Publicações

Integrated agricultural systems have been greatly expanding in Brazil and currently cover over 30 million hectares. Although these land use systems help soil and environmental quality, little is known of their impacts on earthworm communities. In the present study we evaluated earthworm abundance, biomass and species richness in various integrated and conventional agricultural production systems (pasture, crops), as well as native forest and Eucalyptus plantations. The research was carried out at Fazenda Canchim (Embrapa Livestock Southeast) and at the neighboring campus of the University de São Carlos (UFSCar), in São Carlos municipality in São Paulo state, Brazil. Two earthworm sampling methods, i.e., quantitative (25 x 25 x 20 cm deep monoliths) and qualitative (holes of similar size and niche sampling), were used in three integrated production systems, three conventional systems and two forest systems, totaling 232 quantitative samples and over 160 qualitative samples. Earthworms were counted and identified using available keys. Eight earthworm species of five families (Rhinodrilidae, Ocnerodrilidae, Megascolecidae, Benhamiidae and Glossoscolecidae) were found, with most of the 2,145 individuals being exotic or peregrine species, particularly Pontoscolex corethrurus (88% of total) and various Dichogaster spp. (8% of total). Two native species were encountered in low abundance (55 individuals), both of which are new to science (Fimoscolex n.sp.7 and Glossoscolex n.sp.9) and must still be formally described. The new species were found in the agricultural systems, but not in the native forest and the Eucalyptus plantation, where P. corethrurus and Megascolecids predominated. One unidentified Ocnerodrilid sp. was found only in the intensive pasture. Species richness was highest in the intensive pasture (7 spp.), followed by the agrosilvopastoral and agropastoral systems, highlighting the importance of integrated and pastoral systems in preserving earthworm richness and native species.

Understanding the cost-effectiveness of restoration initiatives is critical for their successful implementation. In this context, this study presents a new approach to investigating the cost-effectiveness of different forest landscape restoration strategies for achieving multiple restoration goals. The approach is based on an optimization model that allocates forest restoration to maximize three environmental benefits (biodiversity conservation, carbon stock increase, and soil loss reduction) while minimizing the cost. We explore scenarios based on the Brazilian Forest Code and the National Policy for Payment for Ecosystem Services. Our optimization approach simultaneously achieves high levels of multiple environmental benefits – more than 90% of the maximum possible biodiversity, carbon, and soil in a cost-effective manner for all scenarios. Variation among the scenarios in the absolute performance concerning the three objectives was small (within 2.5%) compared to variation in costs (up to 19.4%). These results reinforce the importance of quantifying trade-offs among objectives to a better understanding of the cost-effectiveness of restoration initiatives before their implementation.

The Land Surface Temperature (LST) obtained by remote sensing data is an essential indicator for analyzing the Surface Urban Heat Island (SUHI). A factor contributing to its occurrence is the reflections of the different materials in urban and rural areas, which significantly affect the energy balance near the surface. Therefore, recent studies have increasingly used the Local Climate Zones (LCZs) classification system to discriminate those urban areas. Therefore, our study aims to perform a systematic review using the PRISMA method of LCZ classification applied to understand the LST and the SUHI phenomenon. At first, 10,403 related articles were found in the scientific literature which, after passing through filtering stages, resulted in 51 that were further analyzed. Our results showed that these articles were very recent, beginning in 2016, and present an increasing trend. Even though all articles reviewed somehow try to understand the Urban Heat Island phenomenon, in more than half of them, the SUHI calculation method was not mentioned. China was the country with the most studies. Images from Landsat and TERRA/AQUA sensors appeared in 82% of the studies. The method that appears the most to LCZ definitions is from the World Urban Database. Finally, we conclude that LCZ mapping methodologies were accurate enough for SUHI studies considering the current climatic changes. Therefore, this systematic review can help new studies on SUHI identification through LCZ in different world areas using remote sensing data to estimate the LST.

