ALBERT

Description: In this work, an interval-parameter two-stage stochastic programming (IPTSP) model of water resources allocation was established for maximizing the restored habitat area of large, rare, and endangered water birds by adjusting the recommended scheme of water replenishment under different scenarios and constraints. The established model can efficiently deal with the uncertainties, such as the interval parameters and random variables, in the management system of water resources simultaneously. A case study was conducted in the Momoge National Nature Reserve (MNNR) in northeast China to maximize the restored habitat area of large, rare and endangered water birds based on limited water resources. According to the previous studies, a water area with a depth of 0–40 cm is a suitable habitat area in the MNNR for the Siberian crane, oriental stork, and red-crowned crane. The results of the present work show that the habitat area restored by water replenishment schemes under low, medium, and high flood flow scenarios after optimization increased in comparison to 13.36 × 103 ha of the recommended scheme, with an increase of [0.62, 5.23], [1.49, 6.42], and [2.43, 7.17] × 103 ha, respectively (the two numbers within each bracket represent the lower and upper bounds of the restored habitat areas). As a result, the carrying capacity of suitable habitat areas increased by [0.82, 6.88], [1.96, 8.45], and [3.21, 9.43] × 103 birds, correspondingly. The restored wetland area of the project recommendation scheme was 34.23 × 103 ha, and that of the optimal water replenishment schemes was [29.35, 41.01], [31.02, 44.13], and [33.88, 46.04] × 103 ha, respectively under the three flood flow scenarios. The results reveal that the model constructed in this work realizes the optimization and adjustment of the initial scheme to an increased restored wetland and habitat area with an increase in the flow level. Here, the upper bound of the interval value mentioned above is significantly higher than the lower bound value, which indicates that a feasible decision space was provided for decision makers to optimize and adjust the recommended scheme on the basis of the actual situation. The model-optimized schemes significantly improved the utilization of limited water resources. The results of this study can provide valuable theoretical support for the restoration and protection of rare and endangered water bird habitats and planning and management of water resources.

Description: The optimization of ecological water supplement scheme in Momoge National Nature Reserve (MNNR), using an interval-parameter two-stage stochastic programming model (IPTSP), still experiences problems with fuzzy uncertainties and the wide scope of the obtained optimization schemes. These two limitations pose a high risk of system failure causing high decision risk for decision-makers and render it difficult to further undertake optimization schemes respectively. Therefore, an interval-parameter fuzzy two-stage stochastic programming (IPFTSP) model derived from an IPTSP model was constructed to address the random variable, the interval uncertainties and the fuzzy uncertainties in the water management system in the present study, to reduce decision risk and narrow down the scope of the optimization schemes. The constructed IPFTSP model was subsequently applied to the optimization of the ecological water supplement scheme of MNNR under different scenarios, to maximize the recovered habitat area and the carrying capacity for rare migratory water birds. As per the results of the IPFTSP model, the recovered habitat areas for rare migratory birds under low, medium and high flood flow scenarios were (14.06, 17.88) × 103, (14.92, 18.96) × 103 and (15.83, 19.43) × 103 ha, respectively, and the target value was (14.60, 18.47) × 103 ha with a fuzzy membership of (0.01, 0.83). Fuzzy membership reflects the possibility level that the model solutions satisfy the target value and the corresponding decision risk. We further observed that the habitat area recovered by the optimization schemes of the IPFTSP model was significantly increased compared to the recommended scheme, and the increases observed were (5.22%, 33.78%), (11.62%, 41.88%) and (18.44%, 45.39%). In addition, the interval widths of the recovered habitat areas in the IPFTSP model were reduced by 17.15%, 17.98% and 23.86%, in comparison to those from the IPTSP model. It was revealed that the IPFTSP model, besides generating the optimal decision schemes under different scenarios for decision-makers to select and providing decision space to adjust the decision schemes, also shortened the decision range, thereby reducing the decision risk and the difficulty of undertaking decision schemes. In addition, the fuzzy membership obtained from the IPFTSP model, reflecting the relationship among the possibility level, the target value, and the decision risk, assists the decision-makers in planning the ecological water supplement scheme with a preference for target value and decision risk.

