Publicações

Aquaculture in the Amazon holds the potential to meet increasing food demands while offering economic opportunities in a region facing deforestation and biodiversity loss. However, expanding aquaculture in this biodiverse region comes with complex environmental and social trade-offs. This Review explores how aquaculture can support sustainable development by minimizing its environmental impact, promoting equitable livelihoods and enhancing food security. It also highlights key challenges, such as greenhouse gas emissions and land-use changes, that need to be addressed for aquaculture to thrive sustainably in the Amazon.

With intensifying climate change impacts on dryland regions, it is essential to better understand how actors relate to each other to sustainably manage natural resources. The literature on environmental governance networks has studied actor collaborations, but it is only starting to investigate networks that sustain conflictive situations. Moreover, while actors traditionally defined as powerful have received important scholarly attention, those who do not hold formal authority or key financial resources have not, as well as their sources of power. In this paper we analyse Net-Map data to better understand the sources of power of actor groups that traditionally are not perceived as influential, hence they are neglected in actor networks. We use social network analysis and a typology of power to understand these actors links in the networks, aiming to decipher what might explain why the traditionally neglected actors are perceived as particularly influential. We apply these methods to local sites in three case countries, all located in dryland regions. Net-Map workshops with diverse groups of participants were held with a focus on agricultural production systems. The results reveal that a broad variety of actors that traditionally have been, and still are, neglected in decision making domains, are perceived as particularly influential in their regions, pointing to the various modes in which power is understood and exercised. The competing interests over natural resources shed light on the role that conflictive tensions played in power relations. Through this work a broader understanding of power asymmetries in actor networks is gained.

O trabalho analisa a percepção da paisagem na bacia do Paraíba do Sul (trecho paulista), comparando dados de mapas de uso e cobertura com dados da pesquisa de percepção ambiental realizada na bacia. A análise na paisagem da região é importante para ajudar a identificar as atividades humanas ocorridas e como estas transformaram o território. Além da pesquisa de percepção socioambiental, realizada em 2019, foram utilizados dados de uso e cobertura da terra do projeto MapBiomas (1985 e 2019) e outros estudos envolvendo a bacia, verificando as principais mudanças ocorridas na paisagem nesses 34 anos e se isso foi percebido pelos entrevistados. Os resultados mostram que algumas mudanças na paisagem da região que foram percebidas pelos entrevistados também foram observadas nos mapas de uso e cobertura e foram corroboradas por pesquisas em todo o Vale do Paraíba. É o caso do aumento da monocultura do Eucalipto observada por eles como reflorestamento, aumento da área urbanizada e de queimadas que podem ter relação com a pecuária e contribuem para a poluição do ar. Uma parcela significativa dos entrevistados apresentou sugestões para melhoria da situação ambiental da sua região, sendo que das respostas obtidas a Educação Ambiental foi a solução mais mencionada pelos participantes. Espera-se que este estudo incentive políticas públicas mais incisivas em educação ambiental para a população da bacia, levando-os a se mobilizar e reconhecer a importância de se preservar a natureza para o futuro da humanidade.

Large-scale forest restoration is vital for delivering a broad array of ecosystem services benefits to society. However, it is often perceived as an economically noncompetitive land use choice. Integrating economic opportunities into restoration aligns socioeconomic and environmental goals, reducing conflicts between forest production and conservation-oriented management decisions. Supply chains focusing on high-value goods can enhance the reach of forest restoration efforts and unite ecological and economic benefits in a multifunctional manner. The bioeconomy has emerged as a potential but critical driver for attracting investments in restoration. We outline the challenges and solutions to reconcile forest restoration and bioeconomy, specifically about (i) native timber production, (ii) non-timber forest products, (iii) biotechnological products, and (iv) intangible ecosystem services. This requires collaborative and multidisciplinary efforts to improve investment in large-scale projects. The intricacies of these issues intersect with research development, market dynamics, legal frameworks, and regulatory paradigms, underscoring the necessity for nuanced and tailored public policy interventions. These integrated approaches should enable tropical countries to lead the global forest-based economy and usher in a new era of forest restoration.

