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Continuous and high-frequency measurements in limnology: History, applications and future challenges
Abstract
Over the past 15 years, an increasing number of studies in limnology have been using data from high-frequency measurements (HFM).This new technology offers scientists a chance to investigate lakes at time scales that were not possible earlier and in places where regular sampling would be complicated or even dangerous. This has allowed capturing the effects of episodic or extreme events, such as typhoons on lakes. In the present paper we review the various fields of limnology such as monitoring, studying highly dynamic processes, lake metabolism studies, and budget calculations where HFM has been applied, and which have benefitted most from the application. Our meta-analysis showed that more than half of the high-frequency studies from lakes were made in North-America and Europe. The main field of application has been lake ecology (monitoring, lake metabolism) followed by physical limnology. Water temperature and dissolved oxygen have been the most universal and commonly measured parameters and we review the various study purposes for which these measurements have been used. Although a considerable challenge forthe future, our review highlights that broadening the spatial scale of HFM would substantially broaden the applicability of these data across a spectrum of different fields.
... Although significant progress has been made in recognizing the importance of the LOAC as a whole system (e.g. Raymond et al., 2013;Regnier et al., 2013;Downing 2014;Palmer et al., 2015;Xenopoulos et al., 2017), huge knowledge gaps are still present, particularly related to limited field data availability (Meinson et al., 2016). Often, this is due to different measuring techniques and protocols, both with respect to in situ/autonomous observations and the collection of discrete data. ...
... Inland water investigations have also seen clear progress with the development of continuous, autonomous measurement techniques (e.g. DeGrandpre et al., 1995;Baehr and DeGrandpre, 2004;Crawford et al., 2014;Meinson et al., 2016;Brandt et al., 2017). Yet, only few studies have employed membrane-based equilibration sensors with non-dispersive infrared spectrometry (NDIR) detection (e.g. ...
... They also require more maintenance (see reference gases), and the data acquisition is therefore more labour-intensive, also increasing the probability of human error. Sensors designed for inland water bodies tend to be on the lower price range for various reasons, which unfortunately leads to lower accuracies and greater inconsistencies (Meinson et al., 2016;Friedlingstein et al., 2019;Canning, 2020). Measurements across the LOAC need high-accuracy sensors as the concentrations and dynamic ranges usually decrease from inland waters to the ocean and, thus, have to match with the oceanic standards, and the set-up presented here was designed to fulfil these requirements. ...
The ocean and inland waters are two separate regimes, with concentrations in greenhouse gases differing on orders of magnitude between them. Together, they create the land–ocean aquatic continuum (LOAC), which comprises itself largely of areas with little to no data with regards to understanding the global carbon system. Reasons for this include remote and inaccessible sample locations, often tedious methods that require collection of water samples and subsequent analysis in the lab, and the complex interplay of biological, physical and chemical processes. This has led to large inconsistencies, increasing errors and has inevitably lead to potentially false upscaling. A set-up of multiple pre-existing oceanographic sensors allowing for highly detailed and accurate measurements was successfully deployed in oceanic to remote inland regions over extreme concentration ranges. The set-up consists of four sensors simultaneously measuring pCO2, pCH4 (both flow-through, membrane-based non-dispersive infrared (NDIR) or tunable diode laser absorption spectroscopy (TDLAS) sensors), O2 and a thermosalinograph at high resolution from the same water source. The flexibility of the system allowed for deployment from freshwater to open ocean conditions on varying vessel sizes, where we managed to capture day–night cycles, repeat transects and also delineate small-scale variability. Our work demonstrates the need for increased spatiotemporal monitoring and shows a way of homogenizing methods and data streams in the ocean and limnic realms.
... Although significant progress has been made recognizing the importance of the LOAC as a whole system (e.g. Downing 2014;Xenopoulos et al. 2017), huge knowledge gaps are still present, particularly related to limited field data availability (Meinson et al. 2016). Often this is due to using different measuring techniques and protocols, both with respect to in-situ/autonomous observations and the collection of discrete data. ...
... Inland water investigations have also seen clear progress with the development of continuous, autonomous measurement techniques (e.g. Degrandpre et al. 1999;Baehr and Degrandpre 2004;Meinson et al. 2016;Brandt et al. 2017). Yet, only few studies have employed membrane-based equilibration sensors with NDIR detection (non-dispersive infrared spectrometry) (e.g. ...
... Although improvements can be made in terms of size and accessibility, this setup and data readings show the vitality of having high resolution multi-gas data for mapping and diel cycle extraction, which can further assist with modelling efforts and assessing concentrations and fluxes. Given there is much need for both high spatial data coverage and accurate concentrations for inland CO 2 and CH 4 measurements Meinson et al. 2016;Grinham et al. 2018), this type of dataset can help fill the gap in this specific region, and can further show areas of much needed improvement as previously suggested. This can enable better classification of regions, thus furthering monitoring activities and overall carbon budget investigations which benefit from enhanced data acquisitions on higher spatial and temporal resolutions. ...
Carbon dioxide (CO2) and methane (CH4) are major greenhouse gases (GHG) and have been under constant monitoring for decades. Both gases have significantly increased in recent years due to anthropogenic activities, with fossil fuel CO2 emissions peaking over 10GtCyr−1forthefirsttimeinhistoryin2018. This has huge detrimental repercussions within natural systems including the warming of the planet. Although these GHG are extremelysignificant,therearealsovastareasofstudywithlittletonodatainregardsto emissions and budgets. These gaps are mainly within the aquatic regions (or the Land Ocean Aquatic Continuum (LOAC)).As a consequence, there can be large discrepancies between budget numbers and in turn, scaling and future predictions. One of the main reasons for discrepancies is due to differing regimes between the land and ocean where the two systems use different practices to optimise the instruments and measuring standards. Oceanographers, for example, focus more on accuracy and precision due to far smaller concentrations and variability. In order to combine oceanographic and limnological methods this thesis presents a novel sensor package and show its application in multiple campaigns across the entire LOAC. The sensor set-up contained the sensors HydroC CO2 FT (pCO2), HydroC CH4 FT (CH4), HydroFlash O2 (O2) and a thermosalinograph for temperature and conductivity measuring all simultaneously. We extensively mapped inland regions and assessed the ways in which such high-resolution and accuracy measurements could potentially assist in filling some of these data gaps: First, the sensors’ capabilities were tested in a range of salinities (saline to fresh) and across a range of seasons (spring, summer and autumn). We found the sensors performed well in all regions, however, to fully appreciate the data, extensive corrections had to be applied, vital within inland regions. Following on from this we applied a simple model to calculate a continuous dataset for total alkalinity (TA) for the inland delta system. With this dataset, and our continuous pCO2 data, we were able to calculate the full carbonate system. We found the whole delta system to be supersaturated in regards to CO2, with each system (lakes, rivers or channels) showing very different dynamics. Both lakes and channels typically fluctuated between under and supersaturation (depending on season and region of the delta), while rivers were consistently supersaturated. Dissolved inorganic carbon (DIC) and O2 ratios were extracted for each region (∆DIC: ∆O2), showing lakes tending to be heavily influenced by regions adjacent to them, such as wetlands that typically had the highest ranges of DIC. On top of this spatial-variability extraction, by extensive mapping techniques we were able to assess the presence of diel cycles. We found that lakes tended to have a strong diel cycle, with pCO2 increasing during the night but typically returning to previous concentrations over the day. However, during these diel cycles, even though we observed a strong hysteresis, pCO2 rarely rose above saturation (∼ > 400 µatm). This led us on to the final section where we extracted full diel cycles. Due to CH4 being highly prominent in inland waters, the focus was mainly on the fluxes and concentrations. We found extreme diel cycles for CH4, even more so than with pCO2. In the lakes there was a clear hysteresis linking with sunrise and sunset. With the almost linear CH4 increase and O2 decrease during the night (molar CH4:O2 ratio 1:50) this led to the explanation of strong stratification during the day, followed by nocturnal convection during the night. This would release the build-up of CH4 in the bottom waters, mixing with the high O2 surface waters. This was further confirmed by the concentrations reducing to initial conditions, such as with pCO2, following sunrise as stratification occurred. In channels, however, this was slightly different yet still showed the potential of stratificationwithinthewaterbody,leadingtoCH4 build-up in the bottom waters before release following the mixing during the night. Channel concentrations varied roughly a magnitude larger than lakes, however all regions of the delta were supersaturated with CH4 in comparison with the atmosphere. We found channel CH4 concentrations and fluxes potentially being underestimated by up to +25% and +20% respectively when not including a full diel cycle. In lakes however, we found the opposite, with an overestimation in concentration and fluxes (+3.3% and +4.2%) when not considering the diel cycle, although this greatly depends on time of the sampling. Overall, this work presents a set-up that is capable to transverse across salinity boundaries, while gathering much needed, high-resolution, spatiotemporal data. We showed the possibilities that such a set-up can do, and the significance of sampling times in highly dynamic systems. These results confirm the existence of a diel cycle that, although have been noted before, are still not considered within the global budgets or within climate and environmental models.
... New developments in sensor and network technology promise advances in how high-frequency data can be collected in situ (Porter et al. 2005, Benson et al. 2009). Research groups around the world are interested in increasing the amount of data (Porter et al. 2005, Meinson et al. 2016. Physical and biological processes in lakes, for example effects of circulation patterns on nutrient cycling, metabolism and algal blooms, have been under comprehensive study during the past decades (Hamilton et al. 2014, Meinson et al. 2016. ...
... Research groups around the world are interested in increasing the amount of data (Porter et al. 2005, Meinson et al. 2016. Physical and biological processes in lakes, for example effects of circulation patterns on nutrient cycling, metabolism and algal blooms, have been under comprehensive study during the past decades (Hamilton et al. 2014, Meinson et al. 2016. Building new hypothesis and understanding previously unknown phenomena becomes possible by using AWQM as a part of traditional research or as a tool of its own (Williamson et al. 2014). ...
... Frequent time-series data is irreplaceable in designing environmental models for lakes and their catchment areas. However, well-designed AWQM networks have to be established to accomplish accurate data collection (Meinson et al. 2016). Instrument management is a key task in AWQM. ...
... An increasingly popular method for assessing metabolic rates of lakes is based on measuring changes in dissolved oxygen (DO) concentrations in the upper mixed layer, corrected for O 2 exchange at the air–water interface (Staehr et al. 2012). Collecting these data has been greatly facilitated by the advent of cheap data loggers mounted on buoys and teleconnection systems to transfer large amounts of high-frequency (HF) data (Laas et al. 2012, Alfonso et al. 2015, Meinson et al. 2015). These advances in data collection have been paralleled by the development of performant metabolic models based on Bayesian calculations that can reconstruct metabolic rates based on diel measurements of input parameters (Solomon et al. 2013). ...
... For 3 lakes (deep mesotrophic Saadjärv, shallow oligotrophic Äntu Sinijärv, and hypertrophic Erastvere) GPP:CR coupling was weaker than for the other lakes in our study, although the relatively low number of observations for Äntu Sinijärv and Saadjärv mitigates the robustness of the relationship. In deep stratified lakes like Saadjärv, most of the R occurring in the hypolimnion is not connected to the upper layers, which thus seem to have low CR:GPP coupling (Laas et al. 2015). In shallow oligotrophic Äntu Sinijärv, the water column is fed by CO 2 -rich groundwater springs that might blur the relationship between CO 2 and metabolic rates (Laas et al. 2015). ...
... In deep stratified lakes like Saadjärv, most of the R occurring in the hypolimnion is not connected to the upper layers, which thus seem to have low CR:GPP coupling (Laas et al. 2015). In shallow oligotrophic Äntu Sinijärv, the water column is fed by CO 2 -rich groundwater springs that might blur the relationship between CO 2 and metabolic rates (Laas et al. 2015). The absence of GPP:CR coupling in hypertrophic Lake Erastvere could be linked to an episode of cyanobacterial bloom during our experiment. ...
We employed a Bayesian model to assess the metabolic state of 8 Estonian lakes representing the 8 lake types according to the European Union Water Framework Directive. We hypothesized that long-term averages of light-related variables would be better predictors of lake metabolism than nutrient-related variables. Model input parameters were in situ high-frequency measurements of dissolved oxygen, temperature, and irradiance. Model simulations were conducted for several (5–12) diel cycles for each lake during the summer season. Accounting for uncertainty, the results from the Bayesian model revealed that 2 lakes were autotrophic for the duration of the experiment, 1 was heterotrophic, and 5 were balanced or had an ambiguous metabolic state. Cross-comparison with a traditional bookkeeping model showed that the majority of lakes were in metabolic balance. A strong coupling between primary production and respiration was observed, with the share of autochthonous primary production respired by consumers increasing with light extinction and nutrient-related variables. Unlike gross primary production, community respiration was strongly related to light extinction, dissolved organic carbon (DOC) and total phosphorus. These findings suggest that a drastic decrease in light-limited primary production along the DOC gradient counter-balanced nutrient supply in the darker lakes and thus blurred the relationship between primary production and nutrients. Thus, contrary to our hypothesis, both light and nutrient-related variables seemed to be good predictors of lake respiration and its coupling to lake primary production.
