How sediment dredging alters phosphorus dynamics in a lowland rural river?

China's lowland rural rivers are facing severe eutrophication problems due to excessive phosphorus (P) from anthropogenic activities. However, quantifying P dynamics in a lowland rural river is challenging due to its complex interaction with surrounding areas. A P dynamic model (River-P) was specifically designed for lowland rural rivers to address this challenge. This model was coupled with the Environmental Fluid Dynamics Code (EFDC) and the Phosphorus Dynamic Model for lowland Polder systems (PDP) to characterize P dynamics under the impact of dredging in a lowland rural river. Based on a two-year (2020-2021) dataset from a representative lowland rural river in the Lake Taihu Basin, China, the coupled model was calibrated and achieved a model performance (R2>0.59, RMSE<0.04 mg/L) for total P (TP) concentrations. Our research in the study river revealed that (1) the time scale for the effectiveness of sediment dredging for P control was ∼300 days, with an increase in P retention capacity by 74.8 kg/year and a decrease in TP concentrations of 23% after dredging. (2) Dredging significantly reduced P release from sediment by 98%, while increased P resuspension and settling capacities by 16% and 46%, respectively. (3) The sediment-water interface (SWI) plays a critical role in P transfer within the river, as resuspension accounts for 16% of TP imports, and settling accounts for 47% of TP exports. Given the large P retention capacity of lowland rural rivers, drainage ditches and ponds with macrophytes are promising approaches to enhance P retention capacity. Our study provides valuable insights for local environmental departments, allowing a comprehensive understanding of P dynamics in lowland rural rivers. This enable the evaluation of the efficacy of sediment dredging in P control and the implementation of corresponding P control measures.

Shifts of the pond area ratio for lowland polders: Implication for nutrient control.

Shifts for natural ecosystems were increasingly concerned due to its profound impacts on ecosystem services. Ponds within lowland artificial watersheds (polders) play a critical role in nitrogen (N) and phosphorus (P) cycling. From the perspective of N & P control in management practices, it is needed to determine an optimal pond area ratio for polders. For this purpose, our study proposed a process-based modelling framework to investigate the response of polder N & P loss to pond area, and thus to determine the threshold value of pond area ratio to achieve maximum N & P reduction for polders. The proposed framework included two process-based models (NDP and PDP) specially developed to describe N & P dynamics in lowland polders. To evaluate the proposed performance of the framework, it was applied to 171 polders in Zhong River Watershed in Lake Taihu Basin, eastern China. Our investigation results revealed that the correlation between polder N & P reduction rate and pond area ratio had an abrupt shift of 13.6 %, 14.7 % for N & P, respectively. Therefore, polders with a pond area ratio of 13.6-14.7 % had the largest N & P reduction (5.27 and 0.19 kg/ha). Polder size affected P reduction rate, with smaller polders (<200 ha) showing a higher P reduction rate, while it did not affect N reduction rate. Compared with annual precipitation, rainy-season precipitation more significantly (P<0.01) determined polder N & P reduction. This study demonstrated the use of our process-based framework in characterizing the shifts for the pond area ratio for polders, and thus provided technical support for N & P control of lowland areas in water management practices.

A comprehensive review on the recent advances for 5-aminolevulinic acid production by the engineered bacteria.

5-Aminolevulinic acid (5-ALA) is a non-proteinogenic amino acid essential for synthesizing tetrapyrrole compounds, including heme, chlorophyll, cytochrome, and vitamin B12. As a plant growth regulator, 5-ALA is extensively used in agriculture to enhance crop yield and quality. The complexity and low yield of chemical synthesis methods have led to significant interest in the microbial synthesis of 5-ALA. Advanced strategies, including the: enhancement of precursor and cofactor supply, compartmentalization of key enzymes, product transporters engineering, by-product formation reduction, and biosensor-based dynamic regulation, have been implemented in bacteria for 5-ALA production, significantly advancing its industrialization. This article offers a comprehensive review of recent developments in 5-ALA production using engineered bacteria and presents new insights to propel the field forward.

Improving Gibberellin GA3 Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi.

