US Long-Term Ecological Research Network

Microbial Observatory at North Temperate Lakes LTER High-resolution temporal and spatial dynamics of microbial community structure in freshwater bog lakes 2005 - 2009 original format

Abstract
The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Core Areas
Dataset ID
349
Date Range
-
Methods
Protocol available in methods section of: http://msphere.asm.org/content/2/3/e00169-17
Prior to collection, water temperature and dissolved oxygen concentrations are measured using a YSI 550a. The ranges of the epilimnion and hypolimnion are determined based on the location of the thermocline (where temperature/oxygen is changing the fastest). The two layers are collected separately in 1 meter increments using an integrated water column sampler. Water samples are taken back to the lab, shaken thoroughly, and filtered via peristaltic pump through 0.22 micron filters (Pall Supor). Filters are temporarily stored at -20C after collection and then transferred to -80C after transport on dry ice from Trout Lake Station to UW-Madison. Nutrient samples are collected bi-weekly following standard LTER protocols. DNA is extracted from filters using a FASTDNA SpinKit for Soil with minor modifications. (In cases of low yield or specialized sequencing methods, a phenol-chloroform extraction is used instead). The protocol for sequencing and analysis of data varies by year and by sub-project.
Version Number
4

Microbial Observatory at North Temperate Lakes LTER Spatial and temporal cyanobacterial population dynamics in Lake Mendota 2009 - 2011

