Minjiang River Research Articles

Evaluation of evapotranspiration for exorheic basins in China using an improved estimate of terrestrial water storage change

Evapotranspiration (ET) is a critical component of the global water cycle, but basin-scale ET is often difficult to accurately estimate. Due to the limitations of the temporal resolution of the Gravity Recovery and Climate Experiment (GRACE) satellites and coverage period, daily or monthly terrestrial water storage (TWS) changes at basin scale are hard to obtain, which limits the application of water balance in ET estimation. To surmount this limitation, we established a daily TWS anomaly reconstruction framework. Based on this framework, the reconstructed daily TWS anomalies (TWSAs) were used for the first time to estimate the basin-scale ET in nine exorheic basins of China. Furthermore, we combined four commonly used ET models and TWS change (TWSC) derived by two different TWSA interpolation methods to evaluate the uncertainty of the different methodologies using the three-cornered hat (TCH) approach. The results show that: (i) the number of negative values of ET from the two TWSA interpolation methods is close to each other. For the reconstruction method, the number of negative values is reduced by about 70% relative to interpolation methods, which significantly improves the quality of the ET estimates; and (ii) among the seven sequences involved in the TCH calculation, the two TWSA interpolation methods show the largest uncertainty, while the reconstruction method has similar or optimal performance to the four ET models in all the basins except the Huaihe River Basin and the Minjiang River Basin. The results of this study demonstrate the superiority of derived TWSC based on the reconstruction framework in basin-scale ET estimation, which has a great potential for the application in the quantitative evaluation of ET and further assessment of ET models.

Effects of Training Data on the Learning Performance of LSTM Network for Runoff Simulation

With the rapid development of Artificial Intelligence (AI) technology, the Long Short-Term Memory (LSTM) network has been widely used for forecasting hydrological process. To evaluate the effect of training data amount on the performance of LSTM, the study proposed an experiment scheme. First, K-Nearest Neighbour (KNN) algorithm is employed for generating the meteorological data series of 130 years based on the observed data, and the Soil and Water Assessment Tool (SWAT) model is used to obtain the corresponding runoff series with the generated meteorological data series. Then, the 130 years of rainfall and runoff data is divided into two parts: the first 80 years of data for model training and the remaining 50 years of data for model verification. Finally, the LSTM models are developed and evaluated, with the first 5-year, 10-year, 20-year, 40-year and 80-year data series as training data respectively. The results obtained in Yalong River, Minjiang River and Jialing River show that increasing the training data amount can effectively reduce the over-fittings of LSTM network and improve the prediction accuracy and stability of LSTM network.

Study on sediment erosion of high head Francis turbine runner in Minjiang River basin

The Wenchuan earthquake greatly reduced the forest water conservation capacity along the banks of Minjiang River. With the intensified soil erosion and the rapid increasing sediment transport, the sediment erosion of hydraulic turbines running on the river has become more and more serious, especially of high head Francis turbines. In this study, the k-ε multiphase flow turbulence model was used to calculate the sediment-water flow of a high head Francis turbine with long and short blades in Minjiang River. The distribution pattern of sediment concentration (sediment volume fraction) on the blade surface shows that the sediment particles mainly gather on the outlet edge at 10% of the blade height on the suction surface of the long blade, while the sediment concentration on the surface of the short blade is small. The erosion of the 0Cr13Ni5Mo runner blade was tested by the flow around erosion method, and the erosion amount on the blade surface in the severe erosion area was obtained. Based on the test data of erosion and the numerical calculation results of sediment flow, a formula to calculate the sediment erosion rate of flow passage components with 0Cr13Ni5Mo material was given for turbines operating in Minjiang River. By using this formula, the sediment erosion of flow passage components in hydraulic turbines with 0Cr13Ni5Mo or similar materials operating in Minjiang River can be predicted.

Atmospheric simulation‐based precipitation datasets outperform satellite‐based products in closing basin‐wide water budget in the eastern Tibetan Plateau

