Both ammonia-oxidizing bacteria (AOB) and archaea (AOA) can play important roles in ammonia biotransformation in ecosystems. However, the factors regulating the distribution of these microorganisms in lacustrine ecosystems remain essentially unclear. The present study investigated the effects of geographic location on the distribution of sediment AOA and AOB in 13 freshwater lakes on the Yunnan Plateau (China). The spatial dissimilarity in the abundance and structure of sediment AOA and AOB communities was observed in these plateau lakes. AOA abundance was usually less than AOB abundance, and the AOA/AOB ratio was positively correlated with water depth. Nitrososphaera-like AOA occurred in most of the studied lakes and were dominant in two lakes. Nitrosospira was the dominant AOB species in most of the lakes, while Nitrosomonas showed high abundance only in three lakes. In addition, geographic location was found to affect lake sediment AOB community structure.
Understanding the relationships between hydrological regime and climate change is important for water resources management. In this study, the streamflow response to climate change was investigated in the Lake Dianchi watershed, which is one of the most important eutrophic lakes in China. Daily time-series of temperature and precipitation in the future periods (2020, 2050 and 2080s) were projected from HadCM3 model. Statistical downscaling model (SDSM) and the previously calibrated and validated Soil and water assessment tool (SWAT) model were used to quantify the impacts of climate change on streamflow in this watershed. The results showed that SDSM can well capture the statistical relationships between the large scale climate variables and the observed weather at regional scale. The downscaled results showed that annual average maximum and minimum temperature would rise by 4.28 (3.25) and 4.71 A degrees C (3.33 A degrees C) in the 2080s under A2 (B2) scenario. Annual average precipitation would decrease within the range between 20.34 and 74.12 mm under both scenarios in the future. Based on SWAT model simulation, annual average streamflow would decrease in the future by the declination of -7.12 to -21.83 % and -6.34 to -17.09 % under A2 (B2) scenarios in the outlet of this watershed. The frequency of drought and extreme rainfall events would increase in the future, which is not beneficial to protect Lake Dianchi. This study could lead to a better understanding of the streamflow response under climate change and also raised concerns about the sustainability of future water resources in Lake Dianchi watershed.
Both Bacteria and Archaea might be involved in various biogeochemical processes in lacustrine sediment ecosystems. However, the factors governing the intra-lake distribution of sediment bacterial and archaeal communities in various freshwater lakes remain unclear. The present study investigated the sediment bacterial and archaeal communities in 13 freshwater lakes on the Yunnan Plateau. Quantitative PCR assay showed a large variation in bacterial and archaeal abundances. Illumina MiSeq sequencing illustrated high bacterial and archaeal diversities. Bacterial abundance was regulated by sediment total organic carbon and total nitrogen, and water depth, while nitrate nitrogen was an important determinant of bacterial diversity. Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, Chlorobi, Chloroflexi, Cyanobacteria, Firmicutes, Gemmatimonadetes, Nitrospirae, Planctomycetes, and Verrucomicrobia were the major components of sediment bacterial communities. Proteobacteria was the largest phylum, but its major classes and their proportions varied greatly among different lakes, affected by sediment nitrate nitrogen. In addition, both Euryarchaeota and Crenarchaeota were important members in sediment archaeal communities, while unclassified Archaea usually showed the dominance.