Abstract
Toxic cyanobacterial blooms threaten freshwaters worldwide but have proven difficult to predict because the mechanisms of bloom formation and toxin production are unknown, especially on weekly time scales. Water quality management continues to focus on aggregated metrics, such as chlorophyll and total nutrients, which may not be sufficient to explain complex community changes and functions such as toxin production. For example, nitrogen (N) speciation and cycling play an important role, on daily time scales, in shaping cyanobacterial communities because declining N has been shown to select for N fixers. In addition, subsequent N pulses from N<sub>2</sub> fixation may stimulate and sustain toxic cyanobacterial growth. Herein, we describe how rapid early summer declines in N followed by bursts of N fixation have shaped cyanobacterial communities in a eutrophic lake (Lake Mendota, Wisconsin, USA), possibly driving toxic <em>Microcystis</em> blooms throughout the growing season. On weekly time scales in 2010 and *2011, we monitored the cyanobacterial community in a eutrophic lake using the phycocyanin intergenic spacer (PC-IGS) region to determine population dynamics. In parallel, we measured microcystin concentrations, N<sub>2</sub> fixation rates, and potential environmental drivers that contribute to structuring the community.
Core Areas
Dataset ID
299
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Field sample collection and processingAt each location, temperature, dissolved oxygen (DO), and pH were collected at 1 m increments from the surface to the maximum depth (YSI 556MPS). Photic zone depth was defined at 1percent of photosynthetically active radiation (PAR) as measured using a PAR sensor (LiCor 192SA). Integrated photic zone samples were then collected using a weighted 2-inch diameter polypropylene tube. Samples for DNA, nutrients, toxins, and pigment analyses were collected in acid-washed, sterile bottles, (rinsed three times with in situ water before collection) and stored on ice until further processing.Once transported back to the lab, samples were immediately processed. For dissolved reactive phosphorus (DRP), total dissolved phosphorus (TDP), total dissolved nitrogen (TDN), nitrate, and nitrite, 100 mL of water was filtered through a Whatman glass fiber filter (GForF) and frozen at -20 degreeC. For TP and total nitrogen (TN), HCl was added to 100mL of sample to a final concentration of 0.1percent and stored at -20 degreeC. Ammonium samples were immediately measured to avoid oxidation during freezing. Chlorophyll-a and phycocyanin samples were collected onto GForF filters and stored in black tubes at -20 degreeC. For community analysis (DNA), samples were filtered onto 0.2 &micro;m polyethersulfone membrane filters (Supor-200; Pall Corporation) and frozen at -20 degreeC until extraction. 20 mL of unfiltered water was preserved in formalin (3percent final concentration) and stored at room temperature in the dark for microscopy. An additional 50 mL of unfiltered water was stored at -20 degreeC for toxin analysis.Analytical measurementsDRP was measured by the ascorbic acid-molybdenum blue method 4500 P E (Greenberg et al. 1992). Ammonium was measured spectrophotometrically (Solórzano 1969). Nitrate and nitrite were measured individually using high-performance liquid chromatography (HPLC) (Flowers et al. 2009). TPorTDP and TNorTDN were digested as previously described (White et al. 2010), prior to analysis as for DRP and nitrate. For TDN and TN, the resulting solution was oxidized completely to nitrate and was measured via HPLC as above. Nitrate, nitrite, and ammonium were summed and reported as dissolved inorganic nitrogen (DIN).Phycocyanin was extracted in 20 mM sodium acetate buffer (pH 5.5) following three freeze-thaw cycles at -20 &ordm;C and on ice, respectively. The extract was centrifuged and then measured spectrophotometrically at 620 nm with correction at 650 nm (Demarsac and Houmard 1988). Chlorophyll-a (Chl-a) was extracted overnight at -20 &ordm;C in 90percent acetone and then measured spectrophotometrically with acid correction (Tett et al. 1975).For toxin analysis, whole water samples were lyophilized, resuspended in 5percent acetic acid, separated by solid phase extraction (SPE; Bond Elut C18 column, Varian), and eluted in 50percent methanol as previously described (Harada et al. 1988). Microcystin (MC) variants of leucine (L), arginine (R), and tyrosine (Y) were detected and quantified at the Wisconsin State Lab of Hygiene (SLOH) using liquid chromatography electrospray ionization tandem mass spectroscopy (API 3200, MSorMS) after separation by HPLC (Eaglesham et al. 1999). We report only MCLR concentrations since MCYR and MCRR were near the limit of quantification for the sampling period (0.01 &micro;g L-1).In situ N2 fixation measurementsN2 fixation rates were measured, with some modifications, following the acetylene reduction assay (Stewart et al. 1967). A fresh batch of acetylene was generated each day before sampling by combing 1 g of calcium carbide (Sigma Aldrich 270296) with 100 mL ddH2O. Following sample collection, 1 L of water was concentrated by gentle filtration onto a 47 mm GForF filter in the field. The filter was then gently washed into a 25 mL serum bottle using the lake water filtrate (final volumes 10 mL aqueous, 15 mL gas). Samples were spiked with 1 mL of acetylene gas and incubated in situ for two hours. The assay was terminated with 5percent final concentration trichloracetic acid and serum bottles were transported back to the lab. For each sampling period, rates were controlled and corrected for using a series of the following incubated acetylene blanks: 1) 1 mL of acetylene in filtrate alone, 2) 1 mL of acetylene in a killed sample, and 3) 1 mL of acetylene in ddH2O. Ethylene formed was measured by a gas chromatograph (GC; Shimadzu GC-8A) equipped with a flame ionization detector (FID), Porapak N column (80or100 mesh, 1or8OD x 6), and integrator (Hewlett Packard 3396) with N2 as the carrier gas (25 mL min-1 flow rate). Molar N2 fixation rates were estimated using a 1:4 ratio of N2 fixed to ethylene formed (Jensen and Cox 1983). All N2 fixation values are reported as integrated photic zone rates of &micro;g N L-1 hr-1.DNA extraction and processing of PC-IGS fragmentDNA was extracted from frozen filters using a xanthogenate-phenol-chloroform protocol previously described (Miller and McMahon 2011). For amplification of the phycocyanin intergenic spacer (PC-IGS) region, we used primers PCalphaR (5-CCAGTACCACCAGCAACTAA-3) and PCbetaF (5-GGCTGCTTGTTTACGCGACA-3, 6-FAM-labelled) and PCR conditions that were previously described (Neilan et al. 1995). Briefly, each 50 &micro;l reaction mixture contained 5 &micro;l of 10X buffer (Promega, Madison, WI), 2.5 &micro;l of dNTPs (5 mM), 2 &micro;l of forward and reverse primers (10 &micro;M), 2 &micro;l of template DNA, and 0.5 &micro;l of Taq DNA polymerase (5 U &micro;l-1). Following precipitation with ammonium acetate and isopropanol, the DNA pellet was resuspended in ddH2O and digested for 2 hrs at 37 &ordm;C using the MspI restriction enzyme, BSA, and Buffer B (Promega, Madison, WI). The digested product was precipitated and then resuspended in 20 &micro;L of ddH2O. 2 &micro;L of final product was combined with 10 &micro;L of formamide and 0.4 &micro;L of a custom carboxy-x-rhodamine (ROX) size standard (BioVentures, Inc).Cyanobacterial PC-IGS community fingerprinting and cell countsWe analyzed the cyanobacterial community using an automated phycocyanin intergenic spacer analysis (APISA) similar to the automated ribosomal intergenic spacer analysis (ARISA) previously described (Yannarell et al. 2003). Briefly, this cyanobacterial-specific analysis exploits the variable PC-IGS region of the phycocyanin operon (Neilan et al. 1995). Following MspI digestion, the variable lengths of the PC-IGS fragment can be used to identify subgenus level taxonomic units of the larger cyanobacterial community (Miller and McMahon 2011). The MspI fragments were sized using denaturing capillary electrophoresis (ABI 3730xl DNA Analyzer; University of Wisconsin Biotechnology Center (UWBC)). For each sample, triplicate electropherogram profiles were analyzed using GeneMarker&reg; (SoftGenetics) software v 1.5. In addition, a script developed in the R Statistics Environment was used to distinguish potential peaks from baseline noise (Jones and McMahon 2009, Jones et al. 2012). Relative abundance data output from this script were created using the relative proportion of fluorescence each peak height contributed per sample. Aligned, overlapping peaks were binned into subgenus taxonomic units (Miller and McMahon 2011). These taxa were named based on the genus and base pair length of the PC-IGS fragment identified (e.g. For Mic215, Mic = Microcystis and 215 = 215 base pair fragment). Fragment lengths were matched to an in silico digested database of PC-IGS sequences using the Phylogenetic Assignment Tool (https:ororsecure.limnology.wisc.eduortrflpor).The NTL-LTER program collects biweekly phytoplankton samples between April and September for cell counts and detailed descriptions of the field and laboratory protocols are available online at http:ororlter.limnology.wisc.edu. When indicated, biomass has been converted to mg L-1 using the biovolume calculated during the cell count process and assuming a density equivalent to water.
Version Number
22