Air pollution has become one of the factors that most affect the quality of life, human health, and the environment. Gaseous pollutants from motor vehicles have a significantly harmful effect on air quality in the Metropolitan Area of São Paulo (MASP)Brazil. Motor vehicles emit large amounts of particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), and volatile organic compounds (VOCs), the last three acting as the main tropospheric ozone (O3) precursors. In this study, we evaluated the effects of these pollutants on air quality in the MASP during the partial lockdown that was imposed to ensure the social distancing necessitated by the COVID-19 pandemic. We compared the monthly data for nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI) and CO, SO2, and BC from MERRA-2 for the period between April and May 2020 (during the pandemic) with the average for the same period for the (pre-pandemic) years 2017 to 2019 in the southeast region of Brazil. The meteorological and pollutant concentration data from the CETESB air quality monitoring stations for the MASP were compared with the diurnal cycle of three previous years, with regard to the monthly averages of April and May (2017, 2018, and 2019) and the same period in 2020, when the partial lockdown was first imposed in southeast Brazil. Our findings showed that there was a decrease in NO2 concentrations ranging from 10% to more than 60% in the MASP and the Metropolitan Area of Rio de Janeiro (MARJ), whereas in the Metropolitan Area of Belo Horizonte and Vitoria (MABH and MAV, respectively), there was a reduction of around 10%. In the case of the concentrations of CO and BC from MERRA-2, there was a considerable decrease (approx. 10%) during the period of partial lockdown caused by COVID-19 throughout almost the entire state of São Paulo, particularly in the region bordering the state of Rio de Janeiro. The concentration of SO2 from MERRA-2 was 5 to 10% lower in the MASP and MARJ and the west of the MABH, and there was a decrease of 30 to 50% on the border between the states of São Paulo and Rio de Janeiro, while in the MAV region, there was an increase in pollutant levels, as this region was not significantly affected by the COVID-19 pandemic. Sharp reductions in the average hourly concentrations of CO (38.8%), NO (44.9%), NO2 (38.7%), and PM2.5 (6%) were noted at the CETESB air quality monitoring stations in the MASP during the partial lockdown in 2020 compared with the hourly average rate in the pre-pandemic period. In contrast, there was an increase of approximately 16.0% in O3 concentrations in urban areas that are seriously affected by vehicular emissions, which is probably related to a decrease in NOx.

There is an urgent need for countries to transition their national food and land-use systems toward food and nutritional security, climate stability, and environmental integrity. How can countries satisfy their demands while jointly delivering the required transformative change to achieve global sustainability targets? Here, we present a collaborative approach developed with the FABLEâFood, Agriculture, Biodiversity, Land, and EnergyâConsortium to reconcile both global and national elements for developing national food and land-use system pathways. This approach includes three key features: (1) global targets, (2) country-driven multi-objective pathways, and (3) multiple iterations of pathway refinement informed by both national and international impacts. This approach strengthens policy coherence and highlights where greater national and international ambition is needed to achieve global goals (e.g., the SDGs). We discuss how this could be used to support future climate and biodiversity negotiations and what further developments would be needed.

Located in Southeast Brazil, the Paraíba do Sul River Basin is considered one of the most strategic in the country since it is the main source of fresh water for more than 14.3 million people. The population growth in recent decades, in combination with increased demand for water for industrial and agricultural activities, has generated concerns about how the combined effect of land uses and global climate change might affect water availability in the future. Once irrigation is one of the main water consumers, especially for paddy rice cultivation, in this study we used a crop simulation model to determine the water requirements of paddy rice under current and future climate conditions based on three different regionalized climate scenarios and for different land use and land cover change projections. In addition, we estimated water footprints for different irrigation and soil fertility strategies. Finally, we explored adaptation actions that can lead to more sustainable production. Projections indicate an increase in the productivity and efficiency of irrigated rice. Intermittent flooding proved to be an efficient alternative, rather than the traditional practice of continuous ponding. Most scenarios projected a gradual decrease in water footprint for rice cultivated using irrigation and soil fertility management. On the other hand, the water footprint under rainfed and non-optimum soil fertility resulted in higher water footprints. Due to changes in land use and land cover, mainly urban sprawl, the rice areas are expected to decrease in the future reducing the production in the region, which is expected to decrease by almost 10% in the period 20162035 and up to 38% in the period 20362055. This trend can be compensated by adopting sustainable practices in rice cultivation, such as rational soil fertility and water management, which can boost the current level of productivity by 50% and reduce water use by up to 15%.

