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The Guanabara Bay hydrographic region (GBHR) has served as a central hub for human settlement and resource utilization throughout Brazil's history. However, the region's high population density and intense industrial activity have come at a cost, leading to a significant decline in water quality. This work aimed to identify homogeneous regions in GBHR according to water quality parameters in dry and rainy periods. The following water quality monitoring variables were monitored at 49 gauge stations: total phosphorus (TP), nitrate (NO 3 - ), dissolved oxygen (DO), hydrogenionic potential (pH), turbidity (Turb), thermotolerant coliforms (TCol), total dissolved solids (TDS), biochemical oxygen demand (BOD), water temperature (Tw), and air temperature (Ta). The statistical analysis consisted of determining principal components, cluster analysis, seasonal differences, and Spearman's correlation. The water quality parameter correlations were not expressively influenced by seasonality, but there are differences in the concentrations of these parameters in the dry and rainy periods. In the dry period, urban pressure on water quality is mainly due to fecal coliforms. The resulting clusters delimited areas under urban, agricultural, and forestry influence. Clusters located in areas with high demographic density showed high concentrations of TCol and TP, while clusters influenced by forestry and agriculture had better water quality. In the rainy season, clusters with urban influence showed problems with TCol and TP, in addition to some characteristics in each group, such as high TDS, NO 3 - , and BOD. Forested areas showed high DO, and clusters under agricultural influence had higher concentrations of TCol, BOD, and NO 3 - concerning forested regions. The troubling state of sanitation in GBHR occurs in metropolitan regions due to lack of a formal sanitation system., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Drought indices are a numerical representation of drought conditions aimed to provide quantitative assessments of the magnitude, spatial extent, timing, and duration of drought events. Since the adverse effects of droughts vary according to the characteristics of the event, the socioeconomic vulnerabilities, exposed communities or environments, there is a profusion of drought indicators to assess drought impacts in different sectors. In this study, we evaluated the performance of two drought indices, the Standardized Precipitation Index-SPI and Standardized Precipitation Evapotranspiration Index-SPEI over Brazil derived from gridded meteorological information over the period 1980-2019. Firstly, we compared the gridded derived indices against the same indices derived from weather station data and available from a global dataset for time scales of 3, 6, 12, 24 months. Then we analyzed the spatio-temporal trends in SPI and SPEI time-series, which revealed statistically significant trends toward drier conditions across central Brazil for all time scales, though with more intensity for time scales of 12 months and larger. Trends were more significant in magnitude for SPEI than SPI, indicating an important role in the increase in evaporation, driven by increasingly higher temperatures. Finally, we demonstrated that climate signals are already having a disruptive effect on the country's energy security., Supplementary Information: The online version contains supplementary material available at 10.1007/s11069-022-05759-0., Competing Interests: Conflict of interestThe authors declare that they have no known competing financial interests or personal., (© The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Perennial grasses are promising feedstocks for bioenergy production in the Midwestern USA. Few experiments have addressed how drought influences their carbon fluxes and storage. This study provides a direct comparison of ecosystem-scale measurements of carbon fluxes associated with miscanthus (Miscanthus × giganteus), switchgrass (Panicum virgatum), restored native prairie and maize (Zea mays)/soybean (Glycine max) ecosystems. The main objective of this study was to assess the influence of a naturally occurring drought during 2012 on key components of the carbon cycle and plant development relative to non-extreme years. The perennials reached full maturity 3-5 years after establishment. Miscanthus had the highest gross primary production (GPP) and lowest net ecosystem exchange (NEE) in 2012 followed by similar values for switchgrass and prairie, and the row crops had the lowest GPP and highest NEE. A post-drought effect was observed for miscanthus. Over the duration of the experiment, perennial ecosystems were carbon sinks, as indicated by negative net ecosystem carbon balance (NECB), while maize/soybean was a net carbon source. Our observations suggest that perennial ecosystems, and in particular miscanthus, can provide a high yield and a large potential for CO2 fixation even during drought, although drought may negatively influence carbon uptake in the following year, questioning the long-term consequence of its maintained productivity., (© 2016 John Wiley & Sons Ltd.)