Microbial Observatory at North Temperate Lakes LTER Time series of bacterial community dynamics in Lake Mendota 2000 - 2009

Abstract
With an unprecedented decade-long time series from a temperate eutrophic lake, we analyzed bacterial and environmental co-occurrence networks to gain insight into seasonal dynamics at the community level. We found that (1) bacterial co-occurrence networks were non-random, (2) season explained the network complexity and (3) co-occurrence network complexity was negatively correlated with the underlying community diversity across different seasons. Network complexity was not related to the variance of associated environmental factors. Temperature and productivity may drive changes in diversity across seasons in temperate aquatic systems, much as they control diversity across latitude. While the implications of bacterioplankton network structure on ecosystem function are still largely unknown, network analysis, in conjunction with traditional multivariate techniques, continues to increase our understanding of bacterioplankton temporal dynamics.
Core Areas
Dataset ID
298
Date Range
Maintenance
completed
Metadata Provider
Methods
Surface water samples were collected from Lake Mendota, WI, USA, and analyzed by automated ribosomal intergenic spacer analysis as described previously (Shade et al., 2007). From 2000 to 2009, a total of 34 spring, 53 summer and 34 autumn observations were made. Thirty-two environmental variables were collected at the same location by the North Temperate Lakes Long Term Ecological Research program (lter.limnology.wisc.edu)
Short Name
MEMOTY
Version Number
18

Microbial Observatory at North Temperate Lakes LTER epilimnion versus hypolimnion transplant 2005

