Publicações

The use of stable isotopes of hydrogen and oxygen is a tool widely used to trace water paths along the hydrological cycle, providing support for understanding climatic conditions in different spatial scales. One of the main synoptic scale events acting in southeastern Brazil is the South Atlantic Convergence Zone (SACZ), which causes a large amount of precipitation from southern Amazonia to southeastern Brazil during the southern summer. In order to determine the isotopic composition of precipitation during the action of SACZ in São Francisco Xavier in southeastern Brazil, information from the Weather Forecasting and Climate Studies Center of the National Institute for Space Research (CPTEC) was used regarding SACZ performance days, the retrograde trajectories of the HYSPLIT model, and images from the GOES-16 satellite, in addition to the non-parametric statistical tests by Spearman and Kruskal-Wallis. A high frequency of air mass trajectories from the Amazon to southeastern Brazil was observed when the SACZ was operating. During the SACZ events, the average isotopic composition of precipitation was more depleted, with a δ18O of −9.9 (±2.1), a δ2H of −69.3 (±17.9), and d-excess of 10.1 (±4.0). When disregarding the SACZ performance, the annual isotopic composition can present an enrichment of 1.0 for δ18O and 8.8 for the δ2H. The long-term monitoring of trends in the isotopic composition of precipitation during the SACZ events can assist in indicating the evapotranspiration contribution of the Amazon rainforest to the water supply of southeastern Brazil.

In their comments about our paper, the authors remark on two issues regarding our results relating to the MACCS-ATCOR Joint Algorithm (MAJA). The first relates to the sub-optimal performance of this algorithm under the conditions of our tests, while the second corresponds to an error in our interpretation of MAJA’s bit mask. To answer the first issue, we acknowledge MAJA’s capacity to improve its performance as the number of images increases with time. However, in our paper, we used the images we had available at the time we wrote our paper. Regarding the second issue, we misread the MAJA’s bit mask and mistakenly labelled shadows as clouds. We regret our error and here we present the updated tables and images. We corrected our estimation and, consequently, there is an increment in MAJA’s accuracy in the detection of clouds and cloud shadows. However, these increments are not enough to change the conclusion of our original paper.

Global Environmental Assessments (GEAs) are in a unique position to influence environmental decision-making in the context of sustainability challenges. To do this effectively, however, new methods are needed to respond to the needs of decision-makers for a more integrated, contextualized and goal-seeking evaluation of different policies, geared for action from global to local. While scenarios are an important tool for GEAs to link short-term decisions and medium and long-term consequences, these current information needs cannot be met only through deductive approaches focused on the global level. In this paper, we argue that a more diverse set of futures tools operating at multiple scales are needed to improve GEA scenario development and analysis to meet the information needs of policymakers and other stakeholders better. Based on the literature, we highlight four challenges that GEAs need to be able to address in order to contribute to global environmental decision-making about the future: 1. anticipate unpredictable future conditions; 2. be relevant at multiple scales, 3. include diverse actors, perspectives and contexts; and 4. leverage the imagination to inspire action. We present a toolbox of future-oriented approaches and methods that can be used to effectively address the four challenges currently faced by GEAs.

Agricultural systems play a key role in achieving many of the Sustainable Development Goals, established by the United Nations, given the current challenge of producing enough food to feed a global population that is expected to reach 10 billion people by 2050. More efficient and sustainable use of nutrients in agriculture is an important step to increasing production while minimizing threats to natural ecosystems and resource depletion. In this study, we developed a system nutrient balance for nitrogen (N) and phosphorus (P) to evaluate nutrient use practices in cropping and grazing systems in the Vermelho River watershed (VRW), Upper Pantanal, Brazil, and investigated options to improve N and P use efficiency (NUE and PUE). Our results show P balance in cropping systems are positive while those in grazing systems tend to be negative. The positive values in cropping systems are due to both high P inputs from mineral fertilizers and high soil P-sorbing capacities. The negative values in grazing systems are a result of the removal of animal products without replacing the nutrients. Most of the N inputs in the crops grown in this region come from biological nitrogen fixation. The NUE in cropping systems is about 0.95, which is higher than the upper critical value of the desirable range (0.60.9). Given the high NUE value and the risk of soil mining, improving cropping systems NUE by adjusting the inputs to replenish N outputs and avoid soil erosion in the VRW are of considerable interest.

