Advancing projections of phytoplankton responses to climate change through ensemble modelling
| Autor: | Dennis Trolle, Jan H. Janse, J. Alex Elliott, Karsten Bolding, Wolf M. Mooij, David P. Hamilton, Erik Jeppesen |
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| Přispěvatelé: | Aquatic Ecology (AqE) |
| Rok vydání: | 2014 |
| Předmět: |
Water resources
Aquatic Ecology and Water Quality Management fresh-water cyanobacteria restoration Environmental Engineering Environmental change Ecosystem modelling Climate change challenges environmental-change Cyanobacteria Ecology and Environment Phytoplankton Ecosystem Robustness (economics) blooms WIMEK shallow lakes Ecological Modeling Aquatic ecosystem Community structure temperature Aquatische Ecologie en Waterkwaliteitsbeheer PE&RC international Climatology multimodel ensembles Future climate Environmental science community structure predictions Software |
| Zdroj: | Environmental Modelling and Software, 61, 371-379. Elsevier B.V. Environmental Modelling & Software 61 (2014) Trolle, D, Elliott, J A, Mooij, W M, Janse, J J, Bolding, K, Hamilton, D P & Jeppesen, E 2014, ' Advancing projections of phytoplankton responses to climate change through ensemble modelling ', Environmental Modelling & Software, vol. 61, pp. 371–379 . https://doi.org/10.1016/j.envsoft.2014.01.032 Environmental Modelling & Software, 61, 371-379 |
| ISSN: | 1364-8152 |
| DOI: | 10.1016/j.envsoft.2014.01.032 |
| Popis: | A global trend of increasing health hazards associated with proliferation of toxin-producing cyanobacteria makes the ability to project phytoplankton dynamics of paramount importance. Whilst ensemble (multi-)modelling approaches have been used for a number of years to improve the robustness of weather forecasts this approach has until now never been adopted for ecosystem modelling. We show that the average simulated phytoplankton biomass derived from three different aquatic ecosystem models is generally superior to any of the three individual models in describing observed phytoplankton biomass in a typical temperate lake ecosystem, and we simulate a series of climate change projections. While this is the first multi-model ensemble approach applied for some of the most complex aquatic ecosystem models available, we consider it sets a precedent for what will become commonplace methodology in the future, as it enables increased robustness of model projections, and scenario uncertainty estimation due to differences in model structures. (C) 2014 Elsevier Ltd. All rights reserved. |
| Databáze: | OpenAIRE |
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