Influence of fire foci on forest cover in the Atlantic Forest in Rio de Janeiro, Brazil

Freitas, Welington Kiffer de; Góis, Givanildo de; Pereira, Edimir Andrade; Junior, J.F. Oliveira; Magalhães, Luís Mauro Sampaio; Brasil, F.C.; Sobral, Bruno Serafini

doi:10.1016/j.ecolind.2020.106340

Cited by 17 publications

(4 citation statements)

References 46 publications

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“…In Brazilian tropical forests, fires disproportionately affect LULC types, with pastures and croplands being the most likely to burn (Abreu et al, 2022;Cano-Crespo et al, 2015;de Assis Barros et al, 2022;de Santana et al, 2020;Freitas et al, 2020;Gutiérrez-Vélez et al, 2014;Herrmann et al, 2023;Uriarte et al, 2016). Conversely, a negative correlation is expected between fire occurrence and spread and the cover of oldgrowth forests (de Assis Barros et al, 2022;Fonseca et al, 2019;Singh & Huang, 2022).…”

Section: Introductionmentioning

confidence: 99%

Relative fire-proneness of land cover types in the Brazilian Atlantic Forest

Adorno,

Piratelli,

Hasui

et al. 2024

Preprint

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Fires have long posed a global problem, but they are now increasingly affecting tropical biomes where landscape-fire interactions remain understudied. We investigate the fire-proneness of different land use and land cover types (LULCs) within the Brazilian Atlantic Forest (AF), one of the world's most important biodiversity hotspots, experiencing increased fire frequency due to human activities and climate change. Using a selection ratio-based approach, we analyzed fire-LULC interactions in 40,128 fires over a 35-year period (1987-2022) across various vegetational regions in the AF, evaluating the relative fire-proneness of different LULCs in a tropical biome for the first time. Our findings revealed that secondary forests, forest areas that have regrown after major disturbances, burned 61% more than expected by chance, whereas old-growth forests, native forests that have developed over very long periods, burned 57% less than expected, highlighting a nearly inverse relationship in their fire-proneness. Interestingly, our data indicate that pastures in the AF are less prone to fire than expected, despite being considered among the land uses that burn the most in Brazil. Other LULCs showed variable fire-proneness, with some differences between vegetational regions. Over time, the fire-proneness of secondary forests decreased, likely due to forest maturation and changes in land management practices. We emphasize the necessity for tailored fire management strategies that address the unique vulnerabilities of secondary forests, particularly in the context of ongoing restoration efforts aimed at increasing native forests. Effective measures, including the implementation of fire-smart management practices and enhancing the perceived value of secondary forests among local communities, are crucial for mitigating fire risks. Integrating these strategies with incentive-based approaches can bolster fire prevention, ensuring the long-term success of restoration programs. Our study provides a framework for understanding fire-landscape dynamics in tropical forests and offers actionable insights for practitioners working to safeguard these biomes from the escalating threat of wildfires.

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Section: Introductionmentioning

confidence: 99%

Relative fire-proneness of land cover types in the Brazilian Atlantic Forest

Adorno,

Piratelli,

Hasui

et al. 2024

Preprint

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“…Despite the importance of the Atlantic rainforest and fire threat, studies on impacts of disturbances such as burnings over this biome are scarce [17,[18][19][20][21][22][23][24]. In Brazil, burning is forbidden as a management tool (unless under environmental permission or when done by traditional communities: [25,26].…”

Section: Introductionmentioning

confidence: 99%

The relationship between forest fire and deforestation in the southeast Atlantic rainforest

et al. 2023

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Given the scarcity of studies relating fire to deforestation in the Atlantic Forest and great economic and ecological importances of this biome, this work aimed to investigate this relationship in the Atlantic Forest of the State of São Paulo, trying to answer whether deforestation is related to fire events in up to three years, if there are regions most affected by this relationship and what land use and land cover predominates after fire and deforestation in these areas. The study was carried out in Evergreen Forest and Semideciduous Seasonal, along the time series from 2000 to 2019 using the MapBiomas Project database to survey deforested and burned sites with moderate to high severity fires. Burning positively influenced deforestation in EGF in eight of 19 years studied (2001, 2004, 2005, 2007, 2008 and 2009, 2013 and 2015), while only for three years in the SSF. Burning followed by deforestation corresponded to only 3.2% of the total deforestation, located mainly in the eastern region of the state with the highest density in the EGF. Most of these areas have been converted to agriculture. This study provides the first indication that, generally, fire is not a driver of deforestation in the southeast Atlantic Forest.

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“…Some scholars have recently concentrated their fire prediction research on wildfire occurrence time series and spatial distribution. Spatial and temporal variation have an impact not only on vegetation productivity [22] and vegetation cover patterns [23,24], but also on fuel moisture [25], wind conditions, and fuel loadings [26]. Numerous experiments have established a positive association between seasonal variations in meteorological variables and long-term fire activity throughout the year [19].…”

Section: Introductionmentioning

confidence: 99%

Wildfire Prediction Model Based on Spatial and Temporal Characteristics: A Case Study of a Wildfire in Portugal’s Montesinho Natural Park

Dong

Wu²,

Sun

et al. 2022

Sustainability

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Wildfires influence the global carbon cycle, and the regularity of wildfires is mostly determined by elements such as meteorological conditions, combustible material states, and human activities. The time series and spatial dispersion of wildfires have been studied by some scholars. Wildfire samples were acquired in a monthly series for the Montesinho Natural Park historical fire site dataset (January 2000 to December 2003), which can be used to assess the possible effects of geographical and temporal variations on forest fires. Based on the above dataset, dynamic wildfire distribution thresholds were examined using a K-means++ clustering technique for each subgroup, and monthly series data were categorized as flammable or non-flammable depending on the thresholds. A five-fold hierarchical cross-validation strategy was used to train four machine learning models: extreme gradient boosting (XGBoost), random forest (RF), support vector machine (SVM), and decision tree (DT). Finally, to explore the performance of those we have mentioned, we used accuracy (ACC), F1 score (F1), and the values for the area under the curve (AUC) of the receiver operating characteristics (ROCs). The results depicted that the XGBoost model works best under the evaluation of the three metrics (ACC = 0.8132, F1 = 0.7862, and AUC = 0.8052). The model performance is significantly improved when compared to the approach of classifying wildfires by burned area size (ACC = 72.3%), demonstrating that spatiotemporal heterogeneity has a broad influence on wildfire occurrence. The law of a spatiotemporal distribution connection in wildfires could aid in the prediction and management of wildfires and fire disasters.

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Influence of fire foci on forest cover in the Atlantic Forest in Rio de Janeiro, Brazil

Cited by 17 publications

References 46 publications

Relative fire-proneness of land cover types in the Brazilian Atlantic Forest

Relative fire-proneness of land cover types in the Brazilian Atlantic Forest

The relationship between forest fire and deforestation in the southeast Atlantic rainforest

Wildfire Prediction Model Based on Spatial and Temporal Characteristics: A Case Study of a Wildfire in Portugal’s Montesinho Natural Park

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