The term “downscaling” means to study a phenomenon first at larger or broader scales, then its results are used as a boundary condition for the continuing study at smaller or narrower scales, and so on. The major purposes form Chapters 2 to 5 were in a hierarchy of this logic. The main purposes of Chapter 2 were to define bulk APA behavior in Feitsui Reservoir and to find out the controlling mechanisms for its seasonal and inert-annual variations. Using the finding of bulk APA as a boundary, the main purpose of Chapter 3 was to identify which size fraction of plankton APA determined bulk APA variation in general. And it turned out to be the pico-fraction (0.2~3 μm) which was composed mainly by osmotrophs. The ELF method was adopted in Chapter 4 to make out the relative contribution of osmotrophs to the APA of the pico-fraction. In Chapter 5, a series of light/nutrient manipulation experiments were performed to examine their effects on osmotrophs’ growth.
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- 12 -
Fig. 1.1. Brief diagram shows the ecological importance of alkaline phosphatase (APase) in aquatic ecosystems. In phosphorus (P)-limited conditions, plankton (including bacterioplankton, phytoplankton, and zooplankton) could produce extracellular APase to hydrolyze dissolved organic phosphorus (DOP) and get additional phosphate (PO4
3-) source in compensating for their P-deficiency. The figure was modified from the book “Enzymes in the Environment: Activity, Ecology, and Applications” (Chrost & Siuda 2002).
Chapter 2
Temporal Variations of Alkaline Phosphatase Activity in a Subtropical Reservoir
Abstract
Weekly to bi-weekly samplings of alkaline phosphate activity (APA) as well as related environmental variables were investigated in a deep (100 m depth) subtropical reservoir during the period of 2006~2009. Within the epilimnion (depth <20 m), integrated-averaged bulk APA (1.6~95.2 nM h-1) and biomass normalized specific APA (124~1,253 nmol mgC-1 h-1) varied obviously during the investigation period. Multiple linear regression analysis indicated that in the order of importance, mixed layer depth (MLD, 3~90 m, an index of phosphate availability), picocyanobacteria abundance (0.3~3.7×1011 cells m-3), light intensity (0~102 mE m-2 d-1), and soluble reactive phosphorus concentrations (<0.02~0.15 μM P) were the four major factors that accounted for 65% of the variation of bulk APA. As to specific APA, light intensity, MLD, and temperature (17.5~32.1℃) explained 66% of its variation. Further analysis depicted that the strength of summer typhoon was the factor responsible for the inter-annual variability of bulk and specific APA. The temperature responses of bulk and specific APA in the strong-typhoon-years (2007 & 2008) were significant, while those of the weak-typhoon-years (2006 & 2009) became either lower or insignificant.
This highlighted the importance of episodic events (e.g. strong typhoon and extreme precipitation) in affecting the seasonal cycles of plankton APA in sub-tropical to tropical aquatic ecosystems.
2.1 Introduction
In phosphorus (P)-limited aquatic ecosystems, phosphate is usually in a concentration of nano molar, which is far lower than the detection limit of chemical (spectro-photometry) method (~20 nM; Parsons et al. 1984). Alternatively, extracellular enzyme activity has been adopted as an indicator for the responses of plankton communities to P-deficiency. In aquatic systems, plankton can utilize dissolved organic phosphate (DOP) as an alternative P-source to sustain their growth by producing extracellular alkaline phosphatase (i.e. APase) under P-limited conditions (Chapter 1, Fig. 1.1). Numerous researches have demonstrated that APase activity (i.e. APA) changed proportionally with the status of P-deficiency (Berman 1970, Jones 1972, Jansson 1976, Jansson et al. 1988b, Newman et al. 1994, Cao et al. 2010). This phenomenon has been named as the “induction-repression” mechanism (Jansson et al.
1988a). Accordingly, APA has been suggested as a good indicator for P-status in plankton communities (Healey & Hendzel 1980, Pettersson 1980, Istvanovics et al. 1992, Rose &
Axler 1998, Ammerman & Glover 2000, Kahlert et al. 2002, Cao et al. 2005, Guildford et
al. 2005, Gouvea et al. 2006, Strojsova & Vrba 2009).
