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Vertical structure of tidal currents in the Xuliujing Section of Changjiang River Estuary
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Zhigao Chen1, 2, 3, 4, *, Ya Ban2, Xiaoye Chen1, Dajun Li1, Shengping Wang1, 4, *
Acta Oceanologica Sinica | 2023, 42(2) : 44 - 55
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Acta Oceanologica Sinica | 2023, 42(2): 44-55
• Physical Oceanography, Marine Meteorology and Marine Physics •
Vertical structure of tidal currents in the Xuliujing Section of Changjiang River Estuary
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Zhigao Chen1, 2, 3, 4, *, Ya Ban2, Xiaoye Chen1, Dajun Li1, Shengping Wang1, 4, *
Affiliations
  • 1 Faculty of Geomatics, East China University of Technology, Nanchang 330013, China
  • 2 Chongqing Academy of Metrology and Quality Inspection, Chongqing 401120, China
  • 3 Nanjing White Shark Surveying and Mapping Technology Co., Ltd, Nanjing 210038, China
  • 4 Key Laboratory of Marine Environmental Survey Technology and Application, Ministry of Natural Resources, Guangzhou 510300, China
Published: 2023-02-25 doi: 10.1007/s13131-021-1976-y
Outline
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Three long-term fixed acoustic Doppler current profilers were first used for investigating the vertical structure of tidal currents in Xuliujing Section of Changjiang River Estuary. Moreover, three different periods (spring, summer and fall) were also considered for investigating seasonal variations. The semi-diurnal tides were the most energetic, with along-channel speed of up to 80 cm/s for M2 constituent, which dominates at all stations with percent energy up to 65%–75% during seasons. The shape of tidal ellipses of the most energetic semi-diurnal constituent M2 showed obvious polarization of the flow paralleling to the riverbank, with the minor semi-axis being generally less than 20% of the major one. The maximum velocity of mean current is appeared in top layers at all the three stations, and the velocity decreased with the depth. The seasonal variations of direction are also observed, which is probably caused by complex local topography since the erosion and deposition in riverbed. Observed vertical variation of four parameters of M2 ellipses, agreed well with the optimally fit frictional solutions in top and middle layers. However, there was an obvious difference between frictional model and observed data in the lower water column. Discrepancies are probably on account of stratification, which strengthens in summer and fall due to the freshening influence of the Changjiang River Estuary outflow.

vertical structure  /  seasonal variations  /  tidal current  /  mean current  /  acoustic Doppler current profiler  /  Changjiang River Estuary
Zhigao Chen, Ya Ban, Xiaoye Chen, Dajun Li, Shengping Wang. Vertical structure of tidal currents in the Xuliujing Section of Changjiang River Estuary[J]. Acta Oceanologica Sinica, 2023 , 42 (2) : 44 -55 . DOI: 10.1007/s13131-021-1976-y
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1 Introduction
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Flow in estuaries is very complex, characterized by the interactions of tidal currents, runoff (outflow), topography constraint and strong turbulence. Although the runoff or outflow may have large speed in tidal river, the weaker tidal currents are also important in determining the transport of dissolved and particulate matter in suspension (Bolaños et al., 2013; López et al., 2021). Knowledge of the vertical and horizontal structure of tidal currents is important to understand the dispersal and net drift of sediment and pollutants in the water column, and it is vital for long-term estuarine management (Prandle, 1982; Davies, 1990; Siagian et al., 2021).
Observations of basic tidal current structure have been carried out all over the world. The energy of tidal currents in coastal areas differs according to water depth and location and is driven by distinct responses to astronomical forcing (DiMarco and Reid, 1998; Tsimplis, 2000; Teague et al., 2002; Bi et al., 2019). Observation results usually indicate the current amplitude decrease toward the bottom of the water column and a phase advance with depth, indicating that the maximum current is reached earlier at depth than at the surface (Kundu et al., 1981; Tsimplis, 2000; Sánchez-Román et al., 2008). Analytic models for frictional bottom boundary layers have been developed to account for the observed amplitude decrease and phase advance. A constant eddy viscosity model is often used to compare with observations and the results showed that the model did well in describing most of the tidal current features throughout all depths (Kundu et al., 1981; Tsimplis, 2000; Codiga and Rear, 2004).