Abstract
Lake mixing disrupts chemical and physical gradients that structure bacterial communities. A transplant experiment was designed to investigate the influence of post-mixing environmental conditions and biotic interactions on bacterial community composition. The experimental design was 3 &times; 2 factorial, where water was incubated from three different sources (epilimnion, hypolimnion, and mixed epilimnion and hypolimnion) at two different locations in the water column (epilimnion or hypolimnion). Three replicate mesocosms of each treatment were removed every day for 5 days for bacterial community profiling, assessed by automated ribosomal intergenic spacer analysis. There were significant treatment effects observed, and temperature was the strongest measured driver of community change (<em>r </em>= &minus;0.66). Epilimnion-incubated communities changed more than hypolimnion-incubated. Across all treatments, we classified generalist, layer-preferential and layer-specialist populations based on occurrence patterns. Most classified populations were generalists that occurred in both strata, suggesting that communities were robust to mixing. In a network analysis of the mixed-inocula treatments, there was correlative evidence of inter-population biotic interactions, where many of these interactions involved generalists. These results reveal differential responses of bacterial populations to lake mixing and highlight the role of generalist taxa in structuring an emergent community-level response.
Core Areas
Dataset ID
297
Date Range
LTER Keywords
Maintenance
completed
Metadata Provider
Short Name
TRNS07
Version Number
15

Microbial Observatory at North Temperate Lakes LTER Three Bog 2005 study

Abstract
Multiple forces structure natural microbial communities, but the relative roles and interactions of these drivers are poorly understood. Gradients of physical and chemical parameters can be especially influential. In traditional ecological theory, variability in environmental conditions across space and time represents habitat heterogeneity, which may shape communities. Here we used aquatic microbial communities as a model to investigate the relationship between habitat heterogeneity and community composition and dynamics. We defined spatial habitat heterogeneity as vertical temperature and dissolved oxygen (DO) gradients in the water column, and temporal habitat heterogeneity as variation throughout the open-water season in these environmental parameters. Seasonal lake mixing events contribute to temporal habitat heterogeneity by destroying and re-creating these gradients. Because of this, we selected three lakes along a range of annual mixing frequency (polymictic, dimictic, meromictic) for our study. We found that bacterial community composition (BCC) was distinct between the epilimnion and hypolimnion within stratified lakes, and also more variable within the epilimnia through time. We found stark differences in patterns of epilimnion and hypolimnion dynamics over time and across lakes, suggesting that specific drivers have distinct relative importance for each community.
Core Areas
Dataset ID
295
Date Range
-
LTER Keywords
Maintenance
completed
Metadata Provider
Methods
The BCC of three small northern Wisconsin lakes, CB (polymictic, maximum depth 2.5 m), TB (dimictic, maximum depth 7 m) and MA (meromictic, maximum depth 21.5 m), were sampled weekly during the open-water period of 2005 (late May to early November). These lakes were chosen because of their shared dystrophy, acidity, similar surface area (range 0.6&ndash;1.2 ha), comparable physicalorchemical characteristics, proximity to one another and range of annual of mixing frequencies. Samples were collected over the deepest point of each lake. All lakes were sampled on the same day each week.Temperature and DO measurements were observed for every sample date using YSI model 58 dissolved oxygen meter (Yellow Springs, OH) calibrated at each sample date as per manufacturer s instruction. Trout Bog and MA profiles were observed at every metre and CB profiles were observed at every half metre. Integrated water column samples were collected for each thermal layer. Thermal layer boundaries were determined based on temperature profiles. The top of the hypolimnion was determined to be where the temperature decreased by 1.5&ndash;2.0degreeC over 0.5 m or less. In polymictic CB, the epilimnion was consistently sampled at 0.0&ndash;1.0 m, and the hypolimnion at 1.0&ndash;2.0 m; these depths were based on thermal profiles of CB s weak stratification (rate of change of 0.5degreeC m&minus;1 or greater), as observed in instrumented buoy temperature profiles available from the Global Lakes Ecological Observatory Network database (GLEON, http:ororwww.gleon.org). According to buoy data temperature profiles, CB mixed a minimum of nine times over the sampling season in 2005.Bacterial cells were immediately recovered from 100 to 250 ml of lake sample water by filtration onto a 0.2 μm polyestersulfone filter (Pall, New York, NY), and stored at &minus;80degreeC until further processing.Mean difference in DO and temperature for each layer was calculated by averaging the profile observations included in the layer of interest for each sample date, and then subtracting the average of the hypolimnion profile from the epilimnion. These differences were then averaged over the entire sampling period when a global mean was desired.Additional physical and chemical data for TB and CB were provided by the North Temperate Lakes Long-term Ecological Research (NTL-LTER) and the Center for Limnology at University of Wisconsin-Madison.
NTL Keyword
Short Name
3BOG05
Version Number
18

