A literature analysis of 158 papers published in international peer-reviewed journals indexed by the Thomson Reuters Web of Knowledge from 1994 to 2013 showed that CO2C emission was significantly lower in free water surface (FWS) constructed wetlands (CW) than in subsurface flow (SF) CWs (median values from 95.8 to 137.0 mg m−2h−1, respectively). In vertical subsurface flow (VSSF) CWs the CH4Cemission was significantly lower than in horizontal subsurface flow (HSSF) CWs (median values 3.0, 6.4,and 4.0 mg m−2h−1, respectively). There were no significant differences in N2O N emission in various Cw types (median for FWS, VSSF and HSSF CWs: 0.09, 0.12, and 0.13 mg m−2h−1correspondingly).The highest value of emission factor (EF) of CH4((CH4C/inflow TOCin) * 100%) was found for FWSCWs (median 18.0%), followed by HSSF CWs (3.8%), and VSSF CWs (1.28%). Median values of N2O EFs((N2O N/inflow TNin) * 100%) differed significantly in all three CW types: 0.34% for HSSF, 0.11% for FWS,and 0.018% for VSSF CWs.We found a significant correlation between TOCin and CH4C emission and between the TNinandN2O N emission values for all of the types of CWs we studied.Hybrid CWs (e.g., the subsequent combination of VSSF, HSSF and FWS CWs) are beneficial from thepoint of view of both water purification and minimization of greenhouse gas (GHG) emissions. Likewise,intermittent loading in VSSF CWs and macrophyte harvesting in HSSF and FWS CWs can mitigate GH Gemissions.201

This work brings a refined estimation of the land use change and derived CO₂ emissions associated with sugarcane cultivation, including changes in management practices and refined land-use carbon stocks, over the last two decades for Brazil’s center–south and north regions. The analysis was carried out at the rural property level, considering spatially explicit land conversion data. With the refinements, we found a net carbon removal of 9.8 TgCO₂∙yr⁻¹ in sugarcane cultivation areas in the 2000–2020 period, which was due to the expansion of sugarcane over poor quality pastures (55% of the gross removals), croplands (15%) and mosaic (14%) areas, and the transition from the conventional burned harvesting to unburned (16%). Moreover, 98.4% of expansion was over existent agricultural areas. Considering all the land use changes within sugarcane-producing rural properties, the net removal is even larger, of 17 TgCO₂∙yr⁻¹, which is due to vegetation recovery. This suggests that public policies and private control mechanisms might have been effective not only to control deforestation but also to induce carbon removals associated with sugarcane cultivation. These results indicate sugarcane production system and derived products as contributors to net carbon removals in the land sector in Brazil and should be considered for both bioenergy and agricultural sustainability evaluation.

The unavoidable diet change in emerging countries, projected for the coming years, will significantly increase the global consumption of animal protein. It is expected that Brazilian livestock production, responsible for close to 15% of global production, be prepared to answer to the increasing demand of beef. Consequently, the evaluation of pasture quality at regional scale is important to inform public policies towards a rational land use strategy directed to improve livestock productivity in the country. Our hypothesis is that MODIS images can be used to evaluate the processes of degradation, restoration and renovation of tropical pastures. To test this hypothesis, two field campaigns were performed covering a route of approximately 40,000 km through nine Brazilian states. To characterize the sampled pastures, biophysical parameters were measured and observations about the pastures, the adopted management and the landscape were collected. Each sampled pasture was evaluated using a time series of MODIS EVI2 images from 2000–2012, according to a new protocol based on seven phenological metrics, 14 Boolean criteria and two numerical criteria. The theoretical basis of this protocol was derived from interviews with producers and livestock experts during a third field campaign. The analysis of the MODIS EVI2 time series provided valuable historical information on the type of intervention and on the biological degradation process of the sampled pastures. Of the 782 pastures sampled, 26.6% experienced some type of intervention, 19.1% were under biological degradation, and 54.3% presented neither intervention nor trend of biomass decrease during the period analyzed.