Changjiang River Estuary is the largest and most important estuary in China, which is world-famous for its great abundance and development intensity of soil and water, water transport and fishery resources. With an average annual discharge of 3.0×104 m3/s, Changjiang River accounts for 90% of the total freshwater content into the East China Sea (Beardsley et al., 1985; Chen et al., 2001). Xuliujing Section located near Shanghai City, and it is about 110 km away from the river mouth (Fig. 1). Moreover, Xuliujing is the demarcation point of South and North Branches and it is the starting point of multilevel branching in the Changjiang River Estuary. As an important boundary point for the Changjiang River to enter the estuary, the study of the tidal characteristics of Xuliujing becomes very important not only for the estuary scientific research itself, but also for the discussion of the impacts of major projects such as the Three Gorges Dam, the South-to-North Water Transfer Project, and the Changjiang River Estuary Deepwater Channel (Mei et al., 2019). Salinity intrusion generally reaches to less than 100 km seaward from the delta apex and can reach beyond the Xuliujing Section only during extremely low flows (Liu, 2004), so the studied area is generally subject to freshwater conditions.
Previous studies have resolved some of the major features of the tidal signal (Larsen et al., 1985; Yang et al., 2012). Nevertheless, as the measurement of these studies were taken by conventional current meters or the short-term data, the vertical resolution was poor. Three long-term mooring acoustic Doppler current profilers (ADCPs) are first used to investigate the vertical structure of the tidal currents in the Xuliujing Section of Changjiang River Estuary in this paper (Fig. 1). The contribution of primary tidal constituents is examined, as well as the structure of tidal currents in the horizontal and vertical primary. Influences of bathymetry variation on tidal current structure are also investigated.
The discharge of the Changjiang River is huge with which a marked seasonal variation (Fig. 2). The discharge is smaller in dry winter with the daily average is about 2.0×104 m3/s and increases slightly in spring, while in the flood-period summer, the discharge reaches the peak of more than 5.0×104 m3/s, which is more than twice that in winter. In fall, the discharge is decreasing. The seasons are therefore divided referring to the discharge variations. In this way, the mean currents at the study stations are also measured for interpreting variations of tidal currents during different seasons.
2 Data and methods
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Three 300 kHz Workhorse ADCPs, named C1, C2 and C3, were mounted upward on the river-bed at Xuliujing Section with different water depth (Fig. 3). C2 located in the thalweg of the river, while C1 and C3 located in northern and southern shallow water, respectively. The depth cell length was set as 1.0 m, and the sampling interval was set as 0.5 h for the three ADCP. The tidally-averaged depth, top and bottom unmeasured length, and number of valid bins for each ADCP profile were shown in the following Table 1. More details about the obtain and calibration of field data can be found in the literature of Zhao et al. (2016).
Three representative periods have been selected (March 1 to May 31, 2011, June 1 to August 31, 2011 and September 1 to November 30, 2011) for investigating seasonal variations of the vertical profiles according to the marked seasonal change of river discharge. Although these periods do not exactly correspond to specific seasons, they can also be referred as spring, summer and fall periods, respectively. All of the raw ADCP data are screened to exclude abnormal and poor data (Wong and Münchow, 1995). The screening criteria are set such that the valid ADCP data should meet the following requirements: error velocity is less than 6 cm/s, vertical velocity is less than 8 cm/s, and percentage good data is greater than 95%. Taking the result of traditional flowmeter as a reference, the ADCP velocity data achieved respectively 5 cm/s of measurement accuracies after the post-treatment.
Tidal constituents are analyzed by use of least squares harmonic method implemented by toolbox “T_tide” of Matlab (Pawlowicz et al., 2002). Velocity observations at each depth bin were used to compute the tidal ellipses of the main semidiurnal (M2) and main diurnal (K1) constituents. Tidal ellipses can be presented in terms of four parameters, including semi-major axis (W), semi-minor axis (w), orientation angle (Θ, direction of the maximum current speed), and the Greenwich phase lag (Φ). The conventional notations and basic equations are provided in Appendix A. Bootstrap method is used for estimating the standard error and 95% confidence intervals (Pawlowicz et al., 2002).
