The complete or partial collapse of the forests of Amazonia is consistently named as one of the top ten possible tipping points of Planet Earth in a changing climate. However, apart from a few observational studies that showed increased mortality after the severe droughts of 2005 and 2010, the evidence for such collapse depends primarily on modelling. Such studies are notoriously deficient at predicting the rainfall in the Amazon basin and how the vegetation interacts with the rainfall is poorly represented. Here, we use long-term surface-based observations of the air temperature and rainfall in Amazonia to provide a constraint on the modelled sensitivity of temperature to changes in precipitation. This emergent constraint also allows us to significantly constrain the likelihood of a forest collapse or dieback. We conclude that Amazon dieback under IPCC scenario RCP8.5 (crossing the tipping point) is not likely to occur in the twenty-first century.

The analysis of gross primary production (GPP) is crucial to better understand CO₂ exchanges between terrestrial ecosystems and the atmosphere, while the quantification of water-use efficiency (WUE) allows for the estimation of the compensation between carbon gained and water lost by the ecosystem. Understanding these dynamics is essential to better comprehend the responses of environments to ongoing climatic changes. The objective of the present study was to analyze, through AMERIFLUX and LBA network measurements, the variability of GPP and WUE in four distinct tropical biomes in Brazil: Pantanal, Amazonia, Caatinga and Cerrado (savanna). Furthermore, data measured by eddy covariance systems were used to assess remotely sensed GPP products (MOD17). We found a distinct seasonality of meteorological variables and energy fluxes with different latent heat controls regarding available energy in each site. Remotely sensed GPP was satisfactorily related with observed data, despite weak correlations in interannual estimates and consistent overestimations and underestimations during certain months. WUE was strongly dependent on water availability, with values of 0.95 gC kg⁻¹ H₂O (5.79 gC kg⁻¹ H₂O) in the wetter (drier) sites. These values reveal new thresholds that had not been previously reported in the literature. Our findings have crucial implications for ecosystem management and the design of climate policies regarding the conservation of tropical biomes, since WUE is expected to change in the ongoing climate change scenario that indicates an increase in frequency and severity of dry periods.

Studies on numerical modeling in Amazonia show that the models fail to capture important aspects of climate variability in this region and it is important to understand the reasons that cause this drawback. Here, we study how the general circulation models of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate the inter-relations between regional precipitation, moisture convergence and Sea Surface Temperature (SST) in the adjacent oceans, to assess how flaws in the representation of these processes can translate into biases in simulated rainfall in Amazonia. Using observational data (GPCP, CMAP, ERSST.v3, ERAI and evapotranspiration) and 21 numerical simulations from CMIP5 during the present climate (1979–2005) in June, July and August (JJA) and December, January and February (DJF), respectively, to represent dry and wet season characteristics, we evaluate how the models simulate precipitation, moisture transport and convergence, and pressure velocity (omega) in different regions of Amazonia. Thus, it is possible to identify areas of Amazonia that are more or less influenced by adjacent ocean SSTs. Our results showed that most of the CMIP5 models have poor skill in adequately representing the observed data. The regional analysis of the variables used showed that the underestimation in the dry season (JJA) was twice in relation to rainy season as quantified by the Standard Error of the Mean (SEM). It was found that Atlantic and Pacific SSTs modulate the northern sector of Amazonia during JJA, while in DJF Pacific SST only influences the eastern sector of the region. The analysis of moisture transport in JJA showed that moisture preferentially enters Amazonia via its eastern edge. In DJF this occurs both via its northern and eastern edge. The moisture balance is always positive, which indicates that Amazonia is a source of moisture to the atmosphere. Additionally, our results showed that during DJF the simulations in northeast sector of Amazonia have a strong bias in precipitation and an underestimation of moisture convergence due to the higher influence of biases in the Pacific SST. During JJA, a strong precipitation bias was observed in the southwest sector associated, also with a negative bias of moisture convergence, but with weaker influence of SSTs of adjacent oceans. The poor representation of precipitation-producing systems in Amazonia by the models and the difficulty of adequately representing the variability of SSTs in the Pacific and Atlantic oceans may be responsible for these underestimates in Amazonia.