The purposes of this study were: (1) to investigate seasonal variations of APA and its ecological relationships (controlling mechanisms) with other environmental factors, and (2) to examine summer typhoon impact on the inter-annual variations of APA, so that the regulation mechanisms of APA at seasonal and inter-annual scales could be explored. The physical measurements included temperature, light intensity, mixed layer depth; the chemical measurements included dissolved inorganic nitrogen and soluble reactive phosphorus concentrations; and the biological measurements included chlorophyll a concentrations and the abundances of picocyanobacteria and heterotrophic bacteria.
2.2 Materials and Methods 2.2.1 Study site and sampling
The study site (Feitsui Reservoir) locates in northern Taiwan (24°55’N, 121°35’E;
Fig. 2.1) with an averaged surface area of 10.24 km2 and a mean depth of 40 m. It is an artificially-build reservoir, and has served as the major source of drinking water for mega Taipei city. This reservoir (and its tributaries) has been well-protected from anthropogenic activities since 1976.
Weekly to biweekly sampling was conducted at the dam-site (depth ~100 m) from Jan 2006 to Dec 2009. The 5-Liter Go-Flo bottles were used for water sampling. The vertical sampling was conducted at 10 depths (0, 2, 5, 10, 15, 20, 30, 50, 70, and 90 m) from the surface to the near bottom manually. Conductivity-temperature-depth (CTD) and the sensors attached onto it were used to record the vertical structures of the measurements, which included temperature, photosynthetic available radiance (PAR), and chlorophyll fluorescence. Water samples stored in 20 L polycarbonate bottles were transported back to the laboratory within 2 hrs for the measurements listed below. Daily hydrographic data (reservoir water levels, water discharges, and precipitation data) were obtained from the web-site (www.feitsui.gov.tw) of Taipei Feitsui Reservoir Administration Bureau. The mixed layer depth (MLD) is defined as the depth at which its temperature is 0.5℃ lower than the surface (Levitus et al. 1982). Typhoon impact index was calculated as the product of daily maximum wind speed and daily maximum precipitation for each typhoon event.
2.2.2 Inorganic Nutrients
Water samples for nutrient analysis were filtered through 500℃ pre-combusted 47-mm GF/F filters under low (<100 mmHg) pressure. The filtrates were used for
nutrients analysis immediately. Nitrate, nitrite, and soluble reactive phosphorus (SRP) concentrations were determined following the methods of Parsons et al (1984) with a spectrophotometer (Shimadzu, UV-1201). Dissolved inorganic nitrogen (DIN) was the sum of nitrate and nitrite. In calculating dissolved N/P ratio, the SRP data below the detection limit (0.02 μM P) were not included. Total phosphorus (TP) concentrations of the surface water were obtained from Taipei Feitsui Reservoir Administration Bureau.
2.2.3 Chlorophyll a (Chl a)
Chl a concentrations were determined by the non-acidification fluorometric procedure of Welschmewer (1994). Water samples were filtered through 47-mm GF/F filters, the filters were extracted with 100% v/v acetone in the dark at -20℃ for 12~16 hrs. Fluorescence was measured using a fluorometer (Turner Designs, TD-700). Algal biomass in carbon (C) unit was determined with a C: Chl a factor of 50 gC gChl a-1 (Antia et al. 1963).
2.2.4 Abundance of picocyanobacteria (CYA) and heterotrophic bacteria (BA)
CYA and BA (<3 μm size fraction) were enumerated by flow cytometry (Partec CyFlow) quipped with a 15 mW, 488 nm argon laser, and the FloMax analysis software.CYA signals were identified by their signatures in a plot of red fluorescence versus orange fluorescence. For BA, samples were pre-diluted 10 times and then stained with SYBR Green (Molecular Probes; final concs., 2.5 μM) for 15 mins. BA signals were identified by their signatures in a plot of side scatter vs. green fluorescence. A solution of yellow-green 1 μm latex beads (~103 beads mL-1; Polysciences) was used as the size indicator. Samples were run at speeds of 800~1200 particles s-1 until ~30000 counts were made. Bacteria biomass in C unit was converted by a conversion factor of 20 fg C cell-1 (Lancelot & Billen 1984).