3 Results
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3.1 Energy partition
Kinetic energy variance ratio (V E) is usually used to examine the relative contribution of the tidal component to the total flow,
$ {V_E} = \left( {{{\sigma _{{\rm{K}}{{\rm{E}}_{{\text{fit}}}}}^2} \mathord{\left/ {\vphantom {{\sigma _{{\rm{K}}{{\rm{E}}_{{\text{fit}}}}}^2} {\sigma _{K{E_{{\text{dat}}}}}^2}}} \right. } {\sigma _{{\rm{K}}{{\rm{E}}_{{\text{dat}}}}}^2}}} \right) \times 100{\text{% }}. $
V E compares the kinetic energy variance σ 2 KE, where KE=(u 2+v 2)/2 is the kinetic energy per unit mass, of the multiple-constituent harmonics (subscript ‘‘fit’’) to that of the total measured raw velocities (subscript ‘‘dat’’). Relative energy in individual tidal constituents is gauged as
$ {E_n} = \left( {{{{\rm{K}}{{\rm{E}}_n}} \mathord{\left/ {\vphantom {{K{E_n}} {\sum\limits_{i = 1}^N {{\rm{K}}{{\rm{E}}_i}} }}} \right. } {\sum\limits_{i = 1}^N {{\rm{K}}{{\rm{E}}_i}} }}} \right) \times 100{\text{% }}, $
where n is an index of the number (N) of constituents included in the harmonic fit. Five most energetic tidal constituents (including diurnal constituents O1, K1, and semidiurnal constituents N2, M2, and S2, which are determined by harmonic analysis of 35 tidal constituents) are shown in the pie chart of Fig. 4. From the pie chart it appears that the total kinetic energy variance (area of the pie, including summed tidal and non-tidal variance) varies with season and water depth.
The general pattern is that the total kinetic energy variance decreases from the deep station (C2) to the shallow stations (C1 and C3). Total variances at the deep stations are obvious greater than that at shallow station. The relative contribution V E ranges from 32% to 70%. At deeper station C2, V E ranges from 36% to 70%, which is greater than that of shallower stations C1 (32%–52%) and C3 (34%–55%). The near-resonance of the trumpet-shaped Changjiang River Estuary to semidiurnal forcing may contribute to this energy distribution, which causes strongly amplified tidal currents to dominate the total kinetic energy near the mouth of Changjiang River relative to the far-field sites of East China Sea (Wang et al., 1999; Zhu et al., 2012). Similar patterns can also be found in other estuaries (Wünchow et al., 1992; Codiga and Rear, 2004).
In addition, percent energy (E n) is used for accessing relative energy of individual tidal constituents to all the tidal components (histograms in Fig. 4). The M2 constituent dominates at all stations with the E n range from 65% to 75%. S2 constituent is the next most important tide with the E n range from 9% to 14%. For diurnal tidal constituents, the percent energy E n of K1 and O1 is less than 5%. Overall, semi-diurnal tidal group is overwhelmingly dominant with the percent energy over 80%.
3.2 Mean currents
Frictional model using constant eddy viscosity may fail to capture the characteristics of observed tidal ellipses, especially for the bottom water layer. Therefore, the vertical structure of the mean currents (outflow) at three stations in different seasons is also examined for investigating the impact of outflow on tidal current (Fig. 5). The maximum flow velocity (speed) appears in top layers at all the three stations, and the velocity decreases with the depths slowly. In addition, for seasonal variations of mean currents is obvious: the velocity in summer with the maximum of 0.6 m/s is much bigger than that in another two seasons at each depth. The most important reason for this is that the annual discharge distribution of Changjiang River Basin directly controlled by the rainfall. Precipitation along the lower basin is primarily between May and August, account for nearly 73% of the annual total (Chen et al., 2001). The seasonal variations of mean currents are very consistent with discharge variations.
Flow direction remains almost constant from top to bottom water layers (within 10°) and parallel to the riverbank. The direction slowly increases with the depth until to the bottom in Station C1 and Station C2, on the contrary, it seems increases with the depth in Station C3. In addition, there have been some minor differences between directions of three seasons. These variations are probably due to complex local bathymetry since the erosion and deposition of riverbed significantly influence the depth of the three stations (Zhao et al., 2016). It is interesting to notice that Xuliujing Section locates in the middle of the bend river channel (Fig. 1). Influenced by both of Coriolis force and centrifugal force, the surface of the water appears transverse slope in which the water level of concave bank is higher than that of convex bank (Zhao et al., 2016). Therefore, the transverse shear velocity generated and will also result in the seasonal variations of direction. In addition, due to the freshwater condition, barotropic current dominated in all the three seasons (can be found in the following Section 3.3). The barotropic current varies with the seasons and it also contributes to the flow direction of main current.