Integrated continuous simulation-optimization models can be effective predictors of a process-based responses for cost-benefit optimization of best management practices (BMPs) selection and placement. However, practical application of simulation-optimization model is computationally prohibitive for large-scale systems. This study proposes an enhanced Nonlinearity Interval Mapping Scheme (NIMS) to solve large-scale watershed simulation-optimization problems several orders of magnitude faster than other commonly used algorithms. An efficient interval response coefficient (IRC) derivation method was incorporated into the NIMS framework to overcome a computational bottleneck. The proposed algorithm was evaluated using a case study watershed in the Los Angeles County Flood Control District. Using a continuous simulation watershed/stream-transport model, Loading Simulation Program in C++ (LSPC), three nested in-stream compliance points (CP)each with multiple Total Maximum Daily Loads (TMDL) targetswere selected to derive optimal treatment levels for each of the 28 subwatersheds, so that the TMDL targets at all the CP were met with the lowest possible BMP implementation cost. Genetic Algorithm (GA) and NIMS were both applied and compared. The results showed that the NIMS took 11 iterations (about 11 min) to complete with the resulting optimal solution having a total cost of \$67.2 million, while each of the multiple GA executions took 21-38 days to reach near optimal solutions. The best solution obtained among all the GA executions compared had a minimized cost of \$67.7 millionmarginally higher, but approximately equal to that of the NIMS solution. The results highlight the utility for decision making in large-scale watershed simulation-optimization formulations.
Both aerobic methane-oxidizing bacteria (MOB) and nitrite-dependent anaerobic methane oxidation (n-damo) bacteria can play an important role in mitigating the methane emission produced in anoxic sediment layers to the atmosphere. However, the environmental factors regulating the distribution of these methane-oxidizing microorganisms in lacustrine ecosystems remain essentially unclear. The present study investigated the distribution of aerobic MOB and n-damo bacteria in sediments of various freshwater lakes on the Yunnan Plateau (China). Quantitative PCR assay and clone library analysis illustrated the spatial variations in the abundances and structures of aerobic MOB and n-damo bacterial communities. Type I MOB (Methylosoma and Methylobacter) and type II MOB (Methylocystis) were detected, while type I MOB was more abundant than type II MOB. Lake sediments n-damo bacterial communities were composed of novel Methylomirabilis oxyfera-like pmoA genes. Lake sediments in the same geographic region could share a relatively similar aerobic MOB community structure. Moreover, Pearson's correlation analysis indicated that n-damo pmoA gene diversity showed a positive correlation with the ratio of organic matter to total nitrogen in lake sediment.
Eutrophication has become a top environmental issue for most lake ecosystems in the world and enhanced phosphorus (P) input is usually considered the primary stressor. Focused on the role of phosphorus in eutrophic lakes, a bibliometric approach was applied to quantitatively evaluate the main interests of research and trends in this area. Using data from the Science Citation Index Expanded database between 1900 and 2013, a total of 3,875 publications was returned by searching topic keywords. Spatial, temporal, and interactive characteristics of the articles, countries, and keywords are presented using time series, frequency, and co-occurrence analysis. Result shows that the annual publications on P in eutrophic lakes keep an exponential growth (R (2) = 0.93; p < 0.0001) over the last two decades, reflecting an increasing attraction in this area. However, publications of phosphorus research make up only 40 % of total records in eutrophic lakes, indicating that there are other significant topics in eutrophication problems of lakes. The USA is the largest output country in this area, contributing 23 % of the total articles, followed by China with a proportion of 15 %. However. China has replaced the USA as the largest output country in the world since 2011, but its citation per paper is significantly lower than the USA, indicating its' favor on quantity over quality. Based on international cooperation analysis, five regional groups were found, and the USA, the UK, P.R. China, Sweden, and German are the centers of their groups. The top 20 title keywords, author keywords and keywords plus were identified according to their frequency to assist our understanding of interests of research and modes. Surprisingly, nitrogen is a high co-occurrence keyword in this study, and its share of publications with P research in eutrophic lakes is increasing rapidly. Furthermore, the high correlation between P and N research in spatial distribution also indicates the increasing significance of N research in eutrophic lakes.
