The Global Lake Ecological Observatory Network (GLEON) has evolved as a grassroots network over the past twenty years. The following publications document the history of GLEON’s network of people, lakes and data:

  • The Global Lake Ecological Observatory Network (GLEON): The evolution of grassroots network science – Weathers, Kathleen C., Paul C. Hanson, P. Arzberger, Jennifer A. Brentrup, J. Brookes, Cayelan C. Carey, E. Gaiser, et al. (2013). Limnology and Oceanography Bulletin. link
  • Networked lake science: how the Global Lake Ecological Observatory Network (GLEON) works to understand, predict, and communicate lake ecosystem response to global change – Hanson, P. C., Weathers, K. C., & Kratz, T. K. (2016). Inland Waters, 6(4), 543–554. https://doi.org/10.1080/IW-6.4.904
  • A Global Lake Ecological Observatory Network (GLEON) for synthesizing high frequency sensor data for validation of deterministic ecological models – Hamilton, D. P., Carey, C. C., Arvola, L., Arzberger, P., Brewer, C., Cole, J. J., … Brookes, J. D. (2015). Inland Waters, 5(1), 49–56. https://doi.org/10.5268/IW-5.1.566
  • Insights from the Global Lake Ecological Observatory Network (GLEON) – Rose, K. C., Weathers, K. C., Hetherington, A. L., & Hamilton, D. P. (2016). Inland Waters6(4), 476–482. https://doi.org/10.1080/IW-6.4.1051
  • The Global Lake Ecological Observatory Network – Hanson, P.C., Weathers, K.C., Dugan, H.A., Gries, C. (2018). In: Recknagel, F., Michener, W. (eds) Ecological Informatics. Springer, Cham. https://doi.org/10.1007/978-3-319-59928-1_19
Image: GLEON Network structure and process. Credit: Adapted from Hanson et al. 2017.
GLEON is a network of people, lakes, and data, with a diversity of resources. Through network structure and process, GLEON is able to use its diversity of resources to address the five pillars of ecosystem science. Credit: Hanson et al. (2018)
Image: GLEON socio-technological approach. Credit: Hanson et al. 2017.
In an Socio-Technological system, people are an integral part of the information management system. Teams both produce and consume data and are involved in the creation of technologies and models used in the iterative process of science. Credit: Hanson et al. (2018)