Significant improvements have been made in estimating gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) from diel, “free‐water” changes in dissolved oxygen ...(DO). Here we evaluate some of the assumptions and uncertainties that are still embedded in the technique and provide guidelines on how to estimate reliable metabolic rates from high‐frequency sonde data. True whole‐system estimates are often not obtained because measurements reflect an unknown zone of influence which varies over space and time. A minimum logging frequency of 30 min was sufficient to capture metabolism at the daily time scale. Higher sampling frequencies capture additional pattern in the DO data, primarily related to physical mixing. Causes behind the often large daily variability are discussed and evaluated for an oligotrophic and a eutrophic lake. Despite a 3‐fold higher day‐to‐day variability in absolute GPP rates in the eutrophic lake, both lakes required at least 3 sonde days per week for GPP estimates to be within 20% of the weekly average. A sensitivity analysis evaluated uncertainties associated with DO measurements, piston velocity (k), and the assumption that daytime R equals nighttime R. In low productivity lakes, uncertainty in DO measurements and piston velocity strongly impacts R but has no effect on GPP or NEP. Lack of accounting for higher R during the day underestimates R and GPP but has no effect on NEP. We finally provide suggestions for future research to improve the technique.
A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological ...advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process-based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.
1. We tested the degree to which a lake's landscape position constrains the expression of limnological features and imposes a characteristic spatial pattern in a glacial lake district, the Northern ...Highland Lake District in north‐central Wisconsin.
2. We defined lake order as a metric to analyze the effect of landscape position on limnological features. Lake order, analogous to stream order, is based solely on geographical information and is simple to measure.
3. We examined the strength of the relationship between lake order and a set of 25 variables, which included measures of lake morphometry, water optical properties, major ions, nutrients, biology, and human settlement patterns.
4. Lake order explained a significant fraction of the variance of 21 of the 25 variables tested with ANOVA. The fraction of variance explained varied from 12% (maximum depth) to 56% (calcium concentration). The variables most strongly related to lake order were: measures of lake size and shape, concentrations of major ions (except sulfate) and silica, biological variables (chlorophyll concentration, crayfish abundance, and fish species richness), and human‐use variables (density of cottages and resorts). Lake depth, water optical properties, and nutrient concentrations (other than silica) were poorly associated with lake order.
5. Potential explanations for a relationship with lake order differed among variables. In some cases, we could hypothesize a direct link. For example, major ion concentration is a function of groundwater input, which is directly related to lake order. We see these as a direct influence of the geomorphic template left by the retreat of the glacier that led to the formation of this lake district.
6. In other cases, a set of indirect links was hypothesized. For example, the effect of lake order on lake size, water chemistry, and lake connectivity may ultimately explain the relation between lake order and fish species richness. We interpret these relationships as the result of constraints imposed by the geomorphic template on lake development over the last 12 000 years.
7. By identifying relationships between lake characteristics and a measure of landscape position, and by identifying geomorphologic constraints on lake features and lake evolution, our analysis explains an important aspect of the spatial organization of a lake district.
influences of typhoon‐induced mixing in a shallow lake Kimura, Nobuaki; Liu, Wen‐Cheng; Chiu, Chih‐Yu ...
Lakes & Reservoirs : Science, Policy and Management for Sustainable Use,
September 2012, Letnik:
17, Številka:
3
Journal Article
Recenzirano
Vertical mixing affects the vertical transport of biochemical materials and modifies the characteristics of basin‐scale internal waves in subtropical, subalpine Yang Yuan Lake (YYL), in the north ...central region of Taiwan. Vertical mixing in YYL is generally caused by typhoons (strong winds and heavy rainfalls) during the spring, summer and early fall, or by cooling of the water column during late fall and winter. Vertical mixing caused by typhoons significantly affects internal thermal dynamics and biochemical processes, with basin‐scale internal waves enhanced before complete mixing occurs, and temporal variations of water temperature dramatically changing after typhoon events. This study quantitatively determines when the complete mixing (defined as homogenous temperature in a water column) occurs on the basis of the balance between kinetic energy and potential energy and also shows what meteorological conditions contribute to the vertical mixing. Data on water column thermal profiles and meteorological variables were collected by a wireless, instrumented buoy in the deepest location of YYL and from a nearby meteorological station, from spring 2004 to summer 2006. This study also investigated how a physical process (internal waves) is affected by the mixing associated with typhoons. Signal processing and a two‐layer model of the water column are used to understand the characteristics of basin‐scale internal waves.