O presente trabalho realiza um comparativo entre os três principais eventos de seca e crise Revista Brasileira de Climatologia, Dourados, MS, v. 32, Jan. / Jun. 2023, ISSN 2237-8642 130 hídrica ocorridos a partir do início do século XXI, nos anos 2001, 2014 e 2021. Por meio de revisão bibliográfica, realizou-se o levantamento de dados e informações que tangem aspectos físicos, políticos e socioeconômicos ambientais para cada um desses eventos no Sudeste do Brasil, com foco sobre as regiões que integram a Bacia do Rio Paraná. O aspecto físico abrange índices de precipitação, vazão e temperatura, bem como nível de intensidade da seca para cada evento; o aspecto político compreende as informações sobre políticas públicas e tomadas de decisão frente ao alerta e durante as crises; por fim, os impactos sociais, econômicos e ambientais advindos dos eventos de seca são contemplados no aspecto socioeconômico ambiental. Com base no comparativo, pôde-se concluir que a implantação ou melhoria de ferramentas auxiliares no monitoramento de seca e de seus impactos aconteceram ao longo dos anos, mas políticas de gestão dos recursos hídricos e de seus riscos, com atenção às pessoas vulnerabilizadas, ainda precisam ser efetivamente incorporadas para minimização dos efeitos de tais eventos e, maior resiliência e adaptabilidade das áreas afetadas.

Mangrove distribution maps are used for a variety of applications, ranging from estimates of mangrove extent, defor-estation rates, quantify carbon stocks, to modelling response to climate change. There are multiple mangrove distribu-tion datasets, which were derived from different remote sensing data and classification methods, and so there are some discrepancies among these datasets, especially with respect to the locations of their range limits. We investigate the latitudinal discrepancies in poleward mangrove range limits represented by these datasets and how these differences translate climatologically considering factors known to control mangrove distributions. We compare four widely used global mangrove distribution maps -the World Atlas of Mangroves, the World Atlas of Mangroves 2, the Global Distri-bution of Mangroves, the Global Mangrove Watch. We examine differences in climate among 21 range limit positions by analysing a set of bioclimatic variables that have been commonly related to the distribution of mangroves. Global mangrove maps show important discrepancies in the position of poleward range limits. Latitudinal differences be-tween mangrove range limits in the datasets exceed 5 degrees, 7 degrees and 10 degrees in western North America, western Australia and northern West Africa, respectively. In some range limit areas, such as Japan, discrepancies in the position of mangrove range limits in different datasets correspond to differences exceeding 600 mm in annual precipitation and > 10 degrees C in the minimum temperature of the coldest month. We conclude that dissimilarities in mapping mangrove range limits in different parts of the world can jeopardise inferences of climatic thresholds. We expect that global mapping efforts should prioritise the position of range limits with greater accuracy, ideally combining data from field-based surveys and very high-resolution remote sensing data. An accurate representation of range limits will contribute to better predicting mangrove range dynamics and shifts in response to climate change.

Monitoring changes in tree cover for assessment of deforestation is a premise for policies to reduce carbon emission in the tropics. Here, a U-net deep learning model was used to map monthly tropical tree cover in the Brazilian state of Mato Grosso between 2015 and 2021 using 5 m spatial resolution Planet NICFI satellite images. The accuracy of the tree cover model was extremely high, with an F1-score >0.98, further confirmed by an independent LiDAR validation showing that 95% of tree cover pixels had a height >5 m while 98% of non-tree cover pixels had a height <5 m. The biannual map of deforestation was then built from the monthly tree cover map. The deforestation map showed relatively consistent agreement with the official deforestation map from Brazil (67.2%) but deviated significantly from Global Forest Change (GFC)s year of forest loss, showing that our product is closest to the product made by visual interpretation. Finally, we estimated that 14.8% of Mato Grossos total area had undergone clear-cut logging between 2015 and 2021, and that deforestation was increasing, with December 2021, the last date, being the highest. High-resolution imagery from Planet NICFI in conjunction with deep learning techniques can significantly improve the mapping of deforestation extent in tropical regions.