The proliferation of digital cameras co-located with eddy covariance instrumentation provides new opportunities to better understand the relationship between canopy phenology and the seasonality of canopy photosynthesis. In this paper we analyze the abilities and limitations of canopy color metrics measured by digital repeat photography to track seasonal canopy development and photosynthesis, determine phenological transition dates, and estimate intra-annual and interannual variability in canopy photosynthesis. We used 59 site-years of camera imagery and net ecosystem exchange measurements from 17 towers spanning three plant functional types (deciduous broadleaf forest, evergreen needleleaf forest, and grassland/crops) to derive color indices and estimate gross primary productivity (GPP). GPP was strongly correlated with greenness derived from camera imagery in all three plant functional types. Specifically, the beginning of the photosynthetic period in deciduous broadleaf forest and grassland/crops and the end of the photosynthetic period in grassland/crops were both correlated with changes in greenness; changes in redness were correlated with the end of the photosynthetic period in deciduous broadleaf forest. However, it was not possible to accurately identify the beginning or ending of the photosynthetic period using camera greenness in evergreen needleleaf forest. At deciduous broadleaf sites, anomalies in integrated greenness and total GPP were significantly correlated up to 60 days after the mean onset date for the start of spring. More generally, results from this work demonstrate that digital repeat photography can be used to quantify both the duration of the photosynthetically active period as well as total GPP in deciduous broadleaf forest and grassland/crops, but that new and different approaches are required before comparable results can be achieved in evergreen needleleaf forest.

The carbon and water cycles for a southwestern Amazonian forest site were investigated using the longest time series of fluxes of CO2 and water vapor ever reported for this site. The period from 2004 to 2010 included two severe droughts (2005 and 2010) and a flooding year (2009). The effects of such climate extremes were detected in annual sums of fluxes as well as in other components of the carbon and water cycles, such as gross primary production and water use efficiency. Gap-filling and flux-partitioning were applied in order to fill gaps due to missing data, and errors analysis made it possible to infer the uncertainty on the carbon balance. Overall, the site was found to have a net carbon uptake of ≈5 t C ha(-1) year(-1), but the effects of the drought of 2005 were still noticed in 2006, when the climate disturbance caused the site to become a net source of carbon to the atmosphere. Different regions of the Amazon forest might respond differently to climate extremes due to differences in dry season length, annual precipitation, species compositions, albedo and soil type. Longer time series of fluxes measured over several locations are required to better characterize the effects of climate anomalies on the carbon and water balances for the whole Amazon region. Such valuable datasets can also be used to calibrate biogeochemical models and infer on future scenarios of the Amazon forest carbon balance under the influence of climate change.

Soil respiration (Rsoil ) is one of the largest CO2 fluxes in the global carbon (C) cycle. Estimation of annual Rsoil requires extrapolation of survey measurements or gap filling of automated records to produce a complete time series. Although many gap filling methodologies have been employed, there is no standardized procedure for producing defensible estimates of annual Rsoil . Here, we test the reliability of nine different gap filling techniques by inserting artificial gaps into 20 automated Rsoil records and comparing gap filling Rsoil estimates of each technique to measured values. We show that although the most commonly used techniques do not, on average, produce large systematic biases, gap filling accuracy may be significantly improved through application of the most reliable methods. All methods performed best at lower gap fractions and had relatively high, systematic errors for simulated survey measurements. Overall, the most accurate technique estimated Rsoil based on the soil temperature dependence of Rsoil by assuming constant temperature sensitivity and linearly interpolating reference respiration (Rsoil at 10 °C) across gaps. The linear interpolation method was the second best-performing method. In contrast, estimating Rsoil based on a single annual Rsoil - Tsoil relationship, which is currently the most commonly used technique, was among the most poorly-performing methods. Thus, our analysis demonstrates that gap filling accuracy may be improved substantially without sacrificing computational simplicity. Improved and standardized techniques for estimation of annual Rsoil will be valuable for understanding the role of Rsoil in the global C cycle., (© 2012 Blackwell Publishing Ltd.)