The Global Lake Ecological Observatory Network (Gleon): The Evolution of Grassroots Network Science

Weathers, Kathleen C.; Hanson, Paul C.; Arzberger, Peter; Brentrup, Jennifer A.; Brookes, Justin D.; Carey, Cayelan C.; Gaiser, Evelyn E.; Hamilton, David P.; Hong, Grace S.; Ibelings, Bas W.; Istvánovics, Vera; Jennings, Eleanor; Kim, Bomchul; Kratz, Tim; Lin, Fang‐Pang; Muraoka, Kohji; O’Reilly, Catherine M.; Rose, Kevin C.; Ryder, Elizabeth F.; Zhu, Guangwei

doi:10.1002/lob.201322371

Cited by 76 publications

(81 citation statements)

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“…Traditionally, metabolism has been estimated directly from bottle incubations or diel oxygen fluctuations using a 'bookkeeping' calculation (Odum 1956;Cole et al 2000;Staehr et al 2010). Advances in high-frequency dissolved oxygen sensor technology (e.g., Staehr et al 2012;Weathers et al 2013), increased metabolism model complexity, and use of parametric statistical techniques (van de Bogert et al 2007;Hanson et al 2008) have improved the spatial and temporal resolution of metabolism estimates. These advances have enabled new discoveries about the role of lakes in the global C cycle (e.g., Solomon et al 2013), controls on metabolism (Hoellein et al 2013), and spatial variability of metabolism within lakes (Van de Bogert et al 2012).…”

Section: Introductionmentioning

confidence: 99%

“…To date, most lake metabolism studies using these techniques have focused on temporal variation based on measurements made in the epilimnion and restricted to one year time periods (e.g., Carignan et al 2000;Sadro et al 2011;Klug et al 2012;Solomon et al 2013;Morales-Pineda et al 2014), in part because the deployment of high-frequency sensors is a recent phenomenon (Weathers et al 2013). In the few studies when metabolism was estimated across multiple years in lakes, rivers, or estuaries, metabolic rates were linked to anthropogenic nutrient loading (Uehlinger 2006) and climatic variation (Roberts et al 2007;Staehr and Sand-Jensen 2007;Einola et al 2011;Laas et al 2012;Caffrey et al 2014;Roley et al 2014).…”

Section: Introductionmentioning

confidence: 99%

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Intra- and inter-annual variability in metabolism in an oligotrophic lake

et al. 2016

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Lakes are sentinels of change in the landscapes in which they are located. Changes in lake function are reflected in whole-system metabolism, which integrates ecosystem processes across spatial and temporal scales. Recent improvements in high-frequency open-water metabolism modeling techniques have enabled estimation of rates of gross primary production (GPP), respiration (R), and net ecosystem production (NEP) at high temporal resolution. However, few studies have examined metabolic rates over daily to multi-year temporal scales, especially in oligotrophic ecosystems. Here, we modified a metabolism modeling technique to reveal substantial intra-and interannual variability in metabolic rates in Lake Sunapee, a temperate, oligotrophic lake in New Hampshire, USA. Annual GPP and R increased each summer, paralleling increases in littoral, but not pelagic, total phosphorus concentrations. Storms temporarily decoupled GPP and R, resulting in greater decreases in GPP than R. Daily rates of GPP and R were positively correlated on warm days that had stable water columns, and metabolism model fits were best on warm, sunny days, indicating the importance of lake physics when evaluating metabolic rates. These metabolism data span a range of temporal scales and together suggest that Lake Sunapee may be moving toward mesotrophy. We suggest that functional, integrative metrics, such as metabolic rates, are useful indicators and sentinels of ecosystem change. We also highlight the challenges and opportunities of using high-frequency measurements to elucidate the drivers and consequences of intra-and inter-annual variability in metabolic rates, especially in oligotrophic lakes.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intra- and inter-annual variability in metabolism in an oligotrophic lake

et al. 2016

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“…The initial motivation for forming GLEON was the use of sensors and sensor networks to provide new scales of lake observations (Weathers et al 2013a). Sensor data, together with long-term data from traditional sampling paradigms, "book end" the time scales that can be observed directly.…”

