Future projections for terrestrial biomes indicate widespread warming and moisture reduction in forests up to 2100 in South America

Anjos, Luciano J S; Souza, Everaldo Barreiros de; Amaral, Calil Torres; Igawa, Tassio Koiti; Toledo, Peter Mann de

doi:10.1016/j.gecco.2020.e01441

Cited by 21 publications

(16 citation statements)

References 53 publications

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“…a similar approach to calculate future projections was used by Anjos et al (2021), Maksic et al (2022) and Zevallos and Lavado-Casimiro (2022), respectively, for the whole South America, Brazil and Peru.…”

Section: /24mentioning

confidence: 99%

“…However, ensemble modeling is known to provide more advantages than using individual machine learning models, since ensemble models reduce model uncertainty and are more robust towards extrapolation (Bonannella et al, 2022;Mehra et al, 2019). For future projections, "ensemble datasets" are more common than ensemble models: climate is assumed to be the major driving force for large-scale vegetation patterns (Whittaker and Marks, 1975); starting from this assumption, multiple studies create the training dataset by averaging together temperature and precipitation values as calculated by different Global Circulation Models (GCM) simulations (Beigaitė et al, 2022;Anjos et al, 2021).…”

Section: /24mentioning

confidence: 99%

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Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation

Bonannella¹,

Hengl²,

Parente³

et al. 2023

Preprint

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The global potential distribution of biomes (natural vegetation) was modelled using 8959 training points from the BIOME 6000 dataset and a stack of 72 environmental covariates representing terrain and the current climatic conditions based on historical long term averages (1979–2013). An ensemble machine learning model based on stacked regularization was used, with multinomial logistic regression as the meta-learner and spatial blocking (100 km) to deal with spatial autocorrelation of the training points. Results of spatial cross-validation for the BIOME 6000 classes show an overall accuracy of 0.67 and R2logloss of 0.61, with ”tropical evergreen broadleaf forest” being the class with highest gain in predictive performances (R2logloss = 0.74) and ”prostrate dwarf shrub tundra” the class with the lowest (R2logloss = -0.09) compared to the baseline. Temperature-related covariates were the most important predictors, with the mean diurnal range (BIO2) being shared by all the base-learners (i.e. random forest, gradient boosted trees and generalized linear models). The model was next used to predict the distribution of future biomes for the periods 2040–2060 and 2061–2080 under three climate change scenarios (RCP 2.6, 4.5 and 8.5). Comparisons of predictions for the three epochs (present, 2040–2060 and 2061–2080) show that increasing aridity and higher temperatures will likely result in significant shifts in natural vegetation in the tropical area (shifts from tropical forests to savannas up to 1.7 × 105 km2 by 2080) and around the Arctic Circle (shifts from tundra to boreal forests up to 2.4 × 105 km2 by 2080). Projected global maps at 1 km spatial resolution are provided as probability and hard classes maps for BIOME 6000 classes and as hard classes maps for the IUCN classes (6 aggregated classes). Uncertainty maps (prediction error) are also provided and should be used for careful interpretation of the future projections.

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Section: /24mentioning

confidence: 99%

Section: /24mentioning

confidence: 99%

Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation

Bonannella¹,

Hengl²,

Parente³

et al. 2023

Preprint

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“…Since when uncontrolled forest exploitation occurs, deforestation increases and this leads to profound changes in the con gurations of the primary balance between the biomass of current forests and the climate on a continental scale, decisively affecting their structure, operation and the respective internal feedbacks of these ecosystems. (Anjos et al 2021).…”

Section: Discussionmentioning

confidence: 99%

“…However, deforestation in the world has increased; there has been a net loss of 7 million hectares of forest per year in tropical countries and a net increase in agricultural land of 6 million hectares per year. The greatest deforestation occurred in low-income countries, due to an increase in rural population (Anjos et al 2021;Mataveli et al 2021). The situation of the forests in Ecuador does not escape this reality.…”

Section: Introductionmentioning

confidence: 99%

Sustainable forest use of legal origin in the province of Napo Amazonia Ecuador

Espinosa

Aguirre-Mejía

Villota-González

et al. 2022

Preprint

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The study proposes to analyze the legal use of forest resources in the province of Napo Ecuador during the period of 2011–2015. The data collected was analyzed in three stages: secondary information gathering, systematization of information and interpretation of results. Thereafter, based on the stated objectives, it was possible to obtain: the analysis of legal forest use by program type, plant formation and species used during different years, and the volume of legal forest use. Based on interviews directed to local stakeholders involved in the forestry sector, it was possible to analyze the factors that have influenced the legal use of forest resources. The highest rate for legal forest use was concentrated in simplified forest harvesting programs. Forest utilization in native forest represents 43.62%, in which the year 2011 showed the greatest increase for legal forest use; however, 2012 recorded a drastic decrease, with a slight improvement in 2013, and a continued decline in 2014 and 2015. The species with the highest rate of use was laurel. The variations for legal forest use in the province of Napo are linked to the effectiveness and strengthening of the National Forestry Control System, 2011 was the year with the most effective performance.

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“…Thus, in the current scenario of potential consolidation of a non-analogous climate, studies that estimate the possible impacts on agricultural production chains caused by climate change are of great importance. Some projections regarding South American biomes also indicated the persistence of an annual temperature rise over a long period and a significant reduction in humidity in forest biomes [ 15 ]. In this sense, Brazil has carried out several projects to promote low carbon rural development by maximizing conservation and economic production in the region, such as the Legal Amazon Ecological–Economic Macro-Zoning (MacroZEE) [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Climate change could reduce and spatially reconfigure cocoa cultivation in the Brazilian Amazon by 2050

2022

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Cocoa is a plant with origins in northwestern South America with high relevance in the global economy. Evidence indicates that cocoa is sensitive to a dry climate, under which crop production is reduced. Projections for future climate change scenarios suggest a warmer and drier climate in the Amazon basin. In this paper, we quantify the potential effects in cocoa production due to its edaphoclimatic suitability changes to the Brazilian Amazon biome and account for regional differences in planning occupation territories. We modeled the suitability of cocoa’s geographical distribution using an ensemble of 10 correlative models that were run in the “biomod2” library and projected to two future climate scenarios (RCPs 4.5 and 8.5) by 2050. Combining information on climate and soil suitability and installed infrastructure in the macro-regions of the Brazilian Amazon. We defined a zoning system to indicate how cocoa production may respond to climate change according to the current and future suitability model. Our results suggest that a reduction in precipitation and an increase in temperature may promote a reduction in the suitability of cocoa production in the Brazilian Amazon biome. In addition of the areas suitable for cocoa plantation, we found a 37.05% and 73.15% decrease in the areas suitable for intensification and expansion zones under RCP 4.5 and 8.5, respectively, compared with the current scenario. We conclude that there may be a need to expand land to cocoa production in the future, or else it will be necessary to plant a cocoa variety resistant to new climatic conditions. Besides, we recommend procedures to combat illegal deforestation to prevent the most critical climate change scenarios from occurring.

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Future projections for terrestrial biomes indicate widespread warming and moisture reduction in forests up to 2100 in South America

Cited by 21 publications

References 53 publications

Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation

Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation

Sustainable forest use of legal origin in the province of Napo Amazonia Ecuador

Climate change could reduce and spatially reconfigure cocoa cultivation in the Brazilian Amazon by 2050

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