... Automated high-frequency measurements (AHFM) of chlorophyll fluorescence with buoys equipped with various sensors, allow insight into processes within a lake in subhourly timescales . This enables the study of the diurnal and seasonal variations of C Chl-a and lake metabolism in close details (Meinson et al., 2016) and provides a deeper insight into ecosystem dynamics, suits for assessing matter fluxes, and establishing precise chemical budgets (Rinke et al., 2013). AHFM systems are particularly useful to capture short-term events (e.g., cyanobacterial blooms) and fast water quality shifts in highly dynamic systems, together with enhancements in overall predictive capacity (Marcé et al., 2016). ...
... Profiling sensors in lakes give an overview of the vertical water column, while sensors deployed at fixed depths give information about one specific depth and location. Earlier, AHFM buoys were mainly equipped with underwater sensors to measure water temperature, electrical conductivity, pH, and dissolved oxygen properties, while information about biota, e.g., C Chl-a , was much scarcer (Meinson et al., 2016;Meinson, 2017). Over the last decade, most of the new AHFM systems have at least some sensors to detect algal pigment changes, and therefore many studies have also explained C Chl-a variability in lakes (Brentrup et al., 2016;Rusak et al., 2018). ...
Phytoplankton and its most common pigment chlorophyll a (Chl-a) are important parameters in characterizing lake ecosystems. We compared six methods to measure the concentration of Chl a (CChl-a) in two optically different lakes: stratified clear-water Lake Saadjärv and non-stratified turbid Lake Võrtsjärv. CChl-a was estimated from: in vitro (spectrophotometric, high-performance liquid chromatography); fluorescence (in situ automated high-frequency measurement (AHFM) buoys) and spectral (in situ high-frequency hyperspectral above-water radiometer (WISPStation), satellites Sentinel-3 OLCI and Sentinel-2 MSI) measurements. The agreement between methods ranged from weak (R 2 = 0.26) to strong (R 2 = 0.93). The consistency was better in turbid lake compared to the clear-water lake where the vertical and short-term temporal variability of the CChl-a was larger. The agreement between the methods depends on multiple factors, e.g., the environmental and in-water conditions, placement of sensors, sensitivity of algorithms. Also in case of some methods, seasonal bias can be detected in both lakes due to signal strength and background turbidity. The inherent differences of the methods should be studied before the synergistic use of data which will clearly increase the spatial (via satellites), temporal (AHFM buoy, WISPStation and satellites) and vertical (profiling AHFM buoy) coverage of data necessary to advance the research on phytoplankton dynamics in lakes.
... Moreover, because of the low sampling frequency, this approach often fails to capture the dynamics of biotic and abiotic processes within freshwater ecosystems. Despite the usefulness of traditional monitoring programs, the discrete nature of sampling means it is vital to fill the knowledge gaps related to short-lived, extremely episodic, or unpredictable events, and in general to any process with a characteristic temporal scale shorter than the sampling frequency (Jennings et al., 2012;Meinson et al., 2016). ...
... The limited spatial and temporal coverage of discrete monitoring methods prompted the development of alternative and complementary monitoring techniques. As regards algal pigment, during the last 2 decades, field fluorometers for in-situ measurement have become increasingly common worldwide (Marcé et al., 2016;Meinson et al., 2016). Fluorometric quantification of Chl-a and other common algal pigments such as phycocyanin and phycoerythrin is generally cost-effective and allows frequent observations during sudden phenomena such as mixing events or short-lived algal blooms (Jennings et al., 2012;Klug et al., 2012). ...
Lake Maggiore is a site of the Long-Term Ecosystem Research (LTER) network, belonging to the deep subalpine Lake District in Northern Italy. Studies on the physical, chemical, and biological features of the lake have been performed continuously since the 1980s. The lake recovered from eutrophication reaching the present oligotrophic condition. In the last decade, climate change represents the main driving factor for the long-term evolution of the lake, affecting its hydrodynamics, nutrient status, and biological communities. In 2020 a high-frequency monitoring (HFM) system was deployed, with the aim to integrate long-term monitoring based on discrete sampling and analysis. The system consists of a buoy equipped with sensors for limnological variables and algal pigments. The high-frequency monitoring program is part of a cross-border project between Italy and Switzerland focusing on lake quality monitoring as a critical input for successful lake management. In this paper we focus on Chlorophyll-a data, with the aim to test whether in-situ fluorescence measurements may provide a reliable estimate of lake phytoplankton biovolume and its seasonal dynamic. Sensor’s performance was regularly tested comparing chlorophyll-a data taken by the in-situ fluorescent sensors (Cyclops7, Turner Design), data from laboratory fluorescence analysis (FluoroProbe, BBE Moldaenke), values obtained from chlorophyll-a analysis by UV-VIS spectrophotometry and data from phytoplankton microscopy analysis. We found a general good agreement between the Chlorophyll-a data obtained with the different methods, confirming the use of in-situ sensors as a reliable approach to measure algal pigments, especially to assess their variability in the short-term, but also to describe the seasonal pattern of phytoplankton biovolume. However, phytoplankton community composition played a substantial role in the performance of the different methods and in the reliability of in-situ data as a tool to assess algal biovolume. This study demonstrates that high-frequency monitoring (HFM), used in conjunction with discrete chemical and biological monitoring, represents an important advance and support in the long-term monitoring of freshwaters and is a useful tool to detect ecological changes. Regular checking and validation of the sensor readings through laboratory analyses are important to get trustworthy data.
... A literature review of papers published from 2000 to 2015, carried out by Meinson et al. (2016), showed that more than two-thirds of the studies that used high-frequency monitoring in lakes were carried out in northern temperate zone, either in North America or in Europe. The authors, also showed that water temperature was the most common measured parameter, because of the sensor reasonable price and low maintenance and the most important, because water temperature is a controlling factor of biological, ecological and chemical processes (Meinson et al., 2016). ...
... A literature review of papers published from 2000 to 2015, carried out by Meinson et al. (2016), showed that more than two-thirds of the studies that used high-frequency monitoring in lakes were carried out in northern temperate zone, either in North America or in Europe. The authors, also showed that water temperature was the most common measured parameter, because of the sensor reasonable price and low maintenance and the most important, because water temperature is a controlling factor of biological, ecological and chemical processes (Meinson et al., 2016). ...
Urban lakes and reservoirs provide important ecosystem services. However, their water quality is being affected by anthropogenic pressures. The thermal regime is a strong driver of the vertical transport of nutrients, phytoplankton and oxygen. Thermal stratification can modify biogeochemical processes. In this paper, a three-dimensional hydrodynamic model was implemented and validated with high-frequency measurement of water temperature. The simulation results were in agreement with the measurements. For all simulation period, the model performance was evaluated based on hourly values, presenting a maximum RMSE of 0.65 ºC and Relative Error of 2.08%. The results show that high-frequency measurement associated with a three-dimensional model could help to understand and identify the reasons for the changes in the thermal condition of a shallow urban lake. The impact of the stream inflow on the temperature was highlighted, showing that during higher discharge events, when the river temperature is colder than the lake water, it flows into the lake deeper layers. The inflow water sank to the deeper layers where the lake morphology changes. The model showed an impact along the entire lake, showing the importance of monitoring the inflow water temperature. This modelling tool could be further used to study specific patterns of reservoir hydrodynamics.
... In addition, some LECs may not impact the whole lake, rather one isolated area. To make reasonable management decisions, monitoring data in sufficient temporal and spatial resolution to detect changes in LEC are necessary (Meinson et al., 2016). ...
... Even though there is no doubt about the usefulness of conventional monitoring programs, short-lived, extreme and unpredictable events with a temporal scale shorter than the sampling frequency of a traditional monitoring program can frequently go undetected (Marce et al., 2016). Automatic high-frequency monitoring (AHFM) with temporal resolution ranging down to the sub-minute level (Meinson et al., 2016) can help to overcome this problem (Rode et al., 2016). In the last decade profiling buoys equipped with high-frequency sensors have been increasingly deployed in limnology to document temporal and vertical lake dynamics (Brentrup et al., 2016). ...
Freshwater lakes are dynamic ecosystems and provide multiple ecosystem services to humans. Sudden changes in lake environmental conditions such as cyanobacterial blooms can negatively impact lake usage. Automated high-frequency monitoring (AHFM) systems allow the detection of short-lived extreme and unpredictable events and enable lake managers to take mitigation actions earlier than if basing decisions on conventional monitoring programmes. In this study a cost-benefit approach was used to compare the costs of implementing and running an AHFM system with its potential benefits for three case study lakes. It was shown that AHFM can help avoid human health impacts, lost recreation opportunities, and revenue losses for livestock, aquaculture and agriculture as well as reputational damages for drinking water treatment. Our results showed that the largest benefits of AHFM can be expected in prevention of human health impacts and reputational damages. The potential benefits of AHFM, however, do not always outweigh installation and operation costs. While for Lake Kinneret (Israel) over a 10-year period, the depreciated total benefits are higher than the depreciated total costs, this is not the case for Lough Gara (Ireland). For Lake Mälaren in Sweden it would depend on the configuration of the AHFM system, as well as on how the benefits are calculated. In general, the higher the frequency and severity of changes in lake environmental conditions associated with detrimental consequences for humans and the higher the number of lake users, the more likely it is that the application of an AHFM system is financially viable.
... continuous, autonomous measurement techniques (e.g. DeGrandpre et al., 1995;Baehr and DeGrandpre, 2004;Crawford et al., 2014;Meinson et al., 2016;Brandt et al., 2017). Yet, only few studies have employed membrane-based equilibration sensors with NDIR detection (non-dispersive infrared spectrometry) (e.g. ...
... Improvements can be made in terms of size, individual placement of the sensors and accessibility, however, this setup and 450 data readings show the vitality of having high spatiotemporal resolution multi-gas data for mapping and diel cycle extraction, which can further assist with modelling efforts and assessing concentrations and fluxes. Given there is much need for both high spatial data coverage and accurate concentrations for inland CO 2 and CH 4 measurements (Crawford et al., 2014;Meinson et al., 2016;Yoon et al., 2016;Natchimuthu et al., 2017;Grinham et al., 2018), this type of dataset can help fill the gap in this specific region, and can further show areas of much needed improvement as previously suggested. This can enable better 455 classification of regions, thus furthering monitoring activities and overall carbon budget investigations which benefit from enhanced data acquisitions on higher spatial and temporal resolutions. ...
Abstract. Comparatively the ocean and inland waters are two separate worlds, with concentrations in greenhouse gases having orders of magnitude in difference between the two. Together they create the Land-Ocean Aquatic Continuum (LOAC), which comprises itself largely of areas with little to no data in regards to understanding the global carbon system. Reasons for this include remote and inaccessible sample locations, often tedious methods that require collection of water samples and subsequent analysis in the lab, as well as the complex interplay of biological, physical and chemical processes. This has led to large inconsistencies, increasing errors and inevitably leading to potentially false upscaling. Here we demonstrate successful deployment in oceanic to remote inland regions, over extreme concentration ranges with multiple pre-existing oceanographic sensors combined set-up, allowing for highly detailed and accurate measurements. The set-up consists of sensors measuring p CO<sub>2</sub>, p CH<sub>4</sub> (both flow-through, membrane-based NDIR or TDLAS sensors), O<sub>2</sub>, and a thermosalinograph at high-resolution from the same water source simultaneously. The flexibility of the system allowed deployment from freshwater to open ocean conditions on varying vessel sizes, where we managed to capture day-night cycles, repeat transects and also delineate small scale variability. Our work demonstrates the need for increased spatiotemporal monitoring, and shows a way to homogenize methods and data streams in the ocean and limnic realms.
... Indeed, many AHFM systems have successfully been deployed across the globe and provide researchers with a wealth of information on changes in water quality, the physical environment, and carbon and nutrient cycling in response to anthropogenic and climatic drivers. 18 Science networks like Networking Lake Observatories in Europe (NETLAKE; www.dkit.ie/netlake) and the Global Lake Ecological Observatory Network (GLEON; www.gleon.org) ...
... 33 Applying AHFM on moving platforms (e.g., unmanned boats) allows for the detection of horizontal distribution patterns at scales never achievable by means of conventional sampling. 18 However, in large systems a single AHFM system may fail detecting a particular event, e.g. a phytoplankton bloom localized far from the AHFM system. Therefore, decision on how many sampling stations and their location is paramount for a successful AHFM application in a large system, which will depend on the management target (e.g., bloom detection) and previous knowledge of the system (common location and spatial heterogeneity of blooms). ...
Recent technological developments have increased the number of variables being monitored in lakes and reservoirs using automatic high frequency monitoring (AHFM). However, design of AHFM systems and posterior data handling and interpretation are currently being developed on a site-by-site and issue-by-issue basis with minimal standardization of protocols or knowledge sharing. As a result, many deployments become short-lived or underutilized, and many new scientific developments that are potentially useful for water management and environmental legislation remain underexplored. This Critical Review bridges scientific uses of AHFM with their applications by providing an overview of the current AHFM capabilities, together with examples of successful applications. We review the use of AHFM for maximizing the provision of ecosystem services supplied by lakes and reservoirs (consumptive and non consumptive uses, food production, and recreation), and for reporting lake status in the EU Water Framework Directive. We also highlight critical issues to enhance the application of AHFM, and suggest the establishment of appropriate networks to facilitate knowledge sharing and technological transfer between potential users. Finally, we give advice on how modern sensor technology can successfully be applied on a larger scale to the management of lakes and reservoirs and maximize the ecosystem services they provide.
http://pubs.acs.org/doi/pdfplus/10.1021/acs.est.6b01604
... There are about 117 million lakes in the world [3], but only a small fraction of them is included in in situ monitoring networks and the frequency of in situ monitoring is often limited. Increasing amount of lakes has been equipped with automated monitoring systems [4,5] that provided data with sufficient frequency. However, the number of lakes with such systems is still rather small. ...