3.3 Tidal ellipses
The vertical profiles of M2 tidal ellipses at three stations in different seasons are displayed in Fig. 6, which shows the obvious polarization of the flow with the axis paralleling to the riverbank in all seasons. The minor semi-axis is always less than 20% of the major one, similar to the results in river mouth of Changjiang River Estuary (Pu et al., 2017), but significantly different from that in open-water estuary or shelf (Codiga and Rear, 2004; Herrera et al., 2008). The percentage of minor and major decreases towards the water surface.
Similarly, these diurnal ellipses align in almost the same direction and remain little changed at top and middle layers (not showed). The major semi-axis of K1 less than one-fifth of that of M2, which is highly consistent with the energy partition shown in Fig. 4. For this reason, the following harmonic analysis only be used to calculate the ellipse parameters of M2 tidal constituent for investigating the vertical structure of observed and fitted tidal currents.
It is well known that the baroclinic effects play an important role in determining the currents structure in oceans and estuaries. Barotropic current and vertical distribution of baroclinic current for M2 constituent at different stations are shown in Fig. 7. The top layer with an approximate thickness of 3 m in C1 station was slightly baroclinic. However, ADCPs are unable to accurately capture the complete velocity profile in open channels due to draft of ship and measurement errors near their transducers (Muste et al., 2010). In the experiments, the surface layer with an approximate thickness of 3 m of C1/C3 and 5 m of C2 is missing or contaminated and not showed in the figure. Therefore, the baroclinic effects are not well observed in the top layers. In addition, salinity intrusion generally reaches to less than 100 km seaward from the delta apex and can reach beyond the Xuliujing Section only during extremely low flows (Liu, 2004; Mei et al., 2019), so the studied area is generally subject to freshwater conditions. In this way, amplitudes of tidal constituents did not vary in depth for three stations, showing obvious barotropic behaviour.
3.4 Harmonic analysis
As showed in Fig. 8, the semi-major axis decreases slowly towards the bottom with the minimum value about 0.60 m/s, which indicates the speed of tidal current is becoming smaller. Unlike semi-major axis, the semi-minor axis is negative and very small whose values are all less than 0.05 m/s, which means that the tidal ellipse is nearly close to a straight line. Orientations remains almost constant in the vertical profiles of the three periods, which is consistent with the directions of mean current. It is worth noticing that the phases decrease toward the bottom, and the difference between that of upper and bottom is ~5°, which indicating upper currents lagging bottom currents about 10 min.
Only slight variations between the three seasons are found, one of them is that the phases in spring is slightly smaller than that of summer and fall. On the contrary, the semi-major axis of summer and fall are slightly bigger than that of spring.
Station C2 located in the thalweg of the river with the depth of 49.3 m. So, the vertical distribution in Station C2 has some similarities with that in Station C1, but it has its own characteristics: the semi-major axis almost remains constant in the upper profiles, and they decreases slowly from ~30 m towards the bottom. In addition, it is interesting to notice that the semi-minor axis is positive, which indicates the current vectors rotate counterclockwise around these ellipses. Discrepancies between different stations are probably due to high polarization of the flow paralleling to the axis of the channel, and the semi-minor axis have little influence on the characters of the tidal currents.
Seasonal variations of orientations in Station C2 is similar to that of the directions of mean current, that the largest orientations is in fall, next is in summer, and the smallest is in spring. In addition, the phases in spring is slightly smaller than that of summer and fall. On the contrary, the semi-major axes of summer and fall are slightly bigger than that of spring.
Because Stations C3 and C1 are both located in shallow water, the vertical distribution of the M2 ellipses in Station C3 is very similar to that in Station C1. Only slightly difference is that the phases variation between upper and bottom is much smaller in the Station C3, where the maximum difference is ~3°.
4 Discussion
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4.1 Effects of bottom friction on variation of tidal ellipses
The vertical variability of the tidal ellipse can be mainly attributed to the bottom friction, the contribution of the internal tides and the shear stresses variations from the adjacent layers (Tsimplis, 2000). This section will attempt to assess the effects of frictional variation contribution on the simple models.