Meteorological trend analysis is a useful tool for understanding climate change and can provide useful information on the possibility of future change. Lake Dianchi is the sixth largest freshwater body in China with serious eutrophication. Algal blooms outbreak was proven to be closely associated with some climatic factors in Lake Dianchi. It is therefore essential to explore the trends of climatic time series to understand the mechanism of climate change on lake eutrophication. We proposed an integrated method of Mann-Kendall (MK) test, seasonal-trend decomposition using locally weighted regression (LOESS) (STL), and regime shift index (RSI) to decompose the trend analysis and identify the stable and abrupt changes of some climate variables from 1951 to 2009. The variables include mean air temperature (Tm), maximum air temperatures (Tmax), minimum air temperatures (Tmin), precipitation (Prec), average relative humidity (Hum), and average wind speed (Wind). The results showed that (a) annual Tm, Tmax, and Tmin have a significant increasing trend with the increasing rates of 0.26, 0.15and 0.43 A degrees C per decade, respectively; (b) annual precipitation has an insignificant decreasing trend with the decreasing rate of 3.17 mm per decade; (c) annual Hum has a significant decreasing trend in all seasons; and (d) there are two turning points for temperature rise around 1980 and 1995 and two abrupt change periods for precipitation with the extreme points appearing in 1963 and 1976. Temperature rise and precipitation decline in summer and autumn as well as wind speed decrease after the 1990s may be an important reason for algal blooms outbreak in Lake Dianchi. This study was expected to provide foundation and reference for regional water resource management.
Aerobic methane-oxidizing bacteria (MOB) play an important role in mitigating the methane emission in soil ecosystems to the atmosphere. However, the impact of plant species and plantation ways on the distribution of MOB remains unclear. The present study investigated MOB abundance and structure in plateau soils with different plant species and plantation ways (natural and managed). Soils were collected from unmanaged wild grassland and naturally forested sites, and managed farmland and afforested sites. A large variation in MOB abundance and structure was found in these studied soils. In addition, both type I MOB (Methylocaldum) and type II MOB (Methylocystis) were detected in these soils, while type II MOB usually outnumbered type I MOB. The distribution of soil MOB community was found to be collectively regulated by plantation way, plant species, the altitude of sampling site, and soil properties.
The environmental degradation of lakes in China has become increasingly serious over the last 30 years and eutrophication resulting from enhanced nutrient inputs is considered a top threat. In this study, a quasi-mass balance method, net anthropogenic N inputs (NANI), was introduced to assess the human influence on N input into three typical Chinese lake basins. The resultant NANI exceeded 10 000 kg N km(-2) year(-1) for all three basins, and mineral fertilizers were generally the largest sources. However, rapid urbanization and shrinking agricultural production capability may significantly increase N inputs from food and feed imports. Higher percentages of NANI were observed to be exported at urban river outlets, suggesting the acceleration of NANI transfer to rivers by urbanization. Over the last decade, the N inputs have declined in the basins dominated by the fertilizer use but have increased in the basins dominated by the food and feed import. In the foreseeable future, urban areas may arise as new hotspots for nitrogen in China while fertilizer use may decline in importance in areas of high population density.
Lake eutrophication is associated with excessive nutrient enrichment and unobserved internal nutrient cycling. In spite of advances in understanding the role of nitrogen (N) and phosphorus (P) cycling in eutrophication, the relative importance of N and P limitation and release from sediment is still an open question. The complicated interaction between N and P cycling and external driving factors leads to dynamics in N or P limitation patterns and internal release that change over time. We developed a nutrient-driven model of phytoplankton dynamics including the critical nutrient cycling processes. It was fitted using Bayesian inference to explore the roles of N and P inputs from external sources, net sediment release, and internal dynamics in Lake Yilong, a shallow eutrophic lake in China. The model provided a good fit to observations, with time-varying parameters required to fit time-dependent variations in the sediment release process. The results demonstrated that, in Lake Yilong, the pattern of nutrient limitation showed a transformation from P limitation to N and P co-limitation after an observed regime shift occurred in 2008. After the shift in 2008, sediment release had an increasing influence on N and P supply, which could make eutrophication remediation more difficult. For Lake Yilong, it would not be possible to reverse eutrophication solely with watershed nutrient load reduction so in-lake manipulation of physical chemical conditions to inhibit the sediments release should also be considered. (C) 2015 Elsevier B.V. All rights reserved.
