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The grapevine (Vitis vinifera) is widely cultivated for the production of wine and other commodities. Wine is globally traded, with an annual market value of approximately USD 4 billion in Portugal alone. However, climate change is expected to profoundly alter regional temperature and precipitation regimes across the Iberian Peninsula and, thus, in continental Portugal, potentially threatening to impact viticulture. We used boosted regression trees and environmental variables describing the climate, soil, topography, and irrigation with a large number of presences (N = 7002) to estimate grapevine suitability for a baseline (1981–2010) and three future periods spanning from 2011 to 2100 using two climate trajectories (SSP3-7.0 and SSP5-8.5) and irrigation scenarios (continued and ceased). Under SSP3-7.0 with irrigation and SSP5-8.5 without irrigation, our results suggest a decline in suitable viticulture area across continental Portugal of ~20% and ~80% by 2041–2070 and 2011–2041, respectively. Following this decline, our data suggest a potential recovery by 2071–2100 of ~6% and ~186%, respectively. However, regional change is more complex: by 2071–2100, the Região Norte, the Douro wine region, and the Algarve, for example, each would experience future changes in suitable area in the range of approximately −92% to −48%, −86% to −24%, and −59% to 267%, respectively, depending mostly on the practicality of irrigation.

A family of Sigmoidal non-linear models is commonly used to determine the critical period of weed control (CPWC) and acceptable yield loss (AYL) in annual crops. We tried to prove another non-linear model to determine CPWC and AYL in a soybean agroforestry system with kayu putih. The three-year experiment (from 2019–2021) was conducted using a randomised complete block design factorial with five blocks as replications. The treatments comprised weedy and weed-free periods. Non-linear models comprised 45 functions. The results show that the Sigmoidal and Dose-Response Curve (DRC) families were the most suitable for estimating CPWC and AYL. The best fitted non-linear model for weedy and weed-free periods in the dry season used the Sigmoidal family consisting of the Weibull and Richards models, while in the wet season the best fit was obtained using the DRC and Sigmoidal families consisting of the DR-Hill and Richards models, respectively. The CPWC of soybean in the dry season for AYL was 5, 10, and 15%, beginning at 20, 22, and 24 days after emergence (DAE) and ended at 56, 54, and 52 DAE. The AYL in the wet season started at 20, 23, and 26 DAE and ended at 59, 53, and 49 DAE.

Aerobic granular sludge (AGS) is known as excellent biological treatment for wastewater industry, high organic load wastewater and adsorption of heavy metal. AGS have some advantages such as higher density, higher biomass retention, simultaneous nutrient removal and higher tolerance to toxicity. The aim of this research is to use sequencing batch reactor (SBR) to cultivate AGS in the short time (28 days) in laboratory scale. Experimental condition that we use to cultivate AGS are based on this parameter: 1.5 hours of total cycle time, 50 % of exchange ratio, 3 hours of HRT and 3 l/min air flow rate. Even the AGS cultivation successfully achieve in 28 days with pH around 7-9, DO 3.6 mg/l, SVI 232.6 mg/l, and MLSS 500 mg/l, it is still need more time to generate more mature AGS to breakdown organic molecule in the wastewater.

Understanding the environmental niche segregation of ammonia-oxidizing archaea (AOA) and bacteria (AOB) and its impact on their relative contributions to nitrification and nitrous oxide (N