Liquid fermentation is the primary method for GA3 production usingFusarium fujikuroi. However, production capacity is limited due to unknown metabolic pathways. To address this, we constructed a genome-scale metabolic model (iCY1235) with 1753 reactions, 1979 metabolites, and 1235 genes to understand the GA3 regulation mechanisms. The model was validated by analyzing growth rates under different glucose uptake rates and identifying essential genes. We used the model to optimize fermentation conditions, including carbon sources and dissolved oxygen. Through the OptForce algorithm, we identified 20 reactions as targets. Overexpressing FFUJ_02053 and FFUJ_14337 resulted in a 37.5 and 75% increase in GA3 titers, respectively. These targets enhance carbon flux toward GA3 production. Our model holds promise for guiding the metabolic engineering of F. fujikuroi to achieve targeted overproduction. In summary, our study utilizes the iCY1235 model to understand GA3 regulation, optimize fermentation conditions, and identify specific targets for enhancing GA3 production through metabolic engineering.

A raster-based estimation of watershed phosphorus load and its impacts on surrounding rivers based on process-based modelling.

Quantifying phosphorus (P) load from watersheds at a fine scale is crucial for studying P sources in lake or river ecosystems; however, it is particularly challenging for mountain-lowland mixed watersheds. To address this challenge, we proposed a framework to estimate the P load at the grid scale and assessed its risk to surrounding rivers in a typical mountain-lowland mixed watershed (Huxi Region in Lake Taihu Basin, China). The framework coupled three models: the Phosphorus Dynamic model for lowland Polder systems (PDP), the Soil and Water Assessment Tool (SWAT), and the Export Coefficient Model (ECM). The coupled model performed satisfactory for both hydrological and water quality variables (Nash-Sutcliffe efficiency >0.5). Our modelling practice revealed that polder, non-polder, and mountainous areas had P load of 211.4, 437.2, and 149.9 t yr-1, respectively. P load intensity in lowlands and mountains was 1.75 and 0.60 kg ha-1 yr-1, respectively. A higher P load intensity (>3 kg ha-1 yr-1) was mainly observed in the non-polder area. In lowland areas, irrigated cropland, aquaculture ponds and impervious surfaces contributed 36.7%, 24.8%, and 25.8% of the P load, respectively. In mountainous areas, irrigated croplands, aquaculture ponds, and impervious surfaces contributed 28.6%, 27.0%, and 16.4% of the P load, respectively. Rivers with relatively high P load risks were mainly observed around big cities during rice season, owing to a large contribution of P load from the non-point source pollution of urban and agricultural activities. This study demonstrated a raster-based estimation of watershed P load and their impacts on surrounding rivers using coupled process-based models. It would be useful to identify the hotspots and hot moments of P load at the grid scale.

Novel ecological ditch system for nutrient removal from farmland drainage in plain area: Performance and mechanism.

The loading of nitrogen (N) and phosphorus (P) from agricultural drainage as the non-point sources is a worldwide environmental issue for aquatic ecosystem. However, how to remove these nutrients effectively from agricultural drainage remains a big challenge with increasing cemented ditches for better management. Here, we designed a novel ecological ditch system which integrated an earth ditch and a cemented ditch with iron-loaded biochar in the Chengdu Plain to reduce the loss of N and P from farmland. After a two-year monitoring, the removal efficiency of total N and total P reached 24.9% and 36.1% by the earth ditch and 30.7% and 57.8% by the integrated ditch system, respectively. The water quality was evidently improved after passing through the ditch system with the marked decrease in the concentrations of N and P. Dissolved organic N, nitrate, and particulate P became the dominant fractions of N and P loss. Rainfall soon after fertilization increased the concentrations of N and P in the ditch system and markedly affected their removal efficiency. The iron-loaded biochar effectively removed N and P from the drainage, especially at the high concentrations, which was mainly attributed to its high adsorption of the dissolved N and P fractions and the interception of the particulate nutrients. Our results indicate that the designed ecological ditch system has a high potential for alleviating agricultural non-point source pollution in the plain area and can be extended to other lowland agricultural ecosystems.

Environmental impacts and risks of bridges and tunnels across lakes: An overview.

Bridges and tunnels are built across lakes, especially in China, to improve road connectivity for transportation. However, their environmental impacts and risks have not received adequate attention. In this study, the magnitude of bridges and tunnels across 142 lakes in China were investigated. The investigation revealed that 37 bridges and 10 tunnels (a total length of 56.82 km) were built across 26 lakes during 2000-2020. From 2011 to 2020, the construction rate of bridges and tunnels across lakes in China was ∼6 times higher than the average value worldwide. Their environmental impacts and risks on lakes were summarised by analyzing previous publications screened from the Web of Science platform. The environmental impacts and risks during the bridge/tunnel construction period generally include decrease in water exchange, habitat destruction, biological reduction, increase in suspended solids, and water quality pollution. Tunnel construction may also affect the ecological conditions of groundwater due to its disturbances in the underground area. During the bridge/tunnel operation period, environmental impacts and risks were mainly induced by rainfall events and water pollution accidents. The impacts and risks were highly related to the construction location, bridge/tunnel properties, moving vehicles, fixing activities, and atmospheric deposition. Owing to the existing weaknesses in management practices, a framework, aiming to reduce the environmental impacts and risks caused by bridges and tunnels across lakes, was proposed. The framework identified the critical issues and their corresponding management strategies during the bridge/tunnel construction and operation periods and enabled the generation of the best management strategy for each specific period.