Amazonia’s net biome exchange (NBE), the sum of biogenic and wildfire carbon fluxes, is a fundamental indicator of the state of its ecosystems. It also quantifies the magnitude and patterns of short- and long-term carbon dioxide sources and sinks but is poorly quantified and out of equilibrium (non-zero) due to both direct (deforestation) and indirect (climate-related) anthropogenic disturbance. Determining trends in Amazonia’s carbon balance, shifts in carbon exchange pathways of NBE, and timescales of ecosystem sensitivity to disturbance requires reliable biogenic flux models that adequately capture fluxes from diurnal to seasonal and annual timescales. Our study assimilates readily available observations and a derived solar-induced fluorescence (SIF) product to estimate hourly biogenic carbon dioxide (CO2) fluxes (here in units of μmolCO2m-2s-1) as net ecosystem exchange (NEE), as well as its photosynthesis and respiration constituents, at 12 km resolution using four versions of the data-driven diagnostic Vegetation Photosynthesis and Respiration Model (VPRM). The VPRM versions are all calibrated with ground-based eddy flux data and vary based on whether (1) the photosynthesis term incorporates SIF (VPRM-SIF) or traditional surface reflectance (VPRM-TRA) and (2) the respiration term is modified beyond a simple linear air temperature dependence (VPRM-SIFg; VPRM-TRG). We compare the VPRM versions with each other and with hourly fluxes from the bottom-up mechanistic Simple Biosphere 4 (SiB4 v4.2) model. We also use NASA’s Orbiting Carbon Observatory (OCO-2) CO2 column observations to optimize the VPRM and SiB4 models during the 2016 wet season which occurred at the tail of the 2015/2016 severe El Niño. The wet season 2016 case study suggests that relative to SiB4 and the SIF-based VPRMs, the traditional VPRM versions can underestimate uptake by a factor of 3. In addition, the VPRM-SIFg version better captures biogenic CO2 fluxes at hourly to seasonal scales than all other VPRM versions in both anomalously wet and anomalously dry conditions. We also find that the VPRM-SIFg model and the independent bottom-up mechanistic hourly SiB4 model converge in NEE, although there are differences in the partitioning of the photosynthesis and respiration components. We further note that VPRM-SIFg describes greater spatial heterogeneity in carbon exchange throughout the Amazon. Despite the paucity of OCO-2 CO2 column observations (X CO2) over the Amazon in the wet season, incorporating X CO2 into the models significantly reduces near-field model-measurement mismatch at aircraft vertical profiling locations. Finally, a qualitative analysis of the unoptimized biogenic models from 2010-2020 agrees with the wet season 2016 case study, where the traditional VPRM formulations significantly underestimate photosynthesis and respiration relative to VPRM-SIFg. Overall, the VPRM-SIFg biogenic flux model shows promise in its ability to capture Amazonian carbon fluxes across multiple timescale and moisture regimes, suggesting its suitability for larger studies evaluating interannual and seasonal carbon trends in fire as well as the biogenic components of the region’s NB

The authors would like to point out that unfortunately, a factual error has been detected in the original published article which requires correction. This error appears on page 589, in the following statement:

“Notwithstanding the inherent value this Action Track represents, at the time of writing it has not yet been possible to define an indicator or benchmark for teachers and the teaching profession as stipulated in this Action Track, despite this being an essential point for the transformation of education. Participants preferred to avoid creating another multistakeholder structure, as there is already an International Task Force on Teachers for Education 2030 (TTF).”

This statement is only partially accurate, as indicator 4.c.1 currently monitors the number of pre-primary teachers who receive training. However, this indicator does not correspond to all the aspects that were discussed within Action Track 3 on teachers, teaching, and the teaching profession. The corrected statement should therefore read as follows

“Notwithstanding the inherent value of this Action Track to transforming education, at the moment there is one indicator that monitors solely the proportion of teachers with the minimum required qualifications in pre-primary education (Indicator 4.c.1).

The increased intensity and frequency of future climate extremes might invalidate current water policies, particularly in the case of basins with competing water uses. To analyze these challenges, the nexus approach was proposed as an alternative to integrated resources management by simultaneously taking into account synergies and trade-offs on water, energy, and food security. However, the application of nexus approaches is incipient, and scarcity events highlighted challenges in implementing its principles, which are crucial for meeting Sustainable Development Goals (SDGs). Therefore, this study

proposes a set of water, energy, and food indicators that reflect the SDGs, focusing on water use in the Paraiba do Sul River Basin, Brazil for the period 2016-2050. Results showed a limited influence of land use policies on future resource availability, with differences of less than 5% among scenarios. Projections revealed an increased frequency of extreme discharge compared with the baseline period. Moreover, the analysis of the scenarios revealed a higher probability of failing to meet one of the water transfer targets of the basin. The efficiency of wastewater treatment will significantly impact freshwater quality, indicating low water quality 90% of the time considering the current level of wastewater treatment.

