US Long-Term Ecological Research Network

Response of Phytoplankton Communities to Disturbance and Drought

This research investigates the sensitivity of phytoplankton communities to historical droughts and terrestrial disturbances in northern Wisconsin. Questions that motivate me include: To what extent have disturbances, namely clear-cut logging and forest fire, interacted with droughts over time to influence phytoplankton communities in northern Wisconsin lakes? Did phytoplankton dynamics depend upon site-specific characteristics of the lake, namely the lake's landscape position?  To answer these questions, I have collected sediment cores from six lakes situated along a gradient of landscape position...

Microbial Observatory at North Temperate Lakes LTER Phytoplankton and Protoplankton 2000

Abstract
Phytoplankton and Protoplankton collected in North Temparate Lakes Sampling Frequency: monthly Number of sites: 1. Graham JM, Kent AD, Lauster GH, Yannarell AC, Graham LE, Triplett EW. 2004. Seasonal dynamics of phytoplankton and planktonic protozoan communities in a north temperate humic lake: diversity in a dinoflagellate dominated system. Microbial Ecology. 48:528-540.
Core Areas
Dataset ID
52
Data Sources
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Sample Collection and Processing. For phytoplankton and planktonic protozoan community analyses, whole water samples of 500–1000 mL were collected from Crystal Bog in the fall of 1999 (September, October, November), the winter of 2000 (January and February), and biweekly throughout the ice-free period for 2000 (March 26 through November 17). Crystal Bog was sampled over the entire 2-m water column at the point of maximum depth using an integrated water column sampler consisting of a length of PVC pipe equipped with a ball-joint valve. A single sample from a station at the maximum depth of this small bog was collected on each sample date. Samples were preserved with 25percent glutaraldehyde to a final concentration of 2percent in each sample bottle. Samples were stored in the dark in a refrigerator until counted.On the same collection dates throughout the ice-free period of the year 2000, water samples for bacterial community fingerprint analysis were obtained from Crystal Bog and filtered through autoclaved 10-lm nylon mesh screening (Spectrum) to remove eukaryotic cells. Samples were cooled on ice for transport back to the Trout Lake field station. Water samples were filter-concentrated in aliquots of 250 or 500 mL onto sterile 0.2- lm filters (Supor-200, Gelman). Filters were then placed in cryovials, frozen in liquid nitrogen, and stored at 80 C until DNA could be extracted with a FastPrep DNA purification kit (BIO 101). In addition, 250 mL of unfiltered water was also preserved in 2percent glutaraldehyde for later enumeration of bacterial cells. Identification and Enumeration of Algae and Protozoa. Twenty-mL aliquots of preserved sample were J.M. GRAHAM ET AL.: DIVERSITY IN A HUMIC LAKE 529 settled in chambers for 48 h prior to counting. Counting was performed on an Olympus IX-50 inverted microscope at 200 and 400. Algae and protozoa were identified and counted in one half the surface area of the settling chamber, equivalent to 10 mL of sample. The remaining half of the chamber was scanned at 200· for additional counts of larger phytoplankton and protozoan species present at low