Section: Multiscale Observationsmentioning

confidence: 99%

“…The outcome (illustrated in Fig. 1) is that effective networks are really 3 networks-people, data, and ecosystems (Weathers et al 2013a, Cooke et al 2015and that these networks are at the base of scientific advances. We also stress that some of the biggest challenges, as well as opportunities with conducting network science, are to catalyze, guide, and effectively harness the resources distributed in the network and deliver a concerted effort toward addressing relevant science questions.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, one way the science community has responded to unprecedented change is to utilize developments in technology that allow near real-time (NAS 2004, Carpenter 2008, Weathers et al 2013a across regions, continents, and the globe. Over the next decade, we will begin to see how these networks and a collaborative team science approach will meet the challenge.…”

Section: Introductionmentioning

confidence: 99%

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Networked lake science: how the Global Lake Ecological Observatory Network (GLEON) works to understand, predict, and communicate lake ecosystem response to global change

2016

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The Global Lake Ecological Observatory Network (GLEON) has built an international, grassroots network of scientists and citizens, data, and lake observatories to advance understanding of lake ecosystems. Through careful attention to the professional needs and aspirations of a community, GLEON has formed as its foundation the trust and respect essential to product-based network science. As a consequence, GLEON is making significant advancements in lake ecosystem understanding through all "five legs of the table that support scientific understanding"-natural history, multiscale data, experiments, theory, and comparative studies-with particular emphasis on multiscale data and comparative studies. Technical products, such as cyberinfrastructure in support of network data and operations, software tools for calculating lake physical metrics (e.g., thermocline depth, buoyancy frequency, Schmidt stability), and lake metabolism, as well as ecosystem-scale numerical simulation software, have derived from GLEON collaborations and have become community resources catalyzing interdisciplinary science. Education and outreach initiatives have served to engage citizens from outside the traditional boundaries of academia directly in research. Moreover, these cross-boundary collaborations have provided essential links to lake and reservoir stakeholders who have informed how science is prioritized and communicated within GLEON. As a grassroots network, GLEON derives its momentum, flexibility, and impact from its talented members, who are committed to the future sustainability of lakes and reservoirs and the services they provide.

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The role of stratification on lakes' thermal response: The case of Lake Superior

Piccolroaz

Toffolon

Majone

2015

Water Resources Research

106

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During the last several decades, the Great Lakes region has been experiencing a significant rise in temperatures, with the extraordinary summer warming that affected Lake Superior in 1998 as an example of the marked response of the lake to increasingly warmer atmospheric conditions. In this work, we combine the analysis of this exceptional event with some synthetic scenarios, to achieve a deeper understanding of the main processes driving the thermal dynamics of surface water temperature in Lake Superior. The analysis is performed by means of the lumped model air2water, which simulates lake surface temperature as a function of air temperature alone. The model provides information about the seasonal stratification dynamics, suggesting that unusual warming events can result from two factors: anomalously high summer air temperatures, and increased strength of stratification resulting from a warm spring. The relative contribution of the two factors is quantified using the model by means of synthetic scenarios, which provide a simple but effective description of the positive feedback between the thermal behavior and the stratification dynamics of the lake.

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The Global Lake Ecological Observatory Network (Gleon): The Evolution of Grassroots Network Science

Cited by 76 publications

References 10 publications

Intra- and inter-annual variability in metabolism in an oligotrophic lake

Intra- and inter-annual variability in metabolism in an oligotrophic lake

Networked lake science: how the Global Lake Ecological Observatory Network (GLEON) works to understand, predict, and communicate lake ecosystem response to global change

The role of stratification on lakes' thermal response: The case of Lake Superior

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