Both ammonia-oxidizing archaea (AOA) and bacteria (AOB) can be involved in biotransformation of ammonia to nitrite in soil ecosystems. However, the distribution of AOA and AOB in plateau soils and influential factors remain largely unclear. In the present study, the activity, abundance and structure of ammonia oxidizers in different soils on the Yunnan Plateau were assessed using potential nitrification rates (PNRs), quantitative PCR assay and clone library analysis, respectively. Wide variation was found in both AOA and AOB communities in plateau soils. PNRs showed a significant positive correlation with AOB abundance. Both were determined by the ratio of organic carbon to nitrogen (C/N) and total phosphorous (TP). AOB could play a more important role in ammonia oxidation. AOB community diversity was likely affected by soil total nitrogen (TN) and total organic carbon (TOC) and was usually higher than AOA community diversity. Moreover, Nitrososphaera- and Nitrosospira-like organisms, respectively, were the dominant AOA and AOB in plateau soils. AOA community structure was likely shaped by TP and C/N, while AOB community structure was determined by pH. (c) 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.
Ammonia oxidation is known to be performed by both ammonia-oxidizing archaea (AOA) and bacteria (AOB), although their relative significance to nitrification process in soil ecosystems remains controversial. The distribution of AOA and AOB in plateau soils with different land use types and the influential factors remains unclear. The present study investigated the abundance and structure of AOA and AOB communities in upland soils adjacent to Erhai Lake in the Yunnan Plateau (China). Quantitative PCR assays indicated a large variation in the community size of AOA and AOB communities, with the numerical dominance of AOA over AOB in most of soils. Clone library analysis illustrated a marked shift in the structure of soil AOA and AOB communities. A high abundance of Nitrososphaera- and Nitrosotalea-like AOA was observed, while Nitrosospira-like species predominated in AOB. AOA and AOB abundance was positively influenced by total nitrogen and moisture content, respectively. Moreover, moisture content might be a key determinant of AOA community composition, while C/N and nitrate nitrogen played an important role in shaping AOB community composition. However, further efforts will be necessary in order to elucidate the links between soil AOA and AOB and land use.
Predictions in ungauged basins (PUBs) are an increasingly important question in the water resource and quality management fields, especially for small watersheds where the phenomenon of data scarcity is prevalent. The transfer of hydrological parameters on the basis of regionalization is a common approach for solving PUB problems, and plenty of research has been undertaken on how to transfer calibrated parameters from gauged to ungauged watersheds. However, hydrological parameters estimation is substantially influenced by calibration objectives, which may affect model performance on the recipient watershed as well. In this paper the influence of calibration objectives on the transfer of parameter sets from one watershed to another is discussed. The HSPF hydrological model and the PEST automatic calibration model with four calibration objectives (squared error of daily flow, squared error of monthly flow, squared error of exceedance flow time, and sum of these squared errors) were applied. One gauged watershed of the Lake Dianchi Basin with daily flow data from 1999 to 2010 was calibrated by the combined HSPF-PEST model to obtain the transferrable parameters. Then the entire parameter sets were transferred to another neighborhood watershed, and model performance was tested by conventional goodness-of-fit statistics. Results show that (1) parameters transferred from all four calibration objectives perform well on the target watershed; (2) selection of calibration objective has a significant impact on model performance for both donor and recipient watersheds; and (3) the differences among objectives are similar in the two watersheds, suggesting that the objectives' features are transferrable. Therefore, the selection of calibration objective should be considered as a significant factor when transferring parameters to ungauged watersheds. (C) 2014 American Society of Civil Engineers.