We evaluated the predictive ability of a one-dimensional coupled hydrodynamic-biogeochemical model across multiple temporal scales using wavelet analysis and traditional goodness-of-fit metrics. ...High-frequency in situ automated sensor data and long-term manual observational data from Lake Mendota, Wisconsin, USA, were used to parameterize, calibrate, and evaluate model predictions. We focused specifically on short-term predictions of temperature, dissolved oxygen, and phytoplankton biomass over one season. Traditional goodness-of-fit metrics indicated more accurate prediction of physics than chemical or biological variables in the time domain. This was confirmed by wavelet analysis in both the time and frequency domains. For temperature, predicted and observed global wavelet spectra were closely related, while observed dissolved oxygen and chlorophyll fluorescence spectral characteristics were not reproduced by the model for key time scales, indicating that processes not modeled may be important drivers of the observed signal. Although the magnitude and timing of physical and biological changes were simulated adequately at the seasonal time scale through calibration, time scale-specific dynamics, for example short-term cycles, were difficult to reproduce, and were relatively insensitive to the effects of varying parameters. The use of wavelet analysis is novel to aquatic ecosystem modeling, is complementary to traditional goodness-of-fit metrics, and allows for assessment of variability at specific temporal scales. In this way, the effect of processes operating at distinct temporal scales can be isolated and better understood, both in situ and in silico. Wavelet transforms are particularly well suited for assessment of temporal and spatial heterogeneity when coupled to high-frequency data from automated in situ or remote sensing platforms.
Here, we describe and evaluate two low-power wireless sensor networks (WSNs) designed to remotely monitor wetland hydrochemical dynamics over time scales ranging from minutes to decades. Each WSN ...(one student-built and one commercial) has multiple nodes to monitor water level, precipitation, evapotranspiration, temperature, and major solutes at user-defined time intervals. Both WSNs can be configured to report data in near real time via the internet. Based on deployments in two isolated wetlands, we report highly resolved water budgets, transient reversals of flow path, rates of transpiration from peatlands and the dynamics of chromophoric-dissolved organic matter and bulk ionic solutes (specific conductivity)—all on daily or subdaily time scales. Initial results indicate that direct precipitation and evapotranspiration dominate the hydrologic budget of both study wetlands, despite their relatively flat geomorphology and proximity to elevated uplands. Rates of transpiration from peatland sites were typically greater than evaporation from open waters but were more challenging to integrate spatially. Due to the high specific yield of peat, the hydrologic gradient between peatland and open water varied with precipitation events and intervening periods of dry out. The resultant flow path reversals implied that the flux of solutes across the riparian boundary varied over daily time scales. We conclude that WSNs can be deployed in remote wetland-dominated ecosystems at relatively low cost to assess the hydrochemical impacts of weather, climate, and other perturbations.
A grassroots, global network to examine lake function using sensor data? Why not? That was the perspective of Drs.Tim Kratz (limnologist), David Hamilton (limnologist), Peter Arzberger ...(mathematician), and Fang-Pang Lin (computer scientist) in 2004 when they hatched the idea of the Global Lake Ecological Observatory Network (Fig. 1). Nine years later, with over 380 members from 40 countries, and 50 publications to its credit, GLEON is growing at a rapid pace and pushing the boundaries of the practice of network science. GLEON is really three networks: a network of lakes, data, and people (Fig. 1). While the first two underpin the scientific products and analyses that GLEON members produce (Fig. 2), explicit attention to the people network has served both GLEON science and its members exceedingly well.
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