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. 2024 Jul 16;14(1):16414.
doi: 10.1038/s41598-024-67244-x.

Spatial heterogeneity in climate change effects across Brazilian biomes

Adriano Braga #  1 , Márcio Laurini #  2
Affiliations

Spatial heterogeneity in climate change effects across Brazilian biomes

Adriano Braga et al. Sci Rep. .

Abstract

We present a methodology designed to study the spatial heterogeneity of climate change. Our approach involves decomposing the observed changes in temperature patterns into multiple trend, cycle, and seasonal components within a spatio-temporal model. We apply this method to test the hypothesis of a global long-term temperature trend against multiple trends in distinct biomes. Applying this methodology, we delve into the examination of heterogeneity of climate change in Brazil-a country characterized by a spectrum of climate zones. The findings challenge the notion of a global trend, revealing the presence of distinct trends in warming effects, and more accelerated trends for the Amazon and Cerrado biomes, indicating a composition between global warming and deforestation in determining changes in permanent temperature patterns.

Keywords: Climate change; Local climate change; Spatial heterogeneity; Spatio-temporal models; Structural time series.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Brazil biomes. The figure shows the spatial delimitation of the six Brazilian biomes analyzed.
Figure 2
Figure 2
Trend components. The figure shows the posterior mean and a 95% credibility interval for the estimated trend components for each biome, for the sample period 1961–2023. Trend components are defined on a weekly frequency.
Figure 3
Figure 3
Seasonal and cycle components. The figure shows the posterior mean and a 95% credibility interval for the estimated seasonal and cycle components for each biome, for the sample period 1961–2023. Trend components are defined on a monthly frequency.
Figure 4
Figure 4
Active days by station–Pantanal. The figure shows the number of active days for each Station in Pantanal Biome.
Figure 5
Figure 5
Spatial random effects. The figure shows the posterior average of the estimated spatial random effects. These effects are obtained as a spatially continuous projection of the Matérn spatial covariance function.
See this image and copyright information in PMC

References

    1. Ellery M, Scholes W, Mentis RJ. An initial approach to predicting the sensitivity of the South African grassland biome to climate change. S. Afr. J. Sci. 1991;87(10):499–503. doi: 10.10520/AJA00382353_7196. - DOI
    1. Hansen AJ, et al. Global change in forests: Responses of species, communities, and biomes: interactions between climate change and land use are projected to cause large shifts in biodiversity. Bioscience. 2001;51(9):765–779. doi: 10.1641/0006-3568(2001)051[0765:GCIFRO]2.0.CO;2. - DOI
    1. Salazar LF, Nobre CA, Oyama MD. Climate change consequences on the biome distribution in tropical South America. Geophys. Res. Lett. 2007 doi: 10.1029/2007GL029695. - DOI
    1. Salazar LF, Nobre CA. Climate change and thresholds of biome shifts in Amazonia. Geophys. Res. Lett. 2010 doi: 10.1029/2010GL043538. - DOI
    1. de Oliveira G, Araújo M B, Rangel T F, et al. Conserving the Brazilian semiarid (Caatinga) biome under climate change. Biodivers. Conserv. 2012;21(12):2913–2926. doi: 10.1007/s10531-012-0346-7. - DOI

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