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After decades of inadequate responses to scientists’ warnings about global environmental threats, leading analysts of the science-policy interface are seeking an important shift of research focus. This switch is from continued modeling and diagnoses of biogeochemical conditions in favor of enhanced efforts to understand the many socio-political obstacles to achieving just transformations towards sustainability, and how to overcome them. We discuss why this shift continues to prove elusive. We argue that rarely analyzed mutually reinforcing power structures, interests, needs, and norms within the institutions of global environmental change science obstruct rethinking and reform. The blockage created by these countervailing forces are shielded from scrutiny and change through retreats behind shields of neutrality and objectivity, stoked and legitimated by fears of losing scientific authority. These responses are maladaptive, however, since transparency and reflexivity are essential for rethinking and reform, even in contexts marked by anti-environmentalism. We therefore urge greater openness, self-critique, and power-sharing across research communities, to create spaces and support for conversations, diverse knowledges, and decisions conducive to sustainability transformations.

River damming reduces the dispersal rates of biota and filter species by altering the local environmental conditions. Although phytoplankton is a key biotic group to indicate changes in aquatic environments, the effects of river damming on the longitudinal distribution of phytoplankton communities are not widely addressed. Here we investigated the changes on the taxonomic and functional composition of the phytoplankton community in a large tropical dammed river. We expect compositional changes to be higher at taxonomic than functional level especially in the dam-free stretches of the river because running waters select species able to cope with the water turbulence. Furthermore, flow regulation allows species with different traits to colonize the increasingly lentic stretches resulting in higher functional diversity towards dams. Phytoplankton samples were taken in 210 sites, spaced by 5 km, along the whole river channel. Data were split at a reservoir level considering the sites within 30 km before and after each dam to analyze the effects of damming on the community composition. Compositional changes were assessed by estimating the degree to which each community differed from all other communities within the regional pool (community distinctiveness) considering taxonomic and functional composition separately. Functional diversity was estimated as the degree to which species within the same community differed from each other with respect to their trait composition (functional dispersion). We used community-weighted means to test how the different traits were filtered by river damming. Furthermore, we assessed the effects of local environmental conditions on the phytoplankton taxonomic and functional composition using boosted regression trees (BRT). We observed no effects of river damming on species dispersal. Functional turnover was low, suggesting that compositional changes occurred mainly among functionally similar species. However, there was a noticeable reduction of phytoplankton diversity that persisted for more than 100 km after one of the dams. Flow regulation allowed flagellated and mucilaginous species to colonize the dammed areas. After the dams, such species were filtered due to the increase of water mixing downstream, as evidenced by a hump-shaped trend in the functional diversity of the sites within 30 km distance of the dams. BRT analyses highlighted the role of nutrient input in the dammed areas for the community compositional change. This study highlights the importance of considering both taxonomical and functional diversity to describe the effects of human intervention such as damming on aquatic ecosystems.

This study investigated the erosion of the nocturnal boundary layer (NBL) over the central Amazon using a high-resolution model of large-eddy simulation (LES) named PArallel Les Model (PALM) and observational data from Green Ocean Amazon (GoAmazon) project 2014/5. This data set was collected during four intense observation periods (IOPs) in the dry and rainy seasons in the years 2014 (considered a typical year) and 2015, during which an El Niño-Southern Oscillation (ENSO) event predominated and provoked an intense dry season. The outputs from the PALM simulations represented reasonably well the NBL erosion, and the results showed that it has different characteristics between the seasons. During the rainy season, the IOPs exhibited slow surface heating and less intense convection, which resulted in a longer erosion period, typically about 3 h after sunrise (that occurs at 06:00 local time). In contrast, dry IOPs showed more intensive surface warming with stronger convection, resulting in faster NBL erosion, about 2 h after sunrise. A conceptual model was derived to investigate the complete erosion during sunrise hours when there is a very shallow mixed layer formed close to the surface and a stable layer above. The kinematic heat flux for heating this layer during the erosion period showed that for the rainy season, the energy emitted from the surface and the entrainment was not enough to fully heat the NBL layer and erode it. Approximately 30% of additional energy was used in the system, which could come from the release of energy from biomass. The dry period of 2014 showed stronger heating, but it was also not enough, requiring approximately 6% of additional energy. However, for the 2015 dry period, which was under the influence of the ENSO event, it was shown that the released surface fluxes were sufficient to fully heat the layer. The erosion time of the NBL probably influenced the development of the convective boundary layer (CBL), wherein greater vertical development was observed in the dry season IOPs (~1500 m), while the rainy season IOPs had a shallower layer (~1200 m).