Microbial Observatory at North Temperate Lakes LTER North Sparkling Bog Experiment 2007 - 2009

Abstract
For lake microbes, water column mixing acts as a disturbance because it homogenizes thermal and chemical gradients known to define the distributions of microbial taxa. Our first objective was to isolate hypothesized drivers of lake bacterial response to water column mixing. To accomplish this, we designed an enclosure experiment with three treatments to independently test key biogeochemical changes induced by mixing: oxygen addition to the hypolimnion, nutrient addition to the epilimnion, and full water column mixing. We used molecular fingerprinting to observe bacterial community dynamics in the treatment and control enclosures, and in ambient lake water. We found that oxygen and nutrient amendments simulated the physical-chemical water column environment following mixing and resulted in similar bacterial communities to the mixing treatment, affirming that these were important drivers of community change. These results demonstrate that specific environmental changes can replicate broad disturbance effects on microbial communities. Our second objective was to characterize bacterial community stability by quantifying community resistance, recovery and resilience to an episodic disturbance. The communities in the nutrient and oxygen amendments changed quickly (had low resistance), but generally matched the control composition by the 10th day after treatment, exhibiting resilience. These results imply that aquatic bacterial assemblages are generally stable in the face of disturbance.
Dataset ID
294
Date Range
-
Metadata Provider
Methods
Experimental designThe experiment was conducted from 16 to 26 June 2008. In the first treatment, oxygen was added to the hypolimnion. In the second, nutrients were added to the epilimnion. The third treatment simulated a mixing event (overturn). There also was a control enclosure with no treatment and sampling of the ambient lake water. Throughout this manuscript, we refer to these as Oxygen, Nutrient, Mix, Control and Ambient.Twelve limnocorrals were constructed as enclosures for the experiment. Each limnocorral was cylindrical and extended vertically from the surface of the lake to the sediment (approximately 4 m). The total volume was approximately 5050 l. Details of limnocorral construction are provided in online Supporting Information.The limnocorrals were deployed on 15 June 2008 to allow the sediment and water column to stabilize before treatment on 16 June 2008. The limnocorrals were deployed in a random spatial arrangement throughout the lake, at a maximum depth of 3.25 to 3.5 m. Replicates from each treatment were instrumented with a chain of HOBO temperature sensors (Onset), and one replicate from each had a self-logging DO sonde (Yellow Springs Incorporated) in the hypolimnion (3 m depth). More thermistors were deployed in the Oxygen and Mix treatments because thermal stratification was important for evaluating success of these treatments.For the Mix treatment, a 60 cm flat disk was raised and lowered between 3.5 m depth and the lake surface. Holes were drilled through the disk surface to increase turbulence (Sanford, 1997; Regel et al., 2004). A brick was tied underneath the disk to maintain stability. We manually oscillated the disk every 10 min for 1 h and then, after a 1 h break, continued for an additional hour. Temperature and DO profiles were monitored within the limnocorral with a hand-held probe to track mixing progress.The goal of the Oxygen treatment was to aerate the hypolimnion water without allowing it to mix with the epilimnion. This treatment was achieved by pumping hypolimnion water from the bottom of the limnocorral into an external cooler where the water was aerated with bubble diffusers, and then returned to the bottom of the limnocorral (Fig. S1). Valves on a compressed air cylinder were used to control the delivery of air to the coolers. One cooler was maintained for each replicate limnocorral. Thermally insulated tubing was used to transport water. A thermistor was deployed in each cooler to ensure ambient hypolimnion temperature was maintained. The water was removed and returned using two linear diffusers that were 0.6 m in length, spanning a depth range of approximately 2.5&ndash;3.1 m within the hypolimnion. The diffusers faced inward with 0.5 m fixed distance between them, retained by a plastic divider. This treatment was applied continuously over 3 h, until DO concentrations increased.The Nutrient treatment was achieved by adding ammonium chloride (NH4Cl) and potassium phosphate monobasic (KH2PO4) as N and P sources. These compounds were chosen because they are commonly bioavailable sources of nutrients. P was added to the epilimnion to achieve a final concentration of 3 micro g P l&minus;1, which was approximately the average concentration expected in the mixed water column. This value was based on nutrient analyses from integrated water collected on 9 June 2008 in North Sparkling Bog, a week prior to experiment start. Similarly, N was added to achieve a final concentration of 70 &micro;g N l&minus;1. The limnocorral s epilimnion volume (0&ndash;2 m integrated depth) was calculated to be 2520 l, and we used the molar mass to determine the amount of each nutrient added to the epilimnion to achieve the expected mixed concentration. Dry chemicals were dissolved into to 500 ml of surface water from each limnocorral, and then added into each separately. Rationale for directly manipulating only one layer in the Oxygen and Nutrient treatments is given in the online Supporting Information.The Control limnocorrals were left undisturbed. To prevent mixing during equipment removal, all tubing was left inside the limnocorrals until the experiment ended.
Short Name
NB0789
Version Number
13