AbstractSatellite‐based precipitation products (SBPs) have been widely used in hydrological applications in recent decades but may contain large uncertainties in mountainous regions. Atmospheric simulation‐based datasets (ABDs) have been greatly improved in recent years, but their applications in mountainous hydrology are rare and need further validation. This study compares the performance of three SBPs and two ABDs in the mountainous Minjiang River basin, focusing on their potential for closing the basin‐wide water budget. The three SBPs include the China Merged Precipitation Analysis (CMPA), the Integrated Multi‐satellitE Retrievals for Global Precipitation Measurement (IMERG) and the Global Satellite Mapping of Precipitation (GSMaP); the two ABDs are the fifth generation Reanalysis product of the European Centre for Medium Range Weather Forecasts (ERA5) and the High Asia Refined Analysis Version 2 (HAR V2). The five products are validated with rain gauge data and results show that all the five products except IMERG can generally reproduce the spatial pattern and elevation dependence of observed precipitation. Particularly, precipitation amount in the two ABDs is close to gauge observations in the low elevations, but much more than the gauge observations in areas with a sharp rise in elevations. Assessment of water budget shows that all SBPs yield severe negative water imbalance (greater than 50.0% of corresponding runoff) at most sub‐basins, while the ABDs can better close the water budget with water imbalance values between ±30.0% in most sub‐basins, respectively. Further analyses show that large relative differences between SBPs and ABDs mainly occur in areas with large topographical relief and in winter, which is likely because the ABDs outperform the SBPs in capturing orographic precipitation in complex terrain and solid precipitation in winter.

Succession of the Gut Microbiome in the Tibetan Population of Minjiang River Basin.

Tibetans are one of the oldest ethnic groups in China and South Asia. Based on the analysis of 1,059 Tibetans in the Minjiang River basin at an altitude of 500–4,001 m, we found that the dominant phyla of the Tibetan population were Bacteroidota and Firmicutes, and the main genera were Prevotella and Bacteroides, which were mostly in consistent with other nationalities. We further evaluated in total 115 parameters of seven categories, and results showed that altitude was the most important factor affecting the variation in the microbial community. In the process of emigration from high altitudes to the plain, the gut microbial composition of late emigrants was similar to that of plateau aborigines. In addition, regarding immigration from low altitude to high altitude, the microbial community became more similar to that of high altitude population with the increase of immigration time. Changes in these microbes are related to the metabolism, disease incidence and cell functions of the Tibetan population. The results of other two cohorts (AGP and Z208) also showed the impact of altitude on the microbial community. Our study demonstrated that altitude of habitation is an important factor affecting the enterotype of the microflora in the Tibetan population and the study also provided a basis to explore the interaction of impact parameters with gut microbiome for host health and diseases.

Phosphorus forms in marsh soils with different years of Spartina alterniflora invasion in the Minjiang River estuary, China

We examined the effects of Spartina alterniflora invasion on phosphorus forms of marsh soils, based on the method of space-for-time substitution by selecting S. alterniflora marshes with different invasion years (SA1, 5-6 years; SA2, 8-10 years; and SA3, 12-14 years) in Shanyutan of the Minjiang River estuary. The results showed that in marsh soils of different invasion years, the proportion of hardly decomposable phosphorus (HCl-Pi and Residual-P) was the highest (46.4%-46.7%), followed by moderately decomposable phosphorus (NaOH-Pi, NaOH-Po and Sonic-Pi) (40.0%-44.0%), and the easily decomposable phosphorus (Resin-Pi, NaHCO3-Pi and NaHCO3-Po) was the lowest (9.5%-13.3%). With increasing invasion years of S. alterniflora, soil phosphorus forms and their spatial distributions were greatly altered. The contents of moderately decomposable phosphorus, hardly decomposable phosphorus, and total phosphorus (TP) generally increased, while easily decomposable phosphorus content generally decreased. Compared with SA1, the contents of moderately decomposable phosphorus, hardly decomposable phosphorus and TP in SA2 increased by 11.5%, 9.7% and 10.5%, while those in SA3 increased by 24.8%, 13.2% and 13.5%, respectively. The distribution of phosphorus forms was greatly altered with increasing invasion years, which was dependent on the variations of key factors such as EC, pH value and grain composition. The implementation of regular mowing activities for S. alterniflora in the Minjiang River estuary in recent years, to some extent, reduced the return of phosphorus from residues to soils and decreased the availability of the easily decomposable phosphorus in soils.

Evapotranspiration Variations of the Minjiang River Basin in Southeastern China from 2000 to 2019

Evapotranspiration is one of the critical processes in the terrestrial hydrological cycle, and the assessment of evapotranspiration is essential for understanding the regional hydrological cycle. In this study, the Minjiang River Basin, a typical watershed in the humid subtropical climate zone, is selected as the study region. The Penman-Monteith equation and the dual crop coefficient method are used to calculate the actual evapotranspiration (ETa) at seven meteorological stations within the study basin. Meanwhile, the applicability of the Global Land Data Assimilation System-Noah (GLDAS-Noah) ETa data in the Minjiang River Basin is evaluated based on stations P-M equation results, then to analyze the changes of the ETa in the Minjiang River Basin from 2000 to 2019. The results show that the GLDAS-Noah ETa data are well applicable in the Minjiang River Basin (R2 > 0.9 and NSE > 0.8). The ETa in the basin shows an increasing trend since 2000, and the increasing rate is 3.60 mm·yr−1 (p < 0.01). The seasonal variation results show that ETa tends to increase in winter and spring, with increasing rates of 1.10 mm·yr−1 (p < 0.01) and 2.60 mm·yr−1 (p < 0.01), respectively, while the ETa did not change significantly in summer and autumn. Annual air temperature has the largest effect on annual ETa (59.6%), followed by precipitation at 33.9%. ETa increased in spring was mainly influenced by increasing temperatures (89.4%) in the Minjiang River Basin from 2000 to 2019. The research results are of great benefit to further improve the understanding of ETa variations in the basin under global warming.