2.2.5 Alkaline phosphatase activity (APA)
Bulk APA was derived by a fluorometric assay using 3-0-methylfluorescein phosphate (3-0-MFP; Sigma) as the substrate (Perry 1972). Water samples were pre-filtered through a 100 μm nylon sieve to remove large zooplankton. Triplicate 6 mL subsamples were incubated with 750 μL of 3-0-MFP (final concs., 200 nM) in the dark at 25℃ for 1 hr. The fluorescence produced by the 3-0-methylfluorescein (3-0-MF;
excitation, 435 nm; emission, 520 nm) was measured with a fluorometer (Turner Designs, TD-700). Calibration was performed with 3-0-MF standard solutions (Sigma) in the range 20~200 nM. Specific APA (nmol mg C-1 h-1) was derived from the division of APA by the sum of the biomass (in C unit) of Chl a and bacteria. This was based on an assumption that phytoplankton (eukaryotic algae and cyanobacteria) and heterotrophic bacteria constituted the majority of plankton biomass.
2.2.6 Statistical analysis
The depth-integrated averages within epilimnion (upper 20 m) were acquired using trapezoidal method. This is because the signals of APA and many other measurements appeared mostly at a depth <20 m (see the Result section). Statistical analyses including linear correlation analysis, multiple linear regression analysis, one-way ANOVA, and ANCOVA were performed using the statistical software SPSS 12.0TM.
2.3 Results
2.3.1 Physical environment
The depth contour of water temperature (15.9~32.1℃; Fig. 2.2A) revealed that the water column was well-mixed during winter (Dec~Feb of the next year). Stratification occurred during the period of early Apr to late Oct. Surface water temperature (17.5~32.1℃; Fig. 2.3A) varied seasonally with the coldest and warmest temperature recorded in Feb and Aug, respectively. Values of the mixing layer depth (MLD) ranged 3~90 m, with the shallowest and the deepest MLD in summer and winter, respectively (Fig. 2.3B). Weekly light intensity (0~102 mE m-2 d-1; Fig. 2.3A) showed apparent seasonality but seemed varied more than that of surface temperature. Daily precipitation ranged from 0~406 mm (Fig. 2.3C) with lower values recorded in the dry seasons, which covered the period from Nov to Feb of the next year. Higher precipitations came from two sources, the summer evening thunder-showers and the rainfalls induced by typhoon (Fig. 2.3C).
2.3.2 Chemical variables
In the epiliminion, most of the individual SRP (<0.02~0.25 μM P; Fig. 2.2B) and depth-integrated averaged SRP (SRPDIA; <0.02~0.15 μM P; Fig. 2.4B) concentrations were under detection limit (<0.02 μM P) during the stratified seasons except several spikes recorded during post-typhoon periods (Fig. 2.3C). Higher individual SRP and SRPDIA concentrations occurred in the mixing seasons, especially in the winter. The temporal changes of the SRPDIA concentrations in the hypolimnion (20~90 m) were higher than those recorded in the epilimnion (0~20 m) (Fig. 2.4B), but with similar trends (r = +0.60, p<0.01, n=126). Strong inter-annual variation of SRPDIA in both stratified and mixing seasons was noted (Fig. 2.4B). For the stratified seasons, SRPDIA
concentrations in 2007 were very high, even higher than the winter-spring (Dec~May of
the next year) values recorded in 2008. SRPDIA concentrations in the mixing season of 2007 were most undetectable.
During the investigation period, individual dissolved inorganic nitrogen (DIN, = nitrate + nitrite; 14~87 μM N; data not shown) concentrations were always detectable, even in the epilimnion during summer (Fig. 2.4A). In term of stoichiometry, DIN seemed to be much surplus to SRP. The molar ratios of N/P ranged from 230 to 2,995 molN molP-1 with an average of 1,432±685 mol N mol P-1 (Fig. 2.4C), which was about 100-fold greater than that of the Redfield ratio (N/P = 16; Redfield 1958). Total phosphorous (TP, = SRP + DOP) in the surface water ranged from 0.16 to 2.06 μM P with an average of 0.47±0.38 μM P (Fig. 2.5). SRP constituted ca. 8% of the TP.
