Projected changes to ocean food webs and oceanic fisheries

Based on……..

Outline Food webs for tuna Differences in food webs among provinces of the Pacific Ocean Effects of CC on provinces and their food webs Sensitivity of tuna habitats to oceanic variables Effects of climate change on tuna stocks

Image: Marc Taquet, FADIO, IRD/IFREMER

Tuna food web Food webs are complex

Five oceanic provinces

Five oceanic provinces Warm pool Normal El Niño

Five oceanic provinces North and South Gyres (case 3) and equatorial divergence (case 4)

Impact of climate change Surface area of the provinces ↘ of rich equatorial divergence ↗ of poorer gyres and warm pool

Impact of climate change present future Exchanges between deep rich water and surface poorer waters ↘ of nutrients reaching the surface where photosynthesis can occur

3. The impact of climate change Effect on phytoplankton and zooplankton 2100 2035 2050 present ↘ of phytoplankton and zooplankton

3. The impact of climate change Effect on micronekton Image: Valerie Allain, SPC ↘ of micronekton

Now, turning to tuna

Tuna habitat – temperature Each tuna species has evolved with a preferred range in temperature Species Temperature (°C) Skipjack 20-29 Yellowfin 20-30 Bigeye 13-27 Albacore 15-21 Sth. bluefin 17-20 Impacts vertical & horizontal distribution (habitat and food) & reproduction location and timing According to life stage sensitivity to SST degree e.g. larvae and adult. Spawning. Affects habitat and Range of sea surface temperature with substantial catches Source: Sund et al. (1981)

Tuna habitat – oxygen Estimated lower lethal oxygen Skipjack Albacore Sensitive to combined effects of SST + O2 Less tolerant to low values Estimated lower lethal oxygen Skipjack Albacore Yellowfin Bigeye Species Fork length (cm) Lower lethal O2 levels (ml l-1) Skipjack 50 1.87 Albacore 1.23 Yellowfin 1.14 Bigeye 0.40 Most tolerant to low values

Tuna habitat – oxygen 0 m 100 m Well oxygenated Low oxygen 500 m + 0 m 100 m Well oxygenated Skipjack Yellowfin Albacore 500 m Low oxygen Bigeye Typical vertical O2 profile Change in subsurface may have more impact on low oxygen tolerant species

Better understanding of oceanography = better expected projections Now that we understand the oceanography a bit better then before, we have spent some years making a model to better understand the projections expected. Spent years working on a model to incorporate these change. Through this model we see changes in fishing grounds and distributions towards eastern for tuna and this poses challenges for fishing operations like purse seinier and long liners.

Skipjack tuna Samoa +7% Samoa +10% Unexploited Fishing effort x 1.5

Albacore projection Sensative to O2 hence distribution changes 2000 2000 Larval density Adult biomass 2050 2050 No change in O2 Sensative to O2 hence distribution changes With modelled O2

Conclusions There is still uncertainty about impacts of climate change Fishing has a strong impact and will continue to be a major driver of stocks Point to the graph on complexation.

Conclusions Resolution 2° Resolution 1° Resolution 0.25 ° Improved resolutions of SEAPODYM model are needed to update these preliminary results Better projections of key ocean variables for tuna can be achieved using an ensemble of models we expect to be better at these models to get down form coarse scale to finner scale to better capture the oceanic processes. What is important to remember is that even thou there are gaps of knowledge and uncertainty in SEAPODYM, this is currently the only model, which can incorporate all these processes mentioned. Lead the audience thru the diagram. Alex resloution and giving example places in red more tuna then the palces in blue if u go donw from 2 degrees to these with these sort of model we would hope to provide more information to the managers to maange long liners. So as you can see when we go donw from 2 degrees to 0.25 we are better able to see these processes.