densities. Identifications of phytoplankton were based on Smith [39] and Prescott [30] plus additional specialized texts for dinoflagellates [29], desmids [7, 31–34], and chrysophytes [4]. Identifications of protozoa were based on Kudo [21], Patterson [24], and particularly Foissner and Berger [10], together with their associated taxonomic volumes [11]. Identifications were made to species where possible. Abundance of each species was expressed as number of cells, colonies, or filaments per liter. For mean cell, colony, or filament volume estimates, at least 10 individuals (when available) were measured for size with a calibrated ocular micrometer on each sample date, and volumes were calculated based on standard geometric formulas [14]. Novel geometric formulas were devised for some taxa, for example, those shaped like a cone of elliptic cross section or a cylindrical filament wound into a coiled spring. Biovolume of each species was the product of the countorliter and the mean volume. Bacterial Abundance Analysis. Bacterial abundance was determined by staining 2 mL of unfiltered preserved water from Crystal Bog with 40, 60-diamidino- 2-phenylindole (DAPI) according to the procedures given in Porter and Feig [28]. The stained bacterial cells were filtered onto black 25-mm 0.2-lm pore size PCTE filters, mounted on slides, and examined under oil immersion with a Nikon Diaphot epifluorescence microscope. The numbers of bacterial cells were then counted in 10 random Whipple grids per slide on two perpendicular transects. Additional information on bacterial enumeration is available in the on-line methods manual for the Microbial Observatory for the NTLLTER site (http:orormicrobes.limnology.wisc.eduormethods. htm).Community Fingerprint Analysis of Bacteria. Bacterial DNA was extracted from 500 mL of filtered lake water using the FastPrep DNA purification kit (BIO101). Bacterioplankton diversity was assessed by automated ribosomal intergenic spacer analysis (ARISA). PCR for ARISA was performed following the method of Fisher and Triplett [8] with modifications. PCR reactions contained PCR buffer consisting of 50 mM Tris (pH 8.0), 250 lg of bovine serum albumin per mL and 3.0 mM MgCl2 (Idaho Tech), 250 lM of each dNTP, 10 pmol of each primer, 1.25 U of Tag polymerase (Promega), and 1 lL of lake-extracted DNA in a final volume of 25 lL. The primers used for ARISA were 1406f (universal 16S rRNA gene; 50-TGYACACACCGCCCGT-30) labeled with 6- FAM, and 23Sr (bacteria-specific, 23S rRNA gene; 50- GGGTTBCCCCATTCRG-30). All PCR was carried out in an Eppendorf MasterCycler Gradient (Eppendorf). The initial denaturation was performed at 94 C for 2 min, followed by 30 cycles of 94 C for 35 s, 55 C for 45 s, and 72 Cfor 2 min, with a final extension carried out at 72 C for 2 min.Denaturing capillary electrophoresis was carried out for each PCR reaction using an ABI 310 Genetic Analyzer (PE Biosystems). Electrophoresis conditions were 60 C and 15 kV with a run time of 50 min using the POP-4 polymer. A custom 200- to 2000-bp rhodamine X–labeled size standard (Bioventures) was used as the internal size standard for each sample. The data were analyzed using GeneScan 3.1 software (PerkinElmer). To include the maximum number of peaks while excluding background fluorescence, a fluorescence cutoff of 500 fluorescence units was used.
Short Name
MOPP1
Version Number
4