A quarter of the deforested Amazon has regrown as secondary tropical forest and yet the climatic importance of these complex regenerating landscapes is only beginning to be recognised. Advances in satellite remote-sensing have transformed our ability to detect and map changes in forest cover, while detailed ground-based measurements from permanent monitoring plots and eddy-covariance flux towers are providing new insights into the role of secondary forests in the climate system. This review summarises how progress in data availability on Amazonian secondary forests has led to better understanding of their influence on global, regional and local climate through carbon and non-carbon climate benefits. We discuss the climate implications of secondary forest disturbance and the progress in representing forest regrowth in climate models. Much remains to be learned about how secondary forests function and interact with climate, how these processes change with forest age, and the resilience of secondary forest ecosystems faced with increasing anthropogenic disturbance. Secondary forests face numerous threats: half of secondary forests in the Brazilian legal Amazon were 11 years old or younger in 2023. On average, 1%-2% of Amazon secondary forests burn each year, threatening the permanence of sequestered carbon. The forests that burn are predominantly young (in 2023, 55% of burned secondary forests were <6 years old, <4% were over 30 years old). In the context of legally binding international climate treaties and a rapidly changing political backdrop, we discuss the opportunities and challenges of encouraging tropical forest restoration to mitigate anthropogenic climate change. Amazon secondary forests could make a valuable contribution to Brazil’s Nationally Determined Contribution provided there are robust systems in place to ensure permanence. We consider how to improve communication between scientists and decision-makers and identify pressing areas of future research.

Brazil is a country highly dependent on hydroelectricity. Because electricity generation is programmed monthly, one of the most critical information is the inflow of the main hydropower plants of the country. In this context, this study evaluates the predictability and accuracy of raw and bias-corrected ECMWF S2S forecasts as input of a hydrological model, focusing on high and low-flows within the Tocantins-Araguaia Basin in Brazil. Rainfall forecasts were also evaluated against observations across 22 sub-basins of the Tocantins-Araguaia River, considering lead times ranging from 1 to 28 days. Results indicated that the predictability of S2S forecasts vary with the sub-basin area and through seasons (wet and dry periods). Bias corrections were able to improve the accuracy of the forecasts for all lead-times and across sub-basins of different sizes. In the case of low-flows, using raw ECMWF S2S rainfall forecasts as input of the hydrological model resulted in streamflow forecast errors that increase with the scale of the sub-basin. For high-flows results are the opposite, errors are larger in small sub-basins and smaller at larger scales. This is due to the overestimation of dry season rainfall in the ECMWF S2S forecasts. When using bias-corrected rainfall forecasts as input, river flow forecasts are useful up to 28 days of lead-time. The results of this study revealed the potential of using subseasonal forecasts for decision-making in the Tocantins-Araguaia Basin, and encouraging further developments.

The future state of the global water cycle and the prediction of freshwater availability for humans around the world remain among the challenges of climate research and are relevant to several

United Nations Sustainable Development Goals. The Global Precipitation Experiment (GPEX) takes on the challenge of improving the prediction of precipitation quantity, phase, timing, and intensity, characteristics that are products of a complex integrated system. It will achieve this by leveraging existing World Climate Research Programme (WCRP) activities and community capabilities in satellite, surface-based, and airborne observations, modeling, and experimental research and by conducting new and focused activities. It was launched in October 2023 as a WCRP Lighthouse Activity. Here, we present an overview of the GPEX Science Plan that articulates the primary science questions related to precipitation measurements, process understanding, model performance and improvements, and plans for capacity development. The central phase of GPEX is the WCRP Years of Precipitation for 2-3 years with coordinated global field campaigns focusing on different storm types (atmospheric rivers, mesoscale convective systems, monsoons, and tropical cyclones, among others) over different regions and seasons. Activities are planned over the three phases (before, during, and after the Years of Precipitation) spanning a decade. These include gridded data evaluation and development, advanced modeling, enhanced understanding of processes critical to precipitation, multiscale prediction of precipitation events across scales, and capacity development. These activities will be further developed as part of the GPEX Implementation Plan.