Simple frictional models with a constant eddy viscosity have been shown capture characteristics of vertical structure reasonably well in some previous studies (Kundu et al., 1981; Tsimplis, 2000; Lee et al., 2011). Assuming the hydrostatic condition and an unstratified fluid, the horizontal pressure gradients are independent of water depth and are imposed by the free-surface height. A no-stress condition is applied to the surface and a no-slip condition is applied to the layer bottom. The solution of the model is deduced and provided in Appendix B. A cost function (CF) proposed by Codiga and Rear (2004) is used to realize optimal fitting between data and model velocity vectors,
$ {\text{CF}} = \frac{1}{N}\sum\limits_{i = 1}^N {\left( {{{\left| {{\mathbf{w}}_d^ + \left( {{z_i}} \right) - {\mathbf{w}}_m^ + \left( {{z_i}} \right)} \right|}^2} + {{\left| {{\mathbf{w}}_d^ - \left( {{z_i}} \right) - {\mathbf{w}}_m^ - \left( {{z_i}} \right)} \right|}^2}} \right)} , $
where subscript d (m) indicates observed data (model solution), z is the height above the riverbed, i is the index of the N depth bins, w + and w − are respectively the first and second term of Eq. (A4) in Appendix A. The optimization is carried out using function ‘‘fmincon’’ and variants in Matlab, and achieve a minimum value of CF.
Optimal frictional model results (solid line) with the eddy viscosity (denoted as ω) are shown in Fig. 8 for three stations respectively. The optimally fit values of ω vary from 2×10−4 m2/s to 8×10−4 m2/s. The models are successful in describing some of the characteristics of the profiles of the M2 constituent, especially in the top and middle layers, the frictional model is in good agreement with all observed characteristics. The model describes the semimajor axis decrease with depth, and the advance of the phase near the bottom in relation to the phase near the surface. It can be concluded that the indirect effect on the eddy viscosity is a main contributing factor, and the influences of bathymetric changes is secondary at these depths (Codiga and Rear, 2004).
Sample frictional models with constant eddy viscosity are successfully captured some ellipse characteristics at the middle and upper layers. Following will show that the models are failing to capture characteristics near the bottom.
4.2 Inadequacies of frictional models
The major disadvantage of the frictional model for all the three stations is in the lower water column. The observed low-depth semi-major axis is much smaller than that fit by frictional model. On the contrary, the phases fit by frictional model are much advanced than the observed ones. Therefore, frictional models using four different eddy viscosity ω are solved and shown in Fig. 9 to interpret the discrepancies. With the eddy viscosity increase, the semi-major axis is decreased correspondingly at deepest 10 m water column, but the variation gradient is much bigger than that of observation. In addition, it is noteworthy that the phases fit by frictional model decreases rapidly with the increasing eddy viscosity, while the observed phases only slightly decrease in the deepest 3–4 m water column.
Therefore, frictional model does not present a reasonable pattern with decreased or increased eddy viscosity values. The main reason is that the cost function shown in Eq. (3) weights equally for all depths so that changes occur in some lower layers have a limited impact on optimally fit. Complex topography and seasonal variations of estuarine outflow are contributed to this pattern (Mohn et al., 2013), but they are not considered at all in these frictional models.
4.3 Influence of outflow on tidal current ellipses
The characteristics of tidal ellipses cannot be captured well by eddy viscosity variation in astronomical forcing, which prompting other influencing factors may be investigated. Figures 10 and 11 show the mean current and M2 ellipses at different depth for three seasons respectively. In each season, flow is generally eastward, that is from upstream to downstream. Peak speed of mean current reaches from 0.5 m/s to 0.7 m/s in summer for all stations. It is interesting to find that the orientations of ellipses are remarkably consistent with the directions of mean current in all seasons. This pattern is often caused by a combination of estuarine outflow and topography constraints, and it has qualitative characteristics for tidal ellipses.
In addition, the seasonal variations of semi-major axis are basically consistent with velocity of mean currents. Seasonal variations in tidal current ellipses may have relations with the seasonal cycle of stratification, which is enhanced significantly in summer and fall due to a combination of solar heating and the freshening induced by estuarine outflow (Ullman and Codiga, 2004). Lateral shear in the mean current can enhance or weaken effect of Coriolis parameter and thus shift the fixed tidal forcing frequency closer to or farther from resonance, thereby changing the response amplitude.
