IMIS

Publications | Institutes | Persons | Datasets | Projects | Maps
[ report an error in this record ]basket (0): add | show Print this page

Partitioning climate uncertainty in ecological projections: Pacific oysters in a hotter Europe
Wilson, R.J.; Kay, S.; Ciavatta, S. (2024). Partitioning climate uncertainty in ecological projections: Pacific oysters in a hotter Europe. Ecological Informatics 80: 102537. https://dx.doi.org/10.1016/j.ecoinf.2024.102537
In: Ecological Informatics. Elsevier: Amsterdam. ISSN 1574-9541; e-ISSN 1878-0512, more
Peer reviewed article  

Available in  Authors 

Keywords
    Climate change
    Marine/Coastal
Author keywords
    Pacific oysters; Internal variability; CMIP6

Authors  Top 
  • Wilson, R.J.
  • Kay, S.
  • Ciavatta, S.

Abstract
    Projections of the range expansions of marine species are critical if we are to anticipate and mitigate the impacts of climate change on marine ecosystems. However, most projections do not assess the level of uncertainty of future changes, which brings their usefulness for scenario planning and ecosystem management into question. For the overall climate system, these uncertainties take three forms: scenario uncertainty, climate model uncertainty and internal climate variability. Critically, internal variability, a measure of how natural variability affects future climate projections, has largely been ignored in ecological studies. Here we use an ensemble modelling approach for the non-native Pacific oyster in Europe to understand the impact of these uncertainties. Future Pacific oyster recruitment was projected using a model that relates recruitment to cumulative and instantaneous heat exposure. Model projections were carried out for four climate change scenarios: SSP1 2.6, SSP2 4.5, SSP3 7.0 and SSP5 8.5. In each scenario an ensemble of over twenty climate models was used. The impact of internal variability in climate models was assessed by using five climate models which were available with multiple pre-industrial starting points. We find that model uncertainty within SSP1 2.6 is higher than the differences between SSP1 2.6 and SSP 4.5, but it is unclear if overall scenario uncertainty is greater than climate model uncertainty due to its subjective nature. Comparisons of scenario projections indicate that future recruitment areas of Pacific oysters under the SSP5 8.5 scenario could be more than twice as high as in the low emissions SSP1 2.6 scenario. Importantly, the ensemble showed that near-term changes in Pacific oysters are highly uncertain due to internal variability, which is of a similar magnitude to climate model uncertainty on a 20-year timescale. Our results show that it is critical to think about the future in terms of potential scenarios and not individual projections.

All data in the Integrated Marine Information System (IMIS) is subject to the VLIZ privacy policy Top | Authors