This study investigates a summer heat wave (HW) associated with downslope winds (DWs) affecting the central region of the state of Rio Grande do Sul (RS), Brazil. The temporal evolution of both phenomena is analyzed in the atmospheric boundary layer (ABL) using a combination of micrometeorological and rawinsonde data. For spatial characterization, ERA-5 reanalysis data are used. The HW covered a large area in southern Brazil, Argentina, and Paraguay. The main features of the HW were locally enhanced in the central region of RS by the development of DWs. The establishment of DWs near the surface depends on the dynamics of the ABL and local topographic features. The results showed that DWs that occurred during the HW contributed to the extreme temperatures and were associated with strong northerly winds, low relative humidity, and a drop in the dew points. Together, these extreme events influenced the turbulent and mean flow patterns of the ABL. The increase in turbulent activity associated with the warming of the ABL favored enhanced growth of morning ABL, while at night the simultaneous effects of radiative and turbulence cooling inhibited the formation of a strong stable ABL. The analysis highlights the complex interplay of synoptic and local factors associated with DWs and HW.

Amazon forests are being degraded by myriad anthropogenic disturbances, altering ecosystem and climate function. We analyzed the effects of a range of land-use and climate-change disturbances on fine-scale canopy structure using a large database of profiling canopy lidar collected from disturbed and mature Amazon forest plots. At most of the disturbed sites, surveys were conducted 1030 years after disturbance, with many exhibiting signs of recovery. Structural impacts differed in magnitude more than in character among disturbance types, producing a gradient of impacts. Structural changes were highly coordinated in a manner consistent across disturbance types, indicating commonalities in regeneration pathways. At the most severely affected site burned igapó (seasonally flooded forest) no signs of canopy regeneration were observed, indicating a sustained alteration of microclimates and consequently greater vulnerability to transitioning to a more open-canopy, savanna-like state. Notably, disturbances rarely shifted forests beyond the natural background of structural variation within mature plots, highlighting the similarities between anthropogenic and natural disturbance regimes, and indicating a degree of resilience among Amazon forests. Studying diverse disturbance types within an integrated analytical framework builds capacity to predict the risk of degradation-driven forest transitions.

In face of complex socio-environmental issues experienced in different social-ecological systems, we ask if comprehensive lessons could be learned from cases of community self-organization that were successful in solving collective problems at the local level. Considering that the trajectory of each community is unique and self-organization develops in distinctive settings, we sought to identify the common elements shared by six case studies in Brazil and investigate how they interact (i.e., if they generate feedback that amplifies self-organization), synthesizing the lessons drawn from each case so they may be applied to other contexts. In all cases, community self-organization provided good conditions to overcome crisis and led to desirable changes regarding the problem in question. We explored the underlying mechanisms of successful community self-organization from a social-ecological and community resilience standpoint and identified six elements in common: ability and/or willingness to find opportunities in crisis; partnerships with external actors; human and social capital within the community; generation of income opportunities and/or guarantee of rights; existence of spaces that favor social interaction; and agency oriented to collective mobilization and problem solving. Elements were interconnected and often reinforced one another, generating amplifying feedback, which is seen in the repetition and improvement of practices and attitudes over time and space. Agency was a prominent catalyst for self-organization by generating amplifying feedback that positively affected other elements; it was an element of the feedback chain reinforced by the benefits reaped at the individual level. When collective interests prevailed over individual ones, it was less likely to generate feedback that inhibited self-organization. We argued that ordinary relationships related to different cultural practices and livelihoods were important exercises of collective action that provided communities with a repertoire of responses that could be activated in times of crisis, thus enhancing their capacity to self-organize.