Nitrogen (N) is the main nutrient element that maintains productivity in forages; it is inextricably linked to dry matter increase and plant support capacity. In recent years, high spectral and spatial resolution remote sensors, e.g., the European Space Agency (ESA)’s Sentinel satellite missions, have become freely available for agricultural science, and have proven to be powerful monitoring tools. The use of vegetation indices has been essential for crop monitoring and biomass estimation models. The objective of this work is to test and demonstrate the applicability of different vegetation indices to estimate the biomass productivity, the foliar nitrogen content (FNC), the plant height and the leaf area index (LAI) of several tropical grasslands species submitted to different nitrogen (N) rates in an experimental area of São Paulo, Brazil. Field reflectance data of Panicum maximum and Urochloa brizantha species’ cultivars were taken and convoluted to the Sentinel-2 satellite bands. Subsequently, different vegetation indices (Normalized Difference Vegetation Index (NDI), Three Band Index (TBI), Difference light Height (DLH), Three Band Dall’Olmo (DO), and Normalized Area Over reflectance Curve (NAOC)) were tested for the experimental grassland areas, and composed of Urochloa decumbens and Urochloa brizantha grass species, which were sampled and destructively analyzed. Our results show the use of different relevant Sentinel-2 bands in the visible (VIS)–near infrared (NIR) regions for the estimation of the different biophysical parameters. The FNC obtained the best correlation for the TBI index combining blue, green and red bands with a determination coefficient (R²) of 0.38 and Root Mean Square Error (RMSE) of 3.4 g kg⁻¹. The estimation of grassland productivity based on red-edge and NIR bands showed a R² = 0.54 and a RMSE = 1800 kg ha⁻¹. For the LAI, the best index was the NAOC (R² = 0.57 and RMSE = 1.4 m² m⁻²). High values of FNC, productivity and LAI based on different sets of Sentinel-2 bands were consistently obtained for areas under N fertilization.

O objetivo deste trabalho foi identificar a estrutura de dependência espacial de atributos do solo e sua interferência na produção de biomassa epígea de pastagem de capim‑marandu (Urochloa brizantha). Amostras de Latossolo Vermelho‑Amarelo foram coletadas em rede de pontos georreferenciados, para a determinação de atributos físicos e químicos do solo e da produção de biomassa epígea da pastagem, no verão e outono de 2010/2011. Verificou-se dependência espacial das variáveis, por meio de análise geoestatística com construção e ajuste de semivariogramas, interpolação por krigagem ordinária e espacialização em mapas de isolinhas. A dependência espacial ocorreu para alguns atributos físicos e químicos do solo (areia, densidade, resistência à penetração, infiltração, pH, MO, P, K, Ca, Mg, H+Al, Al, CTC e V), e para a biomassa da pastagem medida nas estações verão e outono. A análise espacial de atributos físicos do solo permite identificar áreas degradadas da pastagem. A biomassa da pastagem é mais influenciada pelos atributos físicos do solo do que pelos químicos.

The objective of this study was to apply the Simple Algorithm For Evapotranspiration Retrieving (SAFER) with MODIS images together with meteorological data to analyze evapotranspiration (ET) and biomass production (BIO) according to indicative classes of pasture degradation in Upper Tocantins River Basin. Indicative classes of degraded pastures were obtained from the NDVI time-series (2002-2012). To estimate ET and BIO in each class, MODIS images and data from meteorological stations of the year 2012 were used. The results show that compared to not-degraded pastures, ET and BIO were different in pastures with moderate to strong degradation, mainly during water stress period. Therefore, changes in energy balance partition may occur according to the degradation levels, considering that those indicatives of degradation processes were identified in 24% of the planted pasture areas. In this context, ET and BIO estimates using remote sensing techniques can be a reliable indicator of forage availability, and large-scale aspects related to the degradation of pastures. It is expected that this knowledge may contribute to initiatives of public policies aimed at controlling the loss of production potential of pasture areas in the Upper Tocantins River Basin in the state of Goiás, Brazil.