Methods

Sites are designated according to the NTL numbering scheme established for the shoreline of the south basin of Trout Lake and its islands. The four sites (Trout-07, 46.01809769, -89.65571661; Trout-31, 46.0430698, -89.67157974; Trout-50, 46.01729465, -89.69461296; Trout-56, 46.01921135, -89.6813004) used by the macrophyte component are also used in the NTL fish and crayfish sampling. Five replicate quadrats (0.25 M2) are harvested for all above ground biomass at each site at each of three nominal depths: 1.5 M, 2.5 M and 4 M. Samples are removed along a line parallel to shore - located midway between sites for cover estimates. Four sites with 3 depths and 5 replicates yields 60 samples. In the lab, samples are separated by species and are dried and weighed. From 1989 to 2008 plants were placed in labeled paper bags oven dried, and weights recorded. Biomass weights were determined by weighing dried plants in paper bags and using an average tare for the bags. Consequently, values in the data base can be negative and should be considered as present in very small amounts.
Pre-1987 Data. In 1987, permanent line transects were established at each of the sites. Biomass samples and line transects observed before 1987 were set by more general descriptions at the site and were not identical year to year.

Methods

Details of field collections can be found in Wilson, K.A. 2002. Impacts of the invasive rusty crayfish (Orconectes rusticus) in northern Wisconsin lakes. Ph.D. Dissertation. University of Wisconsin, Madison.

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.

Methods

Macrophyte surveys were conducted on Sparkling Lake, Vilas County, Wisconsin in mid-July of the years 2001 to 2009. Eight sites were chosen that corresponded to trap survey sites for rusty crayfish and represented the range of macrophyte communities in the lake. These sites corresponded to trap survey sites 1, 4, 10, 16, 20, 23, 27, and 35. At each site, we swam a transect perpendicular to shore from 0 to 4 m depths. A tape measure extended from shore to the 4 m depth contour, and buoys were placed at the 1, 2, 3, and 4 m depth contours. We visually estimated the percent cover of each macrophyte species within a 0.24 meter squared quadrat. Quadrats were placed along each transect at 1 m intervals. Thus, we used fewer quadrats on transects with a steeper slope. At site 23, we only found a macrophyte on one event: Vallisneria sp. in 2004.Transect: corresponds to trap survey site number.Quadrat: occur at 1 m intervals starting from shore (0) and going until you reach the 4 m depth contour (highest number).Substrate: substrate within the quadrat categorized as muck, sand, gravel, cobble, logs, leaves, or any combination of these.Abundance: percent cover of each species within the quadrat determined by visual estimation. The percent covers of all species within a quadrat do NOT necessarily add to 100.Depth Interval: depth interval that each quadrat was in. Quadrats between 0 and 1 m deep are in depth interval 1, those between 1 and 2 m deep are in depth interval 2, etc.

Methods

The macrophyte surveys were performed at eight sites within each of the 60 lakes. The sites were chosen by randomly selecting two 50m segments of shoreline per compass quadrant of each lake. At each site, we examined the macrophytes to a depth of 2m along a 50 m long transect perpendicular to the shoreline, beginning at the center point of the 50m segment of shoreline selected for the site. Within a ? m2 quadrat at every meter mark, we noted the species present, the dominant species, the substrate composition and the total percent vegetation cover. If a depth of 2 m was reached before 20 quadrats were measured, a second transect was performed 25 m to the right of the initial point. The distances from shore at 1 m depth and 2 m depth were also recorded on each transect for an estimate of slope. Sampling Frequency: each site sampled once Number of sites: 60 Vilas County lakes were sampled from 2001-2004 (approximately 15 different lakes each year).At each site, we examined the littoral vegetation along a transect perpendicular to the shoreline. Within a 0.25 m2 quadrat at every meter mark, we recorded the total percent vegetation cover, dominant species and all species present to a water depth of 2 meters or 50 meters from shore. If a depth of 2 m was reached before 20 quadrats were measured, a second transect was performed 25 m to the right of the initial point. These observations were averaged to calculate percent total cover of vegetation in the littoral zone per lake (Marburg et al. 2005). The percent cover was transformed using arcsine square root of the decimal proportion.

Methods

This data set provides sampling-point by sampling-point macrophyte data for lakes sampled by a number of agencies in Wisconsin. Sampling timing and intensity varied. An estimate of plant density is given at each point and water depth and substrate information is available for many sampling points. The AQUAPLT2, DATSOUR, MAXDEPLNG, PLTNAME, and LAKEHAB tables are relational and were original used in a database to generate plant community tables. These relational tables contain more detailed and recent data from approximately the 1970s onwardThe LAKESPEC table contains analyzed plant community data that may have been generated from the above tables or gleaned from the literature. The LAKESPEC data contains some historical data from the 1930s and before as well as more recent data. More information on the LAKESPEC data is in Nichols, S.A. and R. A. Martin, 1990. Wisconsin Lake Plant Database. Information Circular 69, Wisconsin Geological and Natural History Survey, Madison, 27 ppVilas County lakes were sampled from 2001-2004 (approximately 15 different lakes each year).