Primary Production and Species Richness in Lake Communities 1997 - 2000

Abstract
An understanding of the relationship between species richness and productivity is crucial to understanding biodiversity in lakes. We investigated the relationship between the primary productivity of lake ecosystems and the number of species for lacustrine phytoplankton, rotifers, cladocerans, copepods, macrophytes, and fish. Our study includes two parts: (1) a survey of 33 well-studied lakes for which data on six major taxonomic groups were available; and (2) a comparison of the effects of short- and long-term whole-lake nutrient addition on primary productivity and planktonic species richness Dodson, Stanley I., Shelley E. Arnott, and Kathryn L. Cottingham. 2000. The relationship in lake communities between primary productivity and species richness. Ecology 81:2662-79. Number of sites: 33
Creator
Dataset ID
222
Date Range
-
Maintenance
completed
Metadata Provider
Methods
Our first goal was to understand the relationship between primary productivity and species richness for several groups of freshwater organisms. By species richness, we mean the number of species observed in a lake over a number of years. It is useful to have several years of observations because the number of species observed varies from year to year. We chose the total list of species (the asymptote of the collectors curve) as our index of species richness. The lakes studied as part of the U.S. Long-Term Ecological Research (LTER) Program are particularly valuable because they have been studied for two decades, and complete species lists exist for many kinds of organisms in these systems. LTER lake sites occur in northern and southern Wisconsin and northern Alaska (Toolik Lake). However, because there are fewer than 15 LTER lakes (and only seven with measured rates of primary productivity), we increased sample size by including data from additional well-studied lakes of similar size, but which span a greater range of primary productivity (see Table 1). These lakes have been studied for several years, and estimates of annual primary productivity exist for each lake. Some well-studied lakes were not included, such as those which lacked much of the crucial data, or lakes that were unusually turbid or saline. For example, Lake Okeechobee (Florida, USA) is turbid and exhibits a wide range of productivity levels, depending on the part of the lake sampled, while Marion Lake (British Columbia, Canada) has a flushing rate of only a few days (W. E. Neill, personal communication). Sampling design and protocol are not standardized among studies of lakes. For example, species identifications were done by different people, sampling period was quite variable, and the number of samples per lake was variable. Such heterogeneity reduces the accuracy and precision of relationships between productivity and species richness.Primary productivity.—Pelagic primary productivity (PPR) can be measured by the 14C method (Vollenweider 1974). This method gives a close approximation to gross primary productivity (GPP), but because some of the fixed carbon is respired quickly, the value obtained is less than GPP (Fee et al.1982). Point values of PPR are then integrated by depth and area to produce estimates of whole-lake annual primary productivity per cubic meter or square meter.Lake primary productivity is fundamentally different than productivity measured in other biomes (e.g., grasslands, forests). The 14C method measures available (gross) primary productivity more than utilized (net) production, which is what is normally measured in terrestrial systems. The 14C method is also a fairly direct measure of productivity, compared to the proxy methods (e.g., nutrient loading, biomass, climate, soil fertility) used in many studies.Sampling protocols for aquatic organisms.—Sampling protocols differed among taxonomic groups and lakes (e.g., Downing and Rigler 1984). For example, phytoplankton samples are taken by capturing (at most) a few liters of lake water, either from a specific depth or with a sampler that integrates water across a range of depths. Zooplankton are usually sampled by vertical tows (i.e., raising a net through the water column). Both zooplankton and phytoplankton samples are typically taken from the center of the lake, although replicate samples at different locations may be taken from larger lakes. Planktonic organisms are much smaller than the sampling device, and hundreds to hundreds of thousands of organisms are typically captured in a single sample. In contrast, aquatic macrophytes are sampled using quadrats and rake samples, or simply based on a walk around the lake, while fish are sampled using a variety of nets andoror electroshocking equipment. Criteria for species lists.—Species lists for fish, macrophytes, and pelagic phytoplankton, rotifers, cladocerans, and copepods were obtained from the literature and from unpublished data. We avoided lists restricted to only dominant or common species, and thus included only lists that were exhaustive. Few lakes had species lists for all six groups of organisms. However, we included any lake that had an estimate of the average annual primary productivity and had lists for at least three taxa.We standardized this database by developing criteria for inclusion of species in analyses. Phytoplankton lists included all prokaryotic and eukaryotic photosynthetic phytoplankton for which there were abundances of more than one organism per milliliter (a criterion also used by Lewis 1979). We included all nonsessile species caught in open water as pelagic rotifers. For the crustacean zooplankton (cladocerans and copepods), we followed the criteria of Dodson (1992). Species lists of macrophytes included all submerged, floating, or emergent species of flowering plants, including Typha, sedges, grasses, and duck weed. We did not include Isoetes or macroalgae such as Chara and Nitella as macrophytes. The fish list included all species reported from the lake, including introduced taxa. Fish species reported to occur in the watershed, but not in the lake (as in Pearse1920) were not considered part of the lakes biota.
Short Name
DODSON1
Version Number
26

Cascade Project at North Temperate Lakes LTER: Phytoplankton 1984 - 1995

Abstract
Data on epilimnetic phytoplankton from 1984-95, determined by light microscopy from pooled Van Dorn samples at 100percent, 50percent, and 25percent of surface irradiance. There have been 4 counters during this period, with the same counter from 1991-95. Standardization among counters is difficult, so I recommend sticking to the 1991-95 data if possible. Cottingham (1996) describes the counting protocols in detail. Sampling Frequency: varies Number of sites: 5
Core Areas
Dataset ID
80
Date Range
-
LTER Keywords
Maintenance
completed
Metadata Provider
Methods
See for detail: Cottingham, K.L., and S.E. Knight. 1995. Effects of grazer size on the response of mesotrophic lakes to experimental enrichment. Water Science and Technology 32(4): 157-163.
Short Name
CPHYT1
Version Number
3

