Models for the Impact of Climate Change on Marine Ecosystems

Using models to predict future changes in ecosystems has become a key tool in tracing the impacts of climate change. These models are more difficult to make in marine ecosystems because of the number of variables. Researchers in Australia are trying to create new models, which is perfect because of the marine biodiversity and amount of data available. Fulton (2011) examined the effect of climate change on three different areas, SE and NW Australian coastline, and the Great Barrier Reef (GBR).  She used a combination of models and model parameters to simulate the changing distribution of species within these areas, and was able to model the entire ecosystem as a whole. One of her main findings was that there were common winners and losers among the SE and NW Australian zones but different from the GBR. The results showed how there are no clean rules on how climate change will affect marine ecosystems. These models however can help humans manage resources better as climate change makes species more vulnerable. The data suggest that in Australia, the climate change scenarios seem to benefit primary producers and basic ocean ecosystem components, which could cause major ecological restructuring.  This result led Fulton to conclude that current fishery management will have to change. She suggests a dynamic strategy of using closed off areas to check the balance of currently fished areas. –Connor O’Boyle

Fulton, E., 2011. Interesting times: winners, losers, and system shifts under climate change around Australia. ICES Journal of Marine Science 68, 1329—1342.

      Fulton used a complex model, the end-to-end (or whole-of-system) model to simulate climate change/human pollution’s impact on marine ecosystems. She looked at the marine ecosystems around Australia, specifically the NW and SE Australian coastal areas and the GBR. These models attempt to integrate abiotic, biotic and anthropogenic factors which will allow further investigation of how climate change will impact Australian ecosystems. For the SE Australia model she used the Atlantis computer system. Atlantis was originally developed for the evaluation of SE Australian federal fisheries; the model however is useful for climate related questions due to its ability to integrate large amounts of variables.  Fitting these variables with the appropriate data would be challenging but in the case of Australia there are 20—90 years of catch history for most species plus other model specific data.
The NW Australian area was modeled using the InVitro model system. This was done by combining two models, the InVitro-NWS and the InVitro—Ningaloo, both developed for evaluating multiple management strategies in NW Australia. Just like Atlantis, the different factors changing the ecosystem, such as human pollutants, differing weather patterns, and even the effects of human tourism are represented by equations or cellular automata. The GBR region was modeled using the Ecoscape system. This model has 32 groups; pelagic and benthic primary producers (surface level to sea floor), as well many benthic invertebrates. The model includes 23 fish groups as well as groups of concern including sea turtles and certain migratory sea birds.  In order to compare the areas, Ecospace models were run for both the NW and SE Australian areas. For every model, the water column properties were simulated using an ocean forecast model developed by Commonwealth Scientific and Industrial Research Organization (CSIRO). This was also used to represent storms, and sea-level rise. NPZD models were used in conjunction with the CSIRO models in the Ecospace framework to more accurately model water mechanics. All models were run from 2010-2060, only changes in relative biomass of primary producers, detritus, plankton, pelagic fish, benthic invertebrates, demersal fish, and top predators were reported.
            The models indicated that there will be a 5—22% biomass increase in plankton in NW and SE Australia. A 20—105% increase in other pelagic invertebrates is indicated as well as 21—881% increase for fish biomass. Demersal fish will experience an 8—35% decline in the GBR. Top predators and benthic invertebrates responded differently in every model, there is turnover in the types of benthic invertebrates that dominate, moving to those that can cope with the changes in temperature, sources of production, detrital loads, and ocean acidification. Squid and sharks initially increased but decreased after 2040 due to poor environmental conditions. In comparing the different simulations, if factors affecting ecosystems are considered in isolation then results were within 10—15% of the values reached during regular simulations. If factors such as acidification are taken into account in conjunction with other variables the values run 40% lower, thus showing the dramatic effect of certain driving mechanisms, particularly increased in atmospheric CO­ independent of warming.

            Fulton suggests that the current models show that in the targeted Australian regions there was an increase in primary producers and pelagic ecosystems components. Each system will have its own set of winners and losers, but the ecosystem will remain in balance as new species fill the gaps. The NW and SE Australian regions increased in overall biomass and the GBR declined in overall biomass. She suggests that Australian fisheries need to switch to management practices that use a dynamic model. Using reference areas, the active fishing areas could be compared to fish free zones, judging the potential of new ecosystem structures. Fulton warns that these models must be taken as theoretical. The parameters of the models limit their range. So no matter how complex the models, they must always be partnered with quantitative experiments in the field. 

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