Microbial Observatory at North Temperate Lakes LTER Mendota Six Years Bacterial Community Composition 2000 - 2005

Abstract
We investigated patterns of intra- and interannual change in pelagic bacterial community composition (BCC), assessed using automated ribosomal intergenic spacer analysis) over six years in eutrophic Lake Mendota, Wisconsin. A regular phenology was repeated across years, implying that freshwater bacterial communities are more predictable in their dynamics than previously thought. Seasonal events, such as water column mixing andtrends in water temperature, were most strongly related to BCC variation. Communities became progressively less similar across years between the months of May and September, when the lake was thermally stratified. Dissolved oxygen and nitrate + nitrite concentrations were highly correlated to BCC change within and across seasons. The relationship between BCC and seasonal drivers suggests that trajectories of community change observed over long time series will reflect large-scale climate variation.
Core Areas
Dataset ID
293
Data Sources
Date Range
-
Maintenance
complete
Metadata Provider
Methods
Sampling Frequency: bi-weekly during ice-off from 2000 to 2005Total number of observations: 82Number of sites: 1 site over the deep hole of the lake (Lake Mendota, 89degree 24 W long, 43degree 06 N lat)Sampling techniques: integrated 0-12 mNomenclature:Lake name is ME. Sample IDs are ME-date with date = MM-DD-YY.DNA extraction protocol: FastPrep DNA extraction kitBinning protocol: Manual in GeneScanorGenotyperCapillary Instrument (from Biotech Center): ABI 3700PCR DNA standardization protocol: By volume of lake water filteredPCR thermocycler protocol:RISA30x protocol: 2 min 94C, [35s. Denature 94C, 45 s. Annealing 55C, 2 min Extension 72C (rep 30x)], 2 min extension 72C.Analyses performed other than ARISA:Additional comments:Raw ABI files are in two batchesBatch 1: Duplicate samples from 2000-2004 with nomenclature basically the same as the sample IDs plus the replicate number, such as ME 2-28-02 rep1. Note that the month is not 2-digit unless it has two digits.Batch 2: Duplicate samples from 2000-2005 with nomenclature as ME-date where date is DD-month-YY and the replicate number, such as ME 27Apr00 rep1.NOTE: We are not sure which samples were used for the final analysis. They must have been a blend of the two batches. Contact Ashley Shade (ashley17061atgmail.com) for clarification if needed.
Short Name
ME0005
Version Number
17

Microbial Observatory at North Temperate Lakes LTER Six Bogs Microbial Communities 2009