Dam construction attenuates trace metal contamination in water through increased sedimentation in the Three Gorges Reservoir.

Dam construction has a far-reaching impact on trace metal accumulation and the metal-induced quality of the aquatic environment. However, the long-term impacts of dam construction and impoundments on the spatial distribution of trace metals and water quality remain poorly understood. Here, we found that the concentrations of trace metals in the mainstream water of the world's largest reservoir, Three Gorges Reservoir (TGR), decreased after impoundment, while their concentrations and contamination in the sediments of the water-level fluctuation zone increased significantly, especially for anthropogenic sources of metals such as cadmium, lead, and zinc. The spatial and temporal variations of anthropogenic metals in the sediments revealed increased anthropogenic dominance in their distribution under current hydrological management, especially for the urban area of the upper TGR. Sediment fluxes, particle composition, and extreme climate modulated the distribution of trace metals in the sediments. The results demonstrate that human activities have increasingly determined the distribution and contamination state of trace metals in the mainstream TGR. However, in contrast to our previously thought, the anthropogenic discharge of trace metals did not adversely affect water quality. Our results indicate that dam construction in riverine systems attenuates trace metal contamination in water through sediment sorting and deposition.

Characterizing the impacts of macrophyte-dominated ponds on nitrogen sources and sinks by coupling multiscale models.

Macrophyte-dominated ponds, widely distributed in lowland areas, play an important role in nitrogen (N) retention for nonpoint source pollution. However, their impacts on N sources and sinks are scarcely quantified at a watershed scale. This study aimed to investigate N dynamics (sources, sinks, transport, etc.) of macrophyte-dominated ponds and their driving factors in a typical lowland artificial watershed (the Zhong River Watershed) in East China. For this purpose, an hourly-scale pond model (nitrogen dynamic model for macrophyte-dominated ponds, NDP-Pond) was developed, and coupled with a daily scale watershed model (Nitrogen Dynamic Polder model, NDP) to simulate N dynamics, and estimate N retention in macrophyte-dominated ponds. A comparison with the measured water level and total nitrogen (TN) revealed an acceptable model performance (coefficient of determination (R2) > 0.53) for these two models. Based on the N source/sink simulations, we found that 1) macrophyte-dominated ponds showed a large TN removal capacity with a rate of 55%, and a TN loading removal rate of 67 kg·ha-1·yr-1. 2) Denitrification was the main pathway for N removal with a contribution of 57.7%, followed by the uptake of macrophytes (35.8%) and sedimentation (6.5%). 3) The optimal coverage of macrophytes (Alternanthera philoxeroides) to enhance N removal is 2-4 kg·m-2. 4) During the macrophyte-growth period, the TN removal capacity of the pond was higher with a retention time of 1-10 days. Increasing the pond retention time would decrease the N removal efficiency. This study revealed the high value of coupling multiscale models to gain in-depth insights into N retention in macrophyte-dominated pond ecosystems.

A novel framework to predict water turbidity using Bayesian modeling.

High water turbidity in aquatic ecosystems is a global challenge due to its harmful impacts. A cost-effective manner to rapidly and accurately measure water turbidity is thus of particular useful in water management with limited resources. This study developed a novel framework aiming to predict water turbidity in various aquatic ecosystems. The framework predicted water turbidity and quantified the uncertainty of the prediction through Bayesian modeling. To improve model performance, a model-update method was implemented in the framework to update the model structure and parameters once more measured data were available. 120 paired records (an image from smartphone and a measured water turbidity value by standard turbidimeters for each record) were collected from rivers, lakes and ponds across China to evaluate the performance of the developed framework. Our cross-validation results revealed a well prediction of water turbidity with Nash-Sutcliffe efficiency (NS) >0.87 (p<0.001) during the training period and NS>0.73 (p<0.001) during the validation period. The model-update method (in case of more measured data) for the developed Bayesian models in the framework resulted in a decreasing trend of model uncertainty and a stable mode fit. This study demonstrated a high value of the Bayesian-based framework in predicting water turbidity in a robust and easy manner.