Desertification is one of the major environmental problems that humanity faces today, since it reduces the availability of ecosystem services, increases food insecurity and poverty, and affects the wellbeing of societies. The analysis of the process is extremely complex, since the phenomenon takes place at different temporal and spatial scales, influenced by different factors. It is widely recognized that land use/land cover change (LULC) is one of the main drivers of desertification since environmental degradation is always triggers by the removal of natural vegetation cover. In this study, a LULC change model was calibrated and validated using climate model simulations, demographic data and land susceptibility maps for the historical period 20002010. Then, desertification susceptibility of the Northeast of Brazil were estimated by integrating LULC trajectories with three different downscaled climate change scenarios and projection of population growth for the period 20152025, 20252035, and 20352045 for the emission scenarios RCP4.5 and RCP8.5. Results indicated that, between 2010 and 20352045, areas of moderate susceptibility decreased 10.34%, while areas of high susceptibility increased 12.28% in the case of the RCP4.5. For the RCP8.5 scenario, those numbers are −16.85% for moderate susceptibility, and +19.62% for high susceptibility. Among all indicators included in the analysis, land management was the main driver of desertification susceptibility, which indicates that mitigation and adaptation strategies for the region should pursue sustainable land use policies.

We investigated the water use of Caatinga vegetation, the largest seasonally dry forest in South America. We identified and analysed the environmental phenological drivers in woody species and their relationship with transpiration. To monitor the phenological evolution, we used remote sensing indices at different spatial and temporal scales: normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and green chromatic coordinate (GCC). To represent the phenology, we used the GCC extracted from in-situ automated digital camera images; indices calculated based on sensors included NDVI, SAVI and GCC from Sentinel-2A and B satellites images, and NDVI products MYD13Q1 and MOD13Q1 from a moderate-resolution imaging spectroradiometer (MODIS). Environmental drivers included continuously monitored rainfall, air temperature, soil moisture, net radiation, and vapour pressure deficit. To monitor soil water status and vegetation water use, we installed soil moisture sensors along three soil profiles and sap flow sensors for five plant species. Our study demonstrated that the near-surface GCC data played an important role in permitting individual monitoring of species, whereas the species’ sap flow data correlated better with NDVI, SAVI, and GCC than with species’ near-surface GCC. The wood density appeared to affect the transpiration cessation times in the dry season, given that species with the lowest wood density reach negligible values of transpiration earlier in the season than those with high woody density. Our results show that soil water availability was the main limiting factor for transpiration during more than 80% of the year, and that both the phenological response and water use are directly related to water availability when relative saturation of the soil profile fell below 0.25.

Extreme rainfall events are likely to become more frequent according to recent scenarios of climate change. This issue is especially important over regions with complex topography, which enhances rainfall variability when associated with weather patterns. The state of Rio de Janeiro (SRJ), southeastern Brazil, is characterized by altitudes ranging from the mean sea level up to 2500 m.a.s.l, in mountain ranges and valleys covering significant parts of the region. Time series data of annual maximum daily rainfall were obtained from 110 stations with a data coverage of at least 20 years, from 1960 to 2010. The Probability Distribution Functions (PDFs) normal, log-normal, exponential, gamma, Gumbel, Weibull, and Generalized Extreme Value (GEV) were fitted to maximum rainfall series. Goodness-of-fit tests (Chi-squared – χ2 and Anderson-Darling) revealed that the Gumbel, GEV, and log-normal were found to be the best choices. However,the Gumbel and GEV PDFs were the best ranking by the χ2 and Anderson-Darling test, respectively. Extreme rainfall events with different recurrence intervals (5, 10, 25, 50 and 100 years) were calculated based on the Gumbel and GEV Cumulative Distribution Function (CDF). The differences between extreme values from Gumbell and GEV function increased as the shape parameter increases from zero, with higher probability and extreme value. Five regions with homogeneous patterns of extreme rainfall were identified using clustering analysis (Ward’s method) and different recurrence intervals. Overall, the regions with higher values of extreme rainfall in all scenarios and CDFs were the ones close to the coast, within 40 km, and south of Serra dos Órgãos mountain range, located in the middle of the state. The mountain range separates the state in two halves, concentrating higher values of extreme rainfall in the lower part, where the city of Rio de Janeiro, the state’s capital, is located. Scenarios for both CDF (GEV and Gumbel) indicated daily rainfall events up to 200 mm, with recurrence intervals of 50 to 100 years. In addition, the southernmost part of the state is subjected to rainfall extremes up to 260 mm in scenarios of 50 to 100 years of recurrence interval. This region, and the state’s capital, are characterized by complex topography and a high fraction of population living in slums over hills, or lowlands near the ocean, increasing the vulnerability to events such as landslides and floods associated with extreme rainfall.

The effects of the visible light wavelengths on germination, mycelial radial growth, and conidial production of the plant pathogens Colletotrichum acutatum and Fusarium fujikuroi were studied. Both fungi were grown on potato dextrose agar medium (PDA) in the dark (control) or on PDA under continuous white, blue, green or red light. In addition, the conidia from each treatment were exposed to UV radiation. The germination and growth of both plant pathogenic fungi were not affected by any of the treatments. C. acutatum produced more conidia when the fungus grew under white and red light. F. fujikuroi produced more conidia in the dark. The tolerances to UV radiation of conidia produced on different light and dark treatments differed for both C. acutatum and F. fujikuroi. Conidia of C. acutatum were at least 30% more tolerant to UV radiation when they were produced under white light than under blue and green light and at least 20% more tolerant than conidia produced in the dark. Conidia of C. acutatum produced under red light were the least tolerant. Conidia of F. fujikuroi produced under white and blue light were at least 30% more UV tolerant than conidia produced in the dark, green, and red light. In conclusion, no differences were found for germination and growth for both fungi under different light regimes and dark; however, significant differences occurred both in production and UV radiation of conidia.

Desertification is a serious threat to human development and sustainability. This process is characterized by land degradation over areas with dry sub-humid, semi-arid and arid climate. In this work, climate susceptibility to desertification was identified for the state of Rio de Janeiro (SRJ), Brazil, the third most populated state in the country. The state is characterized by complex topography, and diverse climate and land uses. Two formulations for the aridity index were used: Ia, defined by Thornthwaite (1948, Geographical Review, 38(1), 5594) and Penman (1953, Horticultural Congress, 2, 913924), and D, a modification of Ia by Hare (1983, Climate and Desertification: A Revised Analysis, Geneva: World Meteorological Organization). Both estimates of the aridity require annual rainfall and potential evapotranspiration, which were calculated from the climatological water balance using times series of rainfall and air temperature (19612010) from 98 stations over the SRJ. Annual rainfall, evapotranspiration, water deficit and the aridity indices were then spatially interpolated over a 5 × 5-km grid using a spline tension method. Both indices agree on the driest regions of the SRJ: Norte and Baixada Litorânea, near the northern coast, both under sub-humid and semi-arid climate. The index Ia indicated susceptibility to desertification over 2,305 km2 on the Norte and Baixada Litorânea regions, which correspond to 5% of SRJ area; similarly, the index D classified a smaller area over the Norte region under desertification (431 km2). These subregions, among the others also considered in this study, are of great importance for the agricultural, forestry and tourism industries and contribute immensely to the economic development of the state. Hence, the evaluation of susceptibility to desertification in those areas is essential to help prevent further land degradation and support policies formulation on long-term sustainable management of land and water resources, especially under regional and global climate change scenarios. The methodology used in this work can be applied to studies of desertification in other regions of the world.

Climate change has caused an increased occurrence of heat waves. As a result of rising temperatures, implications for health and the environment have been more frequently reported. Outdoor labour activities deserve special attention, as is the case with agricultural and construction workers exposed to extreme weather conditions, including intense heat. This paper presents an overview of heat stress conditions in Brazil from 1961 to 2010. It also presents computer-simulated projections of heat stress conditions up to the late 21st century. The proposed climate analysis drew on historical weather data obtained from national weather stations and on reanalysis data, in addition to future projections with the ETA (regarding the model’s unique vertical coordinate) regional forecast model. The projections took into consideration two Representative Concentration Pathways (RCP)the 4.5 and 8.5 climate scenarios, namely, moderate and high emissions scenarios, respectively. Heat stress was inferred based on the wet-bulb globe temperature (WBGT) index. The results of this climate analysis show that Brazilian outdoor workers have been exposed to an increasing level of heat stress. These results suggest that future changes in the regional climate may increase the probability of heat stress situations in the next decades, with expectations of WBGT values greater than those observed in the baseline period (19611990). In terms of spatial distribution, the Brazilian western and northern regions experienced more critical heat stress conditions with higher WBGT values. As a response to the increased frequency trends of hot periods in tropical areas, urgent measures should be taken to review public policies in Brazil. Such policies should include actions towards better working conditions, technological development to improve outdoor labour activities, and employment legislation reviews to mitigate heat impacts on occupational health.