In this work, we evaluate the environmental and economic sustainability dimensions of a run-of-river hydroelectric plant operation regarding environmental impacts and potential direct and indirect effects of climate change. Results suggest the generation of a vicious cycle of clean generation and dirty generation, enhanced by a positive feedback with climate change impacts. This cycle is triggered by the tradeoffs between environmental protection policies and the socioeconomic pressure for energy production, embedded in an energy production matrix that prioritizes fossil fuel-based production as responses to peak energy demand. The climate projections were generated by the Eta Regional Climate Model from the National Institute for Space Research. They were forced by the atmospheric simulations of the Interdisciplinary Climate Research Model (MIROC5) and the Hadley Center Global Environmental Model (HadGEM2-ES) under the RCP4.5 and RCP 8.5 emission scenarios. The MHD-INPE Distributed Hydrological Model was used to generate streamflow projections. Environmental impacts were assessed by accounting for carbon stock and sequestration, greenhouse gas emissions, and energy cost. Climate projections indicated reduced precipitation and increased temperature. The streamflow will present progressively reductions of the flow volume until the end of the century, which undermines the plant’s ability to ensure firm energy and induce thermal plants’ activation to supply the demand. This activation will lead to an increase in greenhouse gas emissions and an increase in the price of energy, which may lower the benefits in carbon stock associated with a run-of-river hydropower plant and negatively influence the reduction commitments assumed by Brazil.

To achieve regional and international large-scale restoration goals with minimum costs, several restoration commitments rely on natural regeneration, a passive and inexpensive strategy. However, natural regeneration potential may vary within the landscape, mainly due to its historical context. In this work, we use spatially explicit restoration scenarios to explore how and where, within a given region, multiple restoration commitments could be combined to achieve cost-effectiveness outcomes. Our goal is to facilitate the elaboration of forest restoration plans at the regional level, taking into consideration the costs for active and passive restoration methods. The approach includes (1) a statistical analysis to estimate the natural regeneration potential for a given area based on alternative sets of biophysical, land cover, and/or socioeconomic factors and (2) the use of a land change allocation model to explore the cost-effectiveness of combining multiple restoration commitments in a given area through alternative scenarios. We test our approach in a strategic region in the Brazilian Atlantic Forest Biome, the Paraiba Valley in São Paulo State. Using the available data for 2011, calibrated for 2015, we build alternative scenarios for allocating natural regeneration until 2025. Our models indicate that the natural regeneration potential of the region is actually very low, and the cost-effectiveness outcomes are similar for all scenarios. We believe our approach can be used to support the regional-level decision-making about the implementation of multiple commitments aiming at the same target area. It can also be combined with other approaches for more refined analysis (e.g., optimization models).

Humanity is on a deeply unsustainable trajectory. We are exceeding planetary boundaries and unlikely to meet many international sustainable development goals and global environmental targets. Until recently, there was no broadly accepted framework of interventions that could ignite the transformations needed to achieve these desired targets and goals. As a component of the IPBES Global Assessment, we conducted an iterative expert deliberation process with an extensive review of scenarios and pathways to sustainability, including the broader literature on indirect drivers, social change and sustainability transformation. We asked, what are the most important elements of pathways to sustainability? Applying a social-ecological systems lens, we identified eight priority points for intervention (leverage points) and five overarching strategic actions and priority interventions (levers), which appear to be key to societal transformation. The eight leverage points are: (1) Visions of a good life, (2) Total consumption and waste, (3) Latent values of responsibility, (4) Inequalities, (5) Justice and inclusion in conservation, (6) Externalities from trade and other telecouplings, (7) Responsible technology, innovation and investment, and (8) Education and knowledge generation and sharing. The five intertwined levers can be applied across the eight leverage points and more broadly. These include: (A) Incentives and capacity building, (B) Coordination across sectors and jurisdictions, (C) Pre-emptive action, (D) Adaptive decision-making and (E) Environmental law and implementation. The levers and leverage points are all non-substitutable, and each enables others, likely leading to synergistic benefits. Transformative change towards sustainable pathways requires more than a simple scaling-up of sustainability initiatives-it entails addressing these levers and leverage points to change the fabric of legal, political, economic and other social systems. These levers and leverage points build upon those approved within the Global Assessment’s Summary for Policymakers, with the aim of enabling leaders in government, business, civil society and academia to spark transformative changes towards a more just and sustainable world.