Linking knowledge of energy fluxes and evapotranspiration (ET) in cacti is useful for understanding plant growth, which acts as an extremely important feed source for dairy farming. However, there is little quantitative understanding of the latent (LE) and sensible (H) heat fluxes in drylands of cactus. We therefore investigated the feedback from plants of Nopalea and Opuntia on an interannual and seasonal scale, of the surface energy balance (SEB) components, morphophysiological parameters, biomass, water relations and photochemical relationships during the wet and dry seasons of 20182021 in the semi-arid region of Brazil. To analyse the data, four periods were selected (dry season, wet season, and dry-wet and wet-dry transitions). Our results showed that the LE (105.26 W m−2) of Opuntia was 77 % greater than that of Nopalea. In all seasons, H was the SEB component with the highest energy consumption in the two cacti, with LE the second most affected. Under Nopalea, the soil heat flux increased at the surface (112 %) during the wet and dry seasons (a mean of 1.61 MJ m−2 day−1). The mean ET of Nopalea and Opuntia was 1.71 and 1.96 mm day−1 respectively. The H/Rn ratio showed decreasing behaviour from the dry to the wet season, with a reduction of 37 % in Nopalea and 14 % in Opuntia. The NDVI ranged from 0.19 to 0.67 (Nopalea), and 0.170.70 for Opuntia, similar to the Chlorophyll Index, which maintained the seasonality of the NDVI. Overall, we found spatial patterns for the Photochemical Reflectance Index of −0.01 to 0.14 for Nopalea and Opuntia. Under the same conditions, Opuntia showed a higher growth rate and net assimilation rate. The mean cladode water content was 86 % in Nopalea and 89 % in Opuntia. Biomass and water use efficiency were greater in Opuntia (56.01 Mg ha−1 and 7.54 kg m−3 respectively). We also found that these comparisons indicate greater sensitivity in Nopalea, and more-significant quantification of the SEB in Opuntia.

The east coast of Northeast Brazil (ENEB) has experienced an increase in extreme precipitation events in recent years because of climate change caused by human activities. ENEB is characterized by the influence of several synoptic-scale systems throughout the year that contribute to the development of extreme precipitation events, emphasizing that the region needs actions to increase its capacity to predict the threat of natural hazards with significant material and human losses. Several studies have shown an increase in the frequency and intensity of these events, accenting the growing importance of accurate numerical weather prediction models has become increasingly critical in aiding decision-makers and governments to plan effective actions that can prevent or mitigate catastrophic consequences. In the present study, one extreme precipitation event developed over the Alagoas state (located at the ENEB) occurred in July 01, 2022 was analyzed. The accumulated rainfall of 185 mm/day was recorded, triggering landslides, floods and river overflows in different cities. The main objective of this study was to apply the Model for Prediction Across Scales Atmosphere (MPAS) model with a variable-resolution mesh to perform the simulation for both extreme precipitation events. A 60-3 km variable resolution mesh with refinement centered on the city of Maceió was configured. The high resolution (3 km) can resolve the known finer-scale mechanisms responsible for cloud formation in the region. Numerical simulations were driven by ERA5 reanalysis to investigate sensitivity to initial conditions. Gridded data from MERGE/CPTEC (0.1°) for hourly accumulated precipitation were used to evaluate the simulated hourly accumulated precipitation. Through the results obtained in the analysis, it was possible to observe a significant variation in the correlations between MPAS and MERGE, with values above 0.67 for some cities affected by heavy rainfall (Quebrangulo, Paulo Jacinto, and Cajueiro), indicating that the model was able to track the temporal variability in these cities. On the other hand, in cities where lower correlations were observed, there might have been some displacement of the rain relative to the observed MERGE data. The BIAS analysis indicated that MPAS tends to underestimate precipitation at all evaluated points, with the highest intensities occurring in locations with higher correlations, suggesting that the model captured the position of the rainfall well but did not accurately represent the volumes. This becomes evident when evaluating the RMSE, MAE, and BIAS, where the values were more pronounced in locations with higher rainfall volumes, reaching up to 7.78 mm/h. These results provide important information into the performance of MPAS, highlighting the need for an extended evaluation with other physical parameterizations and model configurations.