5 Conclusions
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Three ADCPs mounted on the riverbed of Xuliujing Section are firstly used for investigating the vertical structure of the tidal currents and the seasonal variations in Changjiang River Estuary. The observations and analysis of the tidal current in this paper have revealed the noteworthy spatial variation of the tidal currents as well as some minor seasonal changes.
The M2 constituent dominates at all stations with percent energy up to 65%–75% during seasons, while the sum percent energy of diurnal constituents account for less than 5%. The minor semi-axis is much less than the major one, which indicates that the shape of tidal ellipse is close to a straight line and parallel with the axis of the channel. This observation is similar to that in strait or gulf but significantly different from that in open-water estuary.
The maximum velocity of mean current appears in top layers at all the three stations, and the velocity decreases with the depth. Due to the seasonal variation of precipitation, the maximum velocity of 0.6 m/s in rainy season of summer is much bigger than that in spring and fall. Direction of mean current remain almost unchanged from the upper to the lower layers (within 10°) and parallel to the riverbank. The seasonal variations of direction are also observed, which is probably caused by complex local topography since the erosion and deposition in riverbed.
Due to the near-resonance of the trumpet-shaped Changjiang River Estuary to semidiurnal forcing, the semi-major axis of M2 ellipse reaches the maximums ~0.80 m/s at the upper depth in study area, which is nearly twice as large as that in offshores. The orientations of ellipses are remarkably consistent with the directions of mean current in all seasons. The phases slowly decrease toward the bottom with the depth, and the difference between that of upper and bottom is ~5°, which indicating upper currents lagging bottom currents about 10 min.
Some of the characteristics of the profiles of the M2 constituent are successfully described in the frictional model with a constant eddy viscosity, especially in the top and middle layers. However, the major inadequacies of the frictional model are in the lower water layers. Discrepancies are probably due to seasonal cycle in stratification, which is enhanced significantly in the summer and fall due to a combination of solar heating and the freshening influence of the estuarine outflow. In addition, lateral shear in the mean current can enhance or weaken effect of Coriolis parameter and change the response amplitude.
Funding
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  • The National Natural Science Foundation of China under contract Nos 41806114 and 42266006; the Jiangxi Provincial Natural Science Foundation under contract Nos 20202ACBL214019, 20181BAB216031 and 20212BBE53031; the Technological Innovation and Application Development in Chongqing under contract No. CSTB2022TIAD-GPX0016; the Incentive and Guidance Project of Scientific Research Performance for Scientific Research Institutes in Chongqing under contract No. cstc2021jxjl120017; the Open Fund of the Key Laboratory of Marine Environmental Survey Technology and Application of Ministry of Natural Resources under contract Nos MESTA-2020-A002 and MESTA-2021-B001.
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doi: 10.1007/s13131-021-1976-y
  • Receive Date：2021-06-26
  • Online Date：2025-11-21
  • Published：2023-02-25
Article Data
Affiliations
History
  • Received：2021-06-26
  • Accepted：2021-11-14
Funding
The National Natural Science Foundation of China under contract Nos 41806114 and 42266006; the Jiangxi Provincial Natural Science Foundation under contract Nos 20202ACBL214019, 20181BAB216031 and 20212BBE53031; the Technological Innovation and Application Development in Chongqing under contract No. CSTB2022TIAD-GPX0016; the Incentive and Guidance Project of Scientific Research Performance for Scientific Research Institutes in Chongqing under contract No. cstc2021jxjl120017; the Open Fund of the Key Laboratory of Marine Environmental Survey Technology and Application of Ministry of Natural Resources under contract Nos MESTA-2020-A002 and MESTA-2021-B001.
Affiliations
    1 Faculty of Geomatics, East China University of Technology, Nanchang 330013, China
    2 Chongqing Academy of Metrology and Quality Inspection, Chongqing 401120, China
    3 Nanjing White Shark Surveying and Mapping Technology Co., Ltd, Nanjing 210038, China
    4 Key Laboratory of Marine Environmental Survey Technology and Application, Ministry of Natural Resources, Guangzhou 510300, China

Corresponding:

* E-mail: ; shpwang@ecut.edu.cn
shpwang@ecut.edu.cn.
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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