North Temperate Lakes LTER: Phytoplankton - Madison Lakes Area 1995 - current

Abstract
Phytoplankton samples for the 4 southern Wisconsin LTER lakes (Mendota, Monona, Wingra, Fish) have been collected for analysis by LTER since 1995 (1996 Wingra, Fish) when the southern Wisconsin lakes were added to the North Temperate Lakes LTER project. Samples are collected as a composite whole-water sample and are preserved in gluteraldehyde. Composite sample depths are 0-8 meters for Lake Mendota (to conform to samples collected and analyzed since 1990 for a UW/DNR food web research study), and 0-2 meters for the other three lakes. A tube sampler is used for the 0-8 m Lake Mendota samples; samples for the other lakes are obtained by collecting water at 1-meter intervals using a Kemmerer water sampler and compositing the samples in a bucket. Samples are taken in the deep hole region of each lake at the same time and location as other limnological sampling. Phytoplankton samples are analyzed by PhycoTech, Inc., a private lab specializing in phytoplankton analyses (see data protocol for procedures). Samples for Wingra and Fish lakes are archived but not routinely counted. Permanent slide mounts (3 per sample) are prepared for all analyzed Mendota and Monona samples as well as 6 samples per year for Wingra and Fish; the slide mounts are archived at the University of Wisconsin - Madison Zoology Museum. Phytoplankton are identified to species using an inverted microscope (Utermohl technique) and are reported as natural unit (i.e., colonies, filaments, or single cells) densities per mL, cell densities per mL, and algal biovolume densities per mL. Multiple entries for the same species on the same date may be due to different variants or vegetative states - (e.g., colonial or attached vs. free cell.) Biovolumes for individual cells of each species are determined during the counting procedure by obtaining cell measurements needed to calculate volumes for geometric solids (e.g., cylinders, spheres, truncated cones) corresponding to actual cell shapes. Biovolume concentrations are then computed by mulitplying the average cell biovolume by the cell densities in the water sample. Note that one million cubicMicrometers of biovolume PerMilliliter of water are equal to a biovolume concentration of one cubicMillimeterPerMilliliter. Assuming a cell density equal to water, a cubicMillimeterPerMilliliter of biovolume converts to a biomass concentration of one milligramPerLiter. Sampling Frequency: bi-weekly during ice-free season from late March or early April through early September, then every 4 weeks through late November; sampling is conducted usually once during the winter (depending on ice conditions). Number of sites: 4
Several taxonomic updates have been made to this dataset February 2013, see methods for details.
Dataset ID
88
Date Range
-
Maintenance
ongoing
Metadata Provider
Methods
Water samples are taken along routine sampling and then prepared into permanent slides by the company Phyco Tech. Slides are available for all years, however, species may not have been determined for all available slides.
several taxonomic updates were implemented in February 2013, this includes simple name changes to currently accepted names, changes from genus level to species based on long term experience by Phyco Tech, and some slides were revisited to resolve taxonomic uncertainty.
1) Converted all Melosira entries to Aulacoseira. The species names have been changed appropriately. 2) Converted all Oscillatoria entries to Psuedanabaena. The species names have been changed appropriately. 3) Converted all Synedra tenera to Synedra filiformis. 4) Converted all Phacotus entries without a species name to Phacotus lendneri. 5) Converted all Phormidium mucicola to Psuedanabaena 6) Converted Glenodinium entries without a species name to Glenodinium quadridens 7) Assume that all other entries with genera names but not species names cannot be resolved to species. 8) Converted all Chrysococcus entries to Chrysocccus minutus 9) Changed some single-celled Microcystis entries so that they would match the format of the colonial entries (genus + species) 10) Resolved some entries to species that were previously coded incorrectly by genus. 11) Added in Cylindrospermopsis raciborskii entries that were recently recounted and changed from Anabaenopsis raciborskii. 12) Converted all entries of genus Erkenia to Erkenia subaequiciliata
Short Name
NTLPL05
Version Number
29

North Temperate Lakes LTER: Phytoplankton - Trout Lake Area 1984 - current

Abstract
Phytoplankton samples from the seven LTER lakes in the Trout Lake area (Allequash, Big Muskellunge, Crystal, Sparkling, and Trout lakes and bog lakes 27-02 [Crystal Bog], and 12-15 [Trout Bog]) are collected six times per year at the deep hole sampling station at the same time our other limnological sampling is conducted. Sampling dates include winter under ice, spring mixis, June, July, August, and fall mixis. Phytoplankton samples are made into permanent slide mounts, 3 slides per sample, and are archived at the University of Wisconsin - Madison Zoology Museum. Slides are available for all years, however species identification and counts have not been done for all available slides. Sampling Frequency: 6 samples per year. Number of sites: 7
Dataset ID
238
Date Range
-
LTER Keywords
Maintenance
ongoing
Metadata Provider
Methods
Phytoplankton samples are collected using a peristaltic pump and tubing, collecting a separate sample from the epilimnion, metalimnion and hypolimnion for most of the lakes. For 27-2 Bog Lake, which is only 2m deep, we collect one 0-2m composite sample. The samples are preserved with Lugol's iodine solution. We create a single hypsometrically pooled composite sample per lake from subsamples of the epi, meta, and hypo samples. The pooled samples are sent to PhycoTech, Inc., a private lab specializing in plankton analysis, to be made into permanent slide mounts. The slides are archived, and no wet samples are saved.
Short Name
NTLPL08
Version Number
19
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