Spatial relationships between NDVI and topographic factors at multiple scales in a watershed of the Minjiang River, China

Improvement in vegetation cover in the upper reaches of the Minjiang River protects major freshwater sources and constructs ecological barriers in the upstream of Yangtze River located in southwest China. However, the spatially varying relationships between normalized difference vegetation index (NDVI) and topographic factors at multiple scales remain unclear. In this study, the two-dimensional discrete wavelet transform (2D-DWT) and geographically weighted regression (GWR) were combined to build a framework for examining the complex spatial relationships between NDVI and topographic factors at multiple scales. Based on the gridded datasets of NDVI and digital elevation model (DEM) of a small watershed located in the upper reaches of the Minjiang River situated in southwest China, the influence of topographic factors on NDVI variation in each grid and which topographic variables correlated most with the NDVI at each location were analyzed in this study. The grid data were decomposed into smooth and detail components using 2D-DWT. The results revealed that elevation, slope, and aspect exhibited different scale effects on NDVI in different wavelet components. In the smooth components, the spatial correlation of NDVI with elevation, slope, and south-facing index (SFI) of aspect increased with the decomposition scale, whereas topographic factors had different degrees of influence on NDVI. Elevation was found to be the most important topographic factor that determined the spatial distribution of NDVI on both sides of the valley, and SFI exhibited the highest effect on NDVI when elevation was higher than 2500 m. In the detail components, the spatial distribution of the most important topographic factor affecting the NDVI was not evident at a smaller scale, whereas it became obvious at 480 m scale. SFI was found to be more important than elevation and slope at a larger scale. These results will help in understanding the complex relationship between NDVI and topographic factors and determining the appropriate topographic location for ecological restoration.

Landslide-Induced Weathering in Tectonically Active Mountains: Evidence From Dissolved Radiogenic Uranium Isotopes

Understanding weathering processes in landslide-dominated catchments is critical for evaluating the role of landslides in chemical weathering and the global carbon cycle. Previous studies have focused on solute concentrations in landslide-impacted landscapes, but have paid less attention to developing isotopic tracers of landslide-induced weathering fluxes. Recent work found that the dissolved radiogenic uranium isotopes in river water are closely related to the denudation rates in catchments draining steep mountains where landslides are thought to be a major erosion mechanism, suggesting the potential of uranium isotopes to trace landslide-induced weathering fluxes. Here we compile the dissolved radiogenic uranium isotopes (234U/238U ratios) in the river water samples from a group of catchments with variable landslide activities in the Minjiang River Basin at the eastern margin of the Tibetan Plateau. We derive three metrics of landslide activity from the analyses of digital topography and an inventory map of the co-seismic landslides triggered by the 2008 Mw7.9 Wenchuan earthquake: the normalized volume of landslides, the mean catchment slope angle, and the fraction of slopes steeper than a threshold angle beyond which slopes are mechanically unstable. The riverine dissolved 234U/238U ratios correlate negatively with the metrics of landslide activity in each catchment, which likely reflect the influence of landslides on the dissolved 234U/238U ratios. Mechanistically, enhanced bedrock landsliding would accelerate the exposure of fresh rock, promoting bedrock weathering and congruent dissolution of 234U and 238U contained in minerals; reduced landslide activities and enhanced regolith weathering would lead to preferential accumulation of 234U against 238U in solutes through alpha-recoil ejection, thus increasing dissolved 234U/238U. Our findings provide field evidence of using the riverine dissolved 234U/238U ratio to trace weathering fluxes driven by landslides, shedding new light on chemical weathering processes in uplifting mountains.

Data‐Driven Method With Numerical Model: A Combining Framework for Predicting Subtropical River Plumes

AbstractNumerical models are of fundamental usage for estuarine and coastal sciences. Although numerical simulations are widely applied, analyzing and improving them are often challenging tasks given their large volume and huge parameter space. In this study, a novel data‐driven framework is introduced to study the Minjiang River Plume (MJRP). The framework combines Self‐Organizing Map (SOM) clustering with a Hidden Markov Model (HMM). A three‐dimensional Regional Ocean Model System for MJRP is first configurated with realistic atmospheric, oceanic, and riverine forcings. By applying SOM clustering to the modeled sea surface salinity (SSS) with ∼2,000 2‐day averaged records from 2010 to 2020, we identify six major patterns of MJRP. Each pattern exhibits distinct circulation and plume structures. These MJRP patterns contain not only seasonal signals, but also rich short‐term variabilities driven by the riverine inputs and oceanic dynamics. Then, the SOM‐HMM method was applied to predict the future of the hidden state (i.e., patterns of MJRP) from the observable states (wind and river runoff). With a hypothetic SSS product from a geostationary satellite as the ground truth, we show that the SOM‐HMM method can predict MJRP patterns considerably high prediction accuracy and computational efficiency. Further, these patterns were translated back to SSS with high forecast skills. Combining a conventional numerical model with a data‐driven method, this approach can be promisingly applied in the short‐term marine forecast to support the utilization and management of other estuaries.

First fluorescence sensor for hydrazine ion: An effective “turn-on” detection based on thiophene-cyanodistyrene Schiff-base

Hydrazine and its cation were important but hazardous reagents. Although the fluorescence sensor for hydrazine had been widely reported, the fluorescence sensor for hydrazine ion was not presented so far. In this work, the first fluorescence sensor for hydrazine ion was prepared based on the effective “turn-on” fluorescence of thiophene-cyanodistyrene Schiff-base (TCS). TCS was synthesized in simple condensation with high yield. It exhibited weak fluorescence at 450–550 nm in aqueous media due to the strong PET effect suppressing AIE effect. It displayed excellent selective sensing ability for Hg2+ and N2H62+ with strong “turn-on” fluorescence based on the disruption of PET effect. The fluorescence response to Hg2+ was masked by Cl−, achieving the high selective detection for N2H62+ only. The detection limit for N2H62+ was 1.05 × 10−7 M. The 2:1 stoichiometric ratio and the sensing mechanism were confirmed by the Job’s plot, MS spectrum, 1H NMR spectrum, FT-IR spectrum and theory calculation. The detecting experiments for N2H62+ in tap water and water of Minjiang River implied the good application potential for sensing N2H62+ in real water environments.

Reconstruction of catastrophic outburst floods of the Diexi ancient landslide-dammed lake in the Upper Minjiang River, Eastern Tibetan Plateau

Landslide-dammed lake outburst floods (LLOFs) may pose serious safety threats to nearby residents and their livelihoods, as well as cause major damages to the downstream areas in mountainous regions. This study presents the Diexi ancient landslide-dammed lake (DALL), located along the Upper Minjiang River, in the eastern margins of the Tibetan Plateau. The DALL is known to have an estimated previous maximal lake area of 1.1 × 107 m2 and an impounded volume of 2.9 × 109 m3. At approximately 27 ka BP, the ancient landslide dam failed, and catastrophic LLOFs occurred. It was determined that the peak discharge of the Diexi ancient LLOFs could be reconstructed using regression, parametric, and boulder competence approaches. The reconstructed average maximum peak discharge was approximately 79,500 m3/s, with an estimated uncertainty bound of 70,000 to 90,000 m3/s. This indicated that the Diexi ancient LLOFs were the largest outburst floods to have occurred in the Upper Minjiang River Valley since the Late Pleistocene Period. The differences in the widths and slopes within the former and latter reaches of the dam indicated that the geomorphic influences on the river channel resulting from the DALL and its LLOFs have been present for tens of thousands of years. These findings were of major significance in deepening the understanding of the existence and disappearances of important river knickpoints on a time scale of tens of thousands of years.

Landslide Susceptibility Mapping with Deep Learning Algorithms

Among natural hazards, landslides are devastating in China. However, little is known regarding potential landslide-prone areas in Maoxian County. The goal of this study was to apply four deep learning algorithms, the convolutional neural network (CNN), deep neural network (DNN), long short-term memory (LSTM) networks, and recurrent neural network (RNN) in evaluating the possibility of landslides throughout Maoxian County, Sichuan, China. A total of 1290 landslide records was developed using historical records, field observations, and remote sensing techniques. The landslide susceptibility maps showed that most susceptible areas were along the Minjiang River and in some parts of the southeastern portion of the study area. Slope, rainfall, and distance to faults were the most influential factors affecting landslide occurrence. Results revealed that proportion of landslide susceptible areas in Maoxian County was as follows: identified landslides (13.65–23.71%) and non-landslides (76.29–86.35%). The resultant maps were tested against known landslide locations using the area under the curve (AUC). This study indicated that the DNN algorithm performed better than LSTM, CNN, and RNN in identifying landslides in Maoxian County, with AUC values (for prediction accuracy) of 87.30%, 86.50%, 85.60%, and 82.90%, respectively. The results of this study are useful for future landslide risk reduction along with devising sustainable land use planning in the study area.

Quantifying spatiotemporal dynamics of vegetation and its differentiation mechanism based on geographical detector.

The influence of factors on vegetation changes in different regions is still largely unknown. We applied the geographic detector, a new spatial statistical method, to study the interactive effects of factors on the spatial patterns of normalised vegetation index (NDVI) changes and determine the optimal characteristics of key impact factors beneficial to vegetation growth. Our results show that from 2000 to 2015, the vegetation cover for the upper reaches of the Minjiang River, western China was in good condition. Furthermore, more than 80% of the areas had NDVI values ranging from 0.6 to 0.8 and NDVI > 0.8, and the spatial-temporal changes of vegetation cover were significant. The vegetation cover changes showed a significant transformation in the regions with NDVI > 0.6. Our study uniquely illustrated that elevation, annual average temperature and soil type can explain vegetation changes quite well. We propose that interactive effects exist among impact factors on vegetation NDVI, and the synergistic effects of the impact factors show mutual and nonlinear enhancements. The interactions among impact factors significantly enhance the impact of a single factor on vegetation changes. The most suitable characteristics of the main impact factors that promote vegetation growth were revealed by this study and will help improve our understanding of factors that impact NDVI and its driving mechanisms. Our findings suggest that the established favourable value range or the most suitable characteristics of impact factors will help management plans to intervene and promote vegetation change for vegetation restoration and alleviate environmental degradation.

岷江上游干旱河谷岷江柏的光合与水分生理特征干湿季对比研究

PDF HTML阅读 XML下载 导出引用 引用提醒 岷江上游干旱河谷岷江柏的光合与水分生理特征干湿季对比研究 DOI: 10.5846/stxb202109092538 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 四川省科技计划项目（18DZYF0676）；四川省林业科学研究院院基金项目；阿坝州财政专项扶贫资金项目 Comparative study on photosynthetic physiological and water physiological characteristics of Cupressus chengiana in wet and dry season, the upper Minjiang River dry valley Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:岷江柏（Cupressus chengiana）是干旱河谷地区的重要生态恢复物种，为探讨岷江柏对干旱河谷环境的适应策略，以生长于岷江上游干旱河谷自然生境中的岷江柏为研究对象，研究分析了其在湿季（7月）和干季（11月）的水分生理特征和光合生理特征。结果表明：（1）水分生理方面，相较于湿季，干季岷江柏的脯氨酸（Pro）、可溶性糖（SS）、过氧化物酶（POD）显著增加（P<0.05），比叶重（LMA）、黎明水势（Ψpl）、正午水势（Ψml）则显著下降（P<0.05）；（2）光合生理方面，相较于湿季，岷江柏在干季的气孔导度（Gs）、蒸腾速率（Tr）、饱和光下最大净光合速率（Pnmax）、初始羧化效率（CE）、光合能力（Amax）、CO2补偿点（Γ）、光呼吸速率（Rp）、最大羧化速率（Vcmax）、最大电子传递速率（Jmax）、磷酸丙糖利用率（TPU）、Jmax/Vcmax、光能捕获效率（Fv'/Fm'）、PSII实际光化学效率（ФPSII）、光化学猝灭系数（qP）、电子传递效率（ETR）均显著下降（P<0.05），而暗呼吸速率（Rd）、水分利用效率（WUE）、非光化学猝灭系数（NPQ）则显著上升（P<0.05）。干季，岷江柏采取增加水分获取能力并降低水分散失的水分利用策略、增加光合产物消耗策略、增加热耗散的光合器官保护策略等，以适应干季干旱、低温等环境胁迫，进而表现出较强的环境适应性。 Abstract:Cupressus chengiana is an important ecological restoration species in the dry valley. In order to study the adaptive strategy of C. chengiana to environment, photosynthetic physiological characteristics and water physiological characteristics of C. chengiana were measured in wet season (July) and dry season (November), respectively. The results showed that:(1) For water physiology, compared with wet season, peroxidase (POD), soluble sugar (SS) and proline (Pro) of C. chengiana increased significantly in dry season (P<0.05), but leaf mass per area (LMA), predawn leaf water potential (Ψpl) and midday leaf water potential (Ψml) decreased significantly (P<0.05). (2) For photosynthetic physiology, compared with wet season, stomatal conductance (Gs), transpiration rate (Tr), light-saturated net photosynthetic rate (Pnmax), initial carboxylation efficiency (CE), photosynthetic capacity (Amax), CO2 compensation point (Γ), photorespiration rate (Rp), the maximum carboxylation rate (Vcmax), the maximum electron transport rate (Jmax), triose phosphates utilization rate (TPU), Jmax/Vcmax, excitation capture efficiency (Fv'/Fm'), actual photochemical efficiency of PSII (ФPSII), photochemical fluorescence quenching (qP) and electron transport rate (ETR) of C. chengiana decreased significantly in dry season (P<0.05), but dark respiration rate (Rd), water use efficiency (WUE) and non-photochemical fluorescence quenching (NPQ) increased significantly (P<0.05). In conclusion, in order to adapt to drought, low temperature and other environmental stress in dry season, C. chengiana adopted the water use strategy by increasing soil moisture acquisition ability and reducing water loss, the increasing photosynthetic product consumption strategy, and the photosynthetic organ protection strategy by increasing heat dissipation. 参考文献 相似文献 引证文献

干旱叠加海平面上升、氮负荷增加对河口潮汐沼泽生态系统净CO2交换的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 干旱叠加海平面上升、氮负荷增加对河口潮汐沼泽生态系统净CO2交换的影响 DOI: 10.5846/stxb202106291727 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 福建省自然科学基金重点项目（2019J02008）；福建省林业科技项目（201916）；国家自然科学基金项目（41877335） Effects of combination of drought and sea-level rise, nitrogen enrichment on net ecosystem exchange of CO2 in an estuarine tidal marsh Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:河口潮汐沼泽湿地是全球重要的蓝碳生态系统之一。海平面上升和氮负荷增加是入海河流河口湿地面临的两个主要环境问题。近年来，干旱事件频发，干旱及其与海平面上升、氮负荷增加的叠加将如何影响河口潮汐沼泽湿地生态系统净CO2交换，目前还未见报道。2020年夏秋，福建沿海经历了数月严重的气象干旱，这为揭示干旱对河口潮汐沼泽湿地生态系统净CO2交换量（NEE）和生态系统呼吸（ER）的影响提供了一个契机。分别于2019年8-10月（正常天气）和2020年8-10月（干旱天气），在闽江河口微咸水短叶茳芏沼泽湿地运用光合作用测定仪+箱法测定不同处理（对照、模拟海平面上升、模拟氮负荷增加、模拟海平面上升＋模拟氮负荷增加）短叶茳芏湿地生态系统NEE和ER，以期揭示气象干旱与海平面上升、氮负荷增加的叠加对河口沼泽湿地生态系统净CO2交换的影响。与正常天气相比，干旱天气下各处理（包含对照）的NEE均显著降低（P<0.05）；对照、海平面上升以及氮负荷增加处理样地的ER显著减少（P<0.05），海平面上升＋氮负荷增加处理ER显著增加（P<0.05）。NEE （负值）与光合有效辐射（PAR）与呈显著负相关（P<0.05）。研究发现，气象干旱降低了河口潮汐沼泽生态系统固碳规模，且这种固碳规模的降低在叠加海平面上升或氮负荷增加的情景下仍将存在。 Abstract:Estuarine tidal marsh is one of the coastal blue carbon ecosystems in the world. Sea level rise and nitrogen enrichment are two major global environmental issues facing by estuarine wetlands. In recent years, meteorological drought events often occurred. The influences of drought, and combination of drought and sea-level rise, and nitrogen enrichment on net ecosystem exchange (NEE) of CO2 of estuarine tidal marshes remain poorly studied. A novel approach using the weirs for in-situ manipulating sea level rise (including the increase of depth and duration of flooding) at relatively larger spatial scale was developed in the journal of Methods in Ecology & Evolution, however at present, the method has not been actually used in-situ to study effects of sea level rise on carbon cycle in coastal tidal marsh ecosystem. In our study, we improved the weirs and used them to manipulate the sea level rise (SR) treatment in-situ, and meanwhile applied in-situ experimental manipulations of control, nitrogen enrichment (NE), and SR+NE in a tidal brackish marsh of Cyperus malaccensis in the Minjiang River estuary, southeastern China. In summer and autumn of 2020, the meteorological drought occurred in the coastal zone of Fujian Province, which provided an opportunity to determine the effects of drought, the combination of drought and simulated sea-level rise, nitrogen enrichment on the NEE and ecosystem respiration (ER). From August to October in 2019 and 2020, the NEE and ER were measured using transparent static chamber (or black cloth shading)+Licor-6800 method. Compared with 2019 (normal year), the NEE under each treatment (including control) was significantly reduced in 2020 (drought year), and the ER in the control, the SR, and the NE was also significantly decreased in 2020. NEE was significantly negatively correlated with the photosynthetically active radiation (PAR). The results indicate that drought event can reduce net CO2 gain in estuarine tidal marshes, and this decrease still occurs under combination of drought and sea-level rise, nitrogen enrichment. 参考文献 相似文献 引证文献

Variations in phytoplankton primary productivity in aquaculture ponds with &lt;i&gt;Litopenaeus vannamei&lt;/i&gt; from subtropical estuary in southeast China

浮游植物初级生产力是评估水产养殖系统结构与功能的基础环节，对渔业资源的开发与管理具有重要意义.于2018年5—10月，采用黑白瓶法对闽江河口区的3个南美白对虾养殖塘（PondⅠ、PondⅡ和PondⅢ）水体浮游植物初级生产力进行了原位监测，初步研究了初级生产力在池塘间的差异性及其时间变化特征.结果显示，养殖期间养殖塘水体浮游植物总初级生产力（GPP）、呼吸消耗量（R_P）和净初级生产力（NPP）变化范围分别为619.99~9498.67、1003.16~7063.33和-4179.50~6362.96 mg O₂/（m²·d），均值分别为（4386.22±409.72）、（3607.53±150.27）和（778.68±260.16） mg O₂/（m²·d），呈现出Pond Ⅱ>Pond Ⅲ>PondⅠ的特征.时间变化上，养殖塘水体浮游植物GPP和NPP呈现出随养殖阶段推移而增加的特征.多元逐步回归分析结果显示，N营养盐和叶绿素a浓度是影响养殖塘水体浮游植物初级生产力时空变化的主要因子.GPP/R_P系数在养殖初期小于1，而在养殖中后期大于1，表明养殖塘水体在养殖初期以异养生产为主，而中后期以自养生产为主.本文研究结果表明，今后在开展大尺度滨海水产养殖塘初级生产力精确评估及其相关模型参数构建时，需考虑池塘间水体初级生产力的时间变化特征.;The phytoplankton primary productivity is a great basis to evaluate the structure and function of aquaculture ecosystem, which qualify important significance for fishery resources exploitation. In this study, we measured the phytoplankton primary productivity among shrimp (Litopenaeus vannamei) ponds during the aquaculture periods in the Minjiang River estuary, Southeast China. The results showed that the gross primary production (GPP), respiration (R_P) and net primary production (NPP) of phytoplankton among ponds over the shrimp aquaculture period varied from 619.99 to 9498.67, 1003.16 to 7063.33, and -4179.50 to 6362.96 mg O₂/(m²·d) respectively, with mean values of (4386.22±409.72), (3607.53±150.27) and (778.68±260.16) mg O₂/(m²·d) respectively. Overall, the mean GPP, R_P and NPP decreased significantly among the three ponds in the order:PondⅡ > PondⅢ > PondⅠ. The phytoplankton primary productivity demonstrated a clear seasonal pattern, with an increasing trend with time. Multiple stepwise regression analysis showed that nitrogen nutrient and chlorophyll-a were the major impact factors of the spatiotemporal variations of phytoplankton primary productivity in shrimp ponds. Our results highlighted that the importance of considering the spatiotemporal variations in primary productivity in improving the accuracy of large-scale estimation of phytoplankton primary productivity in coastal aquaculture pond.

Spatiotemporal Relationship between Ecosystem Service Value and Ecological Risk in Disaster-Prone Mountainous Areas: Taking the Upper Reaches of the Minjiang River as an Example.

Mountainous areas are susceptible to disasters; the frequent occurrence of disasters drives the changes in ecosystem service value (ESV) and also brings certain ecological risk, which further increases the incidence of disasters. However, few scholars have investigated the spatiotemporal correlation between the ESV of disaster-prone mountainous areas and ecological risk index (ERI) with basin as the unit. This paper aims to clarify the spatial relationship between ESV and ERI under the changes of land use. Taking the upper reaches of the Minjiang River as the study area, the authors collected the land use data of 2000–2020, estimated ESV by the value equivalent factor per unit area method, and constructed the ERI. On this basis, the relationship between ESV and ERI was investigated in details. The results show the following: (1) From 2000 to 2020, the total ESV exhibited a fluctuating upward trend. The spatial distribution of ESV was greatly affected by slope and altitude; an important reason for the rising ESV in the study area is the increase of forest area and water area. (2) The upper reaches of the Minjiang River had a generally low ERI and relatively good overall ecoenvironment. After 2010, however, the ecological risk continued to rise. Most of the strongly high risk areas are areas with frequent human activities, such as low-altitude areas and river banks. (3) There is a spatial correlation and coupling between ESV and ERI in the study area; i.e., the strongly high ESV areas generally had a low ecological risk. The correlation intensified with the elapse of time. The changes in the service value of regional ecosystems driven by unreasonable land use will have a great impact on the ecoenvironment. By clarifying the spatiotemporal relationship between ESV and ERI, this research provides theoretical basis and data support to the formulation of ecoenvironmental restoration and protection plans for the upper reaches of the Minjiang River and to the coordinated development between society, economy, and ecoenvironment in the region.

