TY - JOUR
T1 - Effects of changes in land use and climate on aquatic ecosystems: Coupling of models and decomposition of uncertainties
AU - Trolle, Dennis
AU - Nielsen, Anders
AU - Andersen, Hans Estrup
AU - Thodsen, Hans
AU - Olesen, Jørgen Eivind
AU - Børgesen, Christen Duus
AU - Refsgaard, Jens Christian
AU - Sonnenborg, Torben O.
AU - Karlsson, Ida B.
AU - Christensen, Jesper Philip Aagaard
AU - Markager, Stiig
AU - Jeppesen, Erik
PY - 2019
Y1 - 2019
N2 - To analyse the potential future ecological state of estuaries located in the temperate climate (here exemplified with the Odense Fjord estuary, Denmark), we combined end-of-the-century climate change projections from four different climate models, four contrasting land use scenarios (“Agriculture for nature” “Extensive agriculture” “High-tech agriculture” and “Market driven agriculture”) and two different eco-hydrological models. By decomposing the variance of the model-simulated output from all scenario and model combinations, we identified the key sources of uncertainties of these future projections. There was generally a decline in the ecological state of the estuary in scenarios with a warmer climate. Strikingly, even the most nature-friendly land use scenario, where a proportion of the intensive agricultural area was converted to forest, may not be enough to counteract the negative effects of a future warmer climate on the ecological state of the estuary. The different land use scenarios were the most significant sources of uncertainty in the projections of future ecological state, followed, in order, by eco-hydrological models and climate models, albeit all three sources caused high variability in the simulated outputs. Therefore, when projecting the future state of aquatic ecosystems in a global warming context, one should at the very least consider to evaluate an ensemble of land use scenarios (nutrient loads) but ideally also include multiple eco-hydrological models and climate change projections. Our study may set precedence for future attempts to predict and quantify uncertainties of model and model input ensembles, as this will likely be key elements in future tools for decision-making processes.
AB - To analyse the potential future ecological state of estuaries located in the temperate climate (here exemplified with the Odense Fjord estuary, Denmark), we combined end-of-the-century climate change projections from four different climate models, four contrasting land use scenarios (“Agriculture for nature” “Extensive agriculture” “High-tech agriculture” and “Market driven agriculture”) and two different eco-hydrological models. By decomposing the variance of the model-simulated output from all scenario and model combinations, we identified the key sources of uncertainties of these future projections. There was generally a decline in the ecological state of the estuary in scenarios with a warmer climate. Strikingly, even the most nature-friendly land use scenario, where a proportion of the intensive agricultural area was converted to forest, may not be enough to counteract the negative effects of a future warmer climate on the ecological state of the estuary. The different land use scenarios were the most significant sources of uncertainty in the projections of future ecological state, followed, in order, by eco-hydrological models and climate models, albeit all three sources caused high variability in the simulated outputs. Therefore, when projecting the future state of aquatic ecosystems in a global warming context, one should at the very least consider to evaluate an ensemble of land use scenarios (nutrient loads) but ideally also include multiple eco-hydrological models and climate change projections. Our study may set precedence for future attempts to predict and quantify uncertainties of model and model input ensembles, as this will likely be key elements in future tools for decision-making processes.
U2 - 10.1016/j.scitotenv.2018.12.055
DO - 10.1016/j.scitotenv.2018.12.055
M3 - Journal article
C2 - 30677929
SN - 0048-9697
VL - 657
SP - 627
EP - 633
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -