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Global terrestrial models currently predict that the Amazon rainforest will continue to act as a carbon sink in the future, primarily owing to the rising atmospheric carbon dioxide (CO2) concentration. Soil phosphorus impoverishment in parts of the Amazon basin largely controls its functioning, but the role of phosphorus availability has not been considered in global model ensembles—for example, during the Fifth Climate Model Intercomparison Project. Here we simulate the planned free-air CO2 enrichment experiment AmazonFACE with an ensemble of 14 terrestrial ecosystem models. We show that phosphorus availability reduces the projected CO2-induced biomass carbon growth by about 50% to 79 ± 63 g C m−2 yr−1 over 15 years compared to estimates from carbon and carbon–nitrogen models. Our results suggest that the resilience of the region to climate change may be much less than previously assumed. Variation in the biomass carbon response among the phosphorus-enabled models is considerable, ranging from 5 to 140 g C m−2 yr−1, owing to the contrasting plant phosphorus use and acquisition strategies considered among the models. The Amazon forest response thus depends on the interactions and relative contributions of the phosphorus acquisition and use strategies across individuals, and to what extent these processes can be upregulated under elevated CO2.

Radical and quick transformations towards sustainability will be fundamental to achieving a more sustainable future. However, deliberate interventions to reconfigure systems will result in winners and losers, with the potential for greater or lesser equity and justice outcomes. Positive tipping points (PTPs) have been proposed as interventions in complex systems with the aim to (a) reduce the likelihood of negative Earth system tipping points and/or (b) increase the likelihood of achieving just social foundations. However, many narratives around PTPs often do not take into account the entire spectrum of impacts the proposed alternatives could have or still rely on narratives that maintain current unsustainable behaviours and marginalize many people (i.e. do not take "b" into account). One such example is the move from petrol-based to electric vehicles. An energy transition that remains based on natural resource inputs from the Global South must be unpacked with an equity and justice lens to understand the true cost of this transition. There are two arguments why a critical engagement with these and other similar proposals needs to be made. First, the idea of transitioning through a substitution (e.g. of fuel) while maintaining the system structure (e.g. of private vehicles) may not necessarily be conceived as the kind of radical transformation being called for by global scientific bodies like the Intergovernmental Panel on Climate Change (IPCC) and Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). Second, and probably more importantly, the question of positive for whom, positive where, and positive how must be considered. In this paper, we unpack these narratives using a critical decolonial view from the south and outline their implications for the concept of tipping points. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is recognized as an important driver of terrestrial primary productivity across biomes. Several recent developments in process-based vegetation models aim at the concomitant representation of the carbon (C), nitrogen (N) and P cycles in terrestrial ecosystems, building upon the ecological stoichiometry and the processes that govern nutrient availability in soils. Thus, understanding the spatial distribution of P forms in soil is fundamental to initialize and/or evaluate process-based models that include the biogeochemical cycle of P. One of the major constraints for the large-scale application of these models is the lack of data related to the spatial patterns of the various forms of P present in soils, given the sparse nature of in situ observations. We applied a model selection approach based on random forest regressions models trained and tested for the prediction of different P forms (total, available, organic, and inorganic P) - obtained by the Hedley sequential extraction method. As input for the models, reference soil group and textural properties, geolocation, N and C contents, terrain elevation and slope, soil pH and mean annual precipitation and temperature from 108 sites of the RAINFOR network were used. The selected models were then applied to predict the target P forms using several spatially explicit datasets containing contiguous estimated values across the area of interest. Here, we present a set of maps depicting the distribution of total, available, organic, and inorganic P forms in the topsoil profile (0-30 cm) of the pan-Amazon region in the spatial resolution of 0.5 x 0.5 degrees. The random forest regression models presented a good level of mean accuracy for the total, available, organic, and inorganic P forms (77.37 %, 76,86 %, 75.14 %, and 68.23 % respectively). Our results confirm that the mapped area have generally very low total P concentration status with a clear gradient of soil development and nutrient content. Total N was the most important variable for the prediction of all target P forms and the analysis of partial dependence indicates several features that are also related with soil concentration of all target P forms. We observed that gaps in the data used to train and test the random forest models, especially in the most elevated areas, constitute a problem to the methods applied here. However, most of the area could be mapped with a good level of accuracy. Also, the biases of gridded data used for model prediction are introduced in the P maps. Nonetheless, the final map of total P resembles the expected geographical patterns. Our maps may be useful for the parametrization and evaluation of process-based terrestrial ecosystem models as well as other types of models. Also, they can promote the testing of new hypothesis about the gradient and status of P availability and soil-vegetation feedbacks in the pan-Amazon region. [ABSTRACT FROM AUTHOR]

Climate in the Amazon region is particularly sensitive to surface processes and properties such as heat fluxes and vegetation coverage. Rainfall is a key expression of land surface-atmosphere interactions in the region due to its strong dependence on forest transpiration. While a large number of past studies have shown the impacts of large-scale deforestation on annual rainfall, studies on the isolated effects of elevated atmospheric CO2 concentration (eCO2) on canopy transpiration and rainfall are scarcer. Here for the first time we make a systematic comparison of the plant physiological effects of eCO2 and deforestation on Amazon rainfall. We use the CPTEC-Brazilian Atmospheric Model (BAM) with dynamic vegetation under a 1.5xCO2 and a 100% substitution of the forest by pasture grassland, with all other conditions held similar between the two scenarios. We find that both scenarios result in equivalent average annual rainfall reductions (Physiology: -252 mm, -12%; Deforestation: -292 mm, -13%) that are well above observed Amazon rainfall interannual variability of 5.1%. Rainfall decrease in the two scenarios are caused by a reduction of approximately 20% of canopy transpiration, but for different reasons: eCO2-driven reduction of stomatal conductance in Physiology; decreased leaf area index of pasture (-66%) and its dry-season lower surface vegetation coverage in Deforestation. Walker circulation is strengthened in the two scenarios (with enhanced convection over the Andes and a weak subsidence branch over east Amazon) but, again, through different mechanisms: enhanced west winds from the Pacific and reduced easterlies entering the basin in Physiology, and strongly increased easterlies in Deforestation. Although our results for the Deforestation scenario are in agreement with previous observational and modelling studies, the lack of direct field-based ecosystem-level experimental evidence on the effect of eCO2 in moisture fluxes of tropical forests confers a considerable level of uncertainty to any projections on the physiological effect of eCO2 on Amazon rainfall. Furthermore, our results highlight the responsibilities of both Amazonian and non-Amazonian countries to mitigate potential future climatic change and its impacts in the region driven either by local deforestation or global CO2 emissions. [ABSTRACT FROM AUTHOR]

GLO:FQU/01apr20:cobi13405-fig-0002.jpg PHOTO (COLOR): Vulnerability of 993 Brazilian protected areas (PAs) to climate change relative to (a) number of areas within Brazilian ecological regions, (b) number of areas among PA objectives, (c) area among ecological regions, and (d) area among PA objectives. The ecosystem maintenance pathway (low resilience and low exposure to climate change) should be used alone in only 3 PAs that are highly affected by human activity, mainly in inland Atlantic Forest, and used in combination with refugia pathway in 92 PAs also located mostly in the Atlantic Forest. A more comprehensive consideration of climate change impacts on flora and fauna inside PAs through a method that unifies process-based and niche modeling could be a next step to assess PA climate change risks. The integrity of Brazil's remaining native vegetation within and outside these PAs is imperiled as long as knowledge of the effects of climate change on species distribution and on the community- and ecosystem-level responses to climate change remains superficial (Dawson et al. [6]; Settele et al. [45]). [Extracted from the article]