous Referee #1, 17 May 2025
In this manuscript, the authors describe how they implemented an algorithm for pasture burning date into the LPJmL dynamic global vegetation model (DGVM). This sort of development is really important—ranchers in many parts of the world exert a strong influence on the frequency and timing of fire in grasslands, which can make a big difference on ecosystem dynamics. Most DGVMs have no such representation of fire management practices, especially an endogenous one (as opposed to one prescribed from input files). While it seems that other data limitations prevent this feature from being commonly used in general LPJmL runs, this capability is an important first step.
The authors do not just describe the technical capability, however. They also use the updated model to assess the separate and joint impacts of management fire and grazing on ecosystem carbon and nitrogen. The results show that both processes are important to represent in DGVMs.
I’m very happy to see a manuscript like this. The paper is mostly written well, and the figures are mostly good, with interpretations mostly well-supported. However, I have a major methodological concern along with a number of smaller questions and suggestions.
See attachment for details.
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AC1: 'Reply on RC1', Marie Brunel, 10 Aug 2025
We thank the reviewer for their thorough and constructive feedback. We are pleased that the methodological contribution of this study and the relevance of integrating fire and grazing management into LPJmL were appreciated. In attachment, we provide a point-by-point outline of how we plan to address each of the reviewer’s comments in the revised manuscript.
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AC1: 'Reply on RC1', Marie Brunel, 10 Aug 2025
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RC2: 'Comment on egusphere-2025-922', Pritha Pande, 07 Jul 2025
This manuscript presents a timely and relevant study that integrates a pasture-burning date algorithm into the LPJmL5 dynamic global vegetation model to assess the coupled impacts of fire and grazing on ecosystem carbon and nitrogen cycling in Brazilian grasslands. Using Chalumeau algorithm for climate-driven, management-based fire timing represents a valuable methodological advancement, particularly in regions where human land use plays a dominant role in shaping fire regimes. The paper is well-motivated, generally well-written that emphasize the interplay between grazing pressure, burning frequency, and biogeochemical feedback.
However, the study also has important limitations that should be more clearly acknowledged. Chief among these is the absence of any experimental or observational data used for model calibration or validation, despite the strong claims made about nitrogen and C: N dynamics. Additionally, several key biogeochemical processes—such as nitrogen recycling via manure and biological nitrogen fixation—are either under-described or not quantitatively supported. Such issues do not undermine the value of the study as a modelling exploration. However, they must be addressed more explicitly. Please see my detailed comments in the attached.
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AC2: 'Reply on RC2', Marie Brunel, 10 Aug 2025
We thank the reviewer for their thoughtful and constructive comments, which help us improve the clarity, transparency, and scientific robustness of the manuscript. We appreciate the recognition of the methodological contribution and relevance of our study. In the attachment, we outline how we plan to address each of the specific comments in the revised version of the manuscript.
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AC2: 'Reply on RC2', Marie Brunel, 10 Aug 2025
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