... The small (10 m) pixel size of the Sentinel-2 MSI sensor is a great advantage in lake remote sensing as even very small lakes can be observed. However, several critical for lake remote sensing bands (5)(6)(7) are available with 20 m resolution. To make use of the full spectral resolution between 443 and 783 nm, we resampled MSI spectral bands 1-7 to a common 20 m pixel size. ...
The importance of lakes and reservoirs leads to the high need for monitoring lake water
quality both at local and global scales. The aim of the study was to test suitability of Sentinel-2 Multispectral Imager’s (MSI) data for mapping different lake water quality parameters. In situ data of chlorophyll a (Chl a), water color, colored dissolved organic matter (CDOM) and dissolved organic carbon (DOC) from nine small and two large lakes were compared with band ratio algorithms derived from Sentinel-2 Level-1C and atmospherically corrected (Sen2cor) Level-2A images. The height of the 705 nm peak was used for estimating Chl a. The suitability of the commonly used green to red band ratio was tested for estimating the CDOM, DOC and water color. Concurrent
reflectance measurements were not available. Therefore, we were not able to validate the performance of Sen2cor atmospheric correction available in the Sentinel-2 Toolbox. The shape and magnitude of water reflectance were consistent with our field measurements from previous years. However, the atmospheric correction reduced the correlation between the band ratio algorithms and water quality parameters indicating the need in better atmospheric correction. We were able to show that there is good correlation between band ratio algorithms calculated from Sentinel-2 MSI data and lake water parameters like Chl a (R2 = 0.83), CDOM (R2 = 0.72) and DOC (R2 = 0.92) concentrations as well as water color (R2 = 0.52). The in situ dataset was limited in number, but covered a reasonably wide range of optical water properties. These preliminary results allow us to assume that Sentinel-2 will be a valuable tool for lake monitoring and research, especially taking into account that the data will be
available routinely for many years, the imagery will be frequent, and free of charge.
... 3 Fluorescence and dissolved oxygen sensors are also increasingly used in characterizing physical and biogeochemical processes associated with the metabolic dynamics of lake ecosystems. 4,5 Capturing diel-scale temporal variation in dissolved oxygen, 6 the growth and cell division of phytoplankton biomass 7,8 and vertical migration of zooplankton 9,10 has strongly influenced the paradigms that address carbon and nutrient cycling at larger temporal scales. Simultaneous high-frequency measurements of different variables have also contributed to improve our understanding of aquatic ecosystems. ...
Water inherent optical properties (IOPs) contain integrative information on the optical constituents of surface waters. In lakes, IOP measurements have not been traditionally collected. This study describes how high-frequency IOP profiles can be used to document short-term physical and biogeochemical processes that ultimately influence the long-term trajectory of lake ecosystems. Between October 2018 and May 2020, we collected 1373 high-resolution hyperspectral IOP profiles in the uppermost 50 m of the large mesotrophic Lake Geneva (Switzerland-France), using an autonomous profiler. A data set of this size and content does not exist for any other lake. Results showed seasonal variations in the IOPs, following the expected dynamic of phytoplankton. We found systematic diel patterns in the IOPs. Phases of these diel cycles were consistent year-round, and amplitudes correlated to the diurnal variations of dissolved oxygen, clarifying the link between IOPs and phytoplankton metabolism. Diel amplitudes were largest in spring and summer under low wind condition. Wind-driven changes in thermal stratification impacted the dynamic of the IOPs, illustrating the potential of high-frequency profiles of water optical properties to increase our understanding of carbon cycling in lake ecosystems.
... High-frequency monitoring techniques offer a chance to detect the dynamics of cyanobacterial blooms and synchronous water quality. The amount of data obtained from high-frequency measurements is large even if only one set of sensors is placed into the water body for several days or months, which leads to more accurate analyses of highly dynamic processes (Meinson et al., 2016). ...
Cyanobacterial blooms are increasing in magnitude, frequency, and duration worldwide. However, our knowledge of cyanobacterial blooms dynamics and driving mechanisms is still limited due to their high spatiotemporal variability. To determine the potential driving mechanisms of cyanobacterial blooms in oligotrophic lakes, we collected a high-frequency depth profile of chlorophyll fluorescence (ChlF) and synchronous water quality, hydrometeorological data in early spring 2016 in oligotrophic Lake Qiandaohu. The vertical distribution of ChlF exhibited two patterns, “aggregated” and “discrete”, using Morisita's index, and the aggregated ChlF presented subsurface chlorophyll maxima during the thermal stratification period. The ChlF concentration was positively correlated with water temperature and negatively correlated with turbidity. Significantly linear relationships were observed between ChlF vertical structure parameters (e.g., Morisita's index, subsurface chlorophyll maxima depth and thickness) and thermal stratification parameters (e.g., mixing layer depth and relative water column stability). After rainstorm floods, the ChlF pattern suddenly change from “aggregated” to “discrete” and a ChlF concentration <1 μg/L was observed for 7–11 days with a significant increase in the mixing depth layer and turbidity. The results suggest that cyanobacterial blooms are robustly associated with thermal stratification and rainstorm floods in the deep and oligotrophic lake. Thermal stratification boosts surface phytoplankton accumulation by increasing water temperature, enhancing light availability and restricting phytoplankton vertical distribution. Rainstorm floods interrupt the accumulation by disrupting thermal stratification and decreasing the available light. Furthermore, wind speed and air temperature both regulate the phytoplankton dynamics by affecting thermal stratification. Our research quantifies the cyanobacterial bloom dynamics and their relationship between environmental factors, improving our knowledge of the driving mechanisms of cyanobacterial bloom for the protection of drinking water safety and aquatic organism health in lakes.
... A transition from manual sampling to high-frequency technologies as a standard tool in water quality monitoring is currently an ongoing trend not only in developed countries. Indeed, although the majority of high-frequency studies were undertaken in Europe and North America, as previously identified by Meinson et al. (2016), the rapid proliferation of such sensors are currently allowing its widespread use in the Middle East, South America, and Africa (Fig. 4). ...
Deterministic models have emerged as a widely accepted tool for investigations in lentic aquatic ecosystems. In this study, an extensive literature review is provided by an inventory of papers published over the last six years (2015–2020) to explore the recent progress of deterministic models applied to lakes and reservoirs. The current trends include the application of well-established models across broad ranges of time and spatial scales; the integration of lake, catchment and climate models, in addition to multi-model ensemble approaches; and the proliferation of high-frequency sensors and the usage of remote sensing images for model initialisation, forcing data inputs, and calibration and validation. It is expected that the emerging trends in modelling lakes and reservoirs can be of great use for future research prospects as a source of information for subsequent studies in the field.
... Recent advances in sensor technology can overcome the drawbacks of conventional monitoring, giving the opportunity to measure an increasing number of limnological and ecological parameters at unprecedented short temporal intervals and also during adverse meteorological events (Banas et al., 2005;Johnson et al., 2007;Le Vu et al., 2011;Jennings et al., 2012;Klug et al., 2012;Hamilton et al., 2014;Meinson et al., 2016). Over the past decade, there has been a drastic increase in the use of automated collection of high-frequency data in scientific research and environmental monitoring (Horsburgh et al., 2015). ...
A high frequency monitoring (HFM) system for the deep subalpine lakes Maggiore, Lugano and Como is under development within the EU INTERREG project SIMILE. The HFM system is designed to i) describe often neglected but potentially relevant processes occurring on short time scale; ii) become a cost-effective source of environmental data; and iii) strengthen the coordinated management of water resources in the subalpine lake district. In this project framework, a first HFM station (LM1) consisting of a monitoring buoy was placed in Lake Maggiore. LM1 represents a pilot experience within the project, aimed at providing the practical know-how needed for the development of the whole HFM system. To increase replicability and transferability, LM1 was developed in-house, and conceived as a low-cost modular system. LM1 is presently equipped with solar panels, a weather station, and sensors for water temperature, pH, dissolved oxygen, conductivity, and chlorophyll-a. In this study, we describe the main features of LM1 (hardware and software) and the adopted Quality Assurance/Quality Control (QA/QC) procedures. To this end, we provide examples from a test period, i.e., the first 9-months of functioning of LM1. A description of the software selected as data management software for the HFM system (IstSOS) is also provided. Data gathered during the study period provided clear evidence that coupling HFM and discrete sampling for QA/QC controls is necessary to produce accurate data and to detect and correct errors, mainly because of sensor fouling and calibration drift. These results also provide essential information to develop further the HFM system and shared protocols adapted to the local environmental (i.e., large subalpine lakes) and technical (expertise availability) context. Next challenge is making HFM not only a source of previously unaffordable information, but also a cost-effective tool for environmental monitoring.
... This can be of great importance for education and promotion of rational use of surface waterbodies. The literature proves that AHFM systems have been successfully deployed across the globe and provide researchers with a wealth of information on changes in water quality as a response to anthropogenic and climatic drivers ( Meinson, et al. 2016 ). ...
A method of the simultaneous reduction of external and internal load of phosphorus as a new solution for lake restoration is presented. A flow-through, stratified lake, with diverse morphometry was selected for the study. In all three parts of the lake, an oxygen deficit was noted at the lake bottom at peak summer stagnation, with a simultaneous increase in mineral forms of phosphorus (the concentration of orthophosphates at sites I, II and III reached 0.301, 0.318 and 0.395 mg P l⁻¹, respectively). Additionally, a large load of nutrients originating from the main inflow (annual load of 14395.9 kg P y⁻¹ and 16 4829.8 kg N y⁻¹), indicates that the conditions present in the lake are conducive to more intensive eutrophication. In this situation, reduction of the main loads of nutrients can be achieved by the simultaneous employment of pipelines delivering oxygenated water to the lake bottom during summer stagnation and a pipeline withdrawing deoxygenated and nutrient-rich water from the bottom in the vicinity of the outflow from the lake. It has been calculated that during the period of summer stagnation (VI-IX), the operation of delivering pipelines can reduce the phosphorus load from the main inflow by 5800.5 kg (40.3%). Using the pipeline withdrawing (site III), the amount of phosphorus removed from the lake would increase by 30.4% (from 2259.6 kg to 3247.8 kg). An additional solution, can be dosing the precipitating substances into the pipes delivering water to the lake, which will enable precise inactivation of phosphorus.
... The availability of sensors that record in situ has allowed automated measurements of several water constituents, including temperature and chlorophyll fluorescence (Meinson et al., 2016;Obrador et al., 2014). Chlorophyll fluorescence (ChlF) is a widely used proxy for Chl (Erickson et al., 2016), and ChlF measurements compare favorably with Chl concentrations measured using laboratory methods. ...
Subsurface chlorophyll maxima (SCM) are found in stratified lakes, reservoirs, and oceans. Spatial variations of the SCM magnitude, depth, and thickness during stratification and related factors were examined in a large, deep subtropical reservoir, Lake Qiandaohu. Significant spatial differences in the SCM parameters were found throughout the lake as thermal stratification developed in the late spring of 2014. SCM depth and thickness were positively correlated with euphotic depth and mixed layer depth but negatively correlated with epilimnetic nutrient concentrations. SCM magnitude was negatively correlated with euphotic depth and mixed layer depth and positively correlated with epilimnetic nutrient concentrations. Seasonal variations in SCM differed among subregions of the lake, which were related to seasonal differences in environmental parameters. SCM (averaging 66.2 mg/m² in spring and 96.4 mg/m² in summer) accounted for about 82% of the total areal chlorophyll of the water column (Tchl), and the SCM magnitude was better correlated with Tchl than the surface chlorophyll concentration. This study contributes to understanding of factors causing spatial variations in of SCM in the deep subtropical lakes.
... Therefore, spatial and temporal coverage and representativeness of traditional measurements are generally limited. During the last two decades, field spectrofluorometers to measure chlorophyll in situ have become increasingly common worldwide (Meinson et al., 2015). In the text, we use ''Chl a'' to refer to chlorophyll a concentration measured in laboratory, in contrast to ''Chl'' that refers to in situ fluorescence of chlorophyll. ...
Organic matter (OM) other than living phytoplankton is known to affect fluorometric in situ assessments of chlorophyll in lakes. For this reason, calibrating fluorometric measurements for OM error is important. In this study, chlorophyll (Chl) fluorescence was measured in situ in multiple Finnish lakes using two sondes equipped with Chl fluorometers (ex.470/em.650–700 nm). OM absorbance (A420) was measured from water samples, and one of the two sondes was also equipped with in situ fluorometer for OM (ex.350/em.430 nm). The sonde with Chl and OM fluorometers was also deployed continuously on an automated water quality monitoring station on Lake Konnevesi. For data from multiple lakes, inclusion of water colour estimates into the calibration model improved the predictability of Chl assessments markedly. When OM absorbance or in situ OM fluorescence was used in the calibration model, predictability between the in situ Chl and laboratory Chl a assessments was also enhanced. However, correction was not superior to the one done with the water colour estimate. Our results demonstrated that correction with water colour assessments or in situ measurements of OM fluorescence offers practical means to overcome the variation due to OM when assessing Chl in humic lakes in situ.