Predicting the Hydrological Impacts of Future Climate Change in a Humid-Subtropical Watershed

Future climate change is expected to impact the natural systems. This study used future climate data of general circulation models (GCMs) to investigate the impacts of climate change during the future period (2062–2095) relative to the historical period (1981–2014) on the hydrological system of the Minjiang river watershed, China. A previously calibrated soil and water assessment tool (SWAT) was employed to simulate the future hydrology under the impacts of changes in temperature, precipitation, and atmospheric CO2 concentration for four shared socioeconomic pathways (SSP 1, 2, 3, and 5) of the CMIP6. The study revealed that the impacts of increase in future temperature, i.e., increase in ET, and decrease in surface runoff, water, and sediment yield will be countered by increased atmospheric [CO2], and changes in the hydrological parameters in the future will be mostly associated to changes in precipitation. Data of the GCMs for all the SSPs predicts increase in precipitation of the watershed, which will cause increase in surface runoff, water yield, and sediment yield. Surface runoff will increase more in SSP 5 (47%), while sediment and water yield will increase more in SSP 1, by 33% and 23%, respectively. At the seasonal scale, water yield and surface runoff will increase more in autumn and winter in SSP 1, while in other scenarios, these parameters will increase more in the spring and summer seasons. Sediment yield will increase more in autumn in all scenarios. Similarly, the future climate change is predicted to impact the important parameters related to the flow regime of the Minjiang river, i.e., the frequency and peak of large floods (flows &gt; 14,000 m3/s) will increase along the gradient of scenarios, i.e., more in SSP 5 followed by 3, 2, and 1, while duration will increase in SSP 5 and decrease in the other SSPs. The frequency and duration of extreme low flows will increase in SSP 5 while decrease in SSP 1. Moreover, peak of extreme low flows will decrease in all scenarios except SSP 1, in which it will increase. The study will improve the general understanding about the possible impacts of future climate change in the region and provide support for improving the management and protection of the watershed’s water and soil resources.

Investigation on freshwater crab populations and Paragonimus infections in the Minjiang River basin along the middle section of Wuyi Mountain

To investigate the populations of freshwater crabs, the intermediate host of Paragonimus and Paragonimus infections in freshwater crabs in the Minjiang River basin along the middle section of Wuyi Mountain, so as to provide baseline data for parasitic disease control and research and expansion of the parasite resource bank. From November 2020 to April 2021, freshwater crabs were sampled from streams and ditches neighboring residential areas in Jianning County and its neighboring Ninghua, Shaowu, Jiangle and Shunchang counties. The crab species was identified based on the morphological features of the terminal segment of the first abdominal appendage of male crabs, and Paragonimus infections were detected in freshwater crabs. The Paragonimus metacercariae were isolated, and the types of metacercariae were identified based on the metacercaria size, cystic wall thickness, and the excretory bladder and intestinal tract morphology. In addition, the prevalence, intensity and index of metacercaria infections were calculated in freshwater crabs. There were seven crab species found in Jianning County and six neighboring water systems along the Minjiang River basin, including Sinopotamon jianglense, S. fukinense, Huananpotamon lichuanense, H. lini, H. shenni, H. planopodum, Bottapotamon engelhardti, and there were metacercariae of three Paragonimus species detected in these crabs, including P. westermani, P. skrjabini and P. sanpingensis, with a prevalence rate of 43.6% (125/287). The infection rates of P. westermani, P. sanpingensis and P. skrjabini were 57.1% (48/84), 26.2% (22/84) and 61.8% (21/34) in S. jianglense, and the infection rates of P. westermani and P. sanpingensis were 52.6% (51/97) and 30.9% (30/97) in S. fukinense, while the rate of P. westermani infection was 6.9% (5/72) in H. lichuanense, which is the first record of P. westermani infections in H. lichuanense. Mixed P. westermani and P. sanpingensis infections were predominantly found in freshwater crabs sampled from Jianning County, where the rate of Paragonimus infections was 70.4% (76/108), with 15.3 metacercariae identified in each crab with Paragonimus infections and 1.9 metacercariae found in each gram of crabs with Paragonimus infections, and the index of metacercariae infections was 20.5. In addition, P. westermani, P. skrjabini and P. sanpingensi metacercariae were found in freshwater crabs sampled from Jianning-neighboring counties, where the rate of Paragonimus infections was 52.3% (56/107), with 9.8 metacercariae identified in each crab with Paragonimus infections and 0.9 metacercariae found in each gram of crabs with Paragonimus infections, and the index of metacercariae infections was 4.6. There are multiple freshwater crab species and Paragonimus infection is high in freshwater crabs in Jianning County and its neighboring Minjiang River basin, which is a high-risk natural focus for Paragonimus infections.