2.3.3 Biological measurements
Vertical contours of Chl a (data not shown) indicated that phytoplankton biomass was restricted in the upper 20 m. Epilimnic depth-integrated averaged Chl a concentrations (ChlDIA; Fig. 2.6A; range, 0.5~9.7 μg L-1; mean, 2.4±1.2 μg L-1) varied seasonally, and basically followed the trend of temperature (Table 2.1). In this system, the scale of spring bloom was less significant when compared with that of autumn, as evident by the very high ChlDIA (>9 μg L-1) recorded in Oct 2006. Vertical contour of picocyanobacteria (data not shown) indicated that they distributed mostly in the upper 20 m, and the abundance was higher in the surface water and then decreased with depth.
Epilimnic depth-integrated average of picocyanobacteria abundance (CYADIA) ranged from 0.3 to 3.7×1011 cells m-3, with an average of 1.5±0.6×1011 cells m-3 (Fig. 2.6B). The values of CYADIA were positively correlated with ChlDIA (Table 2.1), and higher CYADIA
values were generally recorded in late autumn. CYA were the most abundant species of the phytoplankton community in Feitsui Reservoir. During 2006 and 2007, CYA on
average constituted 87±12% of the total algal cell counts (Fig. 2.7). Heterotrophic bacteria abundance (BA) was high in the upper 20 m, and then dwindled with depth (data not shown). In term of seasonal variation, depth-integrated average of BA (BADIA; Fig.
2.6B; range, 0.8~4.6×1012 cells m-3; mean, 2.3±0.8×1012 cells m-3) changed positively with temperature and CYADIA (Table 2.1). A negative correlation was observed for BADIA vs. MLD.
2.3.4 Seasonal and inter-annual analyses of bulk APA
Signals of bulk alkaline phosphatase activity (APA) were only observed in the upper 20 m, and then decreased significantly with depth (Fig. 2.2C). Epilimnic depth-averaged bulk APA (APADIA; Fig. 2.6C) varied ~100X with a range of 1.6~95.2 nM h-1, and a mean of 40.4±21.5 nM h-1. In the epilimnion, values of the biomass normalized bulk APA (i.e. specific APADIA; Fig. 2.6C) varied ~10X with a range of 124~1,253 nmol mgC-1 h-1, and a mean of 391±207 nmol mgC-1 h-1.
In term of seasonal variation, values of bulk APADIA were positively correlated with of the changes of temperature, light intensity, ChlDIA, CYADIA, and BADIA; values of bulk APADIA were also negatively correlated with MLD, DINDIA, and SRPDIA
concentrations (Table 2.1). A closer examination indicated that the temperature response of bulk APADIA of each year were different (Fig. 2.8). The slope of bulk APADIA vs.
temperature of 2009 was insignificant, while the slopes of the other 3 years were significant with values ranged 0.08~0.14. The slope of 2008 was significantly different from those of 2006 and 2007 (ANCOVA, p<0.05), while the latter two were not different from each other (ANCOVA, p>0.05). The relationships of specific APADIA to other variables were the same as those of bulk APADIA (Table 2.1).
Results of the multiple linear regression analysis indicated that 65% of the bulk
APADIA variability could be explained by the combination of light intensity, MLD, DINDIA, SRPDIA, and CYADIA (Table 2.2). The relative importance (standardized regression coefficient, i.e. Beta weight) of these independent variables on bulk APADIA
in order was -0.40 for MLD, 0.30 for CYADIA, -0.22 for DINDIA, 0.21 for light intensity, and -0.15 for SRPDIA. The same procedure was performed on the data of each single year. The results showed apparent inter-annual variability of the independent variables in explaining the variation of bulk APADIA. In 2006, ChlDIA and BADIA were the best factors for the changes of bulk APADIA. In 2007, the best combination switched to MLD only. In 2008, MLD and ChlDIA were responsible for 72% of the variation. In 2009, light intensity and CYADIA explained 72% of the variation. Basically the analysis results of specific APADIA were the same as those of bulk APADIA. For the pooled data set, light (Beta = 0.45) and MLD (Beta = -0.41) were the two factors affecting the variability of specific APADIA most.
2.3.5 Typhoon impact
During the investigation period, a total of 18 typhoons had swept through the study
During the investigation period, a total of 18 typhoons had swept through the study