Methods

All methods describing the calculation of these data can be found in Embke et al. (in review)

Methods

I. Study System Lake Mývatn, Iceland (65°36 N, 17°0′ W) is a large (38 km²) shallow (4 m max depth) lake divided into two large basins that function mostly as independent hydrologic bodies (Ólafsson 1979). The number of non-biting midge (Diptera: Chironomidae) larvae on the lake bottom is high, but variable: midge production between 1972-74 ranged from 14-100 g ash-free dw m^-2 yr^-1, averaging 28 g dw m^-2 yr^-1 (Lindegaard and Jónasson 1979). The midge assemblage is mostly comprised of two species (> 90% of total individuals), Chironomus islandicus (Kieffer) and Tanytarsus gracilentus (Holmgren) that feed as larvae in the sediment in silken tubes by scraping diatoms, algae, and detritus off the lake bottom (Lindegaard and Jónasson 1979). At maturity (May-August) midge pupae float to the lake surface, emerge as adults, and fly to land, forming large mating swarms around the lake (Einarsson et al. 2004, Gratton et al. 2008). On land, midges are consumed by terrestrial predators (Dreyer et al. 2012, Gratton et al. 2008), or enter the detrital pool upon death (Gratton et al. 2008, Hoekman et al. 2012). Midge populations naturally cycle with 5-8 year periodicity, with abundances fluctuating by 3-4 orders of magnitude (Einarsson et al. 2002, Ives et al. 2008). II. Midge Emergence Measurement We used submerged conical traps to estimate midge emergence from Lake Mývatn. Traps were constructed of 2 mm clear polycarbonate plastic (Laird Plastics, Madison, WI) formed into a cone with large-diameter opening of 46 cm (0.17 m²). The tops of the cones were open to a diameter of 10 cm, with a clear jar affixed at the apex. The trap was weighted to approximately neutral buoyancy, with the jar at the top containing air to allow mature midges to emerge. Traps were suspended with a nylon line ~1 m below the surface of the lake from an anchored buoy. For sampling, traps were raised to the surface and rapidly inverted, preventing midges from escaping. Jars and traps were thoroughly rinsed with lake water to collect all trapped midges, including unmetamorphosed larvae and pupae, and scrubbed before being returned to the lake to prevent growth of epiphytic algae and colonization by midges. We assume that the emergence traps collect all potentially emerging midges from the sampling area, though it is likely an underestimate, since some midges initially captured could fall out of the trap. Thus, our results should be considered a conservative estimate of potential midge emergence from the surface of the lake.We sampled midge emergence throughout the south basin of Lake Mývatn. Emergence was sampled at six sites in 2008 and 2011 and ten sites in 2009 and 2010, with locations relocated using GPS and natural sightlines. Each site had two traps within 5 m of each other that were monitored during midge activity, approximately from the last week of May to the first week of August. Midge emergence outside of this time frame is extremely low (Lindegaard & Jónasson 1979) and we assume it to be zero. Traps were checked weekly during periods of high emergence (initial and final 2-3 weeks of the study), and bi-weekly during low emergence periods in the middle of the study (July). III. Identification, Counts, and Conversions Midges were counted and identified to morphospecies, small and large. The midge (Diptera,Chrionomidae) assemblage at Mývatn is dominated by two species, Chironomus islandicus (Kieffer)(large, 1.1 mg dw) and Tanytarsus gracilentus (Holmgren)(small, 0.1 mg dw), together comprising 90 percent of total midge abundance (Lindegaard and Jonasson 1979). First, the midges collected in the infall traps were spread out in trays, and counted if there were only a few. Some midges were only identified to the family level of Simuliidae, and other arthropods were counted and categorized as the group, others. Arthropods only identified to the family level Simuliidae or classified as others were not dually counted as Chironomus islandicus or Tanytarsus gracilentus . If there were many midges, generally if there were hundreds to thousands, in an infall trap, subsamples were taken. Subsampling was done using plastic rings that were dropped into the tray. The rings were relatively small compared to the tray, about 2 percent of the area of a tray was represented in a ring. The area inside a ring and the total area of the trays were also measured. Note that different sized rings and trays were used in subsample analysis. These are as follows, trays, small (area of 731 square centimeters), “large1” (area of 1862.40 square centimeters), and large2 (area of 1247 square centimeters). Rings, standard ring (diameter of 7.30 centimeters, subsample area is 41.85 square centimeters) and small ring (diameter of 6.5 centimeters, subsample area is 33.18 square centimeters). A small ring was only used to subsample trays classified as type “large2.”The fraction subsampled was then calculated depending on the size of the tray and ring used for the subsample analysis. If the entire tray was counted and no subsampling was done then the fraction subsampled was assigned a value of 1.0. If subsampling was done the fraction subsampled was calculated as the number of subsamples taken multiplied by the fraction of the tray that a subsample ring area covers (number of subsamples multiplied by (ring area divided by tray area)). Note that this is dependent on the tray and ring used for subsample analysis. Finally, the number of midges in an infall trap accounting for subsampling was calculated as the raw count of midges divided by the fraction subsampled (raw count divided by fraction subsampled).Other metrics such as total insects in meters squared per day, and total insect biomass in grams per meter squared day can be calculated with these data. In addition to the estimated average individual midge masses in grams, For 2008 through 2010 average midge masses were calculated as, Tanytarsus equal to .0001104 grams, Chironomus equal to .0010837 grams. For 2011 average midge masses were, Tanytarsus equal to .000182 grams, Chironomus equal to .001268 grams.