The expansion of agricultural activities in Brazil resulted in a loss of approximately 50% of the native vegetation of the Cerrado biome, mainly to the north of the biome in a region known as MATOPIBA. Besides contributing to accelerate climate change, the removal of native vegetation is associated with increase soil degradation. In this study, we used the decision tree method to predict degradation using as indicators Normalized Difference Vegetation Index (NDVI) derived indices over the period 19852018. Results showed that approximately 4677 km2 (0.63%) of MATOPIBA region is under strong signs of degradation, mostly on pasture and grasslands areas, commonly used for grazing. Although the percentage of degraded areas is relatively small, the mapping indicated that the majority of degradation patches are concentrated not only in areas of low resilience, e.g., areas dominated by weakly structured sandy soils, but also where highly stable latosols dominate. More importantly, these areas were frequently affected by fire over the study period. This finding suggests that the combination of unsustainable traditional land management practices, such as fire, the replacement of forest by pasture, and anthropic activities such as inadequate road planning, are the main factor that trigger degradation processes in this Brazilian region. The study results are important for decision makers for defining investment priorities for conservation and for the recovery of degraded areas.

Este relatório descreve as atividades de campo realizadas na região do Baixo Tocantins, microrregião de Cametá no estado do Pará, nos anos de 2018 e 2019, pela equipe de pesquisa do Laboratório de Investigação em Sistemas Socioambientais (LiSS) do Instituto Nacional de Pesquisas Espaciais (INPE). Essas atividades tiveram como objetivo coletar dados para caracterizar a região em dois aspectos. O primeiro aspecto diz respeito às diferentes formas de uso e ocupação do solo e aos principais métodos de produção associados às atividades extrativas agrícolas e agroflorestais. O segundo aspecto é a distribuição e o tipo de infraestrutura urbana, bem como o acesso aos serviços nos centros populacionais. Em particular, o segundo aspecto foca na validação do uso do sensor Visible Infrared Imaging Radiometer Suite Day/Night-Band (VIIRS/DNB) na detecção de níveis estáveis de radiância de luzes visíveis durante a noite ao longo do ano. Os levantamentos de campo foram realizados por meio de registros fotográficos, registros de observações e descrições da região, além de entrevistas com moradores, representantes de instituições e de localidades, bem como com responsáveis pelos estabelecimentos rurais. Também foram coletadas fotografias aéreas usando um Veículo Aéreo Não Tripulado (VANT). Foram também coletados dados de produção para 21 estabelecimentos rurais. Observou-se que 95% desses estabelecimentos coletam, cultivam e comercializam frutos de açaí, sendo que 76% dos estabelecimentos também cultivam outros produtos agrícolas. Imagens de VANT foram coletadas em 48 áreas. Essas imagens serão usadas para selecionar amostras rotuladas de classes de uso e cobertura da terra para processos de classificação de imagens, bem como para qualificar a infraestrutura urbana e ajudar a descrever as categorias de produção. Em relação à análise das luzes estáveis visíveis durante a noite, observou-se que 61% delas pertenciam a áreas particulares não relacionadas aos serviços de iluminação pública, enquanto 19% das luzes externas identificadas no campo não foram mapeadas como luzes estáveis. Esse resultado indica a necessidade de mais estudos para avaliar o potencial do uso de dados VIIRS/DNB como indicador de infraestrutura na Amazônia. Além disso, foram identificadas áreas de expansão urbana em Cametá e Mocajuba, das quais 26 foram visitadas e coletadas informações sobre educação, saúde, infraestrutura e condições de vida. Estas informações serão utilizadas para caracterizar, classificar e analisar a conectividade das localidades visitadas.