Description: Quinolone (QN) antibiotics are widely used, which lead to their accumulation in soil and toxic effects on ryegrass in pasture. In this study, we employed ryegrass as the research object and selected the total scores of 29 QN molecules docked with two resistant enzyme structures, superoxide dismutase (SOD, PDB ID: 1B06) and proline (Pro, PPEP-2, PDB ID: 6FPC), as dependent variables. The structural parameters of QNs were used as independent variables to construct a QN double-activity 3D-QSAR model for determining the biotoxicity on ryegrass by employing the variation weighting method. This model was constructed to determine modification sites and groups for designing QNs molecules. According to the 3D contour map of the model, by considering enrofloxacin (ENR) and sparfloxacin (SPA) as examples, 23 QN derivatives with low biotoxicity were designed, respectively. The functional properties and environmental friendliness of the QN derivatives were predicted through a two-way selection between biotoxicity and genotoxicity before and after modification; four environmentally friendly derivatives with low biotoxicity and high genotoxicity were screened out. Mixed toxicity index and molecular dynamics methods were used to verify the combined toxicity mechanism of QNs on ryegrass before and after modification. By simulating the combined pollution of ENR and its derivatives in different soils (farmland, garden, and woodland), the types of combined toxicity were determined as partial additive and synergistic. Binding energies were calculated using molecular dynamics. The designed QN derivatives with low biotoxicity, high genotoxicity, and environmental friendliness can highly reduce the combined toxicity on ryegrass and can be used as theoretic reserves to replace QN antibiotics.

Description: In the present work, a comprehensive screening and evaluation system was established to improve the plant–microbial synergistic degradation effects of QNs. The study included the construction of a 3D-QSAR model, the molecular modification, environmental friendliness and functional evaluation of drugs, degradation pathway simulation, and human health risk assessment. Molecular dynamics was applied to quantify the binding capacity of QNs toward the plant degradation enzyme (peroxidase) and microbial degradation enzymes (manganese peroxidase, lignin peroxidase, and laccase). The fuzzy comprehensive evaluation method was used in combination with the weighted average method for normalization and assigning equal weights to the plant and microbial degradation effect values of the QNs. Considering the synergistic degradation effect value as the dependent variable and the molecular information of the QNs as the independent variable, a 3D-QSAR model was constructed for the plant–microbial synergistic degradation effect of QNs. The constructed model was then employed to conduct the molecular modification, environmental friendliness and functional evaluation, degradation pathway simulation, and human health risk assessment of transformation products using pharmacokinetics and toxicokinetics. The results revealed that the synergistic degradation effect 3D-QSAR (CoMSIA) model exhibited good internal and external prediction ability, fitting ability, stability, and no overfitting phenomenon. Norfloxacin (NOR) was used as the target molecule in the molecular modification. A total of 35 NOR derivatives with enhanced plant–microbial synergistic degradation effect (1.32–21.51%) were designed by introducing small-volume, strongly electronegative, and hydrophobic hydrogen bond receptor groups into the active group of the norfloxacin structure. The environment-friendliness and the functionality of NOR were evaluated prior to and after the modification, which revealed seven environment-friendly FQs derivatives exhibiting moderate improvement in stability and bactericidal efficacy. The simulation of the NOR plant and microbial degradation pathways prior to and after the modification and the calculation of the reaction energy barrier revealed Pathway A (D-17 to D-17-2) and Pathway B (D-17 to D-17-4) as the most prone degradation pathways in plants and Pathway A (D-17 to D-17-1) and Pathway B (D-17 to D-17-4) as the most prone degradation pathways in microorganisms. This demonstrated that the degradation of the modified NOR derivatives was significantly enhanced, with the hydroxylation and piperazine ring substitution reaction playing an important role in the degradation process. Finally, the parameters, including hepatotoxicity, mutagenicity, and rodent carcinogenicity, among others, predicted using the pharmacokinetics and toxicokinetics analyses revealed a significant reduction in the human health risk associated with the modified NOR, along with a considerable reduction in the toxicity of its transformation products, implying that the human health risk associated with the transformation products was reduced remarkably. The present study provides a theoretical basis for novel ideas and evaluation programs for improving the plant–microbial synergistic degradation of the QNs antibiotics for source control and drug design, thereby reducing the residues of these antibiotics and the associated hazard in the complex plant–soil environment, ultimately decreasing the potential risks to human health.