With few measurement sites and a great need to validate satellite data to characterize the exchange of energy and carbon fluxes in tropical forest areas, quantified by the Net Ecosystem Exchange (NEE) and associated with phenological measurements, there is an increasing need for studies aimed at characterizing the Amazonian environment in its biosphere–atmosphere interaction, considering the accelerated deforestation in recent years. Using data from a flux measurement tower in the Caxiuanã-PA forest (2005–2008), climatic data, CO₂ exchange estimated by eddy covariance, as well as Gross Primary Productivity (GPP) data and satellite vegetation indices (from MODIS), this work aimed to describe the site’s energy, climatic and carbon cycle flux patterns, correlating its gross primary productivity with satellite vegetation indices. The results found were: (1) marked seasonality of climatic variables and energy flows, with evapotranspiration and air temperature on the site following the annual march of solar radiation and precipitation; (2) energy fluxes in phase and dependent on available energy; (3) the site as a carbon sink (−569.7 ± 444.9 gC m⁻² year⁻¹), with intensity varying according to the site’s annual water availability; (4) low correlation between productivity data and vegetation indices, corroborating data in the literature on these variables in this type of ecosystem. The results show the importance of preserving this type of environment for the mitigation of global warming and the need to improve satellite estimates for this region. NDVI and EVI patterns follow radiative availability, as does LAI, but without direct capture related to GPP data, which correlates better with satellite data only in the months with the highest LAI. The results show the significant difference at a point measurement to a satellite interpolation, presenting how important preserving any type of environment is, even related to its size, for the global climate balance, and also the need to improve satellite estimates for smaller areas.

No Brasil as queimadas são caracterizadas por extensas linhas de fogo de rápida propagação que causam a mortalidade de espécies da flora e da fauna. Para mitigar estes danos, políticas públicas foram implementadas. Para correto funcionamento delas, entretanto, é necessário compreender a variabilidade do fogo e os elementos que o afetam para aperfeiçoar as estratégias de prevenção e combate. Neste sentido, este trabalho teve como escopo analisar a dinâmica das queimadas no Brasil, nos anos de 2003 a 2018, através da climatologia de precipitação e dos acumulados e das anomalias de focos de queima de vegetação. Os resultados demonstraram que há três padrões espaciais de queimadas no Brasil que se relacionam com dois sistemas de precipitação: a Zona de Convergência Intertropical e a Zona de Convergência do Atlântico Sul. Na maioria dos estados foi detectada uma tendência de redução de uso do fogo. Para outros, uma estabilização das taxas de detecção. Apesar destes resultados, as detecções ainda têm maior ocorrência na estiagem, quando tendem a contribuir significativamente para a degradação ambiental e para o dispêndio do orçamento público em operações de combate. Cabe aos entes federativos investirem em atividades de fiscalização, de monitoramento, de educação ambiental e de manejo preventivo para reduzi-las.Space-Time Dynamics of the Burns in Brazil in the Period 2003 to 2018 A B S T R A C TIn Brazil, vegetation fires are characterized by extensive and rapidly spreading fire lines that cause the mortality of flora and fauna species. Public policies were implemented to mitigate these damages, and for their correct enforcement it is necessary to understand the variability of the fire regime and the elements that affect it to improve prevention and combat strategies. In this sense, this work aimed to analyze the dynamics of burning in Brazil from 2003 to 2018 through the accumulated number of active fires and their anomalies as detected in satellite images with the precipitation climatology. The results showed that there are three spatial burning patterns in Brazil that relate with two precipitation systems: the Intertropical Convergence Zone and the South Atlantic Convergence Zone. A tendency to reduce the use of the fire was detected in most states; some indicated a stabilization of detection rates. The detections are still more frequent in drought periods, when the fires tend to contribute significantly to environmental degradation and to public budget expenditure in combat operations. It is up to the federal and state governments to invest in activities of enforcement, monitoring, environmental education and preventive management to reduce the use of fire in the country.Keywords: Variability of fire, climatology precipitation, public policies, active fire.

Climate variability directly influences agriculture, especially in a scenario of global change and transition to a sustainable bioeconomy. This study analyzed historical series (1994–2023) of productivity and harvested area of annual crops (corn, cassava, and beans) and perennial crops (pineapple, cocoa, annatto, avocado, and guava), in order to understand the relationship between rainfall, maximum temperature, and agricultural production in northern Brazil. To achieve this, the Augmented Dickey–Fuller (ADF) test was applied to verify the stationarity of the series, and principal component analysis (PCA) was used to identify correlation patterns between climate and production variables. The ADF test showed that annual precipitation is stationary, while maximum temperature is non-stationary, confirming a warming trend. Among the crops, only bean productivity was stationary, albeit at low levels, while corn, cassava, and cocoa showed non-stationary behavior, reflecting technological advances combined with climatic pressures. PCA indicated different responses: corn showed a positive association with temperature, but signs of recent stagnation, whereas cassava and beans depended more on precipitation, demonstrating vulnerability to drought. Among perennials, avocado and guava responded positively to increased temperature, while annatto and pineapple were more dependent on rainfall. Cocoa showed a balanced correlation with both variables. It can be concluded that climate impacts on agriculture are heterogeneous and require specific adaptive strategies. From a bioeconomy perspective, the importance of productive diversification, technological innovation, and public policies aimed at climate resilience and the sustainability of low-carbon value chains is highlighted.