... Rapid development of in situ sensors and platforms allows higher frequency measurements of fluorescence, turbidity, oxygen, and other parameters on moorings or even on autonomous underwater vehicles (AUVs), creating 3D scans of lake parameters (Cremona et al. 2016, Meinson et al. 2016. Still, some measurements that require lab work will remain difficult to carry out at high frequency, such as measuring phytoplankton primary production (PP). ...
Lake productivity is fundamental to biogeochemical budgets as well as estimating ecological state and predicting future development. Combining modelling with Earth Observation data facilitates a new perspective for studying lake primary production. In this study, primary production was modelled in the large Lake Geneva using the MEdium Resolution Imaging Spectrometer (MERIS) image archive for 2002-2012. We used a semi-empirical model that estimates primary production as a function of photosynthetically absorbed radiation and quantum yield of carbon fixation. The necessary input parameters of the model-concentration of chlorophyll a, downwelling irradiance, and the diffuse attenuation coefficient-were obtained from MERIS products. The primary production maps allow us to study decennial temporal (with daily frequency) and spatial changes in this lake that a single sample point cannot provide. Modelled estimates agreed with in situ results (R 2 = 0.68) and showed a decreasing trend (∼27%) in production in Lake Geneva for the selected decade. Yet, in situ monitoring measurements missed the general increase of productivity near the incoming Rhône River. We show that the temporal and spatial resolution provided by satellite observations allows estimates of primary production at the basin-scale. The phytoplankton annual primary production was estimated as ∼302 (SD 20) g C m −2 yr −1 for Lake Geneva for 2003 to 2011. This study demonstrates that maps of primary production can be obtained even with reduced resolution (1200 m) MERIS data and relatively simple methods, and thereby calls for deeper integration of remote sensing products into conventional in situ observation approaches.
... Autonomous monitoring and in situ sensor technologies enable more comprehensive understanding of lake processes through space and time and are a growth area in aquatic monitoring and research (Meinson et al. 2015). Continuous, near-real-time ('streaming') data provides a range of benefits over and above pure research. ...
Lakes across the globe require help. The Lake Restoration Handbook: A New Zealand Perspective addresses this need through a series of chapters that draw on recent advances in modelling and monitoring tools, citizen science and First Peoples’ roles, catchment and lake-focused restoration techniques, and policy implementation. New Zealand lakes, like lakes across the globe, are subject to multiple pressures that have increased in severity and scale as land use has intensified, invasive species have spread and global climate change becomes manifest. This books builds on the popular Lake Managers Handbook (1987), which provided guidance on undertaking investigations into, and understanding lake ecosystems in New Zealand. The Lake Restoration Handbook: A New Zealand Perspective synthesises contemporary issues related to lake restoration and rehabilitation, integrated with social science and cultural viewpoints, and complemented by authoritative topic-area summaries by renowned scientists and practitioners from across the globe. The book examines the progress of lake restoration and the new and emerging tools available to managers for predicting and effecting change. The book will be a valuable resource for natural and social scientists, policy writers, lake managers, and anyone interested in the health of lake ecosystems.
... Analyzing limnological processes, their time scales, and their constraints requires a high amount of multivariate data, which are increasingly being collected in lakes worldwide (Marcé et al. 2016;Meinson et al. 2016). With automated highfrequency measurements, the temporal resolution has become almost unlimitedly high. ...
State variables in lake ecosystems are subject to processes that act on different time scales. The relative importance of each of these processes changes over time, e.g., due to varying constraints of physical, biological, and biogeochemical processes. Correspondingly, continuous automatic measurements at high temporal resolution often reveal intriguing patterns that can rarely be directly ascribed to single processes. In light of the rather complex interplay of such processes, disentangling them requires more powerful methods than researchers have applied up to this point. For this reason, we tested the potential of wavelet coherence, based on the assumption that different processes result in correlations between different variables, on different time scales and during different time windows across the seasons. The approach was tested on a set of multivariate hourly data measured between the onset of an ice cover and a cyanobacterial summer bloom in the year 2009 in the Müggelsee, a polymictic eutrophic lake. We found that processes such as photosynthesis and respiration, the growth and decay of phytoplankton biomass, dynamics in the CO2‐carbonate system, wind‐induced resuspension of particles, and vertical mixing all occasionally served as dominant drivers of the variability in our data. We therefore conclude that high‐resolution data and a method capable of analyzing time series in both the time and the frequency domain can help to enhance our understanding of the time scales and processes responsible for the high variability in driver variables and response variables, which in turn can lay the ground for mechanistic analyses.
... Over the past 15 yr, there have been rapid advances in electrochemical and optical sensor technology, which was spurred in large part, from the transition of analogue to digital technologies (Meinson et al. 2016). Now, due to reduced costs, increased sensitivity, and decreased maintenance requirements, the aquatic research community is poised to exploit the new sensor technology for the high-resolution biological and chemical monitoring of diverse inland aquatic systems. ...
Integration of inland waters into regional and global carbon (C) budgets requires a comprehensive understanding of factors regulating organic carbon (OC) delivery and in situ processing. This study reviews advances in optical, molecular, and isotopic approaches to resolve the sources, ages, and transformations of OC in aquatic systems. OC characterization using excitation emission matrix spectra, Fourier transform ion cyclotron mass spectrometry, and nuclear magnetic resonance provides detailed molecular level insight. Radiocarbon isotopic approaches and compound‐specific techniques resolve the input, metabolic fate, and turnover time of OC in ecosystems ranging in size from streams to the open ocean. Accumulating evidence suggests that aquatic OC is composed of diverse biogeochemical components. We conclude with enduring and emerging questions that underscore the role of inland systems in the global C cycle and propose unique combinations of approaches to better discern their role in the delivery and transformation of OC from soils to seas.
... However, data collection and analyses are labor intensive and expensive, often limiting the temporal resolution for groundwater assessments. Improvements in instrumentation and data transmission have led to the development of water quality monitoring instruments that analyze water chemistry (e.g., temperature, dissolved oxygen, specific conductance, pH, and nitrate) and transmit the data in real-time (Blaen et al. 2016;Pellerin et al. 2012), creating the opportunity for both high-frequency and long-term water quality monitoring networks (e.g., Meinson et al. 2016). ...
High-frequency, long-term monitoring of water quality has revolutionized the study of surface waters in recent years. However, application of these techniques to groundwater has been limited by the ability to remotely pump and analyze groundwater. This paper describes a novel autonomous groundwater quality monitoring system which samples multiple wells to evaluate temporal changes and identify trends in groundwater chemistry. The system, deployed near Fresno, California, USA, collects and transmits high-frequency data, including water temperature, specific conductance, pH, dissolved oxygen, and nitrate, from supply and monitoring wells, in real-time. The system consists of a water quality sonde and optical nitrate sensor, manifold, submersible three-phase pump, variable frequency drive, data collection platform, solar panels, and rechargeable battery bank. The manifold directs water from three wells to a single set of sensors, thereby reducing setup and operation costs associated with multi-sensor networks. Sampling multiple wells at high frequency for several years provided a means of monitoring the vertical distribution and transport of solutes in the aquifer. Initial results show short period variability of nitrate, specific conductivity, and dissolved oxygen in the shallow aquifer, while the deeper portion of the aquifer remains unchanged-observations that may be missed with traditional discrete sampling approaches. In this aquifer system, nitrate and specific conductance are increasing in the shallow aquifer, while invariant changes in deep groundwater chemistry likely reflect relatively slow groundwater flow. In contrast, systems with high groundwater velocity, such as karst aquifers, have been shown to exhibit higher-frequency groundwater chemistry changes. The stability of the deeper aquifer over the monitoring period was leveraged to develop estimates of measurement system uncertainty, which were typically lower than the manufacturer's stated specifications, enabling the identification of subtle variability in water chemistry that may have otherwise been missed.
... For all data, long embargo periods reduce the accuracy of forecasts, potentially rendering them obsolete before they can even be made. For example, high frequency limnology data typically take 2-5 y to appear in publications (38). Data embargo is driven, in part, by concern that data collectors will not receive sufficient credit (39), as well as concerns about releasing data that has not been fully vetted. ...
Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.
... Sharing data is one of the cornerstones of collaborative science. Over the last few decades, the increased use of automated sensors for lake monitoring (for reviews see Marcé et al. 2016;Meinson et al. 2015), and the availability of more and more "Big Data" from these systems, has fuelled a parallel increase in collaborative network science amongst limnologists, for example, through the Global Lake Ecological Observatory Network, GLEON (www.gleon.org;Weathers et al. 2013). ...
Sharing data is a keystone of collaborative science. A fundamental barrier, however, can be a lack of knowledge on what is being collected, where, and by whom. The aim of NETLAKE (COST Action ES1201) was to build a network of sites and individuals to support development and deployment of automatic sensor-based systems on lakes and reservoirs in Europe. To support this, NETLAKE developed a metadatabase which could provide answers to questions on where lakes were monitored, details on the frequency and duration of monitoring, contact details, and which sensors were being used. Development included challenges related to time and resources, and indeed to communication between lake scientists and database experts. In total, metadata for 71 European lakes were captured. The resulting data revealed interesting facts; for example, seven sites had archives that spanned over a decade, only seven of these lakes were used as drinking water sources, and one was a large fish pond. GLEON, the Global Lake Ecological Observatory Network, and two pan-American projects are now adding their metadata and the metadatabase is developing into a tool for the global community which can promote high frequency monitoring and facilitate network science. © 2017 Association for the Sciences of Limnology and Oceanography
... Automatic stations for high frequency measurements and remote sensing could improve the temporal and spatial representativeness of lake monitoring, although these methods can be also quite expensive. CDOM and DOC are measured with automatic stations only in 16 lakes around the world (Meinson et al., 2016). These stations are not part of the national surveillance monitoring programmes. ...
Organic matter (OM) has numerous geochemical and ecological functions in inland waters and can affect water quality. Different parameters of aquatic OM are measured with various methods as no single analytical tool can provide definitive structural or functional information about it. In the present paper we review different OM metrics used in the European Union (EU) lake surveillance monitoring programmes and assess their suitability to provide sufficient data about the brownification and enrichment with oxygen consuming substances in European lakes. In the EU Water Framework Directive (WFD), metrics of OM are not mandatory physico-chemical parameters, but only recommended parameters to characterize water transparency, oxygenation conditions or acidification status. Our analysis shows that, as lake OM is monitored under the WFD in only 14 countries, no Europe-wide conclusions on the situation regarding brownification and organic enrichment can be drawn based on these data. Applied parameters in lake surveillance monitoring programmes are biochemical oxygen demand (BOD), chemical oxygen demand (COD), total organic carbon (TOC), dissolved organic carbon (DOC), water colour (WCol), and yellow substance. Different national OM metrics used avoid getting a broad picture of lake OM concentration changes in Europe over the last decades. Furthermore, our results demonstrate that the possibilities to convert different OM parameters to each other are limited because empirical relationships between them are region-specific. OM sensors for continuous measurements and remote sensing surveys could improve the effectiveness of lake OM monitoring, especially its temporal and spatial representativeness. It would be highly suggested to include in lake monitoring programmes also methods (e.g. absorbance or fluorescence spectroscopy) allowing to characterize the composition of OM as it influences strongly the biogeochemical role of OM in lakes.
... We developed three EDDIE modules specifically for use in freshwater ecology courses to better prepare undergraduate students to participate in the use of long-term and high-frequency data. Many freshwater ecologists have embraced the use of automated sensors (Weathers et al. 2013, Meinson et al. 2016 and are using high-frequency data to address important ecological research questions, including drivers of whole lake metabolism (Solomon et al. 2013), lake responses to extreme events (Jennings et al. 2012, Klug et al. 2012, feedbacks between nutrient loading and hypoxia (Gerling et al. 2016), and the effects of climate change on lake thermal stratification and productivity (O'Reilly et al. 2003). The three modules were designed to address these emerging themes in freshwater ecology and help students learn quantitative skills (Box 1, Fig. 1). ...
Ecologists are increasingly analyzing long-term and high-frequency sensor datasets as part of their research. As ecology becomes a more data-rich scientific discipline, the next generation of ecologists needs to develop the quantitative literacy required to effectively analyze, visualize, and interpret large datasets. We developed and assessed three modules to teach undergraduate freshwater ecology students both scientific concepts and quantitative skills needed to work with large datasets. These modules covered key ecological topics of phenology, physical mixing, and the balance between primary production and respiration, using lakes as model systems with high-frequency or long-term data. Our assessment demonstrated that participating in these modules significantly increased student comfort using spreadsheet software and their self-reported competence in performing a variety of quantitative tasks. Interestingly, students with the lowest pre-module comfort and skills achieved the biggest gains. Furthermore, students reported that participating in the modules helped them better understand the concepts presented and that they appreciated practicing quantitative skills. Our approach demonstrates that working with large datasets in ecology classrooms helps undergraduate students develop the skills and knowledge needed to help solve complex ecological problems and be more prepared for a data-intensive future.