Abstract
Population dynamics are influenced by drivers acting from outside and from within an ecosystem. Extrinsic forces operating over broad spatial scales can impart synchronous behavior to separate populations, while internal, system-specific drivers often lead to idiosyncratic behavior. Here we demonstrate synchrony in community-level dynamics among phytoplankton and bacteria in six north temperate humic lakes. The influence of regional meteorological factors explained much of the temporal variability in the phytoplankton community, and resulted in synchronous patterns of community change among lakes. Bacterial dynamics, in contrast, were driven by system-specific interactions with phytoplankton. Despite the importance of intrinsic factors for determining bacterial community composition and dynamics, we demonstrated that biological interactions transmitted the signal of the regional extrinsic drivers to the bacterial communities, ultimately resulting in synchronous community phenologies for bacterioplankton communities as well. This demonstrates how linkages between the components of a complex biological system can work to simplify the dynamics of the system and implies that it may be possible to predict the behavior of microbial communities responsible for important biogeochemical services in the landscape.
Core Areas
Dataset ID
292
Date Range
-
Metadata Provider
Methods
See protocols of North Temperate Lakes Microbial ObservatorySampling Techniques: Integrated epilimnionDNA extraction protocol: FastPrep DNA extraction kitBinning protocol: ARISA_v4.2.RCapillary Instrument (from Biotech Center): ABI 3730xLPCR DNA standardization protocol: By volume of DNA extract (1 ul per reaction)PCR thermocycler protocol: RISAASH protocol: 2 min at 94 C, [30 s at 94, 45 s at 55, 1 m at 72, (Repeat 29X)], 1 m at 72, Hold at 4
NTL Keyword
Short Name
6BOG03
Version Number
21

Microbial Obesrvatory at North Temperate Lakes LTER Microbial Planktonic Respiration in Lakes at North Temperate Lakes LTER 2001

Abstract
Respiration of total plankton passing a 70 micron mesh, and bacteria passing a 1 micron mesh, calculated from loss of oxygen in lake water incubated at in situ temperatures. Oxygen concentration was determined using the Winkler reaction with azide modification. Final product concentration determined via spectrometry or titration with sodium thiosulfate. Titrations that may have overrun the endpoint were not included. The following equation for calculation of dissolved oxygen concentration from titration of Winkler end product with thiosulfate (from Wetzel, R. G. and G. E. Likens. 1991. Limnological Analyses, 2nd ed. Springer-Verlag, New York). Thiosulfate with a molarity of 0.20 N was used for all titrations. mg O2 L-1 = (ml titrant)*(molarity of thiosulfate)*(8000)/((ml of sample titrated)*((ml of bottle -3)/(ml of bottle))). The following equation is for calculation of dissolved oxygen calculation from spectophotometric analysis of Winkler reaction end product (from Roland, F., N. F. Caraco, J. J. Cole. 1999. Rapid and precise determination of dissolved organic oxygen by spectrophotometry: Evaluation of interference from color and turbidity. Limnol. Oceanogr. 44(4):1148-1154). mg O2 L-1 = absorbance at 430 nm (in units of cm-1) * 8.1-0.41 Sampling Frequency: fortnightly during ice-free season - every 6 weeks during ice-covered season Number of sites: 4
Dataset ID
53
Date Range
-
LTER Keywords
Maintenance
completed
Metadata Provider
Methods
Respiration of total plankton passing a 70 micron mesh, and bacteria passing a 1 micron mesh, calculated from loss of oxygen in lake water incubated at in situ temperatures. Oxygen concentration was determined using the Winkler reaction with azide modification. Final product concentration determined via spectrometry or titration with sodium thiosulfate. Titrations that may have overrun the endpoint were not included. The following equation for calculation of dissolved oxygen concentration from titration of Winkler end product with thiosulfate (from Wetzel, R. G. and G. E. Likens. 1991. Limnological Analyses, 2nd ed. Springer-Verlag, New York). Thiosulfate with a molarity of 0.20 N was used for all titrations. mg O2 L-1 = (ml titrant)*(molarity of thiosulfate)*(8000)/((ml of sample titrated)*((ml of bottle -3)/(ml of bottle))). The following equation is for calculation of dissolved oxygen calculation from spectophotometric analysis of Winkler reaction end product (from Roland, F., N. F. Caraco, J. J. Cole. 1999. Rapid and precise determination of dissolved organic oxygen by spectrophotometry: Evaluation of interference from color and turbidity. Limnol. Oceanogr. 44(4):1148-1154). mg O2 L-1 = absorbance at 430 nm (in units of cm-1) * 8.1-0.41 Sampling Frequency: fortnightly during ice-free season - every 6 weeks during ice-covered season Number of sites: 4
Short Name
MOPR1
Version Number
4