Methods

Data were collected from two lakes, Sparkling Lake (46.008, -89.701) and Peter Lake (46.253, -89.504), both located in the northern highlands Lake District of Wisconsin and the Upper Peninsula of Michigan over a 10 day period on each lake in July and August of 2007. Refer to Van de Bogert et al. 2011 for limnological characteristics of the study lakes.Measurements of dissolved oxygen and temperature were made every 10 minutes using multiple sondes dispersed horizontally throughout the mixed-layer in the two lakes (n=35 sondes for Sparkling Lake and n=27 sondes for Peter Lake). Dissolved oxygen measurements were corrected for drift.Conductivity, temperature compensated specific conductivity, pH, and oxidation reduction potential were also measured by a subset of sensors in each lake. Of the 35 sondes in Sparkling Lake, 31 were from YSI Incorporated: 15 of model 600XLM, 14 of model 6920, and 2 of model 6600). The remaining sondes placed in Sparkling Lake were 4 D-Opto sensors, Zebra-Tech, LTD. In Peter Lake, 14 YSI model 6920 and 13 YSI model 600XLM sondes were used.Sampling locations were stratified randomly so that a variety of water depths were represented, however, a higher density of sensors were placed in the littoral rather than pelagic zone. See Van de Bogert et al. 2012 for the thermal (stratification) profile of Sparkling Lake and Peter Lake during the period of observation, and for details on how locations were classified as littoral or pelagic. In Sparkling Lake, 11 sensors were placed within the shallowest zone, 12 in the off-shore littoral, and 6 in each of the remaining two zones, for a total of 23 littoral and 12 pelagic sensors. Similarly, 15 sensors were placed in the two littoral zones, and 12 sensors in the pelagic zone.Sensors were randomly assigned locations within each of the zones using rasterized bathymetric maps of the lakes and a random number generator in Matlab. Within each lake, one pelagic sensor was placed at the deep hole which is used for routine-long term sampling.Note that in Sparkling Lake this corresponds to the location of the long-term monitoring buoy. After locations were determined, sensors were randomly assigned to each location with the exception of the four D-Opto sensor is Sparkling Lake, which are a part of larger monitoring buoys used in the NTL-LTER program. One of these was located near the deep hole of the lake while the other three were assigned to random locations along the north shore, south shore and pelagic regions of the lake. Documentation: Van de Bogert, M.C., Bade, D.L., Carpenter, S.R., Cole, J.J., Pace, M.L., Hanson, P.C., Langman, O.C., 2012. Spatial heterogeneity strongly affects estimates of ecosystem metabolism in two north temperate lakes. Limnology and Oceanography 57, 1689-1700.

Methods

Net production of bacteria passing a 70 micron mesh, or bacteria passing a 1 micron mesh, calculated incorporation of 3H labeled leucine into cell proteins. Method based on microcentrifuge method of Smith, David C., and Farooq Azam. 1992. A simple, economical method for measuring bacterial protein synthesis rates in seawater using 3H-leucine, Marine Microbial Food Webs 6(2):107-114. Nanomolar treatments refer to leucine concentration for calculation of isotopic dilution and necessary leucine concentration to saturate uptake into bacterial cells. For a good example on how to calculate isotopic dilution see Pace. Michael L., and Jonathan J. Cole. Primary and bacterial production in lakes: are they coupled over depth? Plankton Research 16(6):661-672. Sampling Frequency: fortnightly during ice-free season - every 6 weeks during ice-covered season Number of sites: 4