... Vertical patterns of ecosystem metabolism vary among chemically and morphologically diverse lakes (Obrador et al. 2014), but information on the drivers of metabolism below the upper mixed layer (epilimnion) remains limited. However, a recent expansion of high-frequency and depth-integrated monitoring of lakes provides an opportunity to extend our understanding of lake metabolism into the metalimnion (Staehr et al. 2010;Obrador et al. 2014;Meinson et al. 2015). ...
Many lakes exhibit seasonal stratification, during which they develop strong thermal and chemical gradients. An expansion of depth-integrated monitoring programs has provided insight into the importance of organic carbon processing that occurs below the upper mixed layer. However, the chemical and physical drivers of metabolism and metabolic coupling remain unresolved, especially in the metalimnion. In this depth zone, sharp gradients in key resources such as light and temperature co-occur with dynamic physical conditions that influence metabolic processes directly and simultaneously hamper the accurate tracing of biological activity. We evaluated the drivers of metalimnetic metabolism and its associated uncertainty across 10 stratified lakes in Europe and North America. We hypothesized that the metalimnion would contribute highly to whole-lake functioning in clear oligotrophic lakes, and that metabolic rates would be highly variable in unstable polymictic lakes. Depth-integrated rates of gross primary production (GPP) and ecosystem respiration (ER) were modelled from diel dissolved oxygen curves using a Bayesian approach. Metabolic estimates were more uncertain below the epilimnion, but uncertainty was not consistently related to lake morphology or mixing regime. Metalimnetic rates exhibited high day-to-day variability in all trophic states, with the metalimnetic contribution to daily whole-lake GPP and ER ranging from 0% to 87% and < 1% to 92%, respectively. Nonetheless, the metalimnion of low-nutrient lakes contributed strongly to whole-lake metabolism on average, driven by a collinear combination of highlight, low surface-water phosphorous concentration and high metalimnetic volume. Consequently, a single-sensor approach does not necessarily reflect whole-ecosystem carbon dynamics in stratified lakes.
... In particular, the short generation times of planktonic producers and consumers allow fast tracking of potentially complex trophic interactions, and the aquatic medium allows for straightforward measurements of ecosystem processes such as primary production and community respiration. Furthermore, technological developments have facilitated continuous depth-integrated measurements of basic lake characteristics (Meinson et al., 2015). Such high-frequency observations have fostered awareness of storm impacts on lake ecosystems (Jennings et al., 2012;Klug et al., 2012). ...
Extreme weather events can pervasively influence ecosystems. Observations in lakes indicate that severe storms in particular can have pronounced ecosystem-scale consequences, but the underlying mechanisms have not been rigorously assessed in experiments. One major effect of storms on lakes is the redistribution of mineral resources and plankton communities as a result of abrupt thermocline deepening. We aimed at elucidating the importance of this effect by mimicking in replicated large enclosures (each 9 m in diameter, ca. 20 m deep, ca. 1300 m³ in volume) a mixing event caused by a severe natural storm that was previously observed in a deep clear-water lake. Metabolic rates were derived from diel changes in vertical profiles of dissolved oxygen concentrations using a Bayesian modelling approach, based on high-frequency measurements. Experimental thermocline deepening stimulated daily gross primary production (GPP) in surface waters by an average of 63% for >4 weeks even though thermal stratification re-established within 5 days. Ecosystem respiration (ER) was tightly coupled to GPP, exceeding that in control enclosures by 53% over the same period. As GPP responded more strongly than ER, net ecosystem productivity (NEP) of the entire water column was also increased. These protracted increases in ecosystem metabolism and autotrophy were driven by a proliferation of inedible filamentous cyanobacteria released from light and nutrient limitation after they were entrained from below the thermocline into the surface water. Thus, thermocline deepening by a single severe storm can induce prolonged responses of lake ecosystem metabolism independent of other storm-induced effects, such as inputs of terrestrial materials by increased catchment run-off. This highlights that future shifts in frequency, severity or timing of storms are an important component of climate change, whose impacts on lake thermal structure will superimpose upon climate trends to influence algal dynamics and organic matter cycling in clear-water lakes.
... Additionally, given the superior ability of high frequency, sensor-based technologies to accurately detect and measure growing season or annual Chl-a maxima, future long-term sensor-based research studies will only improve the quantification and understanding of maximum:mean Chl-a ratios. Although to date sensor technologies have predominantly been applied to lakes (Hamilton et al. 2014, Meinson et al. 2015, these techniques will also increase our understanding of algal biomass dynamics in lotic systems. ...
To further clarify empirical relationships between maximum phytoplankton biomass per unit total phosphorus (TP) and the maximum:mean phytoplankton biomass ratio, predictive models were created from a meta-analysis of datasets from lakes worldwide. Peak concentrations of planktonic chlorophyll a were on average 2.6 times greater than the mean, with most maximum:mean chlorophyll a ratios falling within less than an order-of-magnitude band (from 1.2 to 6 times the mean value). Peak concentrations of planktonic algal biovolume in 22 Organisation for Economic Co-operation and Development (OECD) lakes were on average 3.3 times greater than the mean, with maximum:mean biovolume ratios ranging from 1.2 to 6.3. By contrast, the temporal dynamics of planktonic (suspended) algal biomass in Minnesota streams and rivers were far more constrained; peak concentrations of planktonic chlorophyll a were only on average 1.8 times greater than the mean, with maximum:mean chlorophyll a ratios ranging from 1.3 to 3.8. These data suggest regional differences in maximum chlorophyll a values may exist. Parallel analyses of periphyton biomass in streams and rivers showed far greater variability in the maximum:mean chlorophyll ratio for benthic algae. Peak concentrations of attached chlorophyll a were on average 4.3 times greater than the mean, with the observed maximum:mean chlorophyll a ratios exhibiting exceptionally high variability (ranging from 1.0 to 50 times the mean value), likely reflecting differences in the temporal dynamics of planktonic and benthic algal growth in freshwater ecosystems.
Managing ecosystems to effectively preserve function and services requires reliable tools that can infer changes in the stability and dynamics of a system. Conceptually, functional diversity (FD) appears as a sensitive and viable monitoring metric stemming from suggestions that FD is a universally important measure of biodiversity and has a mechanistic influence on ecological processes. It is however unclear whether changes in FD consistently occur prior to state responses or vice versa, with no current work on the temporal relationship between FD and state to support a transition towards trait‐based indicators. There is consequently a knowledge gap regarding when functioning changes relative to biodiversity change and where FD change falls in that sequence. We therefore examine the lagged relationship between planktonic FD and abundance‐based metrics of system state (e.g. biomass) across five highly monitored lake communities using both correlation and cutting edge non‐linear empirical dynamic modelling approaches. Overall, phytoplankton and zooplankton FD display synchrony with lake state but each lake is idiosyncratic in the strength of relationship. It is therefore unlikely that changes in plankton FD are identifiable before changes in more easily collected abundance metrics. These results highlight the power of empirical dynamic modelling in disentangling time lagged relationships in complex multivariate ecosystems, but suggest that FD cannot be generically viable as an early indicator. Individual lakes therefore require consideration of their specific context and any interpretation of FD across systems requires caution. However, FD still retains value as an alternative state measure or a trait representation of biodiversity when considered at the system level. Using species‐level plankton trait and abundance data from five highly monitored lakes, we determined the timing of functional diversity change relative to ecosystem state/functioning. Simple cross‐correlation and novel convergent cross mapping techniques revealed that planktonic functional diversity was weakly associated with state (with individual lakes displaying unique relationships), but that both measures changed simultaneously. This implies functional diversity is not a leading indicator of state change but contains additional information absent in the state measures used here.
Determining when a disturbance has occurred, its severity, and when the system recovered, is important to numerous questions in the aquatic sciences. This problem can be conceptualized as the timing and degree of perturbation from a typical state, and when the system returns to that typical state. We present an algorithm for detecting disturbance and recovery designed for high‐frequency time series, e.g., data produced by automated sampling devices in instrumented buoys and flux towers. The algorithm quantifies differences in the empirical cumulative distribution functions of moving windows over reference and evaluation periods, and is sensitive to changes in the mean, variance, and higher statistical moments. Tests on simulated data show it accurately identifies disturbance and recovery. Three case studies illustrate the application of our algorithm in different empirical settings. A case study on dissolved oxygen in a Florida, USA estuary following a hurricane identified the disturbance and recovery 73 d later. A case study on air temperature and net ecosystem exchange in the Florida everglades identified cold snaps coinciding with periods of reduced carbon uptake. A case study on rotifer abundance following zebra mussel invasion in the Hudson River, NY showed rotifer collapse following invasion and recovery over a decade later. Methods such as ours can improve understanding response to disturbance and facilitate comparative and synthetic study of disturbance impacts across ecosystems.
Regime shifts have large consequences for ecosystems and the services they provide. However, understanding the potential for, causes of, proximity to, and thresholds for regimes shifts in nearly all settings is difficult. Generic statistical indicators of resilience have been proposed and studied in a wide range of ecosystems as a method to detect when regime shifts are becoming more likely without direct knowledge of underlying system dynamics or thresholds. These early warning statistics (EWS) have been studied separately but there have been few examples that directly compare temporal and spatial EWS in ecosystem‐scale empirical data. To test these methods, we collected high‐frequency time series and high‐resolution spatial data during a whole‐lake fertilization experiment while also monitoring an adjacent reference lake. We calculated two common EWS, standard deviation and autocorrelation, in both time series and spatial data to evaluate their performance prior to the resulting algal bloom. We also applied the quickest detection method to generate binary alarms of resilience change from temporal EWS. One temporal EWS, rolling window standard deviation, provided advanced warning in most variables prior to the bloom, showing trends and between‐lake patterns consistent with theory. In contrast, temporal autocorrelation and both measures of spatial EWS (spatial SD, Moran's I) provided little or no warning. By compiling time series data from this and past experiments with and without nutrient additions, we were able to evaluate temporal EWS performance for both constant and changing resilience conditions. True positive alarm rates were 2.5 – 8.3 times higher for rolling window standard deviation when a lake was being pushed towards a bloom than the rate of false positives when it was not. For rolling window autocorrelation, alarm rates were much lower and no variable had a higher true positive than false positive alarm rate. Our findings suggest temporal EWS provide advanced warning of algal blooms and that this approach could help managers prepare for and/or minimize negative bloom impacts.
Due to the vertical migration of cyanobacteria and frequent wind waves disturbance, the floating, mixing, migration and accumulation of cyanobacteria bloom in Lake Taihu occur rapidly. It is very difficult to accurately capture cyanobacteria bloom occurrence and appearance using the traditional lake positioning and cross-section monitoring due to low temporal and spatial observation frequency and resolution, which limits the in-depth understanding of cyanobacteria bloom formation process, driving mechanism, prevention and control. Satellite remote sensing can realize the synchronous observation of the spatial distribution of cyanobacteria bloom, but it is difficult to capture the rapid dynamics of cyanobacteria bloom due to the limitation of observation frequency. Using independently developed land-based (ground-based, shore-based, or fixed on the platform, ship and pile foundation) hyperspectral water quality remote sensing instrument by the Hangzhou Hikvision Digital Technology Co., Ltd and Nanjing Zhongke Deep Insight Technology Research Institute Co., Ltd installed in Taihu Laboratory for Lake Ecosystem Research (TLLER) of Chinese Academy of Sciences, the short-term sudden and rapid cyanobacteria bloom dynamics in a day was effectively captured through the continuous observation of chlorophyll-a concentration and other key water quality parameters at the second-minute level. The results show that cyanobacteria are easy to float in the surface water under the conditions of breeze and light wind, and the prevailing northwest wind drives the cyanobacteria bloom in the open water area of the lake to float and accumulate to the shore of TLLER quickly. Chlorophyll-a concentration in surface water can rapidly rise from 10 μg/L to more than 100 μg/L in just half an hour. Several chlorophyll-a peaks are recorded in a day from 8:30 to 18:30. All these results clearly show that cyanobacteria have a rapid hourly dynamic change process. Affected by the rapid hourly variations of cyanobacteria, water quality parameters such as secchi disc depth, total nitrogen, total phosphorus and chemical oxygen demand also show rapid hourly variations. Significantly negative relationship between chlorophyll-a and secchi disc depth but significantly positive relationships between chlorophyll-a and total nitrogen, total phosphorus, chemical oxygen demand are found, which indicate short-term floating and gathering of cyanobacteria have a profound impact on the water quality of lakes.
To measure chlorophyll a (Chl a) fluorescence (Fchl), fluorometers use an excitation wavelength that is within the visible spectrum of most zooplankton, and as a result has the potential to cause a phototactic response in zooplankton. The transparent bodies of herbivorous zooplankton may allow viable chlorophyll a within an individual's digestive tract to fluoresce in response to sensor excitation light, resulting in measurement bias. To test for this bias, a fully factorial (± zooplankton and ± light) experiment was conducted in an oligotrophic lake. Excitation light from fluorometers triggered a positive phototactic response during nighttime hours, resulting in swarms of zooplankton congregating beneath the sensor. The maximum hourly mean Fchl from nighttime/open treatments was higher and more variable than nighttime/zooplankton exclusion treatments, with the greatest single hour difference of 7.34 relative fluorescence units (RFU) vs. 0.26 RFU. In open treatments, sustained periods of Fchl exceeded 31x the values of exclusion treatments. A second series of experiments pulsed excitation lights in alternating periods in order to characterize zooplankton response times. Sensor bias was detected in as little as 20 s after initial illumination. Collectively, these results suggest that swarms of phototactic zooplankton can cause substantial bias in Fchl measurements at night. To correct for this bias, post‐processing methods using time series decomposition were demonstrated to remove the majority of Fchl bias.
