Data are collected annually to enable us to track the fish assemblages of Lake Wingra. Sampling is done at six littoral zone sites per lake with a beach seine, minnow or crayfish traps, and fyke nets, while a boat-mounted electrofishing system samples four littoral transects. Vertically hung gill nets are used to obtain two pelagic samples per lake from the deepest point. A trammel net samples across the thermocline at two nearshore sites per lake. Fish are identified to species. Lengths are measured for all fish caught, while weight and scale are collected from a subset. Derived data include catch per unit effort and size distribution by species, lake, and year. Protocol used to generate data: Number caught for each species is summed over repetitions of a gear within a lake and over depth. Sampling Frequency: annually. Number of sites: 1. Note that 2020 data does not exist due to insufficient sampling.
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Dynamics of the stream–lake transitional zone affect littoral lake metabolism
Abstract Lake ecosystems, as integrators of watershed and climate stressors, are sentinels of change. However, there is an inherent time-lag between stressors and whole-lake response. Aquatic metabolism, including gross primary production (GPP) and respiration (R), of stream–lake transitional zones may bridge the time-lag of lake response to allochthonous inputs. In this study, we used high-frequency dissolved oxygen data and inverse modeling to estimate daily rates of summer epilimnetic GPP and R in a nutrient-limited oligotrophic lake at two littoral sites located near different major inflows and at a pelagic site. We examined the relative importance of stream variables in comparison to meteorological and in-lake predictors of GPP and R. One of the inflow streams was substantially warmer than the other and primarily entered the lake’s epilimnion, whereas the colder stream primarily mixed into the metalimnion or hypolimnion. Maximum GPP and R rates were 0.2–2.5 mg O 2 L −1 day −1 (9–670%) higher at littoral sites than the pelagic site. Ensemble machine learning analyses revealed that > 30% of variability in daily littoral zone GPP and R was attributable to stream depth and stream–lake transitional zone mixing metrics. The warm-stream inflow likely stimulated littoral GPP and R, while the cold-stream inflow only stimulated littoral zone GPP and R when mixing with the epilimnion. The higher GPP and R observed near inflows in our study may provide a sentinel-of-the-sentinel signal, bridging the time-lag between stream inputs and in-lake processing, enabling an earlier indication of whole-lake response to upstream stressors.
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- NSF-PAR ID:
- 10350239
- Date Published:
- Journal Name:
- Aquatic Sciences
- Volume:
- 84
- Issue:
- 3
- ISSN:
- 1015-1621
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract In lakes, the rates of gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) are often controlled by resource availability. Herein, we explore how catchment vs. within lake predictors of metabolism compare using data from 16 lakes spanning 39°N to 64°N, a range of inflowing streams, and trophic status. For each lake, we combined stream loads of dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP) with lake DOC, TN, and TP concentrations and high frequency
in situ monitoring of dissolved oxygen. We found that stream load stoichiometry indicated lake stoichiometry for C : N and C : P (r 2 = 0.74 andr 2 = 0.84, respectively), but not for N : P (r 2 = 0.04). As we found a strong positive correlation between TN and TP, we only used TP in our statistical models. For the catchment model, GPP and R were best predicted by DOC load, TP load, and load N : P (R 2 = 0.85 andR 2 = 0.82, respectively). For the lake model, GPP and R were best predicted by TP concentrations (R 2 = 0.86 andR 2 = 0.67, respectively). The inclusion of N : P in the catchment model, but not the lake model, suggests that both N and P regulate metabolism and that organisms may be responding more strongly to catchment inputs than lake resources. Our models predicted NEP poorly, though it is unclear why. Overall, our work stresses the importance of characterizing lake catchment loads to predict metabolic rates, a result that may be particularly important in catchments experiencing changing hydrologic regimes related to global environmental change. -
Data are collected annually to enable us to track the fish assemblages of Lake Wingra. Sampling is done at six littoral zone sites per lake with a beach seine, minnow or crayfish traps, and fyke nets, while a boat-mounted electrofishing system samples four littoral transects. Vertically hung gill nets are used to obtain two pelagic samples per lake from the deepest point. A trammel net samples across the thermocline at two nearshore sites per lake. Fish are identified to species. Lengths are measured for all fish caught, while weight and scale are collected from a subset. Derived data includes catch per unit effort and size distribution by species, lake, and year. Sampling Frequency: annually. Number of sites: 1. Note that 2020 data does not exist due to insufficient sampling.more » « less
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Abstract Lake‐based studies can provide seasonal‐ to millennial‐scale records of sediment yield to improve our understanding of catchment‐scale sediment transfer and complement shorter fluvial‐based sediment transport studies. In this study, sediment accumulation rates at 40 coring locations in Lake Peters, Brooks Range, Alaska, over ca. 42 years, calculated using fallout radionuclides and sediment density patterns, were spatially modelled based on distance from the primary inflow and lake water depth. We estimated mean interdecadal specific sediment yield (Mg km−2 year−1) using the spatially modelled sediment accumulation rates and compared that result to fluvial‐based sediment delivery for 2015–2016 open‐channel seasons, as well as to yields reported for other Arctic catchments. Using the lake‐based method, mean yield to Lake Peters between ca. 1973 and 2015 was 52 ± 12 Mg km−2 year−1, which is comparable with fluvial‐based modelling results of 33 (20–60) Mg km−2 year−1in 2015 and 79 (50–140) Mg km−2 year−1in 2016 (95% confidence intervals), respectively. Although 2016 was a year of above average sedimentation, the last extreme depositional event probably occurred between ca. 1970 and 1976 when a basal layer of fine sand was deposited in a broadly distributed, relatively thick and coarse bed, which we used for lake‐wide correlation. The dual lacustrine–fluvial method approach permits study of within‐lake and catchment‐scale processes. Within Lake Peters, sedimentation patterns show decreasing fluxes down‐lake, sediment bypassing near the primary inflow, the influence of secondary inflows and littoral redistribution, and a focusing effect in the deep proximal basin. At the watershed scale, sediment yield is largely driven by intense summer rainfall and strong seasonal hydroclimatic variability. This research informs paleo‐environmental reconstruction and environmental system modelling in Arctic lake catchments.
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In lakes, ecosystem structure and processes are influenced by gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP). The rates of these metabolic processes are often controlled by resource availability, which often reflects catchment loads. Although the relationship between catchment loads and in-lake nutrient concentrations may be well defined in specific lakes, we explored how watershed vs. in-lake predictors of metabolism compare across lake types. To do this, we combined stream loads of carbon (C), nitrogen (N), and phosphorus (P) with high frequency in situ monitoring of lake metabolism and in-lake C, N, and P concentrations from 16 lakes spanning a range of latitudes (39 to 64 degrees N), inflowing stream (0 - 6 streams), and trophic status (oligotrophic to eutrophic). The data package includes high-frequency dissolved oxygen, water temperature, wind speed, and solar radiation data as well as daily estimates of GPP, R, and NEP derived from those data. In addition, the data package includes in-lake and stream concentrations of dissolved organic carbon, total nitrogen, and total phosphorus and stream discharge data. The package also includes estimates of daily carbon, nitrogen and phosphorus loading to each lake derived from the stream concentrations and discharge.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1007/s00027-022-00854-7
