Advancing projections of phytoplankton responses to climate change through ensemble modelling

TY - JOUR

T1 - Advancing projections of phytoplankton responses to climate change through ensemble modelling

AU - Trolle, Dennis

AU - Elliott, J. Alex

AU - Mooij, Wolf M.

AU - Janse, Jan H.

AU - Bolding, Karsten

AU - Hamilton, David P.

AU - Jeppesen, Erik

N1 - 5758, AqE

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - Future climate

KW - Cyanobacteria

KW - Water resources

KW - Ecosystem modelling

KW - international

U2 - 10.1016/j.envsoft.2014.01.032

DO - 10.1016/j.envsoft.2014.01.032

M3 - Article

SN - 1364-8152

VL - 61

SP - 371

EP - 379

JO - Environmental Modelling and Software

JF - Environmental Modelling and Software

ER -