| 1. |
- Brentrup, Jennifer A., et al.
(författare)
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The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes : an extension of the Plankton Ecology Group (PEG) model
- 2016
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Ingår i: Inland Waters. - 2044-2041 .- 2044-205X. ; 6:4, s. 565-580
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Tidskriftsartikel (refereegranskat)abstract
- The use of high-frequency sensors on profiling buoys to investigate physical, chemical, and biological processes in lakes is increasing rapidly. Profiling buoys with automated winches and sensors that collect high-frequency chlorophyll fluorescence (ChlF) profiles in 11 lakes in the Global Lake Ecological Observatory Network (GLEON) allowed the study of the vertical and temporal distribution of ChlF, including the formation of subsurface chlorophyll maxima (SSCM). The effectiveness of 3 methods for sampling phytoplankton distributions in lakes, including (1) manual profiles, (2) single-depth buoys, and (3) profiling buoys were assessed. High-frequency ChlF surface data and profiles were compared to predictions from the Plankton Ecology Group (PEG) model. The depth-integrated ChlF dynamics measured by the profiling buoy data revealed a greater complexity that neither conventional sampling nor the generalized PEG model captured. Conventional sampling techniques would have missed SSCM in 7 of 11 study lakes. Although surface-only ChlF data underestimated average water column ChlF, at times by nearly 2-fold in 4 of the lakes, overall there was a remarkable similarity between surface and mean water column data. Contrary to the PEG model's proposed negligible role for physical control of phytoplankton during the growing season, thermal structure and light availability were closely associated with ChlF seasonal depth distribution. Thus, an extension of the PEG model is proposed, with a new conceptual framework that explicitly includes physical metrics to better predict SSCM formation in lakes and highlight when profiling buoys are especially informative.
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| 2. |
- Bruce, Louise C, et al.
(författare)
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A multi-lake comparative analysis of the General Lake Model (GLM) : Stress-testing across a global observatory network
- 2018
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Ingår i: Environmental Modelling & Software. - : Elsevier BV. - 1364-8152 .- 1873-6726. ; 102, s. 274-291
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Tidskriftsartikel (refereegranskat)abstract
- The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required.
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| 3. |
- Kara, Emily L., et al.
(författare)
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Time-scale dependence in numerical simulations : Assessment of physical, chemical, and biological predictions in a stratified lake at temporal scales of hours to months
- 2012
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Ingår i: Environmental Modelling & Software. - : Elsevier BV. - 1364-8152 .- 1873-6726. ; 35, s. 104-121
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 4. |
- Read, Jordan S., et al.
(författare)
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Generating community-built tools for data sharing and analysis in environmental networks
- 2016
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Ingår i: Inland Waters. - 2044-2041 .- 2044-205X. ; 6:4, s. 637-644
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Tidskriftsartikel (refereegranskat)abstract
- Rapid data growth in many environmental sectors has necessitated tools to manage and analyze these data. The development of tools often lags behind the proliferation of data, however, which may slow exploratory opportunities and scientific progress. The Global Lake Ecological Observatory Network ( GLEON) collaborative model supports an efficient and comprehensive data-analysis-insight life cycle, including implementations of data quality control checks, statistical calculations/derivations, models, and data visualizations. These tools are community-built and openly shared. We discuss the network structure that enables tool development and a culture of sharing, leading to optimized output from limited resources. Specifically, data sharing and a flat collaborative structure encourage the development of tools that enable scientific insights from these data. Here we provide a cross-section of scientific advances derived from global-scale analyses in GLEON. We document enhancements to science capabilities made possible by the development of analytical tools and highlight opportunities to expand this framework to benefit other environmental networks.
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| 5. |
- Sharma, Sapna, et al.
(författare)
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Widespread loss of lake ice around the Northern Hemisphere in a warming world
- 2019
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Ingår i: Nature Climate Change. - : NATURE PUBLISHING GROUP. - 1758-678X .- 1758-6798. ; 9:3, s. 227-231
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Tidskriftsartikel (refereegranskat)abstract
- Ice provides a range of ecosystem services-including fish harvest(1), cultural traditions(2), transportation(3), recreation(4) and regulation of the hydrological cycle(5)-to more than half of the world's 117 million lakes. One of the earliest observed impacts of climatic warming has been the loss of freshwater ice(6), with corresponding climatic and ecological consequences(7). However, while trends in ice cover phenology have been widely documented(2,6,8,9), a comprehensive large-scale assessment of lake ice loss is absent. Here, using observations from 513 lakes around the Northern Hemisphere, we identify lakes vulnerable to ice-free winters. Our analyses reveal the importance of air temperature, lake depth, elevation and shoreline complexity in governing ice cover. We estimate that 14,800 lakes currently experience intermittent winter ice cover, increasing to 35,300 and 230,400 at 2 and 8 degrees C, respectively, and impacting up to 394 and 656 million people. Our study illustrates that an extensive loss of lake ice will occur within the next generation, stressing the importance of climate mitigation strategies to preserve ecosystem structure and function, as well as local winter cultural heritage.
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