Characterizing the river water quality in China: Recent progress and on-going challenges.

Food production systems, urbanization, and other anthropogenic activities dramatically alter natural hydrological and nutrient cycles, and are primarily responsible for water quality impairments in China's rivers. This study compiled a 16-year (2003-2018) dataset of river water quality (161,337 records from 2424 sites), watershed/landscape features, and meteorological conditions to investigate the spatial water quality patterns and underlying drivers of river impairment (defined as water quality worse than Class V according to China's Environmental Quality Standards for Surface Waters, GB3838-2002) at a national scale. Our analysis provided evidence of a distinct water quality improvement with a gradual decrease in the frequency of prevalence of anoxic conditions, an alleviation of the severity of heavy metal pollution, whereas the cultural eutrophication has only been moderately mitigated between 2003 and 2018. We also identified significant spatial variation with relatively poorer water quality in eastern China, where 17.2% of the sampling sites registered poor water quality conditions, compared with only 4.6% in western China. Total phosphorus (TP) and ammonia-nitrogen (NH3-N) are collectively responsible for >85% of the identified incidences of impaired conditions. Bayesian modelling was used to delineate the most significant covariates of TP/NH3-N riverine levels in six large river basins (Liao, Hai, Yellow, Yangtze, Huai, and Pearl). Water quality impairments are predominantly shaped by anthropogenic drivers (82.5% for TP, 79.5% for NH3-N), whereas natural factors appear to play a secondary role (20.5% for TP, 17.5% for NH3-N). Two indicator variables of urbanization (urban areal extent and nighttime light intensity) and farmland areal extent were the strongest predictors of riverine TP/NH3-N levels and collectively accounted for most of the ambient nutrient variability. We concluded that there is still a long way to go in order to eradicate eutrophication and realize acceptable ecological conditions. The design of the remedial measures must be tailored to the site-specific landscape characteristics, meteorological conditions, and should also consider the increasing importance of non-point source pollution and internal nutrient loading.

The magnitude and drivers of harmful algal blooms in China's lakes and reservoirs: A national-scale characterization.

Harmful algal blooms (HABs) can have dire repercussions on aquatic wildlife and human health, and may negatively affect recreational uses, aesthetics, taste, and odor in drinking water. The factors that influence the occurrence and magnitude of harmful algal blooms and toxin production remain poorly understood and can vary in space and time. It is within this context that we use machine learning (ML) and two 14-year (2005-2018) data sets on water quality and meteorological conditions of China's lakes and reservoirs to shed light on the magnitude and associated drivers of HAB events. General regression neural network (GRNN) models are developed to predict chlorophyll a concentrations for each lake and reservoir during two study periods (2005-2010 and 2011-2018). The developed models with an acceptable model fit are then analyzed by two indices to determine the areal HAB magnitudes and associated drivers. Our national assessment suggests that HAB magnitudes for China's lakes and reservoirs displayed a decreasing trend from 2006 (1363.3 km2) to 2013 (665.2 km2), and a slightly increasing trend from 2013 to 2018 (775.4 km2). Among the 142 studied lakes and reservoirs, most severe HABs were found in Lakes Taihu, Dianchi and Chaohu with their contribution to the total HAB magnitude varying from 89.2% (2013) to 62.6% (2018). HABs in Lakes Taihu and Chaohu were strongly associated with both total phosphorus and nitrogen concentrations, while our results were inconclusive with respect to the predominant environmental factors shaping the eutrophication phenomena in Lake Dianchi. The present study provides evidence that effective HAB mitigation may require both nitrogen and phosphorus reductions and longer recovery times; especially in view of the current climate-change projections. ML represents a robust strategy to elucidate water quality patterns in lakes, where the available information is sufficient to train the constructed algorithms. Our mapping of HAB magnitudes and associated environmental/meteorological drivers can help managers to delineate hot-spots at a national scale, and comprehensively design the best management practices for mitigating the eutrophication severity in China's lakes and reservoirs.

How successful are the restoration efforts of China's lakes and reservoirs?