The use of reference conditions is essential to the monitoring and management of aquatic ecosystems. We examined existing and potential reference sites through historical data, maps, and field data collected from river sites in KwaZulu-Natal (KZN), South Africa. In our study, we applied nine criteria that best reflect the characteristics of South African rivers on 24 a priori selected reference sites. These nine criteria comprised of catchment conditions (flow modification and natural landscape) and site-specific attributes (water quality, human disturbance, river channel, water abstraction, riparian vegetation, riparian zone modification, and instream habitat quality). The a priori selected reference sites were subjected to validation using multivariate methods, such as analysis of similarities (ANOSIM), similarity percentages (SIMPER), and non-parametric multidimensional scaling (MDS) based on the macroinvertebrate fauna by applying a SASS5 threshold considered to be an indicator of undisturbed sites in South African rivers. We identified differences in the macroinvertebrate assemblages of the reference conditions for each river group based on their ecoregions, geomorphology and seasonal variations. Ecoregions and river geomorphology were better in the grouping of sites with similar reference conditions than the seasons. Our findings indicated that all of the selected sites could be considered as valid reference sites; however, caution should be taken in applying this method to lowland rivers because of their noticeable seasonal variability and habitat instability which tend to alter their reference states. We recommend that a type-specific reference condition be developed for lowland rivers. Also, statistical validation of reference conditions should be a continuous process in river biomonitoring.
Las lagunas de la región pampeana son ambientes naturales que poseen la particularidad de “atraparnos” por diferentes razones. Quizás sea por la tranquilidad que trasmiten sus aguas, el sonido del oleaje, el silencio, su aire fresco y renovador, sus amaneceres, sus atardeceres, el sonido de algunas aves, el disfrute de la pesca o por el contacto con la naturaleza. Este libro es una invitación a emprender un viaje, recorrer un camino que nos lleve imaginariamente a una laguna, tomando como caso La Barrancosa, para visualizarla, conocerla, valorarla, protegerla, usarla y disfrutarla responsablemente. El objetivo es dar a conocer diferentes aspectos de las lagunas pampeanas con énfasis en La Barrancosa. Se tiende a que el lector sepa de su existencia, su dinámica, sus factores determinantes, sus bienes y servicios ecológicos, su fragilidad, su pertenencia e identificación con el paisaje folklórico pampeano, sus organismos constituyentes, sus relaciones tróficas, sus vínculos con el hombre actual y del pasado, en definitiva que sean consideradas un escenario propicio para lograr el acercamiento y respeto hacia la Naturaleza y sus diferentes formas de vida. Destino: La Barrancosa. Una invitación a conocer lagunas pampeanas intenta trasmitir esa pasión por las lagunas y compartir conocimientos con un público amplio: docentes y estudiantes de distintos niveles educativos, científicos, productores agropecuarios, pescadores, prestadores turísticos, concesionarios de lagunas, funcionarios, ONGs ambientalistas y público en general.
Las lagunas de la región pampeana son ambientes naturales que poseen la particularidad de “atraparnos” por diferentes razones. Quizás sea por la tranquilidad que trasmiten sus aguas, el sonido del oleaje, el silencio, su aire fresco y renovador, sus amaneceres, sus atardeceres, el sonido de algunas aves, el disfrute de la pesca o por el contacto con la naturaleza. Este libro es una invitación a emprender un viaje, recorrer un camino que nos lleve imaginariamente a una laguna, tomando como caso La Barrancosa, para visualizarla, conocerla, valorarla, protegerla, usarla y disfrutarla responsablemente. El objetivo es dar a conocer diferentes aspectos de las lagunas pampeanas con énfasis en La Barrancosa. Se tiende a que el lector sepa de su existencia, su dinámica, sus factores determinantes, sus bienes y servicios ecológicos, su fragilidad, su pertenencia e identificación con el paisaje folklórico pampeano, sus organismos constituyentes, sus relaciones tróficas, sus vínculos con el hombre actual y del pasado, en definitiva que sean consideradas un escenario propicio para lograr el acercamiento y respeto hacia la Naturaleza y sus diferentes formas de vida. Destino: La Barrancosa. Una invitación a conocer lagunas pampeanas intenta trasmitir esa pasión por las lagunas y compartir conocimientos con un público amplio: docentes y estudiantes de distintos niveles educativos, científicos, productores agropecuarios, pescadores, prestadores turísticos, concesionarios de lagunas, funcionarios, ONGs ambientalistas y público en general
Las lagunas de la región pampeana son ambientes naturales que poseen la particularidad de “atraparnos” por diferentes razones. Quizás sea por la tranquilidad que trasmiten sus aguas, el sonido del oleaje, el silencio, su aire fresco y renovador, sus amaneceres, sus atardeceres, el sonido de algunas aves, el disfrute de la pesca o por el contacto con la naturaleza. Este libro es una invitación a emprender un viaje, recorrer un camino que nos lleve imaginariamente a una laguna, tomando como caso La Barrancosa, para visualizarla, conocerla, valorarla, protegerla, usarla y disfrutarla responsablemente.
El objetivo es dar a conocer diferentes aspectos de las lagunas pampeanas con énfasis en La Barrancosa. Se tiende a que el lector sepa de su existencia, su dinámica, sus factores determinantes, sus bienes y servicios ecológicos, su fragilidad, su pertenencia e identificación con el paisaje folklórico pampeano, sus organismos constituyentes, sus relaciones tróficas, sus vínculos con el hombre actual y del pasado, en definitiva que sean consideradas un escenario propicio para lograr el acercamiento y respeto hacia la Naturaleza y sus diferentes formas de vida.
Destino: La Barrancosa. Una invitación a conocer lagunas pampeanas intenta trasmitir esa pasión por las lagunas y compartir conocimientos con un público amplio: docentes y estudiantes de distintos niveles educativos, científicos, productores agropecuarios, pescadores, prestadores turísticos, concesionarios de lagunas, funcionarios, ONGs ambientalistas y público en general.
The central aim of this thesis is to demonstrate the benefits of innovative frequency-based methods to better explain the variability observed in lake ecosystems. Freshwater ecosystems may be the most threatened part of the hydrosphere. Lake ecosystems are particularly sensitive to changes in climate and land use because they integrate disturbances across their entire catchment. This makes understanding the dynamics of lake ecosystems an intriguing and important research priority. This thesis adds new findings to the baseline knowledge regarding variability in lake ecosystems. It provides a literature-based, data-driven and methodological framework for the investigation of variability and patterns in environmental parameters in the time frequency domain. Observational data often show considerable variability in the environmental parameters of lake ecosystems. This variability is mostly driven by a plethora of periodic and stochastic processes inside and outside the ecosystems. These run in parallel and may operate at vastly different time scales, ranging from seconds to decades. In measured data, all of these signals are superimposed, and dominant processes may obscure the signals of other processes, particularly when analyzing mean values over long time scales. Dominant signals are often caused by phenomena at long time scales like seasonal cycles, and most of these are well understood in the limnological literature. The variability injected by biological, chemical and physical processes operating at smaller time scales is less well understood. However, variability affects the state and health of lake ecosystems at all time scales. Besides measuring time series at sufficiently high temporal resolution, the investigation of the full spectrum of variability requires innovative methods of analysis. Analyzing observational data in the time frequency domain allows to identify variability at different time scales and facilitates their attribution to specific processes. The merit of this approach is subsequently demonstrated in three case studies. The first study uses a conceptual analysis to demonstrate the importance of time scales for the detection of ecosystem responses to climate change. These responses often occur during critical time windows in the year, may exhibit a time lag and can be driven by the exceedance of thresholds in their drivers. This can only be detected if the temporal resolution of the data is high enough. The second study applies Fast Fourier Transform spectral analysis to two decades of daily water temperature measurements to show how temporal and spatial scales of water temperature variability can serve as an indicator for mixing in a shallow, polymictic lake. The final study uses wavelet coherence as a diagnostic tool for limnology on a multivariate high-frequency data set recorded between the onset of ice cover and a cyanobacteria summer bloom in the year 2009 in a polymictic lake. Synchronicities among limnological and meteorological time series in narrow frequency bands were used to identify and disentangle prevailing limnological processes. Beyond the novel empirical findings reported in the three case studies, this thesis aims to more generally be of interest to researchers dealing with now increasingly available time series data at high temporal resolution. A set of innovative methods to attribute patterns to processes, their drivers and constraints is provided to help make more efficient use of this kind of data.
We employed a Bayesian model to assess the metabolic state of 8 Estonian lakes representing the 8 lake types according to the European Union Water Framework Directive. We hypothesized that long-term averages of light-related variables would be better predictors of lake metabolism than nutrient-related variables. Model input parameters were in situ high-frequency measurements of dissolved oxygen, temperature, and irradiance. Model simulations were conducted for several (5–12) diel cycles for each lake during the summer season. Accounting for uncertainty, the results from the Bayesian model revealed that 2 lakes were autotrophic for the duration of the experiment, 1 was heterotrophic, and 5 were balanced or had an ambiguous metabolic state. Cross-comparison with a traditional bookkeeping model showed that the majority of lakes were in metabolic balance. A strong coupling between primary production and respiration was observed, with the share of autochthonous primary production respired by consumers increasing with light extinction and nutrient-related variables. Unlike gross primary production, community respiration was strongly related to light extinction, dissolved organic carbon (DOC) and total phosphorus. These findings suggest that a drastic decrease in light-limited primary production along the DOC gradient counter-balanced nutrient supply in the darker lakes and thus blurred the relationship between primary production and nutrients. Thus, contrary to our hypothesis, both light and nutrient-related variables seemed to be good predictors of lake respiration and its coupling to lake primary production.
China has become the fifth leading nation in terms of its share of the world's scientific publications. The citation rate of papers with a Chinese address for the corresponding author also exhibits exponential growth. More specifically, China has become a major player in critical technologies like nanotechnology. Although it is difficult to delineate nanoscience and nanotechnology, we show that China has recently achieved a position second only to that of the USA. Funding for R&D has been growing exponentially, but since 1997 even more in terms of business expenditure than in terms of government expenditure. It seems that the Chinese government has effectively used the public-sector research potential to boost the knowledge-based economy of the country. Thus, China may be achieving the ("Lisbon") objectives of the transition to a knowledge-based economy more broadly and rapidly than its western counterparts. Because of the sustained increase in Chinese government funding and the virtually unlimited reservoir of highly-skilled human resources, one may expect a continuation of this growth pattern in the near future.
Observations are presented from Lake Biwa and Lake Kinneret showing the ubiquitous and often periodic nature of high-frequency internal waves in large stratified lakes. In both lakes, high-frequency wave events were observed within two distinct categories: (1) Vertical mode 1 solitary waves near a steepened Kelvin wave front and vertical mode 2 solitary waves at the head of an intrusive thermocline jet were found to have wavelengths similar to64-670 m and similar to13-65 m, respectively, and were observed to excite a spectral energy peak near 10(-3) Hz. (2) Sinusoidal vertical mode 1 waves on the crests of Kelvin waves (vertically coherent in both phase and frequency) and bordering the thermocline jets in the high shear region trailing the vertical mode 2 solitary waves (vertically incoherent in both phase and frequency) were found to have wavelengths between 28-37 and 9-35 m, respectively, and excited a spectral energy peak just below the local maximum buoyancy frequency near 10(-2) Hz. The waves in wave event categories 1 and 2 were reasonably described by nonlinear wave and linear stability models, respectively. Analysis of the energetics of these waves suggests that the waves associated with shear instability will dissipate their energy rapidly within the lake interior and are thus responsible for patchy turbulent events that have been observed within the metalimnion. Conversely, the finite-amplitude solitary waves, which each contain as much as 1% of the basin-scale Kelvin wave energy, will propagate to the lake perimeter where they can shoal, thus contributing to the maintenance of the benthic boundary layer.
Net ecosystem production (NEP) is the difference between gross primary production (GPP) and community respiration (R). We estimated in situ NEP using three independent approaches (net CO2 gas flux, net O-2 gas flux, and continuous diel O-2 measurements) over a 4-7 yr period in a series of small lakes in which food webs were manipulated and nutrient loadings were experimentally varied. In the absence of manipulation, these lakes were net heterotrophic according to all three approaches. NEP (NEP = GPP-R) was consistently negative and averaged -35.5 +/- 3.7 (standard error) mmol C m(-2) d(-1). Nutrient enrichment, in the absence of strong planktivory, tended to cause increases in estimates of both GPP and R (estimated from the continuous O-2 data) but resulted in little change in the GPP/R ratio, which remained <1, or NEP, which remained negative. When planktivorous fish dominated the food web, large zooplankton were rare and nutrient enrichment produced positive values of NEP by all three methods. Among lakes and years, daily values of NEP ranged from -241 to +175 mmol m(-2) d(-1); mean seasonal NEP was positive only under a combination of high nutrient loading and a planktivore-dominated food web. Community R is significantly subsidized by allochthonous sources of organic matter in these lakes. Combining all lakes and years, we estimate that 26 mmol C m(-2) d(-1) of allochthonous origin is respired on average. This respiration of allochthonous organic matter represents 13 to 43% of total R, and this fraction declines with increasing GPP.