Microbial Observatory at North Temperate Lakes LTER Microbial Community Composition in Lakes - Taxonomic/Ecological characteristics of the sample at North Temperate Lakes LTER 2000 - 2007

Abstract
Microbial community composition is inferred by a combination of automated ribosomal intergenic spacer analysis (ARISA) and PCR-generated clone library analysis. Clone libraries include both the 16S rRNA gene and the 16S-23S ribosomal intergenic spacer fragment. Phylogenetic assignments for individual ARISA fragments are obtained by comparing the ARISA fragment length from each clone to all of the profiles stored in our database. We have analyzed over 3900 clones obtained from 41 lakes that represent the range of trophic types found in temperate landscapes. Querying by a combination of taxonomic and ecological characteristics of the sample allows the user to retrieve sample information [sample IDs, sample dates, lake information (region, type, size, depth) and physical/chemical data (water temperature, clarity, pH, DOC, SUVA, TN, TP, nitrates/nitrites)] and clone information [clone IDs, sequence data, and characteristics of the sequence (length, chimera status, accession number, taxonomic affiliation)]. The data can be filtered by ecological characteristics of the sample [lake name, sample date, lake information (region, type, size, depth)] and taxonomic characteristics of the community members [clone ID, ARISA fragment length (raw or binned), and/or taxonomic characteristics (Phylum and Phylum-Class)]. The output can include links to individual sample records, which contain links to the taxonomic composition of the sample inferred by dynamically matching clones to ARISA fragments in the individual sample. The output can also include links to clone records directly (though this creates a very large number of lines in the output and is not recommended). Project ID&#39;s 30 Lakes - Survey of 30 lakes in northern and southern Wisconsin. June, August and October, 2002. Lake Characteristics. CB0000 - Time series monitoring microbial community composition in Crystal Bog. 2000-2002. CBX_02 - Food web manipulation experiment in Crystal Bog. Summer, 2002.
Dataset ID
76
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Microbial community composition is inferred by a combination of automated ribosomal intergenic spacer analysis (ARISA) and PCR-generated clone library analysis. Clone libraries include both the 16S rRNA gene and the 16S-23S ribosomal intergenic spacer fragment. Phylogenetic assignments for individual ARISA fragments are obtained by comparing the ARISA fragment length from each clone to all of the profiles stored in our database. We have analyzed over 3900 clones obtained from 41 lakes that represent the range of trophic types found in temperate landscapes. Querying by a combination of taxonomic and ecological characteristics of the sample allows the user to retrieve sample information [sample IDs, sample dates, lake information (region, type, size, depth) and physical/chemical data (water temperature, clarity, pH, DOC, SUVA, TN, TP, nitrates/nitrites)] and clone information [clone IDs, sequence data, and characteristics of the sequence (length, chimera status, accession number, taxonomic affiliation)]. The data can be filtered by ecological characteristics of the sample [lake name, sample date, lake information (region, type, size, depth)] and taxonomic characteristics of the community members [clone ID, ARISA fragment length (raw or binned), and/or taxonomic characteristics (Phylum and Phylum-Class)]. The output can include links to individual sample records, which contain links to the taxonomic composition of the sample inferred by dynamically matching clones to ARISA fragments in the individual sample. The output can also include links to clone records directly (though this creates a very large number of lines in the output and is not recommended). Project ID s 30 Lakes - Survey of 30 lakes in northern and southern Wisconsin. June, August and October, 2002. See http://microbes.limnology.wisc.edu/lakes30.html. Lake Characteristics. CB0000 - Time series monitoring microbial community composition in Crystal Bog. 2000-2002. CBX_02 - Food web manipulation experiment in Crystal Bog. Summer, 2002.
NTL Keyword
Short Name
MOCLON
Version Number
3
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