Nitrification inhibitors (NIs) such as dicyandiamide (DCD), 3,4-dimethylpyrazole phosphate (DMPP), and allylthiourea (AT) are commonly used to suppress ammonia oxidization at different time scales varying from a few hours to several months. Although the responses of NIs to edaphic and temperature conditions have been studied, the influence of the aforementioned factors on their inhibitory effect remains unknown. In this study, laboratory-scale experiments were conducted to assess the short-term (24 h) influence of eight abiotic and biotic factors on the inhibitory effects of DCD, DMPP, and AT across six cropped and non-cropped soils at two temperature conditions with three covariates of soil texture. Simultaneously, the dominant contributions of ammonia-oxidizing archaea (AOA) and bacteria (AOB) to potential ammonia oxidization (PAO) were distinguished using the specific inhibitor 2 phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl 3-oxide (PTIO). Our results revealed that AT demonstrated a considerably greater inhibitory effect (up to 94.9% for an application rate of 75 mg of NI/kg of dry soil) than DCD and DMPP. The inhibitory effect of AT was considerably affected by the relative proportions of silt, sand, and clay in the soil and total PAO. In contrast to previous studies, the inhibitory effects of all three NIs remained largely unaffected by the landcover type and temperature conditions for the incubation period of 24 h. Furthermore, the efficacy of all three tested NIs was not affected by the differential contributions of AOA and AOB to PAO. Collectively, our results suggested a limited influence of temperature on the inhibitory effects of all three NIs but a moderate dependence of AT on the soil texture and PAO. Our findings can enhance the estimation of the inhibitory effect in soil, and pure cultures targeting the AOA and AOB supported ammonia oxidization and, hence, nitrogen dynamics under NI applications.

Understanding the environmental niche segregation of ammonia-oxidizing archaea (AOA) and bacteria (AOB) and its impact on their relative contributions to nitrification and nitrous oxide (N2O) production is essential for predicting N2O dynamics within an ecosystem. Here, we used ammonia oxidizer-specific inhibitors to measure the differential contributions of AOA and AOB to potential ammonia oxidization (PAO) and N2O fluxes over pH (4.0-9.0) and temperature (10-45 °C) gradients in five soils and three wetland sediments. AOA and AOB activities were differentiated using PTIO (2-phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl 3-oxide), 1-octyne, and acetylene. We used square root growth (SQRT) and macromolecular rate theory (MMRT) models to estimate cardinal temperatures and thermodynamic characteristics for AOA- and AOB-dominated PAO and N2O fluxes. We found that AOA and AOB occupied different niches for PAO, and soil temperature was the major determinant of niche specialization. SQRT and MMRT models predicted a higher optimum temperature for AOA-dominated PAO and N2O fluxes compared with those of AOB. Additionally, PAO was dominated by AOA in acidic conditions, whereas both AOA- and AOB-dominated N2O fluxes decreased with increasing pH. Consequently, net N2O fluxes (AOA and AOB) under acidic conditions were approximately one to three-fold higher than those observed in alkaline conditions. Moreover, structural equation and linear regression modeling confirmed a significant positive correlation (R2 = 0.45, p

Water resource modelling has been used to analyze the sustainability of the watershed affected by human activity and natural disasters. The objective of this research was to evaluate the SWAT model and its applicability in the Keduang Sub-Watershed for streamflow prediction, which is part of Bengawan Solo Watershed. A SWAT integrated with Geographic Information Systems (ArcGIS, version 10.4.1) was used to simulate Keduang Sub-Watershed streamflow for the period from 2008 to 2017. Model calibration and validation were performed for monthly and daily periods using Sequential Uncertainty Fitting 2 (SUFI-2) within SWAT-CUP using daily observed streamflow data at the catchment outlet. The results during calibration and validation periods showed that the value of the Nash-Sutcliffe Efficiency (NSE), the coefficient of determination (R2), Percent Bias (PBIAS) and Root Mean Square (RSR) had different values for daily and monthly simulation. The calibration and validation outputs for daily and monthly simulation showed a good model performance for discharges. In the daily simulation, the value of NSE, R2, PBIAS and RSR were 0.57; 0.58; -3.4 and 0.67 for calibration periods, whereas in the validation period the values of NSE, R2, PBIAS and RSR were 0.50; 0.51; -10.7 and 0.65, respectively. The monthly simulation had better results than the daily simulation where the value of NSE, R2, PBIAS, RSR were 0.79; 0.81; -6.2 and 0.54 for calibration periods, as well as 0.73; 0.69;-1.9 and 0.71 for validation periods, respectively. Those results indicated that the SWAT model was acceptable for Keduang watershed simulation based on the model performance which was higher than the minimum standard acceptance.