To characterize the spatial variability of metabolism estimates (gross primary production [GPP], respiration [R], and net ecosystem production [NEP]) in two Northern Wisconsin lakes, we collected data from 27 and 35 dissolved oxygen sensors placed in a two-dimensional array throughout the upper mixed layers over a period of 10 d per lake in midsummer. Averaged over the deployment, aerial metabolism estimates among sensor locations varied 1-2 orders of magnitude and were largely unrelated to physical habitat within the lake. For all sites and days, 76-90% of the explainable variance in GPP and R was attributable to location in the lake rather than day of the deployment. NEP, on the other hand, was less affected by location, with 79-93% of the explained variance attributable to the day of the deployment. Single-location estimates can yield errors of more than an order of magnitude in estimates of daily GPP and R and can mischaracterize the trophic status of the lake. Using a rarefaction approach, we found that using four randomly placed sensors increased the precision of the resulting daily metabolism estimates fourfold over single-location measures in both lakes.
This paper presents an extensive investigation of the mixing processes occurring in the subtropical monomictic Advancetown Lake, which is the main water body supplying the Gold Coast City in Australia. Meteorological, chemical and physical data were collected from weather stations, laboratory analysis of grab samples and an in-situ Vertical Profiling System (VPS), for the period 2008-2012. This comprehensive, high frequency dataset was utilised to develop a one-dimensional model of the vertical transport and mixing processes occurring along the water column. Multivariate analysis revealed that air temperature and rain forecasts enabled a reliable prediction of the strength of the lake stratification. Vertical diffusion is the main process driving vertical mixing, particularly during winter circulation. However, a high reservoir volume and warm winters can limit the degree of winter mixing, causing only partial circulation to occur, as was the case in 2013. This research study provides a comprehensive approach for understanding and predicting mixing processes for similar lakes, whenever high-frequency data are available from VPS or other autonomous water monitoring systems.
Studies based on continuous monitoring of diel changes in dissolved oxygen concentration allow the estimation of ecosystem
metabolism and provide a measure of the overall trophic processes of an ecosystem. In this study, net ecosystem production (NEP), community/ecosystem respiration (R), and gross primary production (GPP) rates were estimated in relation to physicochemical and climatic variables for 18 months in La Salada, a saline shallow lake. Net autotrophic conditions prevailed during the study period (NEP: 64.05 ± 44.22 mmol O2 m−2 day−1). GPP and R were positively correlated and were synchronized on a daily timescale, with GPP typically greater than R. Principal component analysis revealed that monthly rates of GPP, R, and NEP responded, as expected, to temperature and light seasonal patterns. Water level and conductivity fluctuations, because of evapoconcentration and water management, were relevant as a driver of the physicochemical and biological characteristics of the lake. In saline lakes as La Salada, an adequate management of water resources will be relevant to maintain the ecosystem equilibrium and the quality of its resources.
Automated in situ sensors for measuring changes in dissolved oxygen (DO) at high frequency have facilitated estimates of gross primary production (GPP) and respiration (R) in aquatic systems. Lake researchers usually rely on a single sensor for these estimates, but such point measurements may miss important spatial heterogeneity in within-lake processes and may not accurately represent systemwide values of metabolism. Here we combine simultaneous measurements of metabolism using DO sensors along transects from the shore to the center of a lake with a spatial model to better understand the underlying heterogeneity in processes contributing to whole-lake epilimnetic metabolism. We use this model to achieve better estimates of epilimnetic GPP and R and to determine the relative contributions of benthic-littoral vs. pelagic processes to these estimates. We compared the spatially explicit process-based model to estimates of metabolism from both a single sensor at the lake's center and a spatially explicit averaging of multiple sensor sites. Estimates of both GPP and R varied on average 2.5- to 3.2-fold from site to site within the same lake, whereas variations were sometimes as high as 6-to 7-fold. Estimates of GPP and R near the perimeter of lakes were on average greater than measurements in the middle of the lake. Our model estimates that benthic-littoral processes accounted for ∼40% of epilimnetic GPP and R. A single, centrally located sensor often misses a significant component of this benthic metabolism and accounts for only ∼81% of lakewide GPP and R. © 2007, by the American Society of Limnology and Oceanography, Inc.
Knowledge of the horizontal and vertical distribution and habitat use of fish in lakes provides insights into the ecology, evolution and conservation of a species. Using high-resolution, high-frequency sampling, we provide an account of the distribution and movements of adult European grayling, Thymallus thymallus, in a recently colonised subarctic lake. We evaluated summer home range size, daily and seasonal patterns in vertical movement and vertical distribution of individuals relative to the summer thermocline. There was an allometric relationship between body size and home range area. Individuals showed diverse patterns of daily movement and some clear circadian cycles, likely mediated by light. All individuals that were monitored during the winter under ice were within 2 m of the surface. Most fish associated with the thermocline during the period for which we were able to estimate its centre point. We propose that the patterns we observed are primarily driven by foraging opportunity and that foraging tactics differ between individuals and seasons.
We are entering an era of big data – data sets that are characterised by high volume, velocity, variety, exhaustivity, resolution and indexicality, relationality and flexibility. Much of these data are spatially and temporally referenced and offer many possibilities for enhancing geographical understanding, including for post-positivist scholars. Big data also, however, poses a number of challenges and risks to geographic scholarship and raises a number of taxing epistemological, methodological and ethical questions. Geographers need to grasp the opportunities whilst at the same time tackling the challenges, ameliorating the risks and thinking critically about big data as well as conducting big data studies. Failing to do so could be quite costly as the discipline gets left behind as others leverage insights from the growing data deluge.
What can we expect to find beyond Big Data? And how can we exploit Big Data to get there?
Wind-driven mixing in the epilimnion of a deep lake can be suppressed when there is a weak near surface stratification, which occurs frequently during periods of strong solar heating and weak winds. Using data from a vertical chain of fast response thermistors, we analyze the frequency of near surface stratification in the top 2 meters of the epilimnion in Lake Opeongo, Ontario for the periods between May and August in 2009 and 2010. Near surface thermoclines (as defined by dT/dz > 0.2 °C m−1 between 1 and 2 m) occur for 24% of the sampling period in 2009, 37% of the sampling period in 2010 and correspond to periods of high values of gradient Richardson number. During daytime the epilimnion is stratified up to 45% of the time. At night, cooling generally leads to a more isothermal profile, but near surface thermoclines still form at least 20% of the time. Extended periods of near surface stratification (>1 h), account for more than 80% of the stratified period. We compare these findings with previous observations from the Experimental Lakes Area in Northern Ontario, and discuss the biological implications of episodic stratification.
Persistent weak temperature stratification characterizes the epilimnion of Lake Opeongo, Ontario, Canada, and reduces the magnitude of turbulent mixing. Throughout July and August 2009, the epilimnion was isothermal for only 34 % of the record, while for 28 % of the record there was at least a 2 °C temperature difference across the 5 m deep epilimnion. During these stratified periods, there were increases in gradient Richardson numbers (Ri g ), and decreases in rates of dissipation of turbulent kinetic energy ( ε ), the turbulence activity parameter (I = ε/νN 2), an indicator of active mixing, and vertical eddy diffusivity (K z ) inferred from temperature microstructure profiles. During periods of shear induced mixing, values of ε approached 10−6 m2 s−3 and decreased during periods of increasing Ri g . For 0 < Ri g < 1, average values of I were ~1,000 and values of K z were slightly higher than 10−4 m2 s−1. For Ri g >1, average values of I were ~300 and K z was reduced by one to three orders of magnitude. Mixing during cold fronts occurred over time scales of minutes to hours, which worked to erode diurnal thermoclines. However, during periods of persistent secondary thermoclines, mixing was suppressed throughout the epilimnion.
Climate change-derived higher air temperatures and the resulting increase in lake surface temperatures are known to influence the physical, biological and chemical processes of water bodies. By using hydrodynamic lake models coupled with regional climate models the potential future impact of a changing climate can be investigated. The present study hence elucidates limno-physical changes at the peri-Alpine, 83-m deep, currently dimictic Ammersee in southeastern Germany, both to underline the role of lakes as sentinels of climate change and provide a sound basis for further limnological investigations. This was realised by using water temperatures simulated with the hydrodynamic model DYRESM for the period 2041-2050, based on the results of the regional climate model REMO (IPCC A1B emission scenario). Modelling of future heat content resulted in a projected increase in the upper 3 m of the epilimnion from end of March to mid-November, whereas a decrease in future total heat content (January-December) of the entire water column was simulated compared to that observed in 1997-2007. Lake thermal stability is projected to be higher in the period 2041-2050 than in 1985-2007. Stratification is expected to occur earlier and to last longer in the future than the pattern observed in 1985-2007. The future mean May-June depth of the thermocline is simulated to be situated above its past average vertical position, whereas an increase of mean thermocline depth is projected for the beginning of August to October. Furthermore, the mean May-October thickness of the metalimnion is simulated to increase. Additionally, we investigated the sensitivity of these limno-physical results to changes in the model parameter light extinction coefficient which determines how the solar radiation is absorbed by the lake water. The elucidation of physical changes at Ammersee by means of a regional climate model provides a sound basis on which to face the new challenges of lake modelling.
Vertical and horizontal exchanges in Pilkington Bay, a shallow (9 m) embayment of Lake Victoria, were determined from a surface energy budget, time series measurements of temperature, and quasi synoptic transects of conductivity, temperature, and depth conducted over a 2-d period. The surface energy budget is the first from a tropical lake over a diurnal timescale. Strong stratification developed during morning and early afternoon (>40 cycles h-1) but was eroded beginning in the afternoon by the combination of wind and heat loss. Surface heat losses contributed >70% of the energy for surface layer deepening 82% of the time from midafternoon until midmorning. Circulation times of the surface layer were <2 min as it deepened to 1.5 m in the afternoon and were <12 min at night even when mixing extended to the lake bottom. Spatial differences in the rates of heating and cooling and in the depth of wind mixing caused fronts to develop on spatial scales of kilometers within the bay. Convergence of these fronts led to downwelling of surface waters and upwelling of deep waters during the stratified period. Horizontal pressure gradients due to differential heating contributed to thermocline downwelling, lateral movement of deep, anoxic waters, and generation of high-frequency internal waves, all of which contribute to vertical and horizontal transports. Although wind and heat loss at one location generally determine the depth of the surface layer and thermocline, the depths of these key features may be strongly influenced by rates of heating and cooling elsewhere in a basin.
High-resolution time series of physical and bio-optical data were obtained using moored and bottom-mounted instruments on the southern New England continental shelf during the Coastal Mixing and Optics experiment (CMO) from July 1996 through June 1997. The most prominent physical and bio-optical signals observed during the experiment were associated with the seasonal variability. However, several important events interrupted the seasonal cycle. These episodic events appear to have had a great impact on biogenic and nonbiogenic matter. Hurricanes and storms passed over or near the CMO site, resulting in reduced stratification of the water column, particle redistribution, and sediment resuspension. Changing hydrographic conditions that resulted from the influence of several water mass intrusions greatly affected particle concentration on timescales of days to several weeks. The bottom boundary layer had an influence on particle movement in the water column and along the seafloor. The results suggest that there is likely considerable interannual variability in both the physics and bio-optics because of active and diverse physical forcing. This experiment also sets the context for comparing our coastal ocean results with previous open ocean findings. Important differences arise because of coastal bottom boundary layer effects, large-scale water mass intrusions, and the relatively greater role of tides on the shelf. Timescales of optical variability (e.g., changes in phytoplankton spectral shapes of absorption) are thus generally shorter for the coastal environment.
We characterized spatial and temporal variability in net ecosystem production (NEP), community respiration (CR), and gross
primary production (GPP) over an ice-free season in an oligotrophic high-elevation lake using high-frequency measurements
of dissolved oxygen. We combined the use of free-water and incubation chamber measurements to compare pelagic and benthic
habitats and estimate their relative contributions to whole-lake metabolism. Despite a brief period of predominant heterotrophy
after snowmelt, both free-water and incubation chamber measurements confirmed autotrophy of the epilimnion in all habitats
throughout the ice-free season. In contrast, benthic incubation chambers showed the benthos to be consistently heterotrophic.
Although temperature was the strongest seasonal driver of benthic metabolism, bacterioplankton density and indexes of organic
matter quality explained the most variability in pelagic metabolism. Driven largely by benthic metabolism, free-water measurements
of GPP and CR were twice as high in littoral than pelagic habitats. However, rates of water column primary production overlying
the littoral benthos were high enough to overcome net benthic heterotrophy, and seasonal mean NEP in littoral habitats remained
positive and not significantly different from pelagic habitats. Benthic rates averaged about 25% of whole-lake metabolism.
