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. 2023 Feb;29(4):1062-1079.
doi: 10.1111/gcb.16516. Epub 2022 Nov 16.

Climate and socioeconomic drivers of biomass burning and carbon emissions from fires in tropical dry forests: A Pantropical analysis

Rogelio O Corona-Núñez  1   2   3 , Julio E Campo  1
Affiliations

Climate and socioeconomic drivers of biomass burning and carbon emissions from fires in tropical dry forests: A Pantropical analysis

Rogelio O Corona-Núñez et al. Glob Chang Biol. 2023 Feb.

Abstract
in English, Spanish

Global burned area has declined by nearly one quarter between 1998 and 2015. Drylands contain a large proportion of these global fires but there are important differences within the drylands, for example, savannas and tropical dry forests (TDF). Savannas, a biome fire-prone and fire-adapted, have reduced the burned area, while the fire in the TDF is one of the most critical factors impacting biodiversity and carbon emissions. Moreover, under climate change scenarios TDF is expected to increase its current extent and raise the risk of fires. Despite regional and global scale effects, and the influence of this ecosystem on the global carbon cycle, little effort has been dedicated to studying the influence of climate (seasonality and extreme events) and socioeconomic conditions of fire regimen in TDF. Here we use the Global Fire Emissions Database and, climate and socioeconomic metrics to better understand long-term factors explaining the variation in burned area and biomass in TDF at Pantropical scale. On average, fires affected 1.4% of the total TDF' area (60,208 km2 ) and burned 24.4% (259.6 Tg) of the global burned biomass annually at Pantropical scales. Climate modulators largely influence local and regional fire regimes. Inter-annual variation in fire regime is shaped by El Niño and La Niña. During the El Niño and the forthcoming year of La Niña, there is an increment in extension (35.2% and 10.3%) and carbon emissions (42.9% and 10.6%). Socioeconomic indicators such as land-management and population were modulators of the size of both, burned area and carbon emissions. Moreover, fires may reduce the capability to reach the target of "half protected species" in the globe, that is, high-severity fires are recorded in ecoregions classified as nature could reach half protected. These observations may contribute to improving fire-management.

El área global quemada se redujo en casi una cuarta parte entre 1998 y 2015. Los bosques secos contienen una gran proporción de esos incendios globales, pero existen diferencias importantes dentro de ellos, por ejemplo, las sabanas y los bosques secos tropicales (SBC). Las sabanas, son un bioma propenso y adaptado al fuego, y que en los últimos años han reducido su área quemada. Mientras que el fuego en la SBC es uno de los factores más críticos que impactan la biodiversidad y las emisiones de carbono. Además, bajo escenarios de cambio climático, se espera que la SBC aumente su extensión actual y aumente el riesgo de incendios. A pesar de los efectos a escala regional y global, y la influencia de este ecosistema en el ciclo global del carbono, se le ha dedicado poco esfuerzo a estudiar la influencia del clima (estacionalidad y eventos extremos) y las condiciones socioeconómicas del régimen de incendios. Aquí usamos la base de datos global de emisiones de incendios y métricas climáticas y socioeconómicas para comprender mejor los factores a largo plazo que explican la variación en el área quemada y la biomasa a escala Pantropical. En promedio, los incendios afectaron el 1,4% del área total de la SBC (60 208 km2 ) y quemaron el 24,4% (259,6 Tg) de la biomasa global quemada anualmente a escala Pantropical. Los moduladores climáticos influyen en gran medida en los regímenes de incendios locales y regionales. La variación interanual del régimen de incendios está determinada por El Niño y La Niña. Durante El Niño y el año subsecuente de La Niña, se produce un incremento en la extensión (35,2% y 10,3%) y en las emisiones de carbono (42,9% y 10,6%). Los indicadores socioeconómicos como la gestión de la tierra y la población fueron moduladores del tamaño tanto del área quemada como de las emisiones de carbono. Además, los incendios pueden reducir la capacidad de alcanzar el objetivo de “protección de la mitad de las especies” en el mundo, es decir, los incendios de alta gravedad se registran en ecorregiones clasificadas como naturaleza que podría alcanzar la protección de la mitad de su biodiversidad. Estas observaciones pueden contribuir a mejorar la gestión de incendios.