Brazil is currently the largest contributor of land use and land cover change (LULCC) carbon dioxide net emissions worldwide, representing 17%-29% of the global total. There is, however, a lack of agreement among different methodologies on the magnitude and trends in LULCC emissions and their geographic distribution. Here we perform an evaluation of LULCC datasets for Brazil, including those used in the annual global carbon budget (GCB), and national Brazilian assessments over the period 2000-2018. Results show that the latest global HYDE 3.3 LULCC dataset, based on new FAO inventory estimates and multi-annual ESA CCI satellite-based land cover maps, can represent the observed spatial variation in LULCC over the last decades, representing an improvement on the HYDE 3.2 data previously used in GCB. However, the magnitude of LULCC assessed with HYDE 3.3 is lower than estimates based on MapBiomas. We use HYDE 3.3 and MapBiomas as input to a global bookkeeping model (bookkeeping of land use emission, BLUE) and a process-based Dynamic Global Vegetation Model (JULES-ES) to determine Brazil’s LULCC emissions over the period 2000-2019. Results show mean annual LULCC emissions of 0.1-0.4 PgC yr(-1), compared with 0.1-0.24 PgC yr(-1) reported by the Greenhouse Gas Emissions Estimation System of land use changes and forest sector (SEEG/LULUCF) and by FAO in its latest assessment of deforestation emissions in Brazil. Both JULES-ES and BLUE now simulate a slowdown in emissions after 2004 (-0.006 and -0.004 PgC yr(-2) with HYDE 3.3, -0.014 and -0.016 PgC yr(-2) with MapBiomas, respectively), in agreement with the Brazilian INPE-EM, global Houghton and Nassikas book-keeping models, FAO and as reported in the 4th national greenhouse gas inventories. The inclusion of Earth observation data has improved spatial representation of LULCC in HYDE and thus model capability to simulate Brazil’s LULCC emissions. This will likely contribute to reduce uncertainty in global LULCC emissions, and thus better constrains GCB assessments.

Amazonia hosts the Earth’s largest tropical forests and has been shown to be an important carbon sink over recent decades(1-3). This carbon sink seems to be in decline, however, as a result of factors such as deforestation and climate change(1-3). Here we investigate Amazonia’s carbon budget and the main drivers responsible for its change into a carbon source. We performed 590 aircraft vertical profiling measurements of lower-tropospheric concentrations of carbon dioxide and carbon monoxide at four sites in Amazonia from 2010 to 2018(4). We find that total carbon emissions are greater in eastern Amazonia than in the western part, mostly as a result of spatial differences in carbon-monoxide-derived fire emissions. Southeastern Amazonia, in particular, acts as a net carbon source (total carbon flux minus fire emissions) to the atmosphere. Over the past 40 years, eastern Amazonia has been subjected to more deforestation, warming and moisture stress than the western part, especially during the dry season, with the southeast experiencing the strongest trends(5-9). We explore the effect of climate change and deforestation trends on carbon emissions at our study sites, and find that the intensification of the dry season and an increase in deforestation seem to promote ecosystem stress, increase in fire occurrence, and higher carbon emissions in the eastern Amazon. This is in line with recent studies that indicate an increase in tree mortality and a reduction in photosynthesis as a result of climatic changes across Amazonia(1,10). Aircraft observations of atmospheric carbon dioxide and monoxide concentrations in Brazil show higher carbon emissions in eastern Amazonia than in the western part, which are linked to increased ecosystem stress and fire occurrence.

Non-structural carbohydrates (NSC) are major substrates for plant metabolism and have been implicated in mediating drought-induced tree mortality. Despite their significance, NSC dynamics in tropical forests remain little studied. We present leaf and branch NSC data for 82 Amazon canopy tree species in six sites spanning a broad precipitation gradient. During the wet season, total NSC (NSCT) concentrations in both organs were remarkably similar across communities. However, NSCT and its soluble sugar (SS) and starch components varied much more across sites during the dry season. Notably, the proportion of leaf NSCT in the form of SS (SS:NSCT) increased greatly in the dry season in almost all species in the driest sites, implying an important role of SS in mediating water stress in these sites. This adjustment of leaf NSC balance was not observed in tree species less-adapted to water deficit, even under exceptionally dry conditions. Thus, leaf carbon metabolism may help to explain floristic sorting across water availability gradients in Amazonia and enable better prediction of forest responses to future climate change.