Pelagic metabolism measurements were affected by littoral rates about half the time, with the degree of isolation between
the two a function of advection and water column stability. These results emphasize the importance of characterizing spatial
and temporal variability in metabolism within the context of physical dynamics and challenge the notion that benthic metabolism
will necessarily be larger than pelagic metabolism in oligotrophic lakes.
Biofouling is one of the primary limiting factors in terms of measurement accuracy and deployment longevity for oceanographic studies involving autonomous sampling. Copper can significantly reduce marine fouling for long-term optical sensor deployments in coastal and open-ocean environments. Copper can effectively replace previously used highly toxic chemical antifoulant methods. Copper-based antifouling systems can be employed with three types of optical sensors: 1) open, 2) enclosed or semienclosed, and 3) shuttered. Copper plates on open-faced backscattering sensors can enable deployment periods of longer than 60 days in coastal waters without biofouling. In addition, copper tubing on nine-wavelength absorption-attenuation meters (ac-9s) has extended measurement capabilities from about 10 days to greater than 60 days with no signs of biofouling in coastal waters. Implementation of copper shutters on optical sensors in open-ocean waters off Japan has resulted in extended deployment periods (410 days and possibly longer) for optical measurements whereas previous optical measurements in the open ocean were typically degraded within several weeks to at most a few months due to biofouling.
Modeling analyses are conducted with a probabilistic mass balance ammonia model to demonstrate the important role that specifications of model inputs and toxicity standards by regulators can play in determining the assimilative capacity of polluted Onondaga Lake, NY, and to support a critical review of a related Total Maximum Daily Load (TMDL) analysis. More than 90% of the ammonia received by the lake is from a municipal wastewater treatment plant (Metro). It was found that various decisions to be made by regulators in management applications of the model greatly influence the lake's apparent assimilative capacity (TMDL). In particular, the following issues were critical: (1) anticipated hypolimnetic oxygenation treatment, (2) previously documented in-lake nitrification events, (3) effects of residual industrial pollution on pH, (4) effects of uncertainties and potential bias in pH measurements, (5) anticipated increases in population growth served by Metro, and (6) revisions in national guidance toxicity criteria prepared by the U. S. Environmental Protection Agency. Several limitations in the existing ammonia TMDL analysis are reported, including: (1) arbitrary specification of critical conditions, (2) omission of the important features of duration and allowable number of occurrences in the state standard, (3) identification of the wrong month as critical for determining the lake's assimilative capacity, (4) lack of recognition of the artificial assimilative capacity associated with the effects of residual industrial pollution, (5) the specified “margin of safety” was too low, given the level of modeling and input uncertainties, (6) anticipated increases in discharge from Metro were not considered, and (7) incorrect identification of the critical year for tributary hydrology. Recommendations are made to upgrade the ammonia TMDL analysis, including the supporting model framework and data sets.
Net ecosystem production (NEP) is the difference between gross primary production (GPP) and community respiration (R). We estimated in situ NEP using three independent approaches (net CO2 gas flux, net O 2 gas flux, and continuous diel O2 measurements) over a 4-7 yr period in a series of small lakes in which food webs were manipulated and nutrient loadings were experimentally varied. In the absence of manipulation, these lakes were net heterotrophic according to all three approaches. NEP (NEP 5 GPP-R) was consistently negative and averaged 235.5 6 3.7 (standard error) mmol C m 22 d 21 . Nutrient enrichment, in the absence of strong planktivory, tended to cause increases in estimates of both GPP and R (estimated from the continuous O2 data) but resulted in little change in the GPP/R ratio, which remained ,1, or NEP, which remained negative. When planktivorous fish dom- inated the food web, large zooplankton were rare and nutrient enrichment produced positive values of NEP by all three methods. Among lakes and years, daily values of NEP ranged from 2241 to 1175 mmol m 22 d 21 ; mean seasonal NEP was positive only under a combination of high nutrient loading and a planktivore-dominated food web. Community R is significantly subsidized by allochthonous sources of organic matter in these lakes. Combining all lakes and years, we estimate that ;26 mmol C m 22 d 21 of allochthonous origin is respired on average. This respiration of allochthonous organic matter represents 13 to 43% of total R, and this fraction declines with increasing GPP.
Hydrostatic balances between fresh and saline groundwater and saline surface water control the physical and chemical framework of subterranean estuaries, but they are responsive to high frequency (waves and tides), low frequency (seasonal recharge patterns), and episodic (storm) events. In this study, we document a salinity and pressure perturbation to the subterranean estuary in east-central Florida during and after the passage of Tropical Storm Tammy on 04 Oct 2005-05 Oct 2005 and Hurricane Wilma on 24 Oct 2005. These storms reversed hydraulic gradients, forced lagoon water into the aquifer, and shifted the outflow face landward. Salinity at 1.5 m and 2.5 m below a common datum converged on similar values intermediate between fresh and lagoon water salinities. The outflow face reestablished pre-storm conditions after 80 days at 15 m offshore, but more than 160 days at 30 m offshore, confirming that both the flow field and fluid sources control the position of the subterranean estuary. Episodic, high intensity events could influence the biogeochemical setting of the subterranean estuary and the overlying water body by altering redox conditions in the subterranean estuary during the landward migration of the dispersive mixing zone, increasing short-term discharge of potentially contaminated groundwater, and/or changing pore fluid residence time within the seepage face and along the mixing zone-seepage face front.
A simple method to automatically measure the date of ice-on, the date of ice-off, and the duration of lake ice cover is described. The presence of ice cover is detected by recording water temperature just below the ice/water interface and just above the lake bottom using moored temperature sensors. The occurrence of ice-on rapidly leads to detectible levels of inverse stratification, defined as existing when the upper sensor records a temperature at least 0.1°C below that of the bottom sensor, whereas the occurrence of ice-off leads to the return of isothermal mixing. Based on data from 10 lakes over a total of 43 winter seasons, we found that the timing and duration of inverse stratification monitored by recording temperature sensors compares well with ice cover statistics based on human observation. The root mean square difference between the observer-based and temperature-based estimates was 7.1 d for ice-on, 6.4 d for ice-off, and 10.0 d for the duration of ice cover. The coefficient of determination between the two types of estimates was 0.93, 0.86, and 0.91, respectively. The availability of inexpensive self-contained temperature loggers should allow expanded monitoring of ice cover in a large and diverse array of lakes. Such monitoring is needed to improve our ability to monitor the progression of global climate change, and to improve our understanding of the relationship between climate and ice cover over a wide range of temporal and spatial scales.
Abstract
A simple method to automatically measure the date of ice-on, the date of ice-off, and the duration of lake ice cover is described. The presence of ice cover is detected by recording water temperature just below the ice/water interface and just above the lake bottom using moored temperature sensors. The occurrence of ice-on rapidly leads to detectible levels of inverse stratification, defined as existing when the upper sensor records a temperature at least 0.1°C below that of the bottom sensor, whereas the occurrence of ice-off leads to the return of isothermal mixing. Based on data from 10 lakes over a total of 43 winter seasons, we found that the timing and duration of inverse stratification monitored by recording temperature sensors compares well with ice cover statistics based on human observation. The root mean square difference between the observer-based and temperature-based estimates was 7.1 d for ice-on, 6.4 d for ice-off, and 10.0 d for the duration of ice cover. The coefficient of determination between the two types of estimates was 0.93, 0.86, and 0.91, respectively. The availability of inexpensive self-contained temperature loggers should allow expanded monitoring of ice cover in a large and diverse array of lakes. Such monitoring is needed to improve our ability to monitor the progression of global climate change, and to improve our understanding of the relationship between climate and ice cover over a wide range of temporal and spatial scales.
Wireless sensor networks have been in use by ecologists for more than a decade. Many of these networks are hybrid networks, incorporating diverse network technologies to bridge the gap from the sensor in the field and the database in the office or laboratory. We briefly review sensor and available wireless network technologies and then examine, in some detail, several examples of field networks from Taiwan and Virginia (USA). The examples include networks which monitor meteorological variables, lake physical and chemical characteristics, water levels, butterfly habitat, and forest dynamics, including sound and images. We discuss the advantages of using hybrid sensor networks and areas where additional improvements are still needed.
Whole-ecosystem metabolism is often estimated in lakes using high frequency free-water measurements of dissolved oxygen (DO) taken in the upper mixed layer. DO dynamics in the metalimnion are not adequately captured by measurements made in the upper mixed layer, which could reduce the accuracy of whole-lake metabolism estimates made from such data. However, estimating metabolism from metalimnetic DO time series can be challenging because of high variability (noise). This study used simulated and field data to determine if metabolism estimates from metalimnetic data containing noise can be improved by accounting for both process and observation error in models. When DO time series exhibited high variability, free-water metabolism estimates obtained using a Kalman filter (which accounts for both process and observation error) were substantially more accurate than estimates obtained from models that did not account for error or accounted for process error only.
Stream water quality can change substantively during diurnal cycles, discrete flow events, and seasonal time scales. In this study, we assessed event responses in surface water nutrient concentrations and biogeochemical parameters through the deployment of continuous water quality sensors from March to October 2011 in the East Fork Jemez River, located in northern New Mexico, USA. Events included two pre-fire non-monsoonal precipitation events in April, four post-fire precipitation events in August and September (associated with monsoonal thunderstorms), and two post-fire non-monsoonal precipitation events in October. The six post-fire events occurred after the Las Conchas wildfire burned a significant portion of the contributing watershed (36%) beginning in June 2011. Surface water nitrate (NO3N) concentrations increased by an average of 50% after pre-fire and post-fire non-monsoonal precipitation events and were associated with small increases in turbidity (up to 15 NTU). Beginning 1 month after the start of the large regional wildfire, monsoonal precipitation events resulted in large multi-day increases in dissolved NO3N (6 × background levels), dissolved phosphate (100 × background levels), specific conductance (5 × background levels), and turbidity (>100 × background levels). These periods also corresponded with substantial sags in dissolved oxygen (<4 mg l−1) and pH (<6.5). The short duration and rapid rates of change during many of these flow events, particularly following wildfire, highlight the importance of continuous water quality monitoring to quantify the timing and magnitude of event responses in streams and to examine large water quality excursions linked to catchment disturbance. Copyright © 2015 John Wiley & Sons, Ltd.
A series of vertical profiles of dissolved oxygen (DO) collected periodically over two consecutive ice-free seasons in an oligotrophic high-elevation lake (Emerald Lake, California) were used to investigate volumetric and areal rates of gross primary production (GPP), community respiration (CR), and net ecosystem production (NEP). Diel patterns in DO did not weaken with depth in this lake, where the entire 10-m water column was within the euphotic zone and where a deep chlorophyll a (Chl a) maximum was common during periods of thermal stratification. During stratification, both GPP and CR increased with depth, and heterotrophy (NEP < 0) tended to occur below the thermocline in association with higher Chl a and particulate matter concentrations. With the onset of autumn mixing each year, vertical gradients in metabolism weakened or disappeared and the entire water column was autotrophic. Net autotrophy over the growing season was confirmed using three methods of estimating whole-lake metabolism. During periods of stratification, flux across the thermocline, where eddy diffusivities were near molecular, was small (4% of total epilimnetic fluxes), while within the hypolimnion, where stratification was weaker and eddy diffusivities larger, fluxes between strata were more substantial (12% of total fluxes). For this lake and other small lakes with low wind speeds and Lake numbers near 10, mixing due to turbulence should be included in computations of metabolism within the hypolimnion. However, single-station measurements from within the epilimnion provide a reasonable estimate of seasonal metabolism, especially in the autumn when the lake is mixing on a diel basis.
Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to > 45 km hr-1) resulting in high-density, meso-scale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs. backwater nutrient processing in a large river, and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.
We describe a system for the semi-autonomous in situ measurement of lake chemical properties, with high temporal resolution and the potential to map chemical properties in 3 dimensions. The system comprises both fixed sensor locations on moored buoys and one (or potentially more) autonomous underwater vehicles (AUVs) serving as mobile underwater sensor platforms. Sensors Include conventional water quality multiprobes and thermistor strings and the NEREUS underwater mass spectrometer for measurement of dissolved metabolic gases such as methane as well as permanent gases. Data are delivered to a shore station via a network that includes acoustic modems for communication with the AUV and a radio network operating in the license-free ISM (industrial, scientific, and medical) band operating under the IEEE 802.11b protocol. The system is designed to use low-cost commercial hardware and open-source software wherever possible. We constructed a prototype system of 3 buoys, 1 AUV, and a shore station, and field tests have demonstrated its ability to measure and remotely display lake chemical data in real time. © 2008, by the American Society of Limnology and Oceanography, Inc.
Long-term monitoring of changes in dissolved oxygen (DO) and pH is of great importance to quantifying aquatic ecosystem metabolism, particularly for lakes under the changing global environment. During 173 days, diel DO cycles were measured in situ along with the main driving variables of pH, wind speed (WS), and net solar radiation (Rn) in a temperate shallow lake. Best-fit multiple non-linear regression (MNLR) models of diel DO time series were built and validated on a monthly basis, with R2 values ranging from 42.4% in September to 95.4% in November for validation. The strong relationship between diel DO and pH (r = 0.6) appeared to be related to the patterns of ecosystem productivity and respiration, and sensitivity of decomposing bacteria to changes in pH. pH-driven lake metabolism appears to have significant implications for diel and seasonal lake metabolism in a changing global environment.