Keywords: El Niño/southern oscillation; La Niña; burned area; carbon emissions; climate and socioeconomic drivers; drought; fire; human factors.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

FIGURE 1
FIGURE 1
Time series of burned area (top row), burned biomass (middle row) and relationship between burned area and burned biomass (bottom row) between 1997 and 2020 at pantropical scale (a–c), and hemisphere partitioning (d–i). In the top and middle rows, the red line and shading refer to the mean ± 1 SD. In bottom row the red line expresses the regression line with the 95% confidence interval, with the year of each observation indicated in red. **Color online only.
FIGURE 2
FIGURE 2
Mean burned areas (a–c) and burned biomass (e–g) between 1997 and 2020 at pantropical scale, and hemisphere partitioning. Boxplots of the seasonality of burned areas (d) and burned biomass (h) in the pantropic. Different uppercase letters represent clusters of the monthly observations with statistically differences (p < .05).
FIGURE 3
FIGURE 3
Distribution of burned area, burned biomass, and fuel consumption as the proportion of burned biomass in relation to the fuel load in (I) Neotropics including the regions Caribbean Islands, Central America, and Mexico (CEAM), northern hemisphere South America (NHSA) and southern hemisphere South America (SHSA), (II) Afrotropic containing the region southern hemisphere Africa (SAHF), (III) equatorial Asia (EQAS), and (IV) Southeast Asia (SEAS) between 1997 and 2020. Color bars show the magnitudes for the mean and its standard deviation. White background refers to NoData. Top row refers to the (a) mean and (b) standard deviation of burned area in hectares, while middle row expresses the (c) mean and (d) standard deviation of burned biomass in gg and the bottom row presents the (e) mean ratio of the burned biomass in relation to fuel load (this panel is complemented with Figure 4c). The bottom figure cannot be expressed with a standard deviation due to lack of annual fuel loads data, consequently mean burned biomass refers to the mean of the period 1997–2020. In all cases, the information relates to a grid cell of 0.25° and they are the result of the multiple‐year aggregation (1997–2020). **Color online only. Map lines delineate study areas and do not necessarily depict accepted national boundaries.
FIGURE 4
FIGURE 4
Tropical dry forest burned area (a), burned biomass (b), burned biomass density (the ratio of burned biomass and burned area) (c), and proportion of burned biomass in relation to the fuel load (d). Pantropical regions are the Caribbean Islands, Central America, and Mexico (CEAM); equatorial Asia (EQAS); northern hemisphere South America (NHSA); southern hemisphere Africa (SAHF); Southeast Asia (SEAS); and southern hemisphere South America (SHAS). Different uppercase letters represent clusters of the regional observations with statistically differences (p < .05).
FIGURE 5
FIGURE 5
Principal components analysis biplots of the biophysical and socioeconomic influencers of burned area. Green symbols mean burned areas from 0.1 to 5000 ha; red symbols mean burned areas >5000 to 10,000 ha; lilac symbols mean burned areas >10,000 to 30,000 ha. For abbreviations see Table S2. In Table S6 are reported all the objects in the spaces of the first three principal components. In Figure S7 is included a correlation matrix. **Color online only.
FIGURE 6
FIGURE 6
Principal components analysis biplots of the biophysical and socioeconomic influencers of burned biomass. Green symbols mean burned biomasses from 0.1 to 100 gg; red symbols mean burned biomasses >100 to 500 gg; lilac symbols mean burned biomasses >500 to 1000 gg; pink symbols mean burned biomasses >1000 to 2000 gg. For abbreviations see Table S2. In Table S6 are reported all the objects in the spaces of the first three principal components. In Figure S7 is included a correlation matrix. **Color online only.
FIGURE 7
FIGURE 7
Boxplots of the influence of climatic anomalies on mean burned area and burned biomass between 1997 and 2020 at Pantropical scale. Regular refers to years without extreme climatic events (“No El Niño or La Niña year”). El Niño and La Niña refers to the climatic anomalies such as warm and cold global episodes based on a threshold of ±0.5°C for the Oceanic Niño Index (NOAA, 2021). Lagged refers to the forthcoming year after La Niña year. Different uppercase letters represent clusters with statistically differences (p < .05).
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