O objetivo principal deste estudo é avaliar a capacidade da quinta fase dos modelos do Coupled Model Intercomparison Project (CMIP5) em simular chuvas semanais sobre o Brasil Tropical. Vinte e quatro anos do experimento histórico de dezesseis modelos para as estações do verão e outono austral foram avaliados. Nas análises realizadas neste estudo, a distribuição de frequência e a correlação foram utilizadas para avaliar a variabilidade temporal. Análise de componentes principais para verificar as características do padrão dominante de cada modelo. Os resultados sugerem que alguns modelos apresentam dificuldade em simular o padrão espacial de precipitação regional, principalmente em relação à frequência de eventos e variação temporal, porém, o padrão dominante encontrado pela Análise de Componentes Principais mostrou que pelo menos seis modelos (ACCESS1-0, CanESM2, EC-EARTH, GFDL-CM3, MIROC5 e MRI-CGCM3) representaram razoavelmente o regime de precipitação no espaço temporal sobre o Brasil Tropical.

The objective of this study was to use physically based models to carry out a back-analysis of the set of factors that may have infuenced slope instability and the consequent development of 65 landslides in the Bengalar Stream basin, located in the Northern Region of São José dos Campos, São Paulo State, Brazil, associated with rainfall between March 7 and 8, 2016. Unlike other models, the FS FIORI model used in this study allowed extra variables to be added to the model that can infuence hillslope stability and is associated with land use and land cover (LULC) variability. Analysis of intense short-term and accumulated long-term rainfall infuence on slope instability was possible via a TRIGRS model. A comparative analysis was also carried out between a static model (FS FIORI) and a transient model (TRIGRS) which considered the factor of safety and pore pressure to be a function of precipitation and infltration rates. Despite the diferences in their hydrological components, both models were shown to present relatively similar and demonstrated stability rates coherence, according to the characteristics of each model. The FS FIORI model only classifed 1.3% of the entire basin as unstable (FS≤1), whereas the TRIGRS model classifed 4.5% and 2.9% of the entire basin as unstable in scenarios 1 and 2, respectively. The validity and the accuracy of each model were tested via a receiver operating characteristic (ROC) curve and an area under the curve (AUC). AUC values were: 0.6552 for the FS FIORI model, and 0.7238 and 0.7186 for scenarios 1 and 2 of the TRIGRS model, respectively. The models performed well, with values considered to be acceptable. These results demonstrate an advancement in slope stability modeling studies, including conditioning factors associated with LULC for slope stability calculations.

Terrestrial biomes are the main reservoirs of biodiversity and CO2 on the planet. In South America, they play a crucial role in climate regulation and biodiversity conservation. Despite scientific advances and recent efforts, there is still no detailed analysis of trends in surface air temperature and precipitation changes until the end of the 21st century and magnitude of change for South Americas terrestrial biomes. In this study, we used the annual mean of temperature and annual cumulative precipitation variables provided by WorldClim (version 2.1) from an ensemble of five Global Circulation Models from the most recent simulations of the CMIP6 project. We used four-time intervals between 2020 and 2100, combined at two climatic trajectories (SSP2-4.5 and SSP5-8.5), to map climate change scenarios trend magnitude in South America. Also, we evaluate the exposure level of the nine terrestrial biomes according to their respective vegetal cover densities. Our results indicate that in the two possible futures evaluated (SSP2-4.5 & SSP5-8.5), the terrestrial biomes of South America would be exposed to climatic conditions that are not analogous to the current ones. The results indicate a persistent and long-term annual temperature trend increase, indistinctly for all terrestrial biomes and a significant moisture reduction in forest biomes. The consolidation of such climate scenarios can make potentially modify water and carbon cycling patterns and promoting biodiversity loss, mainly at forest biomes, with probably more severe effects under the pessimistic scenario.