China has made considerable efforts to mitigate the pollution of lakes over the past decade, but the success rate of these restoration actions at a national scale remains unclear. The present study compiled a 13-year (2005-2017) comprehensive dataset consisting of 24,319 records from China's 142 lakes and reservoirs. We developed a novel Water Quality Index (WQI-DET), customized to China's water quality classification scheme, to investigate the spatio-temporal pollution patterns. The likelihood of regime shifts during our study period is examined with a sequential algorithm. Our analysis suggests that China's lake water quality has improved and is also characterized by two WQI-DET abrupt shifts in 2007 and 2010. However, we also found that the eutrophication problems have not been eradicated and heavy metal (HM) pollution displayed an increasing trend. Our study suggests that the control of Cr, Cd and As should receive particular attention in an effort to alleviate the severity of HM pollution. Priority strategies to control HM pollution include the reduction of the contribution from mining activities and implementation of soil remediation in highly polluted areas. The mitigation efforts of lake eutrophication are more complicated due to the increasing importance of internal nutrient loading that can profoundly modulate the magnitude and timing of system response to external nutrient loading reduction strategies. We also contend that the development of a rigorous framework to quantify the socioeconomic benefits from well-functioning lake and reservoir ecosystems is critically important to gain leeway and keep the investments to the environment going, especially if the water quality improvements in many Chinese lakes and reservoirs are not realized in a timely manner.

Assessing response of sediment load variation to climate change and human activities with six different approaches.

Understanding the relative contributions of climate change and human activities to variations in sediment load is of great importance for regional soil, and river basin management. Considerable studies have investigated spatial-temporal variation of sediment load within the Loess Plateau; however, contradictory findings exist among methods used. This study systematically reviewed six quantitative methods: simple linear regression, double mass curve, sediment identity factor analysis, dam-sedimentation based method, the Sediment Delivery Distributed (SEDD) model, and the Soil Water Assessment Tool (SWAT) model. The calculation procedures and merits for each method were systematically explained. A case study in the Huangfuchuan watershed on the northern Loess Plateau has been undertaken. The results showed that sediment load had been reduced by 70.5% during the changing period from 1990 to 2012 compared to that of the baseline period from 1955 to 1989. Human activities accounted for an average of 93.6 ±â€¯4.1% of the total decline in sediment load, whereas climate change contributed 6.4 ±â€¯4.1%. Five methods produced similar estimates, but the linear regression yielded relatively different results. The results of this study provide a good reference for assessing the effects of climate change and human activities on sediment load variation by using different methods.

Towards the development of a modeling framework to track nitrogen export from lowland artificial watersheds (polders).

Excess nitrogen (N) export from lowland artificial watersheds (polders) is often assumed to be a major contributor to the cultural eutrophication of downstream aquatic ecosystems. However, the complex transport processes characterizing lowland areas pose significant challenges in accurately quantifying their actual role. In this study, we developed a dynamic model to track N sources and transport pathways in lowland polders. The model is able to accommodate all the unique characteristics of polder dynamics, including artificial drainage, and interactions among surface water, groundwater and soil water. Our model was calibrated and validated against water level data and nitrogen concentrations measured in a lowland polder (Polder Jian) in China during the 2014-2016 period. Model performance was satisfactory with an R2 value of 0.55 and an NS value of 0.53 for total N concentrations. The characterization of the various components of water budget and N cycle derived by the model was on par with local empirical estimates. N export from Polder Jian was approximately 57 kg ha-1 yr-1 and was distinctly higher than values reported from nearby non-polder areas. The largest fraction of N export stemmed from seepage. To our knowledge, this is the first dynamic model to quantify N export from a watershed with artificial drainage network and can be used to design remedial measures of ecosystem degradation.

Sources, distribution and export coefficient of phosphorus in lowland polders of Lake Taihu Basin, China.

Identifying phosphorus (P) sources, distribution and export from lowland polders is important for P pollution management, however, is challenging due to the high complexity of hydrological and P transport processes in lowland areas. In this study, the spatial pattern and temporal dynamics of P export coefficient (PEC) from all the 2539 polders in Lake Taihu Basin, China were estimated using a coupled P model for describing P dynamics in a polder system. The estimated amount of P export from polders in Lake Taihu Basin during 2013 was 1916.2 t/yr, with a spatially-averaged PEC of 1.8 kg/ha/yr. PEC had peak values (more than 4.0 kg/ha/yr) in the polders near/within the large cities, and was high during the rice-cropping season. Sensitivity analysis based on the coupled P model revealed that the sensitive factors controlling the PEC varied spatially and changed through time. Precipitation and air temperature were the most sensitive factors controlling PEC. Culvert controlling and fertilization were sensitive factors controlling PEC during some periods. This study demonstrated an estimation of PEC from 2539 polders in Lake Taihu Basin, and an identification of sensitive environmental factors affecting PEC. The investigation of polder P export in a watershed scale is helpful for water managers to learn the distribution of P sources, to identify key P sources, and thus to achieve best management practice in controlling P export from lowland areas.