Recently, environmental pressures along coasts have increased substantially. Classification of estuaries according to their susceptibility to eutrophication nutrient load is a useful method to determine priority management objects and to enforce control measures. Using historical monitoring data from 2007 to 2012, from 65 estuaries, including 101 estuarine monitoring sections and 260 coastal monitoring stations, a nutrient-driven phytoplankton dynamic model was developed based on the relationship among phytoplankton biomass, Total Nitrogen (TN) load and physical features of estuaries. The ecological filter effect of estuaries was quantified by introducing conversion efficiency parameter values into the model. Markov Chain Monte Carlo algorithm of Bayesian inference was then employed to estimate parameters in the model. The developed model fitted well to the observed chlorophyll, primary production, grazing, and sinking rates. The analysis suggests that an estuary with Q/V (the ratio of river flow to estuarine volume) greater than 2.0 per year and E > (conversion efficiency ratio) less than 1.0 g C/g N can be classified as less susceptible to TN load, Q/V between 0.7 to 2.0 per year and E > between 1.0 to 3.0 g C/g N as moderately susceptible, and E > greater than 3.0 g C/g N as very susceptible. The estuaries with Q/V less than 0.7 per year vary greatly in their susceptibility. The estuaries with high and moderate susceptibility accounted for 67% of all the analyzed estuaries. They have relatively high eutrophication risks and should be the focus of environmental supervision and pollution prevention.
A reliable system simulation to relate socioeconomic development with water environment and to comprehensively represent a watershed's dynamic features is important. In this study, after identifying lake watershed system processes, we developed a system dynamics modeling framework for managing lake water quality at the watershed scale. Two reinforcing loops (Development and Investment Promotion) and three balancing loops (Pollution, Resource Consumption, and Pollution Control) were constituted. Based on this work, we constructed Stock and Flow Diagrams that embedded a pollutant load model and a lake water quality model into a socioeconomic system dynamics model. The Dianchi Lake in Yunnan Province, China, which is the sixth largest and among the most severely polluted freshwater lakes in China, was employed as a case study to demonstrate the applicability of the model. Water quality parameters considered in the model included chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). The business-as-usual (BAU) scenario and three alternative management scenarios on spatial adjustment of industries and population (Si), wastewater treatment capacity construction (S2), and structural adjustment of agriculture (S3), were simulated to assess the effectiveness of certain policies in improving water quality. Results showed that S2 is most effective scenario, and the COD, TN, and TP concentrations in Caohai in 2030 are 52.5, 10.9, and 0.8 mg/L, while those in Waihai are 9.6, 1.2, and 0.08 mg/L, with sustained development in the watershed. Thus, the model can help support the decision making required in development and environmental protection strategies. (C) 2015 Elsevier Ltd. All rights reserved.
Water quality management and load reduction are subject to inherent uncertainties in watershed systems and competing decision objectives. Therefore, optimal decision-making modeling in watershed load reduction is suffering due to the following challenges: (a) it is difficult to obtain absolutely ``optimal'' solutions, and (b) decision schemes may be vulnerable to failure. The probability that solutions are feasible under uncertainties is defined as reliability. A reliability-oriented multi-objective (ROMO) decision-making approach was proposed in this study for optimal decision making with stochastic parameters and multiple decision reliability objectives. Lake Dianchi, one of the three most eutrophic lakes in China, was examined as a case study for optimal watershed nutrient load reduction to restore lake water quality. This study aimed to maximize reliability levels from considerations of cost and load reductions. The Pareto solutions of the ROMO optimization model were generated with the multiobjective evolutionary algorithm, demonstrating schemes representing different biases towards reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios were obtained, which indicated that decisions may be unreliable under unpractical load reduction requirements. A decision scheme identification process was conducted using the back propagation neural network (BPNN) method to provide a shortcut for identifying schemes at specific reliability levels for decision makers. The model results indicated that the ROMO approach can offer decision makers great insights into reliability tradeoffs and can thus help them to avoid ineffective decisions. (C) 2015 Elsevier B.V. All rights reserved.