Hydrology and phosphorus transport simulation in a lowland polder by a coupled modeling system.

Modeling the rain-runoff processes and phosphorus transport processes in lowland polders is critical in finding reasonable measures to alleviate the eutrophication problem of downstream rivers and lakes. This study develops a lowland Polder Hydrology and Phosphorus modeling System (PHPS) by coupling the WALRUS-paddy model and an improved phosphorus module of a Phosphorus Dynamic model for lowland Polder systems (PDP). It considers some important hydrological characteristics, such as groundwater-unsaturated zone coupling, groundwater-surface water feedback, human-controlled irrigation and discharge, and detailed physical and biochemical cycles of phosphorus in surface water. The application of the model in the Jianwei polder shows that the simulated phosphorus matches well with the measured values. The high precision of this model combined with its low input data requirement and efficient computation make it practical and easy to the water resources management of Chinese polders. Parameter sensitivity analysis demonstrates that Kuptake, cQ2, cW1, and cQ1 exert a significant effect on the modeled results, whereas KresuspensionMax, Ksettling, and Kmineralization have little effect on the modeled total phosphorus. Among the three types of uncertainties (i.e., parameter, initial condition, and forcing uncertainties), forcing uncertainty produces the strongest effect on the simulated phosphorus. Based on the analysis result of annual phosphorus balance when considering the high import from irrigation and fertilization, lowland polder is capable of retaining phosphorus and reducing phosphorus export to surrounding aquatic ecosystems because of their special hydrological regulation regime.

How can we reduce phosphorus export from lowland polders? Implications from a sensitivity analysis of a coupled model.

Phosphorus (P) export from lowland polders has caused severe water pollution. Numerical models are an important resource that help water managers control P export. This study coupled three models, i.e., Phosphorus Dynamic model for Polders (PDP), Integrated Catchments model of Phosphorus dynamics (INCA-P) and Universal Soil Loss Equation (USLE), to describe the P dynamics in polders. Based on the coupled models and a dataset collected from Polder Jian in China, sensitivity analysis were carried out to analyze the cause-effect relationships between environmental factors and P export from Polder Jian. The sensitivity analysis results showed that P export from Polder Jian were strongly affected by air temperature, precipitation and fertilization. Proper fertilization management should be a strategic priority for reducing P export from Polder Jian. This study demonstrated the success of model coupling, and its application in investigating potential strategies to support pollution control in polder systems.

Cloning, characterization, and expression analysis of acyl-acyl carrier protein (ACP)-thioesterase B from seeds of Chinese Spicehush (Lindera communis).

Acyl-acyl carrier protein (ACP) thioesterases (TE EC 3.1.2.14) are fatty acid biosynthesis key enzymes that determine fatty acid carbon chain length in most plant tissues. A full-length cDNA corresponding to one of the fatty acyl-ACP thioesterase (Fat) genes, designated LcFatB, was isolated from developing Lindera communis seeds using PCR and RACE with degenerate primers based on conserved sequences of multiple TE gene sequences obtained from GenBank. The 1788 bp cDNA had an open reading frame (ORF) of 1260 bp encoding a protein of 419 amino acids. The deduced amino acid sequence showed 61-73% identity to proteins in the FatB class of plant thioesterases. Real-time quantitative PCR analysis revealed that LcFatB was expressed in all tissues of L. communis, with the highest expression in the developing seeds 75days after flowering. Recombinant pET-MLcFatB was constructed using the pET-30 a vector and transformed into Escherichia coli BL21(DE3)△FadE, a strain that deleted the acyl-CoA dehydrogenase (FadE). SDS-PAGE analysis of proteins isolated from pET-MLcFatB E. coli cells after induction with IPTG revealed a protein band at ~40.5kDa, corresponding to the predicted size of LcFatB mature protein. The decanoic acid and lauric acid contents of the pET-MLcFatB transformant were increased significantly. These findings suggest that an LcFatB gene from a non-traditional oil-seed tree could be used to function as a saturated acyl-ACP thioesterase and could potentially be used to modify the fatty acid